Sample records for minimum variance filtering

  1. Synthesis of correlation filters: a generalized space-domain approach for improved filter characteristics

    NASA Astrophysics Data System (ADS)

    Sudharsanan, Subramania I.; Mahalanobis, Abhijit; Sundareshan, Malur K.

    1990-12-01

    Discrete frequency domain design of Minimum Average Correlation Energy filters for optical pattern recognition introduces an implementational limitation of circular correlation. An alternative methodology which uses space domain computations to overcome this problem is presented. The technique is generalized to construct an improved synthetic discriminant function which satisfies the conflicting requirements of reduced noise variance and sharp correlation peaks to facilitate ease of detection. A quantitative evaluation of the performance characteristics of the new filter is conducted and is shown to compare favorably with the well known Minimum Variance Synthetic Discriminant Function and the space domain Minimum Average Correlation Energy filter, which are special cases of the present design.

  2. Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

    PubMed

    Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

    2018-05-01

    High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Kalman filter for statistical monitoring of forest cover across sub-continental regions [Symposium

    Treesearch

    Raymond L. Czaplewski

    1991-01-01

    The Kalman filter is a generalization of the composite estimator. The univariate composite estimate combines 2 prior estimates of population parameter with a weighted average where the scalar weight is inversely proportional to the variances. The composite estimator is a minimum variance estimator that requires no distributional assumptions other than estimates of the...

  4. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

    PubMed Central

    Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

    2018-01-01

    This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

  5. Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

    PubMed

    Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

    2018-02-06

    This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

  6. Analysis and application of minimum variance discrete time system identification

    NASA Technical Reports Server (NTRS)

    Kaufman, H.; Kotob, S.

    1975-01-01

    An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

  7. Spectral analysis comparisons of Fourier-theory-based methods and minimum variance (Capon) methods

    NASA Astrophysics Data System (ADS)

    Garbanzo-Salas, Marcial; Hocking, Wayne. K.

    2015-09-01

    In recent years, adaptive (data dependent) methods have been introduced into many areas where Fourier spectral analysis has traditionally been used. Although the data-dependent methods are often advanced as being superior to Fourier methods, they do require some finesse in choosing the order of the relevant filters. In performing comparisons, we have found some concerns about the mappings, particularly when related to cases involving many spectral lines or even continuous spectral signals. Using numerical simulations, several comparisons between Fourier transform procedures and minimum variance method (MVM) have been performed. For multiple frequency signals, the MVM resolves most of the frequency content only for filters that have more degrees of freedom than the number of distinct spectral lines in the signal. In the case of Gaussian spectral approximation, MVM will always underestimate the width, and can misappropriate the location of spectral line in some circumstances. Large filters can be used to improve results with multiple frequency signals, but are computationally inefficient. Significant biases can occur when using MVM to study spectral information or echo power from the atmosphere. Artifacts and artificial narrowing of turbulent layers is one such impact.

  8. An adaptive technique for estimating the atmospheric density profile during the AE mission

    NASA Technical Reports Server (NTRS)

    Argentiero, P.

    1973-01-01

    A technique is presented for processing accelerometer data obtained during the AE missions in order to estimate the atmospheric density profile. A minimum variance, adaptive filter is utilized. The trajectory of the probe and probe parameters are in a consider mode where their estimates are unimproved but their associated uncertainties are permitted an impact on filter behavior. Simulations indicate that the technique is effective in estimating a density profile to within a few percentage points.

  9. Fast computation of an optimal controller for large-scale adaptive optics.

    PubMed

    Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Conan, Jean-Marc

    2011-11-01

    The linear quadratic Gaussian regulator provides the minimum-variance control solution for a linear time-invariant system. For adaptive optics (AO) applications, under the hypothesis of a deformable mirror with instantaneous response, such a controller boils down to a minimum-variance phase estimator (a Kalman filter) and a projection onto the mirror space. The Kalman filter gain can be computed by solving an algebraic Riccati matrix equation, whose computational complexity grows very quickly with the size of the telescope aperture. This "curse of dimensionality" makes the standard solvers for Riccati equations very slow in the case of extremely large telescopes. In this article, we propose a way of computing the Kalman gain for AO systems by means of an approximation that considers the turbulence phase screen as the cropped version of an infinite-size screen. We demonstrate the advantages of the methods for both off- and on-line computational time, and we evaluate its performance for classical AO as well as for wide-field tomographic AO with multiple natural guide stars. Simulation results are reported.

  10. A CLT on the SNR of Diagonally Loaded MVDR Filters

    NASA Astrophysics Data System (ADS)

    Rubio, Francisco; Mestre, Xavier; Hachem, Walid

    2012-08-01

    This paper studies the fluctuations of the signal-to-noise ratio (SNR) of minimum variance distorsionless response (MVDR) filters implementing diagonal loading in the estimation of the covariance matrix. Previous results in the signal processing literature are generalized and extended by considering both spatially as well as temporarily correlated samples. Specifically, a central limit theorem (CLT) is established for the fluctuations of the SNR of the diagonally loaded MVDR filter, under both supervised and unsupervised training settings in adaptive filtering applications. Our second-order analysis is based on the Nash-Poincar\\'e inequality and the integration by parts formula for Gaussian functionals, as well as classical tools from statistical asymptotic theory. Numerical evaluations validating the accuracy of the CLT confirm the asymptotic Gaussianity of the fluctuations of the SNR of the MVDR filter.

  11. Minimum Energy-Variance Filters for the detection of compact sources in crowded astronomical images

    NASA Astrophysics Data System (ADS)

    Herranz, D.; Sanz, J. L.; López-Caniego, M.; González-Nuevo, J.

    2006-10-01

    In this paper we address the common problem of the detection and identification of compact sources, such as stars or far galaxies, in Astronomical images. The common approach, that consist in applying a matched filter to the data in order to remove noise and to search for intensity peaks above a certain detection threshold, does not work well when the sources to be detected appear in large number over small regions of the sky due to the effect of source overlapping and interferences among the filtered profiles of the sources. A new class of filter that balances noise removal with signal spatial concentration is introduced, then it is applied to simulated astronomical images of the sky at 857 GHz. We show that with the new filter it is possible to improve the ratio between true detections and false alarms with respect to the matched filter. For low detection thresholds, the improvement is ~ 40%.

  12. Noise sensitivity of portfolio selection in constant conditional correlation GARCH models

    NASA Astrophysics Data System (ADS)

    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.

  13. The Principle of Energetic Consistency

    NASA Technical Reports Server (NTRS)

    Cohn, Stephen E.

    2009-01-01

    A basic result in estimation theory is that the minimum variance estimate of the dynamical state, given the observations, is the conditional mean estimate. This result holds independently of the specifics of any dynamical or observation nonlinearity or stochasticity, requiring only that the probability density function of the state, conditioned on the observations, has two moments. For nonlinear dynamics that conserve a total energy, this general result implies the principle of energetic consistency: if the dynamical variables are taken to be the natural energy variables, then the sum of the total energy of the conditional mean and the trace of the conditional covariance matrix (the total variance) is constant between observations. Ensemble Kalman filtering methods are designed to approximate the evolution of the conditional mean and covariance matrix. For them the principle of energetic consistency holds independently of ensemble size, even with covariance localization. However, full Kalman filter experiments with advection dynamics have shown that a small amount of numerical dissipation can cause a large, state-dependent loss of total variance, to the detriment of filter performance. The principle of energetic consistency offers a simple way to test whether this spurious loss of variance limits ensemble filter performance in full-blown applications. The classical second-moment closure (third-moment discard) equations also satisfy the principle of energetic consistency, independently of the rank of the conditional covariance matrix. Low-rank approximation of these equations offers an energetically consistent, computationally viable alternative to ensemble filtering. Current formulations of long-window, weak-constraint, four-dimensional variational methods are designed to approximate the conditional mode rather than the conditional mean. Thus they neglect the nonlinear bias term in the second-moment closure equation for the conditional mean. The principle of energetic consistency implies that, to precisely the extent that growing modes are important in data assimilation, this term is also important.

  14. Real-valued composite filters for correlation-based optical pattern recognition

    NASA Technical Reports Server (NTRS)

    Rajan, P. K.; Balendra, Anushia

    1992-01-01

    Advances in the technology of optical devices such as spatial light modulators (SLMs) have influenced the research and growth of optical pattern recognition. In the research leading to this report, the design of real-valued composite filters that can be implemented using currently available SLMs for optical pattern recognition and classification was investigated. The design of real-valued minimum average correlation energy (RMACE) filter was investigated. Proper selection of the phase of the output response was shown to reduce the correlation energy. The performance of the filter was evaluated using computer simulations and compared with the complex filters. It was found that the performance degraded only slightly. Continuing the above investigation, the design of a real filter that minimizes the output correlation energy and the output variance due to noise was developed. Simulation studies showed that this filter had better tolerance to distortion and noise compared to that of the RMACE filter. Finally, the space domain design of RMACE filter was developed and implemented on the computer. It was found that the sharpness of the correlation peak was slightly reduced but the filter design was more computationally efficient than the complex filter.

  15. Point focusing using loudspeaker arrays from the perspective of optimal beamforming.

    PubMed

    Bai, Mingsian R; Hsieh, Yu-Hao

    2015-06-01

    Sound focusing is to create a concentrated acoustic field in the region surrounded by a loudspeaker array. This problem was tackled in the previous research via the Helmholtz integral approach, brightness control, acoustic contrast control, etc. In this paper, the same problem was revisited from the perspective of beamforming. A source array model is reformulated in terms of the steering matrix between the source and the field points, which lends itself to the use of beamforming algorithms such as minimum variance distortionless response (MVDR) and linearly constrained minimum variance (LCMV) originally intended for sensor arrays. The beamforming methods are compared with the conventional methods in terms of beam pattern, directional index, and control effort. Objective tests are conducted to assess the audio quality by using perceptual evaluation of audio quality (PEAQ). Experiments of produced sound field and listening tests are conducted in a listening room, with results processed using analysis of variance and regression analysis. In contrast to the conventional energy-based methods, the results have shown that the proposed methods are phase-sensitive in light of the distortionless constraint in formulating the array filters, which helps enhance audio quality and focusing performance.

  16. Demodulation of messages received with low signal to noise ratio

    NASA Astrophysics Data System (ADS)

    Marguinaud, A.; Quignon, T.; Romann, B.

    The implementation of this all-digital demodulator is derived from maximum likelihood considerations applied to an analytical representation of the received signal. Traditional adapted filters and phase lock loops are replaced by minimum variance estimators and hypothesis tests. These statistical tests become very simple when working on phase signal. These methods, combined with rigorous control data representation allow significant computation savings as compared to conventional realizations. Nominal operation has been verified down to energetic signal over noise of -3 dB upon a QPSK demodulator.

  17. Filtering for networked control systems with single/multiple measurement packets subject to multiple-step measurement delays and multiple packet dropouts

    NASA Astrophysics Data System (ADS)

    Moayedi, Maryam; Foo, Yung Kuan; Chai Soh, Yeng

    2011-03-01

    The minimum-variance filtering problem in networked control systems, where both random measurement transmission delays and packet dropouts may occur, is investigated in this article. Instead of following the many existing results that solve the problem by using probabilistic approaches based on the probabilities of the uncertainties occurring between the sensor and the filter, we propose a non-probabilistic approach by time-stamping the measurement packets. Both single-measurement and multiple measurement packets are studied. We also consider the case of burst arrivals, where more than one packet may arrive between the receiver's previous and current sampling times; the scenario where the control input is non-zero and subject to delays and packet dropouts is examined as well. It is shown that, in such a situation, the optimal state estimate would generally be dependent on the possible control input. Simulations are presented to demonstrate the performance of the various proposed filters.

  18. A robust pseudo-inverse spectral filter applied to the Earth Radiation Budget Experiment (ERBE) scanning channels

    NASA Technical Reports Server (NTRS)

    Avis, L. M.; Green, R. N.; Suttles, J. T.; Gupta, S. K.

    1984-01-01

    Computer simulations of a least squares estimator operating on the ERBE scanning channels are discussed. The estimator is designed to minimize the errors produced by nonideal spectral response to spectrally varying and uncertain radiant input. The three ERBE scanning channels cover a shortwave band a longwave band and a ""total'' band from which the pseudo inverse spectral filter estimates the radiance components in the shortwave band and a longwave band. The radiance estimator draws on instantaneous field of view (IFOV) scene type information supplied by another algorithm of the ERBE software, and on a priori probabilistic models of the responses of the scanning channels to the IFOV scene types for given Sun scene spacecraft geometry. It is found that the pseudoinverse spectral filter is stable, tolerant of errors in scene identification and in channel response modeling, and, in the absence of such errors, yields minimum variance and essentially unbiased radiance estimates.

  19. Optimized Beam Sculpting with Generalized Fringe-rate Filters

    NASA Astrophysics Data System (ADS)

    Parsons, Aaron R.; Liu, Adrian; Ali, Zaki S.; Cheng, Carina

    2016-03-01

    We generalize the technique of fringe-rate filtering, whereby visibilities measured by a radio interferometer are re-weighted according to their temporal variation. As the Earth rotates, radio sources traverse through an interferometer’s fringe pattern at rates that depend on their position on the sky. Capitalizing on this geometric interpretation of fringe rates, we employ time-domain convolution kernels to enact fringe-rate filters that sculpt the effective primary beam of antennas in an interferometer. As we show, beam sculpting through fringe-rate filtering can be used to optimize measurements for a variety of applications, including mapmaking, minimizing polarization leakage, suppressing instrumental systematics, and enhancing the sensitivity of power-spectrum measurements. We show that fringe-rate filtering arises naturally in minimum variance treatments of many of these problems, enabling optimal visibility-based approaches to analyses of interferometric data that avoid systematics potentially introduced by traditional approaches such as imaging. Our techniques have recently been demonstrated in Ali et al., where new upper limits were placed on the 21 {cm} power spectrum from reionization, showcasing the ability of fringe-rate filtering to successfully boost sensitivity and reduce the impact of systematics in deep observations.

  20. VizieR Online Data Catalog: AGNs in submm-selected Lockman Hole galaxies (Serjeant+, 2010)

    NASA Astrophysics Data System (ADS)

    Serjeant, S.; Negrello, M.; Pearson, C.; Mortier, A.; Austermann, J.; Aretxaga, I.; Clements, D.; Chapman, S.; Dye, S.; Dunlop, J.; Dunne, L.; Farrah, D.; Hughes, D.; Lee, H. M.; Matsuhara, H.; Ibar, E.; Im, M.; Jeong, W.-S.; Kim, S.; Oyabu, S.; Takagi, T.; Wada, T.; Wilson, G.; Vaccari, M.; Yun, M.

    2013-11-01

    We present a comparison of the SCUBA half degree extragalactic survey (SHADES) at 450μm, 850μm and 1100μm with deep guaranteed time 15μm AKARI FU-HYU survey data and Spitzer guaranteed time data at 3.6-24μm in the Lockman hole east. The AKARI data was analysed using bespoke software based in part on the drizzling and minimum-variance matched filtering developed for SHADES, and was cross-calibrated against ISO fluxes. (2 data files).

  1. A close examination of double filtering with fold change and t test in microarray analysis

    PubMed Central

    2009-01-01

    Background Many researchers use the double filtering procedure with fold change and t test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods. Results This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while t statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure. Conclusion We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure. PMID:19995439

  2. FOG Random Drift Signal Denoising Based on the Improved AR Model and Modified Sage-Husa Adaptive Kalman Filter.

    PubMed

    Sun, Jin; Xu, Xiaosu; Liu, Yiting; Zhang, Tao; Li, Yao

    2016-07-12

    In order to reduce the influence of fiber optic gyroscope (FOG) random drift error on inertial navigation systems, an improved auto regressive (AR) model is put forward in this paper. First, based on real-time observations at each restart of the gyroscope, the model of FOG random drift can be established online. In the improved AR model, the FOG measured signal is employed instead of the zero mean signals. Then, the modified Sage-Husa adaptive Kalman filter (SHAKF) is introduced, which can directly carry out real-time filtering on the FOG signals. Finally, static and dynamic experiments are done to verify the effectiveness. The filtering results are analyzed with Allan variance. The analysis results show that the improved AR model has high fitting accuracy and strong adaptability, and the minimum fitting accuracy of single noise is 93.2%. Based on the improved AR(3) model, the denoising method of SHAKF is more effective than traditional methods, and its effect is better than 30%. The random drift error of FOG is reduced effectively, and the precision of the FOG is improved.

  3. 42 CFR 84.125 - Particulate tests; canisters containing particulate filters; minimum requirements.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... filters; minimum requirements. 84.125 Section 84.125 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF... RESPIRATORY PROTECTIVE DEVICES Gas Masks § 84.125 Particulate tests; canisters containing particulate filters; minimum requirements. Gas mask canisters containing filters for protection against particulates (e.g...

  4. 42 CFR 84.125 - Particulate tests; canisters containing particulate filters; minimum requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... filters; minimum requirements. 84.125 Section 84.125 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF... RESPIRATORY PROTECTIVE DEVICES Gas Masks § 84.125 Particulate tests; canisters containing particulate filters; minimum requirements. Gas mask canisters containing filters for protection against particulates (e.g...

  5. 42 CFR 84.125 - Particulate tests; canisters containing particulate filters; minimum requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... filters; minimum requirements. 84.125 Section 84.125 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF... RESPIRATORY PROTECTIVE DEVICES Gas Masks § 84.125 Particulate tests; canisters containing particulate filters; minimum requirements. Gas mask canisters containing filters for protection against particulates (e.g...

  6. 42 CFR 84.125 - Particulate tests; canisters containing particulate filters; minimum requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... filters; minimum requirements. 84.125 Section 84.125 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF... RESPIRATORY PROTECTIVE DEVICES Gas Masks § 84.125 Particulate tests; canisters containing particulate filters; minimum requirements. Gas mask canisters containing filters for protection against particulates (e.g...

  7. 42 CFR 84.125 - Particulate tests; canisters containing particulate filters; minimum requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... filters; minimum requirements. 84.125 Section 84.125 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF... RESPIRATORY PROTECTIVE DEVICES Gas Masks § 84.125 Particulate tests; canisters containing particulate filters; minimum requirements. Gas mask canisters containing filters for protection against particulates (e.g...

  8. 42 CFR 84.87 - Compressed gas filters; minimum requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Compressed gas filters; minimum requirements. 84.87...-Contained Breathing Apparatus § 84.87 Compressed gas filters; minimum requirements. All self-contained breathing apparatus using compressed gas shall have a filter downstream of the gas source to effectively...

  9. 42 CFR 84.87 - Compressed gas filters; minimum requirements.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 1 2013-10-01 2013-10-01 false Compressed gas filters; minimum requirements. 84.87...-Contained Breathing Apparatus § 84.87 Compressed gas filters; minimum requirements. All self-contained breathing apparatus using compressed gas shall have a filter downstream of the gas source to effectively...

  10. 42 CFR 84.87 - Compressed gas filters; minimum requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 1 2011-10-01 2011-10-01 false Compressed gas filters; minimum requirements. 84.87...-Contained Breathing Apparatus § 84.87 Compressed gas filters; minimum requirements. All self-contained breathing apparatus using compressed gas shall have a filter downstream of the gas source to effectively...

  11. 42 CFR 84.87 - Compressed gas filters; minimum requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false Compressed gas filters; minimum requirements. 84.87...-Contained Breathing Apparatus § 84.87 Compressed gas filters; minimum requirements. All self-contained breathing apparatus using compressed gas shall have a filter downstream of the gas source to effectively...

  12. 42 CFR 84.87 - Compressed gas filters; minimum requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 1 2014-10-01 2014-10-01 false Compressed gas filters; minimum requirements. 84.87...-Contained Breathing Apparatus § 84.87 Compressed gas filters; minimum requirements. All self-contained breathing apparatus using compressed gas shall have a filter downstream of the gas source to effectively...

  13. Adaptive Filtering Using Recurrent Neural Networks

    NASA Technical Reports Server (NTRS)

    Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.

    2005-01-01

    A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.

  14. Distribution of a low dose compound within pharmaceutical tablet by using multivariate curve resolution on Raman hyperspectral images.

    PubMed

    Boiret, Mathieu; de Juan, Anna; Gorretta, Nathalie; Ginot, Yves-Michel; Roger, Jean-Michel

    2015-01-25

    In this work, Raman hyperspectral images and multivariate curve resolution-alternating least squares (MCR-ALS) are used to study the distribution of actives and excipients within a pharmaceutical drug product. This article is mainly focused on the distribution of a low dose constituent. Different approaches are compared, using initially filtered or non-filtered data, or using a column-wise augmented dataset before starting the MCR-ALS iterative process including appended information on the low dose component. In the studied formulation, magnesium stearate is used as a lubricant to improve powder flowability. With a theoretical concentration of 0.5% (w/w) in the drug product, the spectral variance contained in the data is weak. By using a principal component analysis (PCA) filtered dataset as a first step of the MCR-ALS approach, the lubricant information is lost in the non-explained variance and its associated distribution in the tablet cannot be highlighted. A sufficient number of components to generate the PCA noise-filtered matrix has to be used in order to keep the lubricant variability within the data set analyzed or, otherwise, work with the raw non-filtered data. Different models are built using an increasing number of components to perform the PCA reduction. It is shown that the magnesium stearate information can be extracted from a PCA model using a minimum of 20 components. In the last part, a column-wise augmented matrix, including a reference spectrum of the lubricant, is used before starting MCR-ALS process. PCA reduction is performed on the augmented matrix, so the magnesium stearate contribution is included within the MCR-ALS calculations. By using an appropriate PCA reduction, with a sufficient number of components, or by using an augmented dataset including appended information on the low dose component, the distribution of the two actives, the two main excipients and the low dose lubricant are correctly recovered. Copyright © 2014 Elsevier B.V. All rights reserved.

  15. 42 CFR 84.206 - Particulate tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 1 2013-10-01 2013-10-01 false Particulate tests; respirators with filters... filters; minimum requirements; general. (a) Three respirators with cartridges containing, or having attached to them, filters for protection against particulates will be tested in accordance with the...

  16. 42 CFR 84.206 - Particulate tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 1 2011-10-01 2011-10-01 false Particulate tests; respirators with filters... filters; minimum requirements; general. (a) Three respirators with cartridges containing, or having attached to them, filters for protection against particulates will be tested in accordance with the...

  17. 42 CFR 84.206 - Particulate tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false Particulate tests; respirators with filters... filters; minimum requirements; general. (a) Three respirators with cartridges containing, or having attached to them, filters for protection against particulates will be tested in accordance with the...

  18. 42 CFR 84.206 - Particulate tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 1 2014-10-01 2014-10-01 false Particulate tests; respirators with filters... filters; minimum requirements; general. (a) Three respirators with cartridges containing, or having attached to them, filters for protection against particulates will be tested in accordance with the...

  19. 42 CFR 84.206 - Particulate tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Particulate tests; respirators with filters... filters; minimum requirements; general. (a) Three respirators with cartridges containing, or having attached to them, filters for protection against particulates will be tested in accordance with the...

  20. Intelligent ensemble T-S fuzzy neural networks with RCDPSO_DM optimization for effective handling of complex clinical pathway variances.

    PubMed

    Du, Gang; Jiang, Zhibin; Diao, Xiaodi; Yao, Yang

    2013-07-01

    Takagi-Sugeno (T-S) fuzzy neural networks (FNNs) can be used to handle complex, fuzzy, uncertain clinical pathway (CP) variances. However, there are many drawbacks, such as slow training rate, propensity to become trapped in a local minimum and poor ability to perform a global search. In order to improve overall performance of variance handling by T-S FNNs, a new CP variance handling method is proposed in this study. It is based on random cooperative decomposing particle swarm optimization with double mutation mechanism (RCDPSO_DM) for T-S FNNs. Moreover, the proposed integrated learning algorithm, combining the RCDPSO_DM algorithm with a Kalman filtering algorithm, is applied to optimize antecedent and consequent parameters of constructed T-S FNNs. Then, a multi-swarm cooperative immigrating particle swarm algorithm ensemble method is used for intelligent ensemble T-S FNNs with RCDPSO_DM optimization to further improve stability and accuracy of CP variance handling. Finally, two case studies on liver and kidney poisoning variances in osteosarcoma preoperative chemotherapy are used to validate the proposed method. The result demonstrates that intelligent ensemble T-S FNNs based on the RCDPSO_DM achieves superior performances, in terms of stability, efficiency, precision and generalizability, over PSO ensemble of all T-S FNNs with RCDPSO_DM optimization, single T-S FNNs with RCDPSO_DM optimization, standard T-S FNNs, standard Mamdani FNNs and T-S FNNs based on other algorithms (cooperative particle swarm optimization and particle swarm optimization) for CP variance handling. Therefore, it makes CP variance handling more effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Basilar-membrane responses to broadband noise modeled using linear filters with rational transfer functions.

    PubMed

    Recio-Spinoso, Alberto; Fan, Yun-Hui; Ruggero, Mario A

    2011-05-01

    Basilar-membrane responses to white Gaussian noise were recorded using laser velocimetry at basal sites of the chinchilla cochlea with characteristic frequencies near 10 kHz and first-order Wiener kernels were computed by cross correlation of the stimuli and the responses. The presence or absence of minimum-phase behavior was explored by fitting the kernels with discrete linear filters with rational transfer functions. Excellent fits to the kernels were obtained with filters with transfer functions including zeroes located outside the unit circle, implying nonminimum-phase behavior. These filters accurately predicted basilar-membrane responses to other noise stimuli presented at the same level as the stimulus for the kernel computation. Fits with all-pole and other minimum-phase discrete filters were inferior to fits with nonminimum-phase filters. Minimum-phase functions predicted from the amplitude functions of the Wiener kernels by Hilbert transforms were different from the measured phase curves. These results, which suggest that basilar-membrane responses do not have the minimum-phase property, challenge the validity of models of cochlear processing, which incorporate minimum-phase behavior. © 2011 IEEE

  2. 75 FR 40797 - Upper Peninsula Power Company; Notice of Application for Temporary Amendment of License and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-14

    ... for drought-based temporary variance of the reservoir elevations and minimum flow releases at the Dead... temporary variance to the reservoir elevation and minimum flow requirements at the Hoist Development. The...: (1) Releasing a minimum flow of 75 cubic feet per second (cfs) from the Hoist Reservoir, instead of...

  3. Ultrasonic tracking of shear waves using a particle filter.

    PubMed

    Ingle, Atul N; Ma, Chi; Varghese, Tomy

    2015-11-01

    This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques.

  4. Fully invariant wavelet enhanced minimum average correlation energy filter for object recognition in cluttered and occluded environments

    NASA Astrophysics Data System (ADS)

    Tehsin, Sara; Rehman, Saad; Riaz, Farhan; Saeed, Omer; Hassan, Ali; Khan, Muazzam; Alam, Muhammad S.

    2017-05-01

    A fully invariant system helps in resolving difficulties in object detection when camera or object orientation and position are unknown. In this paper, the proposed correlation filter based mechanism provides the capability to suppress noise, clutter and occlusion. Minimum Average Correlation Energy (MACE) filter yields sharp correlation peaks while considering the controlled correlation peak value. Difference of Gaussian (DOG) Wavelet has been added at the preprocessing stage in proposed filter design that facilitates target detection in orientation variant cluttered environment. Logarithmic transformation is combined with a DOG composite minimum average correlation energy filter (WMACE), capable of producing sharp correlation peaks despite any kind of geometric distortion of target object. The proposed filter has shown improved performance over some of the other variant correlation filters which are discussed in the result section.

  5. The Variance of Solar Wind Magnetic Fluctuations: Solutions and Further Puzzles

    NASA Technical Reports Server (NTRS)

    Roberts, D. A.; Goldstein, M. L.

    2006-01-01

    We study the dependence of the variance directions of the magnetic field in the solar wind as a function of scale, radial distance, and Alfvenicity. The study resolves the question of why different studies have arrived at widely differing values for the maximum to minimum power (approximately equal to 3:1 up to approximately equal to 20:1). This is due to the decreasing anisotropy with increasing time interval chosen for the variance, and is a direct result of the "spherical polarization" of the waves which follows from the near constancy of |B|. The reason for the magnitude preserving evolution is still unresolved. Moreover, while the long-known tendency for the minimum variance to lie along the mean field also follows from this view (as shown by Barnes many years ago), there is no theory for why the minimum variance follows the field direction as the Parker angle changes. We show that this turning is quite generally true in Alfvenic regions over a wide range of heliocentric distances. The fact that nonAlfvenic regions, while still showing strong power anisotropies, tend to have a much broader range of angles between the minimum variance and the mean field makes it unlikely that the cause of the variance turning is to be found in a turbulence mechanism. There are no obvious alternative mechanisms, leaving us with another intriguing puzzle.

  6. Minimum variance geographic sampling

    NASA Technical Reports Server (NTRS)

    Terrell, G. R. (Principal Investigator)

    1980-01-01

    Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

  7. Solar Control of Earth's Ionosphere: Observations from Solar Cycle 23

    NASA Astrophysics Data System (ADS)

    Doe, R. A.; Thayer, J. P.; Solomon, S. C.

    2005-05-01

    A nine year database of sunlit E-region electron density altitude profiles (Ne(z)) measured by the Sondrestrom ISR has been partitioned over a 30-bin parameter space of averaged 10.7 cm solar radio flux (F10.7) and solar zenith angle (χ) to investigate long-term solar and thermospheric variability, and to validate contemporary EUV photoionization models. A two stage filter, based on rejection of Ne(z) profiles with large Hall to Pedersen ratio, is used to minimize auroral contamination. Resultant filtered mean Ne(z) compares favorably with subauroral Ne measured for the same F10.7 and χ conditions at the Millstone Hill ISR. Mean Ne, as expected, increases with solar activity and decreases with large χ, and the variance around mean Ne is shown to be greatest at low F10.7 (solar minimum). ISR-derived mean Ne is compared with two EUV models: (1) a simple model without photoelectrons and based on the 5 -- 105 nm EUVAC model solar flux [Richards et al., 1994] and (2) the GLOW model [Solomon et al., 1988; Solomon and Abreu, 1989] suitably modified for inclusion of XUV spectral components and photoelectron flux. Across parameter space and for all altitudes, Model 2 provides a closer match to ISR mean Ne and suggests that the photoelectron and XUV enhancements are essential to replicate measured plasma densities below 150 km. Simulated Ne variance envelopes, given by perturbing the Model 2 neutral atmosphere input by the measured extremum in Ap, F10.7, and Te, are much narrower than ISR-derived geophysical variance envelopes. We thus conclude that long-term variability of the EUV spectra dominates over thermospheric variability and that EUV spectral variability is greatest at solar minimum. ISR -- model comparison also provides evidence for the emergence of an H (Lyman β) Ne feature at solar maximum. Richards, P. G., J. A. Fennelly, and D. G. Torr, EUVAC: A solar EUV flux model for aeronomic calculations, J. Geophys. Res., 99, 8981, 1994. Solomon, S. C., P. B. Hays, and V. J. Abreu, The auroral 6300 Å emission: Observations and Modeling, J. Geophys. Res., 93, 9867, 1988. Solomon, S. C. and V. J. Abreu, The 630 nm dayglow, J. Geophys. Res., 94, 6817, 1989.

  8. Discrete filtering techniques applied to sequential GPS range measurements

    NASA Technical Reports Server (NTRS)

    Vangraas, Frank

    1987-01-01

    The basic navigation solution is described for position and velocity based on range and delta range (Doppler) measurements from NAVSTAR Global Positioning System satellites. The application of discrete filtering techniques is examined to reduce the white noise distortions on the sequential range measurements. A second order (position and velocity states) Kalman filter is implemented to obtain smoothed estimates of range by filtering the dynamics of the signal from each satellite separately. Test results using a simulated GPS receiver show a steady-state noise reduction, the input noise variance divided by the output noise variance, of a factor of four. Recommendations for further noise reduction based on higher order Kalman filters or additional delta range measurements are included.

  9. 40 CFR Table 3 to Subpart Ec of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... scrubber followed by fabric filter Wet scrubber Dry scrubber followed by fabric filter and wet scrubber... flow rate Hourly 1×hour ✔ ✔ Minimum pressure drop across the wet scrubber or minimum horsepower or amperage to wet scrubber Continuous 1×minute ✔ ✔ Minimum scrubber liquor flow rate Continuous 1×minute...

  10. Incorporation of Differential Global Positioning System Measurements Using an Extended Kalman Filter for Improved Reference System Performance

    DTIC Science & Technology

    1991-12-01

    Kalman filtering. As GPS usage expands throughout the military and civilian communities, I hope this thesis provides a small contribution in this area...of the measurement’equation. In this thesis, some of the INS states not part of a measurement equation need a small amount of added noise to...estimating the state, but the variance often goes negative. A small amount of added noise in the filter keeps the variance of the state positive and does not

  11. Ultrasonic tracking of shear waves using a particle filter

    PubMed Central

    Ingle, Atul N.; Ma, Chi; Varghese, Tomy

    2015-01-01

    Purpose: This paper discusses an application of particle filtering for estimating shear wave velocity in tissue using ultrasound elastography data. Shear wave velocity estimates are of significant clinical value as they help differentiate stiffer areas from softer areas which is an indicator of potential pathology. Methods: Radio-frequency ultrasound echo signals are used for tracking axial displacements and obtaining the time-to-peak displacement at different lateral locations. These time-to-peak data are usually very noisy and cannot be used directly for computing velocity. In this paper, the denoising problem is tackled using a hidden Markov model with the hidden states being the unknown (noiseless) time-to-peak values. A particle filter is then used for smoothing out the time-to-peak curve to obtain a fit that is optimal in a minimum mean squared error sense. Results: Simulation results from synthetic data and finite element modeling suggest that the particle filter provides lower mean squared reconstruction error with smaller variance as compared to standard filtering methods, while preserving sharp boundary detail. Results from phantom experiments show that the shear wave velocity estimates in the stiff regions of the phantoms were within 20% of those obtained from a commercial ultrasound scanner and agree with estimates obtained using a standard method using least-squares fit. Estimates of area obtained from the particle filtered shear wave velocity maps were within 10% of those obtained from B-mode ultrasound images. Conclusions: The particle filtering approach can be used for producing visually appealing SWV reconstructions by effectively delineating various areas of the phantom with good image quality properties comparable to existing techniques. PMID:26520761

  12. Equalizing secondary path effects using the periodicity of fMRI acoustic noise.

    PubMed

    Kannan, Govind; Milani, Ali A; Panahi, Issa; Briggs, Richard

    2008-01-01

    Non-minimum phase secondary path has a direct effect on achieving a desired noise attenuation level in active noise control (ANC) systems. The adaptive noise canceling filter is often a causal FIR filter which may not be able to sufficiently equalize the effect of a non-minimum phase secondary path, since in theory only a non-causal filter can equalize it. However a non-causal stable filter can be found to equalize the non-minimum phase effect of secondary path. Realization of non-causal stable filters requires knowledge of future values of input signal. In this paper we develop methods for equalizing the non-minimum phase property of the secondary path and improving the performance of an ANC system by exploiting the periodicity of fMRI acoustic noise. It has been shown that the scanner noise component is highly periodic and hence predictable which enables easy realization of non-causal filtering. Improvement in performance due to the proposed methods (with and without the equalizer) is shown for periodic fMRI acoustic noise.

  13. Ultrasonic Imaging in Solids Using Wave Mode Beamforming.

    PubMed

    di Scalea, Francesco Lanza; Sternini, Simone; Nguyen, Thompson Vu

    2017-03-01

    This paper discusses some improvements to ultrasonic synthetic imaging in solids with primary applications to nondestructive testing of materials and structures. Specifically, the study proposes new adaptive weights applied to the beamforming array that are based on the physics of the propagating waves, specifically the displacement structure of the propagating longitudinal (L) mode and shear (S) mode that are naturally coexisting in a solid. The wave mode structures can be combined with the wave geometrical spreading to better filter the array (in a matched filter approach) and improve its focusing ability compared to static array weights. This paper also proposes compounding, or summing, images obtained from the different wave modes to further improve the array gain without increasing its physical aperture. The wave mode compounding can be performed either incoherently or coherently, in analogy with compounding multiple frequencies or multiple excitations. Numerical simulations and experimental testing demonstrate the potential improvements obtainable by the wave structure adaptive weights compared to either static weights in conventional delay-and-sum focusing, or adaptive weights based on geometrical spreading alone in minimum-variance distortionless response focusing.

  14. Reduction of noise and image artifacts in computed tomography by nonlinear filtration of projection images

    NASA Astrophysics Data System (ADS)

    Demirkaya, Omer

    2001-07-01

    This study investigates the efficacy of filtering two-dimensional (2D) projection images of Computer Tomography (CT) by the nonlinear diffusion filtration in removing the statistical noise prior to reconstruction. The projection images of Shepp-Logan head phantom were degraded by Gaussian noise. The variance of the Gaussian distribution was adaptively changed depending on the intensity at a given pixel in the projection image. The corrupted projection images were then filtered using the nonlinear anisotropic diffusion filter. The filtered projections as well as original noisy projections were reconstructed using filtered backprojection (FBP) with Ram-Lak filter and/or Hanning window. The ensemble variance was computed for each pixel on a slice. The nonlinear filtering of projection images improved the SNR substantially, on the order of fourfold, in these synthetic images. The comparison of intensity profiles across a cross-sectional slice indicated that the filtering did not result in any significant loss of image resolution.

  15. Self-tuning regulators for multicyclic control of helicopter vibration

    NASA Technical Reports Server (NTRS)

    Johnson, W.

    1982-01-01

    A class of algorithms for the multicyclic control of helicopter vibration and loads is derived and discussed. This class is characterized by a linear, quasi-static, frequency-domain model of the helicopter response to control; identification of the helicopter model by least-squared-error or Kalman filter methods; and a minimum variance or quadratic performance function controller. Previous research on such controllers is reviewed. The derivations and discussions cover the helicopter model; the identification problem, including both off-line and on-line (recursive) algorithms; the control problem, including both open-loop and closed-loop feedback; and the various regulator configurations possible within this class. Conclusions from analysis and numerical simulations of the regulators provide guidance in the design and selection of algorithms for further development, including wind tunnel and flight tests.

  16. Portfolio optimization with mean-variance model

    NASA Astrophysics Data System (ADS)

    Hoe, Lam Weng; Siew, Lam Weng

    2016-06-01

    Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

  17. Application of an improved minimum entropy deconvolution method for railway rolling element bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Cheng, Yao; Zhou, Ning; Zhang, Weihua; Wang, Zhiwei

    2018-07-01

    Minimum entropy deconvolution is a widely-used tool in machinery fault diagnosis, because it enhances the impulse component of the signal. The filter coefficients that greatly influence the performance of the minimum entropy deconvolution are calculated by an iterative procedure. This paper proposes an improved deconvolution method for the fault detection of rolling element bearings. The proposed method solves the filter coefficients by the standard particle swarm optimization algorithm, assisted by a generalized spherical coordinate transformation. When optimizing the filters performance for enhancing the impulses in fault diagnosis (namely, faulty rolling element bearings), the proposed method outperformed the classical minimum entropy deconvolution method. The proposed method was validated in simulation and experimental signals from railway bearings. In both simulation and experimental studies, the proposed method delivered better deconvolution performance than the classical minimum entropy deconvolution method, especially in the case of low signal-to-noise ratio.

  18. SU-C-207B-05: Tissue Segmentation of Computed Tomography Images Using a Random Forest Algorithm: A Feasibility Study

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Polan, D; Brady, S; Kaufman, R

    2016-06-15

    Purpose: Develop an automated Random Forest algorithm for tissue segmentation of CT examinations. Methods: Seven materials were classified for segmentation: background, lung/internal gas, fat, muscle, solid organ parenchyma, blood/contrast, and bone using Matlab and the Trainable Weka Segmentation (TWS) plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance each evaluated over a pixel radius of 2n, (n = 0–4). Also noise reduction and edge preserving filters, Gaussian, bilateral, Kuwahara, and anisotropic diffusion, were evaluated. The algorithm used 200 trees with 2 features per node. A training data set was established using anmore » anonymized patient’s (male, 20 yr, 72 kg) chest-abdomen-pelvis CT examination. To establish segmentation ground truth, the training data were manually segmented using Eclipse planning software, and an intra-observer reproducibility test was conducted. Six additional patient data sets were segmented based on classifier data generated from the training data. Accuracy of segmentation was determined by calculating the Dice similarity coefficient (DSC) between manual and auto segmented images. Results: The optimized autosegmentation algorithm resulted in 16 features calculated using maximum, mean, variance, and Gaussian blur filters with kernel radii of 1, 2, and 4 pixels, in addition to the original CT number, and Kuwahara filter (linear kernel of 19 pixels). Ground truth had a DSC of 0.94 (range: 0.90–0.99) for adult and 0.92 (range: 0.85–0.99) for pediatric data sets across all seven segmentation classes. The automated algorithm produced segmentation with an average DSC of 0.85 ± 0.04 (range: 0.81–1.00) for the adult patients, and 0.86 ± 0.03 (range: 0.80–0.99) for the pediatric patients. Conclusion: The TWS Random Forest auto-segmentation algorithm was optimized for CT environment, and able to segment seven material classes over a range of body habitus and CT protocol parameters with an average DSC of 0.86 ± 0.04 (range: 0.80–0.99).« less

  19. Analysis of signal-dependent sensor noise on JPEG 2000-compressed Sentinel-2 multi-spectral images

    NASA Astrophysics Data System (ADS)

    Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

    2017-10-01

    The processing chain of Sentinel-2 MultiSpectral Instrument (MSI) data involves filtering and compression stages that modify MSI sensor noise. As a result, noise in Sentinel-2 Level-1C data distributed to users becomes processed. We demonstrate that processed noise variance model is bivariate: noise variance depends on image intensity (caused by signal-dependency of photon counting detectors) and signal-to-noise ratio (SNR; caused by filtering/compression). To provide information on processed noise parameters, which is missing in Sentinel-2 metadata, we propose to use blind noise parameter estimation approach. Existing methods are restricted to univariate noise model. Therefore, we propose extension of existing vcNI+fBm blind noise parameter estimation method to multivariate noise model, mvcNI+fBm, and apply it to each band of Sentinel-2A data. Obtained results clearly demonstrate that noise variance is affected by filtering/compression for SNR less than about 15. Processed noise variance is reduced by a factor of 2 - 5 in homogeneous areas as compared to noise variance for high SNR values. Estimate of noise variance model parameters are provided for each Sentinel-2A band. Sentinel-2A MSI Level-1C noise models obtained in this paper could be useful for end users and researchers working in a variety of remote sensing applications.

  20. Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

    NASA Astrophysics Data System (ADS)

    Floberg, J. M.; Holden, J. E.

    2013-02-01

    We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

  1. Stratospheric Assimilation of Chemical Tracer Observations Using a Kalman Filter. Pt. 2; Chi-Square Validated Results and Analysis of Variance and Correlation Dynamics

    NASA Technical Reports Server (NTRS)

    Menard, Richard; Chang, Lang-Ping

    1998-01-01

    A Kalman filter system designed for the assimilation of limb-sounding observations of stratospheric chemical tracers, which has four tunable covariance parameters, was developed in Part I (Menard et al. 1998) The assimilation results of CH4 observations from the Cryogenic Limb Array Etalon Sounder instrument (CLAES) and the Halogen Observation Experiment instrument (HALOE) on board of the Upper Atmosphere Research Satellite are described in this paper. A robust (chi)(sup 2) criterion, which provides a statistical validation of the forecast and observational error covariances, was used to estimate the tunable variance parameters of the system. In particular, an estimate of the model error variance was obtained. The effect of model error on the forecast error variance became critical after only three days of assimilation of CLAES observations, although it took 14 days of forecast to double the initial error variance. We further found that the model error due to numerical discretization as arising in the standard Kalman filter algorithm, is comparable in size to the physical model error due to wind and transport modeling errors together. Separate assimilations of CLAES and HALOE observations were compared to validate the state estimate away from the observed locations. A wave-breaking event that took place several thousands of kilometers away from the HALOE observation locations was well captured by the Kalman filter due to highly anisotropic forecast error correlations. The forecast error correlation in the assimilation of the CLAES observations was found to have a structure similar to that in pure forecast mode except for smaller length scales. Finally, we have conducted an analysis of the variance and correlation dynamics to determine their relative importance in chemical tracer assimilation problems. Results show that the optimality of a tracer assimilation system depends, for the most part, on having flow-dependent error correlation rather than on evolving the error variance.

  2. Temporal processing and adaptation in the songbird auditory forebrain.

    PubMed

    Nagel, Katherine I; Doupe, Allison J

    2006-09-21

    Songbird auditory neurons must encode the dynamics of natural sounds at many volumes. We investigated how neural coding depends on the distribution of stimulus intensities. Using reverse-correlation, we modeled responses to amplitude-modulated sounds as the output of a linear filter and a nonlinear gain function, then asked how filters and nonlinearities depend on the stimulus mean and variance. Filter shape depended strongly on mean amplitude (volume): at low mean, most neurons integrated sound over many milliseconds, while at high mean, neurons responded more to local changes in amplitude. Increasing the variance (contrast) of amplitude modulations had less effect on filter shape but decreased the gain of firing in most cells. Both filter and gain changes occurred rapidly after a change in statistics, suggesting that they represent nonlinearities in processing. These changes may permit neurons to signal effectively over a wider dynamic range and are reminiscent of findings in other sensory systems.

  3. 76 FR 1145 - Alabama Power Company; Notice of Application for Amendment of License and Soliciting Comments...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-01-07

    ... drought-based temporary variance of the Martin Project rule curve and minimum flow releases at the Yates... requesting a drought- based temporary variance to the Martin Project rule curve. The rule curve variance...

  4. Adaptive noise Wiener filter for scanning electron microscope imaging system.

    PubMed

    Sim, K S; Teh, V; Nia, M E

    2016-01-01

    Noise on scanning electron microscope (SEM) images is studied. Gaussian noise is the most common type of noise in SEM image. We developed a new noise reduction filter based on the Wiener filter. We compared the performance of this new filter namely adaptive noise Wiener (ANW) filter, with four common existing filters as well as average filter, median filter, Gaussian smoothing filter and the Wiener filter. Based on the experiments results the proposed new filter has better performance on different noise variance comparing to the other existing noise removal filters in the experiments. © Wiley Periodicals, Inc.

  5. Event-Based Variance-Constrained ${\\mathcal {H}}_{\\infty }$ Filtering for Stochastic Parameter Systems Over Sensor Networks With Successive Missing Measurements.

    PubMed

    Wang, Licheng; Wang, Zidong; Han, Qing-Long; Wei, Guoliang

    2018-03-01

    This paper is concerned with the distributed filtering problem for a class of discrete time-varying stochastic parameter systems with error variance constraints over a sensor network where the sensor outputs are subject to successive missing measurements. The phenomenon of the successive missing measurements for each sensor is modeled via a sequence of mutually independent random variables obeying the Bernoulli binary distribution law. To reduce the frequency of unnecessary data transmission and alleviate the communication burden, an event-triggered mechanism is introduced for the sensor node such that only some vitally important data is transmitted to its neighboring sensors when specific events occur. The objective of the problem addressed is to design a time-varying filter such that both the requirements and the variance constraints are guaranteed over a given finite-horizon against the random parameter matrices, successive missing measurements, and stochastic noises. By recurring to stochastic analysis techniques, sufficient conditions are established to ensure the existence of the time-varying filters whose gain matrices are then explicitly characterized in term of the solutions to a series of recursive matrix inequalities. A numerical simulation example is provided to illustrate the effectiveness of the developed event-triggered distributed filter design strategy.

  6. A class of systolizable IIR digital filters and its design for proper scaling and minimum output roundoff noise

    NASA Technical Reports Server (NTRS)

    Lei, Shaw-Min; Yao, Kung

    1990-01-01

    A class of infinite impulse response (IIR) digital filters with a systolizable structure is proposed and its synthesis is investigated. The systolizable structure consists of pipelineable regular modules with local connections and is suitable for VLSI implementation. It is capable of achieving high performance as well as high throughput. This class of filter structure provides certain degrees of freedom that can be used to obtain some desirable properties for the filter. Techniques of evaluating the internal signal powers and the output roundoff noise of the proposed filter structure are developed. Based upon these techniques, a well-scaled IIR digital filter with minimum output roundoff noise is designed using a local optimization approach. The internal signals of all the modes of this filter are scaled to unity in the l2-norm sense. Compared to the Rao-Kailath (1984) orthogonal digital filter and the Gray-Markel (1973) normalized-lattice digital filter, this filter has better scaling properties and lower output roundoff noise.

  7. Color filter array pattern identification using variance of color difference image

    NASA Astrophysics Data System (ADS)

    Shin, Hyun Jun; Jeon, Jong Ju; Eom, Il Kyu

    2017-07-01

    A color filter array is placed on the image sensor of a digital camera to acquire color images. Each pixel uses only one color, since the image sensor can measure only one color per pixel. Therefore, empty pixels are filled using an interpolation process called demosaicing. The original and the interpolated pixels have different statistical characteristics. If the image is modified by manipulation or forgery, the color filter array pattern is altered. This pattern change can be a clue for image forgery detection. However, most forgery detection algorithms have the disadvantage of assuming the color filter array pattern. We present an identification method of the color filter array pattern. Initially, the local mean is eliminated to remove the background effect. Subsequently, the color difference block is constructed to emphasize the difference between the original pixel and the interpolated pixel. The variance measure of the color difference image is proposed as a means of estimating the color filter array configuration. The experimental results show that the proposed method is effective in identifying the color filter array pattern. Compared with conventional methods, our method provides superior performance.

  8. Non-specific filtering of beta-distributed data.

    PubMed

    Wang, Xinhui; Laird, Peter W; Hinoue, Toshinori; Groshen, Susan; Siegmund, Kimberly D

    2014-06-19

    Non-specific feature selection is a dimension reduction procedure performed prior to cluster analysis of high dimensional molecular data. Not all measured features are expected to show biological variation, so only the most varying are selected for analysis. In DNA methylation studies, DNA methylation is measured as a proportion, bounded between 0 and 1, with variance a function of the mean. Filtering on standard deviation biases the selection of probes to those with mean values near 0.5. We explore the effect this has on clustering, and develop alternate filter methods that utilize a variance stabilizing transformation for Beta distributed data and do not share this bias. We compared results for 11 different non-specific filters on eight Infinium HumanMethylation data sets, selected to span a variety of biological conditions. We found that for data sets having a small fraction of samples showing abnormal methylation of a subset of normally unmethylated CpGs, a characteristic of the CpG island methylator phenotype in cancer, a novel filter statistic that utilized a variance-stabilizing transformation for Beta distributed data outperformed the common filter of using standard deviation of the DNA methylation proportion, or its log-transformed M-value, in its ability to detect the cancer subtype in a cluster analysis. However, the standard deviation filter always performed among the best for distinguishing subgroups of normal tissue. The novel filter and standard deviation filter tended to favour features in different genome contexts; for the same data set, the novel filter always selected more features from CpG island promoters and the standard deviation filter always selected more features from non-CpG island intergenic regions. Interestingly, despite selecting largely non-overlapping sets of features, the two filters did find sample subsets that overlapped for some real data sets. We found two different filter statistics that tended to prioritize features with different characteristics, each performed well for identifying clusters of cancer and non-cancer tissue, and identifying a cancer CpG island hypermethylation phenotype. Since cluster analysis is for discovery, we would suggest trying both filters on any new data sets, evaluating the overlap of features selected and clusters discovered.

  9. 42 CFR 84.1158 - Dust, fume, and mist tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 1 2014-10-01 2014-10-01 false Dust, fume, and mist tests; respirators with filters; minimum requirements; general. 84.1158 Section 84.1158 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES...

  10. 42 CFR 84.1158 - Dust, fume, and mist tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 1 2011-10-01 2011-10-01 false Dust, fume, and mist tests; respirators with filters; minimum requirements; general. 84.1158 Section 84.1158 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES...

  11. 42 CFR 84.1158 - Dust, fume, and mist tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Dust, fume, and mist tests; respirators with filters; minimum requirements; general. 84.1158 Section 84.1158 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES...

  12. 42 CFR 84.1158 - Dust, fume, and mist tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false Dust, fume, and mist tests; respirators with filters; minimum requirements; general. 84.1158 Section 84.1158 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES...

  13. 42 CFR 84.1158 - Dust, fume, and mist tests; respirators with filters; minimum requirements; general.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 1 2013-10-01 2013-10-01 false Dust, fume, and mist tests; respirators with filters; minimum requirements; general. 84.1158 Section 84.1158 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH AND RELATED ACTIVITIES...

  14. The Angular Power Spectrum of BATSE 3B Gamma-Ray Bursts

    NASA Technical Reports Server (NTRS)

    Tegmark, Max; Hartmann, Dieter H.; Briggs, Michael S.; Meegan, Charles A.

    1996-01-01

    We compute the angular power spectrum C(sub l) from the BATSE 3B catalog of 1122 gamma-ray bursts and find no evidence for clustering on any scale. These constraints bridge the entire range from small scales (which probe source clustering and burst repetition) to the largest scales (which constrain possible anisotropics from the Galactic halo or from nearby cosmological large-scale structures). We develop an analysis technique that takes the angular position errors into account. For specific clustering or repetition models, strong upper limits can be obtained down to scales l approx. equal to 30, corresponding to a couple of degrees on the sky. The minimum-variance burst weighting that we employ is visualized graphically as an all-sky map in which each burst is smeared out by an amount corresponding to its position uncertainty. We also present separate bandpass-filtered sky maps for the quadrupole term and for the multipole ranges l = 3-10 and l = 11-30, so that the fluctuations on different angular scales can be inspected separately for visual features such as localized 'hot spots' or structures aligned with the Galactic plane. These filtered maps reveal no apparent deviations from isotropy.

  15. Space Object Maneuver Detection Algorithms Using TLE Data

    NASA Astrophysics Data System (ADS)

    Pittelkau, M.

    2016-09-01

    An important aspect of Space Situational Awareness (SSA) is detection of deliberate and accidental orbit changes of space objects. Although space surveillance systems detect orbit maneuvers within their tracking algorithms, maneuver data are not readily disseminated for general use. However, two-line element (TLE) data is available and can be used to detect maneuvers of space objects. This work is an attempt to improve upon existing TLE-based maneuver detection algorithms. Three adaptive maneuver detection algorithms are developed and evaluated: The first is a fading-memory Kalman filter, which is equivalent to the sliding-window least-squares polynomial fit, but computationally more efficient and adaptive to the noise in the TLE data. The second algorithm is based on a sample cumulative distribution function (CDF) computed from a histogram of the magnitude-squared |V|2 of change-in-velocity vectors (V), which is computed from the TLE data. A maneuver detection threshold is computed from the median estimated from the CDF, or from the CDF and a specified probability of false alarm. The third algorithm is a median filter. The median filter is the simplest of a class of nonlinear filters called order statistics filters, which is within the theory of robust statistics. The output of the median filter is practically insensitive to outliers, or large maneuvers. The median of the |V|2 data is proportional to the variance of the V, so the variance is estimated from the output of the median filter. A maneuver is detected when the input data exceeds a constant times the estimated variance.

  16. Lidar inversion of atmospheric backscatter and extinction-to-backscatter ratios by use of a Kalman filter.

    PubMed

    Rocadenbosch, F; Soriano, C; Comerón, A; Baldasano, J M

    1999-05-20

    A first inversion of the backscatter profile and extinction-to-backscatter ratio from pulsed elastic-backscatter lidar returns is treated by means of an extended Kalman filter (EKF). The EKF approach enables one to overcome the intrinsic limitations of standard straightforward nonmemory procedures such as the slope method, exponential curve fitting, and the backward inversion algorithm. Whereas those procedures are inherently not adaptable because independent inversions are performed for each return signal and neither the statistics of the signals nor a priori uncertainties (e.g., boundary calibrations) are taken into account, in the case of the Kalman filter the filter updates itself because it is weighted by the imbalance between the a priori estimates of the optical parameters (i.e., past inversions) and the new estimates based on a minimum-variance criterion, as long as there are different lidar returns. Calibration errors and initialization uncertainties can be assimilated also. The study begins with the formulation of the inversion problem and an appropriate atmospheric stochastic model. Based on extensive simulation and realistic conditions, it is shown that the EKF approach enables one to retrieve the optical parameters as time-range-dependent functions and hence to track the atmospheric evolution; the performance of this approach is limited only by the quality and availability of the a priori information and the accuracy of the atmospheric model used. The study ends with an encouraging practical inversion of a live scene measured at the Nd:YAG elastic-backscatter lidar station at our premises at the Polytechnic University of Catalonia, Barcelona.

  17. Online Estimation of Allan Variance Coefficients Based on a Neural-Extended Kalman Filter

    PubMed Central

    Miao, Zhiyong; Shen, Feng; Xu, Dingjie; He, Kunpeng; Tian, Chunmiao

    2015-01-01

    As a noise analysis method for inertial sensors, the traditional Allan variance method requires the storage of a large amount of data and manual analysis for an Allan variance graph. Although the existing online estimation methods avoid the storage of data and the painful procedure of drawing slope lines for estimation, they require complex transformations and even cause errors during the modeling of dynamic Allan variance. To solve these problems, first, a new state-space model that directly models the stochastic errors to obtain a nonlinear state-space model was established for inertial sensors. Then, a neural-extended Kalman filter algorithm was used to estimate the Allan variance coefficients. The real noises of an ADIS16405 IMU and fiber optic gyro-sensors were analyzed by the proposed method and traditional methods. The experimental results show that the proposed method is more suitable to estimate the Allan variance coefficients than the traditional methods. Moreover, the proposed method effectively avoids the storage of data and can be easily implemented using an online processor. PMID:25625903

  18. Methodological Considerations When Quantifying High-Intensity Efforts in Team Sport Using Global Positioning System Technology.

    PubMed

    Varley, Matthew C; Jaspers, Arne; Helsen, Werner F; Malone, James J

    2017-09-01

    Sprints and accelerations are popular performance indicators in applied sport. The methods used to define these efforts using athlete-tracking technology could affect the number of efforts reported. This study aimed to determine the influence of different techniques and settings for detecting high-intensity efforts using global positioning system (GPS) data. Velocity and acceleration data from a professional soccer match were recorded via 10-Hz GPS. Velocity data were filtered using either a median or an exponential filter. Acceleration data were derived from velocity data over a 0.2-s time interval (with and without an exponential filter applied) and a 0.3-second time interval. High-speed-running (≥4.17 m/s 2 ), sprint (≥7.00 m/s 2 ), and acceleration (≥2.78 m/s 2 ) efforts were then identified using minimum-effort durations (0.1-0.9 s) to assess differences in the total number of efforts reported. Different velocity-filtering methods resulted in small to moderate differences (effect size [ES] 0.28-1.09) in the number of high-speed-running and sprint efforts detected when minimum duration was <0.5 s and small to very large differences (ES -5.69 to 0.26) in the number of accelerations when minimum duration was <0.7 s. There was an exponential decline in the number of all efforts as minimum duration increased, regardless of filtering method, with the largest declines in acceleration efforts. Filtering techniques and minimum durations substantially affect the number of high-speed-running, sprint, and acceleration efforts detected with GPS. Changes to how high-intensity efforts are defined affect reported data. Therefore, consistency in data processing is advised.

  19. 42 CFR 84.122 - Breathing resistance test; minimum requirements.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... Exhalation Front-mounted or back-mounted (without particulate filter) 60 75 20 Front-mounted or back-mounted (with approved particulate filter) 70 85 20 Chin-style (without particulate filter) 40 55 20 Chin-style (with approved particulate filter) 65 80 20 Escape (without particulate filter) 60 75 20 Escape (with...

  20. 42 CFR 84.122 - Breathing resistance test; minimum requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... Exhalation Front-mounted or back-mounted (without particulate filter) 60 75 20 Front-mounted or back-mounted (with approved particulate filter) 70 85 20 Chin-style (without particulate filter) 40 55 20 Chin-style (with approved particulate filter) 65 80 20 Escape (without particulate filter) 60 75 20 Escape (with...

  1. 42 CFR 84.122 - Breathing resistance test; minimum requirements.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... Exhalation Front-mounted or back-mounted (without particulate filter) 60 75 20 Front-mounted or back-mounted (with approved particulate filter) 70 85 20 Chin-style (without particulate filter) 40 55 20 Chin-style (with approved particulate filter) 65 80 20 Escape (without particulate filter) 60 75 20 Escape (with...

  2. 42 CFR 84.122 - Breathing resistance test; minimum requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... Exhalation Front-mounted or back-mounted (without particulate filter) 60 75 20 Front-mounted or back-mounted (with approved particulate filter) 70 85 20 Chin-style (without particulate filter) 40 55 20 Chin-style (with approved particulate filter) 65 80 20 Escape (without particulate filter) 60 75 20 Escape (with...

  3. 42 CFR 84.122 - Breathing resistance test; minimum requirements.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... Exhalation Front-mounted or back-mounted (without particulate filter) 60 75 20 Front-mounted or back-mounted (with approved particulate filter) 70 85 20 Chin-style (without particulate filter) 40 55 20 Chin-style (with approved particulate filter) 65 80 20 Escape (without particulate filter) 60 75 20 Escape (with...

  4. A tool for filtering information in complex systems

    NASA Astrophysics Data System (ADS)

    Tumminello, M.; Aste, T.; Di Matteo, T.; Mantegna, R. N.

    2005-07-01

    We introduce a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0), triangular loops and four-element cliques are formed. The application of this filtering procedure to 100 stocks in the U.S. equity markets shows that such loops and cliques have important and significant relationships with the market structure and properties. This paper was submitted directly (Track II) to the PNAS office.Abbreviations: MST, minimum spanning tree; PMFG, Planar Maximally Filtered Graph; r-clique, clique of r elements.

  5. Conversion and matched filter approximations for serial minimum-shift keyed modulation

    NASA Technical Reports Server (NTRS)

    Ziemer, R. E.; Ryan, C. R.; Stilwell, J. H.

    1982-01-01

    Serial minimum-shift keyed (MSK) modulation, a technique for generating and detecting MSK using series filtering, is ideally suited for high data rate applications provided the required conversion and matched filters can be closely approximated. Low-pass implementations of these filters as parallel inphase- and quadrature-mixer structures are characterized in this paper in terms of signal-to-noise ratio (SNR) degradation from ideal and envelope deviation. Several hardware implementation techniques utilizing microwave devices or lumped elements are presented. Optimization of parameter values results in realizations whose SNR degradation is less than 0.5 dB at error probabilities of .000001.

  6. Microprocessor realizations of range rate filters

    NASA Technical Reports Server (NTRS)

    1979-01-01

    The performance of five digital range rate filters is evaluated. A range rate filter receives an input of range data from a radar unit and produces an output of smoothed range data and its estimated derivative range rate. The filters are compared through simulation on an IBM 370. Two of the filter designs are implemented on a 6800 microprocessor-based system. Comparisons are made on the bases of noise variance reduction ratios and convergence times of the filters in response to simulated range signals.

  7. 42 CFR 84.1144 - Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum...

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 42 Public Health 1 2014-10-01 2014-10-01 false Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum requirements. 84.1144 Section 84.1144 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH...

  8. 42 CFR 84.1144 - Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 42 Public Health 1 2011-10-01 2011-10-01 false Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum requirements. 84.1144 Section 84.1144 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH...

  9. 42 CFR 84.1144 - Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum...

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 42 Public Health 1 2010-10-01 2010-10-01 false Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum requirements. 84.1144 Section 84.1144 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH...

  10. 42 CFR 84.1144 - Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum...

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 42 Public Health 1 2013-10-01 2013-10-01 false Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum requirements. 84.1144 Section 84.1144 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH...

  11. 42 CFR 84.1144 - Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum...

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false Silica dust test for dust, fume, and mist respirators; single-use or reusable filters; minimum requirements. 84.1144 Section 84.1144 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES OCCUPATIONAL SAFETY AND HEALTH RESEARCH...

  12. Wavelets, ridgelets, and curvelets for Poisson noise removal.

    PubMed

    Zhang, Bo; Fadili, Jalal M; Starck, Jean-Luc

    2008-07-01

    In order to denoise Poisson count data, we introduce a variance stabilizing transform (VST) applied on a filtered discrete Poisson process, yielding a near Gaussian process with asymptotic constant variance. This new transform, which can be deemed as an extension of the Anscombe transform to filtered data, is simple, fast, and efficient in (very) low-count situations. We combine this VST with the filter banks of wavelets, ridgelets and curvelets, leading to multiscale VSTs (MS-VSTs) and nonlinear decomposition schemes. By doing so, the noise-contaminated coefficients of these MS-VST-modified transforms are asymptotically normally distributed with known variances. A classical hypothesis-testing framework is adopted to detect the significant coefficients, and a sparsity-driven iterative scheme reconstructs properly the final estimate. A range of examples show the power of this MS-VST approach for recovering important structures of various morphologies in (very) low-count images. These results also demonstrate that the MS-VST approach is competitive relative to many existing denoising methods.

  13. Impact of functional MRI data preprocessing pipeline on default-mode network detectability in patients with disorders of consciousness.

    PubMed

    Andronache, Adrian; Rosazza, Cristina; Sattin, Davide; Leonardi, Matilde; D'Incerti, Ludovico; Minati, Ludovico

    2013-01-01

    An emerging application of resting-state functional MRI (rs-fMRI) is the study of patients with disorders of consciousness (DoC), where integrity of default-mode network (DMN) activity is associated to the clinical level of preservation of consciousness. Due to the inherent inability to follow verbal instructions, arousal induced by scanning noise and postural pain, these patients tend to exhibit substantial levels of movement. This results in spurious, non-neural fluctuations of the rs-fMRI signal, which impair the evaluation of residual functional connectivity. Here, the effect of data preprocessing choices on the detectability of the DMN was systematically evaluated in a representative cohort of 30 clinically and etiologically heterogeneous DoC patients and 33 healthy controls. Starting from a standard preprocessing pipeline, additional steps were gradually inserted, namely band-pass filtering (BPF), removal of co-variance with the movement vectors, removal of co-variance with the global brain parenchyma signal, rejection of realignment outlier volumes and ventricle masking. Both independent-component analysis (ICA) and seed-based analysis (SBA) were performed, and DMN detectability was assessed quantitatively as well as visually. The results of the present study strongly show that the detection of DMN activity in the sub-optimal fMRI series acquired on DoC patients is contingent on the use of adequate filtering steps. ICA and SBA are differently affected but give convergent findings for high-grade preprocessing. We propose that future studies in this area should adopt the described preprocessing procedures as a minimum standard to reduce the probability of wrongly inferring that DMN activity is absent.

  14. Minimum entropy deconvolution optimized sinusoidal synthesis and its application to vibration based fault detection

    NASA Astrophysics Data System (ADS)

    Li, Gang; Zhao, Qing

    2017-03-01

    In this paper, a minimum entropy deconvolution based sinusoidal synthesis (MEDSS) filter is proposed to improve the fault detection performance of the regular sinusoidal synthesis (SS) method. The SS filter is an efficient linear predictor that exploits the frequency properties during model construction. The phase information of the harmonic components is not used in the regular SS filter. However, the phase relationships are important in differentiating noise from characteristic impulsive fault signatures. Therefore, in this work, the minimum entropy deconvolution (MED) technique is used to optimize the SS filter during the model construction process. A time-weighted-error Kalman filter is used to estimate the MEDSS model parameters adaptively. Three simulation examples and a practical application case study are provided to illustrate the effectiveness of the proposed method. The regular SS method and the autoregressive MED (ARMED) method are also implemented for comparison. The MEDSS model has demonstrated superior performance compared to the regular SS method and it also shows comparable or better performance with much less computational intensity than the ARMED method.

  15. Distributed Monte Carlo Information Fusion and Distributed Particle Filtering

    DTIC Science & Technology

    2014-08-24

    Distributed Monte Carlo Information Fusion and Distributed Particle Filtering Isaac L. Manuel and Adrian N. Bishop Australian National University and...2 20 + vit , (21) where vit is Gaussian white noise with a random variance. We initialised the filters with the state xi0 = 0.1 for all i ∈ V . This

  16. Central Auditory Processing of Temporal and Spectral-Variance Cues in Cochlear Implant Listeners

    PubMed Central

    Pham, Carol Q.; Bremen, Peter; Shen, Weidong; Yang, Shi-Ming; Middlebrooks, John C.; Zeng, Fan-Gang; Mc Laughlin, Myles

    2015-01-01

    Cochlear implant (CI) listeners have difficulty understanding speech in complex listening environments. This deficit is thought to be largely due to peripheral encoding problems arising from current spread, which results in wide peripheral filters. In normal hearing (NH) listeners, central processing contributes to segregation of speech from competing sounds. We tested the hypothesis that basic central processing abilities are retained in post-lingually deaf CI listeners, but processing is hampered by degraded input from the periphery. In eight CI listeners, we measured auditory nerve compound action potentials to characterize peripheral filters. Then, we measured psychophysical detection thresholds in the presence of multi-electrode maskers placed either inside (peripheral masking) or outside (central masking) the peripheral filter. This was intended to distinguish peripheral from central contributions to signal detection. Introduction of temporal asynchrony between the signal and masker improved signal detection in both peripheral and central masking conditions for all CI listeners. Randomly varying components of the masker created spectral-variance cues, which seemed to benefit only two out of eight CI listeners. Contrastingly, the spectral-variance cues improved signal detection in all five NH listeners who listened to our CI simulation. Together these results indicate that widened peripheral filters significantly hamper central processing of spectral-variance cues but not of temporal cues in post-lingually deaf CI listeners. As indicated by two CI listeners in our study, however, post-lingually deaf CI listeners may retain some central processing abilities similar to NH listeners. PMID:26176553

  17. Relating the Hadamard Variance to MCS Kalman Filter Clock Estimation

    NASA Technical Reports Server (NTRS)

    Hutsell, Steven T.

    1996-01-01

    The Global Positioning System (GPS) Master Control Station (MCS) currently makes significant use of the Allan Variance. This two-sample variance equation has proven excellent as a handy, understandable tool, both for time domain analysis of GPS cesium frequency standards, and for fine tuning the MCS's state estimation of these atomic clocks. The Allan Variance does not explicitly converge for the nose types of alpha less than or equal to minus 3 and can be greatly affected by frequency drift. Because GPS rubidium frequency standards exhibit non-trivial aging and aging noise characteristics, the basic Allan Variance analysis must be augmented in order to (a) compensate for a dynamic frequency drift, and (b) characterize two additional noise types, specifically alpha = minus 3, and alpha = minus 4. As the GPS program progresses, we will utilize a larger percentage of rubidium frequency standards than ever before. Hence, GPS rubidium clock characterization will require more attention than ever before. The three sample variance, commonly referred to as a renormalized Hadamard Variance, is unaffected by linear frequency drift, converges for alpha is greater than minus 5, and thus has utility for modeling noise in GPS rubidium frequency standards. This paper demonstrates the potential of Hadamard Variance analysis in GPS operations, and presents an equation that relates the Hadamard Variance to the MCS's Kalman filter process noises.

  18. 40 CFR 89.109 - Maintenance instructions and minimum allowable maintenance intervals.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... change, oil filter change, fuel filter change, air filter change, cooling system maintenance, adjustment... AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE NONROAD COMPRESSION...) Exhaust gas recirculation system-related filters and coolers. (ii) Positive crankcase ventilation valve...

  19. 40 CFR 89.109 - Maintenance instructions and minimum allowable maintenance intervals.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... change, oil filter change, fuel filter change, air filter change, cooling system maintenance, adjustment... AGENCY (CONTINUED) AIR PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE NONROAD COMPRESSION...) Exhaust gas recirculation system-related filters and coolers. (ii) Positive crankcase ventilation valve...

  20. Superresolution SAR Imaging Algorithm Based on Mvm and Weighted Norm Extrapolation

    NASA Astrophysics Data System (ADS)

    Zhang, P.; Chen, Q.; Li, Z.; Tang, Z.; Liu, J.; Zhao, L.

    2013-08-01

    In this paper, we present an extrapolation approach, which uses minimum weighted norm constraint and minimum variance spectrum estimation, for improving synthetic aperture radar (SAR) resolution. Minimum variance method is a robust high resolution method to estimate spectrum. Based on the theory of SAR imaging, the signal model of SAR imagery is analyzed to be feasible for using data extrapolation methods to improve the resolution of SAR image. The method is used to extrapolate the efficient bandwidth in phase history field and better results are obtained compared with adaptive weighted norm extrapolation (AWNE) method and traditional imaging method using simulated data and actual measured data.

  1. 40 CFR Table 3 to Subpart Ec of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... Which Construction is Commenced After June 20, 1996 Pt. 60, Subpt. Ec, Table 3 Table 3 to Subpart Ec of... Operating parameters to be monitored Minimum frequency Data measurement Data recording Control system Dry scrubber followed by fabric filter Wet scrubber Dry scrubber followed by fabric filter and wet scrubber...

  2. 40 CFR Table 3 to Subpart Hhh of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... rural HMIWI HMIWI a with dry scrubber followed by fabric filter HMIWI a with wet scrubber HMIWI a with dry scrubber followed by fabric filter and wet scrubber Maximum operating parameters: Maximum charge... mercury (Hg) sorbent flow rate Hourly Once per hour ✔ ✔ Minimum pressure drop across the wet scrubber or...

  3. Adaptive feedforward control of non-minimum phase structural systems

    NASA Astrophysics Data System (ADS)

    Vipperman, J. S.; Burdisso, R. A.

    1995-06-01

    Adaptive feedforward control algorithms have been effectively applied to stationary disturbance rejection. For structural systems, the ideal feedforward compensator is a recursive filter which is a function of the transfer functions between the disturbance and control inputs and the error sensor output. Unfortunately, most control configurations result in a non-minimum phase control path; even a collocated control actuator and error sensor will not necessarily produce a minimum phase control path in the discrete domain. Therefore, the common practice is to choose a suitable approximation of the ideal compensator. In particular, all-zero finite impulse response (FIR) filters are desirable because of their inherent stability for adaptive control approaches. However, for highly resonant systems, large order filters are required for broadband applications. In this work, a control configuration is investigated for controlling non-minimum phase lightly damped structural systems. The control approach uses low order FIR filters as feedforward compensators in a configuration that has one more control actuator than error sensors. The performance of the controller was experimentally evaluated on a simply supported plate under white noise excitation for a two-input, one-output (2I1O) system. The results show excellent error signal reduction, attesting to the effectiveness of the method.

  4. A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

    PubMed Central

    Qu, Jianfeng; Chai, Yi; Yang, Simon X.

    2009-01-01

    A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. PMID:22399946

  5. High exhaust temperature, zoned, electrically-heated particulate matter filter

    DOEpatents

    Gonze, Eugene V.; Paratore, Jr., Michael J.; Bhatia, Garima

    2015-09-22

    A system includes a particulate matter (PM) filter, an electric heater, and a control circuit. The electric heater includes multiple zones, which each correspond to longitudinal zones along a length of the PM filter. A first zone includes multiple discontinuous sub-zones. The control circuit determines whether regeneration is needed based on an estimated level of loading of the PM filter and an exhaust flow rate. In response to a determination that regeneration is needed, the control circuit: controls an operating parameter of an engine to increase an exhaust temperature to a first temperature during a first period; after the first period, activates the first zone; deactivates the first zone in response to a minimum filter face temperature being reached; subsequent to deactivating the first zone, activates a second zone; and deactivates the second zone in response to the minimum filter face temperature being reached.

  6. Inversion of atmospheric optical parameters from elastic-backscatter lidar returns using a Kalman filter

    NASA Astrophysics Data System (ADS)

    Rocadenbosch, Francesc; Comeron, Adolfo; Vazquez, Gregori; Rodriguez-Gomez, Alejandro; Soriano, Cecilia; Baldasano, Jose M.

    1998-12-01

    Up to now, retrieval of the atmospheric extinction and backscatter has mainly relied on standard straightforward non-memory procedures such as slope-method, exponential- curve fitting and Klett's method. Yet, their performance becomes ultimately limited by the inherent lack of adaptability as they only work with present returns and neither past estimations, nor the statistics of the signals or a prior uncertainties are taken into account. In this work, a first inversion of the backscatter and extinction- to-backscatter ratio from pulsed elastic-backscatter lidar returns is tackled by means of an extended Kalman filter (EKF), which overcomes these limitations. Thus, as long as different return signals income,the filter updates itself weighted by the unbalance between the a priori estimates of the optical parameters and the new ones based on a minimum variance criterion. Calibration errors or initialization uncertainties can be assimilated also. The study begins with the formulation of the inversion problem and an appropriate stochastic model. Based on extensive simulation and realistic conditions, it is shown that the EKF approach enables to retrieve the sought-after optical parameters as time-range-dependent functions and hence, to track the atmospheric evolution, its performance being only limited by the quality and availability of the 'a priori' information and the accuracy of the atmospheric model assumed. The study ends with an encouraging practical inversion of a live-scene measured with the Nd:YAG elastic-backscatter lidar station at our premises in Barcelona.

  7. An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

    NASA Astrophysics Data System (ADS)

    Liu, Yahui; Fan, Xiaoqian; Lv, Chen; Wu, Jian; Li, Liang; Ding, Dawei

    2018-02-01

    Information fusion method of INS/GPS navigation system based on filtering technology is a research focus at present. In order to improve the precision of navigation information, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in this paper. The algorithm continuously updates the measurement noise variance and processes noise variance of the system by collecting the estimated and measured values, and this method can suppress white noise. Because a measured value closer to the current time would more accurately reflect the characteristics of the noise, an attenuation factor is introduced to increase the weight of the current value, in order to deal with the noise variance caused by environment disturbance. To validate the effectiveness of the proposed algorithm, a series of road tests are carried out in urban environment. The GPS and IMU data of the experiments were collected and processed by dSPACE and MATLAB/Simulink. Based on the test results, the accuracy of the proposed algorithm is 20% higher than that of a traditional Adaptive Kalman Filter. It also shows that the precision of the integrated navigation can be improved due to the reduction of the influence of environment noise.

  8. A comparison of maximum likelihood and other estimators of eigenvalues from several correlated Monte Carlo samples

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Beer, M.

    1980-12-01

    The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that themore » use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates.« less

  9. EPA Method 1615. Measurement of Enterovirus and Norovirus Occurrence in Water by Culture and RT-qPCR. I. Collection of Virus Samples

    PubMed Central

    Fout, G. Shay; Cashdollar, Jennifer L.; Varughese, Eunice A.; Parshionikar, Sandhya U.; Grimm, Ann C.

    2015-01-01

    EPA Method 1615 was developed with a goal of providing a standard method for measuring enteroviruses and noroviruses in environmental and drinking waters. The standardized sampling component of the method concentrates viruses that may be present in water by passage of a minimum specified volume of water through an electropositive cartridge filter. The minimum specified volumes for surface and finished/ground water are 300 L and 1,500 L, respectively. A major method limitation is the tendency for the filters to clog before meeting the sample volume requirement. Studies using two different, but equivalent, cartridge filter options showed that filter clogging was a problem with 10% of the samples with one of the filter types compared to 6% with the other filter type. Clogging tends to increase with turbidity, but cannot be predicted based on turbidity measurements only. From a cost standpoint one of the filter options is preferable over the other, but the water quality and experience with the water system to be sampled should be taken into consideration in making filter selections. PMID:25867928

  10. Applications of active adaptive noise control to jet engines

    NASA Technical Reports Server (NTRS)

    Shoureshi, Rahmat; Brackney, Larry

    1993-01-01

    During phase 2 research on the application of active noise control to jet engines, the development of multiple-input/multiple-output (MIMO) active adaptive noise control algorithms and acoustic/controls models for turbofan engines were considered. Specific goals for this research phase included: (1) implementation of a MIMO adaptive minimum variance active noise controller; and (2) turbofan engine model development. A minimum variance control law for adaptive active noise control has been developed, simulated, and implemented for single-input/single-output (SISO) systems. Since acoustic systems tend to be distributed, multiple sensors, and actuators are more appropriate. As such, the SISO minimum variance controller was extended to the MIMO case. Simulation and experimental results are presented. A state-space model of a simplified gas turbine engine is developed using the bond graph technique. The model retains important system behavior, yet is of low enough order to be useful for controller design. Expansion of the model to include multiple stages and spools is also discussed.

  11. Large amplitude MHD waves upstream of the Jovian bow shock

    NASA Technical Reports Server (NTRS)

    Goldstein, M. L.; Smith, C. W.; Matthaeus, W. H.

    1983-01-01

    Observations of large amplitude magnetohydrodynamics (MHD) waves upstream of Jupiter's bow shock are analyzed. The waves are found to be right circularly polarized in the solar wind frame which suggests that they are propagating in the fast magnetosonic mode. A complete spectral and minimum variance eigenvalue analysis of the data was performed. The power spectrum of the magnetic fluctuations contains several peaks. The fluctuations at 2.3 mHz have a direction of minimum variance along the direction of the average magnetic field. The direction of minimum variance of these fluctuations lies at approximately 40 deg. to the magnetic field and is parallel to the radial direction. We argue that these fluctuations are waves excited by protons reflected off the Jovian bow shock. The inferred speed of the reflected protons is about two times the solar wind speed in the plasma rest frame. A linear instability analysis is presented which suggests an explanation for many of the observed features of the observations.

  12. An improved state-parameter analysis of ecosystem models using data assimilation

    USGS Publications Warehouse

    Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

    2008-01-01

    Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the simultaneous parameter estimation procedure significantly improves model predictions. Results also show that the SEnKF can dramatically reduce the variance in state variables stemming from the uncertainty of parameters and driving variables. The SEnKF is a robust and effective algorithm in evaluating and developing ecosystem models and in improving the understanding and quantification of carbon cycle parameters and processes. ?? 2008 Elsevier B.V.

  13. Application of adaptive Kalman filter in vehicle laser Doppler velocimetry

    NASA Astrophysics Data System (ADS)

    Fan, Zhe; Sun, Qiao; Du, Lei; Bai, Jie; Liu, Jingyun

    2018-03-01

    Due to the variation of road conditions and motor characteristics of vehicle, great root-mean-square (rms) error and outliers would be caused. Application of Kalman filter in laser Doppler velocimetry(LDV) is important to improve the velocity measurement accuracy. In this paper, the state-space model is built by using current statistical model. A strategy containing two steps is adopted to make the filter adaptive and robust. First, the acceleration variance is adaptively adjusted by using the difference of predictive observation and measured observation. Second, the outliers would be identified and the measured noise variance would be adjusted according to the orthogonal property of innovation to reduce the impaction of outliers. The laboratory rotating table experiments show that adaptive Kalman filter greatly reduces the rms error from 0.59 cm/s to 0.22 cm/s and has eliminated all the outliers. Road experiments compared with a microwave radar show that the rms error of LDV is 0.0218 m/s, and it proves that the adaptive Kalman filtering is suitable for vehicle speed signal processing.

  14. Exploring homogeneity of correlation structures of gene expression datasets within and between etiological disease categories.

    PubMed

    Jong, Victor L; Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

    2014-12-01

    The literature shows that classifiers perform differently across datasets and that correlations within datasets affect the performance of classifiers. The question that arises is whether the correlation structure within datasets differ significantly across diseases. In this study, we evaluated the homogeneity of correlation structures within and between datasets of six etiological disease categories; inflammatory, immune, infectious, degenerative, hereditary and acute myeloid leukemia (AML). We also assessed the effect of filtering; detection call and variance filtering on correlation structures. We downloaded microarray datasets from ArrayExpress for experiments meeting predefined criteria and ended up with 12 datasets for non-cancerous diseases and six for AML. The datasets were preprocessed by a common procedure incorporating platform-specific recommendations and the two filtering methods mentioned above. Homogeneity of correlation matrices between and within datasets of etiological diseases was assessed using the Box's M statistic on permuted samples. We found that correlation structures significantly differ between datasets of the same and/or different etiological disease categories and that variance filtering eliminates more uncorrelated probesets than detection call filtering and thus renders the data highly correlated.

  15. Robust Lee local statistic filter for removal of mixed multiplicative and impulse noise

    NASA Astrophysics Data System (ADS)

    Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Egiazarian, Karen O.; Astola, Jaakko T.

    2004-05-01

    A robust version of Lee local statistic filter able to effectively suppress the mixed multiplicative and impulse noise in images is proposed. The performance of the proposed modification is studied for a set of test images, several values of multiplicative noise variance, Gaussian and Rayleigh probability density functions of speckle, and different characteris-tics of impulse noise. The advantages of the designed filter in comparison to the conventional Lee local statistic filter and some other filters able to cope with mixed multiplicative+impulse noise are demonstrated.

  16. Modeling Multiplicative Error Variance: An Example Predicting Tree Diameter from Stump Dimensions in Baldcypress

    Treesearch

    Bernard R. Parresol

    1993-01-01

    In the context of forest modeling, it is often reasonable to assume a multiplicative heteroscedastic error structure to the data. Under such circumstances ordinary least squares no longer provides minimum variance estimates of the model parameters. Through study of the error structure, a suitable error variance model can be specified and its parameters estimated. This...

  17. 40 CFR Table 3 to Subpart Ec of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... filter Wet scrubber Dry scrubber followed by fabric filter and wet scrubber Maximum operating parameters: Maximum charge rate Continuous 1×hour ✔ ✔ ✔ Maximum fabric filter inlet temperature Continuous 1×minute...

  18. 40 CFR Table 3 to Subpart Ec of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... filter Wet scrubber Dry scrubber followed by fabric filter and wet scrubber Maximum operating parameters: Maximum charge rate Continuous 1×hour ✔ ✔ ✔ Maximum fabric filter inlet temperature Continuous 1×minute...

  19. Methods for the preparation and analysis of solids and suspended solids for methylmercury

    USGS Publications Warehouse

    DeWild, John F.; Olund, Shane D.; Olson, Mark L.; Tate, Michael T.

    2004-01-01

    This report presents the methods and method performance data for the determination of methylmercury concentrations in solids and suspended solids. Using the methods outlined here, the U.S. Geological Survey's Wisconsin District Mercury Laboratory can consistently detect methylmercury in solids and suspended solids at environmentally relevant concentrations. Solids can be analyzed wet or freeze dried with a minimum detection limit of 0.08 ng/g (as-processed). Suspended solids must first be isolated from aqueous matrices by filtration. The minimum detection limit for suspended solids is 0.01 ng per filter resulting in a minimum reporting limit ranging from 0.2 ng/L for a 0.05 L filtered volume to 0.01 ng/L for a 1.0 L filtered volume. Maximum concentrations for both matrices can be extended to cover nearly any amount of methylmercury by limiting sample size.

  20. Use of switched capacitor filters to implement the discrete wavelet transform

    NASA Technical Reports Server (NTRS)

    Kaiser, Kraig E.; Peterson, James N.

    1993-01-01

    This paper analyzes the use of IIR switched capacitor filters to implement the discrete wavelet transform and the inverse transform, using quadrature mirror filters (QMF) which have the necessary symmetry for reconstruction of the data. This is done by examining the sensitivity of the QMF transforms to the manufacturing variance in the desired capacitances. The performance is evaluated at the outputs of the separate filter stages and the error in the reconstruction of the inverse transform is compared with the desired results.

  1. Flight data identification of six degree-of-freedom stability and control derivatives of a large crane type helicopter

    NASA Technical Reports Server (NTRS)

    Tomaine, R. L.

    1976-01-01

    Flight test data from a large 'crane' type helicopter were collected and processed for the purpose of identifying vehicle rigid body stability and control derivatives. The process consisted of using digital and Kalman filtering techniques for state estimation and Extended Kalman filtering for parameter identification, utilizing a least squares algorithm for initial derivative and variance estimates. Data were processed for indicated airspeeds from 0 m/sec to 152 m/sec. Pulse, doublet and step control inputs were investigated. Digital filter frequency did not have a major effect on the identification process, while the initial derivative estimates and the estimated variances had an appreciable effect on many derivative estimates. The major derivatives identified agreed fairly well with analytical predictions and engineering experience. Doublet control inputs provided better results than pulse or step inputs.

  2. Impulsive noise suppression in color images based on the geodesic digital paths

    NASA Astrophysics Data System (ADS)

    Smolka, Bogdan; Cyganek, Boguslaw

    2015-02-01

    In the paper a novel filtering design based on the concept of exploration of the pixel neighborhood by digital paths is presented. The paths start from the boundary of a filtering window and reach its center. The cost of transitions between adjacent pixels is defined in the hybrid spatial-color space. Then, an optimal path of minimum total cost, leading from pixels of the window's boundary to its center is determined. The cost of an optimal path serves as a degree of similarity of the central pixel to the samples from the local processing window. If a pixel is an outlier, then all the paths starting from the window's boundary will have high costs and the minimum one will also be high. The filter output is calculated as a weighted mean of the central pixel and an estimate constructed using the information on the minimum cost assigned to each image pixel. So, first the costs of optimal paths are used to build a smoothed image and in the second step the minimum cost of the central pixel is utilized for construction of the weights of a soft-switching scheme. The experiments performed on a set of standard color images, revealed that the efficiency of the proposed algorithm is superior to the state-of-the-art filtering techniques in terms of the objective restoration quality measures, especially for high noise contamination ratios. The proposed filter, due to its low computational complexity, can be applied for real time image denoising and also for the enhancement of video streams.

  3. Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

    PubMed

    Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

    2017-05-31

    Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

  4. Accuracy of the Estimated Core Temperature (ECTemp) Algorithm in Estimating Circadian Rhythm Indicators

    DTIC Science & Technology

    2017-04-12

    measurement of CT outside of stringent laboratory environments. This study evaluated ECTempTM, a heart rate-based extended Kalman Filter CT...based CT-estimation algorithms [7, 13, 14]. One notable example is ECTempTM, which utilizes an extended Kalman Filter to estimate CT from...3. The extended Kalman filter mapping function variance coefficient (Ct) was computed using the following equation: = −9.1428 ×

  5. Longitudinal Factor Score Estimation Using the Kalman Filter.

    ERIC Educational Resources Information Center

    Oud, Johan H.; And Others

    1990-01-01

    How longitudinal factor score estimation--the estimation of the evolution of factor scores for individual examinees over time--can profit from the Kalman filter technique is described. The Kalman estimates change more cautiously over time, have lower estimation error variances, and reproduce the LISREL program latent state correlations more…

  6. A residual based adaptive unscented Kalman filter for fault recovery in attitude determination system of microsatellites

    NASA Astrophysics Data System (ADS)

    Le, Huy Xuan; Matunaga, Saburo

    2014-12-01

    This paper presents an adaptive unscented Kalman filter (AUKF) to recover the satellite attitude in a fault detection and diagnosis (FDD) subsystem of microsatellites. The FDD subsystem includes a filter and an estimator with residual generators, hypothesis tests for fault detections and a reference logic table for fault isolations and fault recovery. The recovery process is based on the monitoring of mean and variance values of each attitude sensor behaviors from residual vectors. In the case of normal work, the residual vectors should be in the form of Gaussian white noise with zero mean and fixed variance. When the hypothesis tests for the residual vectors detect something unusual by comparing the mean and variance values with dynamic thresholds, the AUKF with real-time updated measurement noise covariance matrix will be used to recover the sensor faults. The scheme developed in this paper resolves the problem of the heavy and complex calculations during residual generations and therefore the delay in the isolation process is reduced. The numerical simulations for TSUBAME, a demonstration microsatellite of Tokyo Institute of Technology, are conducted and analyzed to demonstrate the working of the AUKF and FDD subsystem.

  7. Damping Effect of an Unsaturated-Saturated System on Tempospatial Variations of Pressure Head and Specific Flux

    NASA Astrophysics Data System (ADS)

    Yang, C.; Zhang, Y. K.; Liang, X.

    2014-12-01

    Damping effect of an unsaturated-saturated system on tempospatialvariations of pressurehead and specificflux was investigated. The variance and covariance of both pressure head and specific flux in such a system due to a white noise infiltration were obtained by solving the moment equations of water flow in the system and verified with Monte Carlo simulations. It was found that both the pressure head and specific flux in this case are temporally non-stationary. The variance is zero at early time due to a deterministic initial condition used, then increases with time, and approaches anasymptotic limit at late time.Both pressure head and specific flux arealso non-stationary in space since the variance decreases from source to sink. The unsaturated-saturated systembehavesasa noise filterand it damps both the pressure head and specific flux, i.e., reduces their variations and enhances their correlation. The effect is stronger in upper unsaturated zone than in lower unsaturated zone and saturated zone. As a noise filter, the unsaturated-saturated system is mainly a low pass filter, filtering out the high frequency components in the time series of hydrological variables. The damping effect is much stronger in the saturated zone than in the saturated zone.

  8. Developing a denoising filter for electron microscopy and tomography data in the cloud.

    PubMed

    Starosolski, Zbigniew; Szczepanski, Marek; Wahle, Manuel; Rusu, Mirabela; Wriggers, Willy

    2012-09-01

    The low radiation conditions and the predominantly phase-object image formation of cryo-electron microscopy (cryo-EM) result in extremely high noise levels and low contrast in the recorded micrographs. The process of single particle or tomographic 3D reconstruction does not completely eliminate this noise and is even capable of introducing new sources of noise during alignment or when correcting for instrument parameters. The recently developed Digital Paths Supervised Variance (DPSV) denoising filter uses local variance information to control regional noise in a robust and adaptive manner. The performance of the DPSV filter was evaluated in this review qualitatively and quantitatively using simulated and experimental data from cryo-EM and tomography in two and three dimensions. We also assessed the benefit of filtering experimental reconstructions for visualization purposes and for enhancing the accuracy of feature detection. The DPSV filter eliminates high-frequency noise artifacts (density gaps), which would normally preclude the accurate segmentation of tomography reconstructions or the detection of alpha-helices in single-particle reconstructions. This collaborative software development project was carried out entirely by virtual interactions among the authors using publicly available development and file sharing tools.

  9. Analysis of 20 magnetic clouds at 1 AU during a solar minimum

    NASA Astrophysics Data System (ADS)

    Gulisano, A. M.; Dasso, S.; Mandrini, C. H.; Démoulin, P.

    We study 20 magnetic clouds, observed in situ by the spacecraft Wind, at the Lagrangian point L1, from 22 August, 1995, to 7 November, 1997. In previous works, assuming a cylindrical symmetry for the local magnetic configuration and a satellite trajectory crossing the axis of the cloud, we obtained their orientations using a minimum variance analysis. In this work we compute the orientations and magnetic configurations using a non-linear simultaneous fit of the geometric and physical parameters for a linear force-free model, including the possibility of a not null impact parameter. We quantify global magnitudes such as the relative magnetic helicity per unit length and compare the values found with both methods (minimum variance and the simultaneous fit). FULL TEXT IN SPANISH

  10. Estimation of transformation parameters for microarray data.

    PubMed

    Durbin, Blythe; Rocke, David M

    2003-07-22

    Durbin et al. (2002), Huber et al. (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency. R and Matlab code and test data are available from the authors on request.

  11. Practical implementation of channelized hotelling observers: effect of ROI size

    NASA Astrophysics Data System (ADS)

    Ferrero, Andrea; Favazza, Christopher P.; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

    2017-03-01

    Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

  12. Practical implementation of Channelized Hotelling Observers: Effect of ROI size.

    PubMed

    Ferrero, Andrea; Favazza, Christopher P; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H

    2017-03-01

    Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

  13. Doppler color imaging. Principles and instrumentation.

    PubMed

    Kremkau, F W

    1992-01-01

    DCI acquires Doppler-shifted echoes from a cross-section of tissue scanned by an ultrasound beam. These echoes are then presented in color and superimposed on the gray-scale anatomic image of non-Doppler-shifted echoes received during the scan. The flow echoes are assigned colors according to the color map chosen. Usually red, yellow, or white indicates positive Doppler shifts (approaching flow) and blue, cyan, or white indicates negative shifts (receding flow). Green is added to indicate variance (disturbed or turbulent flow). Several pulses (the number is called the ensemble length) are needed to generate a color scan line. Linear, convex, phased, and annular arrays are used to acquire the gray-scale and color-flow information. Doppler color-flow instruments are pulsed-Doppler instruments and are subject to the same limitations, such as Doppler angle dependence and aliasing, as other Doppler instruments. Color controls include gain, TGC, map selection, variance on/off, persistence, ensemble length, color/gray priority. Nyquist limit (PRF), baseline shift, wall filter, and color window angle, location, and size. Doppler color-flow instruments generally have output intensities intermediate between those of gray-scale imaging and pulsed-Doppler duplex instruments. Although there is no known risk with the use of color-flow instruments, prudent practice dictates that they be used for medical indications and with the minimum exposure time and instrument output required to obtain the needed diagnostic information.

  14. The discrete prolate spheroidal filter as a digital signal processing tool

    NASA Technical Reports Server (NTRS)

    Mathews, J. D.; Breakall, J. K.; Karawas, G. K.

    1983-01-01

    The discrete prolate spheriodall (DPS) filter is one of the glass of nonrecursive finite impulse response (FIR) filters. The DPS filter is superior to other filters in this class in that it has maximum energy concentration in the frequency passband and minimum ringing in the time domain. A mathematical development of the DPS filter properties is given, along with information required to construct the filter. The properties of this filter were compared with those of the more commonly used filters of the same class. Use of the DPS filter allows for particularly meaningful statements of data time/frequency resolution cell values. The filter forms an especially useful tool for digital signal processing.

  15. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Luis, Alfredo

    The use of Renyi entropy as an uncertainty measure alternative to variance leads to the study of states with quantum fluctuations below the levels established by Gaussian states, which are the position-momentum minimum uncertainty states according to variance. We examine the quantum properties of states with exponential wave functions, which combine reduced fluctuations with practical feasibility.

  16. A Filtering of Incomplete GNSS Position Time Series with Probabilistic Principal Component Analysis

    NASA Astrophysics Data System (ADS)

    Gruszczynski, Maciej; Klos, Anna; Bogusz, Janusz

    2018-04-01

    For the first time, we introduced the probabilistic principal component analysis (pPCA) regarding the spatio-temporal filtering of Global Navigation Satellite System (GNSS) position time series to estimate and remove Common Mode Error (CME) without the interpolation of missing values. We used data from the International GNSS Service (IGS) stations which contributed to the latest International Terrestrial Reference Frame (ITRF2014). The efficiency of the proposed algorithm was tested on the simulated incomplete time series, then CME was estimated for a set of 25 stations located in Central Europe. The newly applied pPCA was compared with previously used algorithms, which showed that this method is capable of resolving the problem of proper spatio-temporal filtering of GNSS time series characterized by different observation time span. We showed, that filtering can be carried out with pPCA method when there exist two time series in the dataset having less than 100 common epoch of observations. The 1st Principal Component (PC) explained more than 36% of the total variance represented by time series residuals' (series with deterministic model removed), what compared to the other PCs variances (less than 8%) means that common signals are significant in GNSS residuals. A clear improvement in the spectral indices of the power-law noise was noticed for the Up component, which is reflected by an average shift towards white noise from - 0.98 to - 0.67 (30%). We observed a significant average reduction in the accuracy of stations' velocity estimated for filtered residuals by 35, 28 and 69% for the North, East, and Up components, respectively. CME series were also subjected to analysis in the context of environmental mass loading influences of the filtering results. Subtraction of the environmental loading models from GNSS residuals provides to reduction of the estimated CME variance by 20 and 65% for horizontal and vertical components, respectively.

  17. Maximum Likelihood and Minimum Distance Applied to Univariate Mixture Distributions.

    ERIC Educational Resources Information Center

    Wang, Yuh-Yin Wu; Schafer, William D.

    This Monte-Carlo study compared modified Newton (NW), expectation-maximization algorithm (EM), and minimum Cramer-von Mises distance (MD), used to estimate parameters of univariate mixtures of two components. Data sets were fixed at size 160 and manipulated by mean separation, variance ratio, component proportion, and non-normality. Results…

  18. Minimum Bayes risk image correlation

    NASA Technical Reports Server (NTRS)

    Minter, T. C., Jr.

    1980-01-01

    In this paper, the problem of designing a matched filter for image correlation will be treated as a statistical pattern recognition problem. It is shown that, by minimizing a suitable criterion, a matched filter can be estimated which approximates the optimum Bayes discriminant function in a least-squares sense. It is well known that the use of the Bayes discriminant function in target classification minimizes the Bayes risk, which in turn directly minimizes the probability of a false fix. A fast Fourier implementation of the minimum Bayes risk correlation procedure is described.

  19. Practical implementation of Channelized Hotelling Observers: Effect of ROI size

    PubMed Central

    Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

    2017-01-01

    Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO’s performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO’s performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies. PMID:28943699

  20. 40 CFR Table 3 to Subpart Hhh of... - Operating Parameters To Be Monitored and Minimum Measurement and Recording Frequencies

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... rural HMIWI HMIWI a with dry scrubber followed by fabric filter HMIWI a with wet scrubber HMIWI a with dry scrubber followed by fabric filter and wet scrubber Maximum operating parameters: Maximum charge rate Once per charge Once per charge ✔ ✔ ✔ ✔ Maximum fabric filter inlet temperature Continuous Once...

  1. The human as a detector of changes in variance and bandwidth

    NASA Technical Reports Server (NTRS)

    Curry, R. E.; Govindaraj, T.

    1977-01-01

    The detection of changes in random process variance and bandwidth was studied. Psychophysical thresholds for these two parameters were determined using an adaptive staircase technique for second order random processes at two nominal periods (1 and 3 seconds) and damping ratios (0.2 and 0.707). Thresholds for bandwidth changes were approximately 9% of nominal except for the (3sec,0.2) process which yielded thresholds of 12%. Variance thresholds averaged 17% of nominal except for the (3sec,0.2) process in which they were 32%. Detection times for suprathreshold changes in the parameters may be roughly described by the changes in RMS velocity of the process. A more complex model is presented which consists of a Kalman filter designed for the nominal process using velocity as the input, and a modified Wald sequential test for changes in the variance of the residual. The model predictions agree moderately well with the experimental data. Models using heuristics, e.g. level crossing counters, were also examined and are found to be descriptive but do not afford the unification of the Kalman filter/sequential test model used for changes in mean.

  2. Use of Disjunctive Response Requirements in Dual-Task Environments: Implications for Automation.

    DTIC Science & Technology

    1986-05-01

    could be momentarily held in a short-term sensory buffer for later processing. Broadbent, postulating an early filter model , assumed the physical nature...explicative power of the early filter model , further dichotic listening experiments began to support, as a minimum, a late filter model . Deutsch and Deutsch... filter 63 model came from a study by Cortecn and Wood (1972). Initially, they conditioned a list of city names to electrical shock until the

  3. A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Romero, Louis A; Mason, John J.

    We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, themore » problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.« less

  4. Thermal control design of the Lightning Mapper Sensor narrow-band spectral filter

    NASA Technical Reports Server (NTRS)

    Flannery, Martin R.; Potter, John; Raab, Jeff R.; Manlief, Scott K.

    1992-01-01

    The performance of the Lightning Mapper Sensor is dependent on the temperature shifts of its narrowband spectral filter. To perform over a 10 degree FOV with an 0.8 nm bandwidth, the filter must be 15 cm in diameter and mounted externally to the telescope optics. The filter thermal control required a filter design optimized for minimum bandpass shift with temperature, a thermal analysis of substrate materials for maximum temperature uniformity, and a thermal radiation analysis to determine the parameter sensitivity of the radiation shield for the filter, the filter thermal recovery time after occultation, and heater power to maintain filter performance in the earth-staring geosynchronous environment.

  5. An RC active filter design handbook

    NASA Technical Reports Server (NTRS)

    Deboo, G. J.

    1977-01-01

    The design of filters is described. Emphasis is placed on simplified procedures that can be used by the reader who has minimum knowledge about circuit design and little acquaintance with filter theory. The handbook has three main parts. The first part is a review of some information that is essential for work with filters. The second part includes design information for specific types of filter circuitry and describes simple procedures for obtaining the component values for a filter that will have a desired set of characteristics. Pertinent information relating to actual performance is given. The third part (appendix) is a review of certain topics in filter theory and is intended to provide some basic understanding of how filters are designed.

  6. A method for minimum risk portfolio optimization under hybrid uncertainty

    NASA Astrophysics Data System (ADS)

    Egorova, Yu E.; Yazenin, A. V.

    2018-03-01

    In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.

  7. 42 CFR 84.177 - Inhalation and exhalation valves; minimum requirements.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... air from adversely affecting filters, except where filters are specifically designed to resist... DEVICES Non-Powered Air-Purifying Particulate Respirators § 84.177 Inhalation and exhalation valves... external influence; and (3) Designed and constructed to prevent inward leakage of contaminated air. ...

  8. 42 CFR 84.177 - Inhalation and exhalation valves; minimum requirements.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... air from adversely affecting filters, except where filters are specifically designed to resist... DEVICES Non-Powered Air-Purifying Particulate Respirators § 84.177 Inhalation and exhalation valves... external influence; and (3) Designed and constructed to prevent inward leakage of contaminated air. ...

  9. Energy Systems Integration Facility Office Space | Energy Systems

    Science.gov Websites

    unit has a design capacity of 24,000 cfm (with a minimum outside air of 6,500 cfm) and consists of a pre-filter, heating coil, fan section, cooling coil, and final filter. The office space also has

  10. [Medical image segmentation based on the minimum variation snake model].

    PubMed

    Zhou, Changxiong; Yu, Shenglin

    2007-02-01

    It is difficult for traditional parametric active contour (Snake) model to deal with automatic segmentation of weak edge medical image. After analyzing snake and geometric active contour model, a minimum variation snake model was proposed and successfully applied to weak edge medical image segmentation. This proposed model replaces constant force in the balloon snake model by variable force incorporating foreground and background two regions information. It drives curve to evolve with the criterion of the minimum variation of foreground and background two regions. Experiments and results have proved that the proposed model is robust to initial contours placements and can segment weak edge medical image automatically. Besides, the testing for segmentation on the noise medical image filtered by curvature flow filter, which preserves edge features, shows a significant effect.

  11. Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

    NASA Astrophysics Data System (ADS)

    Setiawan, E. P.; Rosadi, D.

    2017-01-01

    Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

  12. Robust guaranteed-cost adaptive quantum phase estimation

    NASA Astrophysics Data System (ADS)

    Roy, Shibdas; Berry, Dominic W.; Petersen, Ian R.; Huntington, Elanor H.

    2017-05-01

    Quantum parameter estimation plays a key role in many fields like quantum computation, communication, and metrology. Optimal estimation allows one to achieve the most precise parameter estimates, but requires accurate knowledge of the model. Any inevitable uncertainty in the model parameters may heavily degrade the quality of the estimate. It is therefore desired to make the estimation process robust to such uncertainties. Robust estimation was previously studied for a varying phase, where the goal was to estimate the phase at some time in the past, using the measurement results from both before and after that time within a fixed time interval up to current time. Here, we consider a robust guaranteed-cost filter yielding robust estimates of a varying phase in real time, where the current phase is estimated using only past measurements. Our filter minimizes the largest (worst-case) variance in the allowable range of the uncertain model parameter(s) and this determines its guaranteed cost. It outperforms in the worst case the optimal Kalman filter designed for the model with no uncertainty, which corresponds to the center of the possible range of the uncertain parameter(s). Moreover, unlike the Kalman filter, our filter in the worst case always performs better than the best achievable variance for heterodyne measurements, which we consider as the tolerable threshold for our system. Furthermore, we consider effective quantum efficiency and effective noise power, and show that our filter provides the best results by these measures in the worst case.

  13. A class of optimum digital phase locked loops for the DSN advanced receiver

    NASA Technical Reports Server (NTRS)

    Hurd, W. J.; Kumar, R.

    1985-01-01

    A class of optimum digital filters for digital phase locked loop of the deep space network advanced receiver is discussed. The filter minimizes a weighted combination of the variance of the random component of the phase error and the sum square of the deterministic dynamic component of phase error at the output of the numerically controlled oscillator (NCO). By varying the weighting coefficient over a suitable range of values, a wide set of filters are obtained such that, for any specified value of the equivalent loop-noise bandwidth, there corresponds a unique filter in this class. This filter thus has the property of having the best transient response over all possible filters of the same bandwidth and type. The optimum filters are also evaluated in terms of their gain margin for stability and their steady-state error performance.

  14. Event-triggered resilient filtering with stochastic uncertainties and successive packet dropouts via variance-constrained approach

    NASA Astrophysics Data System (ADS)

    Jia, Chaoqing; Hu, Jun; Chen, Dongyan; Liu, Yurong; Alsaadi, Fuad E.

    2018-07-01

    In this paper, we discuss the event-triggered resilient filtering problem for a class of time-varying systems subject to stochastic uncertainties and successive packet dropouts. The event-triggered mechanism is employed with hope to reduce the communication burden and save network resources. The stochastic uncertainties are considered to describe the modelling errors and the phenomenon of successive packet dropouts is characterized by a random variable obeying the Bernoulli distribution. The aim of the paper is to provide a resilient event-based filtering approach for addressed time-varying systems such that, for all stochastic uncertainties, successive packet dropouts and filter gain perturbation, an optimized upper bound of the filtering error covariance is obtained by designing the filter gain. Finally, simulations are provided to demonstrate the effectiveness of the proposed robust optimal filtering strategy.

  15. Resilient filtering for time-varying stochastic coupling networks under the event-triggering scheduling

    NASA Astrophysics Data System (ADS)

    Wang, Fan; Liang, Jinling; Dobaie, Abdullah M.

    2018-07-01

    The resilient filtering problem is considered for a class of time-varying networks with stochastic coupling strengths. An event-triggered strategy is adopted to save the network resources by scheduling the signal transmission from the sensors to the filters based on certain prescribed rules. Moreover, the filter parameters to be designed are subject to gain perturbations. The primary aim of the addressed problem is to determine a resilient filter that ensures an acceptable filtering performance for the considered network with event-triggering scheduling. To handle such an issue, an upper bound on the estimation error variance is established for each node according to the stochastic analysis. Subsequently, the resilient filter is designed by locally minimizing the derived upper bound at each iteration. Moreover, rigorous analysis shows the monotonicity of the minimal upper bound regarding the triggering threshold. Finally, a simulation example is presented to show effectiveness of the established filter scheme.

  16. Apparatus for real-time airborne particulate radionuclide collection and analysis

    DOEpatents

    Smart, John E.; Perkins, Richard W.

    2001-01-01

    An improved apparatus for collecting and analyzing an airborne particulate radionuclide having a filter mounted in a housing, the housing having an air inlet upstream of the filter and an air outlet downstream of the filter, wherein an air stream flows therethrough. The air inlet receives the air stream, the filter collects the airborne particulate radionuclide and permits a filtered air stream to pass through the air outlet. The improvement which permits real time counting is a gamma detecting germanium diode mounted downstream of the filter in the filtered air stream. The gamma detecting germanium diode is spaced apart from a downstream side of the filter a minimum distance for a substantially maximum counting detection while permitting substantially free air flow through the filter and uniform particulate radionuclide deposition on the filter.

  17. Sub-basin-scale sea level budgets from satellite altimetry, Argo floats and satellite gravimetry: a case study in the North Atlantic Ocean

    NASA Astrophysics Data System (ADS)

    Kleinherenbrink, Marcel; Riva, Riccardo; Sun, Yu

    2016-11-01

    In this study, for the first time, an attempt is made to close the sea level budget on a sub-basin scale in terms of trend and amplitude of the annual cycle. We also compare the residual time series after removing the trend, the semiannual and the annual signals. To obtain errors for altimetry and Argo, full variance-covariance matrices are computed using correlation functions and their errors are fully propagated. For altimetry, we apply a geographically dependent intermission bias [Ablain et al.(2015)], which leads to differences in trends up to 0.8 mm yr-1. Since Argo float measurements are non-homogeneously spaced, steric sea levels are first objectively interpolated onto a grid before averaging. For the Gravity Recovery And Climate Experiment (GRACE), gravity fields full variance-covariance matrices are used to propagate errors and statistically filter the gravity fields. We use four different filtered gravity field solutions and determine which post-processing strategy is best for budget closure. As a reference, the standard 96 degree Dense Decorrelation Kernel-5 (DDK5)-filtered Center for Space Research (CSR) solution is used to compute the mass component (MC). A comparison is made with two anisotropic Wiener-filtered CSR solutions up to degree and order 60 and 96 and a Wiener-filtered 90 degree ITSG solution. Budgets are computed for 10 polygons in the North Atlantic Ocean, defined in a way that the error on the trend of the MC plus steric sea level remains within 1 mm yr-1. Using the anisotropic Wiener filter on CSR gravity fields expanded up to spherical harmonic degree 96, it is possible to close the sea level budget in 9 of 10 sub-basins in terms of trend. Wiener-filtered Institute of Theoretical geodesy and Satellite Geodesy (ITSG) and the standard DDK5-filtered CSR solutions also close the trend budget if a glacial isostatic adjustment (GIA) correction error of 10-20 % is applied; however, the performance of the DDK5-filtered solution strongly depends on the orientation of the polygon due to residual striping. In 7 of 10 sub-basins, the budget of the annual cycle is closed, using the DDK5-filtered CSR or the Wiener-filtered ITSG solutions. The Wiener-filtered 60 and 96 degree CSR solutions, in combination with Argo, lack amplitude and suffer from what appears to be hydrological leakage in the Amazon and Sahel regions. After reducing the trend, the semiannual and the annual signals, 24-53 % of the residual variance in altimetry-derived sea level time series is explained by the combination of Argo steric sea levels and the Wiener-filtered ITSG MC. Based on this, we believe that the best overall solution for the MC of the sub-basin-scale budgets is the Wiener-filtered ITSG gravity fields. The interannual variability is primarily a steric signal in the North Atlantic Ocean, so for this the choice of filter and gravity field solution is not really significant.

  18. A MEMS disk resonator-based band pass filter electrical equivalent circuit simulation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sundaram, G. M.; Angira, Mahesh; Gupta, Navneet

    In this paper, coupled beam bandpass Disk filter is designed for 1 MHz bandwidth. Filter electrical equivalent circuit simulation is performed using circuit simulators. Important filter parameters such as insertion loss, shape factor and Q factor aresetimated using coventorware simulation. Disk resonator based radial contour mode filter provides 1.5 MHz bandwidth and unloaded quality factor of resonator and filter as 233480, 21797 respectively. From the simulation result it’s found that insertion loss minimum is 151.49 dB, insertion loss maximum is 213.94 dB, and 40 dB shape factor is 4.17.

  19. Movement trajectory smoothness is not associated with the endpoint accuracy of rapid multi-joint arm movements in young and older adults

    PubMed Central

    Poston, Brach; Van Gemmert, Arend W.A.; Sharma, Siddharth; Chakrabarti, Somesh; Zavaremi, Shahrzad H.; Stelmach, George

    2013-01-01

    The minimum variance theory proposes that motor commands are corrupted by signal-dependent noise and smooth trajectories with low noise levels are selected to minimize endpoint error and endpoint variability. The purpose of the study was to determine the contribution of trajectory smoothness to the endpoint accuracy and endpoint variability of rapid multi-joint arm movements. Young and older adults performed arm movements (4 blocks of 25 trials) as fast and as accurately as possible to a target with the right (dominant) arm. Endpoint accuracy and endpoint variability along with trajectory smoothness and error were quantified for each block of trials. Endpoint error and endpoint variance were greater in older adults compared with young adults, but decreased at a similar rate with practice for the two age groups. The greater endpoint error and endpoint variance exhibited by older adults were primarily due to impairments in movement extent control and not movement direction control. The normalized jerk was similar for the two age groups, but was not strongly associated with endpoint error or endpoint variance for either group. However, endpoint variance was strongly associated with endpoint error for both the young and older adults. Finally, trajectory error was similar for both groups and was weakly associated with endpoint error for the older adults. The findings are not consistent with the predictions of the minimum variance theory, but support and extend previous observations that movement trajectories and endpoints are planned independently. PMID:23584101

  20. Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

    NASA Astrophysics Data System (ADS)

    Piretzidis, D.; Sra, G.; Sideris, M. G.

    2016-12-01

    This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

  1. Effects of important parameters variations on computing eigenspace-based minimum variance weights for ultrasound tissue harmonic imaging

    NASA Astrophysics Data System (ADS)

    Haji Heidari, Mehdi; Mozaffarzadeh, Moein; Manwar, Rayyan; Nasiriavanaki, Mohammadreza

    2018-02-01

    In recent years, the minimum variance (MV) beamforming has been widely studied due to its high resolution and contrast in B-mode Ultrasound imaging (USI). However, the performance of the MV beamformer is degraded at the presence of noise, as a result of the inaccurate covariance matrix estimation which leads to a low quality image. Second harmonic imaging (SHI) provides many advantages over the conventional pulse-echo USI, such as enhanced axial and lateral resolutions. However, the low signal-to-noise ratio (SNR) is a major problem in SHI. In this paper, Eigenspace-based minimum variance (EIBMV) beamformer has been employed for second harmonic USI. The Tissue Harmonic Imaging (THI) is achieved by Pulse Inversion (PI) technique. Using the EIBMV weights, instead of the MV ones, would lead to reduced sidelobes and improved contrast, without compromising the high resolution of the MV beamformer (even at the presence of a strong noise). In addition, we have investigated the effects of variations of the important parameters in computing EIBMV weights, i.e., K, L, and δ, on the resolution and contrast obtained in SHI. The results are evaluated using numerical data (using point target and cyst phantoms), and the proper parameters of EIBMV are indicated for THI.

  2. Hydraulic geometry of river cross sections; theory of minimum variance

    USGS Publications Warehouse

    Williams, Garnett P.

    1978-01-01

    This study deals with the rates at which mean velocity, mean depth, and water-surface width increase with water discharge at a cross section on an alluvial stream. Such relations often follow power laws, the exponents in which are called hydraulic exponents. The Langbein (1964) minimum-variance theory is examined in regard to its validity and its ability to predict observed hydraulic exponents. The variables used with the theory were velocity, depth, width, bed shear stress, friction factor, slope (energy gradient), and stream power. Slope is often constant, in which case only velocity, depth, width, shear and friction factor need be considered. The theory was tested against a wide range of field data from various geographic areas of the United States. The original theory was intended to produce only the average hydraulic exponents for a group of cross sections in a similar type of geologic or hydraulic environment. The theory does predict these average exponents with a reasonable degree of accuracy. An attempt to forecast the exponents at any selected cross section was moderately successful. Empirical equations are more accurate than the minimum variance, Gauckler-Manning, or Chezy methods. Predictions of the exponent of width are most reliable, the exponent of depth fair, and the exponent of mean velocity poor. (Woodard-USGS)

  3. Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm

    NASA Astrophysics Data System (ADS)

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

    2018-02-01

    In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

  4. Mesoscale Gravity Wave Variances from AMSU-A Radiances

    NASA Technical Reports Server (NTRS)

    Wu, Dong L.

    2004-01-01

    A variance analysis technique is developed here to extract gravity wave (GW) induced temperature fluctuations from NOAA AMSU-A (Advanced Microwave Sounding Unit-A) radiance measurements. By carefully removing the instrument/measurement noise, the algorithm can produce reliable GW variances with the minimum detectable value as small as 0.1 K2. Preliminary analyses with AMSU-A data show GW variance maps in the stratosphere have very similar distributions to those found with the UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder). However, the AMSU-A offers better horizontal and temporal resolution for observing regional GW variability, such as activity over sub-Antarctic islands.

  5. Analysis of conditional genetic effects and variance components in developmental genetics.

    PubMed

    Zhu, J

    1995-12-01

    A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

  6. Analysis of Conditional Genetic Effects and Variance Components in Developmental Genetics

    PubMed Central

    Zhu, J.

    1995-01-01

    A genetic model with additive-dominance effects and genotype X environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t - 1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects. PMID:8601500

  7. On the performance of digital phase locked loops in the threshold region

    NASA Technical Reports Server (NTRS)

    Hurst, G. T.; Gupta, S. C.

    1974-01-01

    Extended Kalman filter algorithms are used to obtain a digital phase lock loop structure for demodulation of angle modulated signals. It is shown that the error variance equations obtained directly from this structure enable one to predict threshold if one retains higher frequency terms. This is in sharp contrast to the similar analysis of the analog phase lock loop, where the higher frequency terms are filtered out because of the low pass filter in the loop. Results are compared to actual simulation results and threshold region results obtained previously.

  8. Distributed optical signal processing for microwave photonics subsystems.

    PubMed

    Chew, Suen Xin; Nguyen, Linh; Yi, Xiaoke; Song, Shijie; Li, Liwei; Bian, Pengju; Minasian, Robert

    2016-03-07

    We propose and experimentally demonstrate a novel and practical microwave photonic system that is capable of executing cascaded signal processing functions comprising a microwave photonic bandpass filter and a phase shifter, while providing separate and independent control for each function. The experimental results demonstrate a single bandpass microwave photonic filter with a 3-dB bandwidth of 15 MHz and an out-of-band ratio of over 40 dB, together with a simultaneous RF phase tuning control of 0-215° with less than ± 3 dB filter shape variance.

  9. 40 CFR Appendix B to Part 50 - Reference Method for the Determination of Suspended Particulate Matter in the Atmosphere (High...

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... site, draws a measured quantity of ambient air into a covered housing and through a filter during a 24... filters used are specified to have a minimum collection efficiency of 99 percent for 0.3 µm (DOP) particles (see Section 7.1.4). 2.2 The filter is weighed (after moisture equilibration) before and after use...

  10. Some refinements on the comparison of areal sampling methods via simulation

    Treesearch

    Jeffrey Gove

    2017-01-01

    The design of forest inventories and development of new sampling methods useful in such inventories normally have a two-fold target of design unbiasedness and minimum variance in mind. Many considerations such as costs go into the choices of sampling method for operational and other levels of inventory. However, the variance in terms of meeting a specified level of...

  11. A comparison of coronal and interplanetary current sheet inclinations

    NASA Technical Reports Server (NTRS)

    Behannon, K. W.; Burlaga, L. F.; Hundhausen, A. J.

    1983-01-01

    The HAO white light K-coronameter observations show that the inclination of the heliospheric current sheet at the base of the corona can be both large (nearly vertical with respect to the solar equator) or small during Cararington rotations 1660 - 1666 and even on a single solar rotation. Voyager 1 and 2 magnetic field observations of crossing of the heliospheric current sheet at distances from the Sun of 1.4 and 2.8 AU. Two cases are considered, one in which the corresponding coronameter data indicate a nearly vertical (north-south) current sheet and another in which a nearly horizontal, near equatorial current sheet is indicated. For the crossings of the vertical current sheet, a variance analysis based on hour averages of the magnetic field data gave a minimum variance direction consistent with a steep inclination. The horizontal current sheet was observed by Voyager as a region of mixed polarity and low speeds lasting several days, consistent with multiple crossings of a horizontal but irregular and fluctuating current sheet at 1.4 AU. However, variance analysis of individual current sheet crossings in this interval using 1.92 see averages did not give minimum variance directions consistent with a horizontal current sheet.

  12. Filtering effect of SiO2 optical waveguide ring resonator applied to optoelectronic oscillator.

    PubMed

    Chen, Jiamin; Zheng, Yongqiu; Xue, Chenyang; Zhang, Chengfei; Chen, Yi

    2018-05-14

    Single-mode oscillation is crucial to the practicality of optoelectronic oscillator (OEO). Due to the limited by bandwidth and precision of radio frequency (RF) filters, it is difficult to be achieved for the OEO based on the long fiber-optic delay line. So instead of the long fiber-optic delay line, SiO 2 optical waveguide ring resonator (OWRR) with high-Q and mode selection is first presented to be applied to OEO. The OEOs based on the minimum loop and SiO 2 OWRR are constructed. The oscillation characteristics of the minimum loop OEO and the transmission characteristics of the SiO 2 OWRR are simulated by MATLAB, respectively. The filtering effect of the SiO 2 OWRR applied to the OEO is verified theoretically by comparing these simulation results. Subsequently, the contrastive experiments of the above two OEOs on oscillation modes are carried out. The oscillation mode spacing of 40.32 MHz and 2.137 GHz are obtained. These results show that the SiO 2 OWRR can function as an excellent 'filter' in the minimum loop of the OEO. Moreover, the side mode suppression ratio and the phase noise of the OEO have been improved. Our experimental results demonstrate that the OEO adopting SiO 2 OWRR is feasible to achieve the single-mode oscillation and obtain better performance microwave signals.

  13. Video denoising using low rank tensor decomposition

    NASA Astrophysics Data System (ADS)

    Gui, Lihua; Cui, Gaochao; Zhao, Qibin; Wang, Dongsheng; Cichocki, Andrzej; Cao, Jianting

    2017-03-01

    Reducing noise in a video sequence is of vital important in many real-world applications. One popular method is block matching collaborative filtering. However, the main drawback of this method is that noise standard deviation for the whole video sequence is known in advance. In this paper, we present a tensor based denoising framework that considers 3D patches instead of 2D patches. By collecting the similar 3D patches non-locally, we employ the low-rank tensor decomposition for collaborative filtering. Since we specify the non-informative prior over the noise precision parameter, the noise variance can be inferred automatically from observed video data. Therefore, our method is more practical, which does not require knowing the noise variance. The experimental on video denoising demonstrates the effectiveness of our proposed method.

  14. Reconstruction of signals with unknown spectra in information field theory with parameter uncertainty

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ensslin, Torsten A.; Frommert, Mona

    2011-05-15

    The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured simultaneously from the same data used for the signal reconstruction. We formulate the general problem of signal inference in the presence of unknown parameters within the framework of information field theory. To solve this, we develop a generic parameter-uncertainty renormalized estimation (PURE) technique. As a concrete application, we address the problem of reconstructing Gaussian signals with unknown power-spectrum with five different approaches: (i) separate maximum-a-posteriori power-spectrum measurement and subsequentmore » reconstruction, (ii) maximum-a-posteriori reconstruction with marginalized power-spectrum, (iii) maximizing the joint posterior of signal and spectrum, (iv) guessing the spectrum from the variance in the Wiener-filter map, and (v) renormalization flow analysis of the field-theoretical problem providing the PURE filter. In all cases, the reconstruction can be described or approximated as Wiener-filter operations with assumed signal spectra derived from the data according to the same recipe, but with differing coefficients. All of these filters, except the renormalized one, exhibit a perception threshold in case of a Jeffreys prior for the unknown spectrum. Data modes with variance below this threshold do not affect the signal reconstruction at all. Filter (iv) seems to be similar to the so-called Karhune-Loeve and Feldman-Kaiser-Peacock estimators for galaxy power spectra used in cosmology, which therefore should also exhibit a marginal perception threshold if correctly implemented. We present statistical performance tests and show that the PURE filter is superior to the others, especially if the post-Wiener-filter corrections are included or in case an additional scale-independent spectral smoothness prior can be adopted.« less

  15. Impacts of PM concentrations on visibility impairment

    NASA Astrophysics Data System (ADS)

    Jie, Guo; Wang, Mei-mei; Han, Ye-Xing; Yu, Zhi-Wei; Tang, Huai-Wu

    2016-11-01

    In the paper, an accurate and sensitive cavity attenuated phase shift spectroscopy (CAPS) sensor was used to monitor the atmospheric visibility. The CAPS system mainly includes a LED light source, a band-pass filter, an optical resonant cavity (composed of two high mirror, reflectivity is greater than 99.99%), a photoelectric detector and a lock-in amplifier. The 2L/min flow rate, the optical sensor rise and fall response time is about 15 s, so as to realize the fast measurement of visibility. An Allan variance analysis was carried out evaluating the optical system stability (and hence the maximum averaging time for the minimum detection limit) of the CAPS system. The minima ( 0.1 Mm-1) in the Allan plots show the optimum average time ( 100s) for optimum detection performance of the CAPS system. During this period, the extinction coefficient was correlated with PM2.5 mass (0.88), the extinction coefficient was correlated with PM10 mass (0.85). The atmospheric visibility was correlated with PM2.5 mass (0.74). The atmospheric visibility was correlated with PM10 mass (0.66).

  16. Data assimilation method based on the constraints of confidence region

    NASA Astrophysics Data System (ADS)

    Li, Yong; Li, Siming; Sheng, Yao; Wang, Luheng

    2018-03-01

    The ensemble Kalman filter (EnKF) is a distinguished data assimilation method that is widely used and studied in various fields including methodology and oceanography. However, due to the limited sample size or imprecise dynamics model, it is usually easy for the forecast error variance to be underestimated, which further leads to the phenomenon of filter divergence. Additionally, the assimilation results of the initial stage are poor if the initial condition settings differ greatly from the true initial state. To address these problems, the variance inflation procedure is usually adopted. In this paper, we propose a new method based on the constraints of a confidence region constructed by the observations, called EnCR, to estimate the inflation parameter of the forecast error variance of the EnKF method. In the new method, the state estimate is more robust to both the inaccurate forecast models and initial condition settings. The new method is compared with other adaptive data assimilation methods in the Lorenz-63 and Lorenz-96 models under various model parameter settings. The simulation results show that the new method performs better than the competing methods.

  17. Optical ranked-order filtering using threshold decomposition

    DOEpatents

    Allebach, Jan P.; Ochoa, Ellen; Sweeney, Donald W.

    1990-01-01

    A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed.

  18. Minimum Variance Distortionless Response Beamformer with Enhanced Nulling Level Control via Dynamic Mutated Artificial Immune System

    PubMed Central

    Kiong, Tiong Sieh; Salem, S. Balasem; Paw, Johnny Koh Siaw; Sankar, K. Prajindra

    2014-01-01

    In smart antenna applications, the adaptive beamforming technique is used to cancel interfering signals (placing nulls) and produce or steer a strong beam toward the target signal according to the calculated weight vectors. Minimum variance distortionless response (MVDR) beamforming is capable of determining the weight vectors for beam steering; however, its nulling level on the interference sources remains unsatisfactory. Beamforming can be considered as an optimization problem, such that optimal weight vector should be obtained through computation. Hence, in this paper, a new dynamic mutated artificial immune system (DM-AIS) is proposed to enhance MVDR beamforming for controlling the null steering of interference and increase the signal to interference noise ratio (SINR) for wanted signals. PMID:25003136

  19. Minimum variance distortionless response beamformer with enhanced nulling level control via dynamic mutated artificial immune system.

    PubMed

    Kiong, Tiong Sieh; Salem, S Balasem; Paw, Johnny Koh Siaw; Sankar, K Prajindra; Darzi, Soodabeh

    2014-01-01

    In smart antenna applications, the adaptive beamforming technique is used to cancel interfering signals (placing nulls) and produce or steer a strong beam toward the target signal according to the calculated weight vectors. Minimum variance distortionless response (MVDR) beamforming is capable of determining the weight vectors for beam steering; however, its nulling level on the interference sources remains unsatisfactory. Beamforming can be considered as an optimization problem, such that optimal weight vector should be obtained through computation. Hence, in this paper, a new dynamic mutated artificial immune system (DM-AIS) is proposed to enhance MVDR beamforming for controlling the null steering of interference and increase the signal to interference noise ratio (SINR) for wanted signals.

  20. The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.

    PubMed

    Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck

    2016-07-16

    This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.

  1. Parameter Estimation for the Blind Restoration of Blurred Imagery.

    DTIC Science & Technology

    1986-09-01

    17 Noise Process .... ............. 23 Restoration Methods .... .......... 26 Inverse Filter .... ........... 26 Wiener Filter...of Eq. (155) ....... .................... ... 64 Table 2 Restored Pictures and Noise Variances ........ . 69 v 5𔃼 5- viq °,. r -’ .’S’ .N’% N...restoration system. g(x,y) Degraded image. G(u,v) Discrete Fourier Transform of the degraded image. n(x,y) Noise . N(u,v) Discrete Fourier transform of n

  2. Adaptive Kalman filter based on variance component estimation for the prediction of ionospheric delay in aiding the cycle slip repair of GNSS triple-frequency signals

    NASA Astrophysics Data System (ADS)

    Chang, Guobin; Xu, Tianhe; Yao, Yifei; Wang, Qianxin

    2018-01-01

    In order to incorporate the time smoothness of ionospheric delay to aid the cycle slip detection, an adaptive Kalman filter is developed based on variance component estimation. The correlations between measurements at neighboring epochs are fully considered in developing a filtering algorithm for colored measurement noise. Within this filtering framework, epoch-differenced ionospheric delays are predicted. Using this prediction, the potential cycle slips are repaired for triple-frequency signals of global navigation satellite systems. Cycle slips are repaired in a stepwise manner; i.e., for two extra wide lane combinations firstly and then for the third frequency. In the estimation for the third frequency, a stochastic model is followed in which the correlations between the ionospheric delay prediction errors and the errors in the epoch-differenced phase measurements are considered. The implementing details of the proposed method are tabulated. A real BeiDou Navigation Satellite System data set is used to check the performance of the proposed method. Most cycle slips, no matter trivial or nontrivial, can be estimated in float values with satisfactorily high accuracy and their integer values can hence be correctly obtained by simple rounding. To be more specific, all manually introduced nontrivial cycle slips are correctly repaired.

  3. Spotless Sun

    NASA Image and Video Library

    2017-03-22

    The sun has been virtually spotless, as in no sunspots, over the past 11 days, a spotless stretch that we have not seen since the last solar minimum many years ago. The videos shows the past four days (Mar. 14-17, 2017) with a combination of an extreme ultraviolet image blended with just the filtered sun. If we just showed the filtered sun with no spots for reference points, any viewer would have a hard time telling that the sun was even rotating. The sun is trending again towards the solar minimum period of its 11 year cycle, which is predicted to be around 2020. Movies are available at http://photojournal.jpl.nasa.gov/catalog/PIA21569

  4. 25 CFR 542.18 - How does a gaming operation apply for a variance from the standards of the part?

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false How does a gaming operation apply for a variance from the standards of the part? 542.18 Section 542.18 Indians NATIONAL INDIAN GAMING COMMISSION, DEPARTMENT OF THE INTERIOR HUMAN SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.18 How does a gaming operation apply for a...

  5. The minimum test battery to screen for binocular vision anomalies: report 3 of the BAND study.

    PubMed

    Hussaindeen, Jameel Rizwana; Rakshit, Archayeeta; Singh, Neeraj Kumar; Swaminathan, Meenakshi; George, Ronnie; Kapur, Suman; Scheiman, Mitchell; Ramani, Krishna Kumar

    2018-03-01

    This study aims to report the minimum test battery needed to screen non-strabismic binocular vision anomalies (NSBVAs) in a community set-up. When large numbers are to be screened we aim to identify the most useful test battery when there is no opportunity for a more comprehensive and time-consuming clinical examination. The prevalence estimates and normative data for binocular vision parameters were estimated from the Binocular Vision Anomalies and Normative Data (BAND) study, following which cut-off estimates and receiver operating characteristic curves to identify the minimum test battery have been plotted. In the receiver operating characteristic phase of the study, children between nine and 17 years of age were screened in two schools in the rural arm using the minimum test battery, and the prevalence estimates with the minimum test battery were found. Receiver operating characteristic analyses revealed that near point of convergence with penlight and red filter (> 7.5 cm), monocular accommodative facility (< 10 cycles per minute), and the difference between near and distance phoria (> 1.25 prism dioptres) were significant factors with cut-off values for best sensitivity and specificity. This minimum test battery was applied to a cohort of 305 children. The mean (standard deviation) age of the subjects was 12.7 (two) years with 121 males and 184 females. Using the minimum battery of tests obtained through the receiver operating characteristic analyses, the prevalence of NSBVAs was found to be 26 per cent. Near point of convergence with penlight and red filter > 10 cm was found to have the highest sensitivity (80 per cent) and specificity (73 per cent) for the diagnosis of convergence insufficiency. For the diagnosis of accommodative infacility, monocular accommodative facility with a cut-off of less than seven cycles per minute was the best predictor for screening (92 per cent sensitivity and 90 per cent specificity). The minimum test battery of near point of convergence with penlight and red filter, difference between distance and near phoria, and monocular accommodative facility yield good sensitivity and specificity for diagnosis of NSBVAs in a community set-up. © 2017 Optometry Australia.

  6. Kalman filter data assimilation: targeting observations and parameter estimation.

    PubMed

    Bellsky, Thomas; Kostelich, Eric J; Mahalov, Alex

    2014-06-01

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

  7. Kalman filter data assimilation: Targeting observations and parameter estimation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bellsky, Thomas, E-mail: bellskyt@asu.edu; Kostelich, Eric J.; Mahalov, Alex

    2014-06-15

    This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly locatedmore » observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.« less

  8. Determination of tailored filter sets to create rayfiles including spatial and angular resolved spectral information.

    PubMed

    Rotscholl, Ingo; Trampert, Klaus; Krüger, Udo; Perner, Martin; Schmidt, Franz; Neumann, Cornelius

    2015-11-16

    To simulate and optimize optical designs regarding perceived color and homogeneity in commercial ray tracing software, realistic light source models are needed. Spectral rayfiles provide angular and spatial varying spectral information. We propose a spectral reconstruction method with a minimum of time consuming goniophotometric near field measurements with optical filters for the purpose of creating spectral rayfiles. Our discussion focuses on the selection of the ideal optical filter combination for any arbitrary spectrum out of a given filter set by considering measurement uncertainties with Monte Carlo simulations. We minimize the simulation time by a preselection of all filter combinations, which bases on factorial design.

  9. Efficiency analysis of color image filtering

    NASA Astrophysics Data System (ADS)

    Fevralev, Dmitriy V.; Ponomarenko, Nikolay N.; Lukin, Vladimir V.; Abramov, Sergey K.; Egiazarian, Karen O.; Astola, Jaakko T.

    2011-12-01

    This article addresses under which conditions filtering can visibly improve the image quality. The key points are the following. First, we analyze filtering efficiency for 25 test images, from the color image database TID2008. This database allows assessing filter efficiency for images corrupted by different noise types for several levels of noise variance. Second, the limit of filtering efficiency is determined for independent and identically distributed (i.i.d.) additive noise and compared to the output mean square error of state-of-the-art filters. Third, component-wise and vector denoising is studied, where the latter approach is demonstrated to be more efficient. Fourth, using of modern visual quality metrics, we determine that for which levels of i.i.d. and spatially correlated noise the noise in original images or residual noise and distortions because of filtering in output images are practically invisible. We also demonstrate that it is possible to roughly estimate whether or not the visual quality can clearly be improved by filtering.

  10. Air-Gapped Structures as Magnetic Elements for Use in Power Processing Systems. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Ohri, A. K.

    1977-01-01

    Methodical approaches to the design of inductors for use in LC filters and dc-to-dc converters using air gapped magnetic structures are presented. Methods for the analysis and design of full wave rectifier LC filter circuits operating with the inductor current in both the continuous conduction and the discontinuous conduction modes are also described. In the continuous conduction mode, linear circuit analysis techniques are employed, while in the case of the discontinuous mode, the method of analysis requires computer solutions of the piecewise linear differential equations which describe the filter in the time domain. Procedures for designing filter inductors using air gapped cores are presented. The first procedure requires digital computation to yield a design which is optimized in the sense of minimum core volume and minimum number of turns. The second procedure does not yield an optimized design as defined above, but the design can be obtained by hand calculations or with a small calculator. The third procedure is based on the use of specially prepared magnetic core data and provides an easy way to quickly reach a workable design.

  11. SU-F-J-200: An Improved Method for Event Selection in Compton Camera Imaging for Particle Therapy

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mackin, D; Beddar, S; Polf, J

    2016-06-15

    Purpose: The uncertainty in the beam range in particle therapy limits the conformality of the dose distributions. Compton scatter cameras (CC), which measure the prompt gamma rays produced by nuclear interactions in the patient tissue, can reduce this uncertainty by producing 3D images confirming the particle beam range and dose delivery. However, the high intensity and short time windows of the particle beams limit the number of gammas detected. We attempt to address this problem by developing a method for filtering gamma ray scattering events from the background by applying the known gamma ray spectrum. Methods: We used a 4more » stage Compton camera to record in list mode the energy deposition and scatter positions of gammas from a Co-60 source. Each CC stage contained a 4×4 array of CdZnTe crystal. To produce images, we used a back-projection algorithm and four filtering Methods: basic, energy windowing, delta energy (ΔE), or delta scattering angle (Δθ). Basic filtering requires events to be physically consistent. Energy windowing requires event energy to fall within a defined range. ΔE filtering selects events with the minimum difference between the measured and a known gamma energy (1.17 and 1.33 MeV for Co-60). Δθ filtering selects events with the minimum difference between the measured scattering angle and the angle corresponding to a known gamma energy. Results: Energy window filtering reduced the FWHM from 197.8 mm for basic filtering to 78.3 mm. ΔE and Δθ filtering achieved the best results, FWHMs of 64.3 and 55.6 mm, respectively. In general, Δθ filtering selected events with scattering angles < 40°, while ΔE filtering selected events with angles > 60°. Conclusion: Filtering CC events improved the quality and resolution of the corresponding images. ΔE and Δθ filtering produced similar results but each favored different events.« less

  12. Modeling astronomical adaptive optics performance with temporally filtered Wiener reconstruction of slope data

    NASA Astrophysics Data System (ADS)

    Correia, Carlos M.; Bond, Charlotte Z.; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L.

    2017-10-01

    We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\\lambda}/D$ separations ($\\sim1-5{\\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.

  13. Overview ID/POV Process

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wendelberger, James G.

    2016-08-16

    This is a flowchart of the inventory difference/propagation of variance process, with steps such as determine all relevance transactions, group relevant transactions by affected MATLID, filter groups to S, F and identify required M's, etc.

  14. Hidden Markov analysis of mechanosensitive ion channel gating.

    PubMed

    Khan, R Nazim; Martinac, Boris; Madsen, Barry W; Milne, Robin K; Yeo, Geoffrey F; Edeson, Robert O

    2005-02-01

    Patch clamp data from the large conductance mechanosensitive channel (MscL) in E. coli was studied with the aim of developing a strategy for statistical analysis based on hidden Markov models (HMMs) and determining the number of conductance levels of the channel, together with mean current, mean dwell time and equilibrium probability of occupancy for each level. The models incorporated state-dependent white noise and moving average adjustment for filtering, with maximum likelihood parameter estimates obtained using an EM (expectation-maximisation) based iteration. Adjustment for filtering was included as it could be expected that the electronic filter used in recording would have a major effect on obviously brief intermediate conductance level sojourns. Preliminary data analysis revealed that the brevity of intermediate level sojourns caused difficulties in assignment of data points to levels as a result of over-estimation of noise variances. When reasonable constraints were placed on these variances using the better determined noise variances for the closed and fully open levels, idealisation anomalies were eliminated. Nevertheless, simulations suggested that mean sojourn times for the intermediate levels were still considerably over-estimated, and that recording bandwidth was a major limitation; improved results were obtained with higher bandwidth data (10 kHz sampled at 25 kHz). The simplest model consistent with these data had four open conductance levels, intermediate levels being approximately 20%, 51% and 74% of fully open. The mean lifetime at the fully open level was about 1 ms; estimates for the three intermediate levels were 54-92 micros, probably still over-estimates.

  15. A test of source-surface model predictions of heliospheric current sheet inclination

    NASA Technical Reports Server (NTRS)

    Burton, M. E.; Crooker, N. U.; Siscoe, G. L.; Smith, E. J.

    1994-01-01

    The orientation of the heliospheric current sheet predicted from a source surface model is compared with the orientation determined from minimum-variance analysis of International Sun-Earth Explorer (ISEE) 3 magnetic field data at 1 AU near solar maximum. Of the 37 cases analyzed, 28 have minimum variance normals that lie orthogonal to the predicted Parker spiral direction. For these cases, the correlation coefficient between the predicted and measured inclinations is 0.6. However, for the subset of 14 cases for which transient signatures (either interplanetary shocks or bidirectional electrons) are absent, the agreement in inclinations improves dramatically, with a correlation coefficient of 0.96. These results validate not only the use of the source surface model as a predictor but also the previously questioned usefulness of minimum variance analysis across complex sector boundaries. In addition, the results imply that interplanetary dynamics have little effect on current sheet inclination at 1 AU. The dependence of the correlation on transient occurrence suggests that the leading edge of a coronal mass ejection (CME), where transient signatures are detected, disrupts the heliospheric current sheet but that the sheet re-forms between the trailing legs of the CME. In this way the global structure of the heliosphere, reflected both in the source surface maps and in the interplanetary sector structure, can be maintained even when the CME occurrence rate is high.

  16. Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm.

    PubMed

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

    2018-02-01

    In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  17. A multiscale filter for noise reduction of low-dose cone beam projections.

    PubMed

    Yao, Weiguang; Farr, Jonathan B

    2015-08-21

    The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, exp(-x2/2σ(2)(f)) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of σ(f), which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ(2)(f)) is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

  18. Vegetation greenness impacts on maximum and minimum temperatures in northeast Colorado

    USGS Publications Warehouse

    Hanamean, J. R.; Pielke, R.A.; Castro, C. L.; Ojima, D.S.; Reed, Bradley C.; Gao, Z.

    2003-01-01

    The impact of vegetation on the microclimate has not been adequately considered in the analysis of temperature forecasting and modelling. To fill part of this gap, the following study was undertaken.A daily 850–700 mb layer mean temperature, computed from the National Center for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis, and satellite-derived greenness values, as defined by NDVI (Normalised Difference Vegetation Index), were correlated with surface maximum and minimum temperatures at six sites in northeast Colorado for the years 1989–98. The NDVI values, representing landscape greenness, act as a proxy for latent heat partitioning via transpiration. These sites encompass a wide array of environments, from irrigated-urban to short-grass prairie. The explained variance (r2 value) of surface maximum and minimum temperature by only the 850–700 mb layer mean temperature was subtracted from the corresponding explained variance by the 850–700 mb layer mean temperature and NDVI values. The subtraction shows that by including NDVI values in the analysis, the r2 values, and thus the degree of explanation of the surface temperatures, increase by a mean of 6% for the maxima and 8% for the minima over the period March–October. At most sites, there is a seasonal dependence in the explained variance of the maximum temperatures because of the seasonal cycle of plant growth and senescence. Between individual sites, the highest increase in explained variance occurred at the site with the least amount of anthropogenic influence. This work suggests the vegetation state needs to be included as a factor in surface temperature forecasting, numerical modeling, and climate change assessments.

  19. Optical ranked-order filtering using threshold decomposition

    DOEpatents

    Allebach, J.P.; Ochoa, E.; Sweeney, D.W.

    1987-10-09

    A hybrid optical/electronic system performs median filtering and related ranked-order operations using threshold decomposition to encode the image. Threshold decomposition transforms the nonlinear neighborhood ranking operation into a linear space-invariant filtering step followed by a point-to-point threshold comparison step. Spatial multiplexing allows parallel processing of all the threshold components as well as recombination by a second linear, space-invariant filtering step. An incoherent optical correlation system performs the linear filtering, using a magneto-optic spatial light modulator as the input device and a computer-generated hologram in the filter plane. Thresholding is done electronically. By adjusting the value of the threshold, the same architecture is used to perform median, minimum, and maximum filtering of images. A totally optical system is also disclosed. 3 figs.

  20. Change in mean temperature as a predictor of extreme temperature change in the Asia-Pacific region

    NASA Astrophysics Data System (ADS)

    Griffiths, G. M.; Chambers, L. E.; Haylock, M. R.; Manton, M. J.; Nicholls, N.; Baek, H.-J.; Choi, Y.; della-Marta, P. M.; Gosai, A.; Iga, N.; Lata, R.; Laurent, V.; Maitrepierre, L.; Nakamigawa, H.; Ouprasitwong, N.; Solofa, D.; Tahani, L.; Thuy, D. T.; Tibig, L.; Trewin, B.; Vediapan, K.; Zhai, P.

    2005-08-01

    Trends (1961-2003) in daily maximum and minimum temperatures, extremes and variance were found to be spatially coherent across the Asia-Pacific region. The majority of stations exhibited significant trends: increases in mean maximum and mean minimum temperature, decreases in cold nights and cool days, and increases in warm nights. No station showed a significant increase in cold days or cold nights, but a few sites showed significant decreases in hot days and warm nights. Significant decreases were observed in both maximum and minimum temperature standard deviation in China, Korea and some stations in Japan (probably reflecting urbanization effects), but also for some Thailand and coastal Australian sites. The South Pacific convergence zone (SPCZ) region between Fiji and the Solomon Islands showed a significant increase in maximum temperature variability.Correlations between mean temperature and the frequency of extreme temperatures were strongest in the tropical Pacific Ocean from French Polynesia to Papua New Guinea, Malaysia, the Philippines, Thailand and southern Japan. Correlations were weaker at continental or higher latitude locations, which may partly reflect urbanization.For non-urban stations, the dominant distribution change for both maximum and minimum temperature involved a change in the mean, impacting on one or both extremes, with no change in standard deviation. This occurred from French Polynesia to Papua New Guinea (except for maximum temperature changes near the SPCZ), in Malaysia, the Philippines, and several outlying Japanese islands. For urbanized stations the dominant change was a change in the mean and variance, impacting on one or both extremes. This result was particularly evident for minimum temperature.The results presented here, for non-urban tropical and maritime locations in the Asia-Pacific region, support the hypothesis that changes in mean temperature may be used to predict changes in extreme temperatures. At urbanized or higher latitude locations, changes in variance should be incorporated.

  1. Performance evaluation of an asynchronous multisensor track fusion filter

    NASA Astrophysics Data System (ADS)

    Alouani, Ali T.; Gray, John E.; McCabe, D. H.

    2003-08-01

    Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

  2. A tool for filtering information in complex systems

    PubMed Central

    Tumminello, M.; Aste, T.; Di Matteo, T.; Mantegna, R. N.

    2005-01-01

    We introduce a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0), triangular loops and four-element cliques are formed. The application of this filtering procedure to 100 stocks in the U.S. equity markets shows that such loops and cliques have important and significant relationships with the market structure and properties. PMID:16027373

  3. A tool for filtering information in complex systems.

    PubMed

    Tumminello, M; Aste, T; Di Matteo, T; Mantegna, R N

    2005-07-26

    We introduce a technique to filter out complex data sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation-based graphs, giving filtered graphs that preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0), triangular loops and four-element cliques are formed. The application of this filtering procedure to 100 stocks in the U.S. equity markets shows that such loops and cliques have important and significant relationships with the market structure and properties.

  4. Distortion analysis of subband adaptive filtering methods for FMRI active noise control systems.

    PubMed

    Milani, Ali A; Panahi, Issa M; Briggs, Richard

    2007-01-01

    Delayless subband filtering structure, as a high performance frequency domain filtering technique, is used for canceling broadband fMRI noise (8 kHz bandwidth). In this method, adaptive filtering is done in subbands and the coefficients of the main canceling filter are computed by stacking the subband weights together. There are two types of stacking methods called FFT and FFT-2. In this paper, we analyze the distortion introduced by these two stacking methods. The effect of the stacking distortion on the performance of different adaptive filters in FXLMS algorithm with non-minimum phase secondary path is explored. The investigation is done for different adaptive algorithms (nLMS, APA and RLS), different weight stacking methods, and different number of subbands.

  5. Tissue segmentation of computed tomography images using a Random Forest algorithm: a feasibility study

    NASA Astrophysics Data System (ADS)

    Polan, Daniel F.; Brady, Samuel L.; Kaufman, Robert A.

    2016-09-01

    There is a need for robust, fully automated whole body organ segmentation for diagnostic CT. This study investigates and optimizes a Random Forest algorithm for automated organ segmentation; explores the limitations of a Random Forest algorithm applied to the CT environment; and demonstrates segmentation accuracy in a feasibility study of pediatric and adult patients. To the best of our knowledge, this is the first study to investigate a trainable Weka segmentation (TWS) implementation using Random Forest machine-learning as a means to develop a fully automated tissue segmentation tool developed specifically for pediatric and adult examinations in a diagnostic CT environment. Current innovation in computed tomography (CT) is focused on radiomics, patient-specific radiation dose calculation, and image quality improvement using iterative reconstruction, all of which require specific knowledge of tissue and organ systems within a CT image. The purpose of this study was to develop a fully automated Random Forest classifier algorithm for segmentation of neck-chest-abdomen-pelvis CT examinations based on pediatric and adult CT protocols. Seven materials were classified: background, lung/internal air or gas, fat, muscle, solid organ parenchyma, blood/contrast enhanced fluid, and bone tissue using Matlab and the TWS plugin of FIJI. The following classifier feature filters of TWS were investigated: minimum, maximum, mean, and variance evaluated over a voxel radius of 2 n , (n from 0 to 4), along with noise reduction and edge preserving filters: Gaussian, bilateral, Kuwahara, and anisotropic diffusion. The Random Forest algorithm used 200 trees with 2 features randomly selected per node. The optimized auto-segmentation algorithm resulted in 16 image features including features derived from maximum, mean, variance Gaussian and Kuwahara filters. Dice similarity coefficient (DSC) calculations between manually segmented and Random Forest algorithm segmented images from 21 patient image sections, were analyzed. The automated algorithm produced segmentation of seven material classes with a median DSC of 0.86  ±  0.03 for pediatric patient protocols, and 0.85  ±  0.04 for adult patient protocols. Additionally, 100 randomly selected patient examinations were segmented and analyzed, and a mean sensitivity of 0.91 (range: 0.82-0.98), specificity of 0.89 (range: 0.70-0.98), and accuracy of 0.90 (range: 0.76-0.98) were demonstrated. In this study, we demonstrate that this fully automated segmentation tool was able to produce fast and accurate segmentation of the neck and trunk of the body over a wide range of patient habitus and scan parameters.

  6. Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurement

    NASA Technical Reports Server (NTRS)

    Weimer, Daniel R.

    2001-01-01

    The first draft of a manuscript titled "Variable time delays in the propagation of the interplanetary magnetic field" has been completed, for submission to the Journal of Geophysical Research. In the preparation of this manuscript all data and analysis programs had been updated to the highest temporal resolution possible, at 16 seconds or better. The program which computes the "measured" IMF propagation time delays from these data has also undergone another improvement. In another significant development, a technique has been developed in order to predict IMF phase plane orientations, and the resulting time delays, using only measurements from a single satellite at L1. The "minimum variance" method is used for this computation. Further work will be done on optimizing the choice of several parameters for the minimum variance calculation.

  7. Iterative raw measurements restoration method with penalized weighted least squares approach for low-dose CT

    NASA Astrophysics Data System (ADS)

    Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu

    2014-03-01

    Statistical iterative reconstruction and post-log data restoration algorithms for CT noise reduction have been widely studied and these techniques have enabled us to reduce irradiation doses while maintaining image qualities. In low dose scanning, electronic noise becomes obvious and it results in some non-positive signals in raw measurements. The nonpositive signal should be converted to positive signal so that it can be log-transformed. Since conventional conversion methods do not consider local variance on the sinogram, they have difficulty of controlling the strength of the filtering. Thus, in this work, we propose a method to convert the non-positive signal to the positive signal by mainly controlling the local variance. The method is implemented in two separate steps. First, an iterative restoration algorithm based on penalized weighted least squares is used to mitigate the effect of electronic noise. The algorithm preserves the local mean and reduces the local variance induced by the electronic noise. Second, smoothed raw measurements by the iterative algorithm are converted to the positive signal according to a function which replaces the non-positive signal with its local mean. In phantom studies, we confirm that the proposed method properly preserves the local mean and reduce the variance induced by the electronic noise. Our technique results in dramatically reduced shading artifacts and can also successfully cooperate with the post-log data filter to reduce streak artifacts.

  8. Comparing closed quotient in children singers' voices as measured by high-speed-imaging, electroglottography, and inverse filtering.

    PubMed

    Mecke, Ann-Christine; Sundberg, Johan; Granqvist, Svante; Echternach, Matthias

    2012-01-01

    The closed quotient, i.e., the ratio between the closed phase and the period, is commonly studied in voice research. However, the term may refer to measures derived from different methods, such as inverse filtering, electroglottography or high-speed digital imaging (HSDI). This investigation compares closed quotient data measured by these three methods in two boy singers. Each singer produced sustained tones on two different pitches and a glissando. Audio, electroglottographic signal (EGG), and HSDI were recorded simultaneously. The audio signal was inverse filtered by means of the decap program; the closed phase was defined as the flat minimum portion of the flow glottogram. Glottal area was automatically measured in the high speed images by the built-in camera software, and the closed phase was defined as the flat minimum portion of the area-signal. The EGG-signal was analyzed in four different ways using the matlab open quotient interface. The closed quotient data taken from the EGG were found to be considerably higher than those obtained from inverse filtering. Also, substantial differences were found between the closed quotient derived from HSDI and those derived from inverse filtering. The findings illustrate the importance of distinguishing between these quotients. © 2012 Acoustical Society of America.

  9. Study of the use of a nonlinear, rate limited, filter on pilot control signals

    NASA Technical Reports Server (NTRS)

    Adams, J. J.

    1977-01-01

    The use of a filter on the pilot's control output could improve the performance of the pilot-aircraft system. What is needed is a filter with a sharp high frequency cut-off, no resonance peak, and a minimum of lag at low frequencies. The present investigation studies the usefulness of a nonlinear, rate limited, filter in performing the needed function. The nonlinear filter is compared with a linear, first order filter, and no filter. An analytical study using pilot models and a simulation study using experienced test pilots was performed. The results showed that the nonlinear filter does promote quick, steady maneuvering. It is shown that the nonlinear filter attenuates the high frequency remnant and adds less phase lag to the low frequency signal than does the linear filter. It is also shown that the rate limit in the nonlinear filter can be set to be too restrictive, causing an unstable pilot-aircraft system response.

  10. Precision of proportion estimation with binary compressed Raman spectrum.

    PubMed

    Réfrégier, Philippe; Scotté, Camille; de Aguiar, Hilton B; Rigneault, Hervé; Galland, Frédéric

    2018-01-01

    The precision of proportion estimation with binary filtering of a Raman spectrum mixture is analyzed when the number of binary filters is equal to the number of present species and when the measurements are corrupted with Poisson photon noise. It is shown that the Cramer-Rao bound provides a useful methodology to analyze the performance of such an approach, in particular when the binary filters are orthogonal. It is demonstrated that a simple linear mean square error estimation method is efficient (i.e., has a variance equal to the Cramer-Rao bound). Evolutions of the Cramer-Rao bound are analyzed when the measuring times are optimized or when the considered proportion for binary filter synthesis is not optimized. Two strategies for the appropriate choice of this considered proportion are also analyzed for the binary filter synthesis.

  11. The influence of SO4 and NO3 to the acidity (pH) of rainwater using minimum variance quadratic unbiased estimation (MIVQUE) and maximum likelihood methods

    NASA Astrophysics Data System (ADS)

    Dilla, Shintia Ulfa; Andriyana, Yudhie; Sudartianto

    2017-03-01

    Acid rain causes many bad effects in life. It is formed by two strong acids, sulfuric acid (H2SO4) and nitric acid (HNO3), where sulfuric acid is derived from SO2 and nitric acid from NOx {x=1,2}. The purpose of the research is to find out the influence of So4 and NO3 levels contained in the rain to the acidity (pH) of rainwater. The data are incomplete panel data with two-way error component model. The panel data is a collection of some of the observations that observed from time to time. It is said incomplete if each individual has a different amount of observation. The model used in this research is in the form of random effects model (REM). Minimum variance quadratic unbiased estimation (MIVQUE) is used to estimate the variance error components, while maximum likelihood estimation is used to estimate the parameters. As a result, we obtain the following model: Ŷ* = 0.41276446 - 0.00107302X1 + 0.00215470X2.

  12. Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

    DOE PAGES

    Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres; ...

    2014-10-23

    Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

  13. Pattern recognition with composite correlation filters designed with multi-object combinatorial optimization

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Awwal, Abdul; Diaz-Ramirez, Victor H.; Cuevas, Andres

    Composite correlation filters are used for solving a wide variety of pattern recognition problems. These filters are given by a combination of several training templates chosen by a designer in an ad hoc manner. In this work, we present a new approach for the design of composite filters based on multi-objective combinatorial optimization. Given a vast search space of training templates, an iterative algorithm is used to synthesize a filter with an optimized performance in terms of several competing criteria. Furthermore, by employing a suggested binary-search procedure a filter bank with a minimum number of filters can be constructed, formore » a prespecified trade-off of performance metrics. Computer simulation results obtained with the proposed method in recognizing geometrically distorted versions of a target in cluttered and noisy scenes are discussed and compared in terms of recognition performance and complexity with existing state-of-the-art filters.« less

  14. Vision Assisted Navigation for Miniature Unmanned Aerial Vehicles (MAVs)

    DTIC Science & Technology

    2009-11-01

    commanded to orbit a target of known location. The error in target geolocation is shown for 200 frames with filtering (dashed line) and without (solid...so the performance of the filter was determined by using the estimated poses to solve a geolocation problem. An MAV flying at an altitude of 70 meters... geolocation as well as significantly reducing the short-term variance in the estimates based on the GPS/IMU alone. Due to the nature of the autopilot

  15. Data Filtering of Western Hemisphere GOES Wildfire ABBA Products

    NASA Astrophysics Data System (ADS)

    Theisen, M.; Prins, E.; Schmidt, C.; Reid, J. S.; Hunter, J.; Westphal, D.

    2002-05-01

    The Fire Locating and Modeling of Burning Emissions (FLAMBE') project was developed to model biomass burning emissions, transport, and radiative effects in real time. The model relies on data from the Geostationary Operational Environment Satellites (GOES-8, GOES-10), that is generated by the Wildfire Automated Biomass Burning Algorithm (WF ABBA). In an attempt to develop the most accurate modeling system the data set needs to be filtered to distinguish the true fire pixels from false alarms. False alarms occur due to reflection of solar radiation off of standing water, surface structure variances, and heat anomalies. The Reoccurring Fire Filtering algorithm (ReFF) was developed to address such false alarms by filtering data dependent on reoccurrence, location in relation to region and satellite, as well as heat intensity. WF ABBA data for the year 2000 during the peak of the burning season were analyzed using ReFF. The analysis resulted in a 45% decrease in North America and only a 15% decrease in South America, respectively, in total fire pixel occurrence. The lower percentage decrease in South America is a result of fires burning for longer periods of time, less surface variance, as well as an increase in heat intensity of fires for that region. Also fires are so prevalent in the region that multiple fires may coexist in the same 4-kilometer pixel.

  16. Comparison of Gravity Wave Temperature Variances from Ray-Based Spectral Parameterization of Convective Gravity Wave Drag with AIRS Observations

    NASA Technical Reports Server (NTRS)

    Choi, Hyun-Joo; Chun, Hye-Yeong; Gong, Jie; Wu, Dong L.

    2012-01-01

    The realism of ray-based spectral parameterization of convective gravity wave drag, which considers the updated moving speed of the convective source and multiple wave propagation directions, is tested against the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite. Offline parameterization calculations are performed using the global reanalysis data for January and July 2005, and gravity wave temperature variances (GWTVs) are calculated at z = 2.5 hPa (unfiltered GWTV). AIRS-filtered GWTV, which is directly compared with AIRS, is calculated by applying the AIRS visibility function to the unfiltered GWTV. A comparison between the parameterization calculations and AIRS observations shows that the spatial distribution of the AIRS-filtered GWTV agrees well with that of the AIRS GWTV. However, the magnitude of the AIRS-filtered GWTV is smaller than that of the AIRS GWTV. When an additional cloud top gravity wave momentum flux spectrum with longer horizontal wavelength components that were obtained from the mesoscale simulations is included in the parameterization, both the magnitude and spatial distribution of the AIRS-filtered GWTVs from the parameterization are in good agreement with those of the AIRS GWTVs. The AIRS GWTV can be reproduced reasonably well by the parameterization not only with multiple wave propagation directions but also with two wave propagation directions of 45 degrees (northeast-southwest) and 135 degrees (northwest-southeast), which are optimally chosen for computational efficiency.

  17. Unstrained and strained flamelets for LES of premixed combustion

    NASA Astrophysics Data System (ADS)

    Langella, Ivan; Swaminathan, Nedunchezhian

    2016-05-01

    The unstrained and strained flamelet closures for filtered reaction rate in large eddy simulation (LES) of premixed flames are studied. The required sub-grid scale (SGS) PDF in these closures is presumed using the Beta function. The relative performances of these closures are assessed by comparing numerical results from large eddy simulations of piloted Bunsen flames of stoichiometric methane-air mixture with experimental measurements. The strained flamelets closure is observed to underestimate the burn rate and thus the reactive scalars mass fractions are under-predicted with an over-prediction of fuel mass fraction compared with the unstrained flamelet closure. The physical reasons for this relative behaviour are discussed. The results of unstrained flamelet closure compare well with experimental data. The SGS variance of the progress variable required for the presumed PDF is obtained by solving its transport equation. An order of magnitude analysis of this equation suggests that the commonly used algebraic model obtained by balancing source and sink in this transport equation does not hold. This algebraic model is shown to underestimate the SGS variance substantially and the implications of this variance model for the filtered reaction rate closures are highlighted.

  18. Reliability of reflectance measures in passive filters

    NASA Astrophysics Data System (ADS)

    Saldiva de André, Carmen Diva; Afonso de André, Paulo; Rocha, Francisco Marcelo; Saldiva, Paulo Hilário Nascimento; Carvalho de Oliveira, Regiani; Singer, Julio M.

    2014-08-01

    Measurements of optical reflectance in passive filters impregnated with a reactive chemical solution may be transformed to ozone concentrations via a calibration curve and constitute a low cost alternative for environmental monitoring, mainly to estimate human exposure. Given the possibility of errors caused by exposure bias, it is common to consider sets of m filters exposed during a certain period to estimate the latent reflectance on n different sample occasions at a certain location. Mixed models with sample occasions as random effects are useful to analyze data obtained under such setups. The intra-class correlation coefficient of the mean of the m measurements is an indicator of the reliability of the latent reflectance estimates. Our objective is to determine m in order to obtain a pre-specified reliability of the estimates, taking possible outliers into account. To illustrate the procedure, we consider an experiment conducted at the Laboratory of Experimental Air Pollution, University of São Paulo, Brazil (LPAE/FMUSP), where sets of m = 3 filters were exposed during 7 days on n = 9 different occasions at a certain location. The results show that the reliability of the latent reflectance estimates for each occasion obtained under homoskedasticity is km = 0.74. A residual analysis suggests that the within-occasion variance for two of the occasions should be different from the others. A refined model with two within-occasion variance components was considered, yielding km = 0.56 for these occasions and km = 0.87 for the remaining ones. To guarantee that all estimates have a reliability of at least 80% we require measurements on m = 10 filters on each occasion.

  19. Distributed Kalman filtering compared to Fourier domain preconditioned conjugate gradient for laser guide star tomography on extremely large telescopes.

    PubMed

    Gilles, Luc; Massioni, Paolo; Kulcsár, Caroline; Raynaud, Henri-François; Ellerbroek, Brent

    2013-05-01

    This paper discusses the performance and cost of two computationally efficient Fourier-based tomographic wavefront reconstruction algorithms for wide-field laser guide star (LGS) adaptive optics (AO). The first algorithm is the iterative Fourier domain preconditioned conjugate gradient (FDPCG) algorithm developed by Yang et al. [Appl. Opt.45, 5281 (2006)], combined with pseudo-open-loop control (POLC). FDPCG's computational cost is proportional to N log(N), where N denotes the dimensionality of the tomography problem. The second algorithm is the distributed Kalman filter (DKF) developed by Massioni et al. [J. Opt. Soc. Am. A28, 2298 (2011)], which is a noniterative spatially invariant controller. When implemented in the Fourier domain, DKF's cost is also proportional to N log(N). Both algorithms are capable of estimating spatial frequency components of the residual phase beyond the wavefront sensor (WFS) cutoff frequency thanks to regularization, thereby reducing WFS spatial aliasing at the expense of more computations. We present performance and cost analyses for the LGS multiconjugate AO system under design for the Thirty Meter Telescope, as well as DKF's sensitivity to uncertainties in wind profile prior information. We found that, provided the wind profile is known to better than 10% wind speed accuracy and 20 deg wind direction accuracy, DKF, despite its spatial invariance assumptions, delivers a significantly reduced wavefront error compared to the static FDPCG minimum variance estimator combined with POLC. Due to its nonsequential nature and high degree of parallelism, DKF is particularly well suited for real-time implementation on inexpensive off-the-shelf graphics processing units.

  20. Point process analysis of noise in early invertebrate vision

    PubMed Central

    Vinnicombe, Glenn

    2017-01-01

    Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps). Here, randomness of both the photon inputs (regarded as extrinsic noise) and the conversion process (intrinsic noise) are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance. This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder) filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this delay could potentially limit the speed at which invertebrates can respond to stimuli. Consequently, if one wants to increase visual fidelity, reducing the photoconversion lag is much more important than improving the regularity of the electrical signal. PMID:29077703

  1. A sensitivity analysis on the variability in accelerometer data processing for monitoring physical activity.

    PubMed

    Lee, Paul H

    2015-02-01

    Accelerometers are gaining popularity for measuring physical activity, but there are many different ways to process accelerometer data. A sensitivity analysis was conducted to study the effect of varying accelerometer data processing protocols on estimating the association between PA level and socio-demographic characteristics using the National Health and Nutrition Examination Survey (NHANES) accelerometer data. The NHANES waves 2003-2004 and 2005-2006 accelerometer data (n=14,072) were used to investigate the effect of changing the accelerometer non-wearing time and valid day definitions on the demographic composition of the filtered datasets and the association between physical activity (PA) and socio-demographic characteristics (sex, age, race, educational level, marital status). Under different filtering rules (minimum number of valid day and definition of non-wear time), the demographic characteristics of the final sample varied. The proportion of participants aged 20-29 decreased from 18.9% to 15.8% when the minimum number of valid days required increased from 1 to 4 (p for trend<0.001), whereas that for aged ≥70 years increased from 18.9% to 20.6% (p for trend<0.001). Furthermore, with different filters, the effect of these demographic variables and PA varied, with some variables being significant under certain filtering rules but becoming insignificant under some other rules. The sensitivity analysis showed that the significance of the association between socio-demographic variables and PA could be varied with the definition of non-wearing time and minimum number of valid days. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. Water sample filtration unit

    USGS Publications Warehouse

    Skougstad, M.W.; Scarbro, G.F.

    1968-01-01

    A readily portable, all plastic, pressure filtration unit is described which greatly facilitates rapid micropore membrane field filtration of up to several liters of water with a minimum risk of inorganic chemical alteration or contamination of the sample. The unit accommodates standard 10.2-cm. (4-inch) diameter filters. The storage and carrying case serves as a convenient filter stand for both field and laboratory use.

  3. 40 CFR 1065.308 - Continuous gas analyzer system-response and updating-recording verification-for gas analyzers not...

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... meets a minimum response time. You may use the results of this test to determine transformation time, t... you use any analog or real-time digital filters during emission testing, you must operate those... the rise time and fall time as needed. You may also configure analog or digital filters before...

  4. Yield modeling of acoustic charge transport transversal filters

    NASA Technical Reports Server (NTRS)

    Kenney, J. S.; May, G. S.; Hunt, W. D.

    1995-01-01

    This paper presents a yield model for acoustic charge transport transversal filters. This model differs from previous IC yield models in that it does not assume that individual failures of the nondestructive sensing taps necessarily cause a device failure. A redundancy in the number of taps included in the design is explained. Poisson statistics are used to describe the tap failures, weighted over a uniform defect density distribution. A representative design example is presented. The minimum number of taps needed to realize the filter is calculated, and tap weights for various numbers of redundant taps are calculated. The critical area for device failure is calculated for each level of redundancy. Yield is predicted for a range of defect densities and redundancies. To verify the model, a Monte Carlo simulation is performed on an equivalent circuit model of the device. The results of the yield model are then compared to the Monte Carlo simulation. Better than 95% agreement was obtained for the Poisson model with redundant taps ranging from 30% to 150% over the minimum.

  5. Diallel analysis for sex-linked and maternal effects.

    PubMed

    Zhu, J; Weir, B S

    1996-01-01

    Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

  6. Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

    NASA Technical Reports Server (NTRS)

    Lin, Qian; Allebach, Jan P.

    1990-01-01

    An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

  7. Mixed model approaches for diallel analysis based on a bio-model.

    PubMed

    Zhu, J; Weir, B S

    1996-12-01

    A MINQUE(1) procedure, which is minimum norm quadratic unbiased estimation (MINQUE) method with 1 for all the prior values, is suggested for estimating variance and covariance components in a bio-model for diallel crosses. Unbiasedness and efficiency of estimation were compared for MINQUE(1), restricted maximum likelihood (REML) and MINQUE theta which has parameter values for the prior values. MINQUE(1) is almost as efficient as MINQUE theta for unbiased estimation of genetic variance and covariance components. The bio-model is efficient and robust for estimating variance and covariance components for maternal and paternal effects as well as for nuclear effects. A procedure of adjusted unbiased prediction (AUP) is proposed for predicting random genetic effects in the bio-model. The jack-knife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects. Worked examples are given for estimation of variance and covariance components and for prediction of genetic merits.

  8. Minimum number of measurements for evaluating Bertholletia excelsa.

    PubMed

    Baldoni, A B; Tonini, H; Tardin, F D; Botelho, S C C; Teodoro, P E

    2017-09-27

    Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of Brazil nut tree (Bertholletia excelsa) genotypes based on fruit yield. For this, we assessed the number of fruits and dry mass of seeds of 75 Brazil nut genotypes, from native forest, located in the municipality of Itaúba, MT, for 5 years. To better estimate r, four procedures were used: analysis of variance (ANOVA), principal component analysis based on the correlation matrix (CPCOR), principal component analysis based on the phenotypic variance and covariance matrix (CPCOV), and structural analysis based on the correlation matrix (mean r - AECOR). There was a significant effect of genotypes and measurements, which reveals the need to study the minimum number of measurements for selecting superior Brazil nut genotypes for a production increase. Estimates of r by ANOVA were lower than those observed with the principal component methodology and close to AECOR. The CPCOV methodology provided the highest estimate of r, which resulted in a lower number of measurements needed to identify superior Brazil nut genotypes for the number of fruits and dry mass of seeds. Based on this methodology, three measurements are necessary to predict the true value of the Brazil nut genotypes with a minimum accuracy of 85%.

  9. Cooperative Estimation of Targets by Multiple Aircraft

    DTIC Science & Technology

    1980-06-01

    would be necessary first to modify the filter according to the third approach given in recommendation number one. 92 Bibliography 1. Aden , Timmy C...Description 1. QF(9) Q l.xlO 7 pos., vel . Disturbance noise 256. acc. strength assumed in filter, see 2., below 2. TQ* 0. sec Time at which to reset...pos., vel . QF to zero. 3. RR RR 900. Range measurementvariance. (30 ft, 10) 4. RE RVR 16.xlO 6 Elevation measurement variance. (4 mr, la) 5. RT RUR

  10. Investigation on the kurtosis filter and the derivation of convolutional sparse filter for impulsive signature enhancement

    NASA Astrophysics Data System (ADS)

    Jia, Xiaodong; Zhao, Ming; Di, Yuan; Jin, Chao; Lee, Jay

    2017-01-01

    Minimum Entropy Deconvolution (MED) filter, which is a non-parametric approach for impulsive signature detection, has been widely studied recently. Although the merits of the MED filter are manifold, this method tends to over highlight the dominant peaks and its performance becomes less stable when strong noise exists. In order to better understand the behavior of the MED filter, this study first investigated the mathematical fundamentals of the MED filter and then explained the reason why the MED filter tends to over highlight the dominant peaks. In order to pursue finer solutions for weak impulsive signature enhancement, the Convolutional Sparse Filter (CSF) is originally proposed in this work and the derivation of the CSF is presented in details. The superiority of the proposed CSF over the MED filter is validated by both simulated data and experimental data. The results demonstrate that CSF is an effective method for impulsive signature enhancement that could be applied in rotating machines for incipient fault detection.

  11. On the design of classifiers for crop inventories

    NASA Technical Reports Server (NTRS)

    Heydorn, R. P.; Takacs, H. C.

    1986-01-01

    Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

  12. A comparison of methods for DPLL loop filter design

    NASA Technical Reports Server (NTRS)

    Aguirre, S.; Hurd, W. J.; Kumar, R.; Statman, J.

    1986-01-01

    Four design methodologies for loop filters for a class of digital phase-locked loops (DPLLs) are presented. The first design maps an optimum analog filter into the digital domain; the second approach designs a filter that minimizes in discrete time weighted combination of the variance of the phase error due to noise and the sum square of the deterministic phase error component; the third method uses Kalman filter estimation theory to design a filter composed of a least squares fading memory estimator and a predictor. The last design relies on classical theory, including rules for the design of compensators. Linear analysis is used throughout the article to compare different designs, and includes stability, steady state performance and transient behavior of the loops. Design methodology is not critical when the loop update rate can be made high relative to loop bandwidth, as the performance approaches that of continuous time. For low update rates, however, the miminization method is significantly superior to the other methods.

  13. [Design Method Analysis and Performance Comparison of Wall Filter for Ultrasound Color Flow Imaging].

    PubMed

    Wang, Lutao; Xiao, Jun; Chai, Hua

    2015-08-01

    The successful suppression of clutter arising from stationary or slowly moving tissue is one of the key issues in medical ultrasound color blood imaging. Remaining clutter may cause bias in the mean blood frequency estimation and results in a potentially misleading description of blood-flow. In this paper, based on the principle of general wall-filter, the design process of three classes of filters, infinitely impulse response with projection initialization (Prj-IIR), polynomials regression (Pol-Reg), and eigen-based filters are previewed and analyzed. The performance of the filters was assessed by calculating the bias and variance of a mean blood velocity using a standard autocorrelation estimator. Simulation results show that the performance of Pol-Reg filter is similar to Prj-IIR filters. Both of them can offer accurate estimation of mean blood flow speed under steady clutter conditions, and the clutter rejection ability can be enhanced by increasing the ensemble size of Doppler vector. Eigen-based filters can effectively remove the non-stationary clutter component, and further improve the estimation accuracy for low speed blood flow signals. There is also no significant increase in computation complexity for eigen-based filters when the ensemble size is less than 10.

  14. Computationally efficient video restoration for Nyquist sampled imaging sensors combining an affine-motion-based temporal Kalman filter and adaptive Wiener filter.

    PubMed

    Rucci, Michael; Hardie, Russell C; Barnard, Kenneth J

    2014-05-01

    In this paper, we present a computationally efficient video restoration algorithm to address both blur and noise for a Nyquist sampled imaging system. The proposed method utilizes a temporal Kalman filter followed by a correlation-model based spatial adaptive Wiener filter (AWF). The Kalman filter employs an affine background motion model and novel process-noise variance estimate. We also propose and demonstrate a new multidelay temporal Kalman filter designed to more robustly treat local motion. The AWF is a spatial operation that performs deconvolution and adapts to the spatially varying residual noise left in the Kalman filter stage. In image areas where the temporal Kalman filter is able to provide significant noise reduction, the AWF can be aggressive in its deconvolution. In other areas, where less noise reduction is achieved with the Kalman filter, the AWF balances the deconvolution with spatial noise reduction. In this way, the Kalman filter and AWF work together effectively, but without the computational burden of full joint spatiotemporal processing. We also propose a novel hybrid system that combines a temporal Kalman filter and BM3D processing. To illustrate the efficacy of the proposed methods, we test the algorithms on both simulated imagery and video collected with a visible camera.

  15. The AGN fraction of submm-selected galaxies and contributions to the submm/mm-wave extragalactic background light

    NASA Astrophysics Data System (ADS)

    Serjeant, S.; Negrello, M.; Pearson, C.; Mortier, A.; Austermann, J.; Aretxaga, I.; Clements, D.; Chapman, S.; Dye, S.; Dunlop, J.; Dunne, L.; Farrah, D.; Hughes, D.; Lee, H.-M.; Matsuhara, H.; Ibar, E.; Im, M.; Jeong, W.-S.; Kim, S.; Oyabu, S.; Takagi, T.; Wada, T.; Wilson, G.; Vaccari, M.; Yun, M.

    2010-05-01

    We present a comparison of the SCUBA half degree extragalactic survey (SHADES) at 450 μm, 850 μm and 1100 μm with deep guaranteed time 15 μm AKARI FU-HYU survey data and Spitzer guaranteed time data at 3.6-24 μm in the Lockman hole east. The AKARI data was analysed using bespoke software based in part on the drizzling and minimum-variance matched filtering developed for SHADES, and was cross-calibrated against ISO fluxes. Our stacking analyses find AKARI 15 μm galaxies with ⪆200 μJy contribute >10% of the 450 μm background, but only <4% of the 1100 μm background, suggesting that different populations contribute at mm-wavelengths. We confirm our earlier result that the ultra-deep 450 μm SCUBA-2 cosmology survey will be dominated by populations already detected by AKARI and Spitzer mid-infrared surveys. The superb mid-infrared wavelength coverage afforded by combining Spitzer and AKARI photometry is an excellent diagnostic of AGN contributions, and we find that (23-52)% of submm-selected galaxies have AGN bolometric fractions fAGN > 0.3.

  16. Seasonal and height variation of gravity wave activities observed by a meteor radar at King Sejong Station (62°S, 57°W), Antarctica

    NASA Astrophysics Data System (ADS)

    Kim, Y.; Lee, C.; Kim, J.; Choi, J.; Jee, G.

    2010-12-01

    We have analyzed wind data from individual meteor echoes detected by a meteor radar at King Sejong Station, Antarctica to measure gravity wave activity in the mesopause region. Wind data in the meteor altitudes has been obtained routinely by the meteor radar since its installation in March 2007. The mean variances in the wind data that were filtered for large scale motions (mean winds and tides) can be regarded as the gravity wave activity. Monthly mean gravity wave activities show strong seasonal and height dependences in the altitude range of 80 to 100 km. The gravity wave activities except summer monotonically increase with altitude, which is expected since decreasing atmospheric densities cause wave amplitudes to increase. During summer (Dec. - Feb.) the height profiles of gravity wave activities show a minimum near 90 - 95 km, which may be due to different zonal wind and strong wind shear near 80 - 95 km. Our gravity wave activities are generally stronger than those of the Rothera station, implying sensitive dependency on location. The difference may be related to gravity wave sources in the lower atmosphere near Antarctic vortex.

  17. Discrete Inverse and State Estimation Problems

    NASA Astrophysics Data System (ADS)

    Wunsch, Carl

    2006-06-01

    The problems of making inferences about the natural world from noisy observations and imperfect theories occur in almost all scientific disciplines. This book addresses these problems using examples taken from geophysical fluid dynamics. It focuses on discrete formulations, both static and time-varying, known variously as inverse, state estimation or data assimilation problems. Starting with fundamental algebraic and statistical ideas, the book guides the reader through a range of inference tools including the singular value decomposition, Gauss-Markov and minimum variance estimates, Kalman filters and related smoothers, and adjoint (Lagrange multiplier) methods. The final chapters discuss a variety of practical applications to geophysical flow problems. Discrete Inverse and State Estimation Problems is an ideal introduction to the topic for graduate students and researchers in oceanography, meteorology, climate dynamics, and geophysical fluid dynamics. It is also accessible to a wider scientific audience; the only prerequisite is an understanding of linear algebra. Provides a comprehensive introduction to discrete methods of inference from incomplete information Based upon 25 years of practical experience using real data and models Develops sequential and whole-domain analysis methods from simple least-squares Contains many examples and problems, and web-based support through MIT opencourseware

  18. Source mechanism analysis of central Aceh earthquake July 2, 2013 Mw 6.2 using moment tensor inversion with BMKG waveform data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Prasetyo, Retno Agung, E-mail: prasetyo.agung@bmkg.go.id; Heryandoko, Nova; Afnimar

    The source mechanism of earthquake on July 2, 2013 was investigated by using moment tensor inversion. The result also compared by the field observation. Five waveform data of BMKG’s seismic network used to estimate the mechanism of earthquake, namely ; KCSI, MLSI, LASI, TPTI and SNSI. Main shock data taken during 200 seconds and filtered by using Butterworth band pass method from 0.03 to 0.05 Hz of frequency. Moment tensor inversion method is applied based on the point source assumption. Furthermore, the Green function calculated using the extended reflectivity method which modified by Kohketsu. The inversion result showed a strike-slipmore » faulting, where the nodal plane strike/dip/rake (124/80.6/152.8) and minimum variance value 0.3285 at a depth of 6 km (centroid). It categorized as a shallow earthquake. Field observation indicated that the building orientated to the east. It can be related to the southwest of dip direction which has 152 degrees of slip. As conclusion, the Pressure (P) and Tension (T) axis described dominant compression is happen from the south which is caused by pressure of the Indo-Australian plate.« less

  19. A multiscale filter for noise reduction of low-dose cone beam projections

    NASA Astrophysics Data System (ADS)

    Yao, Weiguang; Farr, Jonathan B.

    2015-08-01

    The Poisson or compound Poisson process governs the randomness of photon fluence in cone beam computed tomography (CBCT) imaging systems. The probability density function depends on the mean (noiseless) of the fluence at a certain detector. This dependence indicates the natural requirement of multiscale filters to smooth noise while preserving structures of the imaged object on the low-dose cone beam projection. In this work, we used a Gaussian filter, \\text{exp}≤ft(-{{x}2}/2σ f2\\right) as the multiscale filter to de-noise the low-dose cone beam projections. We analytically obtained the expression of {σf} , which represents the scale of the filter, by minimizing local noise-to-signal ratio. We analytically derived the variance of residual noise from the Poisson or compound Poisson processes after Gaussian filtering. From the derived analytical form of the variance of residual noise, optimal σ f2 is proved to be proportional to the noiseless fluence and modulated by local structure strength expressed as the linear fitting error of the structure. A strategy was used to obtain the reliable linear fitting error: smoothing the projection along the longitudinal direction to calculate the linear fitting error along the lateral direction and vice versa. The performance of our multiscale filter was examined on low-dose cone beam projections of a Catphan phantom and a head-and-neck patient. After performing the filter on the Catphan phantom projections scanned with pulse time 4 ms, the number of visible line pairs was similar to that scanned with 16 ms, and the contrast-to-noise ratio of the inserts was higher than that scanned with 16 ms about 64% in average. For the simulated head-and-neck patient projections with pulse time 4 ms, the visibility of soft tissue structures in the patient was comparable to that scanned with 20 ms. The image processing took less than 0.5 s per projection with 1024   ×   768 pixels.

  20. Modeling the subfilter scalar variance for large eddy simulation in forced isotropic turbulence

    NASA Astrophysics Data System (ADS)

    Cheminet, Adam; Blanquart, Guillaume

    2011-11-01

    Static and dynamic model for the subfilter scalar variance in homogeneous isotropic turbulence are investigated using direct numerical simulations (DNS) of a lineary forced passive scalar field. First, we introduce a new scalar forcing technique conditioned only on the scalar field which allows the fluctuating scalar field to reach a statistically stationary state. Statistical properties, including 2nd and 3rd statistical moments, spectra, and probability density functions of the scalar field have been analyzed. Using this technique, we performed constant density and variable density DNS of scalar mixing in isotropic turbulence. The results are used in an a-priori study of scalar variance models. Emphasis is placed on further studying the dynamic model introduced by G. Balarac, H. Pitsch and V. Raman [Phys. Fluids 20, (2008)]. Scalar variance models based on Bedford and Yeo's expansion are accurate for small filter width but errors arise in the inertial subrange. Results suggest that a constant coefficient computed from an assumed Kolmogorov spectrum is often sufficient to predict the subfilter scalar variance.

  1. Noise modeling and analysis of an IMU-based attitude sensor: improvement of performance by filtering and sensor fusion

    NASA Astrophysics Data System (ADS)

    K., Nirmal; A. G., Sreejith; Mathew, Joice; Sarpotdar, Mayuresh; Suresh, Ambily; Prakash, Ajin; Safonova, Margarita; Murthy, Jayant

    2016-07-01

    We describe the characterization and removal of noises present in the Inertial Measurement Unit (IMU) MPU- 6050, which was initially used in an attitude sensor, and later used in the development of a pointing system for small balloon-borne astronomical payloads. We found that the performance of the IMU degraded with time because of the accumulation of different errors. Using Allan variance analysis method, we identified the different components of noise present in the IMU, and verified the results by the power spectral density analysis (PSD). We tried to remove the high-frequency noise using smooth filters such as moving average filter and then Savitzky Golay (SG) filter. Even though we managed to filter some high-frequency noise, these filters performance wasn't satisfactory for our application. We found the distribution of the random noise present in IMU using probability density analysis and identified that the noise in our IMU was white Gaussian in nature. Hence, we used a Kalman filter to remove the noise and which gave us good performance real time.

  2. Design of coupled mace filters for optical pattern recognition using practical spatial light modulators

    NASA Technical Reports Server (NTRS)

    Rajan, P. K.; Khan, Ajmal

    1993-01-01

    Spatial light modulators (SLMs) are being used in correlation-based optical pattern recognition systems to implement the Fourier domain filters. Currently available SLMs have certain limitations with respect to the realizability of these filters. Therefore, it is necessary to incorporate the SLM constraints in the design of the filters. The design of a SLM-constrained minimum average correlation energy (SLM-MACE) filter using the simulated annealing-based optimization technique was investigated. The SLM-MACE filter was synthesized for three different types of constraints. The performance of the filter was evaluated in terms of its recognition (discrimination) capabilities using computer simulations. The correlation plane characteristics of the SLM-MACE filter were found to be reasonably good. The SLM-MACE filter yielded far better results than the analytical MACE filter implemented on practical SLMs using the constrained magnitude technique. Further, the filter performance was evaluated in the presence of noise in the input test images. This work demonstrated the need to include the SLM constraints in the filter design. Finally, a method is suggested to reduce the computation time required for the synthesis of the SLM-MACE filter.

  3. Minimum-variance Brownian motion control of an optically trapped probe.

    PubMed

    Huang, Yanan; Zhang, Zhipeng; Menq, Chia-Hsiang

    2009-10-20

    This paper presents a theoretical and experimental investigation of the Brownian motion control of an optically trapped probe. The Langevin equation is employed to describe the motion of the probe experiencing random thermal force and optical trapping force. Since active feedback control is applied to suppress the probe's Brownian motion, actuator dynamics and measurement delay are included in the equation. The equation of motion is simplified to a first-order linear differential equation and transformed to a discrete model for the purpose of controller design and data analysis. The derived model is experimentally verified by comparing the model prediction to the measured response of a 1.87 microm trapped probe subject to proportional control. It is then employed to design the optimal controller that minimizes the variance of the probe's Brownian motion. Theoretical analysis is derived to evaluate the control performance of a specific optical trap. Both experiment and simulation are used to validate the design as well as theoretical analysis, and to illustrate the performance envelope of the active control. Moreover, adaptive minimum variance control is implemented to maintain the optimal performance in the case in which the system is time varying when operating the actively controlled optical trap in a complex environment.

  4. Cost effective stream-gaging strategies for the Lower Colorado River basin; the Blythe field office operations

    USGS Publications Warehouse

    Moss, Marshall E.; Gilroy, Edward J.

    1980-01-01

    This report describes the theoretical developments and illustrates the applications of techniques that recently have been assembled to analyze the cost-effectiveness of federally funded stream-gaging activities in support of the Colorado River compact and subsequent adjudications. The cost effectiveness of 19 stream gages in terms of minimizing the sum of the variances of the errors of estimation of annual mean discharge is explored by means of a sequential-search optimization scheme. The search is conducted over a set of decision variables that describes the number of times that each gaging route is traveled in a year. A gage route is defined as the most expeditious circuit that is made from a field office to visit one or more stream gages and return to the office. The error variance is defined as a function of the frequency of visits to a gage by using optimal estimation theory. Currently a minimum of 12 visits per year is made to any gage. By changing to a six-visit minimum, the same total error variance can be attained for the 19 stations with a budget of 10% less than the current one. Other strategies are also explored. (USGS)

  5. River meanders - Theory of minimum variance

    USGS Publications Warehouse

    Langbein, Walter Basil; Leopold, Luna Bergere

    1966-01-01

    Meanders are the result of erosion-deposition processes tending toward the most stable form in which the variability of certain essential properties is minimized. This minimization involves the adjustment of the planimetric geometry and the hydraulic factors of depth, velocity, and local slope.The planimetric geometry of a meander is that of a random walk whose most frequent form minimizes the sum of the squares of the changes in direction in each successive unit length. The direction angles are then sine functions of channel distance. This yields a meander shape typically present in meandering rivers and has the characteristic that the ratio of meander length to average radius of curvature in the bend is 4.7.Depth, velocity, and slope are shown by field observations to be adjusted so as to decrease the variance of shear and the friction factor in a meander curve over that in an otherwise comparable straight reach of the same riverSince theory and observation indicate meanders achieve the minimum variance postulated, it follows that for channels in which alternating pools and riffles occur, meandering is the most probable form of channel geometry and thus is more stable geometry than a straight or nonmeandering alinement.

  6. Moving Bed Granular Bed Filter Development Program. Topical report, September 1994

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Haas, J.C.; Prudhomme, J.W.; Wilson, K.W.

    1994-09-01

    Five test arrangements have been designed to support the Granular Bed Filter Development Program as defined in the Test Plan. The first arrangement is a 3.6 ft. diameter half filter, with a glass covering along the cross section to allow visual examination of the granular alumina material passing through the filter. The second test arrangement is a 3.6 ft diameter full size filter having refractory lining to simulate actual surface roughness conditions. The third test arrangement will examine filter geometry scale up by testing a 6.0 ft. diameter full size filter. The fourth Test Arrangement consists of a small 12more » inch diameter fluidizer to measure the minimum fluidization velocity of the 7 m (approx. size) alumina material to be used in the filter assemblies. The last Test Unit is used to evaluation relative abrasion characteristics of potential refractory and ceramic materials to be installed in high abrasion areas in the pneumatic transport piping.« less

  7. RFI in hybrid loops - Simulation and experimental results.

    NASA Technical Reports Server (NTRS)

    Ziemer, R. E.; Nelson, D. R.; Raghavan, H. R.

    1972-01-01

    A digital simulation of an imperfect second-order hybrid phase-locked loop (HPLL) operating in radio frequency interference (RFI) is described. Its performance is characterized in terms of phase error variance and phase error probability density function (PDF). Monte-Carlo simulation is used to show that the HPLL can be superior to the conventional phase-locked loops in RFI backgrounds when minimum phase error variance is the goodness criterion. Similar experimentally obtained data are given in support of the simulation data.

  8. 40 CFR Appendix B to Part 50 - Reference Method for the Determination of Suspended Particulate Matter in the Atmosphere (High...

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... filters used are specified to have a minimum collection efficiency of 99 percent for 0.3 µm (DOP... electronic timers have much better set-point resolution than mechanical timers, but require a battery backup... Collection efficiency: 99 percent minimum as measured by the DOP test (ASTM-2986) for particles of 0.3 µm...

  9. 40 CFR Appendix B to Part 50 - Reference Method for the Determination of Suspended Particulate Matter in the Atmosphere (High...

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... filters used are specified to have a minimum collection efficiency of 99 percent for 0.3 µm (DOP... electronic timers have much better set-point resolution than mechanical timers, but require a battery backup... Collection efficiency: 99 percent minimum as measured by the DOP test (ASTM-2986) for particles of 0.3 µm...

  10. Eigenspace-based minimum variance adaptive beamformer combined with delay multiply and sum: experimental study

    NASA Astrophysics Data System (ADS)

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-02-01

    Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra, called EIBMV-DMAS, using the expansion of DMAS algorithm. The proposed method is used as the reconstruction algorithm in linear-array PAI. EIBMV-DMAS is experimentally evaluated where the quantitative and qualitative results show that it outperforms DAS, DMAS and EIBMV. The proposed method degrades the sidelobes for about 365 %, 221 % and 40 %, compared to DAS, DMAS and EIBMV, respectively. Moreover, EIBMV-DMAS improves the SNR about 158 %, 63 % and 20 %, respectively.

  11. Charged particle tracking at Titan, and further applications

    NASA Astrophysics Data System (ADS)

    Bebesi, Zsofia; Erdos, Geza; Szego, Karoly

    2016-04-01

    We use the CAPS ion data of Cassini to investigate the dynamics and origin of Titan's atmospheric ions. We developed a 4th order Runge-Kutta method to calculate particle trajectories in a time reversed scenario. The test particle magnetic field environment imitates the curved magnetic environment in the vicinity of Titan. The minimum variance directions along the S/C trajectory have been calculated for all available Titan flybys, and we assumed a homogeneous field that is perpendicular to the minimum variance direction. Using this method the magnetic field lines have been calculated along the flyby orbits so we could select those observational intervals when Cassini and the upper atmosphere of Titan were magnetically connected. We have also taken the Kronian magnetodisc into consideration, and used different upstream magnetic field approximations depending on whether Titan was located inside of the magnetodisc current sheet, or in the lobe regions. We also discuss the code's applicability to comets.

  12. Microstructure of the IMF turbulences at 2.5 AU

    NASA Technical Reports Server (NTRS)

    Mavromichalaki, H.; Vassilaki, A.; Marmatsouri, L.; Moussas, X.; Quenby, J. J.; Smith, E. J.

    1995-01-01

    A detailed analysis of small period (15-900 sec) magnetohydrodynamic (MHD) turbulences of the interplanetary magnetic field (IMF) has been made using Pioneer-11 high time resolution data (0.75 sec) inside a Corotating Interaction Region (CIR) at a heliocentric distance of 2.5 AU in 1973. The methods used are the hodogram analysis, the minimum variance matrix analysis and the cohenrence analysis. The minimum variance analysis gives evidence of linear polarized wave modes. Coherence analysis has shown that the field fluctuations are dominated by the magnetosonic fast modes with periods 15 sec to 15 min. However, it is also shown that some small amplitude Alfven waves are present in the trailing edge of this region with characteristic periods (15-200 sec). The observed wave modes are locally generated and possibly attributed to the scattering of Alfven waves energy into random magnetosonic waves.

  13. Optical tomographic detection of rheumatoid arthritis with computer-aided classification schemes

    NASA Astrophysics Data System (ADS)

    Klose, Christian D.; Klose, Alexander D.; Netz, Uwe; Beuthan, Jürgen; Hielscher, Andreas H.

    2009-02-01

    A recent research study has shown that combining multiple parameters, drawn from optical tomographic images, leads to better classification results to identifying human finger joints that are affected or not affected by rheumatic arthritis RA. Building up on the research findings of the previous study, this article presents an advanced computer-aided classification approach for interpreting optical image data to detect RA in finger joints. Additional data are used including, for example, maximum and minimum values of the absorption coefficient as well as their ratios and image variances. Classification performances obtained by the proposed method were evaluated in terms of sensitivity, specificity, Youden index and area under the curve AUC. Results were compared to different benchmarks ("gold standard"): magnet resonance, ultrasound and clinical evaluation. Maximum accuracies (AUC=0.88) were reached when combining minimum/maximum-ratios and image variances and using ultrasound as gold standard.

  14. An exact algorithm for optimal MAE stack filter design.

    PubMed

    Dellamonica, Domingos; Silva, Paulo J S; Humes, Carlos; Hirata, Nina S T; Barrera, Junior

    2007-02-01

    We propose a new algorithm for optimal MAE stack filter design. It is based on three main ingredients. First, we show that the dual of the integer programming formulation of the filter design problem is a minimum cost network flow problem. Next, we present a decomposition principle that can be used to break this dual problem into smaller subproblems. Finally, we propose a specialization of the network Simplex algorithm based on column generation to solve these smaller subproblems. Using our method, we were able to efficiently solve instances of the filter problem with window size up to 25 pixels. To the best of our knowledge, this is the largest dimension for which this problem was ever solved exactly.

  15. A Maximum Entropy Method for Particle Filtering

    NASA Astrophysics Data System (ADS)

    Eyink, Gregory L.; Kim, Sangil

    2006-06-01

    Standard ensemble or particle filtering schemes do not properly represent states of low priori probability when the number of available samples is too small, as is often the case in practical applications. We introduce here a set of parametric resampling methods to solve this problem. Motivated by a general H-theorem for relative entropy, we construct parametric models for the filter distributions as maximum-entropy/minimum-information models consistent with moments of the particle ensemble. When the prior distributions are modeled as mixtures of Gaussians, our method naturally generalizes the ensemble Kalman filter to systems with highly non-Gaussian statistics. We apply the new particle filters presented here to two simple test cases: a one-dimensional diffusion process in a double-well potential and the three-dimensional chaotic dynamical system of Lorenz.

  16. Geodesy by radio interferometry: Water vapor radiometry for estimation of the wet delay

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Elgered, G.; Davis, J.L.; Herring, T.A.

    1991-04-10

    An important source of error in very-long-baseline interferometry (VLBI) estimates of baseline length is unmodeled variations of the refractivity of the neutral atmosphere along the propagation path of the radio signals. The authors present and discuss the method of using data from a water vapor readiometer (WVR) to correct for the propagation delay caused by atmospheric water vapor, the major cause of these variations. Data from different WVRs are compared with estimated propagation delays obtained by Kalman filtering of the VLBI data themselves. The consequences of using either WVR data of Kalman filtering to correct for atmospheric propagation delay atmore » the Onsala VLBI site are investigated by studying the repeatability of estimated baseline lengths from Onsala to several other sites. The lengths of the baselines range from 919 to 7,941 km. The repeatability obtained for baseline length estimates shows that the methods of water vapor radiometry and Kalman filtering offer comparable accuracies when applied to VLBI observations obtained in the climate of the Swedish west coast. The use of WVR data yielded a 13% smaller weighted-root-mean-square (WRMS) scatter of the baseline length estimates compared to the use of a Kalman filter. It is also clear that the best minimum elevation angle for VLBI observations depends on the accuracy of the determinations of the total propagation delay to be used, since the error in this delay increases with increasing air mass. For use of WVR data along with accurate determinations of total surface pressure, the best minimum is about 20{degrees}; for use of a model for the wet delay based on the humidity and temperature at the ground, the best minimum is about 35{degrees}.« less

  17. Adaptation to Variance of Stimuli in Drosophila Larva Navigation

    NASA Astrophysics Data System (ADS)

    Wolk, Jason; Gepner, Ruben; Gershow, Marc

    In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.

  18. Improved virus removal in ceramic depth filters modified with MgO.

    PubMed

    Michen, Benjamin; Fritsch, Johannes; Aneziris, Christos; Graule, Thomas

    2013-02-05

    Ceramic filters, working on the depth filtration principle, are known to improve drinking water quality by removing human pathogenic microorganisms from contaminated water. However, these microfilters show no sufficient barrier for viruses having diameters down to 20 nm. Recently, it was shown that the addition of positively charged materials, for example, iron oxyhydroxide, can improve virus removal by adsorption mechanisms. In this work, we modified a common ceramic filter based on diatomaceous earth by introducing a novel virus adsorbent material, magnesium oxyhydroxide, into the filter matrix. Such filters showed an improved removal of about 4-log in regard to bacteriophages MS2 and PhiX174. This is explained with the electrostatic enhanced adsorption approach that is the favorable adsorption of negatively charged viruses onto positively charged patches in an otherwise negatively charged filter matrix. Furthermore, we provide theoretical evidence applying calculations according to Derjaguin-Landau-Verwey-Overbeek theory to strengthen our experimental results. However, modified filters showed a significant variance in virus removal efficiency over the course of long-term filtration experiments with virus removal increasing with filter operation time (or filter aging). This is explained by transformational changes of MgO in the filter upon contact with water. It also demonstrates that filter history is of great concern when filters working on the adsorption principles are evaluated in regard to their retention performance as their surface characteristics may alter with use.

  19. Detection of large scale geomagnetic pulsations by MAGDAS-egypt stations during the solar minimum of the solar cycle 24

    NASA Astrophysics Data System (ADS)

    Fathy, Ibrahim

    2016-07-01

    This paper presents a statistical study of different types of large-scale geomagnetic pulsation (Pc3, Pc4, Pc5 and Pi2) detected simultaneously by two MAGDAS stations located at Fayum (Geo. Coordinates 29.18 N and 30.50 E) and Aswan (Geo. Coordinates 23.59 N and 32.51 E) in Egypt. The second order butter-worth band-pass filter has been used to filter and analyze the horizontal H-component of the geomagnetic field in one-second data. The data was collected during the solar minimum of the current solar cycle 24. We list the most energetic pulsations detected by the two stations instantaneously, in addition; the average amplitude of the pulsation signals was calculated.

  20. Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

    NASA Technical Reports Server (NTRS)

    Semper, Sean R.; Crassidis, John L.; George, Jemin; Mukherjee, Siddharth; Singla, Puneet

    2015-01-01

    When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

  1. Impact of the air filtration on indoor particle concentration by using combination filters in offices building

    NASA Astrophysics Data System (ADS)

    Kabrein, H.; Hariri, A.; Leman, A. M.; Noraini, N. M. R.; Yusof, M. Z. M.; Afandi, A.

    2017-09-01

    Heating ventilation and air conditioning system (HVAC) is very important for offices building and human health. The combining filter method was used to reduce the air pollution indoor such as that particulate matter and gases pollution that affected in health and productivity. Using particle filters in industrial HVAC systems (factories and manufacturing process) does not enough to remove all the indoor pollution. The main objective of this study is to investigate the impact of combination filters for particle and gases removal efficiency. The combining method is by using two filters (particulate filter pre-filter and carbon filter) to reduce particle matter and gases respectively. The purpose of this study is to use minimum efficiency reporting value (MERV filter) rating 13 and activated carbon filter (ACF) to remove indoor air pollution and controlling the air change rate to enhance the air quality and energy saving. It was concluded that the combination filter showed good removal efficiency of particle up to 90.76% and 89.25% for PM10 and PM2.5 respectively. The pressure drop across the filters was small compared with the high-efficiency filters. The filtration efficiency of combination filters after three months’ was better than efficiency by the new MERV filter alone.

  2. Control algorithms for dynamic attenuators.

    PubMed

    Hsieh, Scott S; Pelc, Norbert J

    2014-06-01

    The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not require a priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without increasing peak variance. The 15-element piecewise-linear dynamic attenuator reduces dose by an average of 42%, and the perfect attenuator reduces dose by an average of 50%. Improvements in peak variance are several times larger than improvements in mean variance. Heuristic control eliminates the need for a prescan. For the piecewise-linear attenuator, the cost of heuristic control is an increase in dose of 9%. The proposed iterated WMV minimization produces results that are within a few percent of the true solution. Dynamic attenuators show potential for significant dose reduction. A wide class of dynamic attenuators can be accurately controlled using the described methods.

  3. Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter

    NASA Astrophysics Data System (ADS)

    Moaveni, Bijan; Khosravi Roqaye Abad, Mahdi; Nasiri, Sayyad

    2015-10-01

    In this paper, vehicle longitudinal velocity during the braking process is estimated by measuring the wheels speed. Here, a new algorithm based on the unknown input Kalman filter is developed to estimate the vehicle longitudinal velocity with a minimum mean square error and without using the value of braking torque in the estimation procedure. The stability and convergence of the filter are analysed and proved. Effectiveness of the method is shown by designing a real experiment and comparing the estimation result with actual longitudinal velocity computing from a three-axis accelerometer output.

  4. CUDA-based acceleration and BPN-assisted automation of bilateral filtering for brain MR image restoration.

    PubMed

    Chang, Herng-Hua; Chang, Yu-Ning

    2017-04-01

    Bilateral filters have been substantially exploited in numerous magnetic resonance (MR) image restoration applications for decades. Due to the deficiency of theoretical basis on the filter parameter setting, empirical manipulation with fixed values and noise variance-related adjustments has generally been employed. The outcome of these strategies is usually sensitive to the variation of the brain structures and not all the three parameter values are optimal. This article is in an attempt to investigate the optimal setting of the bilateral filter, from which an accelerated and automated restoration framework is developed. To reduce the computational burden of the bilateral filter, parallel computing with the graphics processing unit (GPU) architecture is first introduced. The NVIDIA Tesla K40c GPU with the compute unified device architecture (CUDA) functionality is specifically utilized to emphasize thread usages and memory resources. To correlate the filter parameters with image characteristics for automation, optimal image texture features are subsequently acquired based on the sequential forward floating selection (SFFS) scheme. Subsequently, the selected features are introduced into the back propagation network (BPN) model for filter parameter estimation. Finally, the k-fold cross validation method is adopted to evaluate the accuracy of the proposed filter parameter prediction framework. A wide variety of T1-weighted brain MR images with various scenarios of noise levels and anatomic structures were utilized to train and validate this new parameter decision system with CUDA-based bilateral filtering. For a common brain MR image volume of 256 × 256 × 256 pixels, the speed-up gain reached 284. Six optimal texture features were acquired and associated with the BPN to establish a "high accuracy" parameter prediction system, which achieved a mean absolute percentage error (MAPE) of 5.6%. Automatic restoration results on 2460 brain MR images received an average relative error in terms of peak signal-to-noise ratio (PSNR) less than 0.1%. In comparison with many state-of-the-art filters, the proposed automation framework with CUDA-based bilateral filtering provided more favorable results both quantitatively and qualitatively. Possessing unique characteristics and demonstrating exceptional performances, the proposed CUDA-based bilateral filter adequately removed random noise in multifarious brain MR images for further study in neurosciences and radiological sciences. It requires no prior knowledge of the noise variance and automatically restores MR images while preserving fine details. The strategy of exploiting the CUDA to accelerate the computation and incorporating texture features into the BPN to completely automate the bilateral filtering process is achievable and validated, from which the best performance is reached. © 2017 American Association of Physicists in Medicine.

  5. Contrasts between estimates of baseflow help discern multiple sources of water contributing to rivers

    NASA Astrophysics Data System (ADS)

    Cartwright, I.; Gilfedder, B.; Hofmann, H.

    2014-01-01

    This study compares baseflow estimates using chemical mass balance, local minimum methods, and recursive digital filters in the upper reaches of the Barwon River, southeast Australia. During the early stages of high-discharge events, the chemical mass balance overestimates groundwater inflows, probably due to flushing of saline water from wetlands and marshes, soils, or the unsaturated zone. Overall, however, estimates of baseflow from the local minimum and recursive digital filters are higher than those based on chemical mass balance using Cl calculated from continuous electrical conductivity measurements. Between 2001 and 2011, the baseflow contribution to the upper Barwon River calculated using chemical mass balance is between 12 and 25% of the annual discharge with a net baseflow contribution of 16% of total discharge. Recursive digital filters predict higher baseflow contributions of 19 to 52% of discharge annually with a net baseflow contribution between 2001 and 2011 of 35% of total discharge. These estimates are similar to those from the local minimum method (16 to 45% of annual discharge and 26% of total discharge). These differences most probably reflect how the different techniques characterise baseflow. The local minimum and recursive digital filters probably aggregate much of the water from delayed sources as baseflow. However, as many delayed transient water stores (such as bank return flow, floodplain storage, or interflow) are likely to be geochemically similar to surface runoff, chemical mass balance calculations aggregate them with the surface runoff component. The difference between the estimates is greatest following periods of high discharge in winter, implying that these transient stores of water feed the river for several weeks to months at that time. Cl vs. discharge variations during individual flow events also demonstrate that inflows of high-salinity older water occurs on the rising limbs of hydrographs followed by inflows of low-salinity water from the transient stores as discharge falls. The joint use of complementary techniques allows a better understanding of the different components of water that contribute to river flow, which is important for the management and protection of water resources.

  6. Adaptive Fading Memory H∞ Filter Design for Compensation of Delayed Components in Self Powered Flux Detectors

    NASA Astrophysics Data System (ADS)

    Tamboli, Prakash Kumar; Duttagupta, Siddhartha P.; Roy, Kallol

    2015-08-01

    The paper deals with dynamic compensation of delayed Self Powered Flux Detectors (SPFDs) using discrete time H∞ filtering method for improving the response of SPFDs with significant delayed components such as Platinum and Vanadium SPFD. We also present a comparative study between the Linear Matrix Inequality (LMI) based H∞ filtering and Algebraic Riccati Equation (ARE) based Kalman filtering methods with respect to their delay compensation capabilities. Finally an improved recursive H∞ filter based on the adaptive fading memory technique is proposed which provides an improved performance over existing methods. The existing delay compensation algorithms do not account for the rate of change in the signal for determining the filter gain and therefore add significant noise during the delay compensation process. The proposed adaptive fading memory H∞ filter minimizes the overall noise very effectively at the same time keeps the response time at minimum values. The recursive algorithm is easy to implement in real time as compared to the LMI (or ARE) based solutions.

  7. Maximum correntropy square-root cubature Kalman filter with application to SINS/GPS integrated systems.

    PubMed

    Liu, Xi; Qu, Hua; Zhao, Jihong; Yue, Pengcheng

    2018-05-31

    For a nonlinear system, the cubature Kalman filter (CKF) and its square-root version are useful methods to solve the state estimation problems, and both can obtain good performance in Gaussian noises. However, their performances often degrade significantly in the face of non-Gaussian noises, particularly when the measurements are contaminated by some heavy-tailed impulsive noises. By utilizing the maximum correntropy criterion (MCC) to improve the robust performance instead of traditional minimum mean square error (MMSE) criterion, a new square-root nonlinear filter is proposed in this study, named as the maximum correntropy square-root cubature Kalman filter (MCSCKF). The new filter not only retains the advantage of square-root cubature Kalman filter (SCKF), but also exhibits robust performance against heavy-tailed non-Gaussian noises. A judgment condition that avoids numerical problem is also given. The results of two illustrative examples, especially the SINS/GPS integrated systems, demonstrate the desirable performance of the proposed filter. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  8. SPA- STATISTICAL PACKAGE FOR TIME AND FREQUENCY DOMAIN ANALYSIS

    NASA Technical Reports Server (NTRS)

    Brownlow, J. D.

    1994-01-01

    The need for statistical analysis often arises when data is in the form of a time series. This type of data is usually a collection of numerical observations made at specified time intervals. Two kinds of analysis may be performed on the data. First, the time series may be treated as a set of independent observations using a time domain analysis to derive the usual statistical properties including the mean, variance, and distribution form. Secondly, the order and time intervals of the observations may be used in a frequency domain analysis to examine the time series for periodicities. In almost all practical applications, the collected data is actually a mixture of the desired signal and a noise signal which is collected over a finite time period with a finite precision. Therefore, any statistical calculations and analyses are actually estimates. The Spectrum Analysis (SPA) program was developed to perform a wide range of statistical estimation functions. SPA can provide the data analyst with a rigorous tool for performing time and frequency domain studies. In a time domain statistical analysis the SPA program will compute the mean variance, standard deviation, mean square, and root mean square. It also lists the data maximum, data minimum, and the number of observations included in the sample. In addition, a histogram of the time domain data is generated, a normal curve is fit to the histogram, and a goodness-of-fit test is performed. These time domain calculations may be performed on both raw and filtered data. For a frequency domain statistical analysis the SPA program computes the power spectrum, cross spectrum, coherence, phase angle, amplitude ratio, and transfer function. The estimates of the frequency domain parameters may be smoothed with the use of Hann-Tukey, Hamming, Barlett, or moving average windows. Various digital filters are available to isolate data frequency components. Frequency components with periods longer than the data collection interval are removed by least-squares detrending. As many as ten channels of data may be analyzed at one time. Both tabular and plotted output may be generated by the SPA program. This program is written in FORTRAN IV and has been implemented on a CDC 6000 series computer with a central memory requirement of approximately 142K (octal) of 60 bit words. This core requirement can be reduced by segmentation of the program. The SPA program was developed in 1978.

  9. Astronomical calibration and global correlation of the Santonian (Cretaceous) based on the marine carbon isotope record

    NASA Astrophysics Data System (ADS)

    Thibault, N.; Jarvis, I.; Voigt, S.; Gale, A. S.; Attree, K.; Jenkyns, H. C.

    2016-06-01

    High-resolution records of bulk carbonate carbon isotopes have been generated for the Upper Coniacian to Lower Campanian interval of the sections at Seaford Head (southern England) and Bottaccione (central Italy). An unambiguous stratigraphic correlation is presented for the base and top of the Santonian between the Boreal and Tethyan realms. Orbital forcing of carbon and oxygen isotopes at Seaford Head points to the Boreal Santonian spanning five 405 kyr cycles (Sa1 to Sa5). Correlation of the Seaford Head time scale to that of the Niobrara Formation (Western Interior Basin) permits anchoring these records to the La2011 astronomical solution at the Santonian-Campanian (Sa/Ca) boundary, which has been recently dated to 84.19 ± 0.38 Ma. Among the five tuning options examined, option 2 places the Sa/Ca at the 84.2 Ma 405 kyr insolation minimum and appears as the most likely. This solution indicates that minima of the 405 kyr filtered output of the resistivity in the Niobrara Formation correlate to 405 kyr insolation minima in the astronomical solution and to maxima in the filtered δ13C of Seaford Head. We suggest that variance in δ13C is driven by climate forcing of the proportions of CaCO3 versus organic carbon burial on land and in oceanic basins. The astronomical calibration generates a 200 kyr mismatch of the Coniacian-Santonian boundary age between the Boreal Realm in Europe and the Western Interior, due either to diachronism of the lowest occurrence of the inoceramid Cladoceramus undulatoplicatus between the two regions or to remaining uncertainties of radiometric dating and cyclostratigraphic records.

  10. Optimal multi-type sensor placement for response and excitation reconstruction

    NASA Astrophysics Data System (ADS)

    Zhang, C. D.; Xu, Y. L.

    2016-01-01

    The need to perform dynamic response reconstruction always arises as the measurement of structural response is often limited to a few locations, especially for a large civil structure. Besides, it is usually very difficult, if not impossible, to measure external excitations under the operation condition of a structure. This study presents an algorithm for optimal placement of multi-type sensors, including strain gauges, displacement transducers and accelerometers, for the best reconstruction of responses of key structural components where there are no sensors installed and the best estimation of external excitations acting on the structure at the same time. The algorithm is developed in the framework of Kalman filter with unknown excitation, in which minimum-variance unbiased estimates of the generalized state of the structure and the external excitations are obtained by virtue of limited sensor measurements. The structural responses of key locations without sensors can then be reconstructed with the estimated generalized state and excitation. The asymptotic stability feature of the filter is utilized for optimal sensor placement. The number and spatial location of the multi-type sensors are determined by adding the optimal sensor which gains the maximal reduction of the estimation error of reconstructed responses. For the given mode number in response reconstruction and the given locations of external excitations, the optimal multi-sensor placement achieved by the proposed method is independent of the type and time evolution of external excitation. A simply-supported overhanging steel beam under multiple types of excitation is numerically studied to demonstrate the feasibility and superiority of the proposed method, and the experimental work is then carried out to testify the effectiveness of the proposed method.

  11. Designing an Inverter-based Operational Transconductance Amplifier-capacitor Filter with Low Power Consumption for Biomedical Applications

    PubMed Central

    Yousefinezhad, Sajad; Kermani, Saeed; Hosseinnia, Saeed

    2018-01-01

    The operational transconductance amplifier-capacitor (OTA-C) filter is one of the best structures for implementing continuous-time filters. It is particularly important to design a universal OTA-C filter capable of generating the desired filter response via a single structure, thus reducing the filter circuit power consumption as well as noise and the occupied space on the electronic chip. In this study, an inverter-based universal OTA-C filter with very low power consumption and acceptable noise was designed with applications in bioelectric and biomedical equipment for recording biomedical signals. The very low power consumption of the proposed filter was achieved through introducing bias in subthreshold MOSFET transistors. The proposed filter is also capable of simultaneously receiving favorable low-, band-, and high-pass filter responses. The performance of the proposed filter was simulated and analyzed via HSPICE software (level 49) and 180 nm complementary metal-oxide-semiconductor technology. The rate of power consumption and noise obtained from simulations are 7.1 nW and 10.18 nA, respectively, so this filter has reduced noise as well as power consumption. The proposed universal OTA-C filter was designed based on the minimum number of transconductance blocks and an inverter circuit by three transconductance blocks (OTA). PMID:29535925

  12. Designing an Inverter-based Operational Transconductance Amplifier-capacitor Filter with Low Power Consumption for Biomedical Applications.

    PubMed

    Yousefinezhad, Sajad; Kermani, Saeed; Hosseinnia, Saeed

    2018-01-01

    The operational transconductance amplifier-capacitor (OTA-C) filter is one of the best structures for implementing continuous-time filters. It is particularly important to design a universal OTA-C filter capable of generating the desired filter response via a single structure, thus reducing the filter circuit power consumption as well as noise and the occupied space on the electronic chip. In this study, an inverter-based universal OTA-C filter with very low power consumption and acceptable noise was designed with applications in bioelectric and biomedical equipment for recording biomedical signals. The very low power consumption of the proposed filter was achieved through introducing bias in subthreshold MOSFET transistors. The proposed filter is also capable of simultaneously receiving favorable low-, band-, and high-pass filter responses. The performance of the proposed filter was simulated and analyzed via HSPICE software (level 49) and 180 nm complementary metal-oxide-semiconductor technology. The rate of power consumption and noise obtained from simulations are 7.1 nW and 10.18 nA, respectively, so this filter has reduced noise as well as power consumption. The proposed universal OTA-C filter was designed based on the minimum number of transconductance blocks and an inverter circuit by three transconductance blocks (OTA).

  13. Modification and fixed-point analysis of a Kalman filter for orientation estimation based on 9D inertial measurement unit data.

    PubMed

    Brückner, Hans-Peter; Spindeldreier, Christian; Blume, Holger

    2013-01-01

    A common approach for high accuracy sensor fusion based on 9D inertial measurement unit data is Kalman filtering. State of the art floating-point filter algorithms differ in their computational complexity nevertheless, real-time operation on a low-power microcontroller at high sampling rates is not possible. This work presents algorithmic modifications to reduce the computational demands of a two-step minimum order Kalman filter. Furthermore, the required bit-width of a fixed-point filter version is explored. For evaluation real-world data captured using an Xsens MTx inertial sensor is used. Changes in computational latency and orientation estimation accuracy due to the proposed algorithmic modifications and fixed-point number representation are evaluated in detail on a variety of processing platforms enabling on-board processing on wearable sensor platforms.

  14. Filtering Drifter Trajectories Sampled at Submesoscale Resolution

    DTIC Science & Technology

    2015-05-11

    bution. The modification allows PE variances to change in time through parameterization (10) with the cutoff scale 1.56 10 ms , corresponding to the...more sophisticated real-time ionosphere correction algo- rithms. We consider this study to be an attempt at improving the quality of the drifter data

  15. The EM Method in a Probabilistic Wavelet-Based MRI Denoising

    PubMed Central

    2015-01-01

    Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images. PMID:26089959

  16. The EM Method in a Probabilistic Wavelet-Based MRI Denoising.

    PubMed

    Martin-Fernandez, Marcos; Villullas, Sergio

    2015-01-01

    Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images.

  17. Analysis and Design of Launch Vehicle Flight Control Systems

    NASA Technical Reports Server (NTRS)

    Wie, Bong; Du, Wei; Whorton, Mark

    2008-01-01

    This paper describes the fundamental principles of launch vehicle flight control analysis and design. In particular, the classical concept of "drift-minimum" and "load-minimum" control principles is re-examined and its performance and stability robustness with respect to modeling uncertainties and a gimbal angle constraint is discussed. It is shown that an additional feedback of angle-of-attack or lateral acceleration can significantly improve the overall performance and robustness, especially in the presence of unexpected large wind disturbance. Non-minimum-phase structural filtering of "unstably interacting" bending modes of large flexible launch vehicles is also shown to be effective and robust.

  18. An Attitude Filtering and Magnetometer Calibration Approach for Nanosatellites

    NASA Astrophysics Data System (ADS)

    Söken, Halil Ersin

    2018-04-01

    We propose an attitude filtering and magnetometer calibration approach for nanosatellites. Measurements from magnetometers, Sun sensor and gyros are used in the filtering algorithm to estimate the attitude of the satellite together with the bias terms for the gyros and magnetometers. In the traditional approach for the attitude filtering, the attitude sensor measurements are used in the filter with a nonlinear vector measurement model. In the proposed algorithm, the TRIAD algorithm is used in conjunction with the unscented Kalman filter (UKF) to form the nontraditional attitude filter. First the vector measurements from the magnetometer and Sun sensor are processed with the TRIAD algorithm to obtain a coarse attitude estimate for the spacecraft. In the second phase the estimated coarse attitude is used as quaternion measurements for the UKF. The UKF estimates the fine attitude, and the gyro and magnetometer biases. We evaluate the algorithm for a hypothetical nanosatellite by numerical simulations. The results show that the attitude of the satellite can be estimated with an accuracy better than 0.5{°} and the computational load decreases more than 25% compared to a traditional UKF algorithm. We discuss the algorithm's performance in case of a time-variance in the magnetometer errors.

  19. Optimal Filter Estimation for Lucas-Kanade Optical Flow

    PubMed Central

    Sharmin, Nusrat; Brad, Remus

    2012-01-01

    Optical flow algorithms offer a way to estimate motion from a sequence of images. The computation of optical flow plays a key-role in several computer vision applications, including motion detection and segmentation, frame interpolation, three-dimensional scene reconstruction, robot navigation and video compression. In the case of gradient based optical flow implementation, the pre-filtering step plays a vital role, not only for accurate computation of optical flow, but also for the improvement of performance. Generally, in optical flow computation, filtering is used at the initial level on original input images and afterwards, the images are resized. In this paper, we propose an image filtering approach as a pre-processing step for the Lucas-Kanade pyramidal optical flow algorithm. Based on a study of different types of filtering methods and applied on the Iterative Refined Lucas-Kanade, we have concluded on the best filtering practice. As the Gaussian smoothing filter was selected, an empirical approach for the Gaussian variance estimation was introduced. Tested on the Middlebury image sequences, a correlation between the image intensity value and the standard deviation value of the Gaussian function was established. Finally, we have found that our selection method offers a better performance for the Lucas-Kanade optical flow algorithm.

  20. Aperture averaging in strong oceanic turbulence

    NASA Astrophysics Data System (ADS)

    Gökçe, Muhsin Caner; Baykal, Yahya

    2018-04-01

    Receiver aperture averaging technique is employed in underwater wireless optical communication (UWOC) systems to mitigate the effects of oceanic turbulence, thus to improve the system performance. The irradiance flux variance is a measure of the intensity fluctuations on a lens of the receiver aperture. Using the modified Rytov theory which uses the small-scale and large-scale spatial filters, and our previously presented expression that shows the atmospheric structure constant in terms of oceanic turbulence parameters, we evaluate the irradiance flux variance and the aperture averaging factor of a spherical wave in strong oceanic turbulence. Irradiance flux variance variations are examined versus the oceanic turbulence parameters and the receiver aperture diameter are examined in strong oceanic turbulence. Also, the effect of the receiver aperture diameter on the aperture averaging factor is presented in strong oceanic turbulence.

  1. The use of spatio-temporal correlation to forecast critical transitions

    NASA Astrophysics Data System (ADS)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

  2. An analytic technique for statistically modeling random atomic clock errors in estimation

    NASA Technical Reports Server (NTRS)

    Fell, P. J.

    1981-01-01

    Minimum variance estimation requires that the statistics of random observation errors be modeled properly. If measurements are derived through the use of atomic frequency standards, then one source of error affecting the observable is random fluctuation in frequency. This is the case, for example, with range and integrated Doppler measurements from satellites of the Global Positioning and baseline determination for geodynamic applications. An analytic method is presented which approximates the statistics of this random process. The procedure starts with a model of the Allan variance for a particular oscillator and develops the statistics of range and integrated Doppler measurements. A series of five first order Markov processes is used to approximate the power spectral density obtained from the Allan variance.

  3. Approximate sample size formulas for the two-sample trimmed mean test with unequal variances.

    PubMed

    Luh, Wei-Ming; Guo, Jiin-Huarng

    2007-05-01

    Yuen's two-sample trimmed mean test statistic is one of the most robust methods to apply when variances are heterogeneous. The present study develops formulas for the sample size required for the test. The formulas are applicable for the cases of unequal variances, non-normality and unequal sample sizes. Given the specified alpha and the power (1-beta), the minimum sample size needed by the proposed formulas under various conditions is less than is given by the conventional formulas. Moreover, given a specified size of sample calculated by the proposed formulas, simulation results show that Yuen's test can achieve statistical power which is generally superior to that of the approximate t test. A numerical example is provided.

  4. Software for the grouped optimal aggregation technique

    NASA Technical Reports Server (NTRS)

    Brown, P. M.; Shaw, G. W. (Principal Investigator)

    1982-01-01

    The grouped optimal aggregation technique produces minimum variance, unbiased estimates of acreage and production for countries, zones (states), or any designated collection of acreage strata. It uses yield predictions, historical acreage information, and direct acreage estimate from satellite data. The acreage strata are grouped in such a way that the ratio model over historical acreage provides a smaller variance than if the model were applied to each individual stratum. An optimal weighting matrix based on historical acreages, provides the link between incomplete direct acreage estimates and the total, current acreage estimate.

  5. 40 CFR Table 2 to Subpart Ddddd of... - Emission Limits for Existing Boilers and Process Heaters

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... collect a minimum of 3 dscm. 2. Units design to burn coal/solid fossil fuel a. Filterable PM (or TSM) 4.0E... minimum of 2 dscm per run. 3. Pulverized coal boilers designed to burn coal/solid fossil fuel a. CO (or.../solid fossil fuel a. CO (or CEMS) 160 ppm by volume on a dry basis corrected to 3 percent oxygen, 3-run...

  6. Infrared image background modeling based on improved Susan filtering

    NASA Astrophysics Data System (ADS)

    Yuehua, Xia

    2018-02-01

    When SUSAN filter is used to model the infrared image, the Gaussian filter lacks the ability of direction filtering. After filtering, the edge information of the image cannot be preserved well, so that there are a lot of edge singular points in the difference graph, increase the difficulties of target detection. To solve the above problems, the anisotropy algorithm is introduced in this paper, and the anisotropic Gauss filter is used instead of the Gauss filter in the SUSAN filter operator. Firstly, using anisotropic gradient operator to calculate a point of image's horizontal and vertical gradient, to determine the long axis direction of the filter; Secondly, use the local area of the point and the neighborhood smoothness to calculate the filter length and short axis variance; And then calculate the first-order norm of the difference between the local area of the point's gray-scale and mean, to determine the threshold of the SUSAN filter; Finally, the built SUSAN filter is used to convolution the image to obtain the background image, at the same time, the difference between the background image and the original image is obtained. The experimental results show that the background modeling effect of infrared image is evaluated by Mean Squared Error (MSE), Structural Similarity (SSIM) and local Signal-to-noise Ratio Gain (GSNR). Compared with the traditional filtering algorithm, the improved SUSAN filter has achieved better background modeling effect, which can effectively preserve the edge information in the image, and the dim small target is effectively enhanced in the difference graph, which greatly reduces the false alarm rate of the image.

  7. Source-space ICA for MEG source imaging.

    PubMed

    Jonmohamadi, Yaqub; Jones, Richard D

    2016-02-01

    One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

  8. Estimating Characteristics of a Maneuvering Reentry Vehicle Observed by Multiple Sensors

    DTIC Science & Technology

    2010-03-01

    instead of as one large data set. This method allowed the filter to respond to changing dynamics. Jackson and Farbman’s approach could be of...portion of the entire acceleration was due to drag. Lee and Liu adopted a more hybrid approach , combining a least squares and Kalman filters [9...grows again as the window approaches the end of the available data. Three values for minimum window size, window size, and maximum window size are

  9. Bentonite Clay Adsorption Procedure for Concentrating Enteroviruses from Water.

    DTIC Science & Technology

    1992-07-01

    1 pm (nominal porosity) wool filter bags, and filter beds of sand, glass, or diatomaceous earth , did not retain clay- adsorbed virus as effectively as...number) L/ A method of adsorbing enteroviruses to bentonite clay was developed for use as a concentration technique designed to sample low levels of...bentonite within a 20 minute contact period. A minimum bentonite level of 50 mg/L was necessary to adsorb the virus and to still allow efficient

  10. Size really does matter: effects of filter fractionation on microbial community structure in a model oxygen minimum zone.

    NASA Astrophysics Data System (ADS)

    Torres Beltran, M.

    2016-02-01

    The Scientific Committee on Oceanographic Research (SCOR) Working Group 144 "Microbial Community Responses to Ocean Deoxygenation" workshop held in Vancouver, British Columbia in July 2014 had the primary objective of kick-starting the establishment of a minimal core of technologies, techniques and standard operating procedures (SOPs) to enable compatible process rate and multi-molecular data (DNA, RNA and protein) collection in marine oxygen minimum zones (OMZs) and other oxygen starved waters. Experimental activities conducted in Saanich Inlet, a seasonally anoxic fjord on Vancouver Island British Columbia, were designed to compare and cross-calibrate in situ sampling devices (McLane PPS system) with conventional bottle sampling and incubation methods. Bottle effects on microbial community composition, and activity were tested using different filter combinations and sample volumes to compare PPS/IPS (0.4 µm) versus Sterivex (0.22 µm) filtration methods with and without prefilters (2.7 µm). Resulting biomass was processed for small subunit ribosomal RNA gene sequencing across all three domains of life on the 454 platform followed by downstream community structure analyses. Significant community shifts occurred within and between filter fractions for in situ versus on-ship processed samples. For instance, the relative abundance of several bacterial phyla including Bacteroidetes, Delta and Gammaproteobacteria decreased five-fold on-ship when compared to in situ filtration. Similarly, experimental mesocosms showed similar community structure and activity to in situ filtered samples indicating the need to cross-calibrate incubations to constrain bottle effects. In addition, alpha and beta diversity significantly changed as function of filter size and volume, as well as the operational taxonomic units identified using indicator species analysis for each filter size. Our results provide statistical support that microbial community structure is systematically biased by filter fraction methods and highlight the need for establishing compatible techniques among researchers that facilitate comparative and reproducible science for the whole community.

  11. Separation of man-made and natural patterns in high-altitude imagery of agricultural areas

    NASA Technical Reports Server (NTRS)

    Samulon, A. S.

    1975-01-01

    A nonstationary linear digital filter is designed and implemented which extracts the natural features from high-altitude imagery of agricultural areas. Essentially, from an original image a new image is created which displays information related to soil properties, drainage patterns, crop disease, and other natural phenomena, and contains no information about crop type or row spacing. A model is developed to express the recorded brightness in a narrow-band image in terms of man-made and natural contributions and which describes statistically the spatial properties of each. The form of the minimum mean-square error linear filter for estimation of the natural component of the scene is derived and a suboptimal filter is implemented. Nonstationarity of the two-dimensional random processes contained in the model requires a unique technique for deriving the optimum filter. Finally, the filter depends on knowledge of field boundaries. An algorithm for boundary location is proposed, discussed, and implemented.

  12. Design of a compensation for an ARMA model of a discrete time system. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Mainemer, C. I.

    1978-01-01

    The design of an optimal dynamic compensator for a multivariable discrete time system is studied. Also the design of compensators to achieve minimum variance control strategies for single input single output systems is analyzed. In the first problem the initial conditions of the plant are random variables with known first and second order moments, and the cost is the expected value of the standard cost, quadratic in the states and controls. The compensator is based on the minimum order Luenberger observer and it is found optimally by minimizing a performance index. Necessary and sufficient conditions for optimality of the compensator are derived. The second problem is solved in three different ways; two of them working directly in the frequency domain and one working in the time domain. The first and second order moments of the initial conditions are irrelevant to the solution. Necessary and sufficient conditions are derived for the compensator to minimize the variance of the output.

  13. Chromotomography for a rotating-prism instrument using backprojection, then filtering.

    PubMed

    Deming, Ross W

    2006-08-01

    A simple closed-form solution is derived for reconstructing a 3D spatial-chromatic image cube from a set of chromatically dispersed 2D image frames. The algorithm is tailored for a particular instrument in which the dispersion element is a matching set of mechanically rotated direct vision prisms positioned between a lens and a focal plane array. By using a linear operator formalism to derive the Tikhonov-regularized pseudoinverse operator, it is found that the unique minimum-norm solution is obtained by applying the adjoint operator, followed by 1D filtering with respect to the chromatic variable. Thus the filtering and backprojection (adjoint) steps are applied in reverse order relative to an existing method. Computational efficiency is provided by use of the fast Fourier transform in the filtering step.

  14. Tunable output-frequency filter algorithm for imaging through scattering media under LED illumination

    NASA Astrophysics Data System (ADS)

    Zhou, Meiling; Singh, Alok Kumar; Pedrini, Giancarlo; Osten, Wolfgang; Min, Junwei; Yao, Baoli

    2018-03-01

    We present a tunable output-frequency filter (TOF) algorithm to reconstruct the object from noisy experimental data under low-power partially coherent illumination, such as LED, when imaging through scattering media. In the iterative algorithm, we employ Gaussian functions with different filter windows at different stages of iteration process to reduce corruption from experimental noise to search for a global minimum in the reconstruction. In comparison with the conventional iterative phase retrieval algorithm, we demonstrate that the proposed TOF algorithm achieves consistent and reliable reconstruction in the presence of experimental noise. Moreover, the spatial resolution and distinctive features are retained in the reconstruction since the filter is applied only to the region outside the object. The feasibility of the proposed method is proved by experimental results.

  15. Uncertainty estimation and multi sensor fusion for kinematic laser tracker measurements

    NASA Astrophysics Data System (ADS)

    Ulrich, Thomas

    2013-08-01

    Laser trackers are widely used to measure kinematic tasks such as tracking robot movements. Common methods to evaluate the uncertainty in the kinematic measurement include approximations specified by the manufacturers, various analytical adjustment methods and the Kalman filter. In this paper a new, real-time technique is proposed, which estimates the 4D-path (3D-position + time) uncertainty of an arbitrary path in space. Here a hybrid system estimator is applied in conjunction with the kinematic measurement model. This method can be applied to processes, which include various types of kinematic behaviour, constant velocity, variable acceleration or variable turn rates. The new approach is compared with the Kalman filter and a manufacturer's approximations. The comparison was made using data obtained by tracking an industrial robot's tool centre point with a Leica laser tracker AT901 and a Leica laser tracker LTD500. It shows that the new approach is more appropriate to analysing kinematic processes than the Kalman filter, as it reduces overshoots and decreases the estimated variance. In comparison with the manufacturer's approximations, the new approach takes account of kinematic behaviour with an improved description of the real measurement process and a reduction in estimated variance. This approach is therefore well suited to the analysis of kinematic processes with unknown changes in kinematic behaviour as well as the fusion among laser trackers.

  16. Optimized tuner selection for engine performance estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

    2013-01-01

    A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

  17. Auto Regressive Moving Average (ARMA) Modeling Method for Gyro Random Noise Using a Robust Kalman Filter

    PubMed Central

    Huang, Lei

    2015-01-01

    To solve the problem in which the conventional ARMA modeling methods for gyro random noise require a large number of samples and converge slowly, an ARMA modeling method using a robust Kalman filtering is developed. The ARMA model parameters are employed as state arguments. Unknown time-varying estimators of observation noise are used to achieve the estimated mean and variance of the observation noise. Using the robust Kalman filtering, the ARMA model parameters are estimated accurately. The developed ARMA modeling method has the advantages of a rapid convergence and high accuracy. Thus, the required sample size is reduced. It can be applied to modeling applications for gyro random noise in which a fast and accurate ARMA modeling method is required. PMID:26437409

  18. Seasonal and diurnal variations of ozone at a high-altitude mountain baseline station in East Asia

    NASA Astrophysics Data System (ADS)

    Ou Yang, Chang-Feng; Lin, Neng-Huei; Sheu, Guey-Rong; Lee, Chung-Te; Wang, Jia-Lin

    2012-01-01

    Continuous measurements of tropospheric ozone were conducted at the Lulin Atmospheric Background Station (LABS) at an altitude of 2862 m from April 2006 to the end of 2009. Distinct seasonal variations in the ozone concentration were observed at the LABS, with a springtime maximum and a summertime minimum. Based on a backward trajectory analysis, CO data, and ozonesondes, the springtime maximum was most likely caused by the long-range transport of air masses from Southeast Asia, where biomass burning was intense in spring. In contrast, a greater Pacific influence contributed to the summertime minimum. In addition to seasonal variations, a distinct diurnal pattern was also observed at the LABS, with a daytime minimum and a nighttime maximum. The daytime ozone minimum was presumably caused by sinks of dry deposition and NO titration during the up-slope transport of surface air. The higher nighttime values, however, could be the result of air subsidence at night bringing ozone aloft to the LABS. After filtering out the daytime data to remove possible local surface contributions, the average background ozone value for the period of 2006-2009 was approximately 36.6 ppb, increased from 32.3 ppb prior to data filtering, without any changes in the seasonal pattern. By applying HYSPLIT4 model analysis, the origins of the air masses contributing to the background ozone observed at the LABS were investigated.

  19. Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity.

    PubMed

    Shibata, Sumiya; Matsuhashi, Masao; Kunieda, Takeharu; Yamao, Yukihiro; Inano, Rika; Kikuchi, Takayuki; Imamura, Hisaji; Takaya, Shigetoshi; Matsumoto, Riki; Ikeda, Akio; Takahashi, Ryosuke; Mima, Tatsuya; Fukuyama, Hidenao; Mikuni, Nobuhiro; Miyamoto, Susumu

    2017-05-01

    We describe temporal spread imaging (TSI) that can identify the spatiotemporal pattern of epileptic activity using Magnetoencephalography (MEG). A three-dimensional grid of voxels covering the brain is created. The array-gain minimum-variance spatial filter is applied to an interictal spike to estimate the magnitude of the source and the time (Ta) when the magnitude exceeds a predefined threshold at each voxel. This calculation is performed through all spikes. Each voxel has the mean Ta () and spike number (N sp ), which is the number of spikes whose source exceeds the threshold. Then, a random resampling method is used to determine the cutoff value of N sp for the statistically reproducible pattern of the activity. Finally, all the voxels where the source exceeds the threshold reproducibly shown on the MRI with a color scale representing . Four patients with intractable mesial temporal lobe epilepsy (MTLE) were analyzed. In three patients, the common pattern of the overlap between the propagation and the hypometabolism shown by fluorodeoxyglucose-positron emission tomography (FDG-PET) was identified. TSI can visualize statistically reproducible patterns of the temporal and spatial spread of epileptic activity. TSI can assess the statistical significance of the spatiotemporal pattern based on its reproducibility. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  20. Application of wavefield imaging to characterize scattering from artificial and impact damage in composite laminate panels

    NASA Astrophysics Data System (ADS)

    Williams, Westin B.; Michaels, Thomas E.; Michaels, Jennifer E.

    2018-04-01

    Composite materials used for aerospace applications are highly susceptible to impacts, which can result in barely visible delaminations. Reliable and fast detection of such damage is needed before structural failures occur. One approach is to use ultrasonic guided waves generated from a sparse array consisting of permanently mounted or embedded transducers for performing structural health monitoring. This array can detect introduction of damage after baseline subtraction, and also provide localization and characterization information via the minimum variance imaging algorithm. Imaging performance can vary considerably depending upon where damage is located with respect to the array; however, prior work has shown that knowledge of expected scattering can improve imaging consistency for artificial damage at various locations. In this study, anisotropic material attenuation and wave speed are estimated as a function of propagation angle using wavefield data recorded along radial lines at multiple angles with respect to an omnidirectional guided wave source. Additionally, full wavefield data are recorded before and after the introduction of artificial and impact damage so that wavefield baseline subtraction may be applied. 3-D filtering techniques are then used to reduce noise and isolate scattered waves. A model for estimating scattering of a circular defect is developed and scattering estimates for both artificial and impact damage are presented and compared.

  1. On the application of under-decimated filter banks

    NASA Technical Reports Server (NTRS)

    Lin, Y.-P.; Vaidyanathan, P. P.

    1994-01-01

    Maximally decimated filter banks have been extensively studied in the past. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding. Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate. However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed. In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution. This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving. In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels. Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform (DFT) filter banks and the cosine modulated filter banks. They are well known for their low complexity. In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate. Furthermore, for both systems, the implementation cost of the analysis or synthesis bank is comparable to that of one prototype filter plus some low-complexity modulation matrices. The individual analysis and synthesis filters have complex coefficients in the DFT filter banks but have real coefficients in the cosine modulated filter banks.

  2. On the application of under-decimated filter banks

    NASA Astrophysics Data System (ADS)

    Lin, Y.-P.; Vaidyanathan, P. P.

    1994-11-01

    Maximally decimated filter banks have been extensively studied in the past. A filter bank is said to be under-decimated if the number of channels is more than the decimation ratio in the subbands. A maximally decimated filter bank is well known for its application in subband coding. Another application of maximally decimated filter banks is in block filtering. Convolution through block filtering has the advantages that parallelism is increased and data are processed at a lower rate. However, the computational complexity is comparable to that of direct convolution. More recently, another type of filter bank convolver has been developed. In this scheme, the convolution is performed in the subbands. Quantization and bit allocation of subband signals are based on signal variance, as in subband coding. Consequently, for a fixed rate, the result of convolution is more accurate than is direct convolution. This type of filter bank convolver also enjoys the advantages of block filtering, parallelism, and a lower working rate. Nevertheless, like block filtering, there is no computational saving. In this article, under-decimated systems are introduced to solve the problem. The new system is decimated only by half the number of channels. Two types of filter banks can be used in the under-decimated system: the discrete Fourier transform (DFT) filter banks and the cosine modulated filter banks. They are well known for their low complexity. In both cases, the system is approximately alias free, and the overall response is equivalent to a tunable multilevel filter. Properties of the DFT filter banks and the cosine modulated filter banks can be exploited to simultaneously achieve parallelism, computational saving, and a lower working rate.

  3. Thermospheric mass density model error variance as a function of time scale

    NASA Astrophysics Data System (ADS)

    Emmert, J. T.; Sutton, E. K.

    2017-12-01

    In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

  4. Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

    NASA Technical Reports Server (NTRS)

    Frost, Susan A.; Balas, Mark J.

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

  5. Segmentation-based L-filtering of speckle noise in ultrasonic images

    NASA Astrophysics Data System (ADS)

    Kofidis, Eleftherios; Theodoridis, Sergios; Kotropoulos, Constantine L.; Pitas, Ioannis

    1994-05-01

    We introduce segmentation-based L-filters, that is, filtering processes combining segmentation and (nonadaptive) optimum L-filtering, and use them for the suppression of speckle noise in ultrasonic (US) images. With the aid of a suitable modification of the learning vector quantizer self-organizing neural network, the image is segmented in regions of approximately homogeneous first-order statistics. For each such region a minimum mean-squared error L- filter is designed on the basis of a multiplicative noise model by using the histogram of grey values as an estimate of the parent distribution of the noisy observations and a suitable estimate of the original signal in the corresponding region. Thus, we obtain a bank of L-filters that are corresponding to and are operating on different image regions. Simulation results on a simulated US B-mode image of a tissue mimicking phantom are presented which verify the superiority of the proposed method as compared to a number of conventional filtering strategies in terms of a suitably defined signal-to-noise ratio measure and detection theoretic performance measures.

  6. Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2

    NASA Technical Reports Server (NTRS)

    Balas, Mark J.; Frost, Susan

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

  7. Control algorithms for dynamic attenuators

    PubMed Central

    Hsieh, Scott S.; Pelc, Norbert J.

    2014-01-01

    Purpose: The authors describe algorithms to control dynamic attenuators in CT and compare their performance using simulated scans. Dynamic attenuators are prepatient beam shaping filters that modulate the distribution of x-ray fluence incident on the patient on a view-by-view basis. These attenuators can reduce dose while improving key image quality metrics such as peak or mean variance. In each view, the attenuator presents several degrees of freedom which may be individually adjusted. The total number of degrees of freedom across all views is very large, making many optimization techniques impractical. The authors develop a theory for optimally controlling these attenuators. Special attention is paid to a theoretically perfect attenuator which controls the fluence for each ray individually, but the authors also investigate and compare three other, practical attenuator designs which have been previously proposed: the piecewise-linear attenuator, the translating attenuator, and the double wedge attenuator. Methods: The authors pose and solve the optimization problems of minimizing the mean and peak variance subject to a fixed dose limit. For a perfect attenuator and mean variance minimization, this problem can be solved in simple, closed form. For other attenuator designs, the problem can be decomposed into separate problems for each view to greatly reduce the computational complexity. Peak variance minimization can be approximately solved using iterated, weighted mean variance (WMV) minimization. Also, the authors develop heuristics for the perfect and piecewise-linear attenuators which do not require a priori knowledge of the patient anatomy. The authors compare these control algorithms on different types of dynamic attenuators using simulated raw data from forward projected DICOM files of a thorax and an abdomen. Results: The translating and double wedge attenuators reduce dose by an average of 30% relative to current techniques (bowtie filter with tube current modulation) without increasing peak variance. The 15-element piecewise-linear dynamic attenuator reduces dose by an average of 42%, and the perfect attenuator reduces dose by an average of 50%. Improvements in peak variance are several times larger than improvements in mean variance. Heuristic control eliminates the need for a prescan. For the piecewise-linear attenuator, the cost of heuristic control is an increase in dose of 9%. The proposed iterated WMV minimization produces results that are within a few percent of the true solution. Conclusions: Dynamic attenuators show potential for significant dose reduction. A wide class of dynamic attenuators can be accurately controlled using the described methods. PMID:24877818

  8. 25 CFR 543.18 - What are the minimum internal control standards for the cage, vault, kiosk, cash and cash...

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... available upon demand for each day, shift, and drop cycle (this is not required if the system does not track..., beverage containers, etc., into and out of the cage. (j) Variances. The operation must establish, as...

  9. 25 CFR 543.18 - What are the minimum internal control standards for the cage, vault, kiosk, cash and cash...

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... available upon demand for each day, shift, and drop cycle (this is not required if the system does not track..., beverage containers, etc., into and out of the cage. (j) Variances. The operation must establish, as...

  10. On higher order discrete phase-locked loops.

    NASA Technical Reports Server (NTRS)

    Gill, G. S.; Gupta, S. C.

    1972-01-01

    An exact mathematical model is developed for a discrete loop of a general order particularly suitable for digital computation. The deterministic response of the loop to the phase step and the frequency step is investigated. The design of the digital filter for the second-order loop is considered. Use is made of the incremental phase plane to study the phase error behavior of the loop. The model of the noisy loop is derived and the optimization of the loop filter for minimum mean-square error is considered.

  11. PDF-based heterogeneous multiscale filtration model.

    PubMed

    Gong, Jian; Rutland, Christopher J

    2015-04-21

    Motivated by modeling of gasoline particulate filters (GPFs), a probability density function (PDF) based heterogeneous multiscale filtration (HMF) model is developed to calculate filtration efficiency of clean particulate filters. A new methodology based on statistical theory and classic filtration theory is developed in the HMF model. Based on the analysis of experimental porosimetry data, a pore size probability density function is introduced to represent heterogeneity and multiscale characteristics of the porous wall. The filtration efficiency of a filter can be calculated as the sum of the contributions of individual collectors. The resulting HMF model overcomes the limitations of classic mean filtration models which rely on tuning of the mean collector size. Sensitivity analysis shows that the HMF model recovers the classical mean model when the pore size variance is very small. The HMF model is validated by fundamental filtration experimental data from different scales of filter samples. The model shows a good agreement with experimental data at various operating conditions. The effects of the microstructure of filters on filtration efficiency as well as the most penetrating particle size are correctly predicted by the model.

  12. A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation.

    PubMed

    Vargas-Meléndez, Leandro; Boada, Beatriz L; Boada, María Jesús L; Gauchía, Antonio; Díaz, Vicente

    2016-08-31

    This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a "pseudo-roll angle" through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors' estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator.

  13. Visual selective attention is equally functional for individuals with low and high working memory capacity: evidence from accuracy and eye movements.

    PubMed

    Mall, Jonathan T; Morey, Candice C; Wolff, Michael J; Lehnert, Franziska

    2014-10-01

    Selective attention and working memory capacity (WMC) are related constructs, but debate about the manner in which they are related remains active. One elegant explanation of variance in WMC is that the efficiency of filtering irrelevant information is the crucial determining factor, rather than differences in capacity per se. We examined this hypothesis by relating WMC (as measured by complex span tasks) to accuracy and eye movements during visual change detection tasks with different degrees of attentional filtering and allocation requirements. Our results did not indicate strong filtering differences between high- and low-WMC groups, and where differences were observed, they were counter to those predicted by the strongest attentional filtering hypothesis. Bayes factors indicated evidence favoring positive or null relationships between WMC and correct responses to unemphasized information, as well as between WMC and the time spent looking at unemphasized information. These findings are consistent with the hypothesis that individual differences in storage capacity, not only filtering efficiency, underlie individual differences in working memory.

  14. A Sensor Fusion Method Based on an Integrated Neural Network and Kalman Filter for Vehicle Roll Angle Estimation

    PubMed Central

    Vargas-Meléndez, Leandro; Boada, Beatriz L.; Boada, María Jesús L.; Gauchía, Antonio; Díaz, Vicente

    2016-01-01

    This article presents a novel estimator based on sensor fusion, which combines the Neural Network (NN) with a Kalman filter in order to estimate the vehicle roll angle. The NN estimates a “pseudo-roll angle” through variables that are easily measured from Inertial Measurement Unit (IMU) sensors. An IMU is a device that is commonly used for vehicle motion detection, and its cost has decreased during recent years. The pseudo-roll angle is introduced in the Kalman filter in order to filter noise and minimize the variance of the norm and maximum errors’ estimation. The NN has been trained for J-turn maneuvers, double lane change maneuvers and lane change maneuvers at different speeds and road friction coefficients. The proposed method takes into account the vehicle non-linearities, thus yielding good roll angle estimation. Finally, the proposed estimator has been compared with one that uses the suspension deflections to obtain the pseudo-roll angle. Experimental results show the effectiveness of the proposed NN and Kalman filter-based estimator. PMID:27589763

  15. Scale-by-scale contributions to Lagrangian particle acceleration

    NASA Astrophysics Data System (ADS)

    Lalescu, Cristian C.; Wilczek, Michael

    2017-11-01

    Fluctuations on a wide range of scales in both space and time are characteristic of turbulence. Lagrangian particles, advected by the flow, probe these fluctuations along their trajectories. In an effort to isolate the influence of the different scales on Lagrangian statistics, we employ direct numerical simulations (DNS) combined with a filtering approach. Specifically, we study the acceleration statistics of tracers advected in filtered fields to characterize the smallest temporal scales of the flow. Emphasis is put on the acceleration variance as a function of filter scale, along with the scaling properties of the relevant terms of the Navier-Stokes equations. We furthermore discuss scaling ranges for higher-order moments of the tracer acceleration, as well as the influence of the choice of filter on the results. Starting from the Lagrangian tracer acceleration as the short time limit of the Lagrangian velocity increment, we also quantify the influence of filtering on Lagrangian intermittency. Our work complements existing experimental results on intermittency and accelerations of finite-sized, neutrally-buoyant particles: for the passive tracers used in our DNS, feedback effects are neglected such that the spatial averaging effect is cleanly isolated.

  16. Log-polar mapping-based scale space tracking with adaptive target response

    NASA Astrophysics Data System (ADS)

    Li, Dongdong; Wen, Gongjian; Kuai, Yangliu; Zhang, Ximing

    2017-05-01

    Correlation filter-based tracking has exhibited impressive robustness and accuracy in recent years. Standard correlation filter-based trackers are restricted to translation estimation and equipped with fixed target response. These trackers produce an inferior performance when encountered with a significant scale variation or appearance change. We propose a log-polar mapping-based scale space tracker with an adaptive target response. This tracker transforms the scale variation of the target in the Cartesian space into a shift along the logarithmic axis in the log-polar space. A one-dimensional scale correlation filter is learned online to estimate the shift along the logarithmic axis. With the log-polar representation, scale estimation is achieved accurately without a multiresolution pyramid. To achieve an adaptive target response, a variance of the Gaussian function is computed from the response map and updated online with a learning rate parameter. Our log-polar mapping-based scale correlation filter and adaptive target response can be combined with any correlation filter-based trackers. In addition, the scale correlation filter can be extended to a two-dimensional correlation filter to achieve joint estimation of the scale variation and in-plane rotation. Experiments performed on an OTB50 benchmark demonstrate that our tracker achieves superior performance against state-of-the-art trackers.

  17. Behavior of ambient concentrations of natural radionuclides (7)Be, (210)Pb, (40)K in the Mediterranean coastal city of Málaga (Spain).

    PubMed

    Gordo, E; Dueñas, C; Fernández, M C; Liger, E; Cañete, S

    2015-05-01

    During a 4-year period (January 2009-December 2012), the (7)Be, (210)Pb, and (40)K activity concentrations in airborne particulate matter were weekly determined at the Málaga (Spain) located in the southern Iberian Peninsula. Totally 209 polypropylene filters were analyzed in the mentioned period. In 100% of the filters, (7)Be and (40)K activity concentrations were detected while (210)Pb activity concentration was detected in 96% of the filters. The results from individual measurements of (7)Be, (210)Pb, and (40)K concentrations were analyzed to derive the statistical estimates characterizing the distributions. Principal components analysis (PCA) was applied to the datasets and the results of the study reveal that aerosol behavior is represented by two principal components which explain 73.2% of total variance. Components PC1 and PC2 respectively explain 46.0 and 27.2% of total variance. PC1 was related positively to dust content, (7)Be and (40)K concentrations and negatively to sunspot numbers. In contrast, PC2 was related positively to temperature and (210)Pb activity and negatively to precipitation and relative humidity. The (7)Be levels showed a significant correlation with sunspot numbers due to the cosmogenic origin. (40)K activities showed a good correlation with dust deposition in filters mainly because it was transported to the air as resuspended particle from the soil. An inverse relationship was observed between the (210)Pb concentrations and monthly rainfall, indicating washout of atmospheric aerosols carrying these radionuclides and a pronounced positive correlation with the average monthly temperature of air.

  18. Accounting for the measurement error of spectroscopically inferred soil carbon data for improved precision of spatial predictions.

    PubMed

    Somarathna, P D S N; Minasny, Budiman; Malone, Brendan P; Stockmann, Uta; McBratney, Alex B

    2018-08-01

    Spatial modelling of environmental data commonly only considers spatial variability as the single source of uncertainty. In reality however, the measurement errors should also be accounted for. In recent years, infrared spectroscopy has been shown to offer low cost, yet invaluable information needed for digital soil mapping at meaningful spatial scales for land management. However, spectrally inferred soil carbon data are known to be less accurate compared to laboratory analysed measurements. This study establishes a methodology to filter out the measurement error variability by incorporating the measurement error variance in the spatial covariance structure of the model. The study was carried out in the Lower Hunter Valley, New South Wales, Australia where a combination of laboratory measured, and vis-NIR and MIR inferred topsoil and subsoil soil carbon data are available. We investigated the applicability of residual maximum likelihood (REML) and Markov Chain Monte Carlo (MCMC) simulation methods to generate parameters of the Matérn covariance function directly from the data in the presence of measurement error. The results revealed that the measurement error can be effectively filtered-out through the proposed technique. When the measurement error was filtered from the data, the prediction variance almost halved, which ultimately yielded a greater certainty in spatial predictions of soil carbon. Further, the MCMC technique was successfully used to define the posterior distribution of measurement error. This is an important outcome, as the MCMC technique can be used to estimate the measurement error if it is not explicitly quantified. Although this study dealt with soil carbon data, this method is amenable for filtering the measurement error of any kind of continuous spatial environmental data. Copyright © 2018 Elsevier B.V. All rights reserved.

  19. An Effective Post-Filtering Framework for 3-D PET Image Denoising Based on Noise and Sensitivity Characteristics

    NASA Astrophysics Data System (ADS)

    Kim, Ji Hye; Ahn, Il Jun; Nam, Woo Hyun; Ra, Jong Beom

    2015-02-01

    Positron emission tomography (PET) images usually suffer from a noticeable amount of statistical noise. In order to reduce this noise, a post-filtering process is usually adopted. However, the performance of this approach is limited because the denoising process is mostly performed on the basis of the Gaussian random noise. It has been reported that in a PET image reconstructed by the expectation-maximization (EM), the noise variance of each voxel depends on its mean value, unlike in the case of Gaussian noise. In addition, we observe that the variance also varies with the spatial sensitivity distribution in a PET system, which reflects both the solid angle determined by a given scanner geometry and the attenuation information of a scanned object. Thus, if a post-filtering process based on the Gaussian random noise is applied to PET images without consideration of the noise characteristics along with the spatial sensitivity distribution, the spatially variant non-Gaussian noise cannot be reduced effectively. In the proposed framework, to effectively reduce the noise in PET images reconstructed by the 3-D ordinary Poisson ordered subset EM (3-D OP-OSEM), we first denormalize an image according to the sensitivity of each voxel so that the voxel mean value can represent its statistical properties reliably. Based on our observation that each noisy denormalized voxel has a linear relationship between the mean and variance, we try to convert this non-Gaussian noise image to a Gaussian noise image. We then apply a block matching 4-D algorithm that is optimized for noise reduction of the Gaussian noise image, and reconvert and renormalize the result to obtain a final denoised image. Using simulated phantom data and clinical patient data, we demonstrate that the proposed framework can effectively suppress the noise over the whole region of a PET image while minimizing degradation of the image resolution.

  20. Separating Movement and Gravity Components in an Acceleration Signal and Implications for the Assessment of Human Daily Physical Activity

    PubMed Central

    van Hees, Vincent T.; Gorzelniak, Lukas; Dean León, Emmanuel Carlos; Eder, Martin; Pias, Marcelo; Taherian, Salman; Ekelund, Ulf; Renström, Frida; Franks, Paul W.; Horsch, Alexander; Brage, Søren

    2013-01-01

    Introduction Human body acceleration is often used as an indicator of daily physical activity in epidemiological research. Raw acceleration signals contain three basic components: movement, gravity, and noise. Separation of these becomes increasingly difficult during rotational movements. We aimed to evaluate five different methods (metrics) of processing acceleration signals on their ability to remove the gravitational component of acceleration during standardised mechanical movements and the implications for human daily physical activity assessment. Methods An industrial robot rotated accelerometers in the vertical plane. Radius, frequency, and angular range of motion were systematically varied. Three metrics (Euclidian norm minus one [ENMO], Euclidian norm of the high-pass filtered signals [HFEN], and HFEN plus Euclidean norm of low-pass filtered signals minus 1 g [HFEN+]) were derived for each experimental condition and compared against the reference acceleration (forward kinematics) of the robot arm. We then compared metrics derived from human acceleration signals from the wrist and hip in 97 adults (22–65 yr), and wrist in 63 women (20–35 yr) in whom daily activity-related energy expenditure (PAEE) was available. Results In the robot experiment, HFEN+ had lowest error during (vertical plane) rotations at an oscillating frequency higher than the filter cut-off frequency while for lower frequencies ENMO performed better. In the human experiments, metrics HFEN and ENMO on hip were most discrepant (within- and between-individual explained variance of 0.90 and 0.46, respectively). ENMO, HFEN and HFEN+ explained 34%, 30% and 36% of the variance in daily PAEE, respectively, compared to 26% for a metric which did not attempt to remove the gravitational component (metric EN). Conclusion In conclusion, none of the metrics as evaluated systematically outperformed all other metrics across a wide range of standardised kinematic conditions. However, choice of metric explains different degrees of variance in daily human physical activity. PMID:23626718

  1. Susceptibility-weighted imaging using inter-echo-variance channel combination for improved contrast at 7 tesla.

    PubMed

    Hosseini, Zahra; Liu, Junmin; Solovey, Igor; Menon, Ravi S; Drangova, Maria

    2017-04-01

    To implement and optimize a new approach for susceptibility-weighted image (SWI) generation from multi-echo multi-channel image data and compare its performance against optimized traditional SWI pipelines. Five healthy volunteers were imaged at 7 Tesla. The inter-echo-variance (IEV) channel combination, which uses the variance of the local frequency shift at multiple echo times as a weighting factor during channel combination, was used to calculate multi-echo local phase shift maps. Linear phase masks were combined with the magnitude to generate IEV-SWI. The performance of the IEV-SWI pipeline was compared with that of two accepted SWI pipelines-channel combination followed by (i) Homodyne filtering (HPH-SWI) and (ii) unwrapping and high-pass filtering (SVD-SWI). The filtering steps of each pipeline were optimized. Contrast-to-noise ratio was used as the comparison metric. Qualitative assessment of artifact and vessel conspicuity was performed and processing time of pipelines was evaluated. The optimized IEV-SWI pipeline (σ = 7 mm) resulted in continuous vessel visibility throughout the brain. IEV-SWI had significantly higher contrast compared with HPH-SWI and SVD-SWI (P < 0.001, Friedman nonparametric test). Residual background fields and phase wraps in HPH-SWI and SVD-SWI corrupted the vessel signal and/or generated vessel-mimicking artifact. Optimized implementation of the IEV-SWI pipeline processed a six-echo 16-channel dataset in under 10 min. IEV-SWI benefits from channel-by-channel processing of phase data and results in high contrast images with an optimal balance between contrast and background noise removal, thereby presenting evidence of importance of the order in which postprocessing techniques are applied for multi-channel SWI generation. 2 J. Magn. Reson. Imaging 2017;45:1113-1124. © 2016 International Society for Magnetic Resonance in Medicine.

  2. SU-F-R-40: Robustness Test of Computed Tomography Textures of Lung Tissues to Varying Scanning Protocols Using a Realistic Phantom Environment

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Lee, S; Markel, D; Hegyi, G

    2016-06-15

    Purpose: The reliability of computed tomography (CT) textures is an important element of radiomics analysis. This study investigates the dependency of lung CT textures on different breathing phases and changes in CT image acquisition protocols in a realistic phantom setting. Methods: We investigated 11 CT texture features for radiation-induced lung disease from 3 categories (first-order, grey level co-ocurrence matrix (GLCM), and Law’s filter). A biomechanical swine lung phantom was scanned at two breathing phases (inhale/exhale) and two scanning protocols set for PET/CT and diagnostic CT scanning. Lung volumes acquired from the CT images were divided into 2-dimensional sub-regions with amore » grid spacing of 31 mm. The distribution of the evaluated texture features from these sub-regions were compared between the two scanning protocols and two breathing phases. The significance of each factor on feature values were tested at 95% significance level using analysis of covariance (ANCOVA) model with interaction terms included. Robustness of a feature to a scanning factor was defined as non-significant dependence on the factor. Results: Three GLCM textures (variance, sum entropy, difference entropy) were robust to breathing changes. Two GLCM (variance, sum entropy) and 3 Law’s filter textures (S5L5, E5L5, W5L5) were robust to scanner changes. Moreover, the two GLCM textures (variance, sum entropy) were consistent across all 4 scanning conditions. First-order features, especially Hounsfield unit intensity features, presented the most drastic variation up to 39%. Conclusion: Amongst the studied features, GLCM and Law’s filter texture features were more robust than first-order features. However, the majority of the features were modified by either breathing phase or scanner changes, suggesting a need for calibration when retrospectively comparing scans obtained at different conditions. Further investigation is necessary to identify the sensitivity of individual image acquisition parameters.« less

  3. Separating movement and gravity components in an acceleration signal and implications for the assessment of human daily physical activity.

    PubMed

    van Hees, Vincent T; Gorzelniak, Lukas; Dean León, Emmanuel Carlos; Eder, Martin; Pias, Marcelo; Taherian, Salman; Ekelund, Ulf; Renström, Frida; Franks, Paul W; Horsch, Alexander; Brage, Søren

    2013-01-01

    Human body acceleration is often used as an indicator of daily physical activity in epidemiological research. Raw acceleration signals contain three basic components: movement, gravity, and noise. Separation of these becomes increasingly difficult during rotational movements. We aimed to evaluate five different methods (metrics) of processing acceleration signals on their ability to remove the gravitational component of acceleration during standardised mechanical movements and the implications for human daily physical activity assessment. An industrial robot rotated accelerometers in the vertical plane. Radius, frequency, and angular range of motion were systematically varied. Three metrics (Euclidian norm minus one [ENMO], Euclidian norm of the high-pass filtered signals [HFEN], and HFEN plus Euclidean norm of low-pass filtered signals minus 1 g [HFEN+]) were derived for each experimental condition and compared against the reference acceleration (forward kinematics) of the robot arm. We then compared metrics derived from human acceleration signals from the wrist and hip in 97 adults (22-65 yr), and wrist in 63 women (20-35 yr) in whom daily activity-related energy expenditure (PAEE) was available. In the robot experiment, HFEN+ had lowest error during (vertical plane) rotations at an oscillating frequency higher than the filter cut-off frequency while for lower frequencies ENMO performed better. In the human experiments, metrics HFEN and ENMO on hip were most discrepant (within- and between-individual explained variance of 0.90 and 0.46, respectively). ENMO, HFEN and HFEN+ explained 34%, 30% and 36% of the variance in daily PAEE, respectively, compared to 26% for a metric which did not attempt to remove the gravitational component (metric EN). In conclusion, none of the metrics as evaluated systematically outperformed all other metrics across a wide range of standardised kinematic conditions. However, choice of metric explains different degrees of variance in daily human physical activity.

  4. Sinogram noise reduction for low-dose CT by statistics-based nonlinear filters

    NASA Astrophysics Data System (ADS)

    Wang, Jing; Lu, Hongbing; Li, Tianfang; Liang, Zhengrong

    2005-04-01

    Low-dose CT (computed tomography) sinogram data have been shown to be signal-dependent with an analytical relationship between the sample mean and sample variance. Spatially-invariant low-pass linear filters, such as the Butterworth and Hanning filters, could not adequately handle the data noise and statistics-based nonlinear filters may be an alternative choice, in addition to other choices of minimizing cost functions on the noisy data. Anisotropic diffusion filter and nonlinear Gaussian filters chain (NLGC) are two well-known classes of nonlinear filters based on local statistics for the purpose of edge-preserving noise reduction. These two filters can utilize the noise properties of the low-dose CT sinogram for adaptive noise reduction, but can not incorporate signal correlative information for an optimal regularized solution. Our previously-developed Karhunen-Loeve (KL) domain PWLS (penalized weighted least square) minimization considers the signal correlation via the KL strategy and seeks the PWLS cost function minimization for an optimal regularized solution for each KL component, i.e., adaptive to the KL components. This work compared the nonlinear filters with the KL-PWLS framework for low-dose CT application. Furthermore, we investigated the nonlinear filters for post KL-PWLS noise treatment in the sinogram space, where the filters were applied after ramp operation on the KL-PWLS treated sinogram data prior to backprojection operation (for image reconstruction). By both computer simulation and experimental low-dose CT data, the nonlinear filters could not outperform the KL-PWLS framework. The gain of post KL-PWLS edge-preserving noise filtering in the sinogram space is not significant, even the noise has been modulated by the ramp operation.

  5. Seasonal variation of wave activities near the mesopause region observed at King Sejong Station (62.22°S, 58.78°W), Antarctica

    NASA Astrophysics Data System (ADS)

    Lee, Changsup; Kim, Yong Ha; Kim, Jeong-Han; Jee, Geonhwa; Won, Young-In; Wu, Dong L.

    2013-12-01

    We analyzed the neutral wind data at altitudes of 80-100 km obtained from a VHF meteor radar at King Sejong Station (KSS, 62.22°S, 58.78°W), a key location to study wave activities above the stratospheric vortex near the Antarctic Peninsula. The seasonal behavior of the semidiurnal tides is generally consistent with the prediction of Global Scale Wave Model (GSWM02) except in the altitude region above ~96 km. Gravity wave (GW) activities inferred from the neutral wind variances show a seasonal variation very similar to the semidiurnal tide amplitudes, suggesting a strong interaction between gravity waves and the tide. Despite the consistent seasonal variations of the GW wind variances observed at the adjacent Rothera station, the magnitudes of the wind variance obtained at KSS are much larger than those at Rothera, especially during May-September. The enhanced GW activity at KSS is also observed by Aura Microwave Limb Sounder (MLS) from space in its temperature variance. The observed large wind variances at KSS imply that the Antarctic vortex in the stratosphere may act as an effective filter and source for the GWs in the upper atmosphere.

  6. Patterns and Prevalence of Core Profile Types in the WPPSI Standardization Sample.

    ERIC Educational Resources Information Center

    Glutting, Joseph J.; McDermott, Paul A.

    1990-01-01

    Found most representative subtest profiles for 1,200 children comprising standardization sample of Wechsler Preschool and Primary Scale of Intelligence (WPPSI). Grouped scaled scores from WPPSI subtests according to similar level and shape using sequential minimum-variance cluster analysis with independent replications. Obtained final solution of…

  7. A Review on Sensor, Signal, and Information Processing Algorithms (PREPRINT)

    DTIC Science & Technology

    2010-01-01

    processing [214], ambi- guity surface averaging [215], optimum uncertain field tracking, and optimal minimum variance track - before - detect [216]. In [217, 218...2) (2001) 739–746. [216] S. L. Tantum, L. W. Nolte, J. L. Krolik, K. Harmanci, The performance of matched-field track - before - detect methods using

  8. A Comparison of Item Selection Techniques for Testlets

    ERIC Educational Resources Information Center

    Murphy, Daniel L.; Dodd, Barbara G.; Vaughn, Brandon K.

    2010-01-01

    This study examined the performance of the maximum Fisher's information, the maximum posterior weighted information, and the minimum expected posterior variance methods for selecting items in a computerized adaptive testing system when the items were grouped in testlets. A simulation study compared the efficiency of ability estimation among the…

  9. Designing a composite correlation filter based on iterative optimization of training images for distortion invariant face recognition

    NASA Astrophysics Data System (ADS)

    Wang, Q.; Elbouz, M.; Alfalou, A.; Brosseau, C.

    2017-06-01

    We present a novel method to optimize the discrimination ability and noise robustness of composite filters. This method is based on the iterative preprocessing of training images which can extract boundary and detailed feature information of authentic training faces, thereby improving the peak-to-correlation energy (PCE) ratio of authentic faces and to be immune to intra-class variance and noise interference. By adding the training images directly, one can obtain a composite template with high discrimination ability and robustness for face recognition task. The proposed composite correlation filter does not involve any complicated mathematical analysis and computation which are often required in the design of correlation algorithms. Simulation tests have been conducted to check the effectiveness and feasibility of our proposal. Moreover, to assess robustness of composite filters using receiver operating characteristic (ROC) curves, we devise a new method to count the true positive and false positive rates for which the difference between PCE and threshold is involved.

  10. Subband Approach to Bandlimited Crosstalk Cancellation System in Spatial Sound Reproduction

    NASA Astrophysics Data System (ADS)

    Bai, Mingsian R.; Lee, Chih-Chung

    2006-12-01

    Crosstalk cancellation system (CCS) plays a vital role in spatial sound reproduction using multichannel loudspeakers. However, this technique is still not of full-blown use in practical applications due to heavy computation loading. To reduce the computation loading, a bandlimited CCS is presented in this paper on the basis of subband filtering approach. A pseudoquadrature mirror filter (QMF) bank is employed in the implementation of CCS filters which are bandlimited to 6 kHz, where human's localization is the most sensitive. In addition, a frequency-dependent regularization scheme is adopted in designing the CCS inverse filters. To justify the proposed system, subjective listening experiments were undertaken in an anechoic room. The experiments include two parts: the source localization test and the sound quality test. Analysis of variance (ANOVA) is applied to process the data and assess statistical significance of subjective experiments. The results indicate that the bandlimited CCS performed comparably well as the fullband CCS, whereas the computation loading was reduced by approximately eighty percent.

  11. Segmentation of Coronary Angiograms Using Gabor Filters and Boltzmann Univariate Marginal Distribution Algorithm

    PubMed Central

    Cervantes-Sanchez, Fernando; Hernandez-Aguirre, Arturo; Solorio-Meza, Sergio; Ornelas-Rodriguez, Manuel; Torres-Cisneros, Miguel

    2016-01-01

    This paper presents a novel method for improving the training step of the single-scale Gabor filters by using the Boltzmann univariate marginal distribution algorithm (BUMDA) in X-ray angiograms. Since the single-scale Gabor filters (SSG) are governed by three parameters, the optimal selection of the SSG parameters is highly desirable in order to maximize the detection performance of coronary arteries while reducing the computational time. To obtain the best set of parameters for the SSG, the area (A z) under the receiver operating characteristic curve is used as fitness function. Moreover, to classify vessel and nonvessel pixels from the Gabor filter response, the interclass variance thresholding method has been adopted. The experimental results using the proposed method obtained the highest detection rate with A z = 0.9502 over a training set of 40 images and A z = 0.9583 with a test set of 40 images. In addition, the experimental results of vessel segmentation provided an accuracy of 0.944 with the test set of angiograms. PMID:27738422

  12. A Data Filter for Identifying Steady-State Operating Points in Engine Flight Data for Condition Monitoring Applications

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Litt, Jonathan S.

    2010-01-01

    This paper presents an algorithm that automatically identifies and extracts steady-state engine operating points from engine flight data. It calculates the mean and standard deviation of select parameters contained in the incoming flight data stream. If the standard deviation of the data falls below defined constraints, the engine is assumed to be at a steady-state operating point, and the mean measurement data at that point are archived for subsequent condition monitoring purposes. The fundamental design of the steady-state data filter is completely generic and applicable for any dynamic system. Additional domain-specific logic constraints are applied to reduce data outliers and variance within the collected steady-state data. The filter is designed for on-line real-time processing of streaming data as opposed to post-processing of the data in batch mode. Results of applying the steady-state data filter to recorded helicopter engine flight data are shown, demonstrating its utility for engine condition monitoring applications.

  13. Gated Sensor Fusion: A way to Improve the Precision of Ambulatory Human Body Motion Estimation.

    PubMed

    Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, Gonzalo

    2014-01-01

    Human body motion is usually variable in terms of intensity and, therefore, any Inertial Measurement Unit attached to a subject will measure both low and high angular rate and accelerations. This can be a problem for the accuracy of orientation estimation algorithms based on adaptive filters such as the Kalman filter, since both the variances of the process noise and the measurement noise are set at the beginning of the algorithm and remain constant during its execution. Setting fixed noise parameters burdens the adaptation capability of the filter if the intensity of the motion changes rapidly. In this work we present a conjoint novel algorithm which uses a motion intensity detector to dynamically vary the noise statistical parameters of different approaches of the Kalman filter. Results show that the precision of the estimated orientation in terms of the RMSE can be improved up to 29% with respect to the standard fixed-parameters approaches.

  14. Low genetic variance in the duration of the incubation period in a collared flycatcher (Ficedula albicollis) population.

    PubMed

    Husby, Arild; Gustafsson, Lars; Qvarnström, Anna

    2012-01-01

    The avian incubation period is associated with high energetic costs and mortality risks suggesting that there should be strong selection to reduce the duration to the minimum required for normal offspring development. Although there is much variation in the duration of the incubation period across species, there is also variation within species. It is necessary to estimate to what extent this variation is genetically determined if we want to predict the evolutionary potential of this trait. Here we use a long-term study of collared flycatchers to examine the genetic basis of variation in incubation duration. We demonstrate limited genetic variance as reflected in the low and nonsignificant additive genetic variance, with a corresponding heritability of 0.04 and coefficient of additive genetic variance of 2.16. Any selection acting on incubation duration will therefore be inefficient. To our knowledge, this is the first time heritability of incubation duration has been estimated in a natural bird population. © 2011 by The University of Chicago.

  15. Overlap between treatment and control distributions as an effect size measure in experiments.

    PubMed

    Hedges, Larry V; Olkin, Ingram

    2016-03-01

    The proportion π of treatment group observations that exceed the control group mean has been proposed as an effect size measure for experiments that randomly assign independent units into 2 groups. We give the exact distribution of a simple estimator of π based on the standardized mean difference and use it to study the small sample bias of this estimator. We also give the minimum variance unbiased estimator of π under 2 models, one in which the variance of the mean difference is known and one in which the variance is unknown. We show how to use the relation between the standardized mean difference and the overlap measure to compute confidence intervals for π and show that these results can be used to obtain unbiased estimators, large sample variances, and confidence intervals for 3 related effect size measures based on the overlap. Finally, we show how the effect size π can be used in a meta-analysis. (c) 2016 APA, all rights reserved).

  16. Hollow core waveguide as mid-infrared laser modal beam filter

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Patimisco, P.; Giglio, M.; Spagnolo, V.

    2015-09-21

    A novel method for mid-IR laser beam mode cleaning employing hollow core waveguide as a modal filter element is reported. The influence of the input laser beam quality on fiber optical losses and output beam profile using a hollow core waveguide with 200 μm-bore size was investigated. Our results demonstrate that even when using a laser with a poor spatial profile, there will exist a minimum fiber length that allows transmission of only the Gaussian-like fundamental waveguide mode from the fiber, filtering out all the higher order modes. This essentially single mode output is preserved also when the waveguide is bentmore » to a radius of curvature of 7.5 cm, which demonstrates that laser mode filtering can be realized even if a curved light path is required.« less

  17. Wavelet-based multiscale analysis of minimum toe clearance variability in the young and elderly during walking.

    PubMed

    Khandoker, Ahsan H; Karmakar, Chandan K; Begg, Rezaul K; Palaniswami, Marimuthu

    2007-01-01

    As humans age or are influenced by pathology of the neuromuscular system, gait patterns are known to adjust, accommodating for reduced function in the balance control system. The aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum toe clearance (MTC)] in deriving indexes for understanding age-related declines in gait performance and screening of balance impairments in the elderly. MTC during walking on a treadmill for 30 healthy young, 27 healthy elderly and 10 falls risk elderly subjects with a history of tripping falls were analyzed. The MTC signal from each subject was decomposed to eight detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 8 to 1 were calculated. The multiscale exponent (beta) was then estimated from the slope of the variance progression at successive scales. The variance at scale 5 was significantly (p<0.01) different between young and healthy elderly group. Results also suggest that the Beta between scales 1 to 2 are effective for recognizing falls risk gait patterns. Results have implication for quantifying gait dynamics in normal, ageing and pathological conditions. Early detection of gait pattern changes due to ageing and balance impairments using wavelet-based multiscale analysis might provide the opportunity to initiate preemptive measures to be undertaken to avoid injurious falls.

  18. Determining size and dispersion of minimum viable populations for land management planning and species conservation

    NASA Astrophysics Data System (ADS)

    Lehmkuhl, John F.

    1984-03-01

    The concept of minimum populations of wildlife and plants has only recently been discussed in the literature. Population genetics has emerged as a basic underlying criterion for determining minimum population size. This paper presents a genetic framework and procedure for determining minimum viable population size and dispersion strategies in the context of multiple-use land management planning. A procedure is presented for determining minimum population size based on maintenance of genetic heterozygosity and reduction of inbreeding. A minimum effective population size ( N e ) of 50 breeding animals is taken from the literature as the minimum shortterm size to keep inbreeding below 1% per generation. Steps in the procedure adjust N e to account for variance in progeny number, unequal sex ratios, overlapping generations, population fluctuations, and period of habitat/population constraint. The result is an approximate census number that falls within a range of effective population size of 50 500 individuals. This population range defines the time range of short- to long-term population fitness and evolutionary potential. The length of the term is a relative function of the species generation time. Two population dispersion strategies are proposed: core population and dispersed population.

  19. An effect size filter improves the reproducibility in spectral counting-based comparative proteomics.

    PubMed

    Gregori, Josep; Villarreal, Laura; Sánchez, Alex; Baselga, José; Villanueva, Josep

    2013-12-16

    The microarray community has shown that the low reproducibility observed in gene expression-based biomarker discovery studies is partially due to relying solely on p-values to get the lists of differentially expressed genes. Their conclusions recommended complementing the p-value cutoff with the use of effect-size criteria. The aim of this work was to evaluate the influence of such an effect-size filter on spectral counting-based comparative proteomic analysis. The results proved that the filter increased the number of true positives and decreased the number of false positives and the false discovery rate of the dataset. These results were confirmed by simulation experiments where the effect size filter was used to evaluate systematically variable fractions of differentially expressed proteins. Our results suggest that relaxing the p-value cut-off followed by a post-test filter based on effect size and signal level thresholds can increase the reproducibility of statistical results obtained in comparative proteomic analysis. Based on our work, we recommend using a filter consisting of a minimum absolute log2 fold change of 0.8 and a minimum signal of 2-4 SpC on the most abundant condition for the general practice of comparative proteomics. The implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of the results obtained among independent laboratories and MS platforms. Quality control analysis of microarray-based gene expression studies pointed out that the low reproducibility observed in the lists of differentially expressed genes could be partially attributed to the fact that these lists are generated relying solely on p-values. Our study has established that the implementation of an effect size post-test filter improves the statistical results of spectral count-based quantitative proteomics. The results proved that the filter increased the number of true positives whereas decreased the false positives and the false discovery rate of the datasets. The results presented here prove that a post-test filter applying a reasonable effect size and signal level thresholds helps to increase the reproducibility of statistical results in comparative proteomic analysis. Furthermore, the implementation of feature filtering approaches could improve proteomic biomarker discovery initiatives by increasing the reproducibility of results obtained among independent laboratories and MS platforms. This article is part of a Special Issue entitled: Standardization and Quality Control in Proteomics. Copyright © 2013 Elsevier B.V. All rights reserved.

  20. Classification of Salmonella serotypes with hyperspectral microscope imagery

    USDA-ARS?s Scientific Manuscript database

    Previous research has demonstrated an optical method with acousto-optic tunable filter (AOTF) based hyperspectral microscope imaging (HMI) had potential for classifying gram-negative from gram-positive foodborne pathogenic bacteria rapidly and nondestructively with a minimum sample preparation. In t...

  1. Design of a composite filter realizable on practical spatial light modulators

    NASA Technical Reports Server (NTRS)

    Rajan, P. K.; Ramakrishnan, Ramachandran

    1994-01-01

    Hybrid optical correlator systems use two spatial light modulators (SLM's), one at the input plane and the other at the filter plane. Currently available SLM's such as the deformable mirror device (DMD) and liquid crystal television (LCTV) SLM's exhibit arbitrarily constrained operating characteristics. The pattern recognition filters designed with the assumption that the SLM's have ideal operating characteristic may not behave as expected when implemented on the DMD or LCTV SLM's. Therefore it is necessary to incorporate the SLM constraints in the design of the filters. In this report, an iterative method is developed for the design of an unconstrained minimum average correlation energy (MACE) filter. Then using this algorithm a new approach for the design of a SLM constrained distortion invariant filter in the presence of input SLM is developed. Two different optimization algorithms are used to maximize the objective function during filter synthesis, one based on the simplex method and the other based on the Hooke and Jeeves method. Also, the simulated annealing based filter design algorithm proposed by Khan and Rajan is refined and improved. The performance of the filter is evaluated in terms of its recognition/discrimination capabilities using computer simulations and the results are compared with a simulated annealing optimization based MACE filter. The filters are designed for different LCTV SLM's operating characteristics and the correlation responses are compared. The distortion tolerance and the false class image discrimination qualities of the filter are comparable to those of the simulated annealing based filter but the new filter design takes about 1/6 of the computer time taken by the simulated annealing filter design.

  2. Uncertainty in Population Estimates for Endangered Animals and Improving the Recovery Process

    PubMed Central

    Haines, Aaron M.; Zak, Matthew; Hammond, Katie; Scott, J. Michael; Goble, Dale D.; Rachlow, Janet L.

    2013-01-01

    Simple Summary The objective of our study was to evaluate the mention of uncertainty (i.e., variance) associated with population size estimates within U.S. recovery plans for endangered animals. To do this we reviewed all finalized recovery plans for listed terrestrial vertebrate species. We found that more recent recovery plans reported more estimates of population size and uncertainty. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty. We recommend that updated recovery plans combine uncertainty of population size estimates with a minimum detectable difference to aid in successful recovery. Abstract United States recovery plans contain biological information for a species listed under the Endangered Species Act and specify recovery criteria to provide basis for species recovery. The objective of our study was to evaluate whether recovery plans provide uncertainty (e.g., variance) with estimates of population size. We reviewed all finalized recovery plans for listed terrestrial vertebrate species to record the following data: (1) if a current population size was given, (2) if a measure of uncertainty or variance was associated with current estimates of population size and (3) if population size was stipulated for recovery. We found that 59% of completed recovery plans specified a current population size, 14.5% specified a variance for the current population size estimate and 43% specified population size as a recovery criterion. More recent recovery plans reported more estimates of current population size, uncertainty and population size as a recovery criterion. Also, bird and mammal recovery plans reported more estimates of population size and uncertainty compared to reptiles and amphibians. We suggest the use of calculating minimum detectable differences to improve confidence when delisting endangered animals and we identified incentives for individuals to get involved in recovery planning to improve access to quantitative data. PMID:26479531

  3. Sampling intraspecific variability in leaf functional traits: Practical suggestions to maximize collected information.

    PubMed

    Petruzzellis, Francesco; Palandrani, Chiara; Savi, Tadeja; Alberti, Roberto; Nardini, Andrea; Bacaro, Giovanni

    2017-12-01

    The choice of the best sampling strategy to capture mean values of functional traits for a species/population, while maintaining information about traits' variability and minimizing the sampling size and effort, is an open issue in functional trait ecology. Intraspecific variability (ITV) of functional traits strongly influences sampling size and effort. However, while adequate information is available about intraspecific variability between individuals (ITV BI ) and among populations (ITV POP ), relatively few studies have analyzed intraspecific variability within individuals (ITV WI ). Here, we provide an analysis of ITV WI of two foliar traits, namely specific leaf area (SLA) and osmotic potential (π), in a population of Quercus ilex L. We assessed the baseline ITV WI level of variation between the two traits and provided the minimum and optimal sampling size in order to take into account ITV WI , comparing sampling optimization outputs with those previously proposed in the literature. Different factors accounted for different amount of variance of the two traits. SLA variance was mostly spread within individuals (43.4% of the total variance), while π variance was mainly spread between individuals (43.2%). Strategies that did not account for all the canopy strata produced mean values not representative of the sampled population. The minimum size to adequately capture the studied functional traits corresponded to 5 leaves taken randomly from 5 individuals, while the most accurate and feasible sampling size was 4 leaves taken randomly from 10 individuals. We demonstrate that the spatial structure of the canopy could significantly affect traits variability. Moreover, different strategies for different traits could be implemented during sampling surveys. We partially confirm sampling sizes previously proposed in the recent literature and encourage future analysis involving different traits.

  4. REML/BLUP and sequential path analysis in estimating genotypic values and interrelationships among simple maize grain yield-related traits.

    PubMed

    Olivoto, T; Nardino, M; Carvalho, I R; Follmann, D N; Ferrari, M; Szareski, V J; de Pelegrin, A J; de Souza, V Q

    2017-03-22

    Methodologies using restricted maximum likelihood/best linear unbiased prediction (REML/BLUP) in combination with sequential path analysis in maize are still limited in the literature. Therefore, the aims of this study were: i) to use REML/BLUP-based procedures in order to estimate variance components, genetic parameters, and genotypic values of simple maize hybrids, and ii) to fit stepwise regressions considering genotypic values to form a path diagram with multi-order predictors and minimum multicollinearity that explains the relationships of cause and effect among grain yield-related traits. Fifteen commercial simple maize hybrids were evaluated in multi-environment trials in a randomized complete block design with four replications. The environmental variance (78.80%) and genotype-vs-environment variance (20.83%) accounted for more than 99% of the phenotypic variance of grain yield, which difficult the direct selection of breeders for this trait. The sequential path analysis model allowed the selection of traits with high explanatory power and minimum multicollinearity, resulting in models with elevated fit (R 2 > 0.9 and ε < 0.3). The number of kernels per ear (NKE) and thousand-kernel weight (TKW) are the traits with the largest direct effects on grain yield (r = 0.66 and 0.73, respectively). The high accuracy of selection (0.86 and 0.89) associated with the high heritability of the average (0.732 and 0.794) for NKE and TKW, respectively, indicated good reliability and prospects of success in the indirect selection of hybrids with high-yield potential through these traits. The negative direct effect of NKE on TKW (r = -0.856), however, must be considered. The joint use of mixed models and sequential path analysis is effective in the evaluation of maize-breeding trials.

  5. A de-noising method using the improved wavelet threshold function based on noise variance estimation

    NASA Astrophysics Data System (ADS)

    Liu, Hui; Wang, Weida; Xiang, Changle; Han, Lijin; Nie, Haizhao

    2018-01-01

    The precise and efficient noise variance estimation is very important for the processing of all kinds of signals while using the wavelet transform to analyze signals and extract signal features. In view of the problem that the accuracy of traditional noise variance estimation is greatly affected by the fluctuation of noise values, this study puts forward the strategy of using the two-state Gaussian mixture model to classify the high-frequency wavelet coefficients in the minimum scale, which takes both the efficiency and accuracy into account. According to the noise variance estimation, a novel improved wavelet threshold function is proposed by combining the advantages of hard and soft threshold functions, and on the basis of the noise variance estimation algorithm and the improved wavelet threshold function, the research puts forth a novel wavelet threshold de-noising method. The method is tested and validated using random signals and bench test data of an electro-mechanical transmission system. The test results indicate that the wavelet threshold de-noising method based on the noise variance estimation shows preferable performance in processing the testing signals of the electro-mechanical transmission system: it can effectively eliminate the interference of transient signals including voltage, current, and oil pressure and maintain the dynamic characteristics of the signals favorably.

  6. Heat and moisture exchangers and breathing system filters: their use in anaesthesia and intensive care. Part 1 - history, principles and efficiency.

    PubMed

    Wilkes, A R

    2011-01-01

    Heat and moisture exchangers and breathing system filters are intended to replace the normal warming, humidifying and filtering functions of the upper airways when these structures are bypassed during anaesthesia and intensive care. Guidance on their use continues to evolve. The aim of this part of the review is to describe the principles of their action and efficiency and to summarise the findings from clinical and laboratory studies. Based on previous studies, an appropriate minimum target for moisture output is 30 and 20 g.m⁻³ for long-duration use in intensive care and short-duration use in anaesthesia, respectively. The practice of reusing a breathing system in anaesthesia, provided it is protected by a filter, assumes that the filter is effective. However, there is wide variation in the gas-borne filtration performance, and contaminated condensate can potentially pass through some filters under typical pressures encountered during mechanical ventilation. © 2010 The Author. Anaesthesia © 2010 The Association of Anaesthetists of Great Britain and Ireland.

  7. Cellular traction force recovery: An optimal filtering approach in two-dimensional Fourier space.

    PubMed

    Huang, Jianyong; Qin, Lei; Peng, Xiaoling; Zhu, Tao; Xiong, Chunyang; Zhang, Youyi; Fang, Jing

    2009-08-21

    Quantitative estimation of cellular traction has significant physiological and clinical implications. As an inverse problem, traction force recovery is essentially susceptible to noise in the measured displacement data. For traditional procedure of Fourier transform traction cytometry (FTTC), noise amplification is accompanied in the force reconstruction and small tractions cannot be recovered from the displacement field with low signal-noise ratio (SNR). To improve the FTTC process, we develop an optimal filtering scheme to suppress the noise in the force reconstruction procedure. In the framework of the Wiener filtering theory, four filtering parameters are introduced in two-dimensional Fourier space and their analytical expressions are derived in terms of the minimum-mean-squared-error (MMSE) optimization criterion. The optimal filtering approach is validated with simulations and experimental data associated with the adhesion of single cardiac myocyte to elastic substrate. The results indicate that the proposed method can highly enhance SNR of the recovered forces to reveal tiny tractions in cell-substrate interaction.

  8. Evaluation of the ICET Test Stand to Assess the Performance of a Range of Ceramic Media Filter Elements in Support of ASME AG-1 Subsection FO

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Schemmel, A.

    High Efficiency Particulate Air (HEPA) filters are defined as extended-medium, dry-type filters with: (1) a minimum particle removal efficiency of no less than 99.97 percent for 0.3 micrometer particles, (2) a maximum, clean resistance of 1.0 inch water column (in. WC) when operated at 1,000 cubic feet per minute (CFM), and (3) a rigid casing that extends the full depth of the medium. Specifically, ceramic media HEPA filters provide better performance at elevated temperatures, are moisture resistant and nonflammable, can perform their function if wetted and exposed to greater pressures, and can be cleaned and reused. This paper describes themore » modification and design of a large scale test stand which properly evaluates the filtration characteristics of a range of ceramic media filters challenged with a nuclear aerosol agent in order to develop Section FO of ASME AG-1.« less

  9. A three-mode microstrip resonator and a miniature ultra-wideband filter based on it

    NASA Astrophysics Data System (ADS)

    Belyaev, B. A.; Khodenkov, S. A.; Leksikov, An. A.; Shabanov, V. F.

    2017-06-01

    An original microstrip resonator design with a strip conductor split by a slot at one of its ends is investigated. It is demonstrated that at the optimal slot sizes, when the eigenfrequency of the second oscillation mode hits the center between the first and third oscillation modes, the resonator can work as a thirdorder bandpass filter. The structure formed from only two such resonators electromagnetically coupled by split conductor sections is a miniature six-order wideband filter with high selectivity. The test prototype of the filter with a central passband frequency of 1.2 GHz and a passband width of 0.75 GHz fabricated on a substrate (45 × 11 × 1) mm3 in size with a permittivity of 80 is characterized by minimum loss in a passband of 0.5 dB. The parametric synthesis of the filter structure was performed using electrodynamic analysis of the 3D model. The measured characteristics of the test prototype agree well with the calculated data.

  10. Design of adaptive control systems by means of self-adjusting transversal filters

    NASA Technical Reports Server (NTRS)

    Merhav, S. J.

    1986-01-01

    The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

  11. Improving indoor air quality and thermal comfort in office building by using combination filters

    NASA Astrophysics Data System (ADS)

    Kabrein, H.; Yusof, M. Z. M.; Hariri, A.; Leman, A. M.; Afandi, A.

    2017-09-01

    Poor indoor air quality and thermal comfort condition in the workspace affected the occupants’ health and work productivity, especially when adapting the recirculation of air in heating ventilation and air-conditioning (HVAC) system. The recirculation of air was implemented in this study by mixing the circulated returned indoor air with the outdoor fresh air. The aims of this study are to assess the indoor thermal comfort and indoor air quality (IAQ) in the office buildings, equipped with combination filters. The air filtration technique consisting minimum efficiency reporting value (MERV) filter and activated carbon fiber (ACF) filter, located before the fan coil units. The findings of the study show that the technique of mixing recirculation air with the fresh air through the combination filters met the recommended thermal comfort condition in the workspace. Furthermore, the result of the post-occupancy evaluation (POE) and the environmental measurements comply with the ASHRAE 55 standard. In addition, the level of CO2 concentration continued to decrease during the period of the measurement.

  12. Applications of Kalman filtering to real-time trace gas concentration measurements

    NASA Technical Reports Server (NTRS)

    Leleux, D. P.; Claps, R.; Chen, W.; Tittel, F. K.; Harman, T. L.

    2002-01-01

    A Kalman filtering technique is applied to the simultaneous detection of NH3 and CO2 with a diode-laser-based sensor operating at 1.53 micrometers. This technique is developed for improving the sensitivity and precision of trace gas concentration levels based on direct overtone laser absorption spectroscopy in the presence of various sensor noise sources. Filter performance is demonstrated to be adaptive to real-time noise and data statistics. Additionally, filter operation is successfully performed with dynamic ranges differing by three orders of magnitude. Details of Kalman filter theory applied to the acquired spectroscopic data are discussed. The effectiveness of this technique is evaluated by performing NH3 and CO2 concentration measurements and utilizing it to monitor varying ammonia and carbon dioxide levels in a bioreactor for water reprocessing, located at the NASA-Johnson Space Center. Results indicate a sensitivity enhancement of six times, in terms of improved minimum detectable absorption by the gas sensor.

  13. Sequential Blood Filtration for Extracorporeal Circulation: Initial Results from a Proof-of-Concept Prototype.

    PubMed

    Herbst, Daniel P

    2014-09-01

    Micropore filters are used during extracorporeal circulation to prevent gaseous and solid particles from entering the patient's systemic circulation. Although these devices improve patient safety, limitations in current designs have prompted the development of a new concept in micropore filtration. A prototype of the new design was made using 40-μm filter screens and compared against four commercially available filters for performance in pressure loss and gross air handling. Pre- and postfilter bubble counts for 5- and 10-mL bolus injections in an ex vivo test circuit were recorded using a Doppler ultrasound bubble counter. Statistical analysis of results for bubble volume reduction between test filters was performed with one-way repeated-measures analysis of variance using Bonferroni post hoc tests. Changes in filter performance with changes in microbubble load were also assessed with dependent t tests using the 5- and 10-mL bolus injections as the paired sample for each filter. Significance was set at p < .05. All filters in the test group were comparable in pressure loss performance, showing a range of 26-33 mmHg at a flow rate of 6 L/min. In gross air-handling studies, the prototype showed improved bubble volume reduction, reaching statistical significance with three of the four commercial filters. All test filters showed decreased performance in bubble volume reduction when the microbubble load was increased. Findings from this research support the underpinning theories of a sequential arterial-line filter design and suggest that improvements in microbubble filtration may be possible using this technique.

  14. Sequential Blood Filtration for Extracorporeal Circulation: Initial Results from a Proof-of-Concept Prototype

    PubMed Central

    Herbst, Daniel P.

    2014-01-01

    Abstract: Micropore filters are used during extracorporeal circulation to prevent gaseous and solid particles from entering the patient’s systemic circulation. Although these devices improve patient safety, limitations in current designs have prompted the development of a new concept in micropore filtration. A prototype of the new design was made using 40-μm filter screens and compared against four commercially available filters for performance in pressure loss and gross air handling. Pre- and postfilter bubble counts for 5- and 10-mL bolus injections in an ex vivo test circuit were recorded using a Doppler ultrasound bubble counter. Statistical analysis of results for bubble volume reduction between test filters was performed with one-way repeated-measures analysis of variance using Bonferroni post hoc tests. Changes in filter performance with changes in microbubble load were also assessed with dependent t tests using the 5- and 10-mL bolus injections as the paired sample for each filter. Significance was set at p < .05. All filters in the test group were comparable in pressure loss performance, showing a range of 26–33 mmHg at a flow rate of 6 L/min. In gross air-handling studies, the prototype showed improved bubble volume reduction, reaching statistical significance with three of the four commercial filters. All test filters showed decreased performance in bubble volume reduction when the microbubble load was increased. Findings from this research support the underpinning theories of a sequential arterial-line filter design and suggest that improvements in microbubble filtration may be possible using this technique. PMID:26357790

  15. Differences in radial expansion force among inferior vena cava filter models support documented perforation rates.

    PubMed

    Robins, J Eli; Ragai, Ihab; Yamaguchi, Dean J

    2018-05-01

    Inferior vena cava (IVC) filters are used in patients at risk for pulmonary embolism who cannot be anticoagulated. Unfortunately, these filters are not without risk, and complications include perforation, migration, and filter fracture. The most prevalent complication is filter perforation of the IVC, with incidence varying among filter models. To our knowledge, the mechanical properties of IVC filters have not been evaluated and are not readily available through the manufacturer. This study sought to determine whether differences in mechanical properties are similar to differences in documented perforation rates. The radial expansion forces of Greenfield (Boston Scientific, Marlborough, Mass), Cook Celect (Cook Medical, Bloomington, Ind), and Cook Platinum filters were analyzed with three replicates per group. The intrinsic force exerted by the filter on the measuring device was collected in real time during controlled expansion. Replicates were averaged and significance was determined by calculating analysis of covariance using SAS software (SAS Institute, Cary, NC). Each filter model generated a significantly different radial expansion force (P < .001), and force was distributed at significantly different rates (P < .001) during expansion. The largest radial expansion force at minimal caval diameter was seen in the Cook Platinum filter, followed by the Cook Celect and Greenfield filters. Radial force dispersion during expansion was greatest in the Cook Celect, followed by the Cook Platinum and Greenfield filters. Differences in radial expansion forces among IVC filter models are consistent with documented perforation rates. Cook Celect IVC filters have a higher incidence of perforation compared with Greenfield filters when they are left in place for >90 days. Evaluation of Cook Celect filters yielded a significantly higher radial expansion force at minimum caval diameter, with greater force dispersion during expansion. Copyright © 2018 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  16. Effects of radiative heat transfer on the turbulence structure in inert and reacting mixing layers

    NASA Astrophysics Data System (ADS)

    Ghosh, Somnath; Friedrich, Rainer

    2015-05-01

    We use large-eddy simulation to study the interaction between turbulence and radiative heat transfer in low-speed inert and reacting plane temporal mixing layers. An explicit filtering scheme based on approximate deconvolution is applied to treat the closure problem arising from quadratic nonlinearities of the filtered transport equations. In the reacting case, the working fluid is a mixture of ideal gases where the low-speed stream consists of hydrogen and nitrogen and the high-speed stream consists of oxygen and nitrogen. Both streams are premixed in a way that the free-stream densities are the same and the stoichiometric mixture fraction is 0.3. The filtered heat release term is modelled using equilibrium chemistry. In the inert case, the low-speed stream consists of nitrogen at a temperature of 1000 K and the highspeed stream is pure water vapour of 2000 K, when radiation is turned off. Simulations assuming the gas mixtures as gray gases with artificially increased Planck mean absorption coefficients are performed in which the large-eddy simulation code and the radiation code PRISSMA are fully coupled. In both cases, radiative heat transfer is found to clearly affect fluctuations of thermodynamic variables, Reynolds stresses, and Reynolds stress budget terms like pressure-strain correlations. Source terms in the transport equation for the variance of temperature are used to explain the decrease of this variance in the reacting case and its increase in the inert case.

  17. Effects of radiative heat transfer on the turbulence structure in inert and reacting mixing layers

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ghosh, Somnath, E-mail: sghosh@aero.iitkgp.ernet.in; Friedrich, Rainer

    2015-05-15

    We use large-eddy simulation to study the interaction between turbulence and radiative heat transfer in low-speed inert and reacting plane temporal mixing layers. An explicit filtering scheme based on approximate deconvolution is applied to treat the closure problem arising from quadratic nonlinearities of the filtered transport equations. In the reacting case, the working fluid is a mixture of ideal gases where the low-speed stream consists of hydrogen and nitrogen and the high-speed stream consists of oxygen and nitrogen. Both streams are premixed in a way that the free-stream densities are the same and the stoichiometric mixture fraction is 0.3. Themore » filtered heat release term is modelled using equilibrium chemistry. In the inert case, the low-speed stream consists of nitrogen at a temperature of 1000 K and the highspeed stream is pure water vapour of 2000 K, when radiation is turned off. Simulations assuming the gas mixtures as gray gases with artificially increased Planck mean absorption coefficients are performed in which the large-eddy simulation code and the radiation code PRISSMA are fully coupled. In both cases, radiative heat transfer is found to clearly affect fluctuations of thermodynamic variables, Reynolds stresses, and Reynolds stress budget terms like pressure-strain correlations. Source terms in the transport equation for the variance of temperature are used to explain the decrease of this variance in the reacting case and its increase in the inert case.« less

  18. Nonlinear Bayesian filtering and learning: a neuronal dynamics for perception.

    PubMed

    Kutschireiter, Anna; Surace, Simone Carlo; Sprekeler, Henning; Pfister, Jean-Pascal

    2017-08-18

    The robust estimation of dynamical hidden features, such as the position of prey, based on sensory inputs is one of the hallmarks of perception. This dynamical estimation can be rigorously formulated by nonlinear Bayesian filtering theory. Recent experimental and behavioral studies have shown that animals' performance in many tasks is consistent with such a Bayesian statistical interpretation. However, it is presently unclear how a nonlinear Bayesian filter can be efficiently implemented in a network of neurons that satisfies some minimum constraints of biological plausibility. Here, we propose the Neural Particle Filter (NPF), a sampling-based nonlinear Bayesian filter, which does not rely on importance weights. We show that this filter can be interpreted as the neuronal dynamics of a recurrently connected rate-based neural network receiving feed-forward input from sensory neurons. Further, it captures properties of temporal and multi-sensory integration that are crucial for perception, and it allows for online parameter learning with a maximum likelihood approach. The NPF holds the promise to avoid the 'curse of dimensionality', and we demonstrate numerically its capability to outperform weighted particle filters in higher dimensions and when the number of particles is limited.

  19. Collisional considerations in axial-collection plasma mass filters

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Ochs, I. E.; Gueroult, R.; Fisch, N. J.

    The chemical inhomogeneity of nuclear waste makes chemical separations difficult, while the correlation between radioactivity and nuclear mass makes mass-based separation, and in particular plasma-based separation, an attractive alternative. Here, we examine a particular class of plasma mass filters, namely filters in which (a) species of different masses are collected along magnetic field lines at opposite ends of an open-field-line plasma device and (b) gyro-drift effects are important for the separation process. Using an idealized cylindrical model, we derive a set of dimensionless parameters which provide minimum necessary conditions for an effective mass filter function in the presence of ion-ionmore » and ion-neutral collisions. Through simulations of the constant-density profile, turbulence-free devices, we find that these parameters accurately describe the mass filter performance in more general magnetic geometries. We then use these parameters to study the design and upgrade of current experiments, as well as to derive general scalings for the throughput of production mass filters. Most importantly, we find that ion temperatures above 3 eV and magnetic fields above 104 G are critical to ensure a feasible mass filter function when operating at an ion density of 10 13 cm –3.« less

  20. Collisional considerations in axial-collection plasma mass filters

    DOE PAGES

    Ochs, I. E.; Gueroult, R.; Fisch, N. J.; ...

    2017-04-01

    The chemical inhomogeneity of nuclear waste makes chemical separations difficult, while the correlation between radioactivity and nuclear mass makes mass-based separation, and in particular plasma-based separation, an attractive alternative. Here, we examine a particular class of plasma mass filters, namely filters in which (a) species of different masses are collected along magnetic field lines at opposite ends of an open-field-line plasma device and (b) gyro-drift effects are important for the separation process. Using an idealized cylindrical model, we derive a set of dimensionless parameters which provide minimum necessary conditions for an effective mass filter function in the presence of ion-ionmore » and ion-neutral collisions. Through simulations of the constant-density profile, turbulence-free devices, we find that these parameters accurately describe the mass filter performance in more general magnetic geometries. We then use these parameters to study the design and upgrade of current experiments, as well as to derive general scalings for the throughput of production mass filters. Most importantly, we find that ion temperatures above 3 eV and magnetic fields above 104 G are critical to ensure a feasible mass filter function when operating at an ion density of 10 13 cm –3.« less

  1. 49 CFR 192.620 - Alternative maximum allowable operating pressure for certain steel pipelines.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... Transportation (Continued) PIPELINE AND HAZARDOUS MATERIALS SAFETY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION (CONTINUED) PIPELINE SAFETY TRANSPORTATION OF NATURAL AND OTHER GAS BY PIPELINE: MINIMUM FEDERAL SAFETY...) At points where gas with potentially deleterious contaminants enters the pipeline, use filter...

  2. Applying six classifiers to airborne hyperspectral imagery for detecting giant reed

    USDA-ARS?s Scientific Manuscript database

    This study evaluated and compared six different image classifiers, including minimum distance (MD), Mahalanobis distance (MAHD), maximum likelihood (ML), spectral angle mapper (SAM), mixture tuned matched filtering (MTMF) and support vector machine (SVM), for detecting and mapping giant reed (Arundo...

  3. Efficient design of cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances.

    PubMed

    van Breukelen, Gerard J P; Candel, Math J J M

    2018-06-10

    Cluster randomized trials evaluate the effect of a treatment on persons nested within clusters, where treatment is randomly assigned to clusters. Current equations for the optimal sample size at the cluster and person level assume that the outcome variances and/or the study costs are known and homogeneous between treatment arms. This paper presents efficient yet robust designs for cluster randomized trials with treatment-dependent costs and treatment-dependent unknown variances, and compares these with 2 practical designs. First, the maximin design (MMD) is derived, which maximizes the minimum efficiency (minimizes the maximum sampling variance) of the treatment effect estimator over a range of treatment-to-control variance ratios. The MMD is then compared with the optimal design for homogeneous variances and costs (balanced design), and with that for homogeneous variances and treatment-dependent costs (cost-considered design). The results show that the balanced design is the MMD if the treatment-to control cost ratio is the same at both design levels (cluster, person) and within the range for the treatment-to-control variance ratio. It still is highly efficient and better than the cost-considered design if the cost ratio is within the range for the squared variance ratio. Outside that range, the cost-considered design is better and highly efficient, but it is not the MMD. An example shows sample size calculation for the MMD, and the computer code (SPSS and R) is provided as supplementary material. The MMD is recommended for trial planning if the study costs are treatment-dependent and homogeneity of variances cannot be assumed. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  4. A new method for inferring carbon monoxide concentrations from gas filter radiometer data

    NASA Technical Reports Server (NTRS)

    Wallio, H. A.; Reichle, H. G., Jr.; Casas, J. C.; Gormsen, B. B.

    1981-01-01

    A method for inferring carbon monoxide concentrations from gas filter radiometer data is presented. The technique can closely approximate the results of more costly line-by-line radiative transfer calculations over a wide range of altitudes, ground temperatures, and carbon monoxide concentrations. The technique can also be used over a larger range of conditions than those used for the regression analysis. Because the influence of the carbon monoxide mixing ratio requires only addition, multiplication and a minimum of logic, the method can be implemented on very small computers or microprocessors.

  5. The Effect of Diethylene Glycol Monomethyl Ether (DiEGME) on Microbial Contamination of Jet Fuel: A Minimum Concentration Study

    DTIC Science & Technology

    2010-03-01

    added as appropriate. Fuel was filtered with a 0.45µm hydrophobic cellulose nitrate filter (Nalge Nunc, Rochester, NY) prior to use in the test setup...it may not be clear from the images above, biofilms were also present in all 0% test setups. In fuel systems, a biofilm is a microbial growth...formation that typically appears as a sheen, pellicule, or mat that forms between the fuel and water layers or on the interior sides of a tank. Biofilms

  6. Numerically stable algorithm for combining census and sample estimates with the multivariate composite estimator

    Treesearch

    R. L. Czaplewski

    2009-01-01

    The minimum variance multivariate composite estimator is a relatively simple sequential estimator for complex sampling designs (Czaplewski 2009). Such designs combine a probability sample of expensive field data with multiple censuses and/or samples of relatively inexpensive multi-sensor, multi-resolution remotely sensed data. Unfortunately, the multivariate composite...

  7. Multiple Signal Classification for Determining Direction of Arrival of Frequency Hopping Spread Spectrum Signals

    DTIC Science & Technology

    2014-03-27

    42 4.2.3 Number of Hops Hs . . . . . . . . . . . . . . . . . . . . . . . . . 45 4.2.4 Number of Sensors M... 45 4.5 Standard deviation vs. Ns. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 4.6 Bias...laboratory MTM multiple taper method MUSIC multiple signal classification MVDR minimum variance distortionless reposnse PSK phase shift keying QAM

  8. Attitude Determination Using a MEMS-Based Flight Information Measurement Unit

    PubMed Central

    Ma, Der-Ming; Shiau, Jaw-Kuen; Wang, I.-Chiang; Lin, Yu-Heng

    2012-01-01

    Obtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to integrate the traditional quaternion and gravitational force decomposition methods for attitude determination algorithm. The proposed extended Kalman filter utilizes the evolution of the four elements in the quaternion method for attitude determination as the dynamic model, with the four elements as the states of the filter. The attitude angles obtained from the gravity computations and from the electronic magnetic sensors are regarded as the measurement of the filter. The immeasurable gravity accelerations are deduced from the outputs of the three axes accelerometers, the relative accelerations, and the accelerations due to body rotation. The constraint of the four elements of the quaternion method is treated as a perfect measurement and is integrated into the filter computation. Approximations of the time-varying noise variances of the measured signals are discussed and presented with details through Taylor series expansions. The algorithm is intuitive, easy to implement, and reliable for long-term high dynamic maneuvers. Moreover, a set of flight test data is utilized to demonstrate the success and practicality of the proposed algorithm and the filter design. PMID:22368455

  9. Attitude determination using a MEMS-based flight information measurement unit.

    PubMed

    Ma, Der-Ming; Shiau, Jaw-Kuen; Wang, I-Chiang; Lin, Yu-Heng

    2012-01-01

    Obtaining precise attitude information is essential for aircraft navigation and control. This paper presents the results of the attitude determination using an in-house designed low-cost MEMS-based flight information measurement unit. This study proposes a quaternion-based extended Kalman filter to integrate the traditional quaternion and gravitational force decomposition methods for attitude determination algorithm. The proposed extended Kalman filter utilizes the evolution of the four elements in the quaternion method for attitude determination as the dynamic model, with the four elements as the states of the filter. The attitude angles obtained from the gravity computations and from the electronic magnetic sensors are regarded as the measurement of the filter. The immeasurable gravity accelerations are deduced from the outputs of the three axes accelerometers, the relative accelerations, and the accelerations due to body rotation. The constraint of the four elements of the quaternion method is treated as a perfect measurement and is integrated into the filter computation. Approximations of the time-varying noise variances of the measured signals are discussed and presented with details through Taylor series expansions. The algorithm is intuitive, easy to implement, and reliable for long-term high dynamic maneuvers. Moreover, a set of flight test data is utilized to demonstrate the success and practicality of the proposed algorithm and the filter design.

  10. Multipoint Optimal Minimum Entropy Deconvolution and Convolution Fix: Application to vibration fault detection

    NASA Astrophysics Data System (ADS)

    McDonald, Geoff L.; Zhao, Qing

    2017-01-01

    Minimum Entropy Deconvolution (MED) has been applied successfully to rotating machine fault detection from vibration data, however this method has limitations. A convolution adjustment to the MED definition and solution is proposed in this paper to address the discontinuity at the start of the signal - in some cases causing spurious impulses to be erroneously deconvolved. A problem with the MED solution is that it is an iterative selection process, and will not necessarily design an optimal filter for the posed problem. Additionally, the problem goal in MED prefers to deconvolve a single-impulse, while in rotating machine faults we expect one impulse-like vibration source per rotational period of the faulty element. Maximum Correlated Kurtosis Deconvolution was proposed to address some of these problems, and although it solves the target goal of multiple periodic impulses, it is still an iterative non-optimal solution to the posed problem and only solves for a limited set of impulses in a row. Ideally, the problem goal should target an impulse train as the output goal, and should directly solve for the optimal filter in a non-iterative manner. To meet these goals, we propose a non-iterative deconvolution approach called Multipoint Optimal Minimum Entropy Deconvolution Adjusted (MOMEDA). MOMEDA proposes a deconvolution problem with an infinite impulse train as the goal and the optimal filter solution can be solved for directly. From experimental data on a gearbox with and without a gear tooth chip, we show that MOMEDA and its deconvolution spectrums according to the period between the impulses can be used to detect faults and study the health of rotating machine elements effectively.

  11. Correlation filtering in financial time series (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Aste, T.; Di Matteo, Tiziana; Tumminello, M.; Mantegna, R. N.

    2005-05-01

    We apply a method to filter relevant information from the correlation coefficient matrix by extracting a network of relevant interactions. This method succeeds to generate networks with the same hierarchical structure of the Minimum Spanning Tree but containing a larger amount of links resulting in a richer network topology allowing loops and cliques. In Tumminello et al.,1 we have shown that this method, applied to a financial portfolio of 100 stocks in the USA equity markets, is pretty efficient in filtering relevant information about the clustering of the system and its hierarchical structure both on the whole system and within each cluster. In particular, we have found that triangular loops and 4 element cliques have important and significant relations with the market structure and properties. Here we apply this filtering procedure to the analysis of correlation in two different kind of interest rate time series (16 Eurodollars and 34 US interest rates).

  12. Ultra-Low Background Measurements Of Decayed Aerosol Filters

    NASA Astrophysics Data System (ADS)

    Miley, H.

    2009-04-01

    To experimentally evaluate the opportunity to apply ultra-low background measurement methods to samples collected, for instance, by the Comprehensive Test Ban Treaty International Monitoring System (IMS), aerosol samples collected on filter media were measured using HPGe spectrometers of varying low-background technology approaches. In this way, realistic estimates of the impact of low-background methodology can be assessed on the Minimum Detectable Activities obtained in systems such as the IMS. The current measurement requirement of stations in the IMS is 30 microBq per cubic meter of air for 140Ba, or about 106 fissions per daily sample. Importantly, this is for a fresh aerosol filter. Decay varying form 3 days to one week reduce the intrinsic background from radon daughters in the sample. Computational estimates of the improvement factor for these decayed filters for underground-based HPGe in clean shielding materials are orders of magnitude less, even when the decay of the isotopes of interest is included.

  13. High throughput fabrication of large-area plasmonic color filters by soft-X-ray interference lithography.

    PubMed

    Sun, Libin; Hu, Xiaolin; Wu, Qingjun; Wang, Liansheng; Zhao, Jun; Yang, Shumin; Tai, Renzhong; Fecht, Hans-Jorg; Zhang, Dong-Xian; Wang, Li-Qiang; Jiang, Jian-Zhong

    2016-08-22

    Plasmonic color filters in mass production have been restricted from current fabrication technology, which impede their applications. Soft-X-ray interference lithography (XIL) has recently generated considerable interest as a newly developed technique for the production of periodic nano-structures with resolution theoretically below 4 nm. Here we ameliorate XIL by adding an order sorting aperture and designing the light path properly to achieve perfect-stitching nano-patterns and fast fabrication of large-area color filters. The fill factor of nanostructures prepared on ultrathin Ag films can largely affect the transmission minimum of plasmonic color filters. By changing the fill factor, the color can be controlled flexibly, improving the utilization efficiency of the mask in XIL simultaneously. The calculated data agree well with the experimental results. Finally, an underlying mechanism has been uncovered after systematically analyzing the localized surface plasmon polaritons (LSPPs) coupling in electric field distribution.

  14. Optical security system for the protection of personal identification information.

    PubMed

    Doh, Yang-Hoi; Yoon, Jong-Soo; Choi, Kyung-Hyun; Alam, Mohammad S

    2005-02-10

    A new optical security system for the protection of personal identification information is proposed. First, authentication of the encrypted personal information is carried out by primary recognition of a personal identification number (PIN) with the proposed multiplexed minimum average correlation energy phase-encrypted (MMACE_p) filter. The MMACE_p filter, synthesized with phase-encrypted training images, can increase the discrimination capability and prevent the leak of personal identification information. After the PIN is recognized, speedy authentication of personal information can be achieved through one-to-one optical correlation by means of the optical wavelet filter. The possibility of information counterfeiting can be significantly decreased with the double-identification process. Simulation results demonstrate the effectiveness of the proposed technique.

  15. Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

    NASA Astrophysics Data System (ADS)

    Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah@Rozita

    2014-06-01

    Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stable information ratio.

  16. Optimal Recursive Digital Filters for Active Bending Stabilization

    NASA Technical Reports Server (NTRS)

    Orr, Jeb S.

    2013-01-01

    In the design of flight control systems for large flexible boosters, it is common practice to utilize active feedback control of the first lateral structural bending mode so as to suppress transients and reduce gust loading. Typically, active stabilization or phase stabilization is achieved by carefully shaping the loop transfer function in the frequency domain via the use of compensating filters combined with the frequency response characteristics of the nozzle/actuator system. In this paper we present a new approach for parameterizing and determining optimal low-order recursive linear digital filters so as to satisfy phase shaping constraints for bending and sloshing dynamics while simultaneously maximizing attenuation in other frequency bands of interest, e.g. near higher frequency parasitic structural modes. By parameterizing the filter directly in the z-plane with certain restrictions, the search space of candidate filter designs that satisfy the constraints is restricted to stable, minimum phase recursive low-pass filters with well-conditioned coefficients. Combined with optimal output feedback blending from multiple rate gyros, the present approach enables rapid and robust parametrization of autopilot bending filters to attain flight control performance objectives. Numerical results are presented that illustrate the application of the present technique to the development of rate gyro filters for an exploration-class multi-engined space launch vehicle.

  17. Comparison of fluorescence microscopy and solid-phase cytometry methods for counting bacteria in water

    USGS Publications Warehouse

    Lisle, John T.; Hamilton, Martin A.; Willse, Alan R.; McFeters, Gordon A.

    2004-01-01

    Total direct counts of bacterial abundance are central in assessing the biomass and bacteriological quality of water in ecological and industrial applications. Several factors have been identified that contribute to the variability in bacterial abundance counts when using fluorescent microscopy, the most significant of which is retaining an adequate number of cells per filter to ensure an acceptable level of statistical confidence in the resulting data. Previous studies that have assessed the components of total-direct-count methods that contribute to this variance have attempted to maintain a bacterial cell abundance value per filter of approximately 106 cells filter-1. In this study we have established the lower limit for the number of bacterial cells per filter at which the statistical reliability of the abundance estimate is no longer acceptable. Our results indicate that when the numbers of bacterial cells per filter were progressively reduced below 105, the microscopic methods increasingly overestimated the true bacterial abundance (range, 15.0 to 99.3%). The solid-phase cytometer only slightly overestimated the true bacterial abundances and was more consistent over the same range of bacterial abundances per filter (range, 8.9 to 12.5%). The solid-phase cytometer method for conducting total direct counts of bacteria was less biased and performed significantly better than any of the microscope methods. It was also found that microscopic count data from counting 5 fields on three separate filters were statistically equivalent to data from counting 20 fields on a single filter.

  18. Dual Energy Method for Breast Imaging: A Simulation Study.

    PubMed

    Koukou, V; Martini, N; Michail, C; Sotiropoulou, P; Fountzoula, C; Kalyvas, N; Kandarakis, I; Nikiforidis, G; Fountos, G

    2015-01-01

    Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNR tc ) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels.

  19. Dual Energy Method for Breast Imaging: A Simulation Study

    PubMed Central

    2015-01-01

    Dual energy methods can suppress the contrast between adipose and glandular tissues in the breast and therefore enhance the visibility of calcifications. In this study, a dual energy method based on analytical modeling was developed for the detection of minimum microcalcification thickness. To this aim, a modified radiographic X-ray unit was considered, in order to overcome the limited kVp range of mammographic units used in previous DE studies, combined with a high resolution CMOS sensor (pixel size of 22.5 μm) for improved resolution. Various filter materials were examined based on their K-absorption edge. Hydroxyapatite (HAp) was used to simulate microcalcifications. The contrast to noise ratio (CNRtc) of the subtracted images was calculated for both monoenergetic and polyenergetic X-ray beams. The optimum monoenergetic pair was 23/58 keV for the low and high energy, respectively, resulting in a minimum detectable microcalcification thickness of 100 μm. In the polyenergetic X-ray study, the optimal spectral combination was 40/70 kVp filtered with 100 μm cadmium and 1000 μm copper, respectively. In this case, the minimum detectable microcalcification thickness was 150 μm. The proposed dual energy method provides improved microcalcification detectability in breast imaging with mean glandular dose values within acceptable levels. PMID:26246848

  20. Implementation of a Parallel Kalman Filter for Stratospheric Chemical Tracer Assimilation

    NASA Technical Reports Server (NTRS)

    Chang, Lang-Ping; Lyster, Peter M.; Menard, R.; Cohn, S. E.

    1998-01-01

    A Kalman filter for the assimilation of long-lived atmospheric chemical constituents has been developed for two-dimensional transport models on isentropic surfaces over the globe. An important attribute of the Kalman filter is that it calculates error covariances of the constituent fields using the tracer dynamics. Consequently, the current Kalman-filter assimilation is a five-dimensional problem (coordinates of two points and time), and it can only be handled on computers with large memory and high floating point speed. In this paper, an implementation of the Kalman filter for distributed-memory, message-passing parallel computers is discussed. Two approaches were studied: an operator decomposition and a covariance decomposition. The latter was found to be more scalable than the former, and it possesses the property that the dynamical model does not need to be parallelized, which is of considerable practical advantage. This code is currently used to assimilate constituent data retrieved by limb sounders on the Upper Atmosphere Research Satellite. Tests of the code examined the variance transport and observability properties. Aspects of the parallel implementation, some timing results, and a brief discussion of the physical results will be presented.

  1. Multi-focus image fusion using a guided-filter-based difference image.

    PubMed

    Yan, Xiang; Qin, Hanlin; Li, Jia; Zhou, Huixin; Yang, Tingwu

    2016-03-20

    The aim of multi-focus image fusion technology is to integrate different partially focused images into one all-focused image. To realize this goal, a new multi-focus image fusion method based on a guided filter is proposed and an efficient salient feature extraction method is presented in this paper. Furthermore, feature extraction is primarily the main objective of the present work. Based on salient feature extraction, the guided filter is first used to acquire the smoothing image containing the most sharpness regions. To obtain the initial fusion map, we compose a mixed focus measure by combining the variance of image intensities and the energy of the image gradient together. Then, the initial fusion map is further processed by a morphological filter to obtain a good reprocessed fusion map. Lastly, the final fusion map is determined via the reprocessed fusion map and is optimized by a guided filter. Experimental results demonstrate that the proposed method does markedly improve the fusion performance compared to previous fusion methods and can be competitive with or even outperform state-of-the-art fusion methods in terms of both subjective visual effects and objective quality metrics.

  2. Using frequency analysis to improve the precision of human body posture algorithms based on Kalman filters.

    PubMed

    Olivares, Alberto; Górriz, J M; Ramírez, J; Olivares, G

    2016-05-01

    With the advent of miniaturized inertial sensors many systems have been developed within the last decade to study and analyze human motion and posture, specially in the medical field. Data measured by the sensors are usually processed by algorithms based on Kalman Filters in order to estimate the orientation of the body parts under study. These filters traditionally include fixed parameters, such as the process and observation noise variances, whose value has large influence in the overall performance. It has been demonstrated that the optimal value of these parameters differs considerably for different motion intensities. Therefore, in this work, we show that, by applying frequency analysis to determine motion intensity, and varying the formerly fixed parameters accordingly, the overall precision of orientation estimation algorithms can be improved, therefore providing physicians with reliable objective data they can use in their daily practice. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. Assessing mass change trends in GRACE models

    NASA Astrophysics Data System (ADS)

    Siemes, C.; Liu, X.; Ditmar, P.; Revtova, E.; Slobbe, C.; Klees, R.; Zhao, Q.

    2009-04-01

    The DEOS Mass Transport model, release 1 (DMT-1), has been recently presented to the scientific community. The model is based on GRACE data and consists of sets of spherical harmonic coefficients to degree 120, which are estimated once per month. Currently, the DMT-1 model covers the time span from Feb. 2003 to Dec. 2006. The high spatial resolution of the model could be achieved by applying a statistically optimal Wiener-type filter, which is superior to standard filtering techniques. The optimal Wiener-type filter is a regularization-type filter which makes full use of the variance/covariance matrices of the sets of spherical harmonic coefficients. It can be shown that applying this filter is equivalent to introducing an additional set of observations: Each set of spherical harmonic coefficients is assumed to be zero. The variance/covariance matrix of this information is chosen according to the signal contained within the sets of spherical harmonic coefficients, expressed in terms of equivalent water layer thickness in the spatial domain, with respect to its variations in time. It will be demonstrated that DMT-1 provides a much better localization and more realistic amplitudes than alternative filtered models. In particular, we will consider a lower maximum degree of the spherical harmonic expansion (e.g. 70), as well as standard filters like an isotropic Gaussian filter. For the sake of a fair comparison, we will use the same GRACE observations as well as the same method for the inversion of the observations to obtain the alternative filtered models. For the inversion method, we will choose the three-point range combination approach. Thus, we will compare four different models: (1) GRACE solution with maximum degree 120, filtered by optimal Wiener-type filter (the DMT-1 model) (2) GRACE solution with maximum degree 120, filtered by standard filter (3) GRACE solution with maximum degree 70, filtered by optimal Wiener-type filter (4) GRACE solution with maximum degree 70, filtered by standard filter Within the comparison, we will focus on the amplitude of long-term mass change signals with respect to spatial resolution. The challenge for the recovery of such signals from GRACE based solutions results from the fact that the solutions must be filtered and that filtering of always smoothes not only noise, but also to some extend signal. Since the observation density is much higher near the poles than at the equator, which is due to the orbits of the GRACE satellites, we expect that the magnitude of estimated mass change signals in polar areas is less underestimated than in equatorial areas. For this reason will investigate trends at locations in equatorial areas as well as trends at locations in polar areas. In particular, we will investigate Lake Victoria, Lake Malawi and Lake Tanganyika, which are all located in Eastern Africa, near to the equator. Furthermore, we will show trends of two locations at the South-East coast of Greenland, Abbot Ice-Shelf and Marie-Byrd-Land in Antarctica For validation, we use water level variations in Lake Victoria (69000 km2), Lake Malawi (29000 km2) and Lake Tanganyika (33000 km2) as ground truth. The water level, which is measured by satellite radar altimetry, decreases at a rate of approximately 47 cm in Lake Victoria, 42 cm in Lake Malawi and 30 cm in Lake Tanganyika over the period from Feb. 2003 to Dec. 2006. Because all three lakes are located in tropical and subtropical clime, the mass change signal will consist of large seasonal variations in addition to the trend component we are interested in. However, also the amplitude of estimated seasonal variations can be used as an indicator of the quality of the models within the comparison. Since the lakes' areas are at the edge of the spatial resolution GRACE data can provide, they are a good example of the advantages of high-resolution mass change models like DMT-1.

  4. SU-F-T-18: The Importance of Immobilization Devices in Brachytherapy Treatments of Vaginal Cuff

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shojaei, M; Dumitru, N; Pella, S

    2016-06-15

    Purpose: High dose rate brachytherapy is a highly localized radiation therapy that has a very high dose gradient. Thus one of the most important parts of the treatment is the immobilization. The smallest movement of the patient or applicator can result in dose variation to the surrounding tissues as well as to the tumor to be treated. We will revise the ML Cylinder treatments and their localization challenges. Methods: A retrospective study of 25 patients with 5 treatments each looking into the applicator’s placement in regard to the organs at risk. Motion possibilities for each applicator intra and inter fractionationmore » with their dosimetric implications were covered and measured in regard with their dose variance. The localization immobilization devices used were assessed for the capability to prevent motion before and during the treatment delivery. Results: We focused on the 100% isodose on central axis and a 15 degree displacement due to possible rotation analyzing the dose variations to the bladder and rectum walls. The average dose variation for bladder was 15% of the accepted tolerance, with a minimum variance of 11.1% and a maximum one of 23.14% on the central axis. For the off axis measurements we found an average variation of 16.84% of the accepted tolerance, with a minimum variance of 11.47% and a maximum one of 27.69%. For the rectum we focused on the rectum wall closest to the 120% isodose line. The average dose variation was 19.4%, minimum 11.3% and a maximum of 34.02% from the accepted tolerance values Conclusion: Improved immobilization devices are recommended. For inter-fractionation, localization devices are recommended in place with consistent planning in regards with the initial fraction. Many of the present immobilization devices produced for external radiotherapy can be used to improve the localization of HDR applicators during transportation of the patient and during treatment.« less

  5. Far-ultraviolet refractive index of optical materials for solar blind channel (SBC) filters for the HST advanced camera for surveys (ACS)

    NASA Astrophysics Data System (ADS)

    Leviton, Douglas B.; Madison, Timothy J.; Petrone, Peter

    1998-10-01

    Refractive index measurements using the minimum deviation method have been carried out for prisms of a variety of far ultraviolet optical materials used in the manufacture of Solar Blind Channel (SBC) filters for the HST Advanced Camera for Surveys (ACS). Some of the materials measured are gaining popularity in a variety of high technology applications including high power excimer lasers and advanced microlithography optics operating in a wavelength region where high quality knowledge of optical material properties is sparse yet critical. Our measurements are of unusually high accuracy and precision for this wavelength region owing to advanced instrumentation in the large vacuum chamber of the Diffraction Grating Evaluation Facility (DGEF) at Goddard Space Flight Center (GSFC) used to implement a minimum deviation method refractometer. Index values for CaF2, BaF2, LiF, and far ultraviolet grades of synthetic sapphire and synthetic fused silica are reported and compared with values from the literature.

  6. Quantization noise in digital speech. M.S. Thesis- Houston Univ.

    NASA Technical Reports Server (NTRS)

    Schmidt, O. L.

    1972-01-01

    The amount of quantization noise generated in a digital-to-analog converter is dependent on the number of bits or quantization levels used to digitize the analog signal in the analog-to-digital converter. The minimum number of quantization levels and the minimum sample rate were derived for a digital voice channel. A sample rate of 6000 samples per second and lowpass filters with a 3 db cutoff of 2400 Hz are required for 100 percent sentence intelligibility. Consonant sounds are the first speech components to be degraded by quantization noise. A compression amplifier can be used to increase the weighting of the consonant sound amplitudes in the analog-to-digital converter. An expansion network must be installed at the output of the digital-to-analog converter to restore the original weighting of the consonant sounds. This technique results in 100 percent sentence intelligibility for a sample rate of 5000 samples per second, eight quantization levels, and lowpass filters with a 3 db cutoff of 2000 Hz.

  7. Prediction of episodic acidification in North-eastern USA: An empirical/mechanistic approach

    USGS Publications Warehouse

    Davies, T.D.; Tranter, M.; Wigington, P.J.; Eshleman, K.N.; Peters, N.E.; Van Sickle, J.; DeWalle, David R.; Murdoch, Peter S.

    1999-01-01

    Observations from the US Environmental Protection Agency's Episodic Response Project (ERP) in the North-eastern United States are used to develop an empirical/mechanistic scheme for prediction of the minimum values of acid neutralizing capacity (ANC) during episodes. An acidification episode is defined as a hydrological event during which ANC decreases. The pre-episode ANC is used to index the antecedent condition, and the stream flow increase reflects how much the relative contributions of sources of waters change during the episode. As much as 92% of the total variation in the minimum ANC in individual catchments can be explained (with levels of explanation >70% for nine of the 13 streams) by a multiple linear regression model that includes pre-episode ANC and change in discharge as independent variable. The predictive scheme is demonstrated to be regionally robust, with the regional variance explained ranging from 77 to 83%. The scheme is not successful for each ERP stream, and reasons are suggested for the individual failures. The potential for applying the predictive scheme to other watersheds is demonstrated by testing the model with data from the Panola Mountain Research Watershed in the South-eastern United States, where the variance explained by the model was 74%. The model can also be utilized to assess 'chemically new' and 'chemically old' water sources during acidification episodes.Observations from the US Environmental Protection Agency's Episodic Response Project (ERP) in the Northeastern United States are used to develop an empirical/mechanistic scheme for prediction of the minimum values of acid neutralizing capacity (ANC) during episodes. An acidification episode is defined as a hydrological event during which ANC decreases. The pre-episode ANC is used to index the antecedent condition, and the stream flow increase reflects how much the relative contributions of sources of waters change during the episode. As much as 92% of the total variation in the minimum ANC in individual catchments can be explained (with levels of explanation >70% for nine of the 13 streams) by a multiple linear regression model that includes pre-episode ANC and change in discharge as independent variables. The predictive scheme is demonstrated to be regionally robust, with the regional variance explained ranging from 77 to 83%. The scheme is not successful for each ERP stream, and reasons are suggested for the individual failures. The potential for applying the predictive scheme to other watersheds is demonstrated by testing the model with data from the Panola Mountain Research Watershed in the South-eastern United States, where the variance explained by the model was 74%. The model can also be utilized to assess `chemically new' and `chemically old' water sources during acidification episodes.

  8. Variable variance Preisach model for multilayers with perpendicular magnetic anisotropy

    NASA Astrophysics Data System (ADS)

    Franco, A. F.; Gonzalez-Fuentes, C.; Morales, R.; Ross, C. A.; Dumas, R.; Åkerman, J.; Garcia, C.

    2016-08-01

    We present a variable variance Preisach model that fully accounts for the different magnetization processes of a multilayer structure with perpendicular magnetic anisotropy by adjusting the evolution of the interaction variance as the magnetization changes. We successfully compare in a quantitative manner the results obtained with this model to experimental hysteresis loops of several [CoFeB/Pd ] n multilayers. The effect of the number of repetitions and the thicknesses of the CoFeB and Pd layers on the magnetization reversal of the multilayer structure is studied, and it is found that many of the observed phenomena can be attributed to an increase of the magnetostatic interactions and subsequent decrease of the size of the magnetic domains. Increasing the CoFeB thickness leads to the disappearance of the perpendicular anisotropy, and such a minimum thickness of the Pd layer is necessary to achieve an out-of-plane magnetization.

  9. Experimental study on an FBG strain sensor

    NASA Astrophysics Data System (ADS)

    Liu, Hong-lin; Zhu, Zheng-wei; Zheng, Yong; Liu, Bang; Xiao, Feng

    2018-01-01

    Landslides and other geological disasters occur frequently and often cause high financial and humanitarian cost. The real-time, early-warning monitoring of landslides has important significance in reducing casualties and property losses. In this paper, by taking the high initial precision and high sensitivity advantage of FBG, an FBG strain sensor is designed combining FBGs with inclinometer. The sensor was regarded as a cantilever beam with one end fixed. According to the anisotropic material properties of the inclinometer, a theoretical formula between the FBG wavelength and the deflection of the sensor was established using the elastic mechanics principle. Accuracy of the formula established had been verified through laboratory calibration testing and model slope monitoring experiments. The displacement of landslide could be calculated by the established theoretical formula using the changing values of FBG central wavelength obtained by the demodulation instrument remotely. Results showed that the maximum error at different heights was 9.09%; the average of the maximum error was 6.35%, and its corresponding variance was 2.12; the minimum error was 4.18%; the average of the minimum error was 5.99%, and its corresponding variance was 0.50. The maximum error of the theoretical and the measured displacement decrease gradually, and the variance of the error also decreases gradually. This indicates that the theoretical results are more and more reliable. It also shows that the sensor and the theoretical formula established in this paper can be used for remote, real-time, high precision and early warning monitoring of the slope.

  10. Aseptic minimum volume vitrification technique for porcine parthenogenetically activated blastocyst.

    PubMed

    Lin, Lin; Yu, Yutao; Zhang, Xiuqing; Yang, Huanming; Bolund, Lars; Callesen, Henrik; Vajta, Gábor

    2011-01-01

    Minimum volume vitrification may provide extremely high cooling and warming rates if the sample and the surrounding medium contacts directly with the respective liquid nitrogen and warming medium. However, this direct contact may result in microbial contamination. In this work, an earlier aseptic technique was applied for minimum volume vitrification. After equilibration, samples were loaded on a plastic film, immersed rapidly into factory derived, filter-sterilized liquid nitrogen, and sealed into sterile, pre-cooled straws. At warming, the straw was cut, the filmstrip was immersed into a 39 degree C warming medium, and the sample was stepwise rehydrated. Cryosurvival rates of porcine blastocysts produced by parthenogenetical activation did not differ from control, vitrified blastocysts with Cryotop. This approach can be used for minimum volume vitrification methods and may be suitable to overcome the biological dangers and legal restrictions that hamper the application of open vitrification techniques.

  11. The development of a Kalman filter clock predictor

    NASA Technical Reports Server (NTRS)

    Davis, John A.; Greenhall, Charles A.; Boudjemaa, Redoane

    2005-01-01

    A Kalman filter based clock predictor is developed, and its performance evaluated using both simulated and real data. The clock predictor is shown to possess a neat to optimal Prediction Error Variance (PEV) when the underlying noise consists of one of the power law noise processes commonly encountered in time and frequency measurements. The predictor's performance is the presence of multiple noise processes is also examined. The relationship between the PEV obtained in the presence of multiple noise processes and those obtained for the individual component noise processes is examined. Comparisons are made with a simple linear clock predictor. The clock predictor is used to predict future values of the time offset between pairs of NPL's active hydrogen masers.

  12. Performance of zeolite ceramic membrane synthesized by wet mixing method as methylene blue dye wastewater filter

    NASA Astrophysics Data System (ADS)

    Masturi; Widodo, R. D.; Edie, S. S.; Amri, U.; Sidiq, A. L.; Alighiri, D.; Wulandari, N. A.; Susilawati; Amanah, S. N.

    2018-03-01

    Problem of pollution in water continues in Indonesia, with its manufacturing sector as biggest contributor to economic growth. One out of many technological solutions is post-treating industrial wastewater by membrane filtering technology. We presented a result of our fabrication of ceramic membrane made from zeolite with simple mixing and he. At 5% of (poring agent):(total weight), its permeability stays around 2.8 mD (10‑14m2) with slight variance around it, attributed to the mixture being in far below percolating threshold. All our membranes achieve remarkable above 90% rejection rate of methylene blue as solute waste in water solvent.

  13. 7 CFR 58.406 - Starter facility.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... precaution shall be taken to prevent contamination of the facility, equipment and the air therein. A filtered air supply with a minimum average efficiency of 90 percent when tested in accordance with the ASHRAE....406 Starter facility. A separate starter room or properly designed starter tanks and satisfactory air...

  14. On methods of estimating cosmological bulk flows

    NASA Astrophysics Data System (ADS)

    Nusser, Adi

    2016-01-01

    We explore similarities and differences between several estimators of the cosmological bulk flow, B, from the observed radial peculiar velocities of galaxies. A distinction is made between two theoretical definitions of B as a dipole moment of the velocity field weighted by a radial window function. One definition involves the three-dimensional (3D) peculiar velocity, while the other is based on its radial component alone. Different methods attempt at inferring B for either of these definitions which coincide only for the case of a velocity field which is constant in space. We focus on the Wiener Filtering (WF) and the Constrained Minimum Variance (CMV) methodologies. Both methodologies require a prior expressed in terms of the radial velocity correlation function. Hoffman et al. compute B in Top-Hat windows from a WF realization of the 3D peculiar velocity field. Feldman et al. infer B directly from the observed velocities for the second definition of B. The WF methodology could easily be adapted to the second definition, in which case it will be equivalent to the CMV with the exception of the imposed constraint. For a prior with vanishing correlations or very noisy data, CMV reproduces the standard Maximum Likelihood estimation for B of the entire sample independent of the radial weighting function. Therefore, this estimator is likely more susceptible to observational biases that could be present in measurements of distant galaxies. Finally, two additional estimators are proposed.

  15. A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV.

    PubMed

    Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

    2016-12-02

    Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy.

  16. A Novel Method for Vertical Acceleration Noise Suppression of a Thrust-Vectored VTOL UAV

    PubMed Central

    Li, Huanyu; Wu, Linfeng; Li, Yingjie; Li, Chunwen; Li, Hangyu

    2016-01-01

    Acceleration is of great importance in motion control for unmanned aerial vehicles (UAVs), especially during the takeoff and landing stages. However, the measured acceleration is inevitably polluted by severe noise. Therefore, a proper noise suppression procedure is required. This paper presents a novel method to reduce the noise in the measured vertical acceleration for a thrust-vectored tail-sitter vertical takeoff and landing (VTOL) UAV. In the new procedure, a Kalman filter is first applied to estimate the UAV mass by using the information in the vertical thrust and measured acceleration. The UAV mass is then used to compute an estimate of UAV vertical acceleration. The estimated acceleration is finally fused with the measured acceleration to obtain the minimum variance estimate of vertical acceleration. By doing this, the new approach incorporates the thrust information into the acceleration estimate. The method is applied to the data measured in a VTOL UAV takeoff experiment. Two other denoising approaches developed by former researchers are also tested for comparison. The results demonstrate that the new method is able to suppress the acceleration noise substantially. It also maintains the real-time performance in the final estimated acceleration, which is not seen in the former denoising approaches. The acceleration treated with the new method can be readily used in the motion control applications for UAVs to achieve improved accuracy. PMID:27918422

  17. Vertical velocity variance in the mixed layer from radar wind profilers

    USGS Publications Warehouse

    Eng, K.; Coulter, R.L.; Brutsaert, W.

    2003-01-01

    Vertical velocity variance data were derived from remotely sensed mixed layer turbulence measurements at the Atmospheric Boundary Layer Experiments (ABLE) facility in Butler County, Kansas. These measurements and associated data were provided by a collection of instruments that included two 915 MHz wind profilers, two radio acoustic sounding systems, and two eddy correlation devices. The data from these devices were available through the Atmospheric Boundary Layer Experiment (ABLE) database operated by Argonne National Laboratory. A signal processing procedure outlined by Angevine et al. was adapted and further built upon to derive vertical velocity variance, w_pm???2, from 915 MHz wind profiler measurements in the mixed layer. The proposed procedure consisted of the application of a height-dependent signal-to-noise ratio (SNR) filter, removal of outliers plus and minus two standard deviations about the mean on the spectral width squared, and removal of the effects of beam broadening and vertical shearing of horizontal winds. The scatter associated with w_pm???2 was mainly affected by the choice of SNR filter cutoff values. Several different sets of cutoff values were considered, and the optimal one was selected which reduced the overall scatter on w_pm???2 and yet retained a sufficient number of data points to average. A similarity relationship of w_pm???2 versus height was established for the mixed layer on the basis of the available data. A strong link between the SNR and growth/decay phases of turbulence was identified. Thus, the mid to late afternoon hours, when strong surface heating occurred, were observed to produce the highest quality signals.

  18. Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Garg, Sanjay

    2010-01-01

    A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

  19. A Probabilistic Collocation Based Iterative Kalman Filter for Landfill Data Assimilation

    NASA Astrophysics Data System (ADS)

    Qiang, Z.; Zeng, L.; Wu, L.

    2016-12-01

    Due to the strong spatial heterogeneity of landfill, uncertainty is ubiquitous in gas transport process in landfill. To accurately characterize the landfill properties, the ensemble Kalman filter (EnKF) has been employed to assimilate the measurements, e.g., the gas pressure. As a Monte Carlo (MC) based method, the EnKF usually requires a large ensemble size, which poses a high computational cost for large scale problems. In this work, we propose a probabilistic collocation based iterative Kalman filter (PCIKF) to estimate permeability in a liquid-gas coupling model. This method employs polynomial chaos expansion (PCE) to represent and propagate the uncertainties of model parameters and states, and an iterative form of Kalman filter to assimilate the current gas pressure data. To further reduce the computation cost, the functional ANOVA (analysis of variance) decomposition is conducted, and only the first order ANOVA components are remained for PCE. Illustrated with numerical case studies, this proposed method shows significant superiority in computation efficiency compared with the traditional MC based iterative EnKF. The developed method has promising potential in reliable prediction and management of landfill gas production.

  20. Extended Kalman filtering for the detection of damage in linear mechanical structures

    NASA Astrophysics Data System (ADS)

    Liu, X.; Escamilla-Ambrosio, P. J.; Lieven, N. A. J.

    2009-09-01

    This paper addresses the problem of assessing the location and extent of damage in a vibrating structure by means of vibration measurements. Frequency domain identification methods (e.g. finite element model updating) have been widely used in this area while time domain methods such as the extended Kalman filter (EKF) method, are more sparsely represented. The difficulty of applying EKF in mechanical system damage identification and localisation lies in: the high computational cost, the dependence of estimation results on the initial estimation error covariance matrix P(0), the initial value of parameters to be estimated, and on the statistics of measurement noise R and process noise Q. To resolve these problems in the EKF, a multiple model adaptive estimator consisting of a bank of EKF in modal domain was designed, each filter in the bank is based on different P(0). The algorithm was iterated by using the weighted global iteration method. A fuzzy logic model was incorporated in each filter to estimate the variance of the measurement noise R. The application of the method is illustrated by simulated and real examples.

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

    NASA Astrophysics Data System (ADS)

    Ortolan, A.; Baggio, L.; Cerdonio, M.; Prodi, G. A.; Vedovato, G.; Vitale, S.

    2002-04-01

    We report on our experience gained in the signal processing of the resonant GW detector AURIGA. Signal amplitude and arrival time are estimated by means of a matched-adaptive Wiener filter. The detector noise, entering in the filter set-up, is modelled as a parametric ARMA process; to account for slow non-stationarity of the noise, the ARMA parameters are estimated on an hourly basis. A requirement of the set-up of an unbiased Wiener filter is the separation of time spans with 'almost Gaussian' noise from non-Gaussian and/or strongly non-stationary time spans. The separation algorithm consists basically of a variance estimate with the Chauvenet convergence method and a threshold on the Curtosis index. The subsequent validation of data is strictly connected with the separation procedure: in fact, by injecting a large number of artificial GW signals into the 'almost Gaussian' part of the AURIGA data stream, we have demonstrated that the effective probability distributions of the signal-to-noise ratio χ2 and the time of arrival are those that are expected.

  2. Post-stratified estimation: with-in strata and total sample size recommendations

    Treesearch

    James A. Westfall; Paul L. Patterson; John W. Coulston

    2011-01-01

    Post-stratification is used to reduce the variance of estimates of the mean. Because the stratification is not fixed in advance, within-strata sample sizes can be quite small. The survey statistics literature provides some guidance on minimum within-strata sample sizes; however, the recommendations and justifications are inconsistent and apply broadly for many...

  3. Integrated optic single-ring filter for narrowband phase demodulation

    NASA Astrophysics Data System (ADS)

    Madsen, C. K.

    2017-05-01

    Integrated optic notch filters are key building blocks for higher-order spectral filter responses and have been demonstrated in many technology platforms from dielectrics (such as Si3N4) to semiconductors (Si photonics). Photonic-assisted RF processing applications for notch filters include identifying and filtering out high-amplitude, narrowband signals that may be interfering with the desired signal, including undesired frequencies detected in radar and free-space optical links. The fundamental tradeoffs for bandwidth and rejection depth as a function of the roundtrip loss and coupling coefficient are investigated along with the resulting spectral phase response for minimum-phase and maximum-phase responses compared to the critical coupling condition and integration within a Mach Zehnder interferometer. Based on a full width at half maximum criterion, it is shown that maximum-phase responses offer the smallest bandwidths for a given roundtrip loss. Then, a new role for passive notch filters in combination with high-speed electro-optic phase modulation is explored around narrowband phase-to-amplitude demodulation using a single ring operating on one sideband. Applications may include microwave processing and instantaneous frequency measurement (IFM) for radar, space and defense applications.

  4. Low level determination of (226)Ra in water using a micro-precipitate track method for large-scale environmental monitoring.

    PubMed

    Taheri, M; Sohrabi, M; Jaleh, B; Hosseini, T; Montazer Rahmati, M M

    2009-12-01

    In the present paper a method has been developed for the determination of (226)Ra in water by the detection, using a solid-state nuclear track detector (SSNTD), of alpha particles from (226)Ra in equilibrium with (222)Rn in micro-precipitates collected on a filter. The micro-precipitates were prepared from environmental water samples by collection of radium with lead as Pb/RaSO(4). Several factors affect the (226)Ra precipitation on the filter and its recovery, in particular the filter pore size. Therefore in this experiment Whatman #42 and Millipore filters with different pore sizes were used. Using a 0.45 microm Millipore filter, the recovery efficiency was increased up to 96%, and the alpha self-absorption and scattering decreased remarkably. For efficient detection of alphas from (226)Ra/(222)Rn in equilibrium, three types of SSNTD were used-polycarbonate (PC) electrochemically etched (ECE), CR-39 and LR-115 chemically etched (CE). By preparing a standard micro-precipitate on a filter with known (226)Ra/(222)Rn characteristics, the calibration response of each detector and its minimum detection limit (MDL) were determined.

  5. Simple Refractometers for Index Measurements by Minimum Deviation Method from Far-ultraviolet to Near Infrared

    NASA Technical Reports Server (NTRS)

    Leviton, Douglas B.; Madison, Timothy J.; Petrone, Peter

    1998-01-01

    The focal shift of an optical filter used in non-collimated light depends directly on substrate thickness and index of refraction. The HST Advanced Camera for Surveys (ACS) requires a set of filters whose focal shifts are tightly matched. Knowing the index of refraction for substrate glasses allows precise substrate thicknesses to be specified. Two refractometers have been developed at the Goddard Space Flight Center (GSFC) to determine the indices of refraction of materials from which ACS filters are made. Modem imaging detectors for the near infrared, visible, and far ultraviolet spectral regions make these simple yet sophisticated refractometers possible. A new technology, high accuracy, angular encoder also developed at GSFC makes high precision index measurement possible in the vacuum ultraviolet.

  6. Robust Speech Enhancement Using Two-Stage Filtered Minima Controlled Recursive Averaging

    NASA Astrophysics Data System (ADS)

    Ghourchian, Negar; Selouani, Sid-Ahmed; O'Shaughnessy, Douglas

    In this paper we propose an algorithm for estimating noise in highly non-stationary noisy environments, which is a challenging problem in speech enhancement. This method is based on minima-controlled recursive averaging (MCRA) whereby an accurate, robust and efficient noise power spectrum estimation is demonstrated. We propose a two-stage technique to prevent the appearance of musical noise after enhancement. This algorithm filters the noisy speech to achieve a robust signal with minimum distortion in the first stage. Subsequently, it estimates the residual noise using MCRA and removes it with spectral subtraction. The proposed Filtered MCRA (FMCRA) performance is evaluated using objective tests on the Aurora database under various noisy environments. These measures indicate the higher output SNR and lower output residual noise and distortion.

  7. Development and test of video systems for airborne surveillance of oil spills

    NASA Technical Reports Server (NTRS)

    Millard, J. P.; Arvesen, J. C.; Lewis, P. L.

    1975-01-01

    Five video systems - potentially useful for airborne surveillance of oil spills - were developed, flight tested, and evaluated. The systems are: (1) conventional black and white TV, (2) conventional TV with false color, (3) differential TV, (4) prototype Lunar Surface TV, and (5) field sequential TV. Wavelength and polarization filtering were utilized in all systems. Greatly enhanced detection of oil spills, relative to that possible with the unaided eye, was achieved. The most practical video system is a conventional TV camera with silicon-diode-array image tube, filtered with a Corning 7-54 filter and a polarizer oriented with its principal axis in the horizontal direction. Best contrast between oil and water was achieved when winds and sea states were low. The minimum detectable oil film thickness was about 0.1 micrometer.

  8. MEDOF - MINIMUM EUCLIDEAN DISTANCE OPTIMAL FILTER

    NASA Technical Reports Server (NTRS)

    Barton, R. S.

    1994-01-01

    The Minimum Euclidean Distance Optimal Filter program, MEDOF, generates filters for use in optical correlators. The algorithm implemented in MEDOF follows theory put forth by Richard D. Juday of NASA/JSC. This program analytically optimizes filters on arbitrary spatial light modulators such as coupled, binary, full complex, and fractional 2pi phase. MEDOF optimizes these modulators on a number of metrics including: correlation peak intensity at the origin for the centered appearance of the reference image in the input plane, signal to noise ratio including the correlation detector noise as well as the colored additive input noise, peak to correlation energy defined as the fraction of the signal energy passed by the filter that shows up in the correlation spot, and the peak to total energy which is a generalization of PCE that adds the passed colored input noise to the input image's passed energy. The user of MEDOF supplies the functions that describe the following quantities: 1) the reference signal, 2) the realizable complex encodings of both the input and filter SLM, 3) the noise model, possibly colored, as it adds at the reference image and at the correlation detection plane, and 4) the metric to analyze, here taken to be one of the analytical ones like SNR (signal to noise ratio) or PCE (peak to correlation energy) rather than peak to secondary ratio. MEDOF calculates filters for arbitrary modulators and a wide range of metrics as described above. MEDOF examines the statistics of the encoded input image's noise (if SNR or PCE is selected) and the filter SLM's (Spatial Light Modulator) available values. These statistics are used as the basis of a range for searching for the magnitude and phase of k, a pragmatically based complex constant for computing the filter transmittance from the electric field. The filter is produced for the mesh points in those ranges and the value of the metric that results from these points is computed. When the search is concluded, the values of amplitude and phase for the k whose metric was largest, as well as consistency checks, are reported. A finer search can be done in the neighborhood of the optimal k if desired. The filter finally selected is written to disk in terms of drive values, not in terms of the filter's complex transmittance. Optionally, the impulse response of the filter may be created to permit users to examine the response for the features the algorithm deems important to the recognition process under the selected metric, limitations of the filter SLM, etc. MEDOF uses the filter SLM to its greatest potential, therefore filter competence is not compromised for simplicity of computation. MEDOF is written in C-language for Sun series computers running SunOS. With slight modifications, it has been implemented on DEC VAX series computers using the DEC-C v3.30 compiler, although the documentation does not currently support this platform. MEDOF can also be compiled using Borland International Inc.'s Turbo C++ v1.0, but IBM PC memory restrictions greatly reduce the maximum size of the reference images from which the filters can be calculated. MEDOF requires a two dimensional Fast Fourier Transform (2DFFT). One 2DFFT routine which has been used successfully with MEDOF is a routine found in "Numerical Recipes in C: The Art of Scientific Programming," which is available from Cambridge University Press, New Rochelle, NY 10801. The standard distribution medium for MEDOF is a .25 inch streaming magnetic tape cartridge (Sun QIC-24) in UNIX tar format. MEDOF was developed in 1992-1993.

  9. Calculation of airborne radioactivity in a Technegas lung ventilation unit.

    PubMed

    López Medina, A; Miñano, J A; Terrón, J A; Bullejos, J A; Guerrero, R; Arroyo, T; Ramírez, A; Llamas, J M

    1999-12-01

    Airborne contamination by 99Tcm has been monitored in the Nuclear Medicine Department in our hospital to assess the risk of internal contamination to occupational workers exposed to Technegas studies. An air sampler fitted with a membrane filter was used. The optimum time for air absorption for obtaining the maximum activity in the filter was calculated. Maximum activity in the membrane filter ensures minimum uncertainty, which is especially important when low-level activities are being measured. The optimum time depends on air absorption velocity, room volume and filter efficiency for isotope collection. It tends to 1/lambda (lambda = disintegration constant for 99Tcm) for large volume and low velocity. Room activity with the air pump switched on was related to filter activity, and its variation with time was studied. Free activity in air for each study was approximately 7 x 10(-4) the activity used, and the effective half-life of the isotope in the room was 13.9 min (decay and diffusion). For a typical study (630 MBq), the effective dose to staff was 0.01 microSv when in the room for 10 min.

  10. 40 CFR 420.21 - Specialized definitions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... emission control system that utilizes filters to remove iron-bearing particles (fines) from blast furnace...-tetrachlorodibenzofuran, the minimum level is 10 pg/L per EPA Method 1613B for water and wastewater samples. (d) The term... term wet air pollution control system means an emission control system that utilizes water to clean...

  11. Stitching-error reduction in gratings by shot-shifted electron-beam lithography

    NASA Technical Reports Server (NTRS)

    Dougherty, D. J.; Muller, R. E.; Maker, P. D.; Forouhar, S.

    2001-01-01

    Calculations of the grating spatial-frequency spectrum and the filtering properties of multiple-pass electron-beam writing demonstrate a tradeoff between stitching-error suppression and minimum pitch separation. High-resolution measurements of optical-diffraction patterns show a 25-dB reduction in stitching-error side modes.

  12. Spectrum-agile hundred-watt-level high-power random fiber laser enabled by watt-level tunable optical filter

    NASA Astrophysics Data System (ADS)

    Ye, Jun; Xu, Jiangming; Song, Jiaxin; Wu, Hanshuo; Zhang, Hanwei; Wu, Jian; Zhou, Pu

    2018-06-01

    Through high-fidelity numerical modeling and careful system-parameter design, we demonstrate the spectral manipulation of a hundred-watt-level high-power random fiber laser (RFL) by employing a watt-level tunable optical filter. Consequently, a >100-W RFL with the spectrum-agile property is achieved. The central wavelength can be continuously tuned with a range of ∼20 nm, and the tuning range of the full width at half maximum linewidth, which is closely related to the central wavelength, covers ∼1.1 to ∼2.7 times of the minimum linewidth.

  13. An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture.

    PubMed

    Craciun, Stefan; Brockmeier, Austin J; George, Alan D; Lam, Herman; Príncipe, José C

    2011-01-01

    Methods for decoding movements from neural spike counts using adaptive filters often rely on minimizing the mean-squared error. However, for non-Gaussian distribution of errors, this approach is not optimal for performance. Therefore, rather than using probabilistic modeling, we propose an alternate non-parametric approach. In order to extract more structure from the input signal (neuronal spike counts) we propose using minimum error entropy (MEE), an information-theoretic approach that minimizes the error entropy as part of an iterative cost function. However, the disadvantage of using MEE as the cost function for adaptive filters is the increase in computational complexity. In this paper we present a comparison between the decoding performance of the analytic Wiener filter and a linear filter trained with MEE, which is then mapped to a parallel architecture in reconfigurable hardware tailored to the computational needs of the MEE filter. We observe considerable speedup from the hardware design. The adaptation of filter weights for the multiple-input, multiple-output linear filters, necessary in motor decoding, is a highly parallelizable algorithm. It can be decomposed into many independent computational blocks with a parallel architecture readily mapped to a field-programmable gate array (FPGA) and scales to large numbers of neurons. By pipelining and parallelizing independent computations in the algorithm, the proposed parallel architecture has sublinear increases in execution time with respect to both window size and filter order.

  14. Robustifying the Kalman Filter.

    DTIC Science & Technology

    1987-11-01

    School Code 55 6c ADDRESN Cq> State and ZiP( odk ,) 7b ADDRE SS(City State and Z/IPCode) Monterey, CA 93943-5000 8a NAME J); ;. ND S"ONSOR’Nu Bt, O FiCE... collected are the estimation error 6n - On for n=25, 50, 75, 100 and the estimate of variance Cn, n=25, 50, 75, 100. The number of independent

  15. Limited variance control in statistical low thrust guidance analysis. [stochastic algorithm for SEP comet Encke flyby mission

    NASA Technical Reports Server (NTRS)

    Jacobson, R. A.

    1975-01-01

    Difficulties arise in guiding a solar electric propulsion spacecraft due to nongravitational accelerations caused by random fluctuations in the magnitude and direction of the thrust vector. These difficulties may be handled by using a low thrust guidance law based on the linear-quadratic-Gaussian problem of stochastic control theory with a minimum terminal miss performance criterion. Explicit constraints are imposed on the variances of the control parameters, and an algorithm based on the Hilbert space extension of a parameter optimization method is presented for calculation of gains in the guidance law. The terminal navigation of a 1980 flyby mission to the comet Encke is used as an example.

  16. Static vs stochastic optimization: A case study of FTSE Bursa Malaysia sectorial indices

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

    2014-06-19

    Traditional portfolio optimization methods in the likes of Markowitz' mean-variance model and semi-variance model utilize static expected return and volatility risk from historical data to generate an optimal portfolio. The optimal portfolio may not truly be optimal in reality due to the fact that maximum and minimum values from the data may largely influence the expected return and volatility risk values. This paper considers distributions of assets' return and volatility risk to determine a more realistic optimized portfolio. For illustration purposes, the sectorial indices data in FTSE Bursa Malaysia is employed. The results show that stochastic optimization provides more stablemore » information ratio.« less

  17. Modeling post-eruptive deformation at Okmok volcano from GPS and InSAR using unscented Kalman filter

    NASA Astrophysics Data System (ADS)

    Xue, X.; Freymueller, J. T.

    2017-12-01

    Okmok, occupies most of northeastern Umnak Island in the Aleutian arc, started inflating soon after the 2008 eruption. Seven GPS sites have been operated after the eruption. Two of them are located within the caldera, three are around the rim of the caldera and two are out of the caldera. The InSAR timeseries have been generated using data from the C-band Envisat and X-band TerraSAR-X satellites (Qu et al., 2015). Both GPS and InSAR indicate more than 0.6 m uplift within the caldera and subtle subsidence outside the caldera. Based on single Mogi source, an unscented Kalman filter was successfully used to model the deformation at Okmok detected by GPS during 2000-2007. We have expanded it to be able to model multiple Mogi sources at different depths and integrate the InSAR observations. Before applying the Kalman filter, We remove a time-independent Mogi source and phase ramp from each InSAR image and obtain its variance-covariance information from the residual. We also determine the relative weight between GPS and InSAR data using variance component estimation. The GPS and InSAR timeseries can then be combined for the Kalman filter. Preliminary results show that two Mogi sources are more likely beneath Okmok volcano. The deep source is located at 8.5 km depth which deflated 0.016 km3 during the first 3 years after the eruption then reached a stable state. The deflating source explains the subsidence outside the caldera which can not be modeled with only one inflating source in any way. The shallow source, migrating 0.5 km from north to south, is located at 2 km depth within the caldera where is close to the source position before the eruption (Freymueller et al., 2010). The magma volume accumulation of the shallow source in the following 7 years from the 2008 eruption is 0.035 km3.

  18. Enhanced Performance Controller Design for Stochastic Systems by Adding Extra State Estimation onto the Existing Closed Loop Control

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhou, Yuyang; Zhang, Qichun; Wang, Hong

    To enhance the performance of the tracking property , this paper presents a novel control algorithm for a class of linear dynamic stochastic systems with unmeasurable states, where the performance enhancement loop is established based on Kalman filter. Without changing the existing closed loop with the PI controller, the compensative controller is designed to minimize the variances of the tracking errors using the estimated states and the propagation of state variances. Moreover, the stability of the closed-loop systems has been analyzed in the mean-square sense. A simulated example is included to show the effectiveness of the presented control algorithm, wheremore » encouraging results have been obtained.« less

  19. Numerical investigation of a helicopter combustion chamber using LES and tabulated chemistry

    NASA Astrophysics Data System (ADS)

    Auzillon, Pierre; Riber, Eléonore; Gicquel, Laurent Y. M.; Gicquel, Olivier; Darabiha, Nasser; Veynante, Denis; Fiorina, Benoît

    2013-01-01

    This article presents Large Eddy Simulations (LES) of a realistic aeronautical combustor device: the chamber CTA1 designed by TURBOMECA. Under nominal operating conditions, experiments show hot spots observed on the combustor walls, in the vicinity of the injectors. These high temperature regions disappear when modifying the fuel stream equivalence ratio. In order to account for detailed chemistry effects within LES, the numerical simulation uses the recently developed turbulent combustion model F-TACLES (Filtered TAbulated Chemistry for LES). The principle of this model is first to generate a lookup table where thermochemical variables are computed from a set of filtered laminar unstrained premixed flamelets. To model the interactions between the flame and the turbulence at the subgrid scale, a flame wrinkling analytical model is introduced and the Filtered Density Function (FDF) of the mixture fraction is modeled by a β function. Filtered thermochemical quantities are stored as a function of three coordinates: the filtered progress variable, the filtered mixture fraction and the mixture fraction subgrid scale variance. The chemical lookup table is then coupled with the LES using a mathematical formalism that ensures an accurate prediction of the flame dynamics. The numerical simulation of the CTA1 chamber with the F-TACLES turbulent combustion model reproduces fairly the temperature fields observed in experiments. In particular the influence of the fuel stream equivalence ratio on the flame position is well captured.

  20. Temperature variation effects on stochastic characteristics for low-cost MEMS-based inertial sensor error

    NASA Astrophysics Data System (ADS)

    El-Diasty, M.; El-Rabbany, A.; Pagiatakis, S.

    2007-11-01

    We examine the effect of varying the temperature points on MEMS inertial sensors' noise models using Allan variance and least-squares spectral analysis (LSSA). Allan variance is a method of representing root-mean-square random drift error as a function of averaging times. LSSA is an alternative to the classical Fourier methods and has been applied successfully by a number of researchers in the study of the noise characteristics of experimental series. Static data sets are collected at different temperature points using two MEMS-based IMUs, namely MotionPakII and Crossbow AHRS300CC. The performance of the two MEMS inertial sensors is predicted from the Allan variance estimation results at different temperature points and the LSSA is used to study the noise characteristics and define the sensors' stochastic model parameters. It is shown that the stochastic characteristics of MEMS-based inertial sensors can be identified using Allan variance estimation and LSSA and the sensors' stochastic model parameters are temperature dependent. Also, the Kaiser window FIR low-pass filter is used to investigate the effect of de-noising stage on the stochastic model. It is shown that the stochastic model is also dependent on the chosen cut-off frequency.

  1. Methods for the preparation and analysis of solids and suspended solids for total mercury

    USGS Publications Warehouse

    Olund, Shane D.; DeWild, John F.; Olson, Mark L.; Tate, Michael T.

    2004-01-01

    The methods documented in this report are utilized by the Wisconsin District Mercury Lab for analysis of total mercury in solids (soils and sediments) and suspended solids (isolated on filters). Separate procedures are required for the different sample types. For solids, samples are prepared by room-temperature acid digestion and oxidation with aqua regia. The samples are brought up to volume with a 5 percent bromine monochloride solution to ensure complete oxidation and heated at 50?C in an oven overnight. Samples are then analyzed with an automated flow injection system incorporating a cold vapor atomic fluorescence spectrometer. A method detection limit of 0.3 ng of mercury per digestion bomb was established using multiple analyses of an environmental sample. Based on the range of masses processed, the minimum sample reporting limit varies from 0.6 ng/g to 6 ng/g. Suspended solids samples are oxidized with a 5 percent bromine monochloride solution and held at 50?C in an oven for 5 days. The samples are then analyzed with an automated flow injection system incorporating a cold vapor atomic fluorescence spectrometer. Using a certified reference material as a surrogate for an environmental sample, a method detection limit of 0.059 ng of mercury per filter was established. The minimum sample reporting limit varies from 0.059 ng/L to 1.18 ng/L, depending on the volume of water filtered.

  2. Design of minimum multiplier fractional order differentiator based on lattice wave digital filter.

    PubMed

    Barsainya, Richa; Rawat, Tarun Kumar; Kumar, Manjeet

    2017-01-01

    In this paper, a novel design of fractional order differentiator (FOD) based on lattice wave digital filter (LWDF) is proposed which requires minimum number of multiplier for its structural realization. Firstly, the FOD design problem is formulated as an optimization problem using the transfer function of lattice wave digital filter. Then, three optimization algorithms, namely, genetic algorithm (GA), particle swarm optimization (PSO) and cuckoo search algorithm (CSA) are applied to determine the optimal LWDF coefficients. The realization of FOD using LWD structure increases the design accuracy, as only N number of coefficients are to be optimized for Nth order FOD. Finally, two design examples of 3rd and 5th order lattice wave digital fractional order differentiator (LWDFOD) are demonstrated to justify the design accuracy. The performance analysis of the proposed design is carried out based on magnitude response, absolute magnitude error (dB), root mean square (RMS) magnitude error, arithmetic complexity, convergence profile and computation time. Simulation results are attained to show the comparison of the proposed LWDFOD with the published works and it is observed that an improvement of 29% is obtained in the proposed design. The proposed LWDFOD approximates the ideal FOD and surpasses the existing ones reasonably well in mid and high frequency range, thereby making the proposed LWDFOD a promising technique for the design of digital FODs. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  3. Kinematics of ram filter feeding and beat-glide swimming in the northern anchovy Engraulis mordax.

    PubMed

    Carey, Nicholas; Goldbogen, Jeremy A

    2017-08-01

    In the dense aquatic environment, the most adept swimmers are streamlined to reduce drag and increase the efficiency of locomotion. However, because they open their mouth to wide gape angles to deploy their filtering apparatus, ram filter feeders apparently switch between diametrically opposite swimming modes: highly efficient, streamlined 'beat-glide' swimming, and ram filter feeding, which has been hypothesized to be a high-cost feeding mode because of presumed increased drag. Ram filter-feeding forage fish are thought to play an important role in the flux of nutrients and energy in upwelling ecosystems; however, the biomechanics and energetics of this feeding mechanism remain poorly understood. We quantified the kinematics of an iconic forage fish, the northern anchovy, Engraulis mordax , during ram filter feeding and non-feeding, mouth-closed beat-glide swimming. Although many kinematic parameters between the two swimming modes were similar, we found that swimming speeds and tailbeat frequencies were significantly lower during ram feeding. Rather than maintain speed with the school, a speed which closely matches theoretical optimum filter-feeding speeds was consistently observed. Beat-glide swimming was characterized by high variability in all kinematic parameters, but variance in kinematic parameters was much lower during ram filter feeding. Under this mode, body kinematics are substantially modified, and E. mordax swims more slowly and with decreased lateral movement along the entire body, but most noticeably in the anterior. Our results suggest that hydrodynamic effects that come with deployment of the filtering anatomy may limit behavioral options during foraging and result in slower swimming speeds during ram filtration. © 2017. Published by The Company of Biologists Ltd.

  4. Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment.

    PubMed

    Cecala, A B; Organiscak, J A; Noll, J D; Zimmer, J A

    2016-08-01

    Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design.

  5. Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment

    PubMed Central

    Cecala, A.B.; Organiscak, J.A.; Noll, J.D.; Zimmer, J.A.

    2016-01-01

    Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design. PMID:27524838

  6. Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration

    PubMed Central

    Zhang, Xi; Miao, Lingjuan; Shao, Haijun

    2016-01-01

    If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper. PMID:27144570

  7. Tracking Architecture Based on Dual-Filter with State Feedback and Its Application in Ultra-Tight GPS/INS Integration.

    PubMed

    Zhang, Xi; Miao, Lingjuan; Shao, Haijun

    2016-05-02

    If a Kalman Filter (KF) is applied to Global Positioning System (GPS) baseband signal preprocessing, the estimates of signal phase and frequency can have low variance, even in highly dynamic situations. This paper presents a novel preprocessing scheme based on a dual-filter structure. Compared with the traditional model utilizing a single KF, this structure avoids carrier tracking being subjected to code tracking errors. Meanwhile, as the loop filters are completely removed, state feedback values are adopted to generate local carrier and code. Although local carrier frequency has a wide fluctuation, the accuracy of Doppler shift estimation is improved. In the ultra-tight GPS/Inertial Navigation System (INS) integration, the carrier frequency derived from the external navigation information is not viewed as the local carrier frequency directly. That facilitates retaining the design principle of state feedback. However, under harsh conditions, the GPS outputs may still bear large errors which can destroy the estimation of INS errors. Thus, an innovative integrated navigation filter is constructed by modeling the non-negligible errors in the estimated Doppler shifts, to ensure INS is properly calibrated. Finally, field test and semi-physical simulation based on telemetered missile trajectory validate the effectiveness of methods proposed in this paper.

  8. A Two-Stage Kalman Filter Approach for Robust and Real-Time Power System State Estimation

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhang, Jinghe; Welch, Greg; Bishop, Gary

    2014-04-01

    As electricity demand continues to grow and renewable energy increases its penetration in the power grid, realtime state estimation becomes essential for system monitoring and control. Recent development in phasor technology makes it possible with high-speed time-synchronized data provided by Phasor Measurement Units (PMU). In this paper we present a two-stage Kalman filter approach to estimate the static state of voltage magnitudes and phase angles, as well as the dynamic state of generator rotor angles and speeds. Kalman filters achieve optimal performance only when the system noise characteristics have known statistical properties (zero-mean, Gaussian, and spectrally white). However in practicemore » the process and measurement noise models are usually difficult to obtain. Thus we have developed the Adaptive Kalman Filter with Inflatable Noise Variances (AKF with InNoVa), an algorithm that can efficiently identify and reduce the impact of incorrect system modeling and/or erroneous measurements. In stage one, we estimate the static state from raw PMU measurements using the AKF with InNoVa; then in stage two, the estimated static state is fed into an extended Kalman filter to estimate the dynamic state. Simulations demonstrate its robustness to sudden changes of system dynamics and erroneous measurements.« less

  9. Assessing the Minimum Number of Synchronization Triggers Necessary for Temporal Variance Compensation in Commercial Electroencephalography (EEG) Systems

    DTIC Science & Technology

    2012-09-01

    by the ARL Translational Neuroscience Branch. It covers the Emotiv EPOC,6 Advanced Brain Monitoring (ABM) B-Alert X10,7 Quasar 8 DSI helmet-based...Systems; ARL-TR-5945; U.S. Army Research Laboratory: Aberdeen Proving Ground, MD, 2012 4 Ibid. 5 Ibid. 6 EPOC is a trademark of Emotiv . 7 B

  10. Foreign Language Training in U.S. Undergraduate IB Programs: Are We Providing Students What They Need to Be Successful?

    ERIC Educational Resources Information Center

    Johnson, Jim

    2017-01-01

    A growing number of U.S. business schools now offer an undergraduate degree in international business (IB), for which training in a foreign language is a requirement. However, there appears to be considerable variance in the minimum requirements for foreign language training across U.S. business schools, including the provision of…

  11. Erythemal irradiances of filtered ultraviolet radiation

    NASA Astrophysics Data System (ADS)

    Parisi, A. V.; Wong, J. C. F.

    1997-07-01

    A spectrum evaluator employing four passive dosimeters has been used to evaluate the time averaged spectrum to allow calculation of the erythemal exposures resulting from the predominantly UVA component of filtered solar ultraviolet radiation. An exposure interval of approximately 20 min to autumn and spring sunshine was required for the spectrum evaluator to allow evaluation of the filtered source spectrum. For a clear spring day an erythemal exposure of 0.85 MED (minimum erythemal dose) to a horizontal plane and 0.38 MED to a vertical plane over a 6 h period was measured within a glass enclosure. For a partially cloudy day six weeks later, these were 0.89 and 0.44 MED for the horizontal and the vertical planes respectively. The ratios of the filtered to the unfiltered erythemal exposures within and outside the enclosure respectively ranged from 0.08 to 0.18 throughout the two days.

  12. Optical filter requirements in an EML-based single-sideband PAM4 intensity-modulation and direct-detection transmission system.

    PubMed

    Chen, Hsing-Yu; Kaneda, Noriaki; Lee, Jeffrey; Chen, Jyehong; Chen, Young-Kai

    2017-03-20

    The feasibility of a single sideband (SSB) PAM4 intensity-modulation and direct-detection (IM/DD) transmission based on a CMOS ADC and DAC is experimentally demonstrated in this work. To cost effectively build a >50 Gb/s system as well as to extend the transmission distance, a low cost EML and a passive optical filter are utilized to generate the SSB signal. However, the EML-induced chirp and dispersion-induced power fading limit the requirements of the SSB filter. To separate the effect of signal-signal beating interference, filters with different roll-off factors are employed to demonstrate the performance tolerance at different transmission distance. Moreover, a high resolution spectrum analysis is proposed to depict the system limitation. Experimental results show that a minimum roll-off factor of 7 dB/10GHz is required to achieve a 51.84Gb/s 40-km transmission with only linear feed-forward equalization.

  13. Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

    PubMed

    Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

    2018-06-04

    Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

  14. GIS-based niche modeling for mapping species' habitats

    USGS Publications Warehouse

    Rotenberry, J.T.; Preston, K.L.; Knick, S.

    2006-01-01

    Ecological a??niche modelinga?? using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

  15. An Experience Oriented-Convergence Improved Gravitational Search Algorithm for Minimum Variance Distortionless Response Beamforming Optimum.

    PubMed

    Darzi, Soodabeh; Tiong, Sieh Kiong; Tariqul Islam, Mohammad; Rezai Soleymanpour, Hassan; Kibria, Salehin

    2016-01-01

    An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents' positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness.

  16. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    NASA Astrophysics Data System (ADS)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  17. The performance of matched-field track-before-detect methods using shallow-water Pacific data.

    PubMed

    Tantum, Stacy L; Nolte, Loren W; Krolik, Jeffrey L; Harmanci, Kerem

    2002-07-01

    Matched-field track-before-detect processing, which extends the concept of matched-field processing to include modeling of the source dynamics, has recently emerged as a promising approach for maintaining the track of a moving source. In this paper, optimal Bayesian and minimum variance beamforming track-before-detect algorithms which incorporate a priori knowledge of the source dynamics in addition to the underlying uncertainties in the ocean environment are presented. A Markov model is utilized for the source motion as a means of capturing the stochastic nature of the source dynamics without assuming uniform motion. In addition, the relationship between optimal Bayesian track-before-detect processing and minimum variance track-before-detect beamforming is examined, revealing how an optimal tracking philosophy may be used to guide the modification of existing beamforming techniques to incorporate track-before-detect capabilities. Further, the benefits of implementing an optimal approach over conventional methods are illustrated through application of these methods to shallow-water Pacific data collected as part of the SWellEX-1 experiment. The results show that incorporating Markovian dynamics for the source motion provides marked improvement in the ability to maintain target track without the use of a uniform velocity hypothesis.

  18. A semiempirical linear model of indirect, flat-panel x-ray detectors.

    PubMed

    Huang, Shih-Ying; Yang, Kai; Abbey, Craig K; Boone, John M

    2012-04-01

    It is important to understand signal and noise transfer in the indirect, flat-panel x-ray detector when developing and optimizing imaging systems. For optimization where simulating images is necessary, this study introduces a semiempirical model to simulate projection images with user-defined x-ray fluence interaction. The signal and noise transfer in the indirect, flat-panel x-ray detectors is characterized by statistics consistent with energy-integration of x-ray photons. For an incident x-ray spectrum, x-ray photons are attenuated and absorbed in the x-ray scintillator to produce light photons, which are coupled to photodiodes for signal readout. The signal mean and variance are linearly related to the energy-integrated x-ray spectrum by empirically determined factors. With the known first- and second-order statistics, images can be simulated by incorporating multipixel signal statistics and the modulation transfer function of the imaging system. To estimate the semiempirical input to this model, 500 projection images (using an indirect, flat-panel x-ray detector in the breast CT system) were acquired with 50-100 kilovolt (kV) x-ray spectra filtered with 0.1-mm tin (Sn), 0.2-mm copper (Cu), 1.5-mm aluminum (Al), or 0.05-mm silver (Ag). The signal mean and variance of each detector element and the noise power spectra (NPS) were calculated and incorporated into this model for accuracy. Additionally, the modulation transfer function of the detector system was physically measured and incorporated in the image simulation steps. For validation purposes, simulated and measured projection images of air scans were compared using 40 kV∕0.1-mm Sn, 65 kV∕0.2-mm Cu, 85 kV∕1.5-mm Al, and 95 kV∕0.05-mm Ag. The linear relationship between the measured signal statistics and the energy-integrated x-ray spectrum was confirmed and incorporated into the model. The signal mean and variance factors were linearly related to kV for each filter material (r(2) of signal mean to kV: 0.91, 0.93, 0.86, and 0.99 for 0.1-mm Sn, 0.2-mm Cu, 1.5-mm Al, and 0.05-mm Ag, respectively; r(2) of signal variance to kV: 0.99 for all four filters). The comparison of the signal and noise (mean, variance, and NPS) between the simulated and measured air scan images suggested that this model was reasonable in predicting accurate signal statistics of air scan images using absolute percent error. Overall, the model was found to be accurate in estimating signal statistics and spatial correlation between the detector elements of the images acquired with indirect, flat-panel x-ray detectors. The semiempirical linear model of the indirect, flat-panel x-ray detectors was described and validated with images of air scans. The model was found to be a useful tool in understanding the signal and noise transfer within indirect, flat-panel x-ray detector systems.

  19. Precise orbit determination using the batch filter based on particle filtering with genetic resampling approach

    NASA Astrophysics Data System (ADS)

    Kim, Young-Rok; Park, Eunseo; Choi, Eun-Jung; Park, Sang-Young; Park, Chandeok; Lim, Hyung-Chul

    2014-09-01

    In this study, genetic resampling (GRS) approach is utilized for precise orbit determination (POD) using the batch filter based on particle filtering (PF). Two genetic operations, which are arithmetic crossover and residual mutation, are used for GRS of the batch filter based on PF (PF batch filter). For POD, Laser-ranging Precise Orbit Determination System (LPODS) and satellite laser ranging (SLR) observations of the CHAMP satellite are used. Monte Carlo trials for POD are performed by one hundred times. The characteristics of the POD results by PF batch filter with GRS are compared with those of a PF batch filter with minimum residual resampling (MRRS). The post-fit residual, 3D error by external orbit comparison, and POD repeatability are analyzed for orbit quality assessments. The POD results are externally checked by NASA JPL’s orbits using totally different software, measurements, and techniques. For post-fit residuals and 3D errors, both MRRS and GRS give accurate estimation results whose mean root mean square (RMS) values are at a level of 5 cm and 10-13 cm, respectively. The mean radial orbit errors of both methods are at a level of 5 cm. For POD repeatability represented as the standard deviations of post-fit residuals and 3D errors by repetitive PODs, however, GRS yields 25% and 13% more robust estimation results than MRRS for post-fit residual and 3D error, respectively. This study shows that PF batch filter with GRS approach using genetic operations is superior to PF batch filter with MRRS in terms of robustness in POD with SLR observations.

  20. Volcano plots in analyzing differential expressions with mRNA microarrays.

    PubMed

    Li, Wentian

    2012-12-01

    A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.

  1. Fusion of KLMS and blob based pre-screener for buried landmine detection using ground penetrating radar

    NASA Astrophysics Data System (ADS)

    Baydar, Bora; Akar, Gözde Bozdaǧi.; Yüksel, Seniha E.; Öztürk, Serhat

    2016-05-01

    In this paper, a decision level fusion using multiple pre-screener algorithms is proposed for the detection of buried landmines from Ground Penetrating Radar (GPR) data. The Kernel Least Mean Square (KLMS) and the Blob Filter pre-screeners are fused together to work in real time with less false alarms and higher true detection rates. The effect of the kernel variance is investigated for the KLMS algorithm. Also, the results of the KLMS and KLMS+Blob filter algorithms are compared to the LMS method in terms of processing time and false alarm rates. Proposed algorithm is tested on both simulated data and real data collected at the field of IPA Defence at METU, Ankara, Turkey.

  2. Adaptive estimation of the log fluctuating conductivity from tracer data at the Cape Cod Site

    USGS Publications Warehouse

    Deng, F.W.; Cushman, J.H.; Delleur, J.W.

    1993-01-01

    An adaptive estimation scheme is used to obtain the integral scale and variance of the log-fluctuating conductivity at the Cape Cod site based on the fast Fourier transform/stochastic model of Deng et al. (1993) and a Kalmanlike filter. The filter incorporates prior estimates of the unknown parameters with tracer moment data to adaptively obtain improved estimates as the tracer evolves. The results show that significant improvement in the prior estimates of the conductivity can lead to substantial improvement in the ability to predict plume movement. The structure of the covariance function of the log-fluctuating conductivity can be identified from the robustness of the estimation. Both the longitudinal and transverse spatial moment data are important to the estimation.

  3. Number-phase minimum-uncertainty state with reduced number uncertainty in a Kerr nonlinear interferometer

    NASA Astrophysics Data System (ADS)

    Kitagawa, M.; Yamamoto, Y.

    1987-11-01

    An alternative scheme for generating amplitude-squeezed states of photons based on unitary evolution which can properly be described by quantum mechanics is presented. This scheme is a nonlinear Mach-Zehnder interferometer containing an optical Kerr medium. The quasi-probability density (QPD) and photon-number distribution of the output field are calculated, and it is demonstrated that the reduced photon-number uncertainty and enhanced phase uncertainty maintain the minimum-uncertainty product. A self-phase-modulation of the single-mode quantized field in the Kerr medium is described based on localized operators. The spatial evolution of the state is demonstrated by QPD in the Schroedinger picture. It is shown that photon-number variance can be reduced to a level far below the limit for an ordinary squeezed state, and that the state prepared using this scheme remains a number-phase minimum-uncertainty state until the maximum reduction of number fluctuations is surpassed.

  4. An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers.

    PubMed

    Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

    2017-11-18

    Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration-which are the basis of tracking error estimation-are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (-0.25 cycle, 0.25 cycle) to (-0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz.

  5. An Enhanced Non-Coherent Pre-Filter Design for Tracking Error Estimation in GNSS Receivers

    PubMed Central

    Luo, Zhibin; Ding, Jicheng; Zhao, Lin; Wu, Mouyan

    2017-01-01

    Tracking error estimation is of great importance in global navigation satellite system (GNSS) receivers. Any inaccurate estimation for tracking error will decrease the signal tracking ability of signal tracking loops and the accuracies of position fixing, velocity determination, and timing. Tracking error estimation can be done by traditional discriminator, or Kalman filter-based pre-filter. The pre-filter can be divided into two categories: coherent and non-coherent. This paper focuses on the performance improvements of non-coherent pre-filter. Firstly, the signal characteristics of coherent and non-coherent integration—which are the basis of tracking error estimation—are analyzed in detail. After that, the probability distribution of estimation noise of four-quadrant arctangent (ATAN2) discriminator is derived according to the mathematical model of coherent integration. Secondly, the statistical property of observation noise of non-coherent pre-filter is studied through Monte Carlo simulation to set the observation noise variance matrix correctly. Thirdly, a simple fault detection and exclusion (FDE) structure is introduced to the non-coherent pre-filter design, and thus its effective working range for carrier phase error estimation extends from (−0.25 cycle, 0.25 cycle) to (−0.5 cycle, 0.5 cycle). Finally, the estimation accuracies of discriminator, coherent pre-filter, and the enhanced non-coherent pre-filter are evaluated comprehensively through the carefully designed experiment scenario. The pre-filter outperforms traditional discriminator in estimation accuracy. In a highly dynamic scenario, the enhanced non-coherent pre-filter provides accuracy improvements of 41.6%, 46.4%, and 50.36% for carrier phase error, carrier frequency error, and code phase error estimation, respectively, when compared with coherent pre-filter. The enhanced non-coherent pre-filter outperforms the coherent pre-filter in code phase error estimation when carrier-to-noise density ratio is less than 28.8 dB-Hz, in carrier frequency error estimation when carrier-to-noise density ratio is less than 20 dB-Hz, and in carrier phase error estimation when carrier-to-noise density belongs to (15, 23) dB-Hz ∪ (26, 50) dB-Hz. PMID:29156581

  6. 40 CFR 86.137-94 - Dynamometer test run, gaseous and particulate emissions.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ..., if applicable), the temperature recorder, the vehicle cooling fan, and the heated THC analysis... diesel-cycle THC analyzer continuous sample line and filter, methanol-fueled vehicle THC, methanol and... measuring devices to zero. (i) For gaseous bag samples (except THC samples), the minimum flow rate is 0.17...

  7. 40 CFR 86.137-94 - Dynamometer test run, gaseous and particulate emissions.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ..., if applicable), the temperature recorder, the vehicle cooling fan, and the heated THC analysis... diesel-cycle THC analyzer continuous sample line and filter, methanol-fueled vehicle THC, methanol and... measuring devices to zero. (i) For gaseous bag samples (except THC samples), the minimum flow rate is 0.17...

  8. An Explicit Linear Filtering Solution for the Optimization of Guidance Systems with Statistical Inputs

    NASA Technical Reports Server (NTRS)

    Stewart, Elwood C.

    1961-01-01

    The determination of optimum filtering characteristics for guidance system design is generally a tedious process which cannot usually be carried out in general terms. In this report a simple explicit solution is given which is applicable to many different types of problems. It is shown to be applicable to problems which involve optimization of constant-coefficient guidance systems and time-varying homing type systems for several stationary and nonstationary inputs. The solution is also applicable to off-design performance, that is, the evaluation of system performance for inputs for which the system was not specifically optimized. The solution is given in generalized form in terms of the minimum theoretical error, the optimum transfer functions, and the optimum transient response. The effects of input signal, contaminating noise, and limitations on the response are included. From the results given, it is possible in an interception problem, for example, to rapidly assess the effects on minimum theoretical error of such factors as target noise and missile acceleration. It is also possible to answer important questions regarding the effect of type of target maneuver on optimum performance.

  9. The CFHT MegaCam control system: new solutions based on PLCs, WorldFIP fieldbus and Java softwares

    NASA Astrophysics Data System (ADS)

    Rousse, Jean Y.; Boulade, Olivier; Charlot, Xavier; Abbon, P.; Aune, Stephan; Borgeaud, Pierre; Carton, Pierre-Henri; Carty, M.; Da Costa, J.; Deschamps, H.; Desforge, D.; Eppele, Dominique; Gallais, Pascal; Gosset, L.; Granelli, Remy; Gros, Michel; de Kat, Jean; Loiseau, Denis; Ritou, J. L.; Starzynski, Pierre; Vignal, Nicolas; Vigroux, Laurent G.

    2003-03-01

    MegaCam is a wide-field imaging camera built for the prime focus of the 3.6m Canada-France-Hawaii Telescope. This large detector has required new approaches from the hardware up to the instrument control system software. Safe control of the three sub-systems of the instrument (cryogenics, filters and shutter), measurement of the exposure time with an accuracy of 0.1%, identification of the filters and management of the internal calibration source are the major challenges that are taken up by the control system. Another challenge is to insure all these functionalities with the minimum space available on the telescope structure for the electrical hardware and a minimum number of cables to keep the highest reliability. All these requirements have been met with a control system which different elements are linked by a WorldFip fieldbus on optical fiber. The diagnosis and remote user support will be insured with an Engineering Control System station based on software developed on Internet JAVA technologies (applets, servlets) and connected on the fieldbus.

  10. Adaptive data rate SSMA system for personal and mobile satellite communications

    NASA Technical Reports Server (NTRS)

    Ikegami, Tetsushi; Takahashi, Takashi; Arakaki, Yoshiya; Wakana, Hiromitsu

    1995-01-01

    An adaptive data rate SSMA (spread spectrum multiple access) system is proposed for mobile and personal multimedia satellite communications without the aid of system control earth stations. This system has a constant occupied bandwidth and has variable data rates and processing gains to mitigate communication link impairments such as fading, rain attenuation and interference as well as to handle variable data rate on demand. Proof of concept hardware for 6MHz bandwidth transponder is developed, that uses offset-QPSK (quadrature phase shift keying) and MSK (minimum shift keying) for direct sequence spread spectrum modulation and handle data rates of 4k to 64kbps. The RS422 data interface, low rate voice and H.261 video codecs are installed. The receiver is designed with coherent matched filter technique to achieve fast code acquisition, AFC (automatic frequency control) and coherent detection with minimum hardware losses in a single matched filter circuit. This receiver structure facilitates variable data rate on demand during a call. This paper shows the outline of the proposed system and the performance of the prototype equipment.

  11. Alpha particle spectroscopy in radon/thoron progeny measurements.

    PubMed

    Thiessen, N P

    1994-12-01

    A comparison is made between the relative variances and counting time requirements for obtaining radon and thoron progeny air concentrations from total alpha count data and from spectroscopically resolved alpha count data collected from air sampling filters. Spectral resolution is shown to have significant advantages, especially in mixed radon/thoron atmospheres. Systematic biases resulting from imperfect energy peak resolution are shown to be subject to accurate mathematical compensation.

  12. GPR image analysis to locate water leaks from buried pipes by applying variance filters

    NASA Astrophysics Data System (ADS)

    Ocaña-Levario, Silvia J.; Carreño-Alvarado, Elizabeth P.; Ayala-Cabrera, David; Izquierdo, Joaquín

    2018-05-01

    Nowadays, there is growing interest in controlling and reducing the amount of water lost through leakage in water supply systems (WSSs). Leakage is, in fact, one of the biggest problems faced by the managers of these utilities. This work addresses the problem of leakage in WSSs by using GPR (Ground Penetrating Radar) as a non-destructive method. The main objective is to identify and extract features from GPR images such as leaks and components in a controlled laboratory condition by a methodology based on second order statistical parameters and, using the obtained features, to create 3D models that allows quick visualization of components and leaks in WSSs from GPR image analysis and subsequent interpretation. This methodology has been used before in other fields and provided promising results. The results obtained with the proposed methodology are presented, analyzed, interpreted and compared with the results obtained by using a well-established multi-agent based methodology. These results show that the variance filter is capable of highlighting the characteristics of components and anomalies, in an intuitive manner, which can be identified by non-highly qualified personnel, using the 3D models we develop. This research intends to pave the way towards future intelligent detection systems that enable the automatic detection of leaks in WSSs.

  13. Improvement of Microtremor Data Filtering and Processing Methods Used in Determining the Fundamental Frequency of Urban Areas

    NASA Astrophysics Data System (ADS)

    Mousavi Anzehaee, Mohammad; Adib, Ahmad; Heydarzadeh, Kobra

    2015-10-01

    The manner of microtremor data collection and filtering operation and also the method used for processing have a considerable effect on the accuracy of estimation of dynamic soil parameters. In this paper, running variance method was used to improve the automatic detection of data sections infected by local perturbations. In this method, the microtremor data running variance is computed using a sliding window. Then the obtained signal is used to remove the ranges of data affected by perturbations from the original data. Additionally, to determinate the fundamental frequency of a site, this study has proposed a statistical characteristics-based method. Actually, statistical characteristics, such as the probability density graph and the average and the standard deviation of all the frequencies corresponding to the maximum peaks in the H/ V spectra of all data windows, are used to differentiate the real peaks from the false peaks resulting from perturbations. The methods have been applied to the data recorded for the City of Meybod in central Iran. Experimental results show that the applied methods are able to successfully reduce the effects of extensive local perturbations on microtremor data and eventually to estimate the fundamental frequency more accurately compared to other common methods.

  14. Cosmic Bulk Flow and the Local Motion from Cosmicflows-2

    NASA Astrophysics Data System (ADS)

    Courtois, Helene M.; Hoffman, Yehuda; Tully, R. Brent

    2015-08-01

    Full sky surveys of peculiar velocity are arguably the best way to map the large scale structure out to distances of a few times 100 Mpc/h.Using the largest and most accurate ever catalog of galaxy peculiar velocities Cosmicflows-2, the large scale structure has been reconstructed by means of the Wiener filter and constrained realizations assuming as a Bayesian prior model the LCDM standard model of cosmology. The present paper focuses on studying the bulk flow of the local flow field, defined as the mean velocity of top-hat spheres with radii ranging out to R=500 Mpc/h. Our main results is that the estimated bulk flow is consistent with the LCDM model with the WMAP inferred cosmological parameters. At R=50 (150)Mpc/h the estimated bulk velocity is 250 +/- 21 (239 +/- 38) km/s. The corresponding cosmic variance at these radii is 126 (60) km/s, which implies that these estimated bulk flows are dominated by the data and not by the assumed prior model. The estimated bulk velocity is dominated by the data out to R ˜200 Mpc/h, where the cosmic variance on the individual Supergalactic Cartesian components (of the r.m.s. values) exceeds the variance of the constrined realizations by at least a factor of 2. The SGX and SGY components of the CMB dipole velocity are recovered by the Wiener Filter velocity field down to a very few km/s. The SGZ component of the estimated velocity, the one that is most affected by the Zone of Avoidance, is off by 126km/s (an almost 2 sigma discrepancy).The bulk velocity analysis reported here is virtually unaffected by the Malmquist bias and very similar results are obtained for the data with and without the bias correction.

  15. Relation between Pressure Balance Structures and Polar Plumes from Ulysses High Latitude Observations

    NASA Technical Reports Server (NTRS)

    Yamauchi, Yohei; Suess, Steven T.; Sakurai, Takashi

    2002-01-01

    Ulysses observations have shown that pressure balance structures (PBSs) are a common feature in high-latitude, fast solar wind near solar minimum. Previous studies of Ulysses/SWOOPS plasma data suggest these PBSs may be remnants of coronal polar plumes. Here we find support for this suggestion in an analysis of PBS magnetic structure. We used Ulysses magnetometer data and applied a minimum variance analysis to magnetic discontinuities in PBSs. We found that PBSs preferentially contain tangential discontinuities, as opposed to rotational discontinuities and to non-PBS regions in the solar wind. This suggests that PBSs contain structures like current sheets or plasmoids that may be associated with network activity at the base of plumes.

  16. Relation Between Pressure Balance Structures and Polar Plumes from Ulysses High Latitude Observations

    NASA Technical Reports Server (NTRS)

    Yamauchi, Y.; Suess, Steven T.; Sakurai, T.; Whitaker, Ann F. (Technical Monitor)

    2001-01-01

    Ulysses observations have shown that pressure balance structures (PBSs) are a common feature in high-latitude, fast solar wind near solar minimum. Previous studies of Ulysses/SWOOPS plasma data suggest these PBSs may be remnants of coronal polar plumes. Here we find support for this suggestion in an analysis of PBS magnetic structure. We used Ulysses magnetometer data and applied a minimum variance analysis to discontinuities. We found that PBSs preferentially contain tangential discontinuities, as opposed to rotational discontinuities and to non-PBS regions in the solar wind. This suggests that PBSs contain structures like current sheets or plasmoids that may be associated with network activity at the base of plumes.

  17. Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

    PubMed Central

    Wang, Guohua; Liu, Qiong

    2015-01-01

    Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only. PMID:26703611

  18. Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

    PubMed

    Wang, Guohua; Liu, Qiong

    2015-12-21

    Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

  19. Effects of MERV 16 filters and routine work practices on enclosed cabs for reducing respirable dust and DPM exposures in an underground limestone mine

    PubMed Central

    Noll, J.D.; Cecala, A.B.; J.A.Organiscak; Rider, J.P.

    2015-01-01

    An effective technique to minimize miners’ respirable dust and diesel exposure on mobile mining equipment is to place mine operators in enclosed cabs with designed filtration and pressurization systems. Many factors affect the performance of these enclosed cab systems, and one of the most significant factors is the effectiveness of the filtration system. High-efficiency particulate air (HEPA)-type filters are typically used because they are highly efficient at capturing all types and sizes of particles, including those in the submicron range such as diesel particulate matter (DPM). However, in laboratory tests, minimum efficiency reporting value (MERV) 16 filters have proven to be highly efficient for capturing DPM and respirable dust. Also, MERV 16 filters can be less restrictive to cab airflow and less expensive than HEPA filters. To verify their effectiveness in the field, MERV 16 filters were used in the enclosed cab filtration system on a face drill and roof bolting mining machine and tested at an underground limestone mine. Test results showed that DPM and respirable dust concentrations were reduced by more than 90% when the cabs were properly sealed. However, when the cab door was opened periodically throughout the shift, the reduction efficiency of the MERV 16 filters was reduced to 80% on average. PMID:26236044

  20. Design and manufacture of super-multilayer optical filters based on PARMS technology

    NASA Astrophysics Data System (ADS)

    Lü, Shaobo; Wang, Ruisheng; Ma, Jing; Jiang, Chao; Mu, Jiali; Zhao, Shuaifeng; Yin, Xiaojun

    2018-04-01

    Three multilayer interference optical filters, including a UV band-pass, a VIS dual-band-pass and a notch filter, were designed by using Ta2O5, Nb2O5, Al2O3 and SiO2 as high- and low-index materials. During the design of the coating process, a hybrid optical monitoring and RATE-controlled layer thickness control scheme was adopted. The coating process was simulated by using the optical monitoring system (OMS) Simulator, and the simulation result indicated that the layer thickness can be controlled within an error of less than ±0.1%. The three filters were manufactured on a plasma-assisted reactive magnetic sputtering (PARMS) coating machine. The measurements indicate that for the UV band-pass filter, the peak transmittance is higher than 95% and the blocking density is better than OD6 in the 300-1100 nm region, whereas for the dual-band-pass filter, the center wavelength positioning accuracy of the two passbands are less than ±2 nm, the peak transmittance is higher than 95% and blocking density is better than OD6 in the 300-950 nm region. Finally, for the notch filter, the minimum transmittance rates are >90% and >94% in the visible and near infrared, respectively, and the blocking density is better than OD5.5 at 808 nm.

  1. Image defog algorithm based on open close filter and gradient domain recursive bilateral filter

    NASA Astrophysics Data System (ADS)

    Liu, Daqian; Liu, Wanjun; Zhao, Qingguo; Fei, Bowen

    2017-11-01

    To solve the problems of fuzzy details, color distortion, low brightness of the image obtained by the dark channel prior defog algorithm, an image defog algorithm based on open close filter and gradient domain recursive bilateral filter, referred to as OCRBF, was put forward. The algorithm named OCRBF firstly makes use of weighted quad tree to obtain more accurate the global atmospheric value, then exploits multiple-structure element morphological open and close filter towards the minimum channel map to obtain a rough scattering map by dark channel prior, makes use of variogram to correct the transmittance map,and uses gradient domain recursive bilateral filter for the smooth operation, finally gets recovery images by image degradation model, and makes contrast adjustment to get bright, clear and no fog image. A large number of experimental results show that the proposed defog method in this paper can be good to remove the fog , recover color and definition of the fog image containing close range image, image perspective, the image including the bright areas very well, compared with other image defog algorithms,obtain more clear and natural fog free images with details of higher visibility, what's more, the relationship between the time complexity of SIDA algorithm and the number of image pixels is a linear correlation.

  2. Particle Filtering for Obstacle Tracking in UAS Sense and Avoid Applications

    PubMed Central

    Moccia, Antonio

    2014-01-01

    Obstacle detection and tracking is a key function for UAS sense and avoid applications. In fact, obstacles in the flight path must be detected and tracked in an accurate and timely manner in order to execute a collision avoidance maneuver in case of collision threat. The most important parameter for the assessment of a collision risk is the Distance at Closest Point of Approach, that is, the predicted minimum distance between own aircraft and intruder for assigned current position and speed. Since assessed methodologies can cause some loss of accuracy due to nonlinearities, advanced filtering methodologies, such as particle filters, can provide more accurate estimates of the target state in case of nonlinear problems, thus improving system performance in terms of collision risk estimation. The paper focuses on algorithm development and performance evaluation for an obstacle tracking system based on a particle filter. The particle filter algorithm was tested in off-line simulations based on data gathered during flight tests. In particular, radar-based tracking was considered in order to evaluate the impact of particle filtering in a single sensor framework. The analysis shows some accuracy improvements in the estimation of Distance at Closest Point of Approach, thus reducing the delay in collision detection. PMID:25105154

  3. Attempts to Simulate Anisotropies of Solar Wind Fluctuations Using MHD with a Turning Magnetic Field

    NASA Technical Reports Server (NTRS)

    Ghosh, Sanjoy; Roberts, D. Aaron

    2010-01-01

    We examine a "two-component" model of the solar wind to see if any of the observed anisotropies of the fields can be explained in light of the need for various quantities, such as the magnetic minimum variance direction, to turn along with the Parker spiral. Previous results used a 3-D MHD spectral code to show that neither Q2D nor slab-wave components will turn their wave vectors in a turning Parker-like field, and that nonlinear interactions between the components are required to reproduce observations. In these new simulations we use higher resolution in both decaying and driven cases, and with and without a turning background field, to see what, if any, conditions lead to variance anisotropies similar to observations. We focus especially on the middle spectral range, and not the energy-containing scales, of the simulation for comparison with the solar wind. Preliminary results have shown that it is very difficult to produce the required variances with a turbulent cascade.

  4. DOE Office of Scientific and Technical Information (OSTI.GOV)

    Aziz, Mohd Khairul Bazli Mohd, E-mail: mkbazli@yahoo.com; Yusof, Fadhilah, E-mail: fadhilahy@utm.my; Daud, Zalina Mohd, E-mail: zalina@ic.utm.my

    Recently, many rainfall network design techniques have been developed, discussed and compared by many researchers. Present day hydrological studies require higher levels of accuracy from collected data. In numerous basins, the rain gauge stations are located without clear scientific understanding. In this study, an attempt is made to redesign rain gauge network for Johor, Malaysia in order to meet the required level of accuracy preset by rainfall data users. The existing network of 84 rain gauges in Johor is optimized and redesigned into a new locations by using rainfall, humidity, solar radiation, temperature and wind speed data collected during themore » monsoon season (November - February) of 1975 until 2008. This study used the combination of geostatistics method (variance-reduction method) and simulated annealing as the algorithm of optimization during the redesigned proses. The result shows that the new rain gauge location provides minimum value of estimated variance. This shows that the combination of geostatistics method (variance-reduction method) and simulated annealing is successful in the development of the new optimum rain gauge system.« less

  5. Evaluation of a Cubature Kalman Filtering-Based Phase Unwrapping Method for Differential Interferograms with High Noise in Coal Mining Areas

    PubMed Central

    Liu, Wanli; Bian, Zhengfu; Liu, Zhenguo; Zhang, Qiuzhao

    2015-01-01

    Differential interferometric synthetic aperture radar has been shown to be effective for monitoring subsidence in coal mining areas. Phase unwrapping can have a dramatic influence on the monitoring result. In this paper, a filtering-based phase unwrapping algorithm in combination with path-following is introduced to unwrap differential interferograms with high noise in mining areas. It can perform simultaneous noise filtering and phase unwrapping so that the pre-filtering steps can be omitted, thus usually retaining more details and improving the detectable deformation. For the method, the nonlinear measurement model of phase unwrapping is processed using a simplified Cubature Kalman filtering, which is an effective and efficient tool used in many nonlinear fields. Three case studies are designed to evaluate the performance of the method. In Case 1, two tests are designed to evaluate the performance of the method under different factors including the number of multi-looks and path-guiding indexes. The result demonstrates that the unwrapped results are sensitive to the number of multi-looks and that the Fisher Distance is the most suitable path-guiding index for our study. Two case studies are then designed to evaluate the feasibility of the proposed phase unwrapping method based on Cubature Kalman filtering. The results indicate that, compared with the popular Minimum Cost Flow method, the Cubature Kalman filtering-based phase unwrapping can achieve promising results without pre-filtering and is an appropriate method for coal mining areas with high noise. PMID:26153776

  6. Spectral shaping of an all-fiber torsional acousto-optic tunable filter.

    PubMed

    Ko, Jeakwon; Lee, Kwang Jo; Kim, Byoung Yoon

    2014-12-20

    Spectral shaping of an all-fiber torsional acousto-optic (AO) tunable filter is studied. The technique is based on the axial modulation of AO coupling strength along a highly birefringent optical fiber, which is achieved by tailoring the outer diameter of the fiber along its propagation axis. Two kinds of filter spectral shaping schemes-Gaussian apodization and matched filtering with triple resonance peaks-are proposed and numerically investigated under realistic experimental conditions: at the 50-cm-long AO interaction length of the fiber and at half of the original fiber diameter as the minimum thickness of the tailored fiber section. The results show that the highest peak of sidelobe spectra in filter transmission is suppressed from 11.64% to 0.54% via Gaussian modulation of the AO coupling coefficient (κ). Matched filtering with triple resonance peaks operating with a single radio frequency signal is also achieved by cosine modulation of κ, of which the modulation period determines the spectral distance between two satellite peaks located in both wings of the main resonance peak. The splitting of two satellite peaks in the filter spectra reaches 48.2 nm while the modulation period varies from 7.7 to 50 cm. The overall peak power of two satellite resonances is calculated to be 22% of the main resonance power. The results confirm the validity and practicality of our approach, and we predict robust and stable operation of the designed all-fiber torsional AO filters.

  7. A Pole-Zero Filter Cascade Provides Good Fits to Human Masking Data and to Basilar Membrane and Neural Data

    NASA Astrophysics Data System (ADS)

    Lyon, Richard F.

    2011-11-01

    A cascade of two-pole-two-zero filters with level-dependent pole and zero dampings, with few parameters, can provide a good match to human psychophysical and physiological data. The model has been fitted to data on detection threshold for tones in notched-noise masking, including bandwidth and filter shape changes over a wide range of levels, and has been shown to provide better fits with fewer parameters compared to other auditory filter models such as gammachirps. Originally motivated as an efficient machine implementation of auditory filtering related to the WKB analysis method of cochlear wave propagation, such filter cascades also provide good fits to mechanical basilar membrane data, and to auditory nerve data, including linear low-frequency tail response, level-dependent peak gain, sharp tuning curves, nonlinear compression curves, level-independent zero-crossing times in the impulse response, realistic instantaneous frequency glides, and appropriate level-dependent group delay even with minimum-phase response. As part of exploring different level-dependent parameterizations of such filter cascades, we have identified a simple sufficient condition for stable zero-crossing times, based on the shifting property of the Laplace transform: simply move all the s-domain poles and zeros by equal amounts in the real-s direction. Such pole-zero filter cascades are efficient front ends for machine hearing applications, such as music information retrieval, content identification, speech recognition, and sound indexing.

  8. Analysis of multidimensional difference-of-Gaussians filters in terms of directly observable parameters.

    PubMed

    Cope, Davis; Blakeslee, Barbara; McCourt, Mark E

    2013-05-01

    The difference-of-Gaussians (DOG) filter is a widely used model for the receptive field of neurons in the retina and lateral geniculate nucleus (LGN) and is a potential model in general for responses modulated by an excitatory center with an inhibitory surrounding region. A DOG filter is defined by three standard parameters: the center and surround sigmas (which define the variance of the radially symmetric Gaussians) and the balance (which defines the linear combination of the two Gaussians). These parameters are not directly observable and are typically determined by nonlinear parameter estimation methods applied to the frequency response function. DOG filters show both low-pass (optimal response at zero frequency) and bandpass (optimal response at a nonzero frequency) behavior. This paper reformulates the DOG filter in terms of a directly observable parameter, the zero-crossing radius, and two new (but not directly observable) parameters. In the two-dimensional parameter space, the exact region corresponding to bandpass behavior is determined. A detailed description of the frequency response characteristics of the DOG filter is obtained. It is also found that the directly observable optimal frequency and optimal gain (the ratio of the response at optimal frequency to the response at zero frequency) provide an alternate coordinate system for the bandpass region. Altogether, the DOG filter and its three standard implicit parameters can be determined by three directly observable values. The two-dimensional bandpass region is a potential tool for the analysis of populations of DOG filters (for example, populations of neurons in the retina or LGN), because the clustering of points in this parameter space may indicate an underlying organizational principle. This paper concentrates on circular Gaussians, but the results generalize to multidimensional radially symmetric Gaussians and are given as an appendix.

  9. The Essential Complexity of Auditory Receptive Fields

    PubMed Central

    Thorson, Ivar L.; Liénard, Jean; David, Stephen V.

    2015-01-01

    Encoding properties of sensory neurons are commonly modeled using linear finite impulse response (FIR) filters. For the auditory system, the FIR filter is instantiated in the spectro-temporal receptive field (STRF), often in the framework of the generalized linear model. Despite widespread use of the FIR STRF, numerous formulations for linear filters are possible that require many fewer parameters, potentially permitting more efficient and accurate model estimates. To explore these alternative STRF architectures, we recorded single-unit neural activity from auditory cortex of awake ferrets during presentation of natural sound stimuli. We compared performance of > 1000 linear STRF architectures, evaluating their ability to predict neural responses to a novel natural stimulus. Many were able to outperform the FIR filter. Two basic constraints on the architecture lead to the improved performance: (1) factorization of the STRF matrix into a small number of spectral and temporal filters and (2) low-dimensional parameterization of the factorized filters. The best parameterized model was able to outperform the full FIR filter in both primary and secondary auditory cortex, despite requiring fewer than 30 parameters, about 10% of the number required by the FIR filter. After accounting for noise from finite data sampling, these STRFs were able to explain an average of 40% of A1 response variance. The simpler models permitted more straightforward interpretation of sensory tuning properties. They also showed greater benefit from incorporating nonlinear terms, such as short term plasticity, that provide theoretical advances over the linear model. Architectures that minimize parameter count while maintaining maximum predictive power provide insight into the essential degrees of freedom governing auditory cortical function. They also maximize statistical power available for characterizing additional nonlinear properties that limit current auditory models. PMID:26683490

  10. Modified signal-to-noise: a new simple and practical gene filtering approach based on the concept of projective adaptive resonance theory (PART) filtering method.

    PubMed

    Takahashi, Hiro; Honda, Hiroyuki

    2006-07-01

    Considering the recent advances in and the benefits of DNA microarray technologies, many gene filtering approaches have been employed for the diagnosis and prognosis of diseases. In our previous study, we developed a new filtering method, namely, the projective adaptive resonance theory (PART) filtering method. This method was effective in subclass discrimination. In the PART algorithm, the genes with a low variance in gene expression in either class, not both classes, were selected as important genes for modeling. Based on this concept, we developed novel simple filtering methods such as modified signal-to-noise (S2N') in the present study. The discrimination model constructed using these methods showed higher accuracy with higher reproducibility as compared with many conventional filtering methods, including the t-test, S2N, NSC and SAM. The reproducibility of prediction was evaluated based on the correlation between the sets of U-test p-values on randomly divided datasets. With respect to leukemia, lymphoma and breast cancer, the correlation was high; a difference of >0.13 was obtained by the constructed model by using <50 genes selected by S2N'. Improvement was higher in the smaller genes and such higher correlation was observed when t-test, NSC and SAM were used. These results suggest that these modified methods, such as S2N', have high potential to function as new methods for marker gene selection in cancer diagnosis using DNA microarray data. Software is available upon request.

  11. Optimal focal-plane restoration

    NASA Technical Reports Server (NTRS)

    Reichenbach, Stephen E.; Park, Stephen K.

    1989-01-01

    Image restoration can be implemented efficiently by calculating the convolution of the digital image and a small kernel during image acquisition. Processing the image in the focal-plane in this way requires less computation than traditional Fourier-transform-based techniques such as the Wiener filter and constrained least-squares filter. Here, the values of the convolution kernel that yield the restoration with minimum expected mean-square error are determined using a frequency analysis of the end-to-end imaging system. This development accounts for constraints on the size and shape of the spatial kernel and all the components of the imaging system. Simulation results indicate the technique is effective and efficient.

  12. Integration of radar altimeter, precision navigation, and digital terrain data for low-altitude flight

    NASA Technical Reports Server (NTRS)

    Zelenka, Richard E.

    1992-01-01

    A Kalman filter for the integration of a radar altimeter into a terrain database-dependent guidance system was developed. Results obtained from a low-altitude helicopter flight test data acquired over moderately rugged terrain showed that the proposed Kalman filter removes large disparities in predicted above-ground-level (AGL) altitude in the presence of measurement anomalies and dropouts. Integration of a radar altimeter makes it possible to operate a near-terrain guidance system at or below 50 ft (subject to obstacle-avoidance limitations), whereas without radar altimeter integration, a minimum clearance altitude of 220 AGL is needed, as is suggested by previous work.

  13. Motion adaptive Kalman filter for super-resolution

    NASA Astrophysics Data System (ADS)

    Richter, Martin; Nasse, Fabian; Schröder, Hartmut

    2011-01-01

    Superresolution is a sophisticated strategy to enhance image quality of both low and high resolution video, performing tasks like artifact reduction, scaling and sharpness enhancement in one algorithm, all of them reconstructing high frequency components (above Nyquist frequency) in some way. Especially recursive superresolution algorithms can fulfill high quality aspects because they control the video output using a feed-back loop and adapt the result in the next iteration. In addition to excellent output quality, temporal recursive methods are very hardware efficient and therefore even attractive for real-time video processing. A very promising approach is the utilization of Kalman filters as proposed by Farsiu et al. Reliable motion estimation is crucial for the performance of superresolution. Therefore, robust global motion models are mainly used, but this also limits the application of superresolution algorithm. Thus, handling sequences with complex object motion is essential for a wider field of application. Hence, this paper proposes improvements by extending the Kalman filter approach using motion adaptive variance estimation and segmentation techniques. Experiments confirm the potential of our proposal for ideal and real video sequences with complex motion and further compare its performance to state-of-the-art methods like trainable filters.

  14. Experimental demonstration of quantum teleportation of a squeezed state

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Takei, Nobuyuki; Aoki, Takao; Yonezawa, Hidehiro

    2005-10-15

    Quantum teleportation of a squeezed state is demonstrated experimentally. Due to some inevitable losses in experiments, a squeezed vacuum necessarily becomes a mixed state which is no longer a minimum uncertainty state. We establish an operational method of evaluation for quantum teleportation of such a state using fidelity and discuss the classical limit for the state. The measured fidelity for the input state is 0.85{+-}0.05, which is higher than the classical case of 0.73{+-}0.04. We also verify that the teleportation process operates properly for the nonclassical state input and its squeezed variance is certainly transferred through the process. We observemore » the smaller variance of the teleported squeezed state than that for the vacuum state input.« less

  15. Quantizing and sampling considerations in digital phased-locked loops

    NASA Technical Reports Server (NTRS)

    Hurst, G. T.; Gupta, S. C.

    1974-01-01

    The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

  16. Importance of Geosat orbit and tidal errors in the estimation of large-scale Indian Ocean variations

    NASA Technical Reports Server (NTRS)

    Perigaud, Claire; Zlotnicki, Victor

    1992-01-01

    To improve the estimate accuracy of large-scale meridional sea-level variations, Geosat ERM data on the Indian Ocean for a 26-month period were processed using two different techniques of orbit error reduction. The first technique removes an along-track polynomial of degree 1 over about 5000 km and the second technique removes an along-track once-per-revolution sine wave about 40,000 km. Results obtained show that the polynomial technique produces stronger attenuation of both the tidal error and the large-scale oceanic signal. After filtering, the residual difference between the two methods represents 44 percent of the total variance and 23 percent of the annual variance. The sine-wave method yields a larger estimate of annual and interannual meridional variations.

  17. Identifying differences in brain activities and an accurate detection of autism spectrum disorder using resting state functional-magnetic resonance imaging : A spatial filtering approach.

    PubMed

    Subbaraju, Vigneshwaran; Suresh, Mahanand Belathur; Sundaram, Suresh; Narasimhan, Sundararajan

    2017-01-01

    This paper presents a new approach for detecting major differences in brain activities between Autism Spectrum Disorder (ASD) patients and neurotypical subjects using the resting state fMRI. Further the method also extracts discriminative features for an accurate diagnosis of ASD. The proposed approach determines a spatial filter that projects the covariance matrices of the Blood Oxygen Level Dependent (BOLD) time-series signals from both the ASD patients and neurotypical subjects in orthogonal directions such that they are highly separable. The inverse of this filter also provides a spatial pattern map within the brain that highlights those regions responsible for the distinguishable activities between the ASD patients and neurotypical subjects. For a better classification, highly discriminative log-variance features providing the maximum separation between the two classes are extracted from the projected BOLD time-series data. A detailed study has been carried out using the publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) consortium for the different gender and age-groups. The study results indicate that for all the above categories, the regional differences in resting state activities are more commonly found in the right hemisphere compared to the left hemisphere of the brain. Among males, a clear shift in activities to the prefrontal cortex is observed for ASD patients while other parts of the brain show diminished activities compared to neurotypical subjects. Among females, such a clear shift is not evident; however, several regions, especially in the posterior and medial portions of the brain show diminished activities due to ASD. Finally, the classification performance obtained using the log-variance features is found to be better when compared to earlier studies in the literature. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. A Minimum Fuel Based Estimator for Maneuver and Natrual Dynamics Reconstruction

    NASA Astrophysics Data System (ADS)

    Lubey, D.; Scheeres, D.

    2013-09-01

    The vast and growing population of objects in Earth orbit (active and defunct spacecraft, orbital debris, etc.) offers many unique challenges when it comes to tracking these objects and associating the resulting observations. Complicating these challenges are the inaccurate natural dynamical models of these objects, the active maneuvers of spacecraft that deviate them from their ballistic trajectories, and the fact that spacecraft are tracked and operated by separate agencies. Maneuver detection and reconstruction algorithms can help with each of these issues by estimating mismodeled and unmodeled dynamics through indirect observation of spacecraft. It also helps to verify the associations made by an object correlation algorithm or aid in making those associations, which is essential when tracking objects in orbit. The algorithm developed in this study applies an Optimal Control Problem (OCP) Distance Metric approach to the problems of Maneuver Reconstruction and Dynamics Estimation. This was first developed by Holzinger, Scheeres, and Alfriend (2011), with a subsequent study by Singh, Horwood, and Poore (2012). This method estimates the minimum fuel control policy rather than the state as a typical Kalman Filter would. This difference ensures that the states are connected through a given dynamical model and allows for automatic covariance manipulation, which can help to prevent filter saturation. Using a string of measurements (either verified or hypothesized to correlate with one another), the algorithm outputs a corresponding string of adjoint and state estimates with associated noise. Post-processing techniques are implemented, which when applied to the adjoint estimates can remove noise and expose unmodeled maneuvers and mismodeled natural dynamics. Specifically, the estimated controls are used to determine spacecraft dependent accelerations (atmospheric drag and solar radiation pressure) using an adapted form of the Optimal Control based natural dynamics estimation scheme developed by Lubey and Scheeres (2012). In order to allow for direct comparison, the estimator developed here was modeled after a typical Kalman Filter. The estimator forces the terminal state to lie on a manifold that satisfies the least squares with a priori information cost function, thus establishing a link with a typical Kalman filter. Terms are collected into a pseudo-Kalman Gain, which creates an equivalent form in the state estimates and covariances between the two estimators. While the two estimators share common roots, the inclusion of control in the Minimum Fuel Estimator gives it special properties. For instance, the inclusion of adjoint noise can help to automatically prevent filter saturation in a manner similar to a State Noise Compensation Algorithm. This property is quite important when considering dynamics mismodeling as filter saturation will cause estimate divergence for mismodeled systems. Additional properties and alternative forms of the estimator are also explored in this study. Several implementations of this estimator are given in this paper. It is applied to LEO, GEO, and GTO orbits with drag and SRP mismodeling. The inclusion of unmodeled maneuvers is also considered. These numerical simulations verify the mathematical properties of this estimator, and demonstrate the advantages that this estimator has over typical Kalman Filters.

  19. Is the difference between chemical and numerical estimates of baseflow meaningful?

    NASA Astrophysics Data System (ADS)

    Cartwright, Ian; Gilfedder, Ben; Hofmann, Harald

    2014-05-01

    Both chemical and numerical techniques are commonly used to calculate baseflow inputs to gaining rivers. In general the chemical methods yield lower estimates of baseflow than the numerical techniques. In part, this may be due to the techniques assuming two components (event water and baseflow) whereas there may also be multiple transient stores of water. Bank return waters, interflow, or waters stored on floodplains are delayed components that may be geochemically similar to the surface water from which they are derived; numerical techniques may record these components as baseflow whereas chemical mass balance studies are likely to aggregate them with the surface water component. This study compares baseflow estimates using chemical mass balance, local minimum methods, and recursive digital filters in the upper reaches of the Barwon River, southeast Australia. While more sophisticated techniques exist, these methods of estimating baseflow are readily applied with the available data and have been used widely elsewhere. During the early stages of high-discharge events, chemical mass balance overestimates groundwater inflows, probably due to flushing of saline water from wetlands and marshes, soils, or the unsaturated zone. Overall, however, estimates of baseflow from the local minimum and recursive digital filters are higher than those from chemical mass balance using Cl calculated from continuous electrical conductivity. Between 2001 and 2011, the baseflow contribution to the upper Barwon River calculated using chemical mass balance is between 12 and 25% of annual discharge. Recursive digital filters predict higher baseflow contributions of 19 to 52% of annual discharge. These estimates are similar to those from the local minimum method (16 to 45% of annual discharge). These differences most probably reflect how the different techniques characterise the transient water sources in this catchment. The local minimum and recursive digital filters aggregate much of the water from delayed sources as baseflow. However, as many of these delayed transient water stores (such as bank return flow, floodplain storage, or interflow) have Cl concentrations that are similar to surface runoff, chemical mass balance calculations aggregate them with the surface runoff component. The difference between the estimates is greatest following periods of high discharge in winter, implying that these transient stores of water feed the river for several weeks to months at that time. Cl vs. discharge variations during individual flow events also demonstrate that inflows of high-salinity older water occurs on the rising limbs of hydrographs followed by inflows of low-salinity water from the transient stores as discharge falls. The use of complementary techniques allows a better understanding of the different components of water that contribute to river flow, which is important for the management and protection of water resources.

  20. Statistical procedures for determination and verification of minimum reporting levels for drinking water methods.

    PubMed

    Winslow, Stephen D; Pepich, Barry V; Martin, John J; Hallberg, George R; Munch, David J; Frebis, Christopher P; Hedrick, Elizabeth J; Krop, Richard A

    2006-01-01

    The United States Environmental Protection Agency's Office of Ground Water and Drinking Water has developed a single-laboratory quantitation procedure: the lowest concentration minimum reporting level (LCMRL). The LCMRL is the lowest true concentration for which future recovery is predicted to fall, with high confidence (99%), between 50% and 150%. The procedure takes into account precision and accuracy. Multiple concentration replicates are processed through the entire analytical method and the data are plotted as measured sample concentration (y-axis) versus true concentration (x-axis). If the data support an assumption of constant variance over the concentration range, an ordinary least-squares regression line is drawn; otherwise, a variance-weighted least-squares regression is used. Prediction interval lines of 99% confidence are drawn about the regression. At the points where the prediction interval lines intersect with data quality objective lines of 50% and 150% recovery, lines are dropped to the x-axis. The higher of the two values is the LCMRL. The LCMRL procedure is flexible because the data quality objectives (50-150%) and the prediction interval confidence (99%) can be varied to suit program needs. The LCMRL determination is performed during method development only. A simpler procedure for verification of data quality objectives at a given minimum reporting level (MRL) is also presented. The verification procedure requires a single set of seven samples taken through the entire method procedure. If the calculated prediction interval is contained within data quality recovery limits (50-150%), the laboratory performance at the MRL is verified.

  1. The effectiveness of texture analysis for mapping forest land using the panchromatic bands of Landsat 7, SPOT, and IRS imagery

    Treesearch

    Michael L. Hoppus; Rachel I. Riemann; Andrew J. Lister; Mark V. Finco

    2002-01-01

    The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land use/cover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving...

  2. Solution Methods for Certain Evolution Equations

    NASA Astrophysics Data System (ADS)

    Vega-Guzman, Jose Manuel

    Solution methods for certain linear and nonlinear evolution equations are presented in this dissertation. Emphasis is placed mainly on the analytical treatment of nonautonomous differential equations, which are challenging to solve despite the existent numerical and symbolic computational software programs available. Ideas from the transformation theory are adopted allowing one to solve the problems under consideration from a non-traditional perspective. First, the Cauchy initial value problem is considered for a class of nonautonomous and inhomogeneous linear diffusion-type equation on the entire real line. Explicit transformations are used to reduce the equations under study to their corresponding standard forms emphasizing on natural relations with certain Riccati(and/or Ermakov)-type systems. These relations give solvability results for the Cauchy problem of the parabolic equation considered. The superposition principle allows to solve formally this problem from an unconventional point of view. An eigenfunction expansion approach is also considered for this general evolution equation. Examples considered to corroborate the efficacy of the proposed solution methods include the Fokker-Planck equation, the Black-Scholes model and the one-factor Gaussian Hull-White model. The results obtained in the first part are used to solve the Cauchy initial value problem for certain inhomogeneous Burgers-type equation. The connection between linear (the Diffusion-type) and nonlinear (Burgers-type) parabolic equations is stress in order to establish a strong commutative relation. Traveling wave solutions of a nonautonomous Burgers equation are also investigated. Finally, it is constructed explicitly the minimum-uncertainty squeezed states for quantum harmonic oscillators. They are derived by the action of corresponding maximal kinematical invariance group on the standard ground state solution. It is shown that the product of the variances attains the required minimum value only at the instances that one variance is a minimum and the other is a maximum, when the squeezing of one of the variances occurs. Such explicit construction is possible due to the relation between the diffusion-type equation studied in the first part and the time-dependent Schrodinger equation. A modication of the radiation field operators for squeezed photons in a perfect cavity is also suggested with the help of a nonstandard solution of Heisenberg's equation of motion.

  3. Eigenspace-based minimum variance beamformer combined with Wiener postfilter for medical ultrasound imaging.

    PubMed

    Zeng, Xing; Chen, Cheng; Wang, Yuanyuan

    2012-12-01

    In this paper, a new beamformer which combines the eigenspace-based minimum variance (ESBMV) beamformer with the Wiener postfilter is proposed for medical ultrasound imaging. The primary goal of this work is to further improve the medical ultrasound imaging quality on the basis of the ESBMV beamformer. In this method, we optimize the ESBMV weights with a Wiener postfilter. With the optimization of the Wiener postfilter, the output power of the new beamformer becomes closer to the actual signal power at the imaging point than the ESBMV beamformer. Different from the ordinary Wiener postfilter, the output signal and noise power needed in calculating the Wiener postfilter are estimated respectively by the orthogonal signal subspace and noise subspace constructed from the eigenstructure of the sample covariance matrix. We demonstrate the performance of the new beamformer when resolving point scatterers and cyst phantom using both simulated data and experimental data and compare it with the delay-and-sum (DAS), the minimum variance (MV) and the ESBMV beamformer. We use the full width at half maximum (FWHM) and the peak-side-lobe level (PSL) to quantify the performance of imaging resolution and the contrast ratio (CR) to quantify the performance of imaging contrast. The FWHM of the new beamformer is only 15%, 50% and 50% of those of the DAS, MV and ESBMV beamformer, while the PSL is 127.2dB, 115dB and 60dB lower. What is more, an improvement of 239.8%, 232.5% and 32.9% in CR using simulated data and an improvement of 814%, 1410.7% and 86.7% in CR using experimental data are achieved compared to the DAS, MV and ESBMV beamformer respectively. In addition, the effect of the sound speed error is investigated by artificially overestimating the speed used in calculating the propagation delay and the results show that the new beamformer provides better robustness against the sound speed errors. Therefore, the proposed beamformer offers a better performance than the DAS, MV and ESBMV beamformer, showing its potential in medical ultrasound imaging. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Toward standardized test methods to determine the effectiveness of filtration media against airborne nanoparticles

    NASA Astrophysics Data System (ADS)

    Wang, Jing; Tronville, Paolo

    2014-06-01

    The filtration of airborne nanoparticles is an important control technique as the environmental, health, and safety impacts of nanomaterials grow. A review of the literature shows that significant progress has been made on airborne nanoparticle filtration in the academic field in the recent years. We summarize the filtration mechanisms of fibrous and membrane filters; the air flow resistance and filter media figure of merit are discussed. Our review focuses on the air filtration test methods and instrumentation necessary to implement them; recent experimental studies are summarized accordingly. Two methods using monodisperse and polydisperse challenging aerosols, respectively, are discussed in detail. Our survey shows that the commercial instruments are already available for generating a large amount of nanoparticles, sizing, and quantifying them accurately. The commercial self-contained filter test systems provide the possibility of measurement for particles down to 15 nm. Current international standards dealing with efficiency test for filters and filter media focus on measurement of the minimum efficiency at the most penetrating particle size. The available knowledge and instruments provide a solid base for development of test methods to determine the effectiveness of filtration media against airborne nanoparticles down to single-digit nanometer range.

  5. Proportional-Integral-Derivative (PID) Temperature Control and Data Acquisition System for Faraday Filter based Sodium Spectrometer

    NASA Astrophysics Data System (ADS)

    Semerjyan, Vardan; Yuan, Tao

    2011-04-01

    Sodium (Na) Faraday filters based spectrometer is a relatively new instrument to study sodium nightglow as well as sodium and oxygen chemistry in the mesopause region. Successful spectrometer measurement demands highly accurate control of filter temperature. The ideal, long-term operation site for the Na spectrometer is an isolated location with minimum nocturnal sky background. Thus, the remote control of the filter temperature is a requirement for such operation, whereas current temperature controllers can only be operated manually. The proposed approach is aimed to not only enhance the temperature control, but also achieve spectrometer's remote and autonomous operation. In the meantime, the redesign should relief the burden of the cost for multi temperature controllers. The program will give to the operator flexibility in setting the operation temperatures of the Faraday filters, monitoring the temperature variations, and logging the data during the operation. Research will make diligent efforts to attach preliminary data analysis subroutine to the main control program. The real-time observation results will be posted online after the observation is completed. This approach also can be a good substitute for the temperature control system currently used to run the Lidar system at Utah State University (USU).

  6. Static and Dynamic Characteristics of DC-DC Converter Using a Digital Filter

    NASA Astrophysics Data System (ADS)

    Kurokawa, Fujio; Okamatsu, Masashi

    This paper presents the regulation and dynamic characteristics of the dc-dc converter with digital PID control, the minimum phase FIR filter or the IIR filter, and then the design criterion to improve the dynamic characteristics is discussed. As a result, it is clarified that the DC-DC converter using the IIR filter method has superior performance characteristics. The regulation range is within 1.3%, the undershoot against the step change of the load is less than 2% and the transient time is less than 0.4ms with the IIR filter method. In this case, the switching frequency is 100kHz and the step change of the load R is from 50 Ω to 10 Ω. Further, the superior characteristics are obtained when the first gain, the second gain and the second cut-off frequency are relatively large, and the first cut-off frequency and the passing frequency are relatively low. Moreover, it is important that the gain strongly decreases at the second cut-off frequency because the upper band pass frequency range must be always less than half of the sampling frequency based on the sampling theory.

  7. Investigation of optical current transformer signal processing method based on an improved Kalman algorithm

    NASA Astrophysics Data System (ADS)

    Shen, Yan; Ge, Jin-ming; Zhang, Guo-qing; Yu, Wen-bin; Liu, Rui-tong; Fan, Wei; Yang, Ying-xuan

    2018-01-01

    This paper explores the problem of signal processing in optical current transformers (OCTs). Based on the noise characteristics of OCTs, such as overlapping signals, noise frequency bands, low signal-to-noise ratios, and difficulties in acquiring statistical features of noise power, an improved standard Kalman filtering algorithm was proposed for direct current (DC) signal processing. The state-space model of the OCT DC measurement system is first established, and then mixed noise can be processed by adding mixed noise into measurement and state parameters. According to the minimum mean squared error criterion, state predictions and update equations of the improved Kalman algorithm could be deduced based on the established model. An improved central difference Kalman filter was proposed for alternating current (AC) signal processing, which improved the sampling strategy and noise processing of colored noise. Real-time estimation and correction of noise were achieved by designing AC and DC noise recursive filters. Experimental results show that the improved signal processing algorithms had a good filtering effect on the AC and DC signals with mixed noise of OCT. Furthermore, the proposed algorithm was able to achieve real-time correction of noise during the OCT filtering process.

  8. Applying Kalman filtering to investigate tropospheric effects in VLBI

    NASA Astrophysics Data System (ADS)

    Soja, Benedikt; Nilsson, Tobias; Karbon, Maria; Heinkelmann, Robert; Liu, Li; Lu, Cuixian; Andres Mora-Diaz, Julian; Raposo-Pulido, Virginia; Xu, Minghui; Schuh, Harald

    2014-05-01

    Very Long Baseline Interferometry (VLBI) currently provides results, e.g., estimates of the tropospheric delays, with a delay of more than two weeks. In the future, with the coming VLBI2010 Global Observing System (VGOS) and increased usage of electronic data transfer, it is planned that the time between observations and results is decreased. This may, for instance, allow the integration of VLBI-derived tropospheric delays into numerical weather prediction models. Therefore, future VLBI analysis software packages need to be able to process the observational data autonomously in near real-time. For this purpose, we have extended the Vienna VLBI Software (VieVS) by a Kalman filter module. This presentation describes the filter and discusses its application for tropospheric studies. Instead of estimating zenith wet delays as piece-wise linear functions in a least-squares adjustment, the Kalman filter allows for more sophisticated stochastic modeling. We start with a random walk process to model the time-dependent behavior of the zenith wet delays. Other possible approaches include the stochastic model described by turbulence theory, e.g. the model by Treuhaft and Lanyi (1987). Different variance-covariance matrices of the prediction error, depending on the time of the year and the geographic latitude, have been tested. In winter and closer to the poles, lower variances and covariances are appropriate. The horizontal variations in tropospheric delays have been investigated by comparing three different strategies: assumption of a horizontally stratified troposphere, using north and south gradients modeled, e.g., as Gauss-Markov processes, and applying a turbulence model assuming correlations between observations in different azimuths. By conducting Monte-Carlo simulations of current standard VLBI networks and of future VGOS networks, the different tropospheric modeling strategies are investigated. For this purpose, we use the simulator module of VieVS which takes into account the errors due to the atomic clocks at the stations, the troposphere, and white noise processes. The simulated data as well as actual observational data from the two-week CONT11 campaign are analyzed using the Kalman filter, focusing on the tropospheric effects. The results of the different strategies are compared with solutions applying the classical least-squares method. An advantage of the Kalman filter is the possibility of easily integrating additional external information. It is expected that by including tropospheric delays from GNSS, water vapor radiometers, or ray-traced delays from numerical weather prediction models, the accuracy of the VLBI solution could be improved.

  9. An Adaptive Pheromone Updation of the Ant-System using LMS Technique

    NASA Astrophysics Data System (ADS)

    Paul, Abhishek; Mukhopadhyay, Sumitra

    2010-10-01

    We propose a modified model of pheromone updation for Ant-System, entitled as Adaptive Ant System (AAS), using the properties of basic Adaptive Filters. Here, we have exploited the properties of Least Mean Square (LMS) algorithm for the pheromone updation to find out the best minimum tour for the Travelling Salesman Problem (TSP). TSP library has been used for the selection of benchmark problem and the proposed AAS determines the minimum tour length for the problems containing large number of cities. Our algorithm shows effective results and gives least tour length in most of the cases as compared to other existing approaches.

  10. Metagenomic characterization of biofilter microbial communities in a full-scale drinking water treatment plant.

    PubMed

    Oh, Seungdae; Hammes, Frederik; Liu, Wen-Tso

    2018-01-01

    Microorganisms inhabiting filtration media of a drinking water treatment plant can be beneficial, because they metabolize biodegradable organic matter from source waters and those formed during disinfection processes, leading to the production of biologically stable drinking water. However, which microbial consortia colonize filters and what metabolic capacity they possess remain to be investigated. To gain insights into these issues, we performed metagenome sequencing and analysis of microbial communities in three different filters of a full-scale drinking water treatment plant (DWTP). Filter communities were sampled from a rapid sand filter (RSF), granular activated carbon filter (GAC), and slow sand filter (SSF), and from the Schmutzdecke (SCM, a biologically active scum layer accumulated on top of SSF), respectively. Analysis of community phylogenetic structure revealed that the filter bacterial communities significantly differed from those in the source water and final effluent communities, respectively. Network analysis identified a filter-specific colonization pattern of bacterial groups. Bradyrhizobiaceae were abundant in GAC, whereas Nitrospira were enriched in the sand-associated filters (RSF, SCM, and SSF). The GAC community was enriched with functions associated with aromatics degradation, many of which were encoded by Rhizobiales (∼30% of the total GAC community). Predicting minimum generation time (MGT) of prokaryotic communities suggested that the GAC community potentially select fast-growers (<15 h of MGT) among the four filter communities, consistent with the highest dissolved organic matter removal rate by GAC. Our findings provide new insights into the community phylogenetic structure, colonization pattern, and metabolic capacity that potentially contributes to organic matter removal achieved in the biofiltration stages of the full-scale DWTP. Copyright © 2017 Elsevier Ltd. All rights reserved.

  11. Variables Influencing Extraction of Nucleic Acids from Microbial Plankton (Viruses, Bacteria, and Protists) Collected on Nanoporous Aluminum Oxide Filters

    PubMed Central

    Mueller, Jaclyn A.; Culley, Alexander I.

    2014-01-01

    Anodic aluminum oxide (AAO) filters have high porosity and can be manufactured with a pore size that is small enough to quantitatively capture viruses. These properties make the filters potentially useful for harvesting total microbial communities from water samples for molecular analyses, but their performance for nucleic acid extraction has not been systematically or quantitatively evaluated. In this study, we characterized the flux of water through commercially produced nanoporous (0.02 μm) AAO filters (Anotop; Whatman) and used isolates (a virus, a bacterium, and a protist) and natural seawater samples to test variables that we expected would influence the efficiency with which nucleic acids are recovered from the filters. Extraction chemistry had a significant effect on DNA yield, and back flushing the filters during extraction was found to improve yields of high-molecular-weight DNA. Using the back-flush protocol, the mass of DNA recovered from microorganisms collected on AAO filters was ≥100% of that extracted from pellets of cells and viruses and 94% ± 9% of that obtained by direct extraction of a liquid bacterial culture. The latter is a minimum estimate of the relative recovery of microbial DNA, since liquid cultures include dissolved nucleic acids that are retained inefficiently by the filter. In conclusion, we demonstrate that nucleic acids can be extracted from microorganisms on AAO filters with an efficiency similar to that achievable by direct extraction of microbes in suspension or in pellets. These filters are therefore a convenient means by which to harvest total microbial communities from multiple aqueous samples in parallel for subsequent molecular analyses. PMID:24747903

  12. Comparative Study of Speckle Filtering Methods in PolSAR Radar Images

    NASA Astrophysics Data System (ADS)

    Boutarfa, S.; Bouchemakh, L.; Smara, Y.

    2015-04-01

    Images acquired by polarimetric SAR (PolSAR) radar systems are characterized by the presence of a noise called speckle. This noise has a multiplicative nature, corrupts both the amplitude and phase images, which complicates data interpretation, degrades segmentation performance and reduces the detectability of targets. Hence, the need to preprocess the images by adapted filtering methods before analysis.In this paper, we present a comparative study of implemented methods for reducing speckle in PolSAR images. These developed filters are: refined Lee filter based on the estimation of the minimum mean square error MMSE, improved Sigma filter with detection of strong scatterers based on the calculation of the coherency matrix to detect the different scatterers in order to preserve the polarization signature and maintain structures that are necessary for image interpretation, filtering by stationary wavelet transform SWT using multi-scale edge detection and the technique for improving the wavelet coefficients called SSC (sum of squared coefficients), and Turbo filter which is a combination between two complementary filters the refined Lee filter and the wavelet transform SWT. One filter can boost up the results of the other.The originality of our work is based on the application of these methods to several types of images: amplitude, intensity and complex, from a satellite or an airborne radar, and on the optimization of wavelet filtering by adding a parameter in the calculation of the threshold. This parameter will control the filtering effect and get a good compromise between smoothing homogeneous areas and preserving linear structures.The methods are applied to the fully polarimetric RADARSAT-2 images (HH, HV, VH, VV) acquired on Algiers, Algeria, in C-band and to the three polarimetric E-SAR images (HH, HV, VV) acquired on Oberpfaffenhofen area located in Munich, Germany, in P-band.To evaluate the performance of each filter, we used the following criteria: smoothing homogeneous areas, preserving edges and polarimetric information.Experimental results are included to illustrate the different implemented methods.

  13. Filtering Using Nonlinear Expectations

    DTIC Science & Technology

    2016-04-16

    gives a solution to estimating a Markov chain observed in Gaussian noise when the variance of the noise is unkown. This paper is accepted for the IEEE...Optimization, an A* journal. A short third paper discusses how to estimate a change in the transition dynamics of a noisily observed Markov chain ...The change point time is hidden in a hidden Markov chain , so a second level of discovery is involved. This paper is accepted for Communications in

  14. 40 CFR 63.7525 - What are my monitoring, installation, operation, and maintenance requirements?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... tolerance of 1.27 centimeters of water or a transducer with a minimum tolerance of 1 percent of the pressure... use a fabric filter bag leak detection system to comply with the requirements of this subpart, you must install, calibrate, maintain, and continuously operate a bag leak detection system as specified in...

  15. Can We Legislate Spam?

    ERIC Educational Resources Information Center

    Wigen, Wendy

    2004-01-01

    Spam is not just a technology issue. It is a social issue, and it threatens something very dear: the viability of e-mail. Campuses struggle to support solutions that will control the costs of filtering spam, keep "false positives" to a minimum and not diminish their own marketing use of mass e-mails. The openness of the Internet, long touted as…

  16. 27 CFR 21.122 - Pyridine bases.

    Code of Federal Regulations, 2010 CFR

    2010-04-01

    ... with 1 N H2SO4 until a drop of the mixture placed upon Congo paper shows a distinct blue border, which soon disappears. A minimum of 9.5 ml of the acid must be required for the end point. (Congo paper: filter paper treated with 0.1 percent aqueous solution of Congo red and dried.) (b) Distillation range...

  17. 27 CFR 21.122 - Pyridine bases.

    Code of Federal Regulations, 2012 CFR

    2012-04-01

    ... with 1 N H2SO4 until a drop of the mixture placed upon Congo paper shows a distinct blue border, which soon disappears. A minimum of 9.5 ml of the acid must be required for the end point. (Congo paper: filter paper treated with 0.1 percent aqueous solution of Congo red and dried.) (b) Distillation range...

  18. 27 CFR 21.122 - Pyridine bases.

    Code of Federal Regulations, 2011 CFR

    2011-04-01

    ... with 1 N H2SO4 until a drop of the mixture placed upon Congo paper shows a distinct blue border, which soon disappears. A minimum of 9.5 ml of the acid must be required for the end point. (Congo paper: filter paper treated with 0.1 percent aqueous solution of Congo red and dried.) (b) Distillation range...

  19. 27 CFR 21.122 - Pyridine bases.

    Code of Federal Regulations, 2014 CFR

    2014-04-01

    ... with 1 N H2SO4 until a drop of the mixture placed upon Congo paper shows a distinct blue border, which soon disappears. A minimum of 9.5 ml of the acid must be required for the end point. (Congo paper: filter paper treated with 0.1 percent aqueous solution of Congo red and dried.) (b) Distillation range...

  20. 27 CFR 21.122 - Pyridine bases.

    Code of Federal Regulations, 2013 CFR

    2013-04-01

    ... with 1 N H2SO4 until a drop of the mixture placed upon Congo paper shows a distinct blue border, which soon disappears. A minimum of 9.5 ml of the acid must be required for the end point. (Congo paper: filter paper treated with 0.1 percent aqueous solution of Congo red and dried.) (b) Distillation range...

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