Monte-Carlo error analysis in x-ray spectral deconvolution
International Nuclear Information System (INIS)
Shirk, D.G.; Hoffman, N.M.
1985-01-01
The deconvolution of spectral information from sparse x-ray data is a widely encountered problem in data analysis. An often-neglected aspect of this problem is the propagation of random error in the deconvolution process. We have developed a Monte-Carlo approach that enables us to attach error bars to unfolded x-ray spectra. Our Monte-Carlo error analysis has been incorporated into two specific deconvolution techniques: the first is an iterative convergent weight method; the second is a singular-value-decomposition (SVD) method. These two methods were applied to an x-ray spectral deconvolution problem having m channels of observations with n points in energy space. When m is less than n, this problem has no unique solution. We discuss the systematics of nonunique solutions and energy-dependent error bars for both methods. The Monte-Carlo approach has a particular benefit in relation to the SVD method: It allows us to apply the constraint of spectral nonnegativity after the SVD deconvolution rather than before. Consequently, we can identify inconsistencies between different detector channels
Sarkar, Abhra
2014-10-02
We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are available for sufficiently many subjects. Under the assumption of additive measurement errors this reduces to a problem of deconvolution of densities. Deconvolution methods often make restrictive and unrealistic assumptions about the density of interest and the distribution of measurement errors, e.g., normality and homoscedasticity and thus independence from the variable of interest. This article relaxes these assumptions and introduces novel Bayesian semiparametric methodology based on Dirichlet process mixture models for robust deconvolution of densities in the presence of conditionally heteroscedastic measurement errors. In particular, the models can adapt to asymmetry, heavy tails and multimodality. In simulation experiments, we show that our methods vastly outperform a recent Bayesian approach based on estimating the densities via mixtures of splines. We apply our methods to data from nutritional epidemiology. Even in the special case when the measurement errors are homoscedastic, our methodology is novel and dominates other methods that have been proposed previously. Additional simulation results, instructions on getting access to the data set and R programs implementing our methods are included as part of online supplemental materials.
Sarkar, Abhra; Mallick, Bani K.; Staudenmayer, John; Pati, Debdeep; Carroll, Raymond J.
2014-01-01
We consider the problem of estimating the density of a random variable when precise measurements on the variable are not available, but replicated proxies contaminated with measurement error are available for sufficiently many subjects. Under the assumption of additive measurement errors this reduces to a problem of deconvolution of densities. Deconvolution methods often make restrictive and unrealistic assumptions about the density of interest and the distribution of measurement errors, e.g., normality and homoscedasticity and thus independence from the variable of interest. This article relaxes these assumptions and introduces novel Bayesian semiparametric methodology based on Dirichlet process mixture models for robust deconvolution of densities in the presence of conditionally heteroscedastic measurement errors. In particular, the models can adapt to asymmetry, heavy tails and multimodality. In simulation experiments, we show that our methods vastly outperform a recent Bayesian approach based on estimating the densities via mixtures of splines. We apply our methods to data from nutritional epidemiology. Even in the special case when the measurement errors are homoscedastic, our methodology is novel and dominates other methods that have been proposed previously. Additional simulation results, instructions on getting access to the data set and R programs implementing our methods are included as part of online supplemental materials.
Smoothed Spectra, Ogives, and Error Estimates for Atmospheric Turbulence Data
Dias, Nelson Luís
2018-01-01
A systematic evaluation is conducted of the smoothed spectrum, which is a spectral estimate obtained by averaging over a window of contiguous frequencies. The technique is extended to the ogive, as well as to the cross-spectrum. It is shown that, combined with existing variance estimates for the periodogram, the variance—and therefore the random error—associated with these estimates can be calculated in a straightforward way. The smoothed spectra and ogives are biased estimates; with simple power-law analytical models, correction procedures are devised, as well as a global constraint that enforces Parseval's identity. Several new results are thus obtained: (1) The analytical variance estimates compare well with the sample variance calculated for the Bartlett spectrum and the variance of the inertial subrange of the cospectrum is shown to be relatively much larger than that of the spectrum. (2) Ogives and spectra estimates with reduced bias are calculated. (3) The bias of the smoothed spectrum and ogive is shown to be negligible at the higher frequencies. (4) The ogives and spectra thus calculated have better frequency resolution than the Bartlett spectrum, with (5) gradually increasing variance and relative error towards the low frequencies. (6) Power-law identification and extraction of the rate of dissipation of turbulence kinetic energy are possible directly from the ogive. (7) The smoothed cross-spectrum is a valid inner product and therefore an acceptable candidate for coherence and spectral correlation coefficient estimation by means of the Cauchy-Schwarz inequality. The quadrature, phase function, coherence function and spectral correlation function obtained from the smoothed spectral estimates compare well with the classical ones derived from the Bartlett spectrum.
Wind power forecast error smoothing within a wind farm
International Nuclear Information System (INIS)
Saleck, Nadja; Bremen, Lueder von
2007-01-01
Smoothing of wind power forecast errors is well-known for large areas. Comparable effects within a wind farm are investigated in this paper. A Neural Network was taken to predict the power output of a wind farm in north-western Germany comprising 17 turbines. A comparison was done between an algorithm that fits mean wind and mean power data of the wind farm and a second algorithm that fits wind and power data individually for each turbine. The evaluation of root mean square errors (RMSE) shows that relative small smoothing effects occur. However, it can be shown for this wind farm that individual calculations have the advantage that only a few turbines are needed to give better results than the use of mean data. Furthermore different results occurred if predicted wind speeds are directly fitted to observed wind power or if predicted wind speeds are first fitted to observed wind speeds and then applied to a power curve. The first approach gives slightly better RMSE values, the bias improves considerably
Meresescu, Alina G.; Kowalski, Matthieu; Schmidt, Frédéric; Landais, François
2018-06-01
The Water Residence Time distribution is the equivalent of the impulse response of a linear system allowing the propagation of water through a medium, e.g. the propagation of rain water from the top of the mountain towards the aquifers. We consider the output aquifer levels as the convolution between the input rain levels and the Water Residence Time, starting with an initial aquifer base level. The estimation of Water Residence Time is important for a better understanding of hydro-bio-geochemical processes and mixing properties of wetlands used as filters in ecological applications, as well as protecting fresh water sources for wells from pollutants. Common methods of estimating the Water Residence Time focus on cross-correlation, parameter fitting and non-parametric deconvolution methods. Here we propose a 1D full-deconvolution, regularized, non-parametric inverse problem algorithm that enforces smoothness and uses constraints of causality and positivity to estimate the Water Residence Time curve. Compared to Bayesian non-parametric deconvolution approaches, it has a fast runtime per test case; compared to the popular and fast cross-correlation method, it produces a more precise Water Residence Time curve even in the case of noisy measurements. The algorithm needs only one regularization parameter to balance between smoothness of the Water Residence Time and accuracy of the reconstruction. We propose an approach on how to automatically find a suitable value of the regularization parameter from the input data only. Tests on real data illustrate the potential of this method to analyze hydrological datasets.
Optimal filtering values in renogram deconvolution
Energy Technology Data Exchange (ETDEWEB)
Puchal, R.; Pavia, J.; Gonzalez, A.; Ros, D.
1988-07-01
The evaluation of the isotopic renogram by means of the renal retention function (RRF) is a technique that supplies valuable information about renal function. It is not unusual to perform a smoothing of the data because of the sensitivity of the deconvolution algorithms with respect to noise. The purpose of this work is to confirm the existence of an optimal smoothing which minimises the error between the calculated RRF and the theoretical value for two filters (linear and non-linear). In order to test the effectiveness of these optimal smoothing values, some parameters of the calculated RRF were considered using this optimal smoothing. The comparison of these parameters with the theoretical ones revealed a better result in the case of the linear filter than in the non-linear case. The study was carried out simulating the input and output curves which would be obtained when using hippuran and DTPA as tracers.
Kalman filtering and smoothing for linear wave equations with model error
International Nuclear Information System (INIS)
Lee, Wonjung; McDougall, D; Stuart, A M
2011-01-01
Filtering is a widely used methodology for the incorporation of observed data into time-evolving systems. It provides an online approach to state estimation inverse problems when data are acquired sequentially. The Kalman filter plays a central role in many applications because it is exact for linear systems subject to Gaussian noise, and because it forms the basis for many approximate filters which are used in high-dimensional systems. The aim of this paper is to study the effect of model error on the Kalman filter, in the context of linear wave propagation problems. A consistency result is proved when no model error is present, showing recovery of the true signal in the large data limit. This result, however, is not robust: it is also proved that arbitrarily small model error can lead to inconsistent recovery of the signal in the large data limit. If the model error is in the form of a constant shift to the velocity, the filtering and smoothing distributions only recover a partial Fourier expansion, a phenomenon related to aliasing. On the other hand, for a class of wave velocity model errors which are time dependent, it is possible to recover the filtering distribution exactly, but not the smoothing distribution. Numerical results are presented which corroborate the theory, and also propose a computational approach which overcomes the inconsistency in the presence of model error, by relaxing the model
Perfusion Quantification Using Gaussian Process Deconvolution
DEFF Research Database (Denmark)
Andersen, Irene Klærke; Have, Anna Szynkowiak; Rasmussen, Carl Edward
2002-01-01
The quantification of perfusion using dynamic susceptibility contrast MRI (DSC-MRI) requires deconvolution to obtain the residual impulse response function (IRF). In this work, a method using the Gaussian process for deconvolution (GPD) is proposed. The fact that the IRF is smooth is incorporated...
Partial Deconvolution with Inaccurate Blur Kernel.
Ren, Dongwei; Zuo, Wangmeng; Zhang, David; Xu, Jun; Zhang, Lei
2017-10-17
Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning-based models to suppress the adverse effect of kernel estimation error. Furthermore, an E-M algorithm is developed for estimating the partial map and recovering the latent sharp image alternatively. Experimental results show that our partial deconvolution model is effective in relieving artifacts caused by inaccurate blur kernel, and can achieve favorable deblurring quality on synthetic and real blurry images.Most non-blind deconvolution methods are developed under the error-free kernel assumption, and are not robust to inaccurate blur kernel. Unfortunately, despite the great progress in blind deconvolution, estimation error remains inevitable during blur kernel estimation. Consequently, severe artifacts such as ringing effects and distortions are likely to be introduced in the non-blind deconvolution stage. In this paper, we tackle this issue by suggesting: (i) a partial map in the Fourier domain for modeling kernel estimation error, and (ii) a partial deconvolution model for robust deblurring with inaccurate blur kernel. The partial map is constructed by detecting the reliable Fourier entries of estimated blur kernel. And partial deconvolution is applied to wavelet-based and learning
Oda, Hirokuni; Xuan, Chuang
2014-10-01
development of pass-through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long-core samples. The output of pass-through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor response. Although several studies could restore high-resolution paleomagnetic signal through deconvolution of pass-through measurement, difficulties in accurately measuring the magnetometer sensor response have hindered the application of deconvolution. We acquired reliable sensor response of an SRM at the Oregon State University based on repeated measurements of a precisely fabricated magnetic point source. In addition, we present an improved deconvolution algorithm based on Akaike's Bayesian Information Criterion (ABIC) minimization, incorporating new parameters to account for errors in sample measurement position and length. The new algorithm was tested using synthetic data constructed by convolving "true" paleomagnetic signal containing an "excursion" with the sensor response. Realistic noise was added to the synthetic measurement using Monte Carlo method based on measurement noise distribution acquired from 200 repeated measurements of a u-channel sample. Deconvolution of 1000 synthetic measurements with realistic noise closely resembles the "true" magnetization, and successfully restored fine-scale magnetization variations including the "excursion." Our analyses show that inaccuracy in sample measurement position and length significantly affects deconvolution estimation, and can be resolved using the new deconvolution algorithm. Optimized deconvolution of 20 repeated measurements of a u-channel sample yielded highly consistent deconvolution results and estimates of error in sample measurement position and length, demonstrating the reliability of the new deconvolution algorithm for real pass-through measurements.
Receiver function estimated by maximum entropy deconvolution
Institute of Scientific and Technical Information of China (English)
吴庆举; 田小波; 张乃铃; 李卫平; 曾融生
2003-01-01
Maximum entropy deconvolution is presented to estimate receiver function, with the maximum entropy as the rule to determine auto-correlation and cross-correlation functions. The Toeplitz equation and Levinson algorithm are used to calculate the iterative formula of error-predicting filter, and receiver function is then estimated. During extrapolation, reflective coefficient is always less than 1, which keeps maximum entropy deconvolution stable. The maximum entropy of the data outside window increases the resolution of receiver function. Both synthetic and real seismograms show that maximum entropy deconvolution is an effective method to measure receiver function in time-domain.
Deconvoluting double Doppler spectra
International Nuclear Information System (INIS)
Ho, K.F.; Beling, C.D.; Fung, S.; Chan, K.L.; Tang, H.W.
2001-01-01
The successful deconvolution of data from double Doppler broadening of annihilation radiation (D-DBAR) spectroscopy is a promising area of endeavour aimed at producing momentum distributions of a quality comparable to those of the angular correlation technique. The deconvolution procedure we test in the present study is the constrained generalized least square method. Trials with computer simulated DDBAR spectra are generated and deconvoluted in order to find the best form of regularizer and the regularization parameter. For these trials the Neumann (reflective) boundary condition is used to give a single matrix operation in Fourier space. Experimental D-DBAR spectra are also subject to the same type of deconvolution after having carried out a background subtraction and using a symmetrize resolution function obtained from an 85 Sr source with wide coincidence windows. (orig.)
Deconvolution of Positrons' Lifetime spectra
International Nuclear Information System (INIS)
Calderin Hidalgo, L.; Ortega Villafuerte, Y.
1996-01-01
In this paper, we explain the iterative method previously develop for the deconvolution of Doppler broadening spectra using the mathematical optimization theory. Also, we start the adaptation and application of this method to the deconvolution of positrons' lifetime annihilation spectra
Dreano, Denis; Tandeo, P.; Pulido, M.; Ait-El-Fquih, Boujemaa; Chonavel, T.; Hoteit, Ibrahim
2017-01-01
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended
Dreano, Denis
2017-04-05
Specification and tuning of errors from dynamical models are important issues in data assimilation. In this work, we propose an iterative expectation-maximisation (EM) algorithm to estimate the model error covariances using classical extended and ensemble versions of the Kalman smoother. We show that, for additive model errors, the estimate of the error covariance converges. We also investigate other forms of model error, such as parametric or multiplicative errors. We show that additive Gaussian model error is able to compensate for non additive sources of error in the algorithms we propose. We also demonstrate the limitations of the extended version of the algorithm and recommend the use of the more robust and flexible ensemble version. This article is a proof of concept of the methodology with the Lorenz-63 attractor. We developed an open-source Python library to enable future users to apply the algorithm to their own nonlinear dynamical models.
Deconvolution of neutron scattering data: a new computational approach
International Nuclear Information System (INIS)
Weese, J.; Hendricks, J.; Zorn, R.; Honerkamp, J.; Richter, D.
1996-01-01
In this paper we address the problem of reconstructing the scattering function S Q (E) from neutron spectroscopy data which represent a convolution of the former function with an instrument dependent resolution function. It is well known that this kind of deconvolution is an ill-posed problem. Therefore, we apply the Tikhonov regularization technique to get an estimate of S Q (E) from the data. Special features of the neutron spectroscopy data require modifications of the basic procedure, the most important one being a transformation to a non-linear problem. The method is tested by deconvolution of actual data from the IN6 time-of-flight spectrometer (resolution: 90 μeV) and simulated data. As a result the deconvolution is shown to be feasible down to an energy transfer of ∼100 μeV for this instrument without recognizable error and down to ∼20 μeV with 10% relative error. (orig.)
Deconvolution using a neural network
Energy Technology Data Exchange (ETDEWEB)
Lehman, S.K.
1990-11-15
Viewing one dimensional deconvolution as a matrix inversion problem, we compare a neural network backpropagation matrix inverse with LMS, and pseudo-inverse. This is a largely an exercise in understanding how our neural network code works. 1 ref.
Xuan, Chuang; Oda, Hirokuni
2015-11-01
The rapid accumulation of continuous paleomagnetic and rock magnetic records acquired from pass-through measurements on superconducting rock magnetometers (SRM) has greatly contributed to our understanding of the paleomagnetic field and paleo-environment. Pass-through measurements are inevitably smoothed and altered by the convolution effect of SRM sensor response, and deconvolution is needed to restore high-resolution paleomagnetic and environmental signals. Although various deconvolution algorithms have been developed, the lack of easy-to-use software has hindered the practical application of deconvolution. Here, we present standalone graphical software UDECON as a convenient tool to perform optimized deconvolution for pass-through paleomagnetic measurements using the algorithm recently developed by Oda and Xuan (Geochem Geophys Geosyst 15:3907-3924, 2014). With the preparation of a format file, UDECON can directly read pass-through paleomagnetic measurement files collected at different laboratories. After the SRM sensor response is determined and loaded to the software, optimized deconvolution can be conducted using two different approaches (i.e., "Grid search" and "Simplex method") with adjustable initial values or ranges for smoothness, corrections of sample length, and shifts in measurement position. UDECON provides a suite of tools to view conveniently and check various types of original measurement and deconvolution data. Multiple steps of measurement and/or deconvolution data can be compared simultaneously to check the consistency and to guide further deconvolution optimization. Deconvolved data together with the loaded original measurement and SRM sensor response data can be saved and reloaded for further treatment in UDECON. Users can also export the optimized deconvolution data to a text file for analysis in other software.
Bayesian Exponential Smoothing.
Forbes, C.S.; Snyder, R.D.; Shami, R.S.
2000-01-01
In this paper, a Bayesian version of the exponential smoothing method of forecasting is proposed. The approach is based on a state space model containing only a single source of error for each time interval. This model allows us to improve current practices surrounding exponential smoothing by providing both point predictions and measures of the uncertainty surrounding them.
Is deconvolution applicable to renography?
Kuyvenhoven, JD; Ham, H; Piepsz, A
The feasibility of deconvolution depends on many factors, but the technique cannot provide accurate results if the maximal transit time (MaxTT) is longer than the duration of the acquisition. This study evaluated whether, on the basis of a 20 min renogram, it is possible to predict in which cases
Convolution-deconvolution in DIGES
International Nuclear Information System (INIS)
Philippacopoulos, A.J.; Simos, N.
1995-01-01
Convolution and deconvolution operations is by all means a very important aspect of SSI analysis since it influences the input to the seismic analysis. This paper documents some of the convolution/deconvolution procedures which have been implemented into the DIGES code. The 1-D propagation of shear and dilatational waves in typical layered configurations involving a stack of layers overlying a rock is treated by DIGES in a similar fashion to that of available codes, e.g. CARES, SHAKE. For certain configurations, however, there is no need to perform such analyses since the corresponding solutions can be obtained in analytic form. Typical cases involve deposits which can be modeled by a uniform halfspace or simple layered halfspaces. For such cases DIGES uses closed-form solutions. These solutions are given for one as well as two dimensional deconvolution. The type of waves considered include P, SV and SH waves. The non-vertical incidence is given special attention since deconvolution can be defined differently depending on the problem of interest. For all wave cases considered, corresponding transfer functions are presented in closed-form. Transient solutions are obtained in the frequency domain. Finally, a variety of forms are considered for representing the free field motion both in terms of deterministic as well as probabilistic representations. These include (a) acceleration time histories, (b) response spectra (c) Fourier spectra and (d) cross-spectral densities
Deconvolution algorithms applied in ultrasonics
International Nuclear Information System (INIS)
Perrot, P.
1993-12-01
In a complete system of acquisition and processing of ultrasonic signals, it is often necessary at one stage to use some processing tools to get rid of the influence of the different elements of that system. By that means, the final quality of the signals in terms of resolution is improved. There are two main characteristics of ultrasonic signals which make this task difficult. Firstly, the signals generated by transducers are very often non-minimum phase. The classical deconvolution algorithms are unable to deal with such characteristics. Secondly, depending on the medium, the shape of the propagating pulse is evolving. The spatial invariance assumption often used in classical deconvolution algorithms is rarely valid. Many classical algorithms, parametric and non-parametric, have been investigated: the Wiener-type, the adaptive predictive techniques, the Oldenburg technique in the frequency domain, the minimum variance deconvolution. All the algorithms have been firstly tested on simulated data. One specific experimental set-up has also been analysed. Simulated and real data has been produced. This set-up demonstrated the interest in applying deconvolution, in terms of the achieved resolution. (author). 32 figs., 29 refs
Deconvolution using the complex cepstrum
Energy Technology Data Exchange (ETDEWEB)
Riley, H B
1980-12-01
The theory, description, and implementation of a generalized linear filtering system for the nonlinear filtering of convolved signals are presented. A detailed look at the problems and requirements associated with the deconvolution of signal components is undertaken. Related properties are also developed. A synthetic example is shown and is followed by an application using real seismic data. 29 figures.
Blind Deconvolution With Model Discrepancies
Czech Academy of Sciences Publication Activity Database
Kotera, Jan; Šmídl, Václav; Šroubek, Filip
2017-01-01
Roč. 26, č. 5 (2017), s. 2533-2544 ISSN 1057-7149 R&D Projects: GA ČR GA13-29225S; GA ČR GA15-16928S Institutional support: RVO:67985556 Keywords : blind deconvolution * variational Bayes * automatic relevance determination Subject RIV: JD - Computer Applications, Robotics OBOR OECD: Computer hardware and architecture Impact factor: 4.828, year: 2016 http://library.utia.cas.cz/separaty/2017/ZOI/kotera-0474858.pdf
Hybrid sparse blind deconvolution: an implementation of SOOT algorithm to real data
Pakmanesh, Parvaneh; Goudarzi, Alireza; Kourki, Meisam
2018-06-01
Getting information of seismic data depends on deconvolution as an important processing step; it provides the reflectivity series by signal compression. This compression can be obtained by removing the wavelet effects on the traces. The recently blind deconvolution has provided reliable performance for sparse signal recovery. In this study, two deconvolution methods have been implemented to the seismic data; the convolution of these methods provides a robust spiking deconvolution approach. This hybrid deconvolution is applied using the sparse deconvolution (MM algorithm) and the Smoothed-One-Over-Two algorithm (SOOT) in a chain. The MM algorithm is based on the minimization of the cost function defined by standards l1 and l2. After applying the two algorithms to the seismic data, the SOOT algorithm provided well-compressed data with a higher resolution than the MM algorithm. The SOOT algorithm requires initial values to be applied for real data, such as the wavelet coefficients and reflectivity series that can be achieved through the MM algorithm. The computational cost of the hybrid method is high, and it is necessary to be implemented on post-stack or pre-stack seismic data of complex structure regions.
A method of PSF generation for 3D brightfield deconvolution.
Tadrous, P J
2010-02-01
This paper addresses the problem of 3D deconvolution of through focus widefield microscope datasets (Z-stacks). One of the most difficult stages in brightfield deconvolution is finding the point spread function. A theoretically calculated point spread function (called a 'synthetic PSF' in this paper) requires foreknowledge of many system parameters and still gives only approximate results. A point spread function measured from a sub-resolution bead suffers from low signal-to-noise ratio, compounded in the brightfield setting (by contrast to fluorescence) by absorptive, refractive and dispersal effects. This paper describes a method of point spread function estimation based on measurements of a Z-stack through a thin sample. This Z-stack is deconvolved by an idealized point spread function derived from the same Z-stack to yield a point spread function of high signal-to-noise ratio that is also inherently tailored to the imaging system. The theory is validated by a practical experiment comparing the non-blind 3D deconvolution of the yeast Saccharomyces cerevisiae with the point spread function generated using the method presented in this paper (called the 'extracted PSF') to a synthetic point spread function. Restoration of both high- and low-contrast brightfield structures is achieved with fewer artefacts using the extracted point spread function obtained with this method. Furthermore the deconvolution progresses further (more iterations are allowed before the error function reaches its nadir) with the extracted point spread function compared to the synthetic point spread function indicating that the extracted point spread function is a better fit to the brightfield deconvolution model than the synthetic point spread function.
Machine Learning Approaches to Image Deconvolution
Schuler, Christian
2017-01-01
Image blur is a fundamental problem in both photography and scientific imaging. Even the most well-engineered optics are imperfect, and finite exposure times cause motion blur. To reconstruct the original sharp image, the field of image deconvolution tries to recover recorded photographs algorithmically. When the blur is known, this problem is called non-blind deconvolution. When the blur is unknown and has to be inferred from the observed image, it is called blind deconvolution. The key to r...
Automated processing for proton spectroscopic imaging using water reference deconvolution.
Maudsley, A A; Wu, Z; Meyerhoff, D J; Weiner, M W
1994-06-01
Automated formation of MR spectroscopic images (MRSI) is necessary before routine application of these methods is possible for in vivo studies; however, this task is complicated by the presence of spatially dependent instrumental distortions and the complex nature of the MR spectrum. A data processing method is presented for completely automated formation of in vivo proton spectroscopic images, and applied for analysis of human brain metabolites. This procedure uses the water reference deconvolution method (G. A. Morris, J. Magn. Reson. 80, 547(1988)) to correct for line shape distortions caused by instrumental and sample characteristics, followed by parametric spectral analysis. Results for automated image formation were found to compare favorably with operator dependent spectral integration methods. While the water reference deconvolution processing was found to provide good correction of spatially dependent resonance frequency shifts, it was found to be susceptible to errors for correction of line shape distortions. These occur due to differences between the water reference and the metabolite distributions.
Iterative choice of the optimal regularization parameter in TV image deconvolution
International Nuclear Information System (INIS)
Sixou, B; Toma, A; Peyrin, F; Denis, L
2013-01-01
We present an iterative method for choosing the optimal regularization parameter for the linear inverse problem of Total Variation image deconvolution. This approach is based on the Morozov discrepancy principle and on an exponential model function for the data term. The Total Variation image deconvolution is performed with the Alternating Direction Method of Multipliers (ADMM). With a smoothed l 2 norm, the differentiability of the value of the Lagrangian at the saddle point can be shown and an approximate model function obtained. The choice of the optimal parameter can be refined with a Newton method. The efficiency of the method is demonstrated on a blurred and noisy bone CT cross section
New Lagrange Multipliers for the Blind Adaptive Deconvolution Problem Applicable for the Noisy Case
Directory of Open Access Journals (Sweden)
Monika Pinchas
2016-02-01
Full Text Available Recently, a new blind adaptive deconvolution algorithm was proposed based on a new closed-form approximated expression for the conditional expectation (the expectation of the source input given the equalized or deconvolutional output where the output and input probability density function (pdf of the deconvolutional process were approximated with the maximum entropy density approximation technique. The Lagrange multipliers for the output pdf were set to those used for the input pdf. Although this new blind adaptive deconvolution method has been shown to have improved equalization performance compared to the maximum entropy blind adaptive deconvolution algorithm recently proposed by the same author, it is not applicable for the very noisy case. In this paper, we derive new Lagrange multipliers for the output and input pdfs, where the Lagrange multipliers related to the output pdf are a function of the channel noise power. Simulation results indicate that the newly obtained blind adaptive deconvolution algorithm using these new Lagrange multipliers is robust to signal-to-noise ratios (SNR, unlike the previously proposed method, and is applicable for the whole range of SNR down to 7 dB. In addition, we also obtain new closed-form approximated expressions for the conditional expectation and mean square error (MSE.
Streaming Multiframe Deconvolutions on GPUs
Lee, M. A.; Budavári, T.
2015-09-01
Atmospheric turbulence distorts all ground-based observations, which is especially detrimental to faint detections. The point spread function (PSF) defining this blur is unknown for each exposure and varies significantly over time, making image analysis difficult. Lucky imaging and traditional co-adding throws away lots of information. We developed blind deconvolution algorithms that can simultaneously obtain robust solutions for the background image and all the PSFs. It is done in a streaming setting, which makes it practical for large number of big images. We implemented a new tool that runs of GPUs and achieves exceptional running times that can scale to the new time-domain surveys. Our code can quickly and effectively recover high-resolution images exceeding the quality of traditional co-adds. We demonstrate the power of the method on the repeated exposures in the Sloan Digital Sky Survey's Stripe 82.
Sinha, Rajnikant
2014-01-01
This book offers an introduction to the theory of smooth manifolds, helping students to familiarize themselves with the tools they will need for mathematical research on smooth manifolds and differential geometry. The book primarily focuses on topics concerning differential manifolds, tangent spaces, multivariable differential calculus, topological properties of smooth manifolds, embedded submanifolds, Sard’s theorem and Whitney embedding theorem. It is clearly structured, amply illustrated and includes solved examples for all concepts discussed. Several difficult theorems have been broken into many lemmas and notes (equivalent to sub-lemmas) to enhance the readability of the book. Further, once a concept has been introduced, it reoccurs throughout the book to ensure comprehension. Rank theorem, a vital aspect of smooth manifolds theory, occurs in many manifestations, including rank theorem for Euclidean space and global rank theorem. Though primarily intended for graduate students of mathematics, the book ...
Parsimonious Charge Deconvolution for Native Mass Spectrometry
2018-01-01
Charge deconvolution infers the mass from mass over charge (m/z) measurements in electrospray ionization mass spectra. When applied over a wide input m/z or broad target mass range, charge-deconvolution algorithms can produce artifacts, such as false masses at one-half or one-third of the correct mass. Indeed, a maximum entropy term in the objective function of MaxEnt, the most commonly used charge deconvolution algorithm, favors a deconvolved spectrum with many peaks over one with fewer peaks. Here we describe a new “parsimonious” charge deconvolution algorithm that produces fewer artifacts. The algorithm is especially well-suited to high-resolution native mass spectrometry of intact glycoproteins and protein complexes. Deconvolution of native mass spectra poses special challenges due to salt and small molecule adducts, multimers, wide mass ranges, and fewer and lower charge states. We demonstrate the performance of the new deconvolution algorithm on a range of samples. On the heavily glycosylated plasma properdin glycoprotein, the new algorithm could deconvolve monomer and dimer simultaneously and, when focused on the m/z range of the monomer, gave accurate and interpretable masses for glycoforms that had previously been analyzed manually using m/z peaks rather than deconvolved masses. On therapeutic antibodies, the new algorithm facilitated the analysis of extensions, truncations, and Fab glycosylation. The algorithm facilitates the use of native mass spectrometry for the qualitative and quantitative analysis of protein and protein assemblies. PMID:29376659
Resolving deconvolution ambiguity in gene alternative splicing
Directory of Open Access Journals (Sweden)
Hubbell Earl
2009-08-01
Full Text Available Abstract Background For many gene structures it is impossible to resolve intensity data uniquely to establish abundances of splice variants. This was empirically noted by Wang et al. in which it was called a "degeneracy problem". The ambiguity results from an ill-posed problem where additional information is needed in order to obtain an unique answer in splice variant deconvolution. Results In this paper, we analyze the situations under which the problem occurs and perform a rigorous mathematical study which gives necessary and sufficient conditions on how many and what type of constraints are needed to resolve all ambiguity. This analysis is generally applicable to matrix models of splice variants. We explore the proposal that probe sequence information may provide sufficient additional constraints to resolve real-world instances. However, probe behavior cannot be predicted with sufficient accuracy by any existing probe sequence model, and so we present a Bayesian framework for estimating variant abundances by incorporating the prediction uncertainty from the micro-model of probe responsiveness into the macro-model of probe intensities. Conclusion The matrix analysis of constraints provides a tool for detecting real-world instances in which additional constraints may be necessary to resolve splice variants. While purely mathematical constraints can be stated without error, real-world constraints may themselves be poorly resolved. Our Bayesian framework provides a generic solution to the problem of uniquely estimating transcript abundances given additional constraints that themselves may be uncertain, such as regression fit to probe sequence models. We demonstrate the efficacy of it by extensive simulations as well as various biological data.
Deconvoluting preferences and errors: a model for binomial panel data
DEFF Research Database (Denmark)
Fosgerau, Mogens; Nielsen, Søren Feodor
2010-01-01
In many stated choice experiments researchers observe the random variables Vt, Xt, and Yt = 1{U + δxs22A4Xt + εt
Blind source deconvolution for deep Earth seismology
Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.
2007-12-01
We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.
Parallelization of a blind deconvolution algorithm
Matson, Charles L.; Borelli, Kathy J.
2006-09-01
Often it is of interest to deblur imagery in order to obtain higher-resolution images. Deblurring requires knowledge of the blurring function - information that is often not available separately from the blurred imagery. Blind deconvolution algorithms overcome this problem by jointly estimating both the high-resolution image and the blurring function from the blurred imagery. Because blind deconvolution algorithms are iterative in nature, they can take minutes to days to deblur an image depending how many frames of data are used for the deblurring and the platforms on which the algorithms are executed. Here we present our progress in parallelizing a blind deconvolution algorithm to increase its execution speed. This progress includes sub-frame parallelization and a code structure that is not specialized to a specific computer hardware architecture.
DEFF Research Database (Denmark)
Tummala, Sudhakar; Dam, Erik B.
2010-01-01
accuracy, such novel markers must therefore be validated against clinically meaningful end-goals such as the ability to allow correct diagnosis. We present a method for automatic cartilage surface smoothness quantification in the knee joint. The quantification is based on a curvature flow method used....... We demonstrate that the fully automatic markers eliminate the time required for radiologist annotations, and in addition provide a diagnostic marker superior to the evaluated semi-manual markers....
Histogram deconvolution - An aid to automated classifiers
Lorre, J. J.
1983-01-01
It is shown that N-dimensional histograms are convolved by the addition of noise in the picture domain. Three methods are described which provide the ability to deconvolve such noise-affected histograms. The purpose of the deconvolution is to provide automated classifiers with a higher quality N-dimensional histogram from which to obtain classification statistics.
Preliminary study of some problems in deconvolution
International Nuclear Information System (INIS)
Gilly, Louis; Garderet, Philippe; Lecomte, Alain; Max, Jacques
1975-07-01
After defining convolution operator, its physical meaning and principal properties are given. Several deconvolution methods are analysed: method of Fourier Transform and iterative numerical methods. Positivity of measured magnitude has been object of a new Yvon Biraud's method. Analytic prolongation of Fourier transform applied to unknow fonction, has been studied by M. Jean-Paul Sheidecker. An important bibliography is given [fr
Deconvolution of time series in the laboratory
John, Thomas; Pietschmann, Dirk; Becker, Volker; Wagner, Christian
2016-10-01
In this study, we present two practical applications of the deconvolution of time series in Fourier space. First, we reconstruct a filtered input signal of sound cards that has been heavily distorted by a built-in high-pass filter using a software approach. Using deconvolution, we can partially bypass the filter and extend the dynamic frequency range by two orders of magnitude. Second, we construct required input signals for a mechanical shaker in order to obtain arbitrary acceleration waveforms, referred to as feedforward control. For both situations, experimental and theoretical approaches are discussed to determine the system-dependent frequency response. Moreover, for the shaker, we propose a simple feedback loop as an extension to the feedforward control in order to handle nonlinearities of the system.
Simultaneous super-resolution and blind deconvolution
International Nuclear Information System (INIS)
Sroubek, F; Flusser, J; Cristobal, G
2008-01-01
In many real applications, blur in input low-resolution images is a nuisance, which prevents traditional super-resolution methods from working correctly. This paper presents a unifying approach to the blind deconvolution and superresolution problem of multiple degraded low-resolution frames of the original scene. We introduce a method which assumes no prior information about the shape of degradation blurs and which is properly defined for any rational (fractional) resolution factor. The method minimizes a regularized energy function with respect to the high-resolution image and blurs, where regularization is carried out in both the image and blur domains. The blur regularization is based on a generalized multichannel blind deconvolution constraint. Experiments on real data illustrate robustness and utilization of the method
Convex blind image deconvolution with inverse filtering
Lv, Xiao-Guang; Li, Fang; Zeng, Tieyong
2018-03-01
Blind image deconvolution is the process of estimating both the original image and the blur kernel from the degraded image with only partial or no information about degradation and the imaging system. It is a bilinear ill-posed inverse problem corresponding to the direct problem of convolution. Regularization methods are used to handle the ill-posedness of blind deconvolution and get meaningful solutions. In this paper, we investigate a convex regularized inverse filtering method for blind deconvolution of images. We assume that the support region of the blur object is known, as has been done in a few existing works. By studying the inverse filters of signal and image restoration problems, we observe the oscillation structure of the inverse filters. Inspired by the oscillation structure of the inverse filters, we propose to use the star norm to regularize the inverse filter. Meanwhile, we use the total variation to regularize the resulting image obtained by convolving the inverse filter with the degraded image. The proposed minimization model is shown to be convex. We employ the first-order primal-dual method for the solution of the proposed minimization model. Numerical examples for blind image restoration are given to show that the proposed method outperforms some existing methods in terms of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), visual quality and time consumption.
Constrained blind deconvolution using Wirtinger flow methods
Walk, Philipp; Jung, Peter; Hassibi, Babak
2017-01-01
In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial factorization. In particular this univariate case highly suffers from several non-trivial ambiguities and therefore blind deconvolution is known to be ill-posed in general. However, if additional autocorrelation information is available and the corresponding polynomials are co-prime, blind deconvolution is uniquely solvable up to global phase. Using lifting, the outer product of the unknown vectors is the solution to a (convex) semi-definite program (SDP) demonstrating that -theoretically- recovery is computationally tractable. However, for practical applications efficient algorithms are required which should operate in the original signal space. To this end we also discuss a gradient descent algorithm (Wirtinger flow) for the original non-convex problem. We demonstrate numerically that such an approach has performance comparable to the semidefinite program in the noisy case. Our work is motivated by applications in blind communication scenarios and we will discuss a specific signaling scheme where information is encoded into polynomial roots.
Constrained blind deconvolution using Wirtinger flow methods
Walk, Philipp
2017-09-04
In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial factorization. In particular this univariate case highly suffers from several non-trivial ambiguities and therefore blind deconvolution is known to be ill-posed in general. However, if additional autocorrelation information is available and the corresponding polynomials are co-prime, blind deconvolution is uniquely solvable up to global phase. Using lifting, the outer product of the unknown vectors is the solution to a (convex) semi-definite program (SDP) demonstrating that -theoretically- recovery is computationally tractable. However, for practical applications efficient algorithms are required which should operate in the original signal space. To this end we also discuss a gradient descent algorithm (Wirtinger flow) for the original non-convex problem. We demonstrate numerically that such an approach has performance comparable to the semidefinite program in the noisy case. Our work is motivated by applications in blind communication scenarios and we will discuss a specific signaling scheme where information is encoded into polynomial roots.
Deconvolution of the vestibular evoked myogenic potential.
Lütkenhöner, Bernd; Basel, Türker
2012-02-07
The vestibular evoked myogenic potential (VEMP) and the associated variance modulation can be understood by a convolution model. Two functions of time are incorporated into the model: the motor unit action potential (MUAP) of an average motor unit, and the temporal modulation of the MUAP rate of all contributing motor units, briefly called rate modulation. The latter is the function of interest, whereas the MUAP acts as a filter that distorts the information contained in the measured data. Here, it is shown how to recover the rate modulation by undoing the filtering using a deconvolution approach. The key aspects of our deconvolution algorithm are as follows: (1) the rate modulation is described in terms of just a few parameters; (2) the MUAP is calculated by Wiener deconvolution of the VEMP with the rate modulation; (3) the model parameters are optimized using a figure-of-merit function where the most important term quantifies the difference between measured and model-predicted variance modulation. The effectiveness of the algorithm is demonstrated with simulated data. An analysis of real data confirms the view that there are basically two components, which roughly correspond to the waves p13-n23 and n34-p44 of the VEMP. The rate modulation corresponding to the first, inhibitory component is much stronger than that corresponding to the second, excitatory component. But the latter is more extended so that the two modulations have almost the same equivalent rectangular duration. Copyright © 2011 Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Guvenis, A.; Koc, A.
2015-01-01
Positron emission tomography (PET) imaging has been proven to be useful in radiotherapy planning for the determination of the metabolically active regions of tumours. Delineation of tumours, however, is a difficult task in part due to high noise levels and the partial volume effects originating mainly from the low camera resolution. The goal of this work is to study the effect of blind deconvolution on tumour volume estimation accuracy for different computer-aided contouring methods. The blind deconvolution estimates the point spread function (PSF) of the imaging system in an iterative manner in a way that the likelihood of the given image being the convolution output is maximised. In this way, the PSF of the imaging system does not need to be known. Data were obtained from a NEMA NU-2 IQ-based phantom with a GE DSTE-16 PET/CT scanner. The artificial tumour diameters were 13, 17, 22, 28 and 37 mm with a target/background ratio of 4:1. The tumours were delineated before and after blind deconvolution. Student's two-tailed paired t-test showed a significant decrease in volume estimation error ( p < 0.001) when blind deconvolution was used in conjunction with computer-aided delineation methods. A manual delineation confirmation demonstrated an improvement from 26 to 16 % for the artificial tumour of size 37 mm while an improvement from 57 to 15 % was noted for the small tumour of 13 mm. Therefore, it can be concluded that blind deconvolution of reconstructed PET images may be used to increase tumour delineation accuracy. (authors)
Quantitative fluorescence microscopy and image deconvolution.
Swedlow, Jason R
2013-01-01
Quantitative imaging and image deconvolution have become standard techniques for the modern cell biologist because they can form the basis of an increasing number of assays for molecular function in a cellular context. There are two major types of deconvolution approaches--deblurring and restoration algorithms. Deblurring algorithms remove blur but treat a series of optical sections as individual two-dimensional entities and therefore sometimes mishandle blurred light. Restoration algorithms determine an object that, when convolved with the point-spread function of the microscope, could produce the image data. The advantages and disadvantages of these methods are discussed in this chapter. Image deconvolution in fluorescence microscopy has usually been applied to high-resolution imaging to improve contrast and thus detect small, dim objects that might otherwise be obscured. Their proper use demands some consideration of the imaging hardware, the acquisition process, fundamental aspects of photon detection, and image processing. This can prove daunting for some cell biologists, but the power of these techniques has been proven many times in the works cited in the chapter and elsewhere. Their usage is now well defined, so they can be incorporated into the capabilities of most laboratories. A major application of fluorescence microscopy is the quantitative measurement of the localization, dynamics, and interactions of cellular factors. The introduction of green fluorescent protein and its spectral variants has led to a significant increase in the use of fluorescence microscopy as a quantitative assay system. For quantitative imaging assays, it is critical to consider the nature of the image-acquisition system and to validate its response to known standards. Any image-processing algorithms used before quantitative analysis should preserve the relative signal levels in different parts of the image. A very common image-processing algorithm, image deconvolution, is used
International Nuclear Information System (INIS)
Guo Weijun; Gardner, Robin P.; Mayo, Charles W.
2005-01-01
Two new real-time approaches have been developed and compared to the least-squares fit approach for the deconvolution of experimental waveforms with pile-up pulses. The single pulse shape chosen is typical for scintillators such as LSO and NaI(Tl). Simulated waveforms with pulse pile up were also generated and deconvolved to compare these three different approaches under cases where the single pulse component has a constant shape and the digitization error dominates. The effects of temporal separation and amplitude ratio between pile-up component pulses were also investigated and statistical tests were applied to quantify the consistency of deconvolution results for each case. Monte Carlo simulation demonstrated that applications of these pile-up deconvolution techniques to radiation spectroscopy are effective in extending the counting-rate range while preserving energy resolution for scintillation detectors
Energy Technology Data Exchange (ETDEWEB)
Perrot, P
1993-12-01
In a complete system of acquisition and processing of ultrasonic signals, it is often necessary at one stage to use some processing tools to get rid of the influence of the different elements of that system. By that means, the final quality of the signals in terms of resolution is improved. There are two main characteristics of ultrasonic signals which make this task difficult. Firstly, the signals generated by transducers are very often non-minimum phase. The classical deconvolution algorithms are unable to deal with such characteristics. Secondly, depending on the medium, the shape of the propagating pulse is evolving. The spatial invariance assumption often used in classical deconvolution algorithms is rarely valid. Many classical algorithms, parametric and non-parametric, have been investigated: the Wiener-type, the adaptive predictive techniques, the Oldenburg technique in the frequency domain, the minimum variance deconvolution. All the algorithms have been firstly tested on simulated data. One specific experimental set-up has also been analysed. Simulated and real data has been produced. This set-up demonstrated the interest in applying deconvolution, in terms of the achieved resolution. (author). 32 figs., 29 refs.
Constrained variable projection method for blind deconvolution
International Nuclear Information System (INIS)
Cornelio, A; Piccolomini, E Loli; Nagy, J G
2012-01-01
This paper is focused on the solution of the blind deconvolution problem, here modeled as a separable nonlinear least squares problem. The well known ill-posedness, both on recovering the blurring operator and the true image, makes the problem really difficult to handle. We show that, by imposing appropriate constraints on the variables and with well chosen regularization parameters, it is possible to obtain an objective function that is fairly well behaved. Hence, the resulting nonlinear minimization problem can be effectively solved by classical methods, such as the Gauss-Newton algorithm.
Blind image deconvolution methods and convergence
Chaudhuri, Subhasis; Rameshan, Renu
2014-01-01
Blind deconvolution is a classical image processing problem which has been investigated by a large number of researchers over the last four decades. The purpose of this monograph is not to propose yet another method for blind image restoration. Rather the basic issue of deconvolvability has been explored from a theoretical view point. Some authors claim very good results while quite a few claim that blind restoration does not work. The authors clearly detail when such methods are expected to work and when they will not. In order to avoid the assumptions needed for convergence analysis in the
Comparison of Deconvolution Filters for Photoacoustic Tomography.
Directory of Open Access Journals (Sweden)
Dominique Van de Sompel
Full Text Available In this work, we compare the merits of three temporal data deconvolution methods for use in the filtered backprojection algorithm for photoacoustic tomography (PAT. We evaluate the standard Fourier division technique, the Wiener deconvolution filter, and a Tikhonov L-2 norm regularized matrix inversion method. Our experiments were carried out on subjects of various appearances, namely a pencil lead, two man-made phantoms, an in vivo subcutaneous mouse tumor model, and a perfused and excised mouse brain. All subjects were scanned using an imaging system with a rotatable hemispherical bowl, into which 128 ultrasound transducer elements were embedded in a spiral pattern. We characterized the frequency response of each deconvolution method, compared the final image quality achieved by each deconvolution technique, and evaluated each method's robustness to noise. The frequency response was quantified by measuring the accuracy with which each filter recovered the ideal flat frequency spectrum of an experimentally measured impulse response. Image quality under the various scenarios was quantified by computing noise versus resolution curves for a point source phantom, as well as the full width at half maximum (FWHM and contrast-to-noise ratio (CNR of selected image features such as dots and linear structures in additional imaging subjects. It was found that the Tikhonov filter yielded the most accurate balance of lower and higher frequency content (as measured by comparing the spectra of deconvolved impulse response signals to the ideal flat frequency spectrum, achieved a competitive image resolution and contrast-to-noise ratio, and yielded the greatest robustness to noise. While the Wiener filter achieved a similar image resolution, it tended to underrepresent the lower frequency content of the deconvolved signals, and hence of the reconstructed images after backprojection. In addition, its robustness to noise was poorer than that of the Tikhonov
Smooth Phase Interpolated Keying
Borah, Deva K.
2007-01-01
Smooth phase interpolated keying (SPIK) is an improved method of computing smooth phase-modulation waveforms for radio communication systems that convey digital information. SPIK is applicable to a variety of phase-shift-keying (PSK) modulation schemes, including quaternary PSK (QPSK), octonary PSK (8PSK), and 16PSK. In comparison with a related prior method, SPIK offers advantages of better performance and less complexity of implementation. In a PSK scheme, the underlying information waveform that one seeks to convey consists of discrete rectangular steps, but the spectral width of such a waveform is excessive for practical radio communication. Therefore, the problem is to smooth the step phase waveform in such a manner as to maintain power and bandwidth efficiency without incurring an unacceptably large error rate and without introducing undesired variations in the amplitude of the affected radio signal. Although the ideal constellation of PSK phasor points does not cause amplitude variations, filtering of the modulation waveform (in which, typically, a rectangular pulse is converted to a square-root raised cosine pulse) causes amplitude fluctuations. If a power-efficient nonlinear amplifier is used in the radio communication system, the fluctuating-amplitude signal can undergo significant spectral regrowth, thus compromising the bandwidth efficiency of the system. In the related prior method, one seeks to solve the problem in a procedure that comprises two major steps: phase-value generation and phase interpolation. SPIK follows the two-step approach of the related prior method, but the details of the steps are different. In the phase-value-generation step, the phase values of symbols in the PSK constellation are determined by a phase function that is said to be maximally smooth and that is chosen to minimize the spectral spread of the modulated signal. In this step, the constellation is divided into two groups by assigning, to information symbols, phase values
Maximum entropy deconvolution of low count nuclear medicine images
International Nuclear Information System (INIS)
McGrath, D.M.
1998-12-01
Maximum entropy is applied to the problem of deconvolving nuclear medicine images, with special consideration for very low count data. The physics of the formation of scintigraphic images is described, illustrating the phenomena which degrade planar estimates of the tracer distribution. Various techniques which are used to restore these images are reviewed, outlining the relative merits of each. The development and theoretical justification of maximum entropy as an image processing technique is discussed. Maximum entropy is then applied to the problem of planar deconvolution, highlighting the question of the choice of error parameters for low count data. A novel iterative version of the algorithm is suggested which allows the errors to be estimated from the predicted Poisson mean values. This method is shown to produce the exact results predicted by combining Poisson statistics and a Bayesian interpretation of the maximum entropy approach. A facility for total count preservation has also been incorporated, leading to improved quantification. In order to evaluate this iterative maximum entropy technique, two comparable methods, Wiener filtering and a novel Bayesian maximum likelihood expectation maximisation technique, were implemented. The comparison of results obtained indicated that this maximum entropy approach may produce equivalent or better measures of image quality than the compared methods, depending upon the accuracy of the system model used. The novel Bayesian maximum likelihood expectation maximisation technique was shown to be preferable over many existing maximum a posteriori methods due to its simplicity of implementation. A single parameter is required to define the Bayesian prior, which suppresses noise in the solution and may reduce the processing time substantially. Finally, maximum entropy deconvolution was applied as a pre-processing step in single photon emission computed tomography reconstruction of low count data. Higher contrast results were
Data-driven efficient score tests for deconvolution hypotheses
Langovoy, M.
2008-01-01
We consider testing statistical hypotheses about densities of signals in deconvolution models. A new approach to this problem is proposed. We constructed score tests for the deconvolution density testing with the known noise density and efficient score tests for the case of unknown density. The
Improving the efficiency of deconvolution algorithms for sound source localization
DEFF Research Database (Denmark)
Lylloff, Oliver Ackermann; Fernandez Grande, Efren; Agerkvist, Finn T.
2015-01-01
of the unknown acoustic source distribution and the beamformer's response to a point source, i.e., point-spread function. A significant limitation of deconvolution is, however, an additional computational effort compared to beamforming. In this paper, computationally efficient deconvolution algorithms...
Advanced Source Deconvolution Methods for Compton Telescopes
Zoglauer, Andreas
The next generation of space telescopes utilizing Compton scattering for astrophysical observations is destined to one day unravel the mysteries behind Galactic nucleosynthesis, to determine the origin of the positron annihilation excess near the Galactic center, and to uncover the hidden emission mechanisms behind gamma-ray bursts. Besides astrophysics, Compton telescopes are establishing themselves in heliophysics, planetary sciences, medical imaging, accelerator physics, and environmental monitoring. Since the COMPTEL days, great advances in the achievable energy and position resolution were possible, creating an extremely vast, but also extremely sparsely sampled data space. Unfortunately, the optimum way to analyze the data from the next generation of Compton telescopes has not yet been found, which can retrieve all source parameters (location, spectrum, polarization, flux) and achieves the best possible resolution and sensitivity at the same time. This is especially important for all sciences objectives looking at the inner Galaxy: the large amount of expected sources, the high background (internal and Galactic diffuse emission), and the limited angular resolution, make it the most taxing case for data analysis. In general, two key challenges exist: First, what are the best data space representations to answer the specific science questions? Second, what is the best way to deconvolve the data to fully retrieve the source parameters? For modern Compton telescopes, the existing data space representations can either correctly reconstruct the absolute flux (binned mode) or achieve the best possible resolution (list-mode), both together were not possible up to now. Here we propose to develop a two-stage hybrid reconstruction method which combines the best aspects of both. Using a proof-of-concept implementation we can for the first time show that it is possible to alternate during each deconvolution step between a binned-mode approach to get the flux right and a
Faber, T. L.; Raghunath, N.; Tudorascu, D.; Votaw, J. R.
2009-02-01
Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.
Energy Technology Data Exchange (ETDEWEB)
Faber, T L; Raghunath, N; Tudorascu, D; Votaw, J R [Department of Radiology, Emory University Hospital, 1364 Clifton Road, N.E. Atlanta, GA 30322 (United States)], E-mail: tfaber@emory.edu
2009-02-07
Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. Existing correction methods that use known patient motion obtained from tracking devices either require multi-frame acquisitions, detailed knowledge of the scanner, or specialized reconstruction algorithms. A deconvolution algorithm has been developed that alleviates these drawbacks by using the reconstructed image to estimate the original non-blurred image using maximum likelihood estimation maximization (MLEM) techniques. A high-resolution digital phantom was created by shape-based interpolation of the digital Hoffman brain phantom. Three different sets of 20 movements were applied to the phantom. For each frame of the motion, sinograms with attenuation and three levels of noise were simulated and then reconstructed using filtered backprojection. The average of the 20 frames was considered the motion blurred image, which was restored with the deconvolution algorithm. After correction, contrast increased from a mean of 2.0, 1.8 and 1.4 in the motion blurred images, for the three increasing amounts of movement, to a mean of 2.5, 2.4 and 2.2. Mean error was reduced by an average of 55% with motion correction. In conclusion, deconvolution can be used for correction of motion blur when subject motion is known.
Deconvolution of Complex 1D NMR Spectra Using Objective Model Selection.
Directory of Open Access Journals (Sweden)
Travis S Hughes
Full Text Available Fluorine (19F NMR has emerged as a useful tool for characterization of slow dynamics in 19F-labeled proteins. One-dimensional (1D 19F NMR spectra of proteins can be broad, irregular and complex, due to exchange of probe nuclei between distinct electrostatic environments; and therefore cannot be deconvoluted and analyzed in an objective way using currently available software. We have developed a Python-based deconvolution program, decon1d, which uses Bayesian information criteria (BIC to objectively determine which model (number of peaks would most likely produce the experimentally obtained data. The method also allows for fitting of intermediate exchange spectra, which is not supported by current software in the absence of a specific kinetic model. In current methods, determination of the deconvolution model best supported by the data is done manually through comparison of residual error values, which can be time consuming and requires model selection by the user. In contrast, the BIC method used by decond1d provides a quantitative method for model comparison that penalizes for model complexity helping to prevent over-fitting of the data and allows identification of the most parsimonious model. The decon1d program is freely available as a downloadable Python script at the project website (https://github.com/hughests/decon1d/.
Ensemble Kalman filtering with one-step-ahead smoothing
Raboudi, Naila F.; Ait-El-Fquih, Boujemaa; Hoteit, Ibrahim
2018-01-01
error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance
Fang, Ruogu; Chen, Tsuhan; Sanelli, Pina C.
2014-01-01
Computed tomography perfusion (CTP) is an important functional imaging modality in the evaluation of cerebrovascular diseases, particularly in acute stroke and vasospasm. However, the post-processed parametric maps of blood flow tend to be noisy, especially in low-dose CTP, due to the noisy contrast enhancement profile and the oscillatory nature of the results generated by the current computational methods. In this paper, we propose a robust sparse perfusion deconvolution method (SPD) to estimate cerebral blood flow in CTP performed at low radiation dose. We first build a dictionary from high-dose perfusion maps using online dictionary learning and then perform deconvolution-based hemodynamic parameters estimation on the low-dose CTP data. Our method is validated on clinical data of patients with normal and pathological CBF maps. The results show that we achieve superior performance than existing methods, and potentially improve the differentiation between normal and ischemic tissue in the brain. PMID:23542422
A comparison of deconvolution and the Rutland-Patlak plot in parenchymal renal uptake rate.
Al-Shakhrah, Issa A
2012-07-01
Deconvolution and the Rutland-Patlak (R-P) plot are two of the most commonly used methods for analyzing dynamic radionuclide renography. Both methods allow estimation of absolute and relative renal uptake of radiopharmaceutical and of its rate of transit through the kidney. Seventeen patients (32 kidneys) were referred for further evaluation by renal scanning. All patients were positioned supine with their backs to the scintillation gamma camera, so that the kidneys and the heart are both in the field of view. Approximately 5-7 mCi of (99m)Tc-DTPA (diethylinetriamine penta-acetic acid) in about 0.5 ml of saline is injected intravenously and sequential 20 s frames were acquired, the study on each patient lasts for approximately 20 min. The time-activity curves of the parenchymal region of interest of each kidney, as well as the heart were obtained for analysis. The data were then analyzed with deconvolution and the R-P plot. A strong positive association (n = 32; r = 0.83; R (2) = 0.68) was found between the values that obtained by applying the two methods. Bland-Altman statistical analysis demonstrated that ninety seven percent of the values in the study (31 cases from 32 cases, 97% of the cases) were within limits of agreement (mean ± 1.96 standard deviation). We believe that R-P analysis method is expected to be more reproducible than iterative deconvolution method, because the deconvolution technique (the iterative method) relies heavily on the accuracy of the first point analyzed, as any errors are carried forward into the calculations of all the subsequent points, whereas R-P technique is based on an initial analysis of the data by means of the R-P plot, and it can be considered as an alternative technique to find and calculate the renal uptake rate.
Pixel-by-pixel mean transit time without deconvolution.
Dobbeleir, Andre A; Piepsz, Amy; Ham, Hamphrey R
2008-04-01
Mean transit time (MTT) within a kidney is given by the integral of the renal activity on a well-corrected renogram between time zero and time t divided by the integral of the plasma activity between zero and t, providing that t is close to infinity. However, as the data acquisition of a renogram is finite, the MTT calculated using this approach might result in the underestimation of the true MTT. To evaluate the degree of this underestimation we conducted a simulation study. One thousand renograms were created by convoluting various plasma curves obtained from patients with different renal clearance levels with simulated retentions curves having different shapes and mean transit times. For a 20 min renogram, the calculated MTT started to underestimate the MTT when the MTT was higher than 6 min. The longer the MTT, the greater was the underestimation. Up to a MTT value of 6 min, the error on the MTT estimation is negligible. As normal cortical transit is less than 2 min, this approach is used for patients to calculate pixel-to-pixel cortical mean transit time and to create a MTT parametric image without deconvolution.
Solving a Deconvolution Problem in Photon Spectrometry
Aleksandrov, D; Hille, P T; Polichtchouk, B; Kharlov, Y; Sukhorukov, M; Wang, D; Shabratova, G; Demanov, V; Wang, Y; Tveter, T; Faltys, M; Mao, Y; Larsen, D T; Zaporozhets, S; Sibiryak, I; Lovhoiden, G; Potcheptsov, T; Kucheryaev, Y; Basmanov, V; Mares, J; Yanovsky, V; Qvigstad, H; Zenin, A; Nikolaev, S; Siemiarczuk, T; Yuan, X; Cai, X; Redlich, K; Pavlinov, A; Roehrich, D; Manko, V; Deloff, A; Ma, K; Maruyama, Y; Dobrowolski, T; Shigaki, K; Nikulin, S; Wan, R; Mizoguchi, K; Petrov, V; Mueller, H; Ippolitov, M; Liu, L; Sadovsky, S; Stolpovsky, P; Kurashvili, P; Nomokonov, P; Xu, C; Torii, H; Il'kaev, R; Zhang, X; Peresunko, D; Soloviev, A; Vodopyanov, A; Sugitate, T; Ullaland, K; Huang, M; Zhou, D; Nystrand, J; Punin, V; Yin, Z; Batyunya, B; Karadzhev, K; Nazarov, G; Fil'chagin, S; Nazarenko, S; Buskenes, J I; Horaguchi, T; Djuvsland, O; Chuman, F; Senko, V; Alme, J; Wilk, G; Fehlker, D; Vinogradov, Y; Budilov, V; Iwasaki, T; Ilkiv, I; Budnikov, D; Vinogradov, A; Kazantsev, A; Bogolyubsky, M; Lindal, S; Polak, K; Skaali, B; Mamonov, A; Kuryakin, A; Wikne, J; Skjerdal, K
2010-01-01
We solve numerically a deconvolution problem to extract the undisturbed spectrum from the measured distribution contaminated by the finite resolution of the measuring device. A problem of this kind emerges when one wants to infer the momentum distribution of the neutral pions by detecting the it decay photons using the photon spectrometer of the ALICE LHC experiment at CERN {[}1]. The underlying integral equation connecting the sought for pion spectrum and the measured gamma spectrum has been discretized and subsequently reduced to a system of linear algebraic equations. The latter system, however, is known to be ill-posed and must be regularized to obtain a stable solution. This task has been accomplished here by means of the Tikhonov regularization scheme combined with the L-curve method. The resulting pion spectrum is in an excellent quantitative agreement with the pion spectrum obtained from a Monte Carlo simulation. (C) 2010 Elsevier B.V. All rights reserved.
The discrete Kalman filtering approach for seismic signals deconvolution
International Nuclear Information System (INIS)
Kurniadi, Rizal; Nurhandoko, Bagus Endar B.
2012-01-01
Seismic signals are a convolution of reflectivity and seismic wavelet. One of the most important stages in seismic data processing is deconvolution process; the process of deconvolution is inverse filters based on Wiener filter theory. This theory is limited by certain modelling assumptions, which may not always valid. The discrete form of the Kalman filter is then used to generate an estimate of the reflectivity function. The main advantage of Kalman filtering is capability of technique to handling continually time varying models and has high resolution capabilities. In this work, we use discrete Kalman filter that it was combined with primitive deconvolution. Filtering process works on reflectivity function, hence the work flow of filtering is started with primitive deconvolution using inverse of wavelet. The seismic signals then are obtained by convoluting of filtered reflectivity function with energy waveform which is referred to as the seismic wavelet. The higher frequency of wavelet gives smaller wave length, the graphs of these results are presented.
Z-transform Zeros in Mixed Phase Deconvolution of Speech
DEFF Research Database (Denmark)
Pedersen, Christian Fischer
2013-01-01
The present thesis addresses mixed phase deconvolution of speech by z-transform zeros. This includes investigations into stability, accuracy, and time complexity of a numerical bijection between time domain and the domain of z-transform zeros. Z-transform factorization is by no means esoteric......, but employing zeros of the z-transform (ZZT) as a signal representation, analysis, and processing domain per se, is only scarcely researched. A notable property of this domain is the translation of time domain convolution into union of sets; thus, the ZZT domain is appropriate for convolving and deconvolving...... discrimination achieves mixed phase deconvolution and equivalates complex cepstrum based deconvolution by causality, which has lower time and space complexities as demonstrated. However, deconvolution by ZZT prevents phase wrapping. Existence and persistence of ZZT domain immiscibility of the opening and closing...
Radial smoothing and closed orbit
International Nuclear Information System (INIS)
Burnod, L.; Cornacchia, M.; Wilson, E.
1983-11-01
A complete simulation leading to a description of one of the error curves must involve four phases: (1) random drawing of the six set-up points within a normal population having a standard deviation of 1.3 mm; (b) random drawing of the six vertices of the curve in the sextant mode within a normal population having a standard deviation of 1.2 mm. These vertices are to be set with respect to the axis of the error lunes, while this axis has as its origins the positions defined by the preceding drawing; (c) mathematical definition of six parabolic curves and their junctions. These latter may be curves with very slight curvatures, or segments of a straight line passing through the set-up point and having lengths no longer than one LSS. Thus one gets a mean curve for the absolute errors; (d) plotting of the actually observed radial positions with respect to the mean curve (results of smoothing)
Genomics assisted ancestry deconvolution in grape.
Directory of Open Access Journals (Sweden)
Jason Sawler
Full Text Available The genus Vitis (the grapevine is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world's most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs. We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars.
Mammographic image restoration using maximum entropy deconvolution
International Nuclear Information System (INIS)
Jannetta, A; Jackson, J C; Kotre, C J; Birch, I P; Robson, K J; Padgett, R
2004-01-01
An image restoration approach based on a Bayesian maximum entropy method (MEM) has been applied to a radiological image deconvolution problem, that of reduction of geometric blurring in magnification mammography. The aim of the work is to demonstrate an improvement in image spatial resolution in realistic noisy radiological images with no associated penalty in terms of reduction in the signal-to-noise ratio perceived by the observer. Images of the TORMAM mammographic image quality phantom were recorded using the standard magnification settings of 1.8 magnification/fine focus and also at 1.8 magnification/broad focus and 3.0 magnification/fine focus; the latter two arrangements would normally give rise to unacceptable geometric blurring. Measured point-spread functions were used in conjunction with the MEM image processing to de-blur these images. The results are presented as comparative images of phantom test features and as observer scores for the raw and processed images. Visualization of high resolution features and the total image scores for the test phantom were improved by the application of the MEM processing. It is argued that this successful demonstration of image de-blurring in noisy radiological images offers the possibility of weakening the link between focal spot size and geometric blurring in radiology, thus opening up new approaches to system optimization
Genomics Assisted Ancestry Deconvolution in Grape
Sawler, Jason; Reisch, Bruce; Aradhya, Mallikarjuna K.; Prins, Bernard; Zhong, Gan-Yuan; Schwaninger, Heidi; Simon, Charles; Buckler, Edward; Myles, Sean
2013-01-01
The genus Vitis (the grapevine) is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world’s most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA) based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs). We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars. PMID:24244717
X-ray scatter removal by deconvolution
International Nuclear Information System (INIS)
Seibert, J.A.; Boone, J.M.
1988-01-01
The distribution of scattered x rays detected in a two-dimensional projection radiograph at diagnostic x-ray energies is measured as a function of field size and object thickness at a fixed x-ray potential and air gap. An image intensifier-TV based imaging system is used for image acquisition, manipulation, and analysis. A scatter point spread function (PSF) with an assumed linear, spatially invariant response is modeled as a modified Gaussian distribution, and is characterized by two parameters describing the width of the distribution and the fraction of scattered events detected. The PSF parameters are determined from analysis of images obtained with radio-opaque lead disks centrally placed on the source side of a homogeneous phantom. Analytical methods are used to convert the PSF into the frequency domain. Numerical inversion provides an inverse filter that operates on frequency transformed, scatter degraded images. Resultant inverse transformed images demonstrate the nonarbitrary removal of scatter, increased radiographic contrast, and improved quantitative accuracy. The use of the deconvolution method appears to be clinically applicable to a variety of digital projection images
Impact of spectral smoothing on gamma radiation portal alarm probabilities
International Nuclear Information System (INIS)
Burr, T.; Hamada, M.; Hengartner, N.
2011-01-01
Gamma detector counts are included in radiation portal monitors (RPM) to screen for illicit nuclear material. Gamma counts are sometimes smoothed to reduce variance in the estimated underlying true mean count rate, which is the 'signal' in our context. Smoothing reduces total error variance in the estimated signal if the bias that smoothing introduces is more than offset by the variance reduction. An empirical RPM study for vehicle screening applications is presented for unsmoothed and smoothed gamma counts in low-resolution plastic scintillator detectors and in medium-resolution NaI detectors. - Highlights: → We evaluate options for smoothing counts from gamma detectors deployed for portal monitoring. → A new multiplicative bias correction (MBC) is shown to reduce bias in peak and valley regions. → Performance is measured using mean squared error and detection probabilities for sources. → Smoothing with the MBC improves detection probabilities and the mean squared error.
Use of new spectral analysis methods in gamma spectra deconvolution
International Nuclear Information System (INIS)
Pinault, J.L.
1991-01-01
A general deconvolution method applicable to X and gamma ray spectrometry is proposed. Using new spectral analysis methods, it is applied to an actual case: the accurate on-line analysis of three elements (Ca, Si, Fe) in a cement plant using neutron capture gamma rays. Neutrons are provided by a low activity (5 μg) 252 Cf source; the detector is a BGO 3 in.x8 in. scintillator. The principle of the methods rests on the Fourier transform of the spectrum. The search for peaks and determination of peak areas are worked out in the Fourier representation, which enables separation of background and peaks and very efficiently discriminates peaks, or elements represented by several peaks. First the spectrum is transformed so that in the new representation the full width at half maximum (FWHM) is independent of energy. Thus, the spectrum is arranged symmetrically and transformed into the Fourier representation. The latter is multiplied by a function in order to transform original Gaussian into Lorentzian peaks. An autoregressive filter is calculated, leading to a characteristic polynomial whose complex roots represent both the location and the width of each peak, provided that the absolute value is lower than unit. The amplitude of each component (the area of each peak or the sum of areas of peaks characterizing an element) is fitted by the weighted least squares method, taking into account that errors in spectra are independent and follow a Poisson law. Very accurate results are obtained, which would be hard to achieve by other methods. The DECO FORTRAN code has been developed for compatible PC microcomputers. Some features of the code are given. (orig.)
Full cycle rapid scan EPR deconvolution algorithm.
Tseytlin, Mark
2017-08-01
Rapid scan electron paramagnetic resonance (RS EPR) is a continuous-wave (CW) method that combines narrowband excitation and broadband detection. Sinusoidal magnetic field scans that span the entire EPR spectrum cause electron spin excitations twice during the scan period. Periodic transient RS signals are digitized and time-averaged. Deconvolution of absorption spectrum from the measured full-cycle signal is an ill-posed problem that does not have a stable solution because the magnetic field passes the same EPR line twice per sinusoidal scan during up- and down-field passages. As a result, RS signals consist of two contributions that need to be separated and postprocessed individually. Deconvolution of either of the contributions is a well-posed problem that has a stable solution. The current version of the RS EPR algorithm solves the separation problem by cutting the full-scan signal into two half-period pieces. This imposes a constraint on the experiment; the EPR signal must completely decay by the end of each half-scan in order to not be truncated. The constraint limits the maximum scan frequency and, therefore, the RS signal-to-noise gain. Faster scans permit the use of higher excitation powers without saturating the spin system, translating into a higher EPR sensitivity. A stable, full-scan algorithm is described in this paper that does not require truncation of the periodic response. This algorithm utilizes the additive property of linear systems: the response to a sum of two inputs is equal the sum of responses to each of the inputs separately. Based on this property, the mathematical model for CW RS EPR can be replaced by that of a sum of two independent full-cycle pulsed field-modulated experiments. In each of these experiments, the excitation power equals to zero during either up- or down-field scan. The full-cycle algorithm permits approaching the upper theoretical scan frequency limit; the transient spin system response must decay within the scan
Scalar flux modeling in turbulent flames using iterative deconvolution
Nikolaou, Z. M.; Cant, R. S.; Vervisch, L.
2018-04-01
In the context of large eddy simulations, deconvolution is an attractive alternative for modeling the unclosed terms appearing in the filtered governing equations. Such methods have been used in a number of studies for non-reacting and incompressible flows; however, their application in reacting flows is limited in comparison. Deconvolution methods originate from clearly defined operations, and in theory they can be used in order to model any unclosed term in the filtered equations including the scalar flux. In this study, an iterative deconvolution algorithm is used in order to provide a closure for the scalar flux term in a turbulent premixed flame by explicitly filtering the deconvoluted fields. The assessment of the method is conducted a priori using a three-dimensional direct numerical simulation database of a turbulent freely propagating premixed flame in a canonical configuration. In contrast to most classical a priori studies, the assessment is more stringent as it is performed on a much coarser mesh which is constructed using the filtered fields as obtained from the direct simulations. For the conditions tested in this study, deconvolution is found to provide good estimates both of the scalar flux and of its divergence.
Evaluation of deconvolution modelling applied to numerical combustion
Mehl, Cédric; Idier, Jérôme; Fiorina, Benoît
2018-01-01
A possible modelling approach in the large eddy simulation (LES) of reactive flows is to deconvolve resolved scalars. Indeed, by inverting the LES filter, scalars such as mass fractions are reconstructed. This information can be used to close budget terms of filtered species balance equations, such as the filtered reaction rate. Being ill-posed in the mathematical sense, the problem is very sensitive to any numerical perturbation. The objective of the present study is to assess the ability of this kind of methodology to capture the chemical structure of premixed flames. For that purpose, three deconvolution methods are tested on a one-dimensional filtered laminar premixed flame configuration: the approximate deconvolution method based on Van Cittert iterative deconvolution, a Taylor decomposition-based method, and the regularised deconvolution method based on the minimisation of a quadratic criterion. These methods are then extended to the reconstruction of subgrid scale profiles. Two methodologies are proposed: the first one relies on subgrid scale interpolation of deconvolved profiles and the second uses parametric functions to describe small scales. Conducted tests analyse the ability of the method to capture the chemical filtered flame structure and front propagation speed. Results show that the deconvolution model should include information about small scales in order to regularise the filter inversion. a priori and a posteriori tests showed that the filtered flame propagation speed and structure cannot be captured if the filter size is too large.
Deconvolution using thin-plate splines
International Nuclear Information System (INIS)
Toussaint, Udo v.; Gori, Silvio
2007-01-01
The ubiquitous problem of estimating 2-dimensional profile information from a set of line integrated measurements is tackled with Bayesian probability theory by exploiting prior information about local smoothness. For this purpose thin-plate-splines (the 2-D minimal curvature analogue of cubic-splines in 1-D) are employed. The optimal number of support points required for inversion of 2-D tomographic problems is determined using model comparison. Properties of this approach are discussed and the question of suitable priors is addressed. Finally, we illustrated the properties of this approach with 2-D inversion results using data from line-integrated measurements from fusion experiments
Smooth quantile normalization.
Hicks, Stephanie C; Okrah, Kwame; Paulson, Joseph N; Quackenbush, John; Irizarry, Rafael A; Bravo, Héctor Corrada
2018-04-01
Between-sample normalization is a critical step in genomic data analysis to remove systematic bias and unwanted technical variation in high-throughput data. Global normalization methods are based on the assumption that observed variability in global properties is due to technical reasons and are unrelated to the biology of interest. For example, some methods correct for differences in sequencing read counts by scaling features to have similar median values across samples, but these fail to reduce other forms of unwanted technical variation. Methods such as quantile normalization transform the statistical distributions across samples to be the same and assume global differences in the distribution are induced by only technical variation. However, it remains unclear how to proceed with normalization if these assumptions are violated, for example, if there are global differences in the statistical distributions between biological conditions or groups, and external information, such as negative or control features, is not available. Here, we introduce a generalization of quantile normalization, referred to as smooth quantile normalization (qsmooth), which is based on the assumption that the statistical distribution of each sample should be the same (or have the same distributional shape) within biological groups or conditions, but allowing that they may differ between groups. We illustrate the advantages of our method on several high-throughput datasets with global differences in distributions corresponding to different biological conditions. We also perform a Monte Carlo simulation study to illustrate the bias-variance tradeoff and root mean squared error of qsmooth compared to other global normalization methods. A software implementation is available from https://github.com/stephaniehicks/qsmooth.
Interval Forecast for Smooth Transition Autoregressive Model ...
African Journals Online (AJOL)
In this paper, we propose a simple method for constructing interval forecast for smooth transition autoregressive (STAR) model. This interval forecast is based on bootstrapping the residual error of the estimated STAR model for each forecast horizon and computing various Akaike information criterion (AIC) function. This new ...
Gü nther, Felix; Jiang, Caigui; Pottmann, Helmut
2017-01-01
Polyhedral surfaces are fundamental objects in architectural geometry and industrial design. Whereas closeness of a given mesh to a smooth reference surface and its suitability for numerical simulations were already studied extensively, the aim of our work is to find and to discuss suitable assessments of smoothness of polyhedral surfaces that only take the geometry of the polyhedral surface itself into account. Motivated by analogies to classical differential geometry, we propose a theory of smoothness of polyhedral surfaces including suitable notions of normal vectors, tangent planes, asymptotic directions, and parabolic curves that are invariant under projective transformations. It is remarkable that seemingly mild conditions significantly limit the shapes of faces of a smooth polyhedral surface. Besides being of theoretical interest, we believe that smoothness of polyhedral surfaces is of interest in the architectural context, where vertices and edges of polyhedral surfaces are highly visible.
Günther, Felix
2017-03-15
Polyhedral surfaces are fundamental objects in architectural geometry and industrial design. Whereas closeness of a given mesh to a smooth reference surface and its suitability for numerical simulations were already studied extensively, the aim of our work is to find and to discuss suitable assessments of smoothness of polyhedral surfaces that only take the geometry of the polyhedral surface itself into account. Motivated by analogies to classical differential geometry, we propose a theory of smoothness of polyhedral surfaces including suitable notions of normal vectors, tangent planes, asymptotic directions, and parabolic curves that are invariant under projective transformations. It is remarkable that seemingly mild conditions significantly limit the shapes of faces of a smooth polyhedral surface. Besides being of theoretical interest, we believe that smoothness of polyhedral surfaces is of interest in the architectural context, where vertices and edges of polyhedral surfaces are highly visible.
Blind deconvolution of time-of-flight mass spectra from atom probe tomography
International Nuclear Information System (INIS)
Johnson, L.J.S.; Thuvander, M.; Stiller, K.; Odén, M.; Hultman, L.
2013-01-01
A major source of uncertainty in compositional measurements in atom probe tomography stems from the uncertainties of assigning peaks or parts of peaks in the mass spectrum to their correct identities. In particular, peak overlap is a limiting factor, whereas an ideal mass spectrum would have peaks at their correct positions with zero broadening. Here, we report a method to deconvolute the experimental mass spectrum into such an ideal spectrum and a system function describing the peak broadening introduced by the field evaporation and detection of each ion. By making the assumption of a linear and time-invariant behavior, a system of equations is derived that describes the peak shape and peak intensities. The model is fitted to the observed spectrum by minimizing the squared residuals, regularized by the maximum entropy method. For synthetic data perfectly obeying the assumptions, the method recovered peak intensities to within ±0.33at%. The application of this model to experimental APT data is exemplified with Fe–Cr data. Knowledge of the peak shape opens up several new possibilities, not just for better overall compositional determination, but, e.g., for the estimation of errors of ranging due to peak overlap or peak separation constrained by isotope abundances. - Highlights: • A method for the deconvolution of atom probe mass spectra is proposed. • Applied to synthetic randomly generated spectra the accuracy was ±0.33 at. • Application of the method to an experimental Fe–Cr spectrum is demonstrated
Some asymptotic theory for variance function smoothing | Kibua ...
African Journals Online (AJOL)
Simple selection of the smoothing parameter is suggested. Both homoscedastic and heteroscedastic regression models are considered. Keywords: Asymptotic, Smoothing, Kernel, Bandwidth, Bias, Variance, Mean squared error, Homoscedastic, Heteroscedastic. > East African Journal of Statistics Vol. 1 (1) 2005: pp. 9-22 ...
Gamma-ray spectra deconvolution by maximum-entropy methods
International Nuclear Information System (INIS)
Los Arcos, J.M.
1996-01-01
A maximum-entropy method which includes the response of detectors and the statistical fluctuations of spectra is described and applied to the deconvolution of γ-ray spectra. Resolution enhancement of 25% can be reached for experimental peaks and up to 50% for simulated ones, while the intensities are conserved within 1-2%. (orig.)
Filtering and deconvolution for bioluminescence imaging of small animals
International Nuclear Information System (INIS)
Akkoul, S.
2010-01-01
This thesis is devoted to analysis of bioluminescence images applied to the small animal. This kind of imaging modality is used in cancerology studies. Nevertheless, some problems are related to the diffusion and the absorption of the tissues of the light of internal bioluminescent sources. In addition, system noise and the cosmic rays noise are present. This influences the quality of the images and makes it difficult to analyze. The purpose of this thesis is to overcome these disturbing effects. We first have proposed an image formation model for the bioluminescence images. The processing chain is constituted by a filtering stage followed by a deconvolution stage. We have proposed a new median filter to suppress the random value impulsive noise which corrupts the acquired images; this filter represents the first block of the proposed chain. For the deconvolution stage, we have performed a comparative study of various deconvolution algorithms. It allowed us to choose a blind deconvolution algorithm initialized with the estimated point spread function of the acquisition system. At first, we have validated our global approach by comparing our obtained results with the ground truth. Through various clinical tests, we have shown that the processing chain allows a significant improvement of the spatial resolution and a better distinction of very close tumor sources, what represents considerable contribution for the users of bioluminescence images. (author)
Deconvolution of astronomical images using SOR with adaptive relaxation.
Vorontsov, S V; Strakhov, V N; Jefferies, S M; Borelli, K J
2011-07-04
We address the potential performance of the successive overrelaxation technique (SOR) in image deconvolution, focusing our attention on the restoration of astronomical images distorted by atmospheric turbulence. SOR is the classical Gauss-Seidel iteration, supplemented with relaxation. As indicated by earlier work, the convergence properties of SOR, and its ultimate performance in the deconvolution of blurred and noisy images, can be made competitive to other iterative techniques, including conjugate gradients, by a proper choice of the relaxation parameter. The question of how to choose the relaxation parameter, however, remained open, and in the practical work one had to rely on experimentation. In this paper, using constructive (rather than exact) arguments, we suggest a simple strategy for choosing the relaxation parameter and for updating its value in consecutive iterations to optimize the performance of the SOR algorithm (and its positivity-constrained version, +SOR) at finite iteration counts. We suggest an extension of the algorithm to the notoriously difficult problem of "blind" deconvolution, where both the true object and the point-spread function have to be recovered from the blurred image. We report the results of numerical inversions with artificial and real data, where the algorithm is compared with techniques based on conjugate gradients. In all of our experiments +SOR provides the highest quality results. In addition +SOR is found to be able to detect moderately small changes in the true object between separate data frames: an important quality for multi-frame blind deconvolution where stationarity of the object is a necesessity.
Deconvolution of EPR spectral lines with an approximate method
International Nuclear Information System (INIS)
Jimenez D, H.; Cabral P, A.
1990-10-01
A recently reported approximation expression to deconvolution Lorentzian-Gaussian spectral lines. with small Gaussian contribution, is applied to study an EPR line shape. The potassium-ammonium solution line reported in the literature by other authors was used and the results are compared with those obtained by employing a precise method. (Author)
Euler deconvolution and spectral analysis of regional aeromagnetic ...
African Journals Online (AJOL)
Existing regional aeromagnetic data from the south-central Zimbabwe craton has been analysed using 3D Euler deconvolution and spectral analysis to obtain quantitative information on the geological units and structures for depth constraints on the geotectonic interpretation of the region. The Euler solution maps confirm ...
Improvement in volume estimation from confocal sections after image deconvolution
Czech Academy of Sciences Publication Activity Database
Difato, Francesco; Mazzone, F.; Scaglione, S.; Fato, M.; Beltrame, F.; Kubínová, Lucie; Janáček, Jiří; Ramoino, P.; Vicidomini, G.; Diaspro, A.
2004-01-01
Roč. 64, č. 2 (2004), s. 151-155 ISSN 1059-910X Institutional research plan: CEZ:AV0Z5011922 Keywords : confocal microscopy * image deconvolution * point spread function Subject RIV: EA - Cell Biology Impact factor: 2.609, year: 2004
Linear MALDI-ToF simultaneous spectrum deconvolution and baseline removal.
Picaud, Vincent; Giovannelli, Jean-Francois; Truntzer, Caroline; Charrier, Jean-Philippe; Giremus, Audrey; Grangeat, Pierre; Mercier, Catherine
2018-04-05
Thanks to a reasonable cost and simple sample preparation procedure, linear MALDI-ToF spectrometry is a growing technology for clinical microbiology. With appropriate spectrum databases, this technology can be used for early identification of pathogens in body fluids. However, due to the low resolution of linear MALDI-ToF instruments, robust and accurate peak picking remains a challenging task. In this context we propose a new peak extraction algorithm from raw spectrum. With this method the spectrum baseline and spectrum peaks are processed jointly. The approach relies on an additive model constituted by a smooth baseline part plus a sparse peak list convolved with a known peak shape. The model is then fitted under a Gaussian noise model. The proposed method is well suited to process low resolution spectra with important baseline and unresolved peaks. We developed a new peak deconvolution procedure. The paper describes the method derivation and discusses some of its interpretations. The algorithm is then described in a pseudo-code form where the required optimization procedure is detailed. For synthetic data the method is compared to a more conventional approach. The new method reduces artifacts caused by the usual two-steps procedure, baseline removal then peak extraction. Finally some results on real linear MALDI-ToF spectra are provided. We introduced a new method for peak picking, where peak deconvolution and baseline computation are performed jointly. On simulated data we showed that this global approach performs better than a classical one where baseline and peaks are processed sequentially. A dedicated experiment has been conducted on real spectra. In this study a collection of spectra of spiked proteins were acquired and then analyzed. Better performances of the proposed method, in term of accuracy and reproductibility, have been observed and validated by an extended statistical analysis.
Indian Academy of Sciences (India)
Abstract. Let S be a scheme. Assume that we are given an action of the one dimen- sional split torus Gm,S on a smooth affine S-scheme X. We consider the limit (also called attractor) subfunctor Xλ consisting of points whose orbit under the given action. 'admits a limit at 0'. We show that Xλ is representable by a smooth ...
Energy Technology Data Exchange (ETDEWEB)
Akkoul, S.
2010-06-22
This thesis is devoted to analysis of bioluminescence images applied to the small animal. This kind of imaging modality is used in cancerology studies. Nevertheless, some problems are related to the diffusion and the absorption of the tissues of the light of internal bioluminescent sources. In addition, system noise and the cosmic rays noise are present. This influences the quality of the images and makes it difficult to analyze. The purpose of this thesis is to overcome these disturbing effects. We first have proposed an image formation model for the bioluminescence images. The processing chain is constituted by a filtering stage followed by a deconvolution stage. We have proposed a new median filter to suppress the random value impulsive noise which corrupts the acquired images; this filter represents the first block of the proposed chain. For the deconvolution stage, we have performed a comparative study of various deconvolution algorithms. It allowed us to choose a blind deconvolution algorithm initialized with the estimated point spread function of the acquisition system. At first, we have validated our global approach by comparing our obtained results with the ground truth. Through various clinical tests, we have shown that the processing chain allows a significant improvement of the spatial resolution and a better distinction of very close tumor sources, what represents considerable contribution for the users of bioluminescence images. (author)
Prediction of human errors by maladaptive changes in event-related brain networks
Eichele, T.; Debener, S.; Calhoun, V.D.; Specht, K.; Engel, A.K.; Hugdahl, K.; Cramon, D.Y. von; Ullsperger, M.
2008-01-01
Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional Mill and applying independent component analysis followed by deconvolution of hemodynamic responses, we
An alternating minimization method for blind deconvolution from Poisson data
International Nuclear Information System (INIS)
Prato, Marco; La Camera, Andrea; Bonettini, Silvia
2014-01-01
Blind deconvolution is a particularly challenging inverse problem since information on both the desired target and the acquisition system have to be inferred from the measured data. When the collected data are affected by Poisson noise, this problem is typically addressed by the minimization of the Kullback-Leibler divergence, in which the unknowns are sought in particular feasible sets depending on the a priori information provided by the specific application. If these sets are separated, then the resulting constrained minimization problem can be addressed with an inexact alternating strategy. In this paper we apply this optimization tool to the problem of reconstructing astronomical images from adaptive optics systems, and we show that the proposed approach succeeds in providing very good results in the blind deconvolution of nondense stellar clusters
Deconvolution of In Vivo Ultrasound B-Mode Images
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt; Stage, Bjarne; Mathorne, Jan
1993-01-01
An algorithm for deconvolution of medical ultrasound images is presented. The procedure involves estimation of the basic one-dimensional ultrasound pulse, determining the ratio of the covariance of the noise to the covariance of the reflection signal, and finally deconvolution of the rf signal from...... the transducer. Using pulse and covariance estimators makes the approach self-calibrating, as all parameters for the procedure are estimated from the patient under investigation. An example of use on a clinical, in-vivo image is given. A 2 × 2 cm region of the portal vein in a liver is deconvolved. An increase...... in axial resolution by a factor of 2.4 is obtained. The procedure can also be applied to whole images, when it is ensured that the rf signal is properly measured. A method for doing that is outlined....
Deconvolution of shift-variant broadening for Compton scatter imaging
International Nuclear Information System (INIS)
Evans, Brian L.; Martin, Jeffrey B.; Roggemann, Michael C.
1999-01-01
A technique is presented for deconvolving shift-variant Doppler broadening of singly Compton scattered gamma rays from their recorded energy distribution. Doppler broadening is important in Compton scatter imaging techniques employing gamma rays with energies below roughly 100 keV. The deconvolution unfolds an approximation to the angular distribution of scattered photons from their recorded energy distribution in the presence of statistical noise and background counts. Two unfolding methods are presented, one based on a least-squares algorithm and one based on a maximum likelihood algorithm. Angular distributions unfolded from measurements made on small scattering targets show less evidence of Compton broadening. This deconvolution is shown to improve the quality of filtered backprojection images in multiplexed Compton scatter tomography. Improved sharpness and contrast are evident in the images constructed from unfolded signals
Example-driven manifold priors for image deconvolution.
Ni, Jie; Turaga, Pavan; Patel, Vishal M; Chellappa, Rama
2011-11-01
Image restoration methods that exploit prior information about images to be estimated have been extensively studied, typically using the Bayesian framework. In this paper, we consider the role of prior knowledge of the object class in the form of a patch manifold to address the deconvolution problem. Specifically, we incorporate unlabeled image data of the object class, say natural images, in the form of a patch-manifold prior for the object class. The manifold prior is implicitly estimated from the given unlabeled data. We show how the patch-manifold prior effectively exploits the available sample class data for regularizing the deblurring problem. Furthermore, we derive a generalized cross-validation (GCV) function to automatically determine the regularization parameter at each iteration without explicitly knowing the noise variance. Extensive experiments show that this method performs better than many competitive image deconvolution methods.
Retinal image restoration by means of blind deconvolution
Czech Academy of Sciences Publication Activity Database
Marrugo, A.; Šorel, Michal; Šroubek, Filip; Millan, M.
2011-01-01
Roč. 16, č. 11 (2011), 116016-1-116016-11 ISSN 1083-3668 R&D Projects: GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : blind deconvolution * image restoration * retinal image * deblurring Subject RIV: JD - Computer Applications, Robotics Impact factor: 3.157, year: 2011 http://library.utia.cas.cz/separaty/2011/ZOI/sorel-0366061.pdf
XDGMM: eXtreme Deconvolution Gaussian Mixture Modeling
Holoien, Thomas W.-S.; Marshall, Philip J.; Wechsler, Risa H.
2017-08-01
XDGMM uses Gaussian mixtures to do density estimation of noisy, heterogenous, and incomplete data using extreme deconvolution (XD) algorithms which is compatible with the scikit-learn machine learning methods. It implements both the astroML and Bovy et al. (2011) algorithms, and extends the BaseEstimator class from scikit-learn so that cross-validation methods work. It allows the user to produce a conditioned model if values of some parameters are known.
Robust Multichannel Blind Deconvolution via Fast Alternating Minimization
Czech Academy of Sciences Publication Activity Database
Šroubek, Filip; Milanfar, P.
2012-01-01
Roč. 21, č. 4 (2012), s. 1687-1700 ISSN 1057-7149 R&D Projects: GA MŠk 1M0572; GA ČR GAP103/11/1552; GA MV VG20102013064 Institutional research plan: CEZ:AV0Z10750506 Keywords : blind deconvolution * augmented Lagrangian * sparse representation Subject RIV: JD - Computer Applications, Robotics Impact factor: 3.199, year: 2012 http://library.utia.cas.cz/separaty/2012/ZOI/sroubek-0376080.pdf
Real Time Deconvolution of In-Vivo Ultrasound Images
DEFF Research Database (Denmark)
Jensen, Jørgen Arendt
2013-01-01
and two wavelengths. This can be improved by deconvolution, which increase the bandwidth and equalizes the phase to increase resolution under the constraint of the electronic noise in the received signal. A fixed interval Kalman filter based deconvolution routine written in C is employed. It uses a state...... resolution has been determined from the in-vivo liver image using the auto-covariance function. From the envelope of the estimated pulse the axial resolution at Full-Width-Half-Max is 0.581 mm corresponding to 1.13 l at 3 MHz. The algorithm increases the resolution to 0.116 mm or 0.227 l corresponding...... to a factor of 5.1. The basic pulse can be estimated in roughly 0.176 seconds on a single CPU core on an Intel i5 CPU running at 1.8 GHz. An in-vivo image consisting of 100 lines of 1600 samples can be processed in roughly 0.1 seconds making it possible to perform real-time deconvolution on ultrasound data...
Point spread functions and deconvolution of ultrasonic images.
Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten
2015-03-01
This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.
Designing a stable feedback control system for blind image deconvolution.
Cheng, Shichao; Liu, Risheng; Fan, Xin; Luo, Zhongxuan
2018-05-01
Blind image deconvolution is one of the main low-level vision problems with wide applications. Many previous works manually design regularization to simultaneously estimate the latent sharp image and the blur kernel under maximum a posterior framework. However, it has been demonstrated that such joint estimation strategies may lead to the undesired trivial solution. In this paper, we present a novel perspective, using a stable feedback control system, to simulate the latent sharp image propagation. The controller of our system consists of regularization and guidance, which decide the sparsity and sharp features of latent image, respectively. Furthermore, the formational model of blind image is introduced into the feedback process to avoid the image restoration deviating from the stable point. The stability analysis of the system indicates the latent image propagation in blind deconvolution task can be efficiently estimated and controlled by cues and priors. Thus the kernel estimation used for image restoration becomes more precision. Experimental results show that our system is effective on image propagation, and can perform favorably against the state-of-the-art blind image deconvolution methods on different benchmark image sets and special blurred images. Copyright © 2018 Elsevier Ltd. All rights reserved.
Non-parametric smoothing of experimental data
International Nuclear Information System (INIS)
Kuketayev, A.T.; Pen'kov, F.M.
2007-01-01
Full text: Rapid processing of experimental data samples in nuclear physics often requires differentiation in order to find extrema. Therefore, even at the preliminary stage of data analysis, a range of noise reduction methods are used to smooth experimental data. There are many non-parametric smoothing techniques: interval averages, moving averages, exponential smoothing, etc. Nevertheless, it is more common to use a priori information about the behavior of the experimental curve in order to construct smoothing schemes based on the least squares techniques. The latter methodology's advantage is that the area under the curve can be preserved, which is equivalent to conservation of total speed of counting. The disadvantages of this approach include the lack of a priori information. For example, very often the sums of undifferentiated (by a detector) peaks are replaced with one peak during the processing of data, introducing uncontrolled errors in the determination of the physical quantities. The problem is solvable only by having experienced personnel, whose skills are much greater than the challenge. We propose a set of non-parametric techniques, which allows the use of any additional information on the nature of experimental dependence. The method is based on a construction of a functional, which includes both experimental data and a priori information. Minimum of this functional is reached on a non-parametric smoothed curve. Euler (Lagrange) differential equations are constructed for these curves; then their solutions are obtained analytically or numerically. The proposed approach allows for automated processing of nuclear physics data, eliminating the need for highly skilled laboratory personnel. Pursuant to the proposed approach is the possibility to obtain smoothing curves in a given confidence interval, e.g. according to the χ 2 distribution. This approach is applicable when constructing smooth solutions of ill-posed problems, in particular when solving
MINIMUM ENTROPY DECONVOLUTION OF ONE-AND MULTI-DIMENSIONAL NON-GAUSSIAN LINEAR RANDOM PROCESSES
Institute of Scientific and Technical Information of China (English)
程乾生
1990-01-01
The minimum entropy deconvolution is considered as one of the methods for decomposing non-Gaussian linear processes. The concept of peakedness of a system response sequence is presented and its properties are studied. With the aid of the peakedness, the convergence theory of the minimum entropy deconvolution is established. The problem of the minimum entropy deconvolution of multi-dimensional non-Gaussian linear random processes is first investigated and the corresponding theory is given. In addition, the relation between the minimum entropy deconvolution and parameter method is discussed.
Hoede, C.; Li, Z.
2001-01-01
In coding theory the problem of decoding focuses on error vectors. In the simplest situation code words are $(0,1)$-vectors, as are the received messages and the error vectors. Comparison of a received word with the code words yields a set of error vectors. In deciding on the original code word,
Revealed smooth nontransitive preferences
DEFF Research Database (Denmark)
Keiding, Hans; Tvede, Mich
2013-01-01
In the present paper, we are concerned with the behavioural consequences of consumers having nontransitive preference relations. Data sets consist of ﬁnitely many observations of price vectors and consumption bundles. A preference relation rationalizes a data set provided that for every observed...... consumption bundle, all strictly preferred bundles are more expensive than the observed bundle. Our main result is that data sets can be rationalized by a smooth nontransitive preference relation if and only if prices can normalized such that the law of demand is satisﬁed. Market data sets consist of ﬁnitely...... many observations of price vectors, lists of individual incomes and aggregate demands. We apply our main result to characterize market data sets consistent with equilibrium behaviour of pure-exchange economies with smooth nontransitive consumers....
Generalizing smooth transition autoregressions
DEFF Research Database (Denmark)
Chini, Emilio Zanetti
We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail, with part......We introduce a variant of the smooth transition autoregression - the GSTAR model - capable to parametrize the asymmetry in the tails of the transition equation by using a particular generalization of the logistic function. A General-to-Specific modelling strategy is discussed in detail......, with particular emphasis on two different LM-type tests for the null of symmetric adjustment towards a new regime and three diagnostic tests, whose power properties are explored via Monte Carlo experiments. Four classical real datasets illustrate the empirical properties of the GSTAR, jointly to a rolling...
International Nuclear Information System (INIS)
Erbsman, F.; Ham, H.; Piepsz, A.; Struyven, J.
1978-01-01
The renal impulse response function (Renal IRF) is the time-activity curve measured over one kidney after injection of a radiopharmaceutical in the renal artery. If the tracer is injected intravenously it is possible to compute the renal IRF by deconvoluting the kidney curve by a blood curve. In previous work we demonstrated that the computed IRF is in good agreement with measurements made after injection in the renal artery. The goal of the present work is the analysis of the effect of sampling errors and the influence of extra-renal activity. The sampling error is only important for the first point of the plasma curve and yields an ill-conditioned function P -1 . The addition of 50 computed renal IRF's demonstrated that the three first points show a larger variability due to incomplete mixing of the tracer. These points should thus not be included in the smoothing process. Subtraction of non-renal activity does not modify appreciably the shape of the renal IRF. The mean transit time and the time to half value are almost independent of non-renal activity and seem to be the parameters of choice
... gov/ency/article/003531.htm Anti-smooth muscle antibody To use the sharing features on this page, please enable JavaScript. Anti-smooth muscle antibody is a blood test that detects the presence ...
Directory of Open Access Journals (Sweden)
Dan Siegal-Gaskins
2009-08-01
Full Text Available In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure "just-in-time" assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is an inaccurate measure of what occurs in the average single-cell across a cell cycle. Here, we present a general computational method to extract "single-cell"-like information from population-level time-series expression data. This method removes the effects of 1 variance in growth rate and 2 variance in the physiological and developmental state of the cell. Moreover, this method represents an advance in the deconvolution of molecular expression data in its flexibility, minimal assumptions, and the use of a cross-validation analysis to determine the appropriate level of regularization. Applying our deconvolution algorithm to cell cycle gene expression data from the dimorphic bacterium Caulobacter crescentus, we recovered critical features of cell cycle regulation in essential genes, including ctrA and ftsZ, that were obscured in population-based measurements. In doing so, we highlight the problem with using population data alone to decipher cellular regulatory mechanisms and demonstrate how our deconvolution algorithm can be applied to produce a more realistic picture of temporal regulation in a cell.
Fatal defect in computerized glow curve deconvolution of thermoluminescence
International Nuclear Information System (INIS)
Sakurai, T.
2001-01-01
The method of computerized glow curve deconvolution (CGCD) is a powerful tool in the study of thermoluminescence (TL). In a system where the plural trapping levels have the probability of retrapping, the electrons trapped at one level can transfer from this level to another through retrapping via the conduction band during reading TL. However, at present, the method of CGCD has no affect on the electron transition between the trapping levels; this is a fatal defect. It is shown by computer simulation that CGCD using general-order kinetics thus cannot yield the correct trap parameters. (author)
Seeing deconvolution of globular clusters in M31
International Nuclear Information System (INIS)
Bendinelli, O.; Zavatti, F.; Parmeggiani, G.; Djorgovski, S.
1990-01-01
The morphology of six M31 globular clusters is examined using seeing-deconvolved CCD images. The deconvolution techniques developed by Bendinelli (1989) are reviewed and applied to the M31 globular clusters to demonstrate the methodology. It is found that the effective resolution limit of the method is about 0.1-0.3 arcsec for CCD images obtained in FWHM = 1 arcsec seeing, and sampling of 0.3 arcsec/pixel. Also, the robustness of the method is discussed. The implications of the technique for future studies using data from the Hubble Space Telescope are considered. 68 refs
Nuclear pulse signal processing techniques based on blind deconvolution method
International Nuclear Information System (INIS)
Hong Pengfei; Yang Lei; Qi Zhong; Meng Xiangting; Fu Yanyan; Li Dongcang
2012-01-01
This article presents a method of measurement and analysis of nuclear pulse signal, the FPGA to control high-speed ADC measurement of nuclear radiation signals and control the high-speed transmission status of the USB to make it work on the Slave FIFO mode, using the LabVIEW online data processing and display, using the blind deconvolution method to remove the accumulation of signal acquisition, and to restore the nuclear pulse signal with a transmission speed, real-time measurements show that the advantages. (authors)
Nuclear pulse signal processing technique based on blind deconvolution method
International Nuclear Information System (INIS)
Hong Pengfei; Yang Lei; Fu Tingyan; Qi Zhong; Li Dongcang; Ren Zhongguo
2012-01-01
In this paper, we present a method for measurement and analysis of nuclear pulse signal, with which pile-up signal is removed, the signal baseline is restored, and the original signal is obtained. The data acquisition system includes FPGA, ADC and USB. The FPGA controls the high-speed ADC to sample the signal of nuclear radiation, and the USB makes the ADC work on the Slave FIFO mode to implement high-speed transmission status. Using the LabVIEW, it accomplishes online data processing of the blind deconvolution algorithm and data display. The simulation and experimental results demonstrate advantages of the method. (authors)
Approximate deconvolution models of turbulence analysis, phenomenology and numerical analysis
Layton, William J
2012-01-01
This volume presents a mathematical development of a recent approach to the modeling and simulation of turbulent flows based on methods for the approximate solution of inverse problems. The resulting Approximate Deconvolution Models or ADMs have some advantages over more commonly used turbulence models – as well as some disadvantages. Our goal in this book is to provide a clear and complete mathematical development of ADMs, while pointing out the difficulties that remain. In order to do so, we present the analytical theory of ADMs, along with its connections, motivations and complements in the phenomenology of and algorithms for ADMs.
Deconvolution map-making for cosmic microwave background observations
International Nuclear Information System (INIS)
Armitage, Charmaine; Wandelt, Benjamin D.
2004-01-01
We describe a new map-making code for cosmic microwave background observations. It implements fast algorithms for convolution and transpose convolution of two functions on the sphere [B. Wandelt and K. Gorski, Phys. Rev. D 63, 123002 (2001)]. Our code can account for arbitrary beam asymmetries and can be applied to any scanning strategy. We demonstrate the method using simulated time-ordered data for three beam models and two scanning patterns, including a coarsened version of the WMAP strategy. We quantitatively compare our results with a standard map-making method and demonstrate that the true sky is recovered with high accuracy using deconvolution map-making
Stable Blind Deconvolution over the Reals from Additional Autocorrelations
Walk, Philipp
2017-10-22
Recently the one-dimensional time-discrete blind deconvolution problem was shown to be solvable uniquely, up to a global phase, by a semi-definite program for almost any signal, provided its autocorrelation is known. We will show in this work that under a sufficient zero separation of the corresponding signal in the $z-$domain, a stable reconstruction against additive noise is possible. Moreover, the stability constant depends on the signal dimension and on the signals magnitude of the first and last coefficients. We give an analytical expression for this constant by using spectral bounds of Vandermonde matrices.
Smooth functors vs. differential forms
Schreiber, U.; Waldorf, K.
2011-01-01
We establish a relation between smooth 2-functors defined on the path 2-groupoid of a smooth manifold and differential forms on this manifold. This relation can be understood as a part of a dictionary between fundamental notions from category theory and differential geometry. We show that smooth
International Nuclear Information System (INIS)
Knuefer; Lindauer
1980-01-01
Besides that at spectacular events a combination of component failure and human error is often found. Especially the Rasmussen-Report and the German Risk Assessment Study show for pressurised water reactors that human error must not be underestimated. Although operator errors as a form of human error can never be eliminated entirely, they can be minimized and their effects kept within acceptable limits if a thorough training of personnel is combined with an adequate design of the plant against accidents. Contrary to the investigation of engineering errors, the investigation of human errors has so far been carried out with relatively small budgets. Intensified investigations in this field appear to be a worthwhile effort. (orig.)
Multi-Channel Deconvolution for Forward-Looking Phase Array Radar Imaging
Directory of Open Access Journals (Sweden)
Jie Xia
2017-07-01
Full Text Available The cross-range resolution of forward-looking phase array radar (PAR is limited by the effective antenna beamwidth since the azimuth echo is the convolution of antenna pattern and targets’ backscattering coefficients. Therefore, deconvolution algorithms are proposed to improve the imaging resolution under the limited antenna beamwidth. However, as a typical inverse problem, deconvolution is essentially a highly ill-posed problem which is sensitive to noise and cannot ensure a reliable and robust estimation. In this paper, multi-channel deconvolution is proposed for improving the performance of deconvolution, which intends to considerably alleviate the ill-posed problem of single-channel deconvolution. To depict the performance improvement obtained by multi-channel more effectively, evaluation parameters are generalized to characterize the angular spectrum of antenna pattern or singular value distribution of observation matrix, which are conducted to compare different deconvolution systems. Here we present two multi-channel deconvolution algorithms which improve upon the traditional deconvolution algorithms via combining with multi-channel technique. Extensive simulations and experimental results based on real data are presented to verify the effectiveness of the proposed imaging methods.
Sparse spectral deconvolution algorithm for noncartesian MR spectroscopic imaging.
Bhave, Sampada; Eslami, Ramin; Jacob, Mathews
2014-02-01
To minimize line shape distortions and spectral leakage artifacts in MR spectroscopic imaging (MRSI). A spatially and spectrally regularized non-Cartesian MRSI algorithm that uses the line shape distortion priors, estimated from water reference data, to deconvolve the spectra is introduced. Sparse spectral regularization is used to minimize noise amplification associated with deconvolution. A spiral MRSI sequence that heavily oversamples the central k-space regions is used to acquire the MRSI data. The spatial regularization term uses the spatial supports of brain and extracranial fat regions to recover the metabolite spectra and nuisance signals at two different resolutions. Specifically, the nuisance signals are recovered at the maximum resolution to minimize spectral leakage, while the point spread functions of metabolites are controlled to obtain acceptable signal-to-noise ratio. The comparisons of the algorithm against Tikhonov regularized reconstructions demonstrates considerably reduced line-shape distortions and improved metabolite maps. The proposed sparsity constrained spectral deconvolution scheme is effective in minimizing the line-shape distortions. The dual resolution reconstruction scheme is capable of minimizing spectral leakage artifacts. Copyright © 2013 Wiley Periodicals, Inc.
Retinal image restoration by means of blind deconvolution
Marrugo, Andrés G.; Šorel, Michal; Šroubek, Filip; Millán, María S.
2011-11-01
Retinal imaging plays a key role in the diagnosis and management of ophthalmologic disorders, such as diabetic retinopathy, glaucoma, and age-related macular degeneration. Because of the acquisition process, retinal images often suffer from blurring and uneven illumination. This problem may seriously affect disease diagnosis and progression assessment. Here we present a method for color retinal image restoration by means of multichannel blind deconvolution. The method is applied to a pair of retinal images acquired within a lapse of time, ranging from several minutes to months. It consists of a series of preprocessing steps to adjust the images so they comply with the considered degradation model, followed by the estimation of the point-spread function and, ultimately, image deconvolution. The preprocessing is mainly composed of image registration, uneven illumination compensation, and segmentation of areas with structural changes. In addition, we have developed a procedure for the detection and visualization of structural changes. This enables the identification of subtle developments in the retina not caused by variation in illumination or blur. The method was tested on synthetic and real images. Encouraging experimental results show that the method is capable of significant restoration of degraded retinal images.
A soft double regularization approach to parametric blind image deconvolution.
Chen, Li; Yap, Kim-Hui
2005-05-01
This paper proposes a blind image deconvolution scheme based on soft integration of parametric blur structures. Conventional blind image deconvolution methods encounter a difficult dilemma of either imposing stringent and inflexible preconditions on the problem formulation or experiencing poor restoration results due to lack of information. This paper attempts to address this issue by assessing the relevance of parametric blur information, and incorporating the knowledge into the parametric double regularization (PDR) scheme. The PDR method assumes that the actual blur satisfies up to a certain degree of parametric structure, as there are many well-known parametric blurs in practical applications. Further, it can be tailored flexibly to include other blur types if some prior parametric knowledge of the blur is available. A manifold soft parametric modeling technique is proposed to generate the blur manifolds, and estimate the fuzzy blur structure. The PDR scheme involves the development of the meaningful cost function, the estimation of blur support and structure, and the optimization of the cost function. Experimental results show that it is effective in restoring degraded images under different environments.
Exponential smoothing weighted correlations
Pozzi, F.; Di Matteo, T.; Aste, T.
2012-06-01
In many practical applications, correlation matrices might be affected by the "curse of dimensionality" and by an excessive sensitiveness to outliers and remote observations. These shortcomings can cause problems of statistical robustness especially accentuated when a system of dynamic correlations over a running window is concerned. These drawbacks can be partially mitigated by assigning a structure of weights to observational events. In this paper, we discuss Pearson's ρ and Kendall's τ correlation matrices, weighted with an exponential smoothing, computed on moving windows using a data-set of daily returns for 300 NYSE highly capitalized companies in the period between 2001 and 2003. Criteria for jointly determining optimal weights together with the optimal length of the running window are proposed. We find that the exponential smoothing can provide more robust and reliable dynamic measures and we discuss that a careful choice of the parameters can reduce the autocorrelation of dynamic correlations whilst keeping significance and robustness of the measure. Weighted correlations are found to be smoother and recovering faster from market turbulence than their unweighted counterparts, helping also to discriminate more effectively genuine from spurious correlations.
International Nuclear Information System (INIS)
Hani, Ahmad Fadzil M; Younis, M Shahzad; Halim, M Firdaus M
2009-01-01
A blind deconvolution technique using a modified higher order statistics (HOS)-based eigenvector algorithm (EVA) is presented in this paper. The main purpose of the technique is to enable the processing of low SNR short length seismograms. In our study, the seismogram is assumed to be the output of a mixed phase source wavelet (system) driven by a non-Gaussian input signal (due to earth) with additive Gaussian noise. Techniques based on second-order statistics are shown to fail when processing non-minimum phase seismic signals because they only rely on the autocorrelation function of the observed signal. In contrast, existing HOS-based blind deconvolution techniques are suitable in the processing of a non-minimum (mixed) phase system; however, most of them are unable to converge and show poor performance whenever noise dominates the actual signal, especially in the cases where the observed data are limited (few samples). The developed blind equalization technique is primarily based on the EVA for blind equalization, initially to deal with mixed phase non-Gaussian seismic signals. In order to deal with the dominant noise issue and small number of available samples, certain modifications are incorporated into the EVA. For determining the deconvolution filter, one of the modifications is to use more than one higher order cumulant slice in the EVA. This overcomes the possibility of non-convergence due to a low signal-to-noise ratio (SNR) of the observed signal. The other modification conditions the cumulant slice by increasing the power of eigenvalues of the cumulant slice, related to actual signal, and rejects the eigenvalues below the threshold representing the noise. This modification reduces the effect of the availability of a small number of samples and strong additive noise on the cumulant slices. These modifications are found to improve the overall deconvolution performance, with approximately a five-fold reduction in a mean square error (MSE) and a six
Method for the deconvolution of incompletely resolved CARS spectra in chemical dynamics experiments
International Nuclear Information System (INIS)
Anda, A.A.; Phillips, D.L.; Valentini, J.J.
1986-01-01
We describe a method for deconvoluting incompletely resolved CARS spectra to obtain quantum state population distributions. No particular form for the rotational and vibrational state distribution is assumed, the population of each quantum state is treated as an independent quantity. This method of analysis differs from previously developed approaches for the deconvolution of CARS spectra, all of which assume that the population distribution is Boltzmann, and thus are limited to the analysis of CARS spectra taken under conditions of thermal equilibrium. The method of analysis reported here has been developed to deconvolute CARS spectra of photofragments and chemical reaction products obtained in chemical dynamics experiments under nonequilibrium conditions. The deconvolution procedure has been incorporated into a computer code. The application of that code to the deconvolution of CARS spectra obtained for samples at thermal equilibrium and not at thermal equilibrium is reported. The method is accurate and computationally efficient
International Nuclear Information System (INIS)
Arnold, V.I.
2006-03-01
To describe the topological structure of a real smooth function one associates to it the graph, formed by the topological variety, whose points are the connected components of the level hypersurface of the function. For a Morse function, such a graph is a tree. Generically, it has T triple vertices, T + 2 endpoints, 2T + 2 vertices and 2T + 1 arrows. The main goal of the present paper is to study the statistics of the graphs, corresponding to T triple points: what is the growth rate of the number φ(T) of different graphs? Which part of these graphs is representable by the polynomial functions of corresponding degree? A generic polynomial of degree n has at most (n - 1) 2 critical points on R 2 , corresponding to 2T + 2 = (n - 1) 2 + 1, that is to T = 2k(k - 1) saddle-points for degree n = 2k
Classification of smooth Fano polytopes
DEFF Research Database (Denmark)
Øbro, Mikkel
A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....
Reilhac, Anthonin; Charil, Arnaud; Wimberley, Catriona; Angelis, Georgios; Hamze, Hasar; Callaghan, Paul; Garcia, Marie-Paule; Boisson, Frederic; Ryder, Will; Meikle, Steven R; Gregoire, Marie-Claude
2015-09-01
Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Winterflood, A.H.
1980-01-01
In discussing Einstein's Special Relativity theory it is claimed that it violates the principle of relativity itself and that an anomalous sign in the mathematics is found in the factor which transforms one inertial observer's measurements into those of another inertial observer. The apparent source of this error is discussed. Having corrected the error a new theory, called Observational Kinematics, is introduced to replace Einstein's Special Relativity. (U.K.)
Optimized coincidence Doppler broadening spectroscopy using deconvolution algorithms
International Nuclear Information System (INIS)
Ho, K.F.; Ching, H.M.; Cheng, K.W.; Beling, C.D.; Fung, S.; Ng, K.P.
2004-01-01
In the last few years a number of excellent deconvolution algorithms have been developed for use in ''de-blurring'' 2D images. Here we report briefly on one such algorithm we have studied which uses the non-negativity constraint to optimize the regularization and which is applied to the 2D image like data produced in Coincidence Doppler Broadening Spectroscopy (CDBS). The system instrumental resolution functions are obtained using the 514 keV line from 85 Sr. The technique when applied to a series of well annealed polycrystalline metals gives two photon momentum data on a quality comparable to that obtainable using 1D Angular Correlation of Annihilation Radiation (ACAR). (orig.)
Double spike with isotope pattern deconvolution for mercury speciation
International Nuclear Information System (INIS)
Castillo, A.; Rodriguez-Gonzalez, P.; Centineo, G.; Roig-Navarro, A.F.; Garcia Alonso, J.I.
2009-01-01
Full text: A double-spiking approach, based on an isotope pattern deconvolution numerical methodology, has been developed and applied for the accurate and simultaneous determination of inorganic mercury (IHg) and methylmercury (MeHg). Isotopically enriched mercury species ( 199 IHg and 201 MeHg) are added before sample preparation to quantify the extent of methylation and demethylation processes. Focused microwave digestion was evaluated to perform the quantitative extraction of such compounds from solid matrices of environmental interest. Satisfactory results were obtained in different certificated reference materials (dogfish liver DOLT-4 and tuna fish CRM-464) both by using GC-ICPMS and GC-MS, demonstrating the suitability of the proposed analytical method. (author)
A new deconvolution method applied to ultrasonic images
International Nuclear Information System (INIS)
Sallard, J.
1999-01-01
This dissertation presents the development of a new method for restoration of ultrasonic signals. Our goal is to remove the perturbations induced by the ultrasonic probe and to help to characterize the defects due to a strong local discontinuity of the acoustic impedance. The point of view adopted consists in taking into account the physical properties in the signal processing to develop an algorithm which gives good results even on experimental data. The received ultrasonic signal is modeled as a convolution between a function that represents the waveform emitted by the transducer and a function that is abusively called the 'defect impulse response'. It is established that, in numerous cases, the ultrasonic signal can be expressed as a sum of weighted, phase-shifted replicas of a reference signal. Deconvolution is an ill-posed problem. A priori information must be taken into account to solve the problem. The a priori information translates the physical properties of the ultrasonic signals. The defect impulse response is modeled as a Double-Bernoulli-Gaussian sequence. Deconvolution becomes the problem of detection of the optimal Bernoulli sequence and estimation of the associated complex amplitudes. Optimal parameters of the sequence are those which maximize a likelihood function. We develop a new estimation procedure based on an optimization process. An adapted initialization procedure and an iterative algorithm enables to quickly process a huge number of data. Many experimental ultrasonic data that reflect usual control configurations have been processed and the results demonstrate the robustness of the method. Our algorithm enables not only to remove the waveform emitted by the transducer but also to estimate the phase. This parameter is useful for defect characterization. At last the algorithm makes easier data interpretation by concentrating information. So automatic characterization should be possible in the future. (author)
A deconvolution technique for processing small intestinal transit data
Energy Technology Data Exchange (ETDEWEB)
Brinch, K. [Department of Clinical Physiology and Nuclear Medicine, Glostrup Hospital, University Hospital of Copenhagen (Denmark); Larsson, H.B.W. [Danish Research Center of Magnetic Resonance, Hvidovre Hospital, University Hospital of Copenhagen (Denmark); Madsen, J.L. [Department of Clinical Physiology and Nuclear Medicine, Hvidovre Hospital, University Hospital of Copenhagen (Denmark)
1999-03-01
The deconvolution technique can be used to compute small intestinal impulse response curves from scintigraphic data. Previously suggested approaches, however, are sensitive to noise from the data. We investigated whether deconvolution based on a new simple iterative convolving technique can be recommended. Eight healthy volunteers ingested a meal that contained indium-111 diethylene triamine penta-acetic acid labelled water and technetium-99m stannous colloid labelled omelette. Imaging was performed at 30-min intervals until all radioactivity was located in the colon. A Fermi function=(1+e{sup -{alpha}{beta}})/(1+e{sup (t-{alpha}){beta}}) was chosen to characterize the small intestinal impulse response function. By changing only two parameters, {alpha} and {beta}, it is possible to obtain configurations from nearly a square function to nearly a monoexponential function. Small intestinal input function was obtained from the gastric emptying curve and convolved with the Fermi function. The sum of least squares was used to find {alpha} and {beta} yielding the best fit of the convolved curve to the oberved small intestinal time-activity curve. Finally, a small intestinal mean transit time was calculated from the Fermi function referred to. In all cases, we found an excellent fit of the convolved curve to the observed small intestinal time-activity curve, that is the Fermi function reflected the small intestinal impulse response curve. Small intestinal mean transit time of liquid marker (median 2.02 h) was significantly shorter than that of solid marker (median 2.99 h; P<0.02). The iterative convolving technique seems to be an attractive alternative to ordinary approaches for the processing of small intestinal transit data. (orig.) With 2 figs., 13 refs.
SmoothMoves : Smooth pursuits head movements for augmented reality
Esteves, Augusto; Verweij, David; Suraiya, Liza; Islam, Rasel; Lee, Youryang; Oakley, Ian
2017-01-01
SmoothMoves is an interaction technique for augmented reality (AR) based on smooth pursuits head movements. It works by computing correlations between the movements of on-screen targets and the user's head while tracking those targets. The paper presents three studies. The first suggests that head
SU-F-T-478: Effect of Deconvolution in Analysis of Mega Voltage Photon Beam Profiles
Energy Technology Data Exchange (ETDEWEB)
Muthukumaran, M [Apollo Speciality Hospitals, Chennai, Tamil Nadu (India); Manigandan, D [Fortis Cancer Institute, Mohali, Punjab (India); Murali, V; Chitra, S; Ganapathy, K [Apollo Speciality Hospital, Chennai, Tamil Nadu (India); Vikraman, S [JAYPEE HOSPITAL- RADIATION ONCOLOGY, Noida, UTTAR PRADESH (India)
2016-06-15
Purpose: To study and compare the penumbra of 6 MV and 15 MV photon beam profiles after deconvoluting different volume ionization chambers. Methods: 0.125cc Semi-Flex chamber, Markus Chamber and PTW Farmer chamber were used to measure the in-plane and cross-plane profiles at 5 cm depth for 6 MV and 15 MV photons. The profiles were measured for various field sizes starting from 2×2 cm till 30×30 cm. PTW TBA scan software was used for the measurements and the “deconvolution” functionality in the software was used to remove the volume averaging effect due to finite volume of the chamber along lateral and longitudinal directions for all the ionization chambers. The predicted true profile was compared and the change in penumbra before and after deconvolution was studied. Results: After deconvoluting the penumbra decreased by 1 mm for field sizes ranging from 2 × 2 cm till 20 x20 cm. This is observed for along both lateral and longitudinal directions. However for field sizes from 20 × 20 till 30 ×30 cm the difference in penumbra was around 1.2 till 1.8 mm. This was observed for both 6 MV and 15 MV photon beams. The penumbra was always lesser in the deconvoluted profiles for all the ionization chambers involved in the study. The variation in difference in penumbral values were in the order of 0.1 till 0.3 mm between the deconvoluted profile along lateral and longitudinal directions for all the chambers under study. Deconvolution of the profiles along longitudinal direction for Farmer chamber was not good and is not comparable with other deconvoluted profiles. Conclusion: The results of the deconvoluted profiles for 0.125cc and Markus chamber was comparable and the deconvolution functionality can be used to overcome the volume averaging effect.
International Nuclear Information System (INIS)
Puentes, M.B.
1987-01-01
For the analysis of the XPS (X-ray photoelectron spectroscopy) and Auger spectra, it is important to performe the peaks' separation and estimate its intensity. For this purpose, a methodology was implemented, including: a spectrum's filter; b) substraction of the base line (or inelastic background); c) deconvolution (separation of the distribution that integrates the spectrum) and d) error of calculation of the mean estimation, comprising adjustment quality tests. A software (FORTRAN IV plus) that permits to use the methodology proposed from the experimental spectra was implemented. The quality of the methodology was tested with simulated spectra. (Author) [es
International Nuclear Information System (INIS)
Floyd, C.E.; Beatty, P.T.; Ravin, C.E.
1988-01-01
The Fourier deconvolution algorithm for scatter compensation in digital chest radiography has been evaluated in four anatomically different regions at three energies. A shift invariant scatter distribution shape, optimized for the lung region at 140 kVp, was applied at 90 kVp and 120 kVp in the lung, retrocardiac, subdiaphragmatic, and thoracic spine regions. Scatter estimates from the deconvolution were compared with measured values. While some regional variation is apparent, the use of a shift invariant scatter distribution shape (optimized for a given energy) produces reasonable scatter compensation in the chest. A different set of deconvolution parameters were required at the different energies
Carrier tracking by smoothing filter improves symbol SNR
Pomalaza-Raez, Carlos A.; Hurd, William J.
1986-01-01
The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (SNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.
Carrier tracking by smoothing filter can improve symbol SNR
Hurd, W. J.; Pomalaza-Raez, C. A.
1985-01-01
The potential benefit of using a smoothing filter to estimate carrier phase over use of phase locked loops (PLL) is determined. Numerical results are presented for the performance of three possible configurations of the deep space network advanced receiver. These are residual carrier PLL, sideband aided residual carrier PLL, and finally sideband aiding with a Kalman smoother. The average symbol signal to noise ratio (CNR) after losses due to carrier phase estimation error is computed for different total power SNRs, symbol rates and symbol SNRs. It is found that smoothing is most beneficial for low symbol SNRs and low symbol rates. Smoothing gains up to 0.4 dB over a sideband aided residual carrier PLL, and the combined benefit of smoothing and sideband aiding relative to a residual carrier loop is often in excess of 1 dB.
Energy Technology Data Exchange (ETDEWEB)
Sallard, J
1999-07-01
This dissertation presents the development of a new method for restoration of ultrasonic signals. Our goal is to remove the perturbations induced by the ultrasonic probe and to help to characterize the defects due to a strong local discontinuity of the acoustic impedance. The point of view adopted consists in taking into account the physical properties in the signal processing to develop an algorithm which gives good results even on experimental data. The received ultrasonic signal is modeled as a convolution between a function that represents the waveform emitted by the transducer and a function that is abusively called the 'defect impulse response'. It is established that, in numerous cases, the ultrasonic signal can be expressed as a sum of weighted, phase-shifted replicas of a reference signal. Deconvolution is an ill-posed problem. A priori information must be taken into account to solve the problem. The a priori information translates the physical properties of the ultrasonic signals. The defect impulse response is modeled as a Double-Bernoulli-Gaussian sequence. Deconvolution becomes the problem of detection of the optimal Bernoulli sequence and estimation of the associated complex amplitudes. Optimal parameters of the sequence are those which maximize a likelihood function. We develop a new estimation procedure based on an optimization process. An adapted initialization procedure and an iterative algorithm enables to quickly process a huge number of data. Many experimental ultrasonic data that reflect usual control configurations have been processed and the results demonstrate the robustness of the method. Our algorithm enables not only to remove the waveform emitted by the transducer but also to estimate the phase. This parameter is useful for defect characterization. At last the algorithm makes easier data interpretation by concentrating information. So automatic characterization should be possible in the future. (author)
Smoothness in Binomial Edge Ideals
Directory of Open Access Journals (Sweden)
Hamid Damadi
2016-06-01
Full Text Available In this paper we study some geometric properties of the algebraic set associated to the binomial edge ideal of a graph. We study the singularity and smoothness of the algebraic set associated to the binomial edge ideal of a graph. Some of these algebraic sets are irreducible and some of them are reducible. If every irreducible component of the algebraic set is smooth we call the graph an edge smooth graph, otherwise it is called an edge singular graph. We show that complete graphs are edge smooth and introduce two conditions such that the graph G is edge singular if and only if it satisfies these conditions. Then, it is shown that cycles and most of trees are edge singular. In addition, it is proved that complete bipartite graphs are edge smooth.
Blind Deconvolution of Anisoplanatic Images Collected by a Partially Coherent Imaging System
National Research Council Canada - National Science Library
MacDonald, Adam
2004-01-01
... have limited emissivity or reflectivity. This research proposes a novel blind deconvolution algorithm that is based on a maximum a posteriori Bayesian estimator constructed upon a physically based statistical model for the intensity...
Chen, Zhaoxue; Chen, Hao
2014-01-01
A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.
Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program.
Afouxenidis, D; Polymeris, G S; Tsirliganis, N C; Kitis, G
2012-05-01
This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the GLOw Curve ANalysis INtercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters.
Computerised curve deconvolution of TL/OSL curves using a popular spreadsheet program
International Nuclear Information System (INIS)
Afouxenidis, D.; Polymeris, G. S.; Tsirliganis, N. C.; Kitis, G.
2012-01-01
This paper exploits the possibility of using commercial software for thermoluminescence and optically stimulated luminescence curve deconvolution analysis. The widely used software package Microsoft Excel, with the Solver utility has been used to perform deconvolution analysis to both experimental and reference glow curves resulted from the Glow Curve Analysis Intercomparison project. The simple interface of this programme combined with the powerful Solver utility, allows the analysis of complex stimulated luminescence curves into their components and the evaluation of the associated luminescence parameters. (authors)
Csaszar, Elizabeth; Yu, Mei; Morris, Quaid; Zandstra, Peter W.
2012-01-01
The cellular composition of heterogeneous samples can be predicted using an expression deconvolution algorithm to decompose their gene expression profiles based on pre-defined, reference gene expression profiles of the constituent populations in these samples. However, the expression profiles of the actual constituent populations are often perturbed from those of the reference profiles due to gene expression changes in cells associated with microenvironmental or developmental effects. Existing deconvolution algorithms do not account for these changes and give incorrect results when benchmarked against those measured by well-established flow cytometry, even after batch correction was applied. We introduce PERT, a new probabilistic expression deconvolution method that detects and accounts for a shared, multiplicative perturbation in the reference profiles when performing expression deconvolution. We applied PERT and three other state-of-the-art expression deconvolution methods to predict cell frequencies within heterogeneous human blood samples that were collected under several conditions (uncultured mono-nucleated and lineage-depleted cells, and culture-derived lineage-depleted cells). Only PERT's predicted proportions of the constituent populations matched those assigned by flow cytometry. Genes associated with cell cycle processes were highly enriched among those with the largest predicted expression changes between the cultured and uncultured conditions. We anticipate that PERT will be widely applicable to expression deconvolution strategies that use profiles from reference populations that vary from the corresponding constituent populations in cellular state but not cellular phenotypic identity. PMID:23284283
Statistical modelling and deconvolution of yield meter data
DEFF Research Database (Denmark)
Tøgersen, Frede Aakmann; Waagepetersen, Rasmus Plenge
Data for yield maps can be obtained from modern combine harvesters equipped with a differential global positioning system and a yield monitoring system. Due to delay and smoothing effects in the combine harvester the recorded yield data for a location represents a shifted weighted average of yiel...
Toward fully automated genotyping: Genotyping microsatellite markers by deconvolution
Energy Technology Data Exchange (ETDEWEB)
Perlin, M.W.; Lancia, G.; See-Kiong, Ng [Carnegie Mellon Univ., Pittsburgh, PA (United States)
1995-11-01
Dense genetic linkage maps have been constructed for the human and mouse genomes, with average densities of 2.9 cM and 0.35 cM, respectively. These genetic maps are crucial for mapping both Mendelian and complex traits and are useful in clinical genetic diagnosis. Current maps are largely comprised of abundant, easily assayed, and highly polymorphic PCR-based microsatellite markers, primarily dinucleotide (CA){sub n} repeats. One key limitation of these length polymorphisms is the PCR stutter (or slippage) artifact that introduces additional stutter bands. With two (or more) closely spaced alleles, the stutter bands overlap, and it is difficult to accurately determine the correct alleles; this stutter phenomenon has all but precluded full automation, since a human must visually inspect the allele data. We describe here novel deconvolution methods for accurate genotyping that mathematically remove PCR stutter artifact from microsatellite markers. These methods overcome the manual interpretation bottleneck and thereby enable full automation of genetic map construction and use. New functionalities, including the pooling of DNAs and the pooling of markers, are described that may greatly reduce the associated experimentation requirements. 32 refs., 5 figs., 3 tabs.
Blind deconvolution of seismograms regularized via minimum support
International Nuclear Information System (INIS)
Royer, A A; Bostock, M G; Haber, E
2012-01-01
The separation of earthquake source signature and propagation effects (the Earth’s ‘Green’s function’) that encode a seismogram is a challenging problem in seismology. The task of separating these two effects is called blind deconvolution. By considering seismograms of multiple earthquakes from similar locations recorded at a given station and that therefore share the same Green’s function, we may write a linear relation in the time domain u i (t)*s j (t) − u j (t)*s i (t) = 0, where u i (t) is the seismogram for the ith source and s j (t) is the jth unknown source. The symbol * represents the convolution operator. From two or more seismograms, we obtain a homogeneous linear system where the unknowns are the sources. This system is subject to a scaling constraint to deliver a non-trivial solution. Since source durations are not known a priori and must be determined, we augment our system by introducing the source durations as unknowns and we solve the combined system (sources and source durations) using separation of variables. Our solution is derived using direct linear inversion to recover the sources and Newton’s method to recover source durations. This method is tested using two sets of synthetic seismograms created by convolution of (i) random Gaussian source-time functions and (ii) band-limited sources with a simplified Green’s function and signal to noise levels up to 10% with encouraging results. (paper)
Regularization by fractional filter methods and data smoothing
International Nuclear Information System (INIS)
Klann, E; Ramlau, R
2008-01-01
This paper is concerned with the regularization of linear ill-posed problems by a combination of data smoothing and fractional filter methods. For the data smoothing, a wavelet shrinkage denoising is applied to the noisy data with known error level δ. For the reconstruction, an approximation to the solution of the operator equation is computed from the data estimate by fractional filter methods. These fractional methods are based on the classical Tikhonov and Landweber method, but avoid, at least partially, the well-known drawback of oversmoothing. Convergence rates as well as numerical examples are presented
Energy Technology Data Exchange (ETDEWEB)
Zeng, Dong; Zhang, Xinyu; Bian, Zhaoying, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn; Huang, Jing; Zhang, Hua; Lu, Lijun; Lyu, Wenbing; Feng, Qianjin; Chen, Wufan; Ma, Jianhua, E-mail: zybian@smu.edu.cn, E-mail: jhma@smu.edu.cn [Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong 510515, China and Guangdong Provincial Key Laboratory of Medical Image Processing, Southern Medical University, Guangzhou, Guangdong 510515 (China); Zhang, Jing [Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052 (China)
2016-05-15
Purpose: Cerebral perfusion computed tomography (PCT) imaging as an accurate and fast acute ischemic stroke examination has been widely used in clinic. Meanwhile, a major drawback of PCT imaging is the high radiation dose due to its dynamic scan protocol. The purpose of this work is to develop a robust perfusion deconvolution approach via structure tensor total variation (STV) regularization (PD-STV) for estimating an accurate residue function in PCT imaging with the low-milliampere-seconds (low-mAs) data acquisition. Methods: Besides modeling the spatio-temporal structure information of PCT data, the STV regularization of the present PD-STV approach can utilize the higher order derivatives of the residue function to enhance denoising performance. To minimize the objective function, the authors propose an effective iterative algorithm with a shrinkage/thresholding scheme. A simulation study on a digital brain perfusion phantom and a clinical study on an old infarction patient were conducted to validate and evaluate the performance of the present PD-STV approach. Results: In the digital phantom study, visual inspection and quantitative metrics (i.e., the normalized mean square error, the peak signal-to-noise ratio, and the universal quality index) assessments demonstrated that the PD-STV approach outperformed other existing approaches in terms of the performance of noise-induced artifacts reduction and accurate perfusion hemodynamic maps (PHM) estimation. In the patient data study, the present PD-STV approach could yield accurate PHM estimation with several noticeable gains over other existing approaches in terms of visual inspection and correlation analysis. Conclusions: This study demonstrated the feasibility and efficacy of the present PD-STV approach in utilizing STV regularization to improve the accuracy of residue function estimation of cerebral PCT imaging in the case of low-mAs.
Effects of Piecewise Spatial Smoothing in 4-D SPECT Reconstruction
Qi, Wenyuan; Yang, Yongyi; King, Michael A.
2014-02-01
further reduce the error level in the myocardium in 4-D reconstruction along with motion-compensated temporal smoothing. In contrast to quadratic spatial smoothing, TV smoothing could reduce the noise level in the LV at a faster pace than the increase in the bias level, thereby achieving a net decrease in the error level. In particular, at the same noise level, TV smoothing could reduce the bias by about 30% compared to quadratic smoothing. Moreover, the CHO results indicate that TV could also improve the lesion detectability even when the lesion is small. The PAC results show that, at the same noise level, TV smoothing achieved lower temporal bias, which is also consistent with the improved spatial resolution of the LV in reconstruction. The improvement in blurring effects by TV was also observed in the clinical images.
Studing Regional Wave Source Time Functions Using A Massive Automated EGF Deconvolution Procedure
Xie, J. "; Schaff, D. P.
2010-12-01
Reliably estimated source time functions (STF) from high-frequency regional waveforms, such as Lg, Pn and Pg, provide important input for seismic source studies, explosion detection, and minimization of parameter trade-off in attenuation studies. The empirical Green’s function (EGF) method can be used for estimating STF, but it requires a strict recording condition. Waveforms from pairs of events that are similar in focal mechanism, but different in magnitude must be on-scale recorded on the same stations for the method to work. Searching for such waveforms can be very time consuming, particularly for regional waves that contain complex path effects and have reduced S/N ratios due to attenuation. We have developed a massive, automated procedure to conduct inter-event waveform deconvolution calculations from many candidate event pairs. The procedure automatically evaluates the “spikiness” of the deconvolutions by calculating their “sdc”, which is defined as the peak divided by the background value. The background value is calculated as the mean absolute value of the deconvolution, excluding 10 s around the source time function. When the sdc values are about 10 or higher, the deconvolutions are found to be sufficiently spiky (pulse-like), indicating similar path Green’s functions and good estimates of the STF. We have applied this automated procedure to Lg waves and full regional wavetrains from 989 M ≥ 5 events in and around China, calculating about a million deconvolutions. Of these we found about 2700 deconvolutions with sdc greater than 9, which, if having a sufficiently broad frequency band, can be used to estimate the STF of the larger events. We are currently refining our procedure, as well as the estimated STFs. We will infer the source scaling using the STFs. We will also explore the possibility that the deconvolution procedure could complement cross-correlation in a real time event-screening process.
Breast image feature learning with adaptive deconvolutional networks
Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.
2012-03-01
Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).
Deconvolution of the tree ring based delta13C record
International Nuclear Information System (INIS)
Peng, T.; Broecker, W.S.; Freyer, H.D.; Trumbore, S.
1983-01-01
We assumed that the tree-ring based 13 C/ 12 C record constructed by Freyer and Belacy (1983) to be representative of the fossil fuel and forest-soil induced 13 C/ 12 C change for atmospheric CO 2 . Through the use of a modification of the Oeschger et al. ocean model, we have computed the contribution of the combustion of coal, oil, and natural gas to this observed 13 C/ 12 C change. A large residual remains when the tree-ring-based record is corrected for the contribution of fossil fuel CO 2 . A deconvolution was performed on this residual to determine the time history and magnitude of the forest-soil reservoir changes over the past 150 years. Several important conclusions were reached. (1) The magnitude of the integrated CO 2 input from these sources was about 1.6 times that from fossil fuels. (2) The forest-soil contribution reached a broad maximum centered at about 1900. (3) Over the 2 decade period covered by the Mauna Loa atmospheric CO 2 content record, the input from forests and soils was about 30% that from fossil fuels. (4) The 13 C/ 12 C trend over the last 20 years was dominated by the input of fossil fuel CO 2 . (5) The forest-soil release did not contribute significantly to the secular increase in atmospheric CO 2 observed over the last 20 years. (6) The pre-1850 atmospheric p2 values must have been in the range 245 to 270 x 10 -6 atmospheres
Vinay BC; Nikhitha MK; Patel Sunil B
2015-01-01
In this present review article, regarding medication errors its definition, medication error problem, types of medication errors, common causes of medication errors, monitoring medication errors, consequences of medication errors, prevention of medication error and managing medication errors have been explained neatly and legibly with proper tables which is easy to understand.
Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.
2009-02-01
Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.
International Nuclear Information System (INIS)
Raghunath, N; Faber, T L; Suryanarayanan, S; Votaw, J R
2009-01-01
Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.
Energy Technology Data Exchange (ETDEWEB)
Raghunath, N; Faber, T L; Suryanarayanan, S; Votaw, J R [Department of Radiology, Emory University Hospital, 1364 Clifton Road, N.E. Atlanta, GA 30322 (United States)], E-mail: John.Votaw@Emory.edu
2009-02-07
Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.
Wapenaar, K.; van der Neut, J.; Ruigrok, E.; Draganov, D.; Hunziker, J.; Slob, E.; Thorbecke, J.; Snieder, R.
2008-12-01
It is well-known that under specific conditions the crosscorrelation of wavefields observed at two receivers yields the impulse response between these receivers. This principle is known as 'Green's function retrieval' or 'seismic interferometry'. Recently it has been recognized that in many situations it can be advantageous to replace the correlation process by deconvolution. One of the advantages is that deconvolution compensates for the waveform emitted by the source; another advantage is that it is not necessary to assume that the medium is lossless. The approaches that have been developed to date employ a 1D deconvolution process. We propose a method for seismic interferometry by multidimensional deconvolution and show that under specific circumstances the method compensates for irregularities in the source distribution. This is an important difference with crosscorrelation methods, which rely on the condition that waves are equipartitioned. This condition is for example fulfilled when the sources are regularly distributed along a closed surface and the power spectra of the sources are identical. The proposed multidimensional deconvolution method compensates for anisotropic illumination, without requiring knowledge about the positions and the spectra of the sources.
International Nuclear Information System (INIS)
Foltz Biegalski, K.M.; Biegalski, S.R.; Haas, D.A.
2008-01-01
The Spectral Deconvolution Analysis Tool (SDAT) software was developed to improve counting statistics and detection limits for nuclear explosion radionuclide measurements. SDAT utilizes spectral deconvolution spectroscopy techniques and can analyze both β-γ coincidence spectra for radioxenon isotopes and high-resolution HPGe spectra from aerosol monitors. Spectral deconvolution spectroscopy is an analysis method that utilizes the entire signal deposited in a gamma-ray detector rather than the small portion of the signal that is present in one gamma-ray peak. This method shows promise to improve detection limits over classical gamma-ray spectroscopy analytical techniques; however, this hypothesis has not been tested. To address this issue, we performed three tests to compare the detection ability and variance of SDAT results to those of commercial off- the-shelf (COTS) software which utilizes a standard peak search algorithm. (author)
4Pi microscopy deconvolution with a variable point-spread function.
Baddeley, David; Carl, Christian; Cremer, Christoph
2006-09-20
To remove the axial sidelobes from 4Pi images, deconvolution forms an integral part of 4Pi microscopy. As a result of its high axial resolution, the 4Pi point spread function (PSF) is particularly susceptible to imperfect optical conditions within the sample. This is typically observed as a shift in the position of the maxima under the PSF envelope. A significantly varying phase shift renders deconvolution procedures based on a spatially invariant PSF essentially useless. We present a technique for computing the forward transformation in the case of a varying phase at a computational expense of the same order of magnitude as that of the shift invariant case, a method for the estimation of PSF phase from an acquired image, and a deconvolution procedure built on these techniques.
Triggerless Readout with Time and Amplitude Reconstruction of Event Based on Deconvolution Algorithm
International Nuclear Information System (INIS)
Kulis, S.; Idzik, M.
2011-01-01
In future linear colliders like CLIC, where the period between the bunch crossings is in a sub-nanoseconds range ( 500 ps), an appropriate detection technique with triggerless signal processing is needed. In this work we discuss a technique, based on deconvolution algorithm, suitable for time and amplitude reconstruction of an event. In the implemented method the output of a relatively slow shaper (many bunch crossing periods) is sampled and digitalised in an ADC and then the deconvolution procedure is applied to digital data. The time of an event can be found with a precision of few percent of sampling time. The signal to noise ratio is only slightly decreased after passing through the deconvolution filter. The performed theoretical and Monte Carlo studies are confirmed by the results of preliminary measurements obtained with the dedicated system comprising of radiation source, silicon sensor, front-end electronics, ADC and further digital processing implemented on a PC computer. (author)
Deconvolution for the localization of sound sources using a circular microphone array
DEFF Research Database (Denmark)
Tiana Roig, Elisabet; Jacobsen, Finn
2013-01-01
During the last decade, the aeroacoustic community has examined various methods based on deconvolution to improve the visualization of acoustic fields scanned with planar sparse arrays of microphones. These methods assume that the beamforming map in an observation plane can be approximated by a c......-negative least squares, and the Richardson-Lucy. This investigation examines the matter with computer simulations and measurements....... that the beamformer's point-spread function is shift-invariant. This makes it possible to apply computationally efficient deconvolution algorithms that consist of spectral procedures in the entire region of interest, such as the deconvolution approach for the mapping of the acoustic sources 2, the Fourier-based non...
Waveform inversion with exponential damping using a deconvolution-based objective function
Choi, Yun Seok
2016-09-06
The lack of low frequency components in seismic data usually leads full waveform inversion into the local minima of its objective function. An exponential damping of the data, on the other hand, generates artificial low frequencies, which can be used to admit long wavelength updates for waveform inversion. Another feature of exponential damping is that the energy of each trace also exponentially decreases with source-receiver offset, where the leastsquare misfit function does not work well. Thus, we propose a deconvolution-based objective function for waveform inversion with an exponential damping. Since the deconvolution filter includes a division process, it can properly address the unbalanced energy levels of the individual traces of the damped wavefield. Numerical examples demonstrate that our proposed FWI based on the deconvolution filter can generate a convergent long wavelength structure from the artificial low frequency components coming from an exponential damping.
Simulation Study of Effects of the Blind Deconvolution on Ultrasound Image
He, Xingwu; You, Junchen
2018-03-01
Ultrasonic image restoration is an essential subject in Medical Ultrasound Imaging. However, without enough and precise system knowledge, some traditional image restoration methods based on the system prior knowledge often fail to improve the image quality. In this paper, we use the simulated ultrasound image to find the effectiveness of the blind deconvolution method for ultrasound image restoration. Experimental results demonstrate that the blind deconvolution method can be applied to the ultrasound image restoration and achieve the satisfactory restoration results without the precise prior knowledge, compared with the traditional image restoration method. And with the inaccurate small initial PSF, the results shows blind deconvolution could improve the overall image quality of ultrasound images, like much better SNR and image resolution, and also show the time consumption of these methods. it has no significant increasing on GPU platform.
Blind deconvolution using the similarity of multiscales regularization for infrared spectrum
International Nuclear Information System (INIS)
Huang, Tao; Liu, Hai; Zhang, Zhaoli; Liu, Sanyan; Liu, Tingting; Shen, Xiaoxuan; Zhang, Jianfeng; Zhang, Tianxu
2015-01-01
Band overlap and random noise exist widely when the spectra are captured using an infrared spectrometer, especially since the aging of instruments has become a serious problem. In this paper, via introducing the similarity of multiscales, a blind spectral deconvolution method is proposed. Considering that there is a similarity between latent spectra at different scales, it is used as prior knowledge to constrain the estimated latent spectrum similar to pre-scale to reduce artifacts which are produced from deconvolution. The experimental results indicate that the proposed method is able to obtain a better performance than state-of-the-art methods, and to obtain satisfying deconvolution results with fewer artifacts. The recovered infrared spectra can easily extract the spectral features and recognize unknown objects. (paper)
Image processing of globular clusters - Simulation for deconvolution tests (GlencoeSim)
Blazek, Martin; Pata, Petr
2016-10-01
This paper presents an algorithmic approach for efficiency tests of deconvolution algorithms in astronomic image processing. Due to the existence of noise in astronomical data there is no certainty that a mathematically exact result of stellar deconvolution exists and iterative or other methods such as aperture or PSF fitting photometry are commonly used. Iterative methods are important namely in the case of crowded fields (e.g., globular clusters). For tests of the efficiency of these iterative methods on various stellar fields, information about the real fluxes of the sources is essential. For this purpose a simulator of artificial images with crowded stellar fields provides initial information on source fluxes for a robust statistical comparison of various deconvolution methods. The "GlencoeSim" simulator and the algorithms presented in this paper consider various settings of Point-Spread Functions, noise types and spatial distributions, with the aim of producing as realistic an astronomical optical stellar image as possible.
Optimisation of digital noise filtering in the deconvolution of ultrafast kinetic data
International Nuclear Information System (INIS)
Banyasz, Akos; Dancs, Gabor; Keszei, Erno
2005-01-01
Ultrafast kinetic measurements in the sub-picosecond time range are always distorted by a convolution with the instrumental response function. To restore the undistorted signal, deconvolution of the measured data is needed, which can be done via inverse filtering, using Fourier transforms, if experimental noise can be successfully filtered. However, in the case of experimental data when no underlying physical model is available, no quantitative criteria are known to find an optimal noise filter which would remove excessive noise without distorting the signal itself. In this paper, we analyse the Fourier transforms used during deconvolution and describe a graphical method to find such optimal noise filters. Comparison of graphically found optima to those found by quantitative criteria in the case of known synthetic kinetic signals shows the reliability of the proposed method to get fairly good deconvolved kinetic curves. A few examples of deconvolution of real-life experimental curves with the graphical noise filter optimisation are also shown
Energy Technology Data Exchange (ETDEWEB)
Vinyard, Natalia Sergeevna [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Perry, Theodore Sonne [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Usov, Igor Olegovich [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-10-04
We calculate opacity from k (hn)=-ln[T(hv)]/pL, where T(hv) is the transmission for photon energy hv, p is sample density, and L is path length through the sample. The density and path length are measured together by Rutherford backscatter. Δk = $\\partial k$\\ $\\partial T$ ΔT + $\\partial k$\\ $\\partial (pL)$. We can re-write this in terms of fractional error as Δk/k = Δ1n(T)/T + Δ(pL)/(pL). Transmission itself is calculated from T=(U-E)/(V-E)=B/B0, where B is transmitted backlighter (BL) signal and B_{0} is unattenuated backlighter signal. Then ΔT/T=Δln(T)=ΔB/B+ΔB_{0}/B_{0}, and consequently Δk/k = 1/T (ΔB/B + ΔB$_0$/B$_0$ + Δ(pL)/(pL). Transmission is measured in the range of 0.2
2000-01-01
The book provides a self-contained introduction to the mathematical theory of non-smooth dynamical problems, as they frequently arise from mechanical systems with friction and/or impacts. It is aimed at applied mathematicians, engineers, and applied scientists in general who wish to learn the subject.
Panel Smooth Transition Regression Models
DEFF Research Database (Denmark)
González, Andrés; Terasvirta, Timo; Dijk, Dick van
We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bou...
Smoothing type buffer memory device
International Nuclear Information System (INIS)
Podorozhnyj, D.M.; Yashin, I.V.
1990-01-01
The layout of the micropower 4-bit smoothing type buffer memory device allowing one to record without counting the sequence of input randomly distributed pulses in multi-channel devices with serial poll, is given. The power spent by a memory cell for one binary digit recording is not greater than 0.15 mW, the device dead time is 10 mus
Covariances of smoothed observational data
Czech Academy of Sciences Publication Activity Database
Vondrák, Jan; Čepek, A.
2000-01-01
Roč. 40, 5-6 (2000), s. 42-44 ISSN 1210-2709 R&D Projects: GA ČR GA205/98/1104 Institutional research plan: CEZ:AV0Z1003909 Keywords : digital filter * smoothing * estimation of uncertainties Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics
Income smoothing by Dutch hospitals
Boterenbrood, D.R.
2014-01-01
Research indicates that hospitals manage their earnings. However, these findings might be influenced by methodological issues. In this study, I exploit specific features of Dutch hospitals to study income smoothing while limiting these methodological issues. The managers of Dutch hospitals have the
Ensemble Kalman filtering with one-step-ahead smoothing
Raboudi, Naila F.
2018-01-11
The ensemble Kalman filter (EnKF) is widely used for sequential data assimilation. It operates as a succession of forecast and analysis steps. In realistic large-scale applications, EnKFs are implemented with small ensembles and poorly known model error statistics. This limits their representativeness of the background error covariances and, thus, their performance. This work explores the efficiency of the one-step-ahead (OSA) smoothing formulation of the Bayesian filtering problem to enhance the data assimilation performance of EnKFs. Filtering with OSA smoothing introduces an updated step with future observations, conditioning the ensemble sampling with more information. This should provide an improved background ensemble in the analysis step, which may help to mitigate the suboptimal character of EnKF-based methods. Here, the authors demonstrate the efficiency of a stochastic EnKF with OSA smoothing for state estimation. They then introduce a deterministic-like EnKF-OSA based on the singular evolutive interpolated ensemble Kalman (SEIK) filter. The authors show that the proposed SEIK-OSA outperforms both SEIK, as it efficiently exploits the data twice, and the stochastic EnKF-OSA, as it avoids observational error undersampling. They present extensive assimilation results from numerical experiments conducted with the Lorenz-96 model to demonstrate SEIK-OSA’s capabilities.
Combined failure acoustical diagnosis based on improved frequency domain blind deconvolution
International Nuclear Information System (INIS)
Pan, Nan; Wu, Xing; Chi, YiLin; Liu, Xiaoqin; Liu, Chang
2012-01-01
According to gear box combined failure extraction in complex sound field, an acoustic fault detection method based on improved frequency domain blind deconvolution was proposed. Follow the frequency-domain blind deconvolution flow, the morphological filtering was firstly used to extract modulation features embedded in the observed signals, then the CFPA algorithm was employed to do complex-domain blind separation, finally the J-Divergence of spectrum was employed as distance measure to resolve the permutation. Experiments using real machine sound signals was carried out. The result demonstrate this algorithm can be efficiently applied to gear box combined failure detection in practice.
International Nuclear Information System (INIS)
Kitis, G.; Gomez-Ros, J.M.
2000-01-01
New glow-curve deconvolution functions are proposed for mixed order of kinetics and for continuous-trap distribution. The only free parameters of the presented glow-curve deconvolution functions are the maximum peak intensity (I m ) and the maximum peak temperature (T m ), which can be estimated experimentally together with the activation energy (E). The other free parameter is the activation energy range (ΔE) for the case of the continuous-trap distribution or a constant α for the case of mixed-order kinetics
International Nuclear Information System (INIS)
Tang Bin; Liu Ling; Zhou Shumin; Zhou Rongsheng
2006-01-01
The paper discusses the gamma-ray spectrum interpretation technology on nuclear logging. The principles of familiar quantitative interpretation methods, including the average content method and the traditional spectrum striping method, are introduced, and their limitation of determining the contents of radioactive elements on unsaturated ledges (where radioactive elements distribute unevenly) is presented. On the basis of the intensity gamma-logging quantitative interpretation technology by using the deconvolution method, a new quantitative interpretation method of separating radioactive elements is presented for interpreting the gamma spectrum logging. This is a point-by-point spectrum striping deconvolution technology which can give the logging data a quantitative interpretation. (authors)
International Nuclear Information System (INIS)
Bandzuch, P.; Morhac, M.; Kristiak, J.
1997-01-01
The study of deconvolution by Van Cittert and Gold iterative algorithms and their use in the processing of experimental spectra of Doppler broadening of the annihilation line in positron annihilation measurement is described. By comparing results from both algorithms it was observed that the Gold algorithm was able to eliminate linear instability of the measuring equipment if one uses the 1274 keV 22 Na peak, that was measured simultaneously with the annihilation peak, for deconvolution of annihilation peak 511 keV. This permitted the measurement of small changes of the annihilation peak (e.g. S-parameter) with high confidence. The dependence of γ-ray-like peak parameters on the number of iterations and the ability of these algorithms to distinguish a γ-ray doublet with different intensities and positions were also studied. (orig.)
Accounting for optical errors in microtensiometry.
Hinton, Zachary R; Alvarez, Nicolas J
2018-09-15
Drop shape analysis (DSA) techniques measure interfacial tension subject to error in image analysis and the optical system. While considerable efforts have been made to minimize image analysis errors, very little work has treated optical errors. There are two main sources of error when considering the optical system: the angle of misalignment and the choice of focal plane. Due to the convoluted nature of these sources, small angles of misalignment can lead to large errors in measured curvature. We demonstrate using microtensiometry the contributions of these sources to measured errors in radius, and, more importantly, deconvolute the effects of misalignment and focal plane. Our findings are expected to have broad implications on all optical techniques measuring interfacial curvature. A geometric model is developed to analytically determine the contributions of misalignment angle and choice of focal plane on measurement error for spherical cap interfaces. This work utilizes a microtensiometer to validate the geometric model and to quantify the effect of both sources of error. For the case of a microtensiometer, an empirical calibration is demonstrated that corrects for optical errors and drastically simplifies implementation. The combination of geometric modeling and experimental results reveal a convoluted relationship between the true and measured interfacial radius as a function of the misalignment angle and choice of focal plane. The validated geometric model produces a full operating window that is strongly dependent on the capillary radius and spherical cap height. In all cases, the contribution of optical errors is minimized when the height of the spherical cap is equivalent to the capillary radius, i.e. a hemispherical interface. The understanding of these errors allow for correct measure of interfacial curvature and interfacial tension regardless of experimental setup. For the case of microtensiometry, this greatly decreases the time for experimental setup
Exchange rate smoothing in Hungary
Karádi, Péter
2005-01-01
The paper proposes a structural empirical model capable of examining exchange rate smoothing in the small, open economy of Hungary. The framework assumes the existence of an unobserved and changing implicit exchange rate target. The central bank is assumed to use interest rate policy to obtain this preferred rate in the medium term, while market participants are assumed to form rational expectations about this target and influence exchange rates accordingly. The paper applies unobserved varia...
Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation
DEFF Research Database (Denmark)
Schmidt, Mikkel N.; Mørup, Morten
2006-01-01
We present a novel method for blind separation of instruments in polyphonic music based on a non-negative matrix factor 2-D deconvolution algorithm. Using a model which is convolutive in both time and frequency we factorize a spectrogram representation of music into components corresponding...
Novel response function resolves by image deconvolution more details of surface nanomorphology
DEFF Research Database (Denmark)
Andersen, Jens Enevold Thaulov
2010-01-01
and to imaging by in situ STM of electrocrystallization of copper on gold in electrolytes containing copper sulfate and sulfuric acid. It is suggested that the observed peaks of the recorded image do not represent atoms, but the atomic structure may be recovered by image deconvolution followed by calibration...
Inter-source seismic interferometry by multidimensional deconvolution (MDD) for borehole sources
Liu, Y.; Wapenaar, C.P.A.; Romdhane, A.
2014-01-01
Seismic interferometry (SI) is usually implemented by crosscorrelation (CC) to retrieve the impulse response between pairs of receiver positions. An alternative approach by multidimensional deconvolution (MDD) has been developed and shown in various studies the potential to suppress artifacts due to
Wink, Alle Meije; Hoogduin, Hans; Roerdink, Jos B.T.M.
2008-01-01
Background: We present a simple, data-driven method to extract haemodynamic response functions (HRF) from functional magnetic resonance imaging (fMRI) time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD) technique. HRF data are required for many fMRI applications, such as
Wink, Alle Meije; Hoogduin, Hans; Roerdink, Jos B.T.M.
2010-01-01
Background: We present a simple, data-driven method to extract haemodynamic response functions (HRF) from functional magnetic resonance imaging (fMRI) time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD) technique. HRF data are required for many fMRI applications, such as
Deconvolution in the presence of noise using the Maximum Entropy Principle
International Nuclear Information System (INIS)
Steenstrup, S.
1984-01-01
The main problem in deconvolution in the presence of noise is the nonuniqueness. This problem is overcome by the application of the Maximum Entropy Principle. The way the noise enters in the formulation of the problem is examined in some detail and the final equations are derived such that the necessary assumptions becomes explicit. Examples using X-ray diffraction data are shown. (orig.)
DEFF Research Database (Denmark)
Lylloff, Oliver Ackermann; Fernandez Grande, Efren
Delay-and-sum (DAS) beamforming can be described as a linear convolution of an unknown sound source distribution and the microphone array response to a point source, i.e., point-spread function. Deconvolution tries to compensate for the influence of the array response and reveal the true source...
Lineshape estimation for magnetic resonance spectroscopy (MRS) signals: self-deconvolution revisited
International Nuclear Information System (INIS)
Sima, D M; Garcia, M I Osorio; Poullet, J; Van Huffel, S; Suvichakorn, A; Antoine, J-P; Van Ormondt, D
2009-01-01
Magnetic resonance spectroscopy (MRS) is an effective diagnostic technique for monitoring biochemical changes in an organism. The lineshape of MRS signals can deviate from the theoretical Lorentzian lineshape due to inhomogeneities of the magnetic field applied to patients and to tissue heterogeneity. We call this deviation a distortion and study the self-deconvolution method for automatic estimation of the unknown lineshape distortion. The method is embedded within a time-domain metabolite quantitation algorithm for short-echo-time MRS signals. Monte Carlo simulations are used to analyze whether estimation of the unknown lineshape can improve the overall quantitation result. We use a signal with eight metabolic components inspired by typical MRS signals from healthy human brain and allocate special attention to the step of denoising and spike removal in the self-deconvolution technique. To this end, we compare several modeling techniques, based on complex damped exponentials, splines and wavelets. Our results show that self-deconvolution performs well, provided that some unavoidable hyper-parameters of the denoising methods are well chosen. Comparison of the first and last iterations shows an improvement when considering iterations instead of a single step of self-deconvolution
Application of deconvolution interferometry with both Hi-net and KiK-net data
Nakata, N.
2013-12-01
Application of deconvolution interferometry to wavefields observed by KiK-net, a strong-motion recording network in Japan, is useful for estimating wave velocities and S-wave splitting in the near surface. Using this technique, for example, Nakata and Snieder (2011, 2012) found changed in velocities caused by Tohoku-Oki earthquake in Japan. At the location of the borehole accelerometer of each KiK-net station, a velocity sensor is also installed as a part of a high-sensitivity seismograph network (Hi-net). I present a technique that uses both Hi-net and KiK-net records for computing deconvolution interferometry. The deconvolved waveform obtained from the combination of Hi-net and KiK-net data is similar to the waveform computed from KiK-net data only, which indicates that one can use Hi-net wavefields for deconvolution interferometry. Because Hi-net records have a high signal-to-noise ratio (S/N) and high dynamic resolution, the S/N and the quality of amplitude and phase of deconvolved waveforms can be improved with Hi-net data. These advantages are especially important for short-time moving-window seismic interferometry and deconvolution interferometry using later coda waves.
Sparse Non-negative Matrix Factor 2-D Deconvolution for Automatic Transcription of Polyphonic Music
DEFF Research Database (Denmark)
Schmidt, Mikkel N.; Mørup, Morten
2006-01-01
We present a novel method for automatic transcription of polyphonic music based on a recently published algorithm for non-negative matrix factor 2-D deconvolution. The method works by simultaneously estimating a time-frequency model for an instrument and a pattern corresponding to the notes which...... are played based on a log-frequency spectrogram of the music....
International Nuclear Information System (INIS)
Looe, H.K.; Uphoff, Y.; Poppe, B.; Carl von Ossietzky Univ., Oldenburg; Harder, D.; Willborn, K.C.
2012-01-01
The quality of megavoltage clinical portal images is impaired by physical and geometrical effects. This image blurring can be corrected by a fast numerical two-dimensional (2D) deconvolution algorithm implemented in the electronic portal image device. We present some clinical examples of deconvolved portal images and evaluate the clinical advantages achieved by the improved sharpness and contrast. The principle of numerical 2D image deconvolution and the enhancement of sharpness and contrast thereby achieved are shortly explained. The key concept is the convolution kernel K(x,y), the mathematical equivalent of the smearing or blurring of a picture, and the computer-based elimination of this influence. Enhancements of sharpness and contrast were observed in all clinical portal images investigated. The images of fine bone structures were restored. The identification of organ boundaries and anatomical landmarks was improved, thereby permitting a more accurate comparison with the x-ray simulator radiographs. The visibility of prostate gold markers is also shown to be enhanced by deconvolution. The blurring effects of clinical portal images were eliminated by a numerical deconvolution algorithm that leads to better image sharpness and contrast. The fast algorithm permits the image blurring correction to be performed in real time, so that patient positioning verification with increased accuracy can be achieved in clinical practice. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Looe, H.K.; Uphoff, Y.; Poppe, B. [Pius Hospital, Oldenburg (Germany). Clinic for Radiation Therapy; Carl von Ossietzky Univ., Oldenburg (Germany). WG Medical Radiation Physics; Harder, D. [Georg August Univ., Goettingen (Germany). Medical Physics and Biophysics; Willborn, K.C. [Pius Hospital, Oldenburg (Germany). Clinic for Radiation Therapy
2012-02-15
The quality of megavoltage clinical portal images is impaired by physical and geometrical effects. This image blurring can be corrected by a fast numerical two-dimensional (2D) deconvolution algorithm implemented in the electronic portal image device. We present some clinical examples of deconvolved portal images and evaluate the clinical advantages achieved by the improved sharpness and contrast. The principle of numerical 2D image deconvolution and the enhancement of sharpness and contrast thereby achieved are shortly explained. The key concept is the convolution kernel K(x,y), the mathematical equivalent of the smearing or blurring of a picture, and the computer-based elimination of this influence. Enhancements of sharpness and contrast were observed in all clinical portal images investigated. The images of fine bone structures were restored. The identification of organ boundaries and anatomical landmarks was improved, thereby permitting a more accurate comparison with the x-ray simulator radiographs. The visibility of prostate gold markers is also shown to be enhanced by deconvolution. The blurring effects of clinical portal images were eliminated by a numerical deconvolution algorithm that leads to better image sharpness and contrast. The fast algorithm permits the image blurring correction to be performed in real time, so that patient positioning verification with increased accuracy can be achieved in clinical practice. (orig.)
A fast Fourier transform program for the deconvolution of IN10 data
International Nuclear Information System (INIS)
Howells, W.S.
1981-04-01
A deconvolution program based on the Fast Fourier Transform technique is described and some examples are presented to help users run the programs and interpret the results. Instructions are given for running the program on the RAL IBM 360/195 computer. (author)
Zheng, Yinggan; Gierl, Mark J.; Cui, Ying
2010-01-01
This study combined the kernel smoothing procedure and a nonparametric differential item functioning statistic--Cochran's Z--to statistically test the difference between the kernel-smoothed item response functions for reference and focal groups. Simulation studies were conducted to investigate the Type I error and power of the proposed…
A User Guide for Smoothing Air Traffic Radar Data
Bach, Ralph E.; Paielli, Russell A.
2014-01-01
Matlab software was written to provide smoothing of radar tracking data to simulate ADS-B (Automatic Dependent Surveillance-Broadcast) data in order to test a tactical conflict probe. The probe, called TSAFE (Tactical Separation-Assured Flight Environment), is designed to handle air-traffic conflicts left undetected or unresolved when loss-of-separation is predicted to occur within approximately two minutes. The data stream that is down-linked from an aircraft equipped with an ADS-B system would include accurate GPS-derived position and velocity information at sample rates of 1 Hz. Nation-wide ADS-B equipage (mandated by 2020) should improve surveillance accuracy and TSAFE performance. Currently, position data are provided by Center radar (nominal 12-sec samples) and Terminal radar (nominal 4.8-sec samples). Aircraft ground speed and ground track are estimated using real-time filtering, causing lags up to 60 sec, compromising performance of a tactical resolution tool. Offline smoothing of radar data reduces wild-point errors, provides a sample rate as high as 1 Hz, and yields more accurate and lag-free estimates of ground speed, ground track, and climb rate. Until full ADS-B implementation is available, smoothed radar data should provide reasonable track estimates for testing TSAFE in an ADS-B-like environment. An example illustrates the smoothing of radar data and shows a comparison of smoothed-radar and ADS-B tracking. This document is intended to serve as a guide for using the smoothing software.
International Nuclear Information System (INIS)
Vigineix, Thomas; Guillot, Nicolas; Saurel, Nicolas
2013-06-01
Gamma ray spectrometry is a passive non destructive assay most commonly used to identify and quantify the radionuclides present in complex huge objects such as nuclear waste packages. The treatment of spectra from the measurement of nuclear waste is done in two steps: the first step is to extract the raw data from the spectra (energies and the net photoelectric absorption peaks area) and the second step is to determine the detection efficiency of the measuring scene. Commercial software use different methods to extract the raw data spectrum but none are optimal in the treatment of spectra containing actinides. Spectra should be handled individually and requires settings and an important feedback part from the operator, which prevents the automatic process of spectrum and increases the risk of human error. In this context the Nuclear Measurement and Valuation Laboratory (LMNE) in the Atomic Energy Commission Valduc (CEA Valduc) has developed a new methodology for quantifying the uncertainty associated with the extraction of the raw data over spectrum. This methodology was applied with raw data and commercial software that need configuration by the operator (GENIE2000, Interwinner...). This robust and fully automated methodology of uncertainties calculation is performed on the entire process of the software. The methodology ensures for all peaks processed by the deconvolution software an extraction of energy peaks closed to 2 channels and an extraction of net areas with an uncertainty less than 5 percents. The methodology was tested experimentally with actinides spectrum. (authors)
Smooth surfaces from rational bilinear patches
Shi, Ling; Wang, Jun; Pottmann, Helmut
2014-01-01
Smooth freeform skins from simple panels constitute a challenging topic arising in contemporary architecture. We contribute to this problem area by showing how to approximate a negatively curved surface by smoothly joined rational bilinear patches
Semiparametric Bernstein–von Mises for the error standard deviation
Jonge, de, R.; Zanten, van, J.H.
2013-01-01
We study Bayes procedures for nonparametric regression problems with Gaussian errors, giving conditions under which a Bernstein–von Mises result holds for the marginal posterior distribution of the error standard deviation. We apply our general results to show that a single Bayes procedure using a hierarchical spline-based prior on the regression function and an independent prior on the error variance, can simultaneously achieve adaptive, rate-optimal estimation of a smooth, multivariate regr...
Calcium dynamics in vascular smooth muscle
Amberg, Gregory C.; Navedo, Manuel F.
2013-01-01
Smooth muscle cells are ultimately responsible for determining vascular luminal diameter and blood flow. Dynamic changes in intracellular calcium are a critical mechanism regulating vascular smooth muscle contractility. Processes influencing intracellular calcium are therefore important regulators of vascular function with physiological and pathophysiological consequences. In this review we discuss the major dynamic calcium signals identified and characterized in vascular smooth muscle cells....
multiscale smoothing in supervised statistical learning
Indian Academy of Sciences (India)
Optimum level of smoothing is chosen based on the entire training sample, while a good choice of smoothing parameter may also depend on the observation to be classified. One may like to assess the strength of evidence in favor of different competing class at different scale of smoothing. In allows only one single ...
A SAS IML Macro for Loglinear Smoothing
Moses, Tim; von Davier, Alina
2011-01-01
Polynomial loglinear models for one-, two-, and higher-way contingency tables have important applications to measurement and assessment. They are essentially regarded as a smoothing technique, which is commonly referred to as loglinear smoothing. A SAS IML (SAS Institute, 2002a) macro was created to implement loglinear smoothing according to…
Smooth extrapolation of unknown anatomy via statistical shape models
Grupp, R. B.; Chiang, H.; Otake, Y.; Murphy, R. J.; Gordon, C. R.; Armand, M.; Taylor, R. H.
2015-03-01
Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical images of incomplete anatomy. Le Fort-based, face-jaw-teeth transplant is one such procedure. From CT data of 36 skulls and 21 mandibles separate Statistical Shape Models of the anatomical surfaces were created. Using the Statistical Shape Models, incomplete surfaces were projected to obtain complete surface estimates. The surface estimates exhibit non-zero error in regions where the true surface is known; it is desirable to keep the true surface and seamlessly merge the estimated unknown surface. Existing extrapolation techniques produce non-smooth transitions from the true surface to the estimated surface, resulting in additional error and a less aesthetically pleasing result. The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface. Feathering and Thin Plate Spline approaches both yielded smooth transitions. However, feathering corrupted known vertex values. Leave-one-out analyses were conducted, with 5% to 50% of known anatomy removed from the left-out patient and estimated via the proposed approaches. The Thin Plate Spline approach yielded smaller errors than the other two approaches, with an average vertex error improvement of 1.46 mm and 1.38 mm for the skull and mandible respectively, over the baseline approach.
Modeling coherent errors in quantum error correction
Greenbaum, Daniel; Dutton, Zachary
2018-01-01
Analysis of quantum error correcting codes is typically done using a stochastic, Pauli channel error model for describing the noise on physical qubits. However, it was recently found that coherent errors (systematic rotations) on physical data qubits result in both physical and logical error rates that differ significantly from those predicted by a Pauli model. Here we examine the accuracy of the Pauli approximation for noise containing coherent errors (characterized by a rotation angle ɛ) under the repetition code. We derive an analytic expression for the logical error channel as a function of arbitrary code distance d and concatenation level n, in the small error limit. We find that coherent physical errors result in logical errors that are partially coherent and therefore non-Pauli. However, the coherent part of the logical error is negligible at fewer than {ε }-({dn-1)} error correction cycles when the decoder is optimized for independent Pauli errors, thus providing a regime of validity for the Pauli approximation. Above this number of correction cycles, the persistent coherent logical error will cause logical failure more quickly than the Pauli model would predict, and this may need to be combated with coherent suppression methods at the physical level or larger codes.
Comparative Analysis for Robust Penalized Spline Smoothing Methods
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Bin Wang
2014-01-01
Full Text Available Smoothing noisy data is commonly encountered in engineering domain, and currently robust penalized regression spline models are perceived to be the most promising methods for coping with this issue, due to their flexibilities in capturing the nonlinear trends in the data and effectively alleviating the disturbance from the outliers. Against such a background, this paper conducts a thoroughly comparative analysis of two popular robust smoothing techniques, the M-type estimator and S-estimation for penalized regression splines, both of which are reelaborated starting from their origins, with their derivation process reformulated and the corresponding algorithms reorganized under a unified framework. Performances of these two estimators are thoroughly evaluated from the aspects of fitting accuracy, robustness, and execution time upon the MATLAB platform. Elaborately comparative experiments demonstrate that robust penalized spline smoothing methods possess the capability of resistance to the noise effect compared with the nonrobust penalized LS spline regression method. Furthermore, the M-estimator exerts stable performance only for the observations with moderate perturbation error, whereas the S-estimator behaves fairly well even for heavily contaminated observations, but consuming more execution time. These findings can be served as guidance to the selection of appropriate approach for smoothing the noisy data.
Comparison of some nonlinear smoothing methods
International Nuclear Information System (INIS)
Bell, P.R.; Dillon, R.S.
1977-01-01
Due to the poor quality of many nuclear medicine images, computer-driven smoothing procedures are frequently employed to enhance the diagnostic utility of these images. While linear methods were first tried, it was discovered that nonlinear techniques produced superior smoothing with little detail suppression. We have compared four methods: Gaussian smoothing (linear), two-dimensional least-squares smoothing (linear), two-dimensional least-squares bounding (nonlinear), and two-dimensional median smoothing (nonlinear). The two dimensional least-squares procedures have yielded the most satisfactorily enhanced images, with the median smoothers providing quite good images, even in the presence of widely aberrant points
Smooth random change point models.
van den Hout, Ardo; Muniz-Terrera, Graciela; Matthews, Fiona E
2011-03-15
Change point models are used to describe processes over time that show a change in direction. An example of such a process is cognitive ability, where a decline a few years before death is sometimes observed. A broken-stick model consists of two linear parts and a breakpoint where the two lines intersect. Alternatively, models can be formulated that imply a smooth change between the two linear parts. Change point models can be extended by adding random effects to account for variability between subjects. A new smooth change point model is introduced and examples are presented that show how change point models can be estimated using functions in R for mixed-effects models. The Bayesian inference using WinBUGS is also discussed. The methods are illustrated using data from a population-based longitudinal study of ageing, the Cambridge City over 75 Cohort Study. The aim is to identify how many years before death individuals experience a change in the rate of decline of their cognitive ability. Copyright © 2010 John Wiley & Sons, Ltd.
Calcium signaling in smooth muscle.
Hill-Eubanks, David C; Werner, Matthias E; Heppner, Thomas J; Nelson, Mark T
2011-09-01
Changes in intracellular Ca(2+) are central to the function of smooth muscle, which lines the walls of all hollow organs. These changes take a variety of forms, from sustained, cell-wide increases to temporally varying, localized changes. The nature of the Ca(2+) signal is a reflection of the source of Ca(2+) (extracellular or intracellular) and the molecular entity responsible for generating it. Depending on the specific channel involved and the detection technology employed, extracellular Ca(2+) entry may be detected optically as graded elevations in intracellular Ca(2+), junctional Ca(2+) transients, Ca(2+) flashes, or Ca(2+) sparklets, whereas release of Ca(2+) from intracellular stores may manifest as Ca(2+) sparks, Ca(2+) puffs, or Ca(2+) waves. These diverse Ca(2+) signals collectively regulate a variety of functions. Some functions, such as contractility, are unique to smooth muscle; others are common to other excitable cells (e.g., modulation of membrane potential) and nonexcitable cells (e.g., regulation of gene expression).
Evaluating data acquisition and smoothing functions of currently available videokeratoscopes.
Belin, M W; Ratliff, C D
1996-05-01
To compare the accuracy of computerized videokeratography systems using identical, calibrated test objects. Lions Eye Institute, Albany, New York. We evaluated the accuracy and smoothing of raw data acquisition (axial solution) of seven commercially available videokeratoscopes: Alcon EyeMap, Computed Anatomy TMS, EyeSys CAS, Humphrey MasterVue, Topcon CM-1000, Optikon Keratron, and TechnoMed C-Scan. We used six calibrated test objects to simulate clinical settings: spherical, spherocylindrical, simulated myopic ablation, hyperopic ablation, and a simulated central island. None of the systems accurately imaged all objects. Although all systems imaged spherical objects with reasonable accuracy, errors greater than 4.0 diopters (D) frequently occurred in the central 6.0 mm optical zone (maximum error 10.0 D) Sources of error included excessive raw data smoothing, inability to read large transitions, loss of accuracy in the periphery, and poor central coverage. The clinician should be aware of the potential limitations of corneal topography when making clinical decisions.
Arima model and exponential smoothing method: A comparison
Wan Ahmad, Wan Kamarul Ariffin; Ahmad, Sabri
2013-04-01
This study shows the comparison between Autoregressive Moving Average (ARIMA) model and Exponential Smoothing Method in making a prediction. The comparison is focused on the ability of both methods in making the forecasts with the different number of data sources and the different length of forecasting period. For this purpose, the data from The Price of Crude Palm Oil (RM/tonne), Exchange Rates of Ringgit Malaysia (RM) in comparison to Great Britain Pound (GBP) and also The Price of SMR 20 Rubber Type (cents/kg) with three different time series are used in the comparison process. Then, forecasting accuracy of each model is measured by examinethe prediction error that producedby using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE), and Mean Absolute deviation (MAD). The study shows that the ARIMA model can produce a better prediction for the long-term forecasting with limited data sources, butcannot produce a better prediction for time series with a narrow range of one point to another as in the time series for Exchange Rates. On the contrary, Exponential Smoothing Method can produce a better forecasting for Exchange Rates that has a narrow range of one point to another for its time series, while itcannot produce a better prediction for a longer forecasting period.
National Research Council Canada - National Science Library
Matson, Charles; Haji, Aiim
2006-01-01
Multi-frame blind deconvolution (MFBD) algorithms can be used to reconstruct a single high-resolution image of an object from one or more measurement frames of that are blurred and noisy realizations of that object...
International Nuclear Information System (INIS)
Houghton, J.R.; Packman, P.F.; Townsend, M.A.
1976-01-01
Acoustic emission signals recorded after passage through the instrumentation system can be deconvoluted to produce signal traces indicative of those at the generating source, and these traces can be used to identify characteristics of the source
Zeng, Fanhai; Zhang, Zhongqiang; Karniadakis, George Em
2017-12-01
Starting with the asymptotic expansion of the error equation of the shifted Gr\\"{u}nwald--Letnikov formula, we derive a new modified weighted shifted Gr\\"{u}nwald--Letnikov (WSGL) formula by introducing appropriate correction terms. We then apply one special case of the modified WSGL formula to solve multi-term fractional ordinary and partial differential equations, and we prove the linear stability and second-order convergence for both smooth and non-smooth solutions. We show theoretically and numerically that numerical solutions up to certain accuracy can be obtained with only a few correction terms. Moreover, the correction terms can be tuned according to the fractional derivative orders without explicitly knowing the analytical solutions. Numerical simulations verify the theoretical results and demonstrate that the new formula leads to better performance compared to other known numerical approximations with similar resolution.
Learning from prescribing errors
Dean, B
2002-01-01
The importance of learning from medical error has recently received increasing emphasis. This paper focuses on prescribing errors and argues that, while learning from prescribing errors is a laudable goal, there are currently barriers that can prevent this occurring. Learning from errors can take place on an individual level, at a team level, and across an organisation. Barriers to learning from prescribing errors include the non-discovery of many prescribing errors, lack of feedback to th...
International Nuclear Information System (INIS)
Vivet, L.
1989-01-01
The ultrasonic echography has a lot of advantages which make it attractive for nondestructive testing. But the important acoustic energy useful to go through very attenuating materials can be got only with resonant translators, that is a limit for the resolution on measured echograms. This resolution can be improved by deconvolution. But this method is a problem for austenitic steel. Here is developed a method of time deconvolution which allows to take in account the characteristics of the wave. A first step of phase correction and a second step of spectral equalization which gives back the spectral contents of ideal reflectivity. The two steps use fast Kalman filters which reduce the cost of the method
Deconvolutions based on singular value decomposition and the pseudoinverse: a guide for beginners.
Hendler, R W; Shrager, R I
1994-01-01
Singular value decomposition (SVD) is deeply rooted in the theory of linear algebra, and because of this is not readily understood by a large group of researchers who could profit from its application. In this paper, we discuss the subject on a level that should be understandable to scientists who are not well versed in linear algebra. However, because it is necessary that certain key concepts in linear algebra be appreciated in order to comprehend what is accomplished by SVD, we present the section, 'Bare basics of linear algebra'. This is followed by a discussion of the theory of SVD. Next we present step-by-step examples to illustrate how SVD is applied to deconvolute a titration involving a mixture of three pH indicators. One noiseless case is presented as well as two cases where either a fixed or varying noise level is present. Finally, we discuss additional deconvolutions of mixed spectra based on the use of the pseudoinverse.
Zhang, Pengcheng; De Crevoisier, Renaud; Simon, Antoine; Haigron, Pascal; Coatrieux, Jean-Louis; Li, Baosheng; Shu, Huazhong
2013-09-01
This work addresses random geometrical uncertainties that are intrinsically observed in radiation therapy by means of a new deconvolution method combining a series expansion and a Butterworth filter. The method efficiently suppresses high-frequency components by discarding the higher order terms of the series expansion and then filtering out deviations on the field edges. An additional approximation is made in order to set the fluence values outside the field to zero in the robust profiles. This method is compared to the deconvolution kernel method for a regular 2D fluence map, a real intensity-modulated radiation therapy field, and a prostate case. The results show that accuracy is improved while fulfilling clinical planning requirements.
International Nuclear Information System (INIS)
Zhang Pengcheng; Coatrieux, Jean-Louis; Shu Huazhong; De Crevoisier, Renaud; Simon, Antoine; Haigron, Pascal; Li Baosheng
2013-01-01
This work addresses random geometrical uncertainties that are intrinsically observed in radiation therapy by means of a new deconvolution method combining a series expansion and a Butterworth filter. The method efficiently suppresses high-frequency components by discarding the higher order terms of the series expansion and then filtering out deviations on the field edges. An additional approximation is made in order to set the fluence values outside the field to zero in the robust profiles. This method is compared to the deconvolution kernel method for a regular 2D fluence map, a real intensity-modulated radiation therapy field, and a prostate case. The results show that accuracy is improved while fulfilling clinical planning requirements. (paper)
Favalli, A.; Furetta, C.; Zaragoza, E. Cruz; Reyes, A.
The aim of this work is to study the main thermoluminescence (TL) characteristics of the inorganic polyminerals extracted from dehydrated Jamaica flower or roselle (Hibiscus sabdariffa L.) belonging to Malvaceae family of Mexican origin. TL emission properties of the polymineral fraction in powder were studied using the initial rise (IR) method. The complex structure and kinetic parameters of the glow curves have been analysed accurately using the computerized glow curve deconvolution (CGCD) assuming an exponential distribution of trapping levels. The extension of the IR method to the case of a continuous and exponential distribution of traps is reported, such as the derivation of the TL glow curve deconvolution functions for continuous trap distribution. CGCD is performed both in the case of frequency factor, s, temperature independent, and in the case with the s function of temperature.
Primary variables influencing generation of earthquake motions by a deconvolution process
International Nuclear Information System (INIS)
Idriss, I.M.; Akky, M.R.
1979-01-01
In many engineering problems, the analysis of potential earthquake response of a soil deposit, a soil structure or a soil-foundation-structure system requires the knowledge of earthquake ground motions at some depth below the level at which the motions are recorded, specified, or estimated. A process by which such motions are commonly calculated is termed a deconvolution process. This paper presents the results of a parametric study which was conducted to examine the accuracy, convergence, and stability of a frequency used deconvolution process and the significant parameters that may influence the output of this process. Parameters studied in included included: soil profile characteristics, input motion characteristics, level of input motion, and frequency cut-off. (orig.)
Comparison of alternative methods for multiplet deconvolution in the analysis of gamma-ray spectra
International Nuclear Information System (INIS)
Blaauw, Menno; Keyser, Ronald M.; Fazekas, Bela
1999-01-01
Three methods for multiplet deconvolution were tested using the 1995 IAEA reference spectra: Total area determination, iterative fitting and the library-oriented approach. It is concluded that, if statistical control (i.e. the ability to report results that agree with the known, true values to within the reported uncertainties) is required, the total area determination method performs the best. If high deconvolution power is required and a good, internally consistent library is available, the library oriented method yields the best results. Neither Erdtmann and Soyka's gamma-ray catalogue nor Browne and Firestone's Table of Radioactive Isotopes were found to be internally consistent enough in this respect. In the absence of a good library, iterative fitting with restricted peak width variation performs the best. The ultimate approach as yet to be implemented might be library-oriented fitting with allowed peak position variation according to the peak energy uncertainty specified in the library. (author)
Stain Deconvolution Using Statistical Analysis of Multi-Resolution Stain Colour Representation.
Directory of Open Access Journals (Sweden)
Najah Alsubaie
Full Text Available Stain colour estimation is a prominent factor of the analysis pipeline in most of histology image processing algorithms. Providing a reliable and efficient stain colour deconvolution approach is fundamental for robust algorithm. In this paper, we propose a novel method for stain colour deconvolution of histology images. This approach statistically analyses the multi-resolutional representation of the image to separate the independent observations out of the correlated ones. We then estimate the stain mixing matrix using filtered uncorrelated data. We conducted an extensive set of experiments to compare the proposed method to the recent state of the art methods and demonstrate the robustness of this approach using three different datasets of scanned slides, prepared in different labs using different scanners.
Lensing smoothing of BAO wiggles
Energy Technology Data Exchange (ETDEWEB)
Dio, Enea Di, E-mail: enea.didio@oats.inaf.it [INAF—Osservatorio Astronomico di Trieste, Via G.B. Tiepolo 11, I-34143 Trieste (Italy)
2017-03-01
We study non-perturbatively the effect of the deflection angle on the BAO wiggles of the matter power spectrum in real space. We show that from redshift z ∼2 this introduces a dispersion of roughly 1 Mpc at BAO scale, which corresponds approximately to a 1% effect. The lensing effect induced by the deflection angle, which is completely geometrical and survey independent, smears out the BAO wiggles. The effect on the power spectrum amplitude at BAO scale is about 0.1 % for z ∼2 and 0.2 % for z ∼4. We compare the smoothing effects induced by the lensing potential and non-linear structure formation, showing that the two effects become comparable at z ∼ 4, while the lensing effect dominates for sources at higher redshifts. We note that this effect is not accounted through BAO reconstruction techniques.
A MAP blind image deconvolution algorithm with bandwidth over-constrained
Ren, Zhilei; Liu, Jin; Liang, Yonghui; He, Yulong
2018-03-01
We demonstrate a maximum a posteriori (MAP) blind image deconvolution algorithm with bandwidth over-constrained and total variation (TV) regularization to recover a clear image from the AO corrected images. The point spread functions (PSFs) are estimated by bandwidth limited less than the cutoff frequency of the optical system. Our algorithm performs well in avoiding noise magnification. The performance is demonstrated on simulated data.
An l1-TV Algorithm for Deconvolution with Salt and Pepper Noise
2009-04-01
deblurring in the presence of impulsive noise ,” Int. J. Comput. Vision, vol. 70, no. 3, pp. 279–298, Dec. 2006. [13] A. E. Beaton and J. W. Tukey, “The...AN 1-TV ALGORITHM FOR DECONVOLUTIONWITH SALT AND PEPPER NOISE Brendt Wohlberg∗ T-7 Mathematical Modeling and Analysis Los Alamos National Laboratory...and pepper noise , but the extension of this formulation to more general prob- lems, such as deconvolution, has received little attention. We consider
International Nuclear Information System (INIS)
Vivet, L.
1989-01-01
The ultrasonic echographic technique has specific advantages which makes it essential in a lot of Non Destructive Testing (NDT) investigations. However, the high acoustic power necessary to propagate through highly attenuating media can only be transmitted by resonant transducers, which induces severe limitations of the resolution on the received echograms. This resolution may be improved with deconvolution methods. But one-dimensional deconvolution methods come up against problems in non destructive testing when the investigated medium is highly anisotropic and inhomogeneous (i.e. austenitic steel). Numerous deconvolution techniques are well documented in the NDT literature. But they often come from other application fields (biomedical engineering, geophysics) and we show they do not apply well to specific NDT problems: frequency-dependent attenuation and non-minimum phase of the emitted wavelet. We therefore introduce a new time-domain approach which takes into account the wavelet features. Our method solves the deconvolution problem as an estimation one and is performed in two steps: (i) A phase correction step which takes into account the phase of the wavelet and estimates a phase-corrected echogram. The phase of the wavelet is only due to the transducer and is assumed time-invariant during the propagation. (ii) A band equalization step which restores the spectral content of the ideal reflectivity. The two steps of the method are performed using fast Kalman filters which allow a significant reduction of the computational effort. Synthetic and actual results are given to prove that this is a good approach for resolution improvement in attenuating media [fr
Dino Bindi; Stefano Parolai; M. Picozzi; A. Ansal
2010-01-01
We apply a deconvolution approach to the problem of determining the input motion at the base of an instrumented borehole using only a pair of recordings, one at the borehole surface and the other at its bottom. To stabilize the bottom-tosurface spectral ratio, we apply an iterative regularization algorithm that allows us to constrain the solution to be positively defined and to have a finite time duration. Through the analysis of synthetic data, we show that the method is capab...
Methods for deconvoluting and interpreting complex gamma- and x-ray spectral regions
International Nuclear Information System (INIS)
Gunnink, R.
1983-06-01
Germanium and silicon detectors are now widely used for the detection and measurement of x and gamma radiation. However, some analysis situations and spectral regions have heretofore been too complex to deconvolute and interpret by techniques in general use. One example is the L x-ray spectrum of an element taken with a Ge or Si detector. This paper describes some new tools and methods that were developed to analyze complex spectral regions; they are illustrated with examples
Kumar, Amit; Chellappa, Rama
2017-01-01
Recently, Deep Convolution Networks (DCNNs) have been applied to the task of face alignment and have shown potential for learning improved feature representations. Although deeper layers can capture abstract concepts like pose, it is difficult to capture the geometric relationships among the keypoints in DCNNs. In this paper, we propose a novel convolution-deconvolution network for facial keypoint detection. Our model predicts the 2D locations of the keypoints and their individual visibility ...
A Design Methodology for Efficient Implementation of Deconvolutional Neural Networks on an FPGA
Zhang, Xinyu; Das, Srinjoy; Neopane, Ojash; Kreutz-Delgado, Ken
2017-01-01
In recent years deep learning algorithms have shown extremely high performance on machine learning tasks such as image classification and speech recognition. In support of such applications, various FPGA accelerator architectures have been proposed for convolutional neural networks (CNNs) that enable high performance for classification tasks at lower power than CPU and GPU processors. However, to date, there has been little research on the use of FPGA implementations of deconvolutional neural...
Dupé , François-Xavier; Fadili , Jalal M.; Starck , Jean-Luc
2012-01-01
International audience; In this paper, we propose a Bayesian MAP estimator for solving the deconvolution problems when the observations are corrupted by Poisson noise. Towards this goal, a proper data fidelity term (log-likelihood) is introduced to reflect the Poisson statistics of the noise. On the other hand, as a prior, the images to restore are assumed to be positive and sparsely represented in a dictionary of waveforms such as wavelets or curvelets. Both analysis and synthesis-type spars...
Data Visualization of Item-Total Correlation by Median Smoothing
Directory of Open Access Journals (Sweden)
Chong Ho Yu
2016-02-01
Full Text Available This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT. MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to accomplish two tasks by employing one procedure, users should be cautious of problematic items that affect both factor analysis and IRT. When sample sizes are extremely large, reliability analyses can misidentify even random numbers as meaningful patterns. Data visualization, such as median smoothing, can be used to identify problematic items in preliminary data cleaning.
ALFITeX. A new code for the deconvolution of complex alpha-particle spectra
International Nuclear Information System (INIS)
Caro Marroyo, B.; Martin Sanchez, A.; Jurado Vargas, M.
2013-01-01
A new code for the deconvolution of complex alpha-particle spectra has been developed. The ALFITeX code is written in Visual Basic for Microsoft Office Excel 2010 spreadsheets, incorporating several features aimed at making it a fast, robust and useful tool with a user-friendly interface. The deconvolution procedure is based on the Levenberg-Marquardt algorithm, with the curve fitting the experimental data being the mathematical function formed by the convolution of a Gaussian with two left-handed exponentials in the low-energy-tail region. The code also includes the capability of fitting a possible constant background contribution. The application of the singular value decomposition method for matrix inversion permits the fit of any kind of alpha-particle spectra, even those presenting singularities or an ill-conditioned curvature matrix. ALFITeX has been checked with its application to the deconvolution and the calculation of the alpha-particle emission probabilities of 239 Pu, 241 Am and 235 U. (author)
Blasko, Jaroslav; Kubinec, Róbert; Ostrovský, Ivan; Pavlíková, Eva; Krupcík, Ján; Soják, Ladislav
2009-04-03
A generally known problem of GC separation of trans-7;cis-9; cis-9,trans-11; and trans-8,cis-10 CLA (conjugated linoleic acid) isomers was studied by GC-MS on 100m capillary column coated with cyanopropyl silicone phase at isothermal column temperatures in a range of 140-170 degrees C. The resolution of these CLA isomers obtained at given conditions was not high enough for direct quantitative analysis, but it was, however, sufficient for the determination of their peak areas by commercial deconvolution software. Resolution factors of overlapped CLA isomers determined by the separation of a model CLA mixture prepared by mixing of a commercial CLA mixture and CLA isomer fraction obtained by the HPLC semi-preparative separation of milk fatty acids methyl esters were used to validate the deconvolution procedure. Developed deconvolution procedure allowed the determination of the content of studied CLA isomers in ewes' and cows' milk samples, where dominant isomer cis-9,trans-11 is eluted between two small isomers trans-7,cis-9 and trans-8,cis-10 (in the ratio up to 1:100).
Isotope pattern deconvolution as a tool to study iron metabolism in plants.
Rodríguez-Castrillón, José Angel; Moldovan, Mariella; García Alonso, J Ignacio; Lucena, Juan José; García-Tomé, Maria Luisa; Hernández-Apaolaza, Lourdes
2008-01-01
Isotope pattern deconvolution is a mathematical technique for isolating distinct isotope signatures from mixtures of natural abundance and enriched tracers. In iron metabolism studies measurement of all four isotopes of the element by high-resolution multicollector or collision cell ICP-MS allows the determination of the tracer/tracee ratio with simultaneous internal mass bias correction and lower uncertainties. This technique was applied here for the first time to study iron uptake by cucumber plants using 57Fe-enriched iron chelates of the o,o and o,p isomers of ethylenediaminedi(o-hydroxyphenylacetic) acid (EDDHA) and ethylenediamine tetraacetic acid (EDTA). Samples of root, stem, leaves, and xylem sap, after exposure of the cucumber plants to the mentioned 57Fe chelates, were collected, dried, and digested using nitric acid. The isotopic composition of iron in the samples was measured by ICP-MS using a high-resolution multicollector instrument. Mass bias correction was computed using both a natural abundance iron standard and by internal correction using isotope pattern deconvolution. It was observed that, for plants with low 57Fe enrichment, isotope pattern deconvolution provided lower tracer/tracee ratio uncertainties than the traditional method applying external mass bias correction. The total amount of the element in the plants was determined by isotope dilution analysis, using a collision cell quadrupole ICP-MS instrument, after addition of 57Fe or natural abundance Fe in a known amount which depended on the isotopic composition of the sample.
Isotope pattern deconvolution as a tool to study iron metabolism in plants
Energy Technology Data Exchange (ETDEWEB)
Rodriguez-Castrillon, Jose A.; Moldovan, Mariella; Garcia Alonso, J.I. [University of Oviedo, Department of Physical and Analytical Chemistry, Oviedo (Spain); Lucena, Juan J.; Garcia-Tome, Maria L.; Hernandez-Apaolaza, Lourdes [Autonoma University of Madrid, Department of Agricultural Chemistry, Madrid (Spain)
2008-01-15
Isotope pattern deconvolution is a mathematical technique for isolating distinct isotope signatures from mixtures of natural abundance and enriched tracers. In iron metabolism studies measurement of all four isotopes of the element by high-resolution multicollector or collision cell ICP-MS allows the determination of the tracer/tracee ratio with simultaneous internal mass bias correction and lower uncertainties. This technique was applied here for the first time to study iron uptake by cucumber plants using {sup 57}Fe-enriched iron chelates of the o,o and o,p isomers of ethylenediaminedi(o-hydroxyphenylacetic) acid (EDDHA) and ethylenediamine tetraacetic acid (EDTA). Samples of root, stem, leaves, and xylem sap, after exposure of the cucumber plants to the mentioned {sup 57}Fe chelates, were collected, dried, and digested using nitric acid. The isotopic composition of iron in the samples was measured by ICP-MS using a high-resolution multicollector instrument. Mass bias correction was computed using both a natural abundance iron standard and by internal correction using isotope pattern deconvolution. It was observed that, for plants with low {sup 57}Fe enrichment, isotope pattern deconvolution provided lower tracer/tracee ratio uncertainties than the traditional method applying external mass bias correction. The total amount of the element in the plants was determined by isotope dilution analysis, using a collision cell quadrupole ICP-MS instrument, after addition of {sup 57}Fe or natural abundance Fe in a known amount which depended on the isotopic composition of the sample. (orig.)
Direct imaging of phase objects enables conventional deconvolution in bright field light microscopy.
Directory of Open Access Journals (Sweden)
Carmen Noemí Hernández Candia
Full Text Available In transmitted optical microscopy, absorption structure and phase structure of the specimen determine the three-dimensional intensity distribution of the image. The elementary impulse responses of the bright field microscope therefore consist of separate absorptive and phase components, precluding general application of linear, conventional deconvolution processing methods to improve image contrast and resolution. However, conventional deconvolution can be applied in the case of pure phase (or pure absorptive objects if the corresponding phase (or absorptive impulse responses of the microscope are known. In this work, we present direct measurements of the phase point- and line-spread functions of a high-aperture microscope operating in transmitted bright field. Polystyrene nanoparticles and microtubules (biological polymer filaments serve as the pure phase point and line objects, respectively, that are imaged with high contrast and low noise using standard microscopy plus digital image processing. Our experimental results agree with a proposed model for the response functions, and confirm previous theoretical predictions. Finally, we use the measured phase point-spread function to apply conventional deconvolution on the bright field images of living, unstained bacteria, resulting in improved definition of cell boundaries and sub-cellular features. These developments demonstrate practical application of standard restoration methods to improve imaging of phase objects such as cells in transmitted light microscopy.
MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra
Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.
2018-04-01
The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.
Directory of Open Access Journals (Sweden)
Holger Pfeifer
2011-09-01
Full Text Available We introduce a scheme to obtain the deconvolved density of states (DOS of the tip and sample, from scanning tunneling spectra determined in the constant-current mode (z–V spectroscopy. The scheme is based on the validity of the Wentzel–Kramers–Brillouin (WKB approximation and the trapezoidal approximation of the electron potential within the tunneling barrier. In a numerical treatment of z–V spectroscopy, we first analyze how the position and amplitude of characteristic DOS features change depending on parameters such as the energy position, width, barrier height, and the tip–sample separation. Then it is shown that the deconvolution scheme is capable of recovering the original DOS of tip and sample with an accuracy of better than 97% within the one-dimensional WKB approximation. Application of the deconvolution scheme to experimental data obtained on Nb(110 reveals a convergent behavior, providing separately the DOS of both sample and tip. In detail, however, there are systematic quantitative deviations between the DOS results based on z–V data and those based on I–V data. This points to an inconsistency between the assumed and the actual transmission probability function. Indeed, the experimentally determined differential barrier height still clearly deviates from that derived from the deconvolved DOS. Thus, the present progress in developing a reliable deconvolution scheme shifts the focus towards how to access the actual transmission probability function.
Sparse deconvolution for the large-scale ill-posed inverse problem of impact force reconstruction
Qiao, Baijie; Zhang, Xingwu; Gao, Jiawei; Liu, Ruonan; Chen, Xuefeng
2017-01-01
Most previous regularization methods for solving the inverse problem of force reconstruction are to minimize the l2-norm of the desired force. However, these traditional regularization methods such as Tikhonov regularization and truncated singular value decomposition, commonly fail to solve the large-scale ill-posed inverse problem in moderate computational cost. In this paper, taking into account the sparse characteristic of impact force, the idea of sparse deconvolution is first introduced to the field of impact force reconstruction and a general sparse deconvolution model of impact force is constructed. Second, a novel impact force reconstruction method based on the primal-dual interior point method (PDIPM) is proposed to solve such a large-scale sparse deconvolution model, where minimizing the l2-norm is replaced by minimizing the l1-norm. Meanwhile, the preconditioned conjugate gradient algorithm is used to compute the search direction of PDIPM with high computational efficiency. Finally, two experiments including the small-scale or medium-scale single impact force reconstruction and the relatively large-scale consecutive impact force reconstruction are conducted on a composite wind turbine blade and a shell structure to illustrate the advantage of PDIPM. Compared with Tikhonov regularization, PDIPM is more efficient, accurate and robust whether in the single impact force reconstruction or in the consecutive impact force reconstruction.
Deconvoluting the Friction Stir Weld Process for Optimizing Welds
Schneider, Judy; Nunes, Arthur C.
2008-01-01
In the friction stir welding process, the rotating surfaces of the pin and shoulder contact the weld metal and force a rotational flow within the weld metal. Heat, generated by the metal deformation as well as frictional slippage with the contact surface, softens the metal and makes it easier to deform. As in any thermo-mechanical processing of metal, the flow conditions are critical to the quality of the weld. For example, extrusion of metal from under the shoulder of an excessively hot weld may relax local pressure and result in wormhole defects. The trace of the weld joint in the wake of the weld may vary geometrically depending upon the flow streamlines around the tool with some geometry more vulnerable to loss of strength from joint contamination than others. The material flow path around the tool cannot be seen in real time during the weld. By using analytical "tools" based upon the principles of mathematics and physics, a weld model can be created to compute features that can be observed. By comparing the computed observations with actual data, the weld model can be validated or adjusted to get better agreement. Inputs to the model to predict weld structures and properties include: hot working properties ofthe metal, pin tool geometry, travel rate, rotation and plunge force. Since metals record their prior hot working history, the hot working conditions imparted during FSW can be quantified by interpreting the final microstructure. Variations in texture and grain size result from variations in the strain accommodated at a given strain rate and temperature. Microstructural data from a variety of FSWs has been correlated with prior marker studies to contribute to our understanding of the FSW process. Once this stage is reached, the weld modeling process can save significant development costs by reducing costly trial-and-error approaches to obtaining quality welds.
Doing smooth pursuit paradigms in Windows 7
DEFF Research Database (Denmark)
Wilms, Inge Linda
predict strengths or deficits in perception and attention. However, smooth pursuit movements have been difficult to study and very little normative data is available for smooth pursuit performance in children and adults. This poster describes the challenges in setting up a smooth pursuit paradigm...... in Windows 7 with live capturing of eye movements using a Tobii TX300 eye tracker. In particular, the poster describes the challenges and limitations created by the hardware and the software...
Income and Consumption Smoothing among US States
DEFF Research Database (Denmark)
Sørensen, Bent; Yosha, Oved
within regions but not between regions. This suggests that capital markets transcend regional barriers while credit markets are regional in their nature. Smoothing within the club of rich states is accomplished mainly via capital markets whereas consumption smoothing is dominant within the club of poor...... states. The fraction of a shock to gross state products smoothed by the federal tax-transfer system is the same for various regions and other clubs of states. We calculate the scope for consumption smoothing within various regions and clubs, finding that most gains from risk sharing can be achieved...
International Nuclear Information System (INIS)
Anon.
1991-01-01
This chapter addresses the extension of previous work in one-dimensional (linear) error theory to two-dimensional error analysis. The topics of the chapter include the definition of two-dimensional error, the probability ellipse, the probability circle, elliptical (circular) error evaluation, the application to position accuracy, and the use of control systems (points) in measurements
International Nuclear Information System (INIS)
Picard, R.R.
1989-01-01
Topics covered in this chapter include a discussion of exact results as related to nuclear materials management and accounting in nuclear facilities; propagation of error for a single measured value; propagation of error for several measured values; error propagation for materials balances; and an application of error propagation to an example of uranium hexafluoride conversion process
Martínez-Legaz, Juan Enrique; Soubeyran, Antoine
2003-01-01
We present a model of learning in which agents learn from errors. If an action turns out to be an error, the agent rejects not only that action but also neighboring actions. We find that, keeping memory of his errors, under mild assumptions an acceptable solution is asymptotically reached. Moreover, one can take advantage of big errors for a faster learning.
Carroll, Raymond J.
2013-12-01
The data functions that are studied in the course of functional data analysis are assembled from discrete data, and the level of smoothing that is used is generally that which is appropriate for accurate approximation of the conceptually smooth functions that were not actually observed. Existing literature shows that this approach is effective, and even optimal, when using functional data methods for prediction or hypothesis testing. However, in the present paper we show that this approach is not effective in classification problems. There a useful rule of thumb is that undersmoothing is often desirable, but there are several surprising qualifications to that approach. First, the effect of smoothing the training data can be more significant than that of smoothing the new data set to be classified; second, undersmoothing is not always the right approach, and in fact in some cases using a relatively large bandwidth can be more effective; and third, these perverse results are the consequence of very unusual properties of error rates, expressed as functions of smoothing parameters. For example, the orders of magnitude of optimal smoothing parameter choices depend on the signs and sizes of terms in an expansion of error rate, and those signs and sizes can vary dramatically from one setting to another, even for the same classifier.
Carroll, Raymond J.; Delaigle, Aurore; Hall, Peter
2013-01-01
The data functions that are studied in the course of functional data analysis are assembled from discrete data, and the level of smoothing that is used is generally that which is appropriate for accurate approximation of the conceptually smooth functions that were not actually observed. Existing literature shows that this approach is effective, and even optimal, when using functional data methods for prediction or hypothesis testing. However, in the present paper we show that this approach is not effective in classification problems. There a useful rule of thumb is that undersmoothing is often desirable, but there are several surprising qualifications to that approach. First, the effect of smoothing the training data can be more significant than that of smoothing the new data set to be classified; second, undersmoothing is not always the right approach, and in fact in some cases using a relatively large bandwidth can be more effective; and third, these perverse results are the consequence of very unusual properties of error rates, expressed as functions of smoothing parameters. For example, the orders of magnitude of optimal smoothing parameter choices depend on the signs and sizes of terms in an expansion of error rate, and those signs and sizes can vary dramatically from one setting to another, even for the same classifier.
Generalized Gaussian Error Calculus
Grabe, Michael
2010-01-01
For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large. The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions. The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence inter...
A local cubic smoothing in an adaptation mode
International Nuclear Information System (INIS)
Dikoussar, N.D.
2001-01-01
A new approach to a local curve approximation and the smoothing is proposed. The relation between curve points is defined using a special cross-ratio weight functions. The coordinates of three curve points are used as parameters for both the weight functions and the tree-point cubic model (TPS). A very simple in computing and stable to random errors cubic smoother in an adaptation mode (LOCUS) is constructed. The free parameter of TPS is estimated independently of the fixed parameters by recursion with the effective error suppression and can be controlled by the cross-ratio parameters. Efficiency and the noise stability of the algorithm are confirmed by examples and by comparison with other known non-parametric smoothers
Medication errors: prescribing faults and prescription errors.
Velo, Giampaolo P; Minuz, Pietro
2009-06-01
1. Medication errors are common in general practice and in hospitals. Both errors in the act of writing (prescription errors) and prescribing faults due to erroneous medical decisions can result in harm to patients. 2. Any step in the prescribing process can generate errors. Slips, lapses, or mistakes are sources of errors, as in unintended omissions in the transcription of drugs. Faults in dose selection, omitted transcription, and poor handwriting are common. 3. Inadequate knowledge or competence and incomplete information about clinical characteristics and previous treatment of individual patients can result in prescribing faults, including the use of potentially inappropriate medications. 4. An unsafe working environment, complex or undefined procedures, and inadequate communication among health-care personnel, particularly between doctors and nurses, have been identified as important underlying factors that contribute to prescription errors and prescribing faults. 5. Active interventions aimed at reducing prescription errors and prescribing faults are strongly recommended. These should be focused on the education and training of prescribers and the use of on-line aids. The complexity of the prescribing procedure should be reduced by introducing automated systems or uniform prescribing charts, in order to avoid transcription and omission errors. Feedback control systems and immediate review of prescriptions, which can be performed with the assistance of a hospital pharmacist, are also helpful. Audits should be performed periodically.
Smooth horizons and quantum ripples
International Nuclear Information System (INIS)
Golovnev, Alexey
2015-01-01
Black holes are unique objects which allow for meaningful theoretical studies of strong gravity and even quantum gravity effects. An infalling and a distant observer would have very different views on the structure of the world. However, a careful analysis has shown that it entails no genuine contradictions for physics, and the paradigm of observer complementarity has been coined. Recently this picture was put into doubt. In particular, it was argued that in old black holes a firewall must form in order to protect the basic principles of quantum mechanics. This AMPS paradox has already been discussed in a vast number of papers with different attitudes and conclusions. Here we want to argue that a possible source of confusion is the neglect of quantum gravity effects. Contrary to widespread perception, it does not necessarily mean that effective field theory is inapplicable in rather smooth neighbourhoods of large black hole horizons. The real offender might be an attempt to consistently use it over the huge distances from the near-horizon zone of old black holes to the early radiation. We give simple estimates to support this viewpoint and show how the Page time and (somewhat more speculative) scrambling time do appear. (orig.)
Smooth horizons and quantum ripples
Energy Technology Data Exchange (ETDEWEB)
Golovnev, Alexey [Saint Petersburg State University, High Energy Physics Department, Saint-Petersburg (Russian Federation)
2015-05-15
Black holes are unique objects which allow for meaningful theoretical studies of strong gravity and even quantum gravity effects. An infalling and a distant observer would have very different views on the structure of the world. However, a careful analysis has shown that it entails no genuine contradictions for physics, and the paradigm of observer complementarity has been coined. Recently this picture was put into doubt. In particular, it was argued that in old black holes a firewall must form in order to protect the basic principles of quantum mechanics. This AMPS paradox has already been discussed in a vast number of papers with different attitudes and conclusions. Here we want to argue that a possible source of confusion is the neglect of quantum gravity effects. Contrary to widespread perception, it does not necessarily mean that effective field theory is inapplicable in rather smooth neighbourhoods of large black hole horizons. The real offender might be an attempt to consistently use it over the huge distances from the near-horizon zone of old black holes to the early radiation. We give simple estimates to support this viewpoint and show how the Page time and (somewhat more speculative) scrambling time do appear. (orig.)
Local Transfer Coefficient, Smooth Channel
Directory of Open Access Journals (Sweden)
R. T. Kukreja
1998-01-01
Full Text Available Naphthalene sublimation technique and the heat/mass transfer analogy are used to determine the detailed local heat/mass transfer distributions on the leading and trailing walls of a twopass square channel with smooth walls that rotates about a perpendicular axis. Since the variation of density is small in the flow through the channel, buoyancy effect is negligible. Results show that, in both the stationary and rotating channel cases, very large spanwise variations of the mass transfer exist in he turn and in the region immediately downstream of the turn in the second straight pass. In the first straight pass, the rotation-induced Coriolis forces reduce the mass transfer on the leading wall and increase the mass transfer on the trailing wall. In the turn, rotation significantly increases the mass transfer on the leading wall, especially in the upstream half of the turn. Rotation also increases the mass transfer on the trailing wall, more in the downstream half of the turn than in the upstream half of the turn. Immediately downstream of the turn, rotation causes the mass transfer to be much higher on the trailing wall near the downstream corner of the tip of the inner wall than on the opposite leading wall. The mass transfer in the second pass is higher on the leading wall than on the trailing wall. A slower flow causes higher mass transfer enhancement in the turn on both the leading and trailing walls.
Measurement-induced decoherence and Gaussian smoothing of the Wigner distribution function
International Nuclear Information System (INIS)
Chun, Yong-Jin; Lee, Hai-Woong
2003-01-01
We study the problem of measurement-induced decoherence using the phase-space approach employing the Gaussian-smoothed Wigner distribution function. Our investigation is based on the notion that measurement-induced decoherence is represented by the transition from the Wigner distribution to the Gaussian-smoothed Wigner distribution with the widths of the smoothing function identified as measurement errors. We also compare the smoothed Wigner distribution with the corresponding distribution resulting from the classical analysis. The distributions we computed are the phase-space distributions for simple one-dimensional dynamical systems such as a particle in a square-well potential and a particle moving under the influence of a step potential, and the time-frequency distributions for high-harmonic radiation emitted from an atom irradiated by short, intense laser pulses
Huang, Chengcheng; Zheng, Xiaogu; Tait, Andrew; Dai, Yongjiu; Yang, Chi; Chen, Zhuoqi; Li, Tao; Wang, Zhonglei
2014-01-01
Partial thin-plate smoothing spline model is used to construct the trend surface.Correction of the spline estimated trend surface is often necessary in practice.Cressman weight is modified and applied in residual correction.The modified Cressman weight performs better than Cressman weight.A method for estimating the error covariance matrix of gridded field is provided.
Smoothed Analysis of Local Search Algorithms
Manthey, Bodo; Dehne, Frank; Sack, Jörg-Rüdiger; Stege, Ulrike
2015-01-01
Smoothed analysis is a method for analyzing the performance of algorithms for which classical worst-case analysis fails to explain the performance observed in practice. Smoothed analysis has been applied to explain the performance of a variety of algorithms in the last years. One particular class of
Assessment of smoothed spectra using autocorrelation function
International Nuclear Information System (INIS)
Urbanski, P.; Kowalska, E.
2006-01-01
Recently, data and signal smoothing became almost standard procedures in the spectrometric and chromatographic methods. In radiometry, the main purpose to apply smoothing is minimisation of the statistical fluctuation and avoid distortion. The aim of the work was to find a qualitative parameter, which could be used, as a figure of merit for detecting distortion of the smoothed spectra, based on the linear model. It is assumed that as long as the part of the raw spectrum removed by the smoothing procedure (v s ) will be of random nature, the smoothed spectrum can be considered as undistorted. Thanks to this feature of the autocorrelation function, drifts of the mean value in the removed noise vs as well as its periodicity can be more easily detected from the autocorrelogram than from the original data
Mediators on human airway smooth muscle.
Armour, C; Johnson, P; Anticevich, S; Ammit, A; McKay, K; Hughes, M; Black, J
1997-01-01
1. Bronchial hyperresponsiveness in asthma may be due to several abnormalities, but must include alterations in the airway smooth muscle responsiveness and/or volume. 2. Increased responsiveness of airway smooth muscle in vitro can be induced by certain inflammatory cell products and by induction of sensitization (atopy). 3. Increased airway smooth muscle growth can also be induced by inflammatory cell products and atopic serum. 4. Mast cell numbers are increased in the airways of asthmatics and, in our studies, in airway smooth muscle that is sensitized and hyperresponsive. 5. We propose that there is a relationship between mast cells and airway smooth muscle cells which, once an allergic process has been initiated, results in the development of critical features in the lungs in asthma.
Discrete wavelet transform: a tool in smoothing kinematic data.
Ismail, A R; Asfour, S S
1999-03-01
Motion analysis systems typically introduce noise to the displacement data recorded. Butterworth digital filters have been used to smooth the displacement data in order to obtain smoothed velocities and accelerations. However, this technique does not yield satisfactory results, especially when dealing with complex kinematic motions that occupy the low- and high-frequency bands. The use of the discrete wavelet transform, as an alternative to digital filters, is presented in this paper. The transform passes the original signal through two complementary low- and high-pass FIR filters and decomposes the signal into an approximation function and a detail function. Further decomposition of the signal results in transforming the signal into a hierarchy set of orthogonal approximation and detail functions. A reverse process is employed to perfectly reconstruct the signal (inverse transform) back from its approximation and detail functions. The discrete wavelet transform was applied to the displacement data recorded by Pezzack et al., 1977. The smoothed displacement data were twice differentiated and compared to Pezzack et al.'s acceleration data in order to choose the most appropriate filter coefficients and decomposition level on the basis of maximizing the percentage of retained energy (PRE) and minimizing the root mean square error (RMSE). Daubechies wavelet of the fourth order (Db4) at the second decomposition level showed better results than both the biorthogonal and Coiflet wavelets (PRE = 97.5%, RMSE = 4.7 rad s-2). The Db4 wavelet was then used to compress complex displacement data obtained from a noisy mathematically generated function. Results clearly indicate superiority of this new smoothing approach over traditional filters.
Energy Technology Data Exchange (ETDEWEB)
Elliott, C.J.; McVey, B. (Los Alamos National Lab., NM (USA)); Quimby, D.C. (Spectra Technology, Inc., Bellevue, WA (USA))
1990-01-01
The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of these errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.
Prescription Errors in Psychiatry
African Journals Online (AJOL)
Arun Kumar Agnihotri
clinical pharmacists in detecting errors before they have a (sometimes serious) clinical impact should not be underestimated. Research on medication error in mental health care is limited. .... participation in ward rounds and adverse drug.
Zhou, T.; Popescu, S. C.; Krause, K.; Sheridan, R.; Ku, N. W.
2014-12-01
Increasing attention has been paid in the remote sensing community to the next generation Light Detection and Ranging (lidar) waveform data systems for extracting information on topography and the vertical structure of vegetation. However, processing waveform lidar data raises some challenges compared to analyzing discrete return data. The overall goal of this study was to present a robust de-convolution algorithm- Gold algorithm used to de-convolve waveforms in a lidar dataset acquired within a 60 x 60m study area located in the Harvard Forest in Massachusetts. The waveform lidar data was collected by the National Ecological Observatory Network (NEON). Specific objectives were to: (1) explore advantages and limitations of various waveform processing techniques to derive topography and canopy height information; (2) develop and implement a novel de-convolution algorithm, the Gold algorithm, to extract elevation and canopy metrics; and (3) compare results and assess accuracy. We modeled lidar waveforms with a mixture of Gaussian functions using the Non-least squares (NLS) algorithm implemented in R and derived a Digital Terrain Model (DTM) and canopy height. We compared our waveform-derived topography and canopy height measurements using the Gold de-convolution algorithm to results using the Richardson-Lucy algorithm. Our findings show that the Gold algorithm performed better than the Richardson-Lucy algorithm in terms of recovering the hidden echoes and detecting false echoes for generating a DTM, which indicates that the Gold algorithm could potentially be applied to processing of waveform lidar data to derive information on terrain elevation and canopy characteristics.
Non-parametric PSF estimation from celestial transit solar images using blind deconvolution
Directory of Open Access Journals (Sweden)
González Adriana
2016-01-01
Full Text Available Context: Characterization of instrumental effects in astronomical imaging is important in order to extract accurate physical information from the observations. The measured image in a real optical instrument is usually represented by the convolution of an ideal image with a Point Spread Function (PSF. Additionally, the image acquisition process is also contaminated by other sources of noise (read-out, photon-counting. The problem of estimating both the PSF and a denoised image is called blind deconvolution and is ill-posed. Aims: We propose a blind deconvolution scheme that relies on image regularization. Contrarily to most methods presented in the literature, our method does not assume a parametric model of the PSF and can thus be applied to any telescope. Methods: Our scheme uses a wavelet analysis prior model on the image and weak assumptions on the PSF. We use observations from a celestial transit, where the occulting body can be assumed to be a black disk. These constraints allow us to retain meaningful solutions for the filter and the image, eliminating trivial, translated, and interchanged solutions. Under an additive Gaussian noise assumption, they also enforce noise canceling and avoid reconstruction artifacts by promoting the whiteness of the residual between the blurred observations and the cleaned data. Results: Our method is applied to synthetic and experimental data. The PSF is estimated for the SECCHI/EUVI instrument using the 2007 Lunar transit, and for SDO/AIA using the 2012 Venus transit. Results show that the proposed non-parametric blind deconvolution method is able to estimate the core of the PSF with a similar quality to parametric methods proposed in the literature. We also show that, if these parametric estimations are incorporated in the acquisition model, the resulting PSF outperforms both the parametric and non-parametric methods.
Smooth halos in the cosmic web
International Nuclear Information System (INIS)
Gaite, José
2015-01-01
Dark matter halos can be defined as smooth distributions of dark matter placed in a non-smooth cosmic web structure. This definition of halos demands a precise definition of smoothness and a characterization of the manner in which the transition from smooth halos to the cosmic web takes place. We introduce entropic measures of smoothness, related to measures of inequality previously used in economy and with the advantage of being connected with standard methods of multifractal analysis already used for characterizing the cosmic web structure in cold dark matter N-body simulations. These entropic measures provide us with a quantitative description of the transition from the small scales portrayed as a distribution of halos to the larger scales portrayed as a cosmic web and, therefore, allow us to assign definite sizes to halos. However, these ''smoothness sizes'' have no direct relation to the virial radii. Finally, we discuss the influence of N-body discreteness parameters on smoothness
Smooth halos in the cosmic web
Energy Technology Data Exchange (ETDEWEB)
Gaite, José, E-mail: jose.gaite@upm.es [Physics Dept., ETSIAE, IDR, Universidad Politécnica de Madrid, Pza. Cardenal Cisneros 3, E-28040 Madrid (Spain)
2015-04-01
Dark matter halos can be defined as smooth distributions of dark matter placed in a non-smooth cosmic web structure. This definition of halos demands a precise definition of smoothness and a characterization of the manner in which the transition from smooth halos to the cosmic web takes place. We introduce entropic measures of smoothness, related to measures of inequality previously used in economy and with the advantage of being connected with standard methods of multifractal analysis already used for characterizing the cosmic web structure in cold dark matter N-body simulations. These entropic measures provide us with a quantitative description of the transition from the small scales portrayed as a distribution of halos to the larger scales portrayed as a cosmic web and, therefore, allow us to assign definite sizes to halos. However, these ''smoothness sizes'' have no direct relation to the virial radii. Finally, we discuss the influence of N-body discreteness parameters on smoothness.
Analysis of soda-lime glasses using non-negative matrix factor deconvolution of Raman spectra
Woelffel , William; Claireaux , Corinne; Toplis , Michael J.; Burov , Ekaterina; Barthel , Etienne; Shukla , Abhay; Biscaras , Johan; Chopinet , Marie-Hélène; Gouillart , Emmanuelle
2015-01-01
International audience; Novel statistical analysis and machine learning algorithms are proposed for the deconvolution and interpretation of Raman spectra of silicate glasses in the Na 2 O-CaO-SiO 2 system. Raman spectra are acquired along diffusion profiles of three pairs of glasses centered around an average composition of 69. 9 wt. % SiO 2 , 12. 7 wt. % CaO , 16. 8 wt. % Na 2 O. The shape changes of the Raman spectra across the compositional domain are analyzed using a combination of princi...
DEFF Research Database (Denmark)
Wüstner, Daniel; Faergeman, Nils J
2008-01-01
adipocyte differentiation. DHE is targeted to transferrin-positive recycling endosomes in preadipocytes but associates with droplets in mature adipocytes. Only in adipocytes but not in foam cells fluorescent sterol was confined to the droplet-limiting membrane. We developed an approach to visualize...... macrophage foam cells and in adipocytes. We used deconvolution microscopy and developed image segmentation techniques to assess the DHE content of lipid droplets in both cell types in an automated manner. Pulse-chase studies and colocalization analysis were performed to monitor the redistribution of DHE upon...
Deconvolution of ferromagnetic resonance in devitrification process of Co-based amorphous alloys
International Nuclear Information System (INIS)
Montiel, H.; Alvarez, G.; Betancourt, I.; Zamorano, R.; Valenzuela, R.
2006-01-01
Ferromagnetic resonance (FMR) measurements were carried out on soft magnetic amorphous ribbons of composition Co 66 Fe 4 B 12 Si 13 Nb 4 Cu prepared by melt spinning. In the as-cast sample, a simple FMR spectrum was apparent. For treatment times of 5-20 min a complex resonant absorption at lower fields was detected; deconvolution calculations were carried out on the FMR spectra and it was possible to separate two contributions. These results can be interpreted as the combination of two different magnetic phases, corresponding to the amorphous matrix and nanocrystallites. The parameters of resonant absorptions can be associated with the evolution of nanocrystallization during the annealing
Gabor Deconvolution as Preliminary Method to Reduce Pitfall in Deeper Target Seismic Data
Oktariena, M.; Triyoso, W.
2018-03-01
Anelastic attenuation process during seismic wave propagation is the trigger of seismic non-stationary characteristic. An absorption and a scattering of energy are causing the seismic energy loss as the depth increasing. A series of thin reservoir layers found in the study area is located within Talang Akar Fm. Level, showing an indication of interpretation pitfall due to attenuation effect commonly occurred in deeper level seismic data. Attenuation effect greatly influences the seismic images of deeper target level, creating pitfalls in several aspect. Seismic amplitude in deeper target level often could not represent its real subsurface character due to a low amplitude value or a chaotic event nearing the Basement. Frequency wise, the decaying could be seen as the frequency content diminishing in deeper target. Meanwhile, seismic amplitude is the simple tool to point out Direct Hydrocarbon Indicator (DHI) in preliminary Geophysical study before a further advanced interpretation method applied. A quick-look of Post-Stack Seismic Data shows the reservoir associated with a bright spot DHI while another bigger bright spot body detected in the North East area near the field edge. A horizon slice confirms a possibility that the other bright spot zone has smaller delineation; an interpretation pitfall commonly occurs in deeper level of seismic. We evaluates this pitfall by applying Gabor Deconvolution to address the attenuation problem. Gabor Deconvolution forms a Partition of Unity to factorize the trace into smaller convolution window that could be processed as stationary packets. Gabor Deconvolution estimates both the magnitudes of source signature alongside its attenuation function. The enhanced seismic shows a better imaging in the pitfall area that previously detected as a vast bright spot zone. When the enhanced seismic is used for further advanced reprocessing process, the Seismic Impedance and Vp/Vs Ratio slices show a better reservoir delineation, in which the
Deconvolution of 2D coincident Doppler broadening spectroscopy using the Richardson-Lucy algorithm
International Nuclear Information System (INIS)
Zhang, J.D.; Zhou, T.J.; Cheung, C.K.; Beling, C.D.; Fung, S.; Ng, M.K.
2006-01-01
Coincident Doppler Broadening Spectroscopy (CDBS) measurements are popular in positron solid-state studies of materials. By utilizing the instrumental resolution function obtained from a gamma line close in energy to the 511 keV annihilation line, it is possible to significantly enhance the quality of the CDBS spectra using deconvolution algorithms. In this paper, we compare two algorithms, namely the Non-Negativity Least Squares (NNLS) regularized method and the Richardson-Lucy (RL) algorithm. The latter, which is based on the method of maximum likelihood, is found to give superior results to the regularized least-squares algorithm and with significantly less computer processing time
DEFF Research Database (Denmark)
Rasmussen, Sune Olander; Andersen, Katrine K.; Johnsen, Sigfus Johann
2005-01-01
Continuous flow analysis (CFA) has become a popular measuring technique for obtaining high-resolution chemical ice core records due to an attractive combination of measuring speed and resolution. However, when analyzing the deeper sections of ice cores or cores from low-accumulation areas...... of the data for high-resolution studies such as annual layer counting. The presented method uses deconvolution techniques and is robust to the presence of noise in the measurements. If integrated into the data processing, it requires no additional data collection. The method is applied to selected ice core...
Fourier Deconvolution Methods for Resolution Enhancement in Continuous-Wave EPR Spectroscopy.
Reed, George H; Poyner, Russell R
2015-01-01
An overview of resolution enhancement of conventional, field-swept, continuous-wave electron paramagnetic resonance spectra using Fourier transform-based deconvolution methods is presented. Basic steps that are involved in resolution enhancement of calculated spectra using an implementation based on complex discrete Fourier transform algorithms are illustrated. Advantages and limitations of the method are discussed. An application to an experimentally obtained spectrum is provided to illustrate the power of the method for resolving overlapped transitions. © 2015 Elsevier Inc. All rights reserved.
Role of retinal slip in the prediction of target motion during smooth and saccadic pursuit.
de Brouwer, S; Missal, M; Lefèvre, P
2001-08-01
Visual tracking of moving targets requires the combination of smooth pursuit eye movements with catch-up saccades. In primates, catch-up saccades usually take place only during pursuit initiation because pursuit gain is close to unity. This contrasts with the lower and more variable gain of smooth pursuit in cats, where smooth eye movements are intermingled with catch-up saccades during steady-state pursuit. In this paper, we studied in detail the role of retinal slip in the prediction of target motion during smooth and saccadic pursuit in the cat. We found that the typical pattern of pursuit in the cat was a combination of smooth eye movements with saccades. During smooth pursuit initiation, there was a correlation between peak eye acceleration and target velocity. During pursuit maintenance, eye velocity oscillated at approximately 3 Hz around a steady-state value. The average gain of smooth pursuit was approximately 0.5. Trained cats were able to continue pursuing in the absence of a visible target, suggesting a role of the prediction of future target motion in this species. The analysis of catch-up saccades showed that the smooth-pursuit motor command is added to the saccadic command during catch-up saccades and that both position error and retinal slip are taken into account in their programming. The influence of retinal slip on catch-up saccades showed that prediction about future target motion is used in the programming of catch-up saccades. Altogether, these results suggest that pursuit systems in primates and cats are qualitatively similar, with a lower average gain in the cat and that prediction affects both saccades and smooth eye movements during pursuit.
Experimental investigation of smoothing by spectral dispersion
International Nuclear Information System (INIS)
Regan, Sean P.; Marozas, John A.; Kelly, John H.; Boehly, Thomas R.; Donaldson, William R.; Jaanimagi, Paul A.; Keck, Robert L.; Kessler, Terrance J.; Meyerhofer, David D.; Seka, Wolf
2000-01-01
Measurements of smoothing rates for smoothing by spectral dispersion (SSD) of high-power, solid-state laser beams used for inertial confinement fusion (ICF) research are reported. Smoothing rates were obtained from the intensity distributions of equivalent target plane images for laser pulses of varying duration. Simulations of the experimental data with the known properties of the phase plates and the frequency modulators are in good agreement with the experimental data. These results inspire confidence in extrapolating to higher bandwidths and other SSD configurations that may be suitable for ICF experiments and ultimately for direct-drive laser-fusion ignition. (c) 2000 Optical Society of America
Bifurcations of non-smooth systems
Angulo, Fabiola; Olivar, Gerard; Osorio, Gustavo A.; Escobar, Carlos M.; Ferreira, Jocirei D.; Redondo, Johan M.
2012-12-01
Non-smooth systems (namely piecewise-smooth systems) have received much attention in the last decade. Many contributions in this area show that theory and applications (to electronic circuits, mechanical systems, …) are relevant to problems in science and engineering. Specially, new bifurcations have been reported in the literature, and this was the topic of this minisymposium. Thus both bifurcation theory and its applications were included. Several contributions from different fields show that non-smooth bifurcations are a hot topic in research. Thus in this paper the reader can find contributions from electronics, energy markets and population dynamics. Also, a carefully-written specific algebraic software tool is presented.
Kartush, J M
1996-11-01
Practicing medicine successfully requires that errors in diagnosis and treatment be minimized. Malpractice laws encourage litigators to ascribe all medical errors to incompetence and negligence. There are, however, many other causes of unintended outcomes. This article describes common causes of errors and suggests ways to minimize mistakes in otologic practice. Widespread dissemination of knowledge about common errors and their precursors can reduce the incidence of their occurrence. Consequently, laws should be passed to allow for a system of non-punitive, confidential reporting of errors and "near misses" that can be shared by physicians nationwide.
International Nuclear Information System (INIS)
Britton, D.T.; Bentvelsen, P.; Vries, J. de; Veen, A. van
1988-01-01
A deconvolution scheme for digital lineshapes using fast Fourier transforms and a filter based on background subtraction in Fourier space has been developed. In tests on synthetic data this has been shown to give optimum deconvolution without prior inspection of the Fourier spectrum. Although offering significant improvements on the raw data, deconvolution is shown to be limited. The contribution of the resolution function is substantially reduced but not eliminated completely and unphysical oscillations are introduced into the lineshape. The method is further tested on measurements of the lineshape for positron annihilation in single crystal copper at the relatively poor resolution of 1.7 keV at 512 keV. A two-component fit is possible yielding component widths in agreement with previous measurements. (orig.)
Optimal Smoothing in Adaptive Location Estimation
Mammen, Enno; Park, Byeong U.
1997-01-01
In this paper higher order performance of kernel basedadaptive location estimators are considered. Optimalchoice of smoothing parameters is discussed and it isshown how much is lossed in efficiency by not knowingthe underlying translation density.
Smooth surfaces from rational bilinear patches
Shi, Ling
2014-01-01
Smooth freeform skins from simple panels constitute a challenging topic arising in contemporary architecture. We contribute to this problem area by showing how to approximate a negatively curved surface by smoothly joined rational bilinear patches. The approximation problem is solved with help of a new computational approach to the hyperbolic nets of Huhnen-Venedey and Rörig and optimization algorithms based on it. We also discuss its limits which lie in the topology of the input surface. Finally, freeform deformations based on Darboux transformations are used to generate smooth surfaces from smoothly joined Darboux cyclide patches; in this way we eliminate the restriction to surfaces with negative Gaussian curvature. © 2013 Elsevier B.V.
Smooth embeddings with Stein surface images
Gompf, Robert E.
2011-01-01
A simple characterization is given of open subsets of a complex surface that smoothly perturb to Stein open subsets. As applications, complex 2-space C^2 contains domains of holomorphy (Stein open subsets) that are exotic R^4's, and others homotopy equivalent to the 2-sphere but cut out by smooth, compact 3-manifolds. Pseudoconvex embeddings of Brieskorn spheres and other 3-manifolds into complex surfaces are constructed, as are pseudoconcave holomorphic fillings (with disagreeing contact and...
Some splines produced by smooth interpolation
Czech Academy of Sciences Publication Activity Database
Segeth, Karel
2018-01-01
Roč. 319, 15 February (2018), s. 387-394 ISSN 0096-3003 R&D Projects: GA ČR GA14-02067S Institutional support: RVO:67985840 Keywords : smooth data approximation * smooth data interpolation * cubic spline Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.738, year: 2016 http://www.sciencedirect.com/science/article/pii/S0096300317302746?via%3Dihub
Some splines produced by smooth interpolation
Czech Academy of Sciences Publication Activity Database
Segeth, Karel
2018-01-01
Roč. 319, 15 February (2018), s. 387-394 ISSN 0096-3003 R&D Projects: GA ČR GA14-02067S Institutional support: RVO:67985840 Keywords : smooth data approximation * smooth data interpolation * cubic spline Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.738, year: 2016 http://www. science direct.com/ science /article/pii/S0096300317302746?via%3Dihub
Optimal Smooth Consumption and Annuity Design
DEFF Research Database (Denmark)
Bruhn, Kenneth; Steffensen, Mogens
2013-01-01
We propose an optimization criterion that yields extraordinary consumption smoothing compared to the well known results of the life-cycle model. Under this criterion we solve the related consumption and investment optimization problem faced by individuals with preferences for intertemporal stabil...... stability in consumption. We find that the consumption and investment patterns demanded under the optimization criterion is in general offered as annuity benefits from products in the class of ‘Formula Based Smoothed Investment-Linked Annuities’....
Langenbucher, Frieder
2003-11-01
Convolution and deconvolution are the classical in-vitro-in-vivo correlation tools to describe the relationship between input and weighting/response in a linear system, where input represents the drug release in vitro, weighting/response any body response in vivo. While functional treatment, e.g. in terms of polyexponential or Weibull distribution, is more appropriate for general survey or prediction, numerical algorithms are useful for treating actual experimental data. Deconvolution is not considered an algorithm by its own, but the inversion of a corresponding convolution. MS Excel is shown to be a useful tool for all these applications.
Energy Technology Data Exchange (ETDEWEB)
Sanchez-Bajo, F. [Universidad de Extremadura, Badajoz (Spain). Dept. de Electronica e Ingenieria Electromecanica; Ortiz, A.L.; Cumbrera, F.L. [Universidad de Extremadura, Badajoz (Spain). Dept. de Fisica
2001-07-01
Deconvolution of X-ray diffraction profiles is a fundamental step in obtaining reliable results in the microstructural characterization (crystallite size, lattice microstrain, etc) of polycrystalline materials. In this work we have analyzed a powder sample of 9-YSZ using a technique based on the Fourier series expansion of the pure profile. This procedure, which can be combined with regularization methods, is specially powerful to minimize the effects of the ill-posed nature of the linear integral equation involved in the kinematical theory of X-ray diffraction. Finally, the deconvoluted profiles have been used to obtain microstructural parameters by means of the integral-breadth method. (orig.)
Hubbard, Bernard E.; Hooper, Donald M.; Solano, Federico; Mars, John C.
2018-01-01
We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.
Hubbard, Bernard E.; Hooper, Donald M.; Solano, Federico; Mars, John C.
2018-02-01
We apply linear deconvolution methods to derive mineral and glass proportions for eight field sample training sites at seven dune fields: (1) Algodones, California; (2) Big Dune, Nevada; (3) Bruneau, Idaho; (4) Great Kobuk Sand Dunes, Alaska; (5) Great Sand Dunes National Park and Preserve, Colorado; (6) Sunset Crater, Arizona; and (7) White Sands National Monument, New Mexico. These dune fields were chosen because they represent a wide range of mineral grain mixtures and allow us to gauge a better understanding of both compositional and sorting effects within terrestrial and extraterrestrial dune systems. We also use actual ASTER TIR emissivity imagery to map the spatial distribution of these minerals throughout the seven dune fields and evaluate the effects of degraded spectral resolution on the accuracy of mineral abundances retrieved. Our results show that hyperspectral data convolutions of our laboratory emissivity spectra outperformed multispectral data convolutions of the same data with respect to the mineral, glass and lithic abundances derived. Both the number and wavelength position of spectral bands greatly impacts the accuracy of linear deconvolution retrieval of feldspar proportions (e.g. K-feldspar vs. plagioclase) especially, as well as the detection of certain mafic and carbonate minerals. In particular, ASTER mapping results show that several of the dune sites display patterns such that less dense minerals typically have higher abundances near the center of the active and most evolved dunes in the field, while more dense minerals and glasses appear to be more abundant along the margins of the active dune fields.
Obtaining Crustal Properties From the P Coda Without Deconvolution: an Example From the Dakotas
Frederiksen, A. W.; Delaney, C.
2013-12-01
Receiver functions are a popular technique for mapping variations in crustal thickness and bulk properties, as the travel times of Ps conversions and multiples from the Moho constrain both Moho depth (h) and the Vp/Vs ratio (k) of the crust. The established approach is to generate a suite of receiver functions, which are then stacked along arrival-time curves for a set of (h,k) values (the h-k stacking approach of Zhu and Kanamori, 2000). However, this approach is sensitive to noise issues with the receiver functions, deconvolution artifacts, and the effects of strong crustal layering (such as in sedimentary basins). In principle, however, the deconvolution is unnecessary; for any given crustal model, we can derive a transfer function allowing us to predict the radial component of the P coda from the vertical, and so determine a misfit value for a particular crustal model. We apply this idea to an Earthscope Transportable Array data set from North and South Dakota and western Minnesota, for which we already have measurements obtained using conventional h-k stacking, and so examine the possibility of crustal thinning and modification by a possible failed branch of the Mid-Continent Rift.
Application of Glow Curve Deconvolution Method to Evaluate Low Dose TLD LiF
International Nuclear Information System (INIS)
Kurnia, E; Oetami, H R; Mutiah
1996-01-01
Thermoluminescence Dosimeter (TLD), especially LiF:Mg, Ti material, is one of the most practical personal dosimeter in known to date. Dose measurement under 100 uGy using TLD reader is very difficult in high precision level. The software application is used to improve the precision of the TLD reader. The objectives of the research is to compare three Tl-glow curve analysis method irradiated in the range between 5 up to 250 uGy. The first method is manual analysis, dose information is obtained from the area under the glow curve between pre selected temperature limits, and background signal is estimated by a second readout following the first readout. The second method is deconvolution method, separating glow curve into four peaks mathematically and dose information is obtained from area of peak 5, and background signal is eliminated computationally. The third method is deconvolution method but the dose is represented by the sum of area of peak 3,4 and 5. The result shown that the sum of peak 3,4 and 5 method can improve reproducibility six times better than manual analysis for dose 20 uGy, the ability to reduce MMD until 10 uGy rather than 60 uGy with manual analysis or 20 uGy with peak 5 area method. In linearity, the sum of peak 3,4 and 5 method yields exactly linear dose response curve over the entire dose range
Ultrasonic inspection of studs (bolts) using dynamic predictive deconvolution and wave shaping.
Suh, D M; Kim, W W; Chung, J G
1999-01-01
Bolt degradation has become a major issue in the nuclear industry since the 1980's. If small cracks in stud bolts are not detected early enough, they grow rapidly and cause catastrophic disasters. Their detection, despite its importance, is known to be a very difficult problem due to the complicated structures of the stud bolts. This paper presents a method of detecting and sizing a small crack in the root between two adjacent crests in threads. The key idea is from the fact that the mode-converted Rayleigh wave travels slowly down the face of the crack and turns from the intersection of the crack and the root of thread to the transducer. Thus, when a crack exists, a small delayed pulse due to the Rayleigh wave is detected between large regularly spaced pulses from the thread. The delay time is the same as the propagation delay time of the slow Rayleigh wave and is proportional to the site of the crack. To efficiently detect the slow Rayleigh wave, three methods based on digital signal processing are proposed: wave shaping, dynamic predictive deconvolution, and dynamic predictive deconvolution combined with wave shaping.
The measurement of layer thickness by the deconvolution of ultrasonic signals
International Nuclear Information System (INIS)
McIntyre, P.J.
1977-07-01
An ultrasonic technique for measuring layer thickness, such as oxide on corroded steel, is described. A time domain response function is extracted from an ultrasonic signal reflected from the layered system. This signal is the convolution of the input signal with the response function of the layer. By using a signal reflected from a non-layered surface to represent the input, the response function may be obtained by deconvolution. The advantage of this technique over that described by Haines and Bel (1975) is that the quality of the results obtained using their method depends on the ability of a skilled operator in lining up an arbitrary common feature of the signals received. Using deconvolution no operator manipulations are necessary and so less highly trained personnel may successfully make the measurements. Results are presented for layers of araldite on aluminium and magnetite of steel. The results agreed satisfactorily with predictions but in the case of magnetite, its high velocity of sound meant that thicknesses of less than 250 microns were difficult to measure accurately. (author)
Optimization of deconvolution software used in the study of spectra of soil samples from Madagascar
International Nuclear Information System (INIS)
ANDRIAMADY NARIMANANA, S.F.
2005-01-01
The aim of this work is to perform the deconvolution of gamma spectra by using the deconvolution peak program. Synthetic spectra, reference materials and ten soil samples with various U-238 activities from three regions of Madagascar were used. This work concerns : soil sample spectra with low activities of about (47±2) Bq.kg -1 from Ankatso, soil sample spectra with average activities of about (125±2)Bq.kg -1 from Antsirabe and soil sample spectra with high activities of about (21100± 120) Bq.kg -1 from Vinaninkarena. Singlet and multiplet peaks with various intensities were found in each soil spectrum. Interactive Peak Fit (IPF) program in Genie-PC from Canberra Industries allows to deconvoluate many multiplet regions : quartet within 235 keV-242 keV, Pb-214 and Pb-212 within 294 keV -301 keV; Th-232 daughters within 582 keV - 584 keV; Ac-228 within 904 keV -911 keV and within 964 keV-970 keV and Bi-214 within 1401 keV - 1408 keV. Those peaks were used to quantify considered radionuclides. However, IPF cannot resolve Ra-226 peak at 186,1 keV. [fr
A blind deconvolution method based on L1/L2 regularization prior in the gradient space
Cai, Ying; Shi, Yu; Hua, Xia
2018-02-01
In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.
Schawinski, Kevin; Zhang, Ce; Zhang, Hantian; Fowler, Lucas; Santhanam, Gokula Krishnan
2017-05-01
Observations of astrophysical objects such as galaxies are limited by various sources of random and systematic noise from the sky background, the optical system of the telescope and the detector used to record the data. Conventional deconvolution techniques are limited in their ability to recover features in imaging data by the Shannon-Nyquist sampling theorem. Here, we train a generative adversarial network (GAN) on a sample of 4550 images of nearby galaxies at 0.01 < z < 0.02 from the Sloan Digital Sky Survey and conduct 10× cross-validation to evaluate the results. We present a method using a GAN trained on galaxy images that can recover features from artificially degraded images with worse seeing and higher noise than the original with a performance that far exceeds simple deconvolution. The ability to better recover detailed features such as galaxy morphology from low signal to noise and low angular resolution imaging data significantly increases our ability to study existing data sets of astrophysical objects as well as future observations with observatories such as the Large Synoptic Sky Telescope (LSST) and the Hubble and James Webb space telescopes.
Photoacoustic imaging optimization with raw signal deconvolution and empirical mode decomposition
Guo, Chengwen; Wang, Jing; Qin, Yu; Zhan, Hongchen; Yuan, Jie; Cheng, Qian; Wang, Xueding
2018-02-01
Photoacoustic (PA) signal of an ideal optical absorb particle is a single N-shape wave. PA signals of a complicated biological tissue can be considered as the combination of individual N-shape waves. However, the N-shape wave basis not only complicates the subsequent work, but also results in aliasing between adjacent micro-structures, which deteriorates the quality of the final PA images. In this paper, we propose a method to improve PA image quality through signal processing method directly working on raw signals, which including deconvolution and empirical mode decomposition (EMD). During the deconvolution procedure, the raw PA signals are de-convolved with a system dependent point spread function (PSF) which is measured in advance. Then, EMD is adopted to adaptively re-shape the PA signals with two constraints, positive polarity and spectrum consistence. With our proposed method, the built PA images can yield more detail structural information. Micro-structures are clearly separated and revealed. To validate the effectiveness of this method, we present numerical simulations and phantom studies consist of a densely distributed point sources model and a blood vessel model. In the future, our study might hold the potential for clinical PA imaging as it can help to distinguish micro-structures from the optimized images and even measure the size of objects from deconvolved signals.
Schneiderbauer, Simon; Saeedipour, Mahdi
2018-02-01
Highly resolved two-fluid model (TFM) simulations of gas-solid flows in vertical periodic channels have been performed to study closures for the filtered drag force and the Reynolds-stress-like contribution stemming from the convective terms. An approximate deconvolution model (ADM) for the large-eddy simulation of turbulent gas-solid suspensions is detailed and subsequently used to reconstruct those unresolved contributions in an a priori manner. With such an approach, an approximation of the unfiltered solution is obtained by repeated filtering allowing the determination of the unclosed terms of the filtered equations directly. A priori filtering shows that predictions of the ADM model yield fairly good agreement with the fine grid TFM simulations for various filter sizes and different particle sizes. In particular, strong positive correlation (ρ > 0.98) is observed at intermediate filter sizes for all sub-grid terms. Additionally, our study reveals that the ADM results moderately depend on the choice of the filters, such as box and Gaussian filter, as well as the deconvolution order. The a priori test finally reveals that ADM is superior compared to isotropic functional closures proposed recently [S. Schneiderbauer, "A spatially-averaged two-fluid model for dense large-scale gas-solid flows," AIChE J. 63, 3544-3562 (2017)].
The thermoluminescence glow-curve analysis using GlowFit - the new powerful tool for deconvolution
International Nuclear Information System (INIS)
Puchalska, M.; Bilski, P.
2005-10-01
A new computer program, GlowFit, for deconvoluting first-order kinetics thermoluminescence (TL) glow-curves has been developed. A non-linear function describing a single glow-peak is fitted to experimental points using the least squares Levenberg-Marquardt method. The main advantage of GlowFit is in its ability to resolve complex TL glow-curves consisting of strongly overlapping peaks, such as those observed in heavily doped LiF:Mg,Ti (MTT) detectors. This resolution is achieved mainly by setting constraints or by fixing selected parameters. The initial values of the fitted parameters are placed in the so-called pattern files. GlowFit is a Microsoft Windows-operated user-friendly program. Its graphic interface enables easy intuitive manipulation of glow-peaks, at the initial stage (parameter initialization) and at the final stage (manual adjustment) of fitting peak parameters to the glow-curves. The program is freely downloadable from the web site www.ifj.edu.pl/NPP/deconvolution.htm (author)
Deconvolution analysis of sup(99m)Tc-methylene diphosphonate kinetics in metabolic bone disease
Energy Technology Data Exchange (ETDEWEB)
Knop, J.; Kroeger, E.; Stritzke, P.; Schneider, C.; Kruse, H.P.
1981-02-01
The kinetics of sup(99m)Tc-methylene diphosphonate (MDP) and /sup 47/Ca were studied in three patients with osteoporosis, three patients with hyperparathyroidism, and two patients with osteomalacia. The activities of sup(99m)Tc-MDP were recorded in the lumbar spine, paravertebral soft tissues, and in venous blood samples for 1 h after injection. The results were submitted to deconvolution analysis to determine regional bone accumulation rates. /sup 47/Ca kinetics were analysed by a linear two-compartment model quantitating short-term mineral exchange, exchangeable bone calcium, and calcium accretion. The sup(99m)Tc-MDP accumulation rates were small in osteoporosis, greater in hyperparathyroidism, and greatest in osteomalacia. No correlations were obtained between sup(99m)Tc-MDP bone accumulation rates and the results of /sup 47/Ca kinetics. However, there was a significant relationship between the level of serum alkaline phosphatase and bone accumulation rates (R = 0.71, P < 0.025). As a result deconvolution analysis of regional sup(99m)Tc-MDP kinetics in dynamic bone scans might be useful to quantitate osseous tracer accumulation in metabolic bone disease. The lack of correlation between the results of sup(99m)Tc-MDP kinetics and /sup 47/Ca kinetics might suggest a preferential binding of sup(99m)Tc-MDP to the organic matrix of the bone, as has been suggested by other authors on the basis of experimental and clinical investigations.
Regularization and error assignment to unfolded distributions
Zech, Gunter
2011-01-01
The commonly used approach to present unfolded data only in graphical formwith the diagonal error depending on the regularization strength is unsatisfac-tory. It does not permit the adjustment of parameters of theories, the exclusionof theories that are admitted by the observed data and does not allow the com-bination of data from different experiments. We propose fixing the regulariza-tion strength by a p-value criterion, indicating the experimental uncertaintiesindependent of the regularization and publishing the unfolded data in additionwithout regularization. These considerations are illustrated with three differentunfolding and smoothing approaches applied to a toy example.
The error in total error reduction.
Witnauer, James E; Urcelay, Gonzalo P; Miller, Ralph R
2014-02-01
Most models of human and animal learning assume that learning is proportional to the discrepancy between a delivered outcome and the outcome predicted by all cues present during that trial (i.e., total error across a stimulus compound). This total error reduction (TER) view has been implemented in connectionist and artificial neural network models to describe the conditions under which weights between units change. Electrophysiological work has revealed that the activity of dopamine neurons is correlated with the total error signal in models of reward learning. Similar neural mechanisms presumably support fear conditioning, human contingency learning, and other types of learning. Using a computational modeling approach, we compared several TER models of associative learning to an alternative model that rejects the TER assumption in favor of local error reduction (LER), which assumes that learning about each cue is proportional to the discrepancy between the delivered outcome and the outcome predicted by that specific cue on that trial. The LER model provided a better fit to the reviewed data than the TER models. Given the superiority of the LER model with the present data sets, acceptance of TER should be tempered. Copyright © 2013 Elsevier Inc. All rights reserved.
Antonio Boldrini; Rosa T. Scaramuzzo; Armando Cuttano
2013-01-01
Introduction: Danger and errors are inherent in human activities. In medical practice errors can lean to adverse events for patients. Mass media echo the whole scenario. Methods: We reviewed recent published papers in PubMed database to focus on the evidence and management of errors in medical practice in general and in Neonatology in particular. We compared the results of the literature with our specific experience in Nina Simulation Centre (Pisa, Italy). Results: In Neonatology the main err...
Smoothing of respiratory motion traces for motion-compensated radiotherapy.
Ernst, Floris; Schlaefer, Alexander; Schweikard, Achim
2010-01-01
The CyberKnife system has been used successfully for several years to radiosurgically treat tumors without the need for stereotactic fixation or sedation of the patient. It has been shown that tumor motion in the lung, liver, and pancreas can be tracked with acceptable accuracy and repeatability. However, highly precise targeting for tumors in the lower abdomen, especially for tumors which exhibit strong motion, remains problematic. Reasons for this are manifold, like the slow tracking system operating at 26.5 Hz, and using the signal from the tracking camera "as is." Since the motion recorded with the camera is used to compensate for system latency by prediction and the predicted signal is subsequently used to infer the tumor position from a correlation model based on x-ray imaging of gold fiducials around the tumor, camera noise directly influences the targeting accuracy. The goal of this work is to establish the suitability of a new smoothing method for respiratory motion traces used in motion-compensated radiotherapy. The authors endeavor to show that better prediction--With a lower rms error of the predicted signal--and/or smoother prediction is possible using this method. The authors evaluated six commercially available tracking systems (NDI Aurora, PolarisClassic, Polaris Vicra, MicronTracker2 H40, FP5000, and accuTrack compact). The authors first tracked markers both stationary and while in motion to establish the systems' noise characteristics. Then the authors applied a smoothing method based on the a trous wavelet decomposition to reduce the devices' noise level. Additionally, the smoothed signal of the moving target and a motion trace from actual human respiratory motion were subjected to prediction using the MULIN and the nLMS2 algorithms. The authors established that the noise distribution for a static target is Gaussian and that when the probe is moved such as to mimic human respiration, it remains Gaussian with the exception of the FP5000 and the
Smoothing of respiratory motion traces for motion-compensated radiotherapy
International Nuclear Information System (INIS)
Ernst, Floris; Schlaefer, Alexander; Schweikard, Achim
2010-01-01
Purpose: The CyberKnife system has been used successfully for several years to radiosurgically treat tumors without the need for stereotactic fixation or sedation of the patient. It has been shown that tumor motion in the lung, liver, and pancreas can be tracked with acceptable accuracy and repeatability. However, highly precise targeting for tumors in the lower abdomen, especially for tumors which exhibit strong motion, remains problematic. Reasons for this are manifold, like the slow tracking system operating at 26.5 Hz, and using the signal from the tracking camera ''as is''. Since the motion recorded with the camera is used to compensate for system latency by prediction and the predicted signal is subsequently used to infer the tumor position from a correlation model based on x-ray imaging of gold fiducials around the tumor, camera noise directly influences the targeting accuracy. The goal of this work is to establish the suitability of a new smoothing method for respiratory motion traces used in motion-compensated radiotherapy. The authors endeavor to show that better prediction--With a lower rms error of the predicted signal--and/or smoother prediction is possible using this method. Methods: The authors evaluated six commercially available tracking systems (NDI Aurora, PolarisClassic, Polaris Vicra, MicronTracker2 H40, FP5000, and accuTrack compact). The authors first tracked markers both stationary and while in motion to establish the systems' noise characteristics. Then the authors applied a smoothing method based on the a trous wavelet decomposition to reduce the devices' noise level. Additionally, the smoothed signal of the moving target and a motion trace from actual human respiratory motion were subjected to prediction using the MULIN and the nLMS 2 algorithms. Results: The authors established that the noise distribution for a static target is Gaussian and that when the probe is moved such as to mimic human respiration, it remains Gaussian with the
National Research Council Canada - National Science Library
Byrne, Michael D
2006-01-01
.... This problem has received surprisingly little attention from cognitive psychologists. The research summarized here examines such errors in some detail both empirically and through computational cognitive modeling...
International Nuclear Information System (INIS)
Wahlstroem, B.
1993-01-01
Human errors have a major contribution to the risks for industrial accidents. Accidents have provided important lesson making it possible to build safer systems. In avoiding human errors it is necessary to adapt the systems to their operators. The complexity of modern industrial systems is however increasing the danger of system accidents. Models of the human operator have been proposed, but the models are not able to give accurate predictions of human performance. Human errors can never be eliminated, but their frequency can be decreased by systematic efforts. The paper gives a brief summary of research in human error and it concludes with suggestions for further work. (orig.)
TOP-DRAWER, Histograms, Scatterplots, Curve-Smoothing
International Nuclear Information System (INIS)
Chaffee, R.B.
1988-01-01
Description of program or function: TOP DRAWER produces histograms, scatterplots, data points with error bars and plots symbols, and curves passing through data points, with elaborate titles. It also does smoothing and calculates frequency distributions. There is little facility, however, for arithmetic manipulation. Because of its restricted applicability, TOP DRAWER can be controlled by a relatively simple set of commands, and this control is further simplified by the choice of reasonable default values for all parameters. Despite this emphasis on simplicity, TOP DRAWER plots are of exceptional quality and are suitable for publication. Input is normally from card-image records, although a set of subroutines is provided to accommodate FORTRAN calls. The program contains switches which can be set to generate code suitable for execution on IBM, DECX VAX, and PRIME computers
Smooth conditional distribution function and quantiles under random censorship.
Leconte, Eve; Poiraud-Casanova, Sandrine; Thomas-Agnan, Christine
2002-09-01
We consider a nonparametric random design regression model in which the response variable is possibly right censored. The aim of this paper is to estimate the conditional distribution function and the conditional alpha-quantile of the response variable. We restrict attention to the case where the response variable as well as the explanatory variable are unidimensional and continuous. We propose and discuss two classes of estimators which are smooth with respect to the response variable as well as to the covariate. Some simulations demonstrate that the new methods have better mean square error performances than the generalized Kaplan-Meier estimator introduced by Beran (1981) and considered in the literature by Dabrowska (1989, 1992) and Gonzalez-Manteiga and Cadarso-Suarez (1994).
A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem
Delaigle, Aurore
2009-03-01
Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.
Analysts forecast error : A robust prediction model and its short term trading
Boudt, Kris; de Goeij, Peter; Thewissen, James; Van Campenhout, Geert
We examine the profitability of implementing a short term trading strategy based on predicting the error in analysts' earnings per share forecasts using publicly available information. Since large earnings surprises may lead to extreme values in the forecast error series that disrupt their smooth
Directory of Open Access Journals (Sweden)
Xiaodan Tan
2017-12-01
Full Text Available The auditory steady-state response (ASSR is one of the main approaches in clinic for health screening and frequency-specific hearing assessment. However, its generation mechanism is still of much controversy. In the present study, the linear superposition hypothesis for the generation of ASSRs was investigated by comparing the relationships between the classical 40 Hz ASSR and three synthetic ASSRs obtained from three different templates for transient auditory evoked potential (AEP. These three AEPs are the traditional AEP at 5 Hz and two 40 Hz AEPs derived from two deconvolution algorithms using stimulus sequences, i.e., continuous loop averaging deconvolution (CLAD and multi-rate steady-state average deconvolution (MSAD. CLAD requires irregular inter-stimulus intervals (ISIs in the sequence while MSAD uses the same ISIs but evenly-spaced stimulus sequences which mimics the classical 40 Hz ASSR. It has been reported that these reconstructed templates show similar patterns but significant difference in morphology and distinct frequency characteristics in synthetic ASSRs. The prediction accuracies of ASSR using these templates show significant differences (p < 0.05 in 45.95, 36.28, and 10.84% of total time points within four cycles of ASSR for the traditional, CLAD, and MSAD templates, respectively, as compared with the classical 40 Hz ASSR, and the ASSR synthesized from the MSAD transient AEP suggests the best similarity. And such a similarity is also demonstrated at individuals only in MSAD showing no statistically significant difference (Hotelling's T2 test, T2 = 6.96, F = 0.80, p = 0.592 as compared with the classical 40 Hz ASSR. The present results indicate that both stimulation rate and sequencing factor (ISI variation affect transient AEP reconstructions from steady-state stimulation protocols. Furthermore, both auditory brainstem response (ABR and middle latency response (MLR are observed in contributing to the composition of ASSR but
Effect of smoothing on robust chaos.
Deshpande, Amogh; Chen, Qingfei; Wang, Yan; Lai, Ying-Cheng; Do, Younghae
2010-08-01
In piecewise-smooth dynamical systems, situations can arise where the asymptotic attractors of the system in an open parameter interval are all chaotic (e.g., no periodic windows). This is the phenomenon of robust chaos. Previous works have established that robust chaos can occur through the mechanism of border-collision bifurcation, where border is the phase-space region where discontinuities in the derivatives of the dynamical equations occur. We investigate the effect of smoothing on robust chaos and find that periodic windows can arise when a small amount of smoothness is present. We introduce a parameter of smoothing and find that the measure of the periodic windows in the parameter space scales linearly with the parameter, regardless of the details of the smoothing function. Numerical support and a heuristic theory are provided to establish the scaling relation. Experimental evidence of periodic windows in a supposedly piecewise linear dynamical system, which has been implemented as an electronic circuit, is also provided.
TAX SMOOTHING: TESTS ON INDONESIAN DATA
Directory of Open Access Journals (Sweden)
Rudi Kurniawan
2011-01-01
Full Text Available This paper contributes to the literature of public debt management by testing for tax smoothing behaviour in Indonesia. Tax smoothing means that the government smooths the tax rate across all future time periods to minimize the distortionary costs of taxation over time for a given path of government spending. In a stochastic economy with an incomplete bond market, tax smoothing implies that the tax rate approximates a random walk and changes in the tax rate are nearly unpredictable. For that purpose, two tests were performed. First, random walk behaviour of the tax rate was examined by undertaking unit root tests. The null hypothesis of unit root cannot be rejected, indicating that the tax rate is nonstationary and, hence, it follows a random walk. Second, the predictability of the tax rate was examined by regressing changes in the tax rate on its own lagged values and also on lagged values of changes in the goverment expenditure ratio, and growth of real output. They are found to be not significant in predicting changes in the tax rate. Taken together, the present evidence seems to be consistent with the tax smoothing, therefore provides support to this theory.
Energy Technology Data Exchange (ETDEWEB)
Oba, T. [SOKENDAI (The Graduate University for Advanced Studies), 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252–5210 (Japan); Riethmüller, T. L.; Solanki, S. K. [Max-Planck-Institut für Sonnensystemforschung (MPS), Justus-von-Liebig-Weg 3, D-37077 Göttingen (Germany); Iida, Y. [Department of Science and Technology/Kwansei Gakuin University, Gakuen 2-1, Sanda, Hyogo, 669–1337 Japan (Japan); Quintero Noda, C.; Shimizu, T. [Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency, 3-1-1 Yoshinodai, Chuo-ku, Sagamihara, Kanagawa 252–5210 (Japan)
2017-11-01
Solar granules are bright patterns surrounded by dark channels, called intergranular lanes, in the solar photosphere and are a manifestation of overshooting convection. Observational studies generally find stronger upflows in granules and weaker downflows in intergranular lanes. This trend is, however, inconsistent with the results of numerical simulations in which downflows are stronger than upflows through the joint action of gravitational acceleration/deceleration and pressure gradients. One cause of this discrepancy is the image degradation caused by optical distortion and light diffraction and scattering that takes place in an imaging instrument. We apply a deconvolution technique to Hinode /SP data in an attempt to recover the original solar scene. Our results show a significant enhancement in both the convective upflows and downflows but particularly for the latter. After deconvolution, the up- and downflows reach maximum amplitudes of −3.0 km s{sup −1} and +3.0 km s{sup −1} at an average geometrical height of roughly 50 km, respectively. We found that the velocity distributions after deconvolution match those derived from numerical simulations. After deconvolution, the net LOS velocity averaged over the whole field of view lies close to zero as expected in a rough sense from mass balance.
Deconvolution of^{ 238,239,240}Pu conversion electron spectra measured with a silicon drift detector
DEFF Research Database (Denmark)
Pommé, S.; Marouli, M.; Paepen, J.
2018-01-01
Internal conversion electron (ICE) spectra of thin 238,239,240Pu sources, measured with a windowless Peltier-cooled silicon drift detector (SDD), were deconvoluted and relative ICE intensities were derived from the fitted peak areas. Corrections were made for energy dependence of the full...
Bade, R.; Causanilles, A.; Emke, E.; Bijlsma, L.; Sancho, J.V.; Hernandez, F.; de Voogt, P.
2016-01-01
A screening approach was applied to influent and effluent wastewater samples. After injection in a LC-LTQ-Orbitrap, data analysis was performed using two deconvolution tools, MsXelerator (modules MPeaks and MS Compare) and Sieve 2.1. The outputs were searched incorporating an in-house database of >
Wormeester, Herbert; Sasse, A.G.B.M.; van Silfhout, Arend
1988-01-01
One of the main problems in the analysis of measured spectra is how to reduce the influence of noise in data processing. We show a deconvolution, a differentiation and a Fourier Transform algorithm that can be run on a small computer (64 K RAM) and suffer less from noise than commonly used routines.
Metcalfe, Janet
2017-01-01
Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…
A Model of the Smooth Pursuit Eye Movement with Prediction and Learning
Directory of Open Access Journals (Sweden)
Davide Zambrano
2010-01-01
Full Text Available Smooth pursuit is one of the five main eye movements in humans, consisting of tracking a steadily moving visual target. Smooth pursuit is a good example of a sensory-motor task that is deeply based on prediction: tracking a visual target is not possible by correcting the error between the eye and the target position or velocity with a feedback loop, but it is only possible by predicting the trajectory of the target. This paper presents a model of smooth pursuit based on prediction and learning. It starts from amodel of the neuro-physiological system proposed by Shibata and Schaal (Shibata et al., Neural Networks, vol. 18, pp. 213-224, 2005. The learning component added here decreases the prediction time in the case of target dynamics already experienced by the system. In the implementation described here, the convergence time is, after the learning phase, 0.8 s.
Action errors, error management, and learning in organizations.
Frese, Michael; Keith, Nina
2015-01-03
Every organization is confronted with errors. Most errors are corrected easily, but some may lead to negative consequences. Organizations often focus on error prevention as a single strategy for dealing with errors. Our review suggests that error prevention needs to be supplemented by error management--an approach directed at effectively dealing with errors after they have occurred, with the goal of minimizing negative and maximizing positive error consequences (examples of the latter are learning and innovations). After defining errors and related concepts, we review research on error-related processes affected by error management (error detection, damage control). Empirical evidence on positive effects of error management in individuals and organizations is then discussed, along with emotional, motivational, cognitive, and behavioral pathways of these effects. Learning from errors is central, but like other positive consequences, learning occurs under certain circumstances--one being the development of a mind-set of acceptance of human error.
Lyapunov exponents and smooth ergodic theory
Barreira, Luis
2001-01-01
This book is a systematic introduction to smooth ergodic theory. The topics discussed include the general (abstract) theory of Lyapunov exponents and its applications to the stability theory of differential equations, stable manifold theory, absolute continuity, and the ergodic theory of dynamical systems with nonzero Lyapunov exponents (including geodesic flows). The authors consider several non-trivial examples of dynamical systems with nonzero Lyapunov exponents to illustrate some basic methods and ideas of the theory. This book is self-contained. The reader needs a basic knowledge of real analysis, measure theory, differential equations, and topology. The authors present basic concepts of smooth ergodic theory and provide complete proofs of the main results. They also state some more advanced results to give readers a broader view of smooth ergodic theory. This volume may be used by those nonexperts who wish to become familiar with the field.
Multiple predictor smoothing methods for sensitivity analysis
International Nuclear Information System (INIS)
Helton, Jon Craig; Storlie, Curtis B.
2006-01-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present
Adsorption on smooth electrodes: A radiotracer study
International Nuclear Information System (INIS)
Rice-Jackson, L.M.
1990-01-01
Adsorption on solids is a complicated process and in most cases, occurs as the early stage of other more complicated processes, i.e. chemical reactions, electrooxidation, electroreduction. The research reported here combines the electroanalytical method, cyclic voltammetry, and the use of radio-labeled isotopes, soft beta emitters, to study adsorption processes at smooth electrodes. The in-situ radiotracer method is highly anion (molecule) specific and provides information on the structure and composition of the electric double layer. The emphasis of this research was on studying adsorption processes at smooth electrodes of copper, gold, and platinum. The application of the radiotracer method to these smooth surfaces have led to direct in-situ measurements from which surface coverage was determined; anions and molecules were identified; and weak interactions of adsorbates with the surface of the electrodes were readily monitored. 179 refs
Multiple predictor smoothing methods for sensitivity analysis.
Energy Technology Data Exchange (ETDEWEB)
Helton, Jon Craig; Storlie, Curtis B.
2006-08-01
The use of multiple predictor smoothing methods in sampling-based sensitivity analyses of complex models is investigated. Specifically, sensitivity analysis procedures based on smoothing methods employing the stepwise application of the following nonparametric regression techniques are described: (1) locally weighted regression (LOESS), (2) additive models, (3) projection pursuit regression, and (4) recursive partitioning regression. The indicated procedures are illustrated with both simple test problems and results from a performance assessment for a radioactive waste disposal facility (i.e., the Waste Isolation Pilot Plant). As shown by the example illustrations, the use of smoothing procedures based on nonparametric regression techniques can yield more informative sensitivity analysis results than can be obtained with more traditional sensitivity analysis procedures based on linear regression, rank regression or quadratic regression when nonlinear relationships between model inputs and model predictions are present.
Directory of Open Access Journals (Sweden)
Fausto Carnevale Neto
2016-09-01
Full Text Available Dereplication based on hyphenated techniques has been extensively applied in plant metabolomics, avoiding re-isolation of known natural products. However, due to the complex nature of biological samples and their large concentration range, dereplication requires the use of chemometric tools to comprehensively extract information from the acquired data. In this work we developed a reliable GC-MS-based method for the identification of non-targeted plant metabolites by combining the Ratio Analysis of Mass Spectrometry deconvolution tool (RAMSY with Automated Mass Spectral Deconvolution and Identification System software (AMDIS. Plants species from Solanaceae, Chrysobalanaceae and Euphorbiaceae were selected as model systems due to their molecular diversity, ethnopharmacological potential and economical value. The samples were analyzed by GC-MS after methoximation and silylation reactions. Dereplication initiated with the use of a factorial design of experiments to determine the best AMDIS configuration for each sample, considering linear retention indices and mass spectral data. A heuristic factor (CDF, compound detection factor was developed and applied to the AMDIS results in order to decrease the false-positive rates. Despite the enhancement in deconvolution and peak identification, the empirical AMDIS method was not able to fully deconvolute all GC-peaks, leading to low MF values and/or missing metabolites. RAMSY was applied as a complementary deconvolution method to AMDIS to peaks exhibiting substantial overlap, resulting in recovery of low-intensity co-eluted ions. The results from this combination of optimized AMDIS with RAMSY attested to the ability of this approach as an improved dereplication method for complex biological samples such as plant extracts.
Zollanvari, Amin
2013-05-24
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Zollanvari, Amin; Genton, Marc G.
2013-01-01
We provide a fundamental theorem that can be used in conjunction with Kolmogorov asymptotic conditions to derive the first moments of well-known estimators of the actual error rate in linear discriminant analysis of a multivariate Gaussian model under the assumption of a common known covariance matrix. The estimators studied in this paper are plug-in and smoothed resubstitution error estimators, both of which have not been studied before under Kolmogorov asymptotic conditions. As a result of this work, we present an optimal smoothing parameter that makes the smoothed resubstitution an unbiased estimator of the true error. For the sake of completeness, we further show how to utilize the presented fundamental theorem to achieve several previously reported results, namely the first moment of the resubstitution estimator and the actual error rate. We provide numerical examples to show the accuracy of the succeeding finite sample approximations in situations where the number of dimensions is comparable or even larger than the sample size.
Multi-processor system for real-time deconvolution and flow estimation in medical ultrasound
DEFF Research Database (Denmark)
Jensen, Jesper Lomborg; Jensen, Jørgen Arendt; Stetson, Paul F.
1996-01-01
of the algorithms. Many of the algorithms can only be properly evaluated in a clinical setting with real-time processing, which generally cannot be done with conventional equipment. This paper therefore presents a multi-processor system capable of performing 1.2 billion floating point operations per second on RF...... filter is used with a second time-reversed recursive estimation step. Here it is necessary to perform about 70 arithmetic operations per RF sample or about 1 billion operations per second for real-time deconvolution. Furthermore, these have to be floating point operations due to the adaptive nature...... interfaced to our previously-developed real-time sampling system that can acquire RF data at a rate of 20 MHz and simultaneously transmit the data at 20 MHz to the processing system via several parallel channels. These two systems can, thus, perform real-time processing of ultrasound data. The advantage...
Peckner, Ryan; Myers, Samuel A; Jacome, Alvaro Sebastian Vaca; Egertson, Jarrett D; Abelin, Jennifer G; MacCoss, Michael J; Carr, Steven A; Jaffe, Jacob D
2018-05-01
Mass spectrometry with data-independent acquisition (DIA) is a promising method to improve the comprehensiveness and reproducibility of targeted and discovery proteomics, in theory by systematically measuring all peptide precursors in a biological sample. However, the analytical challenges involved in discriminating between peptides with similar sequences in convoluted spectra have limited its applicability in important cases, such as the detection of single-nucleotide polymorphisms (SNPs) and alternative site localizations in phosphoproteomics data. We report Specter (https://github.com/rpeckner-broad/Specter), an open-source software tool that uses linear algebra to deconvolute DIA mixture spectra directly through comparison to a spectral library, thus circumventing the problems associated with typical fragment-correlation-based approaches. We validate the sensitivity of Specter and its performance relative to that of other methods, and show that Specter is able to successfully analyze cases involving highly similar peptides that are typically challenging for DIA analysis methods.
International Nuclear Information System (INIS)
Carter, G.; Katardjiev, I.V.; Nobes, M.J.
1989-01-01
The quasi-linear partial differential continuity equations that describe the evolution of the depth profiles and surface concentrations of marker atoms in kinematically equivalent systems undergoing sputtering, ion collection and atomic mixing are solved using the method of characteristics. It is shown how atomic mixing probabilities can be deduced from measurements of ion collection depth profiles with increasing ion fluence, and how this information can be used to predict surface concentration evolution. Even with this information, however, it is shown that it is not possible to deconvolute directly the surface concentration measurements to provide initial depth profiles, except when only ion collection and sputtering from the surface layer alone occur. It is demonstrated further that optimal recovery of initial concentration depth profiles could be ensured if the concentration-measuring analytical probe preferentially sampled depths near and at the maximum depth of bombardment-induced perturbations. (author)
Supriyanto, Noor, T.; Suhanto, E.
2017-07-01
The Endut geothermal prospect is located in Banten Province, Indonesia. The geological setting of the area is dominated by quaternary volcanic, tertiary sediments and tertiary rock intrusion. This area has been in the preliminary study phase of geology, geochemistry, and geophysics. As one of the geophysical study, the gravity data measurement has been carried out and analyzed in order to understand geological condition especially subsurface fault structure that control the geothermal system in Endut area. After precondition applied to gravity data, the complete Bouguer anomaly have been analyzed using advanced derivatives method such as Horizontal Gradient (HG) and Euler Deconvolution (ED) to clarify the existance of fault structures. These techniques detected boundaries of body anomalies and faults structure that were compared with the lithologies in the geology map. The analysis result will be useful in making a further realistic conceptual model of the Endut geothermal area.
Deconvolution based attenuation correction for time-of-flight positron emission tomography
Lee, Nam-Yong
2017-10-01
For an accurate quantitative reconstruction of the radioactive tracer distribution in positron emission tomography (PET), we need to take into account the attenuation of the photons by the tissues. For this purpose, we propose an attenuation correction method for the case when a direct measurement of the attenuation distribution in the tissues is not available. The proposed method can determine the attenuation factor up to a constant multiple by exploiting the consistency condition that the exact deconvolution of noise-free time-of-flight (TOF) sinogram must satisfy. Simulation studies shows that the proposed method corrects attenuation artifacts quite accurately for TOF sinograms of a wide range of temporal resolutions and noise levels, and improves the image reconstruction for TOF sinograms of higher temporal resolutions by providing more accurate attenuation correction.
Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media
Edrei, Eitan; Scarcelli, Giuliano
2016-09-01
High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.
Data matching for free-surface multiple attenuation by multidimensional deconvolution
van der Neut, Joost; Frijlink, Martijn; van Borselen, Roald
2012-09-01
A common strategy for surface-related multiple elimination of seismic data is to predict multiples by a convolutional model and subtract these adaptively from the input gathers. Problems can be posed by interfering multiples and primaries. Removing multiples by multidimensional deconvolution (MDD) (inversion) does not suffer from these problems. However, this approach requires data to be consistent, which is often not the case, especially not at interpolated near-offsets. A novel method is proposed to improve data consistency prior to inversion. This is done by backpropagating first-order multiples with a time-gated reference primary event and matching these with early primaries in the input gather. After data matching, multiple elimination by MDD can be applied with a deterministic inversion scheme.
International Nuclear Information System (INIS)
Son, J. D.; Yang, B. S.; Tan, A. C. C.; Mathew, J.
2004-01-01
Many machine failures are not detected well in advance due to the masking of background noise and attenuation of the source signal through the transmission mediums. Advanced signal processing techniques using adaptive filters and higher order statistics have been attempted to extract the source signal from the measured data at the machine surface. In this paper, blind deconvolution using the Eigenvector Algorithm (EVA) technique is used to recover a damaged bearing signal using only the measured signal at the machine surface. A damaged bearing signal corrupted by noise with varying signal-to-noise (s/n) was used to determine the effectiveness of the technique in detecting an incipient signal and the optimum choice of filter length. The results show that the technique is effective in detecting the source signal with an s/n ratio as low as 0.21, but requires a relatively large filter length
Learning High-Order Filters for Efficient Blind Deconvolution of Document Photographs
Xiao, Lei
2016-09-16
Photographs of text documents taken by hand-held cameras can be easily degraded by camera motion during exposure. In this paper, we propose a new method for blind deconvolution of document images. Observing that document images are usually dominated by small-scale high-order structures, we propose to learn a multi-scale, interleaved cascade of shrinkage fields model, which contains a series of high-order filters to facilitate joint recovery of blur kernel and latent image. With extensive experiments, we show that our method produces high quality results and is highly efficient at the same time, making it a practical choice for deblurring high resolution text images captured by modern mobile devices. © Springer International Publishing AG 2016.
Deconvolution of H-alpha profiles measured by Thompson scattering collecting optics
International Nuclear Information System (INIS)
LeBlanc, B.; Grek, B.
1986-01-01
This paper discusses that optically fast multichannel Thomson scattering optics that can be used for H-alpha emission profile measurement. A technique based on the fact that a particular volume element of the overall field of view can be seen by many channels, depending on its location, is discussed. It is applied to measurement made on PDX with the vertically viewing TVTS collecting optics (56 channels). The authors found that for this case, about 28 Fourier modes are optimum to represent the spatial behavior of the plasma emissivity. The coefficients for these modes are obtained by doing a least-square-fit to the data subjet to certain constraints. The important constraints are non-negative emissivity, the assumed up and down symmetry and zero emissivity beyond the liners. H-alpha deconvolutions are presented for diverted and circular discharges
International Nuclear Information System (INIS)
Schmitt, Jeremy
2011-01-01
This thesis presents new methods for spherical Poisson data analysis for the Fermi mission. Fermi main scientific objectives, the study of diffuse galactic background et the building of the source catalog, are complicated by the weakness of photon flux and the point spread function of the instrument. This thesis proposes a new multi-scale representation for Poisson data on the sphere, the Multi-Scale Variance Stabilizing Transform on the Sphere (MS-VSTS), consisting in the combination of a spherical multi-scale transform (wavelets, curvelets) with a variance stabilizing transform (VST). This method is applied to mono- and multichannel Poisson noise removal, missing data interpolation, background extraction and multichannel deconvolution. Finally, this thesis deals with the problem of component separation using sparse representations (template fitting). (author) [fr
DEFF Research Database (Denmark)
Andersen, Jens Enevold Thaulov
observed in high-resolution images of metallic nanocrystallites may be effectively deconvoluted, as to resolve more details of the crystalline morphology (see figure). Images of surface-crystalline metals indicate that more than a single atomic layer is involved in mediating the tunneling current......Upon imaging, electrochemical scanning tunneling microscopy (ESTM), scanning electrochemical micro-scopy (SECM) and in situ STM resolve information on electronic structures and on surface topography. At very high resolution, imaging processing is required, as to obtain information that relates...... to crystallographic-surface structures. Within the wide range of new technologies, those images surface features, the electrochemical scanning tunneling microscope (ESTM) provides means of atomic resolution where the tip participates actively in the process of imaging. Two metallic surfaces influence ions trapped...
Further optimization of SeDDaRA blind image deconvolution algorithm and its DSP implementation
Wen, Bo; Zhang, Qiheng; Zhang, Jianlin
2011-11-01
Efficient algorithm for blind image deconvolution and its high-speed implementation is of great value in practice. Further optimization of SeDDaRA is developed, from algorithm structure to numerical calculation methods. The main optimization covers that, the structure's modularization for good implementation feasibility, reducing the data computation and dependency of 2D-FFT/IFFT, and acceleration of power operation by segmented look-up table. Then the Fast SeDDaRA is proposed and specialized for low complexity. As the final implementation, a hardware system of image restoration is conducted by using the multi-DSP parallel processing. Experimental results show that, the processing time and memory demand of Fast SeDDaRA decreases 50% at least; the data throughput of image restoration system is over 7.8Msps. The optimization is proved efficient and feasible, and the Fast SeDDaRA is able to support the real-time application.
International Nuclear Information System (INIS)
Bolton, P.R.
1987-06-01
A technique is described for measuring and deconvolving response times of microwave diode detection systems in order to generate corrected input signals typical of an infinite detection rate. The method has been applied to cases of 2.86 GHz ultra-short HPM pulse detection where pulse rise time is comparable to that of the detector; whereas, the duration of a few nanoseconds is significantly longer. Results are specified in terms of the enhancement of equivalent deconvolved input voltages for given observed voltages. The convolution integral imposes the constraint of linear detector response to input power levels. This is physically equivalent to the conservation of integrated pulse energy in the deconvolution process. The applicable dynamic range of a microwave diode is therefore limited to a smaller signal region as determined by its calibration
Polarization beam smoothing for inertial confinement fusion
International Nuclear Information System (INIS)
Rothenberg, Joshua E.
2000-01-01
For both direct and indirect drive approaches to inertial confinement fusion (ICF) it is imperative to obtain the best possible drive beam uniformity. The approach chosen for the National Ignition Facility uses a random-phase plate to generate a speckle pattern with a precisely controlled envelope on target. A number of temporal smoothing techniques can then be employed to utilize bandwidth to rapidly change the speckle pattern, and thus average out the small-scale speckle structure. One technique which generally can supplement other smoothing methods is polarization smoothing (PS): the illumination of the target with two distinct and orthogonally polarized speckle patterns. Since these two polarizations do not interfere, the intensity patterns add incoherently, and the rms nonuniformity can be reduced by a factor of (√2). A number of PS schemes are described and compared on the basis of the aggregate rms and the spatial spectrum of the focused illumination distribution. The (√2) rms nonuniformity reduction of PS is present on an instantaneous basis and is, therefore, of particular interest for the suppression of laser plasma instabilities, which have a very rapid response time. When combining PS and temporal methods, such as smoothing by spectral dispersion (SSD), PS can reduce the rms of the temporally smoothed illumination by an additional factor of (√2). However, it has generally been thought that in order to achieve this reduction of (√2), the increased divergence of the beam from PS must exceed the divergence of SSD. It is also shown here that, over the time scales of interest to direct or indirect drive ICF, under some conditions PS can reduce the smoothed illumination rms by nearly (√2) even when the PS divergence is much smaller than that of SSD. (c) 2000 American Institute of Physics
Directory of Open Access Journals (Sweden)
Mustafa Mir
Full Text Available Studying the 3D sub-cellular structure of living cells is essential to our understanding of biological function. However, tomographic imaging of live cells is challenging mainly because they are transparent, i.e., weakly scattering structures. Therefore, this type of imaging has been implemented largely using fluorescence techniques. While confocal fluorescence imaging is a common approach to achieve sectioning, it requires fluorescence probes that are often harmful to the living specimen. On the other hand, by using the intrinsic contrast of the structures it is possible to study living cells in a non-invasive manner. One method that provides high-resolution quantitative information about nanoscale structures is a broadband interferometric technique known as Spatial Light Interference Microscopy (SLIM. In addition to rendering quantitative phase information, when combined with a high numerical aperture objective, SLIM also provides excellent depth sectioning capabilities. However, like in all linear optical systems, SLIM's resolution is limited by diffraction. Here we present a novel 3D field deconvolution algorithm that exploits the sparsity of phase images and renders images with resolution beyond the diffraction limit. We employ this label-free method, called deconvolution Spatial Light Interference Tomography (dSLIT, to visualize coiled sub-cellular structures in E. coli cells which are most likely the cytoskeletal MreB protein and the division site regulating MinCDE proteins. Previously these structures have only been observed using specialized strains and plasmids and fluorescence techniques. Our results indicate that dSLIT can be employed to study such structures in a practical and non-invasive manner.
Chen, Chuihan; Miao, Wei; Zhou, Cheng; Wu, Hongjuan
2017-02-01
Thermogravimetric kinetic of bamboo waste (BW) pyrolysis has been studied using Asymmetric Double Sigmoidal (Asym2sig) function deconvolution. Through deconvolution, BW pyrolytic profiles could be separated into three reactions well, each of which corresponded to pseudo hemicelluloses (P-HC), pseudo cellulose (P-CL), and pseudo lignin (P-LG) decomposition. Based on Friedman method, apparent activation energy of P-HC, P-CL, P-LG was found to be 175.6kJ/mol, 199.7kJ/mol, and 158.4kJ/mol, respectively. Energy compensation effects (lnk 0, z vs. E z ) of pseudo components were in well linearity, from which pre-exponential factors (k 0 ) were determined as 6.22E+11s -1 (P-HC), 4.50E+14s -1 (P-CL) and 1.3E+10s -1 (P-LG). Integral master-plots results showed pyrolytic mechanism of P-HC, P-CL, and P-LG was reaction order of f(α)=(1-α) 2 , f(α)=1-α and f(α)=(1-α) n (n=6-8), respectively. Mechanism of P-HC and P-CL could be further reconstructed to n-th order Avrami-Erofeyev model of f(α)=0.62(1-α)[-ln(1-α)] -0.61 (n=0.62) and f(α)=1.08(1-α)[-ln(1-α)] 0.074 (n=1.08). Two-steps reaction was more suitable for P-LG pyrolysis. Copyright © 2016 Elsevier Ltd. All rights reserved.
Miao, Yonghao; Zhao, Ming; Lin, Jing; Lei, Yaguo
2017-08-01
The extraction of periodic impulses, which are the important indicators of rolling bearing faults, from vibration signals is considerably significance for fault diagnosis. Maximum correlated kurtosis deconvolution (MCKD) developed from minimum entropy deconvolution (MED) has been proven as an efficient tool for enhancing the periodic impulses in the diagnosis of rolling element bearings and gearboxes. However, challenges still exist when MCKD is applied to the bearings operating under harsh working conditions. The difficulties mainly come from the rigorous requires for the multi-input parameters and the complicated resampling process. To overcome these limitations, an improved MCKD (IMCKD) is presented in this paper. The new method estimates the iterative period by calculating the autocorrelation of the envelope signal rather than relies on the provided prior period. Moreover, the iterative period will gradually approach to the true fault period through updating the iterative period after every iterative step. Since IMCKD is unaffected by the impulse signals with the high kurtosis value, the new method selects the maximum kurtosis filtered signal as the final choice from all candidates in the assigned iterative counts. Compared with MCKD, IMCKD has three advantages. First, without considering prior period and the choice of the order of shift, IMCKD is more efficient and has higher robustness. Second, the resampling process is not necessary for IMCKD, which is greatly convenient for the subsequent frequency spectrum analysis and envelope spectrum analysis without resetting the sampling rate. Third, IMCKD has a significant performance advantage in diagnosing the bearing compound-fault which expands the application range. Finally, the effectiveness and superiority of IMCKD are validated by a number of simulated bearing fault signals and applying to compound faults and single fault diagnosis of a locomotive bearing.
Energy Technology Data Exchange (ETDEWEB)
Wylie, P.; Szelewski, M.; Meng, Chin-Kai [Agilent Technologies, Wilmington, DE (United States)
2004-09-15
More than 700 pesticides are approved for use around the world, many of which are suspected endocrine disrupters. Other pesticides, though no longer used, persist in the environment where they bioaccumulate in the flora and fauna. Analytical methods target only a subset of the possible compounds. The analysis of food and environmental samples for pesticides is usually complicated by the presence of co-extracted natural products. Food or tissue extracts can be exceedingly complex matrices that require several stages of sample cleanup prior to analysis. Even then, it can be difficult to detect trace levels of contaminants in the presence of the remaining matrix. For efficiency, multi-residue methods (MRMs) must be used to analyze for most pesticides. Traditionally, these methods have relied upon gas chromatography (GC) with a constellation of element-selective detectors to locate pesticides in the midst of a variable matrix. GC with mass spectral detection (GC/MS) has been widely used for confirmation of hits. Liquid chromatography (LC) has been used for those compounds that are not amenable to GC. Today, more and more pesticide laboratories are relying upon LC with mass spectral detection (LC/MS) and GC/MS as their primary analytical tools. Still, most MRMs are target compound methods that look for a small subset of the possible pesticides. Any compound not on the target list is likely to be missed by these methods. Using the techniques of retention time locking (RTL) and RTL database searching together with spectral deconvolution, a method has been developed to screen for 567 pesticides and suspected endocrine disrupters in a single GC/MS analysis. Spectral deconvolution helps to identify pesticides even when they co-elute with matrix compounds while RTL helps to eliminate false positives and gives greater confidence in the results.
Some properties of the smoothed Wigner function
International Nuclear Information System (INIS)
Soto, F.; Claverie, P.
1981-01-01
Recently it has been proposed a modification of the Wigner function which consists in smoothing it by convolution with a phase-space gaussian function; this smoothed Wigner function is non-negative if the gaussian parameters Δ and delta satisfy the condition Δdelta > h/2π. We analyze in this paper the predictions of this modified Wigner function for the harmonic oscillator, for anharmonic oscillator and finally for the hydrogen atom. We find agreement with experiment in the linear case, but for strongly nonlinear systems, such as the hydrogen atom, the results obtained are completely wrong. (orig.)
Cardiac, Skeletal, and smooth muscle mitochondrial respiration
DEFF Research Database (Denmark)
Park, Song-Young; Gifford, Jayson R; Andtbacka, Robert H I
2014-01-01
, skeletal, and smooth muscle was harvested from a total of 22 subjects (53±6 yrs) and mitochondrial respiration assessed in permeabilized fibers. Complex I+II, state 3 respiration, an index of oxidative phosphorylation capacity, fell progressively from cardiac, skeletal, to smooth muscle (54±1; 39±4; 15......±1 pmol•s(-1)•mg (-1), prespiration rates were normalized by CS (respiration...... per mitochondrial content), oxidative phosphorylation capacity was no longer different between the three muscle types. Interestingly, Complex I state 2 normalized for CS activity, an index of non-phosphorylating respiration per mitochondrial content, increased progressively from cardiac, skeletal...
Smooth massless limit of field theories
International Nuclear Information System (INIS)
Fronsdal, C.
1980-01-01
The massless limit of Fierz-Pauli field theories, describing fields with fixed mass and spin interacting with external sources, is examined. Results are obtained for spins, 1, 3/2, 2 and 3 using conventional models, and then for all half-integral spins in a relatively model-independent manner. It is found that the massless limit is smooth provided that the sources satisfy certain conditions. In the massless limit these conditions reduce to the conservation laws required by internal consistency of massless field theory. Smoothness simply requires that quantities that vanish in the massless case approach zero in a certain well-defined manner. (orig.)
Uncorrected refractive errors.
Naidoo, Kovin S; Jaggernath, Jyoti
2012-01-01
Global estimates indicate that more than 2.3 billion people in the world suffer from poor vision due to refractive error; of which 670 million people are considered visually impaired because they do not have access to corrective treatment. Refractive errors, if uncorrected, results in an impaired quality of life for millions of people worldwide, irrespective of their age, sex and ethnicity. Over the past decade, a series of studies using a survey methodology, referred to as Refractive Error Study in Children (RESC), were performed in populations with different ethnic origins and cultural settings. These studies confirmed that the prevalence of uncorrected refractive errors is considerably high for children in low-and-middle-income countries. Furthermore, uncorrected refractive error has been noted to have extensive social and economic impacts, such as limiting educational and employment opportunities of economically active persons, healthy individuals and communities. The key public health challenges presented by uncorrected refractive errors, the leading cause of vision impairment across the world, require urgent attention. To address these issues, it is critical to focus on the development of human resources and sustainable methods of service delivery. This paper discusses three core pillars to addressing the challenges posed by uncorrected refractive errors: Human Resource (HR) Development, Service Development and Social Entrepreneurship.
Directory of Open Access Journals (Sweden)
Kovin S Naidoo
2012-01-01
Full Text Available Global estimates indicate that more than 2.3 billion people in the world suffer from poor vision due to refractive error; of which 670 million people are considered visually impaired because they do not have access to corrective treatment. Refractive errors, if uncorrected, results in an impaired quality of life for millions of people worldwide, irrespective of their age, sex and ethnicity. Over the past decade, a series of studies using a survey methodology, referred to as Refractive Error Study in Children (RESC, were performed in populations with different ethnic origins and cultural settings. These studies confirmed that the prevalence of uncorrected refractive errors is considerably high for children in low-and-middle-income countries. Furthermore, uncorrected refractive error has been noted to have extensive social and economic impacts, such as limiting educational and employment opportunities of economically active persons, healthy individuals and communities. The key public health challenges presented by uncorrected refractive errors, the leading cause of vision impairment across the world, require urgent attention. To address these issues, it is critical to focus on the development of human resources and sustainable methods of service delivery. This paper discusses three core pillars to addressing the challenges posed by uncorrected refractive errors: Human Resource (HR Development, Service Development and Social Entrepreneurship.
Preventing Errors in Laterality
Landau, Elliot; Hirschorn, David; Koutras, Iakovos; Malek, Alexander; Demissie, Seleshie
2014-01-01
An error in laterality is the reporting of a finding that is present on the right side as on the left or vice versa. While different medical and surgical specialties have implemented protocols to help prevent such errors, very few studies have been published that describe these errors in radiology reports and ways to prevent them. We devised a system that allows the radiologist to view reports in a separate window, displayed in a simple font and with all terms of laterality highlighted in sep...
International Nuclear Information System (INIS)
Reason, J.
1988-01-01
This paper is in three parts. The first part summarizes the human failures responsible for the Chernobyl disaster and argues that, in considering the human contribution to power plant emergencies, it is necessary to distinguish between: errors and violations; and active and latent failures. The second part presents empirical evidence, drawn from driver behavior, which suggest that errors and violations have different psychological origins. The concluding part outlines a resident pathogen view of accident causation, and seeks to identify the various system pathways along which errors and violations may be propagated
16-dimensional smooth projective planes with large collineation groups
Bödi, Richard
1998-01-01
Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch) Smooth projective planes are projective planes defined on smooth manifolds (i.e. the set of points and the set of lines are smooth manifolds) such that the geometric operations of join and intersection are smooth. A systematic study of such planes and of their collineation groups can be found in previous works of the author. We prove in this paper that a 16-dimensional smooth projective plane which admits a ...
Energy Technology Data Exchange (ETDEWEB)
Ju, Lili; Tian, Li; Wang, Desheng
2008-10-31
In this paper, we present a residual-based a posteriori error estimate for the finite volume discretization of steady convection– diffusion–reaction equations defined on surfaces in R3, which are often implicitly represented as level sets of smooth functions. Reliability and efficiency of the proposed a posteriori error estimator are rigorously proved. Numerical experiments are also conducted to verify the theoretical results and demonstrate the robustness of the error estimator.
... this page: //medlineplus.gov/ency/patientinstructions/000618.htm Help prevent hospital errors To use the sharing features ... in the hospital. If You Are Having Surgery, Help Keep Yourself Safe Go to a hospital you ...
2012-03-01
This project examined the prevalence of pedal application errors and the driver, vehicle, roadway and/or environmental characteristics associated with pedal misapplication crashes based on a literature review, analysis of news media reports, a panel ...
International Nuclear Information System (INIS)
Jeach, J.L.
1976-01-01
When rounding error is large relative to weighing error, it cannot be ignored when estimating scale precision and bias from calibration data. Further, if the data grouping is coarse, rounding error is correlated with weighing error and may also have a mean quite different from zero. These facts are taken into account in a moment estimation method. A copy of the program listing for the MERDA program that provides moment estimates is available from the author. Experience suggests that if the data fall into four or more cells or groups, it is not necessary to apply the moment estimation method. Rather, the estimate given by equation (3) is valid in this instance. 5 tables
Spotting software errors sooner
International Nuclear Information System (INIS)
Munro, D.
1989-01-01
Static analysis is helping to identify software errors at an earlier stage and more cheaply than conventional methods of testing. RTP Software's MALPAS system also has the ability to check that a code conforms to its original specification. (author)
International Nuclear Information System (INIS)
Kop, L.
2001-01-01
On request, the Dutch Association for Energy, Environment and Water (VEMW) checks the energy bills for her customers. It appeared that in the year 2000 many small, but also big errors were discovered in the bills of 42 businesses
Medical Errors Reduction Initiative
National Research Council Canada - National Science Library
Mutter, Michael L
2005-01-01
The Valley Hospital of Ridgewood, New Jersey, is proposing to extend a limited but highly successful specimen management and medication administration medical errors reduction initiative on a hospital-wide basis...
An adaptive method for γ spectra smoothing
International Nuclear Information System (INIS)
Xiao Gang; Zhou Chunlin; Li Tiantuo; Han Feng; Di Yuming
2001-01-01
Adaptive wavelet method and multinomial fitting gliding method are used for smoothing γ spectra, respectively, and then FWHM of 1332 keV peak of 60 Co and activities of 238 U standard specimen are calculated. Calculated results show that adaptive wavelet method is better than the other
Smoothness in Banach spaces. Selected problems
Czech Academy of Sciences Publication Activity Database
Fabian, Marián; Montesinos, V.; Zizler, Václav
2006-01-01
Roč. 100, č. 2 (2006), s. 101-125 ISSN 1578-7303 R&D Projects: GA ČR(CZ) GA201/04/0090; GA AV ČR(CZ) IAA100190610 Institutional research plan: CEZ:AV0Z10190503 Keywords : smooth norm * renorming * weakly compactly generated space Subject RIV: BA - General Mathematics
The Koch curve as a smooth manifold
International Nuclear Information System (INIS)
Epstein, Marcelo; Sniatycki, Jedrzej
2008-01-01
We show that there exists a homeomorphism between the closed interval [0,1] is contained in R and the Koch curve endowed with the subset topology of R 2 . We use this homeomorphism to endow the Koch curve with the structure of a smooth manifold with boundary
on Isolated Smooth Muscle Preparation in Rats
African Journals Online (AJOL)
Samuel Olaleye
ABSTRACT. This study investigated the receptor effects of methanolic root extract of ... Phytochemical Analysis: Photochemistry of the methanolic extract was ... mounted with resting tension 0.5g in an organ bath containing .... Effects of extra cellular free Ca2+ and 0.5mM ... isolated smooth muscle by high K+ on the other.
PHANTOM: Smoothed particle hydrodynamics and magnetohydrodynamics code
Price, Daniel J.; Wurster, James; Nixon, Chris; Tricco, Terrence S.; Toupin, Stéven; Pettitt, Alex; Chan, Conrad; Laibe, Guillaume; Glover, Simon; Dobbs, Clare; Nealon, Rebecca; Liptai, David; Worpel, Hauke; Bonnerot, Clément; Dipierro, Giovanni; Ragusa, Enrico; Federrath, Christoph; Iaconi, Roberto; Reichardt, Thomas; Forgan, Duncan; Hutchison, Mark; Constantino, Thomas; Ayliffe, Ben; Mentiplay, Daniel; Hirsh, Kieran; Lodato, Giuseppe
2017-09-01
Phantom is a smoothed particle hydrodynamics and magnetohydrodynamics code focused on stellar, galactic, planetary, and high energy astrophysics. It is modular, and handles sink particles, self-gravity, two fluid and one fluid dust, ISM chemistry and cooling, physical viscosity, non-ideal MHD, and more. Its modular structure makes it easy to add new physics to the code.
Data driven smooth tests for composite hypotheses
Inglot, Tadeusz; Kallenberg, Wilbert C.M.; Ledwina, Teresa
1997-01-01
The classical problem of testing goodness-of-fit of a parametric family is reconsidered. A new test for this problem is proposed and investigated. The new test statistic is a combination of the smooth test statistic and Schwarz's selection rule. More precisely, as the sample size increases, an
Full Waveform Inversion Using Nonlinearly Smoothed Wavefields
Li, Y.; Choi, Yun Seok; Alkhalifah, Tariq Ali; Li, Z.
2017-01-01
The lack of low frequency information in the acquired data makes full waveform inversion (FWI) conditionally converge to the accurate solution. An initial velocity model that results in data with events within a half cycle of their location in the observed data was required to converge. The multiplication of wavefields with slightly different frequencies generates artificial low frequency components. This can be effectively utilized by multiplying the wavefield with itself, which is nonlinear operation, followed by a smoothing operator to extract the artificially produced low frequency information. We construct the objective function using the nonlinearly smoothed wavefields with a global-correlation norm to properly handle the energy imbalance in the nonlinearly smoothed wavefield. Similar to the multi-scale strategy, we progressively reduce the smoothing width applied to the multiplied wavefield to welcome higher resolution. We calculate the gradient of the objective function using the adjoint-state technique, which is similar to the conventional FWI except for the adjoint source. Examples on the Marmousi 2 model demonstrate the feasibility of the proposed FWI method to mitigate the cycle-skipping problem in the case of a lack of low frequency information.
On the theory of smooth structures. 2
International Nuclear Information System (INIS)
Shafei Deh Abad, A.
1992-09-01
In this paper we continue by introducing the concepts of substructures, quotient structures and tensor product, and examine some of their properties. By using the concept of tensor product, in the next paper, we will give another product for smooth structures which is a characterization of integral domains which are not fields. (author). 2 refs
Full Waveform Inversion Using Nonlinearly Smoothed Wavefields
Li, Y.
2017-05-26
The lack of low frequency information in the acquired data makes full waveform inversion (FWI) conditionally converge to the accurate solution. An initial velocity model that results in data with events within a half cycle of their location in the observed data was required to converge. The multiplication of wavefields with slightly different frequencies generates artificial low frequency components. This can be effectively utilized by multiplying the wavefield with itself, which is nonlinear operation, followed by a smoothing operator to extract the artificially produced low frequency information. We construct the objective function using the nonlinearly smoothed wavefields with a global-correlation norm to properly handle the energy imbalance in the nonlinearly smoothed wavefield. Similar to the multi-scale strategy, we progressively reduce the smoothing width applied to the multiplied wavefield to welcome higher resolution. We calculate the gradient of the objective function using the adjoint-state technique, which is similar to the conventional FWI except for the adjoint source. Examples on the Marmousi 2 model demonstrate the feasibility of the proposed FWI method to mitigate the cycle-skipping problem in the case of a lack of low frequency information.
Local smoothness for global optical flow
DEFF Research Database (Denmark)
Rakêt, Lars Lau
2012-01-01
by this technique and work on local-global optical flow we propose a simple method for fusing optical flow estimates of different smoothness by evaluating interpolation quality locally by means of L1 block match on the corresponding set of gradient images. We illustrate the method in a setting where optical flows...
Supplementary speed control for wind power smoothing
Haan, de J.E.S.; Frunt, J.; Kechroud, A.; Kling, W.L.
2010-01-01
Wind fluctuations result in even larger wind power fluctuations because the power of wind is proportional to the cube of the wind speed. This report analyzes wind power fluctuations to investigate inertial power smoothing, in particular for the frequency range of 0.08 - 0.5 Hz. Due to the growing
Klonoff, David C; Lias, Courtney; Vigersky, Robert; Clarke, William; Parkes, Joan Lee; Sacks, David B; Kirkman, M Sue; Kovatchev, Boris
2014-07-01
Currently used error grids for assessing clinical accuracy of blood glucose monitors are based on out-of-date medical practices. Error grids have not been widely embraced by regulatory agencies for clearance of monitors, but this type of tool could be useful for surveillance of the performance of cleared products. Diabetes Technology Society together with representatives from the Food and Drug Administration, the American Diabetes Association, the Endocrine Society, and the Association for the Advancement of Medical Instrumentation, and representatives of academia, industry, and government, have developed a new error grid, called the surveillance error grid (SEG) as a tool to assess the degree of clinical risk from inaccurate blood glucose (BG) monitors. A total of 206 diabetes clinicians were surveyed about the clinical risk of errors of measured BG levels by a monitor. The impact of such errors on 4 patient scenarios was surveyed. Each monitor/reference data pair was scored and color-coded on a graph per its average risk rating. Using modeled data representative of the accuracy of contemporary meters, the relationships between clinical risk and monitor error were calculated for the Clarke error grid (CEG), Parkes error grid (PEG), and SEG. SEG action boundaries were consistent across scenarios, regardless of whether the patient was type 1 or type 2 or using insulin or not. No significant differences were noted between responses of adult/pediatric or 4 types of clinicians. Although small specific differences in risk boundaries between US and non-US clinicians were noted, the panel felt they did not justify separate grids for these 2 types of clinicians. The data points of the SEG were classified in 15 zones according to their assigned level of risk, which allowed for comparisons with the classic CEG and PEG. Modeled glucose monitor data with realistic self-monitoring of blood glucose errors derived from meter testing experiments plotted on the SEG when compared to
DEFF Research Database (Denmark)
Rasmussen, Jens
1983-01-01
An important aspect of the optimal design of computer-based operator support systems is the sensitivity of such systems to operator errors. The author discusses how a system might allow for human variability with the use of reversibility and observability.......An important aspect of the optimal design of computer-based operator support systems is the sensitivity of such systems to operator errors. The author discusses how a system might allow for human variability with the use of reversibility and observability....
2008-01-01
One way in which physicians can respond to a medical error is to apologize. Apologies—statements that acknowledge an error and its consequences, take responsibility, and communicate regret for having caused harm—can decrease blame, decrease anger, increase trust, and improve relationships. Importantly, apologies also have the potential to decrease the risk of a medical malpractice lawsuit and can help settle claims by patients. Patients indicate they want and expect explanations and apologies after medical errors and physicians indicate they want to apologize. However, in practice, physicians tend to provide minimal information to patients after medical errors and infrequently offer complete apologies. Although fears about potential litigation are the most commonly cited barrier to apologizing after medical error, the link between litigation risk and the practice of disclosure and apology is tenuous. Other barriers might include the culture of medicine and the inherent psychological difficulties in facing one’s mistakes and apologizing for them. Despite these barriers, incorporating apology into conversations between physicians and patients can address the needs of both parties and can play a role in the effective resolution of disputes related to medical error. PMID:18972177
Thermodynamics of Error Correction
Directory of Open Access Journals (Sweden)
Pablo Sartori
2015-12-01
Full Text Available Information processing at the molecular scale is limited by thermal fluctuations. This can cause undesired consequences in copying information since thermal noise can lead to errors that can compromise the functionality of the copy. For example, a high error rate during DNA duplication can lead to cell death. Given the importance of accurate copying at the molecular scale, it is fundamental to understand its thermodynamic features. In this paper, we derive a universal expression for the copy error as a function of entropy production and work dissipated by the system during wrong incorporations. Its derivation is based on the second law of thermodynamics; hence, its validity is independent of the details of the molecular machinery, be it any polymerase or artificial copying device. Using this expression, we find that information can be copied in three different regimes. In two of them, work is dissipated to either increase or decrease the error. In the third regime, the protocol extracts work while correcting errors, reminiscent of a Maxwell demon. As a case study, we apply our framework to study a copy protocol assisted by kinetic proofreading, and show that it can operate in any of these three regimes. We finally show that, for any effective proofreading scheme, error reduction is limited by the chemical driving of the proofreading reaction.
Role of Smooth Muscle in Intestinal Inflammation
Directory of Open Access Journals (Sweden)
Stephen M Collins
1996-01-01
Full Text Available The notion that smooth muscle function is altered in inflammation is prompted by clinical observations of altered motility in patients with inflammatory bowel disease (IBD. While altered motility may reflect inflammation-induced changes in intrinsic or extrinsic nerves to the gut, changes in gut hormone release and changes in muscle function, recent studies have provided in vitro evidence of altered muscle contractility in muscle resected from patients with ulcerative colitis or Crohn’s disease. In addition, the observation that smooth muscle cells are more numerous and prominent in the strictured bowel of IBD patients compared with controls suggests that inflammation may alter the growth of intestinal smooth muscle. Thus, inflammation is associated with changes in smooth muscle growth and contractility that, in turn, contribute to important symptoms of IBD including diarrhea (from altered motility and pain (via either altered motility or stricture formation. The involvement of smooth muscle in this context may be as an innocent bystander, where cells and products of the inflammatory process induce alterations in muscle contractility and growth. However, it is likely that intestinal muscle cells play a more active role in the inflammatory process via the elaboration of mediators and trophic factors, including cytokines, and via the production of collagen. The concept of muscle cells as active participants in the intestinal inflammatory process is a new concept that is under intense study. This report summarizes current knowledge as it relates to these two aspects of altered muscle function (growth and contractility in the inflamed intestine, and will focus on mechanisms underlying these changes, based on data obtained from animal models of intestinal inflammation.
Smoothing a Piecewise-Smooth: An Example from Plankton Population Dynamics
DEFF Research Database (Denmark)
Piltz, Sofia Helena
2016-01-01
In this work we discuss a piecewise-smooth dynamical system inspired by plankton observations and constructed for one predator switching its diet between two different types of prey. We then discuss two smooth formulations of the piecewise-smooth model obtained by using a hyperbolic tangent funct...... function and adding a dimension to the system. We compare model behaviour of the three systems and show an example case where the steepness of the switch is determined from a comparison with data on freshwater plankton....
Directory of Open Access Journals (Sweden)
Yuan Xu
2013-11-01
Full Text Available In order to reduce the estimated errors of the inertial navigation system (INS/Wireless sensor network (WSN-integrated navigation for mobile robots indoors, this work proposes an on-line iterated extended Rauch-Tung-Striebel smoothing (IERTSS utilizing inertial measuring units (IMUs and an ultrasonic positioning system. In this mode, an iterated Extended Kalman filter (IEKF is used in forward data processing of the Extended Rauch-Tung-Striebel smoothing (ERTSS to improve the accuracy of the filtering output for the smoother. Furthermore, in order to achieve the on-line smoothing, IERTSS is embedded into the average filter. For verification, a real indoor test has been done to assess the performance of the proposed method. The results show that the proposed method is effective in reducing the errors compared with the conventional schemes.
National Research Council Canada - National Science Library
Matson, Charles; Haji, Alim
2007-01-01
Multi-frame blind deconvolution (MFBD) algorithms can be used to generate a deblurred image of an object from a sequence of short-exposure and atmospherically-blurred images of the object by jointly estimating the common object...
Directory of Open Access Journals (Sweden)
MA. Lendita Kryeziu
2015-06-01
Full Text Available “Errare humanum est”, a well known and widespread Latin proverb which states that: to err is human, and that people make mistakes all the time. However, what counts is that people must learn from mistakes. On these grounds Steve Jobs stated: “Sometimes when you innovate, you make mistakes. It is best to admit them quickly, and get on with improving your other innovations.” Similarly, in learning new language, learners make mistakes, thus it is important to accept them, learn from them, discover the reason why they make them, improve and move on. The significance of studying errors is described by Corder as: “There have always been two justifications proposed for the study of learners' errors: the pedagogical justification, namely that a good understanding of the nature of error is necessary before a systematic means of eradicating them could be found, and the theoretical justification, which claims that a study of learners' errors is part of the systematic study of the learners' language which is itself necessary to an understanding of the process of second language acquisition” (Corder, 1982; 1. Thus the importance and the aim of this paper is analyzing errors in the process of second language acquisition and the way we teachers can benefit from mistakes to help students improve themselves while giving the proper feedback.
Compact disk error measurements
Howe, D.; Harriman, K.; Tehranchi, B.
1993-01-01
The objectives of this project are as follows: provide hardware and software that will perform simple, real-time, high resolution (single-byte) measurement of the error burst and good data gap statistics seen by a photoCD player read channel when recorded CD write-once discs of variable quality (i.e., condition) are being read; extend the above system to enable measurement of the hard decision (i.e., 1-bit error flags) and soft decision (i.e., 2-bit error flags) decoding information that is produced/used by the Cross Interleaved - Reed - Solomon - Code (CIRC) block decoder employed in the photoCD player read channel; construct a model that uses data obtained via the systems described above to produce meaningful estimates of output error rates (due to both uncorrected ECC words and misdecoded ECC words) when a CD disc having specific (measured) error statistics is read (completion date to be determined); and check the hypothesis that current adaptive CIRC block decoders are optimized for pressed (DAD/ROM) CD discs. If warranted, do a conceptual design of an adaptive CIRC decoder that is optimized for write-once CD discs.
Sabini, M G; Cuttone, G; Guasti, A; Mazzocchi, S; Raffaele, L
2002-01-01
In this work, the dose response of TLD-100 dosimeters has been studied in a 62 MeV clinical proton beams. The signal versus dose curve has been compared with the one measured in a sup 6 sup 0 Co beam. Different experiments have been performed in order to observe the thermal stress and the radiation damage effects on the detector sensitivity. A LET dependence of the TL response has been observed. In order to get a physical interpretation of these effects, a computerised glow-curve deconvolution has been employed. The results of all the performed experiments and deconvolutions are extensively reported, and the TLD-100 possible fields of application in the clinical proton dosimetry are discussed.
Directory of Open Access Journals (Sweden)
K. Hacıefendioğlu
2012-04-01
Full Text Available The deconvolution effect of the near-fault earthquake ground motions on the stochastic dynamic response of tunnel-soil deposit interaction systems are investigated by using the finite element method. Two different earthquake input mechanisms are used to consider the deconvolution effects in the analyses: the standard rigid-base input and the deconvolved-base-rock input model. The Bolu tunnel in Turkey is chosen as a numerical example. As near-fault ground motions, 1999 Kocaeli earthquake ground motion is selected. The interface finite elements are used between tunnel and soil deposit. The mean of maximum values of quasi-static, dynamic and total responses obtained from the two input models are compared with each other.
Chae, Kum Ju; Goo, Jin Mo; Ahn, Su Yeon; Yoo, Jin Young; Yoon, Soon Ho
2018-01-01
To evaluate the preference of observers for image quality of chest radiography using the deconvolution algorithm of point spread function (PSF) (TRUVIEW ART algorithm, DRTECH Corp.) compared with that of original chest radiography for visualization of anatomic regions of the chest. Prospectively enrolled 50 pairs of posteroanterior chest radiographs collected with standard protocol and with additional TRUVIEW ART algorithm were compared by four chest radiologists. This algorithm corrects scattered signals generated by a scintillator. Readers independently evaluated the visibility of 10 anatomical regions and overall image quality with a 5-point scale of preference. The significance of the differences in reader's preference was tested with a Wilcoxon's signed rank test. All four readers preferred the images applied with the algorithm to those without algorithm for all 10 anatomical regions (mean, 3.6; range, 3.2-4.0; p chest anatomical structures applied with the deconvolution algorithm of PSF was superior to the original chest radiography.
Error Checking for Chinese Query by Mining Web Log
Directory of Open Access Journals (Sweden)
Jianyong Duan
2015-01-01
Full Text Available For the search engine, error-input query is a common phenomenon. This paper uses web log as the training set for the query error checking. Through the n-gram language model that is trained by web log, the queries are analyzed and checked. Some features including query words and their number are introduced into the model. At the same time data smoothing algorithm is used to solve data sparseness problem. It will improve the overall accuracy of the n-gram model. The experimental results show that it is effective.
Directory of Open Access Journals (Sweden)
Kuo Men
2017-12-01
Full Text Available BackgroundRadiotherapy is one of the main treatment methods for nasopharyngeal carcinoma (NPC. It requires exact delineation of the nasopharynx gross tumor volume (GTVnx, the metastatic lymph node gross tumor volume (GTVnd, the clinical target volume (CTV, and organs at risk in the planning computed tomography images. However, this task is time-consuming and operator dependent. In the present study, we developed an end-to-end deep deconvolutional neural network (DDNN for segmentation of these targets.MethodsThe proposed DDNN is an end-to-end architecture enabling fast training and testing. It consists of two important components: an encoder network and a decoder network. The encoder network was used to extract the visual features of a medical image and the decoder network was used to recover the original resolution by deploying deconvolution. A total of 230 patients diagnosed with NPC stage I or stage II were included in this study. Data from 184 patients were chosen randomly as a training set to adjust the parameters of DDNN, and the remaining 46 patients were the test set to assess the performance of the model. The Dice similarity coefficient (DSC was used to quantify the segmentation results of the GTVnx, GTVnd, and CTV. In addition, the performance of DDNN was compared with the VGG-16 model.ResultsThe proposed DDNN method outperformed the VGG-16 in all the segmentation. The mean DSC values of DDNN were 80.9% for GTVnx, 62.3% for the GTVnd, and 82.6% for CTV, whereas VGG-16 obtained 72.3, 33.7, and 73.7% for the DSC values, respectively.ConclusionDDNN can be used to segment the GTVnx and CTV accurately. The accuracy for the GTVnd segmentation was relatively low due to the considerable differences in its shape, volume, and location among patients. The accuracy is expected to increase with more training data and combination of MR images. In conclusion, DDNN has the potential to improve the consistency of contouring and streamline radiotherapy
Men, Kuo; Chen, Xinyuan; Zhang, Ye; Zhang, Tao; Dai, Jianrong; Yi, Junlin; Li, Yexiong
2017-01-01
Radiotherapy is one of the main treatment methods for nasopharyngeal carcinoma (NPC). It requires exact delineation of the nasopharynx gross tumor volume (GTVnx), the metastatic lymph node gross tumor volume (GTVnd), the clinical target volume (CTV), and organs at risk in the planning computed tomography images. However, this task is time-consuming and operator dependent. In the present study, we developed an end-to-end deep deconvolutional neural network (DDNN) for segmentation of these targets. The proposed DDNN is an end-to-end architecture enabling fast training and testing. It consists of two important components: an encoder network and a decoder network. The encoder network was used to extract the visual features of a medical image and the decoder network was used to recover the original resolution by deploying deconvolution. A total of 230 patients diagnosed with NPC stage I or stage II were included in this study. Data from 184 patients were chosen randomly as a training set to adjust the parameters of DDNN, and the remaining 46 patients were the test set to assess the performance of the model. The Dice similarity coefficient (DSC) was used to quantify the segmentation results of the GTVnx, GTVnd, and CTV. In addition, the performance of DDNN was compared with the VGG-16 model. The proposed DDNN method outperformed the VGG-16 in all the segmentation. The mean DSC values of DDNN were 80.9% for GTVnx, 62.3% for the GTVnd, and 82.6% for CTV, whereas VGG-16 obtained 72.3, 33.7, and 73.7% for the DSC values, respectively. DDNN can be used to segment the GTVnx and CTV accurately. The accuracy for the GTVnd segmentation was relatively low due to the considerable differences in its shape, volume, and location among patients. The accuracy is expected to increase with more training data and combination of MR images. In conclusion, DDNN has the potential to improve the consistency of contouring and streamline radiotherapy workflows, but careful human review and a
Directory of Open Access Journals (Sweden)
Antonio Boldrini
2013-06-01
Full Text Available Introduction: Danger and errors are inherent in human activities. In medical practice errors can lean to adverse events for patients. Mass media echo the whole scenario. Methods: We reviewed recent published papers in PubMed database to focus on the evidence and management of errors in medical practice in general and in Neonatology in particular. We compared the results of the literature with our specific experience in Nina Simulation Centre (Pisa, Italy. Results: In Neonatology the main error domains are: medication and total parenteral nutrition, resuscitation and respiratory care, invasive procedures, nosocomial infections, patient identification, diagnostics. Risk factors include patients’ size, prematurity, vulnerability and underlying disease conditions but also multidisciplinary teams, working conditions providing fatigue, a large variety of treatment and investigative modalities needed. Discussion and Conclusions: In our opinion, it is hardly possible to change the human beings but it is likely possible to change the conditions under they work. Voluntary errors report systems can help in preventing adverse events. Education and re-training by means of simulation can be an effective strategy too. In Pisa (Italy Nina (ceNtro di FormazIone e SimulazioNe NeonAtale is a simulation center that offers the possibility of a continuous retraining for technical and non-technical skills to optimize neonatological care strategies. Furthermore, we have been working on a novel skill trainer for mechanical ventilation (MEchatronic REspiratory System SImulator for Neonatal Applications, MERESSINA. Finally, in our opinion national health policy indirectly influences risk for errors. Proceedings of the 9th International Workshop on Neonatology · Cagliari (Italy · October 23rd-26th, 2013 · Learned lessons, changing practice and cutting-edge research
On smoothness-asymmetric null infinities
International Nuclear Information System (INIS)
Valiente Kroon, Juan Antonio
2006-01-01
We discuss the existence of asymptotically Euclidean initial data sets for the vacuum Einstein field equations which would give rise (modulo an existence result for the evolution equations near spatial infinity) to developments with a past and a future null infinity of different smoothness. For simplicity, the analysis is restricted to the class of conformally flat, axially symmetric initial data sets. It is shown how the free parameters in the second fundamental form of the data can be used to satisfy certain obstructions to the smoothness of null infinity. The resulting initial data sets could be interpreted as those of some sort of (nonlinearly) distorted Schwarzschild black hole. Their developments would be that they admit a peeling future null infinity, but at the same time have a polyhomogeneous (non-peeling) past null infinity
Smooth homogeneous structures in operator theory
Beltita, Daniel
2005-01-01
Geometric ideas and techniques play an important role in operator theory and the theory of operator algebras. Smooth Homogeneous Structures in Operator Theory builds the background needed to understand this circle of ideas and reports on recent developments in this fruitful field of research. Requiring only a moderate familiarity with functional analysis and general topology, the author begins with an introduction to infinite dimensional Lie theory with emphasis on the relationship between Lie groups and Lie algebras. A detailed examination of smooth homogeneous spaces follows. This study is illustrated by familiar examples from operator theory and develops methods that allow endowing such spaces with structures of complex manifolds. The final section of the book explores equivariant monotone operators and Kähler structures. It examines certain symmetry properties of abstract reproducing kernels and arrives at a very general version of the construction of restricted Grassmann manifolds from the theory of loo...
Baniamerian, Jamaledin; Liu, Shuang; Abbas, Mahmoud Ahmed
2018-04-01
The vertical gradient is an essential tool in interpretation algorithms. It is also the primary enhancement technique to improve the resolution of measured gravity and magnetic field data, since it has higher sensitivity to changes in physical properties (density or susceptibility) of the subsurface structures than the measured field. If the field derivatives are not directly measured with the gradiometers, they can be calculated from the collected gravity or magnetic data using numerical methods such as those based on fast Fourier transform technique. The gradients behave similar to high-pass filters and enhance the short-wavelength anomalies which may be associated with either small-shallow sources or high-frequency noise content in data, and their numerical computation is susceptible to suffer from amplification of noise. This behaviour can adversely affect the stability of the derivatives in the presence of even a small level of the noise and consequently limit their application to interpretation methods. Adding a smoothing term to the conventional formulation of calculating the vertical gradient in Fourier domain can improve the stability of numerical differentiation of the field. In this paper, we propose a strategy in which the overall efficiency of the classical algorithm in Fourier domain is improved by incorporating two different smoothing filters. For smoothing term, a simple qualitative procedure based on the upward continuation of the field to a higher altitude is introduced to estimate the related parameters which are called regularization parameter and cut-off wavenumber in the corresponding filters. The efficiency of these new approaches is validated by computing the first- and second-order derivatives of noise-corrupted synthetic data sets and then comparing the results with the true ones. The filtered and unfiltered vertical gradients are incorporated into the extended Euler deconvolution to estimate the depth and structural index of a magnetic
LIBERTARISMO & ERROR CATEGORIAL
Directory of Open Access Journals (Sweden)
Carlos G. Patarroyo G.
2009-01-01
Full Text Available En este artículo se ofrece una defensa del libertarismo frente a dos acusaciones según las cuales éste comete un error categorial. Para ello, se utiliza la filosofía de Gilbert Ryle como herramienta para explicar las razones que fundamentan estas acusaciones y para mostrar por qué, pese a que ciertas versiones del libertarismo que acuden a la causalidad de agentes o al dualismo cartesiano cometen estos errores, un libertarismo que busque en el indeterminismo fisicalista la base de la posibilidad de la libertad humana no necesariamente puede ser acusado de incurrir en ellos.
Libertarismo & Error Categorial
PATARROYO G, CARLOS G
2009-01-01
En este artículo se ofrece una defensa del libertarismo frente a dos acusaciones según las cuales éste comete un error categorial. Para ello, se utiliza la filosofía de Gilbert Ryle como herramienta para explicar las razones que fundamentan estas acusaciones y para mostrar por qué, pese a que ciertas versiones del libertarismo que acuden a la causalidad de agentes o al dualismo cartesiano cometen estos errores, un libertarismo que busque en el indeterminismo fisicalista la base de la posibili...
1985-01-01
A mathematical theory for development of "higher order" software to catch computer mistakes resulted from a Johnson Space Center contract for Apollo spacecraft navigation. Two women who were involved in the project formed Higher Order Software, Inc. to develop and market the system of error analysis and correction. They designed software which is logically error-free, which, in one instance, was found to increase productivity by 600%. USE.IT defines its objectives using AXES -- a user can write in English and the system converts to computer languages. It is employed by several large corporations.
Does responsive pricing smooth demand shocks?
Pascal, Courty; Mario, Pagliero
2011-01-01
Using data from a unique pricing experiment, we investigate Vickrey’s conjecture that responsive pricing can be used to smooth both predictable and unpredictable demand shocks. Our evidence shows that increasing the responsiveness of price to demand conditions reduces the magnitude of deviations in capacity utilization rates from a pre-determined target level. A 10 percent increase in price variability leads to a decrease in the variability of capacity utilization rates between...
The Smooth Muscle of the Artery
1975-01-01
of vascular smooth muscle are contrac- tion, thereby mediating vaso constriction, and the synthesis of the extracellular proteins and polysaccharides ...of the monosaccharides turned out to be different for instance from cornea to aorta (229, 283). In the conditions yed (4 hours incubation at 37 degrees... polysaccharides only. This glyco- protein is not very rich in sugar components (- 5Z) (228, 284), but is a very acidic protein (286). Fig.66 shows
International Nuclear Information System (INIS)
Schaffer, J.P.; Shaughnessy, E.J.; Jones, P.L.
1984-01-01
A deconvolution procedure which corrects Doppler-broadened positron annihilation spectra for instrument resolution is described. The method employs fast Fourier transforms, is model independent, and does not require iteration. The mathematical difficulties associated with the incorrectly posed first order Fredholm integral equation are overcome by using power spectral analysis to select a limited number of low frequency Fourier coefficients. The FFT/power spectrum method is then demonstrated for an irradiated high purity single crystal sapphire sample. (orig.)
International Nuclear Information System (INIS)
Reginatto, M.; Goldhagen, P.
1998-06-01
The problem of analyzing data from a multisphere neutron spectrometer to infer the energy spectrum of the incident neutrons is discussed. The main features of the code MAXED, a computer program developed to apply the maximum entropy principle to the deconvolution (unfolding) of multisphere neutron spectrometer data, are described, and the use of the code is illustrated with an example. A user's guide for the code MAXED is included in an appendix. The code is available from the authors upon request
Directory of Open Access Journals (Sweden)
Olurin Oluwaseun Tolutope
2017-12-01
Full Text Available Interpretation of high resolution aeromagnetic data of Ilesha and its environs within the basement complex of the geological setting of Southwestern Nigeria was carried out in the study. The study area is delimited by geographic latitudes 7°30′–8°00′N and longitudes 4°30′–5°00′E. This investigation was carried out using Euler deconvolution on filtered digitised total magnetic data (Sheet Number 243 to delineate geological structures within the area under consideration. The digitised airborne magnetic data acquired in 2009 were obtained from the archives of the Nigeria Geological Survey Agency (NGSA. The airborne magnetic data were filtered, processed and enhanced; the resultant data were subjected to qualitative and quantitative magnetic interpretation, geometry and depth weighting analyses across the study area using Euler deconvolution filter control file in Oasis Montag software. Total magnetic intensity distribution in the field ranged from –77.7 to 139.7 nT. Total magnetic field intensities reveal high-magnitude magnetic intensity values (high-amplitude anomaly and magnetic low intensities (low-amplitude magnetic anomaly in the area under consideration. The study area is characterised with high intensity correlated with lithological variation in the basement. The sharp contrast is enhanced due to the sharp contrast in magnetic intensity between the magnetic susceptibilities of the crystalline and sedimentary rocks. The reduced-to-equator (RTE map is characterised by high frequencies, short wavelengths, small size, weak intensity, sharp low amplitude and nearly irregular shaped anomalies, which may due to near-surface sources, such as shallow geologic units and cultural features. Euler deconvolution solution indicates a generally undulating basement, with a depth ranging from −500 to 1000 m. The Euler deconvolution results show that the basement relief is generally gentle and flat, lying within the basement terrain.
Energy Technology Data Exchange (ETDEWEB)
Harper, Brett [Institute of Biomedical Studies, Baylor University, Waco, TX 76798 (United States); Neumann, Elizabeth K. [Department of Chemistry and Biochemistry, Baylor University, Waco, TX 76798 (United States); Stow, Sarah M.; May, Jody C.; McLean, John A. [Department of Chemistry, Vanderbilt University, Nashville, TN 37235 (United States); Vanderbilt Institute of Chemical Biology, Nashville, TN 37235 (United States); Vanderbilt Institute for Integrative Biosystems Research and Education, Nashville, TN 37235 (United States); Center for Innovative Technology, Nashville, TN 37235 (United States); Solouki, Touradj, E-mail: Touradj_Solouki@baylor.edu [Department of Chemistry and Biochemistry, Baylor University, Waco, TX 76798 (United States)
2016-10-05
Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288.{sub 8} Å{sup 2}, 295.{sub 1} Å{sup 2}, 296.{sub 8} Å{sup 2}, and 300.{sub 1} Å{sup 2}; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.
International Nuclear Information System (INIS)
Harper, Brett; Neumann, Elizabeth K.; Stow, Sarah M.; May, Jody C.; McLean, John A.; Solouki, Touradj
2016-01-01
Ion mobility (IM) is an important analytical technique for determining ion collision cross section (CCS) values in the gas-phase and gaining insight into molecular structures and conformations. However, limited instrument resolving powers for IM may restrict adequate characterization of conformationally similar ions, such as structural isomers, and reduce the accuracy of IM-based CCS calculations. Recently, we introduced an automated technique for extracting “pure” IM and collision-induced dissociation (CID) mass spectra of IM overlapping species using chemometric deconvolution of post-IM/CID mass spectrometry (MS) data [J. Am. Soc. Mass Spectrom., 2014, 25, 1810–1819]. Here we extend those capabilities to demonstrate how extracted IM profiles can be used to calculate accurate CCS values of peptide isomer ions which are not fully resolved by IM. We show that CCS values obtained from deconvoluted IM spectra match with CCS values measured from the individually analyzed corresponding peptides on uniform field IM instrumentation. We introduce an approach that utilizes experimentally determined IM arrival time (AT) “shift factors” to compensate for ion acceleration variations during post-IM/CID and significantly improve the accuracy of the calculated CCS values. Also, we discuss details of this IM deconvolution approach and compare empirical CCS values from traveling wave (TW)IM-MS and drift tube (DT)IM-MS with theoretically calculated CCS values using the projected superposition approximation (PSA). For example, experimentally measured deconvoluted TWIM-MS mean CCS values for doubly-protonated RYGGFM, RMFGYG, MFRYGG, and FRMYGG peptide isomers were 288._8 Å"2, 295._1 Å"2, 296._8 Å"2, and 300._1 Å"2; all four of these CCS values were within 1.5% of independently measured DTIM-MS values.
Log canonical thresholds of smooth Fano threefolds
International Nuclear Information System (INIS)
Cheltsov, Ivan A; Shramov, Konstantin A
2008-01-01
The complex singularity exponent is a local invariant of a holomorphic function determined by the integrability of fractional powers of the function. The log canonical thresholds of effective Q-divisors on normal algebraic varieties are algebraic counterparts of complex singularity exponents. For a Fano variety, these invariants have global analogues. In the former case, it is the so-called α-invariant of Tian; in the latter case, it is the global log canonical threshold of the Fano variety, which is the infimum of log canonical thresholds of all effective Q-divisors numerically equivalent to the anticanonical divisor. An appendix to this paper contains a proof that the global log canonical threshold of a smooth Fano variety coincides with its α-invariant of Tian. The purpose of the paper is to compute the global log canonical thresholds of smooth Fano threefolds (altogether, there are 105 deformation families of such threefolds). The global log canonical thresholds are computed for every smooth threefold in 64 deformation families, and the global log canonical thresholds are computed for a general threefold in 20 deformation families. Some bounds for the global log canonical thresholds are computed for 14 deformation families. Appendix A is due to J.-P. Demailly.
Smooth Nb surfaces fabricated by buffered electropolishing
International Nuclear Information System (INIS)
Wu, Andy T.; Mammosser, John; Phillips, Larry; Delayen, Jean; Reece, Charles; Wilkerson, Amy; Smith, David; Ike, Robert
2007-01-01
It was demonstrated that smooth Nb surfaces could be obtained through buffered electropolishing (BEP) employing an electrolyte consisting of lactic, sulfuric, and hydrofluoric acids. Parameters that control the polishing process were optimized to achieve a smooth surface finish. The polishing rate of BEP was determined to be 0.646 μm/min which was much higher than 0.381 μm/min achieved by the conventional electropolishing (EP) process widely used in the superconducting radio frequency (SRF) community. Root mean square measurements using a 3D profilometer revealed that Nb surfaces treated by BEP were an order of magnitude smoother than those treated by the optimized EP process. The chemical composition of the Nb surfaces after BEP was analyzed by static and dynamic secondary ion mass spectrometry (SIMS) systems. SIMS results implied that the surface oxide structure of Nb might be more complicated than what usually believed and could be inhomogeneous. Preliminary results of BEP on Nb SRF single cell cavities and half-cells were reported. It was shown that smooth and bright surfaces could be obtained in 1800 s when the electric field inside a SRF cavity was uniform during a BEP process. This study showed that BEP is a promising technique for surface treatment on Nb SRF cavities to be used in particle accelerators
Boutet de Monvel, Jacques; Le Calvez, Sophie; Ulfendahl, Mats
2000-05-01
Image restoration algorithms provide efficient tools for recovering part of the information lost in the imaging process of a microscope. We describe recent progress in the application of deconvolution to confocal microscopy. The point spread function of a Biorad-MRC1024 confocal microscope was measured under various imaging conditions, and used to process 3D-confocal images acquired in an intact preparation of the inner ear developed at Karolinska Institutet. Using these experiments we investigate the application of denoising methods based on wavelet analysis as a natural regularization of the deconvolution process. Within the Bayesian approach to image restoration, we compare wavelet denoising with the use of a maximum entropy constraint as another natural regularization method. Numerical experiments performed with test images show a clear advantage of the wavelet denoising approach, allowing to `cool down' the image with respect to the signal, while suppressing much of the fine-scale artifacts appearing during deconvolution due to the presence of noise, incomplete knowledge of the point spread function, or undersampling problems. We further describe a natural development of this approach, which consists of performing the Bayesian inference directly in the wavelet domain.
Choi, Yun Seok
2017-11-15
Full waveform inversion (FWI) suffers from the cycle-skipping problem when the available frequency-band of data is not low enough. We apply an exponential damping to the data to generate artificial low frequencies, which helps FWI avoid cycle skipping. In this case, the least-square misfit function does not properly deal with the exponentially damped wavefield in FWI, because the amplitude of traces decays almost exponentially with increasing offset in a damped wavefield. Thus, we use a deconvolution-based objective function for FWI of the exponentially damped wavefield. The deconvolution filter includes inherently a normalization between the modeled and observed data, thus it can address the unbalanced amplitude of a damped wavefield. We, specifically, normalize the modeled data with the observed data in the frequency-domain to estimate the deconvolution filter and selectively choose a frequency-band for normalization that mainly includes the artificial low frequencies. We calculate the gradient of the objective function using the adjoint-state method. The synthetic and benchmark data examples show that our FWI algorithm generates a convergent long wavelength structure without low frequency information in the recorded data.
International Nuclear Information System (INIS)
Wille, M-L; Langton, C M; Zapf, M; Ruiter, N V; Gemmeke, H
2015-01-01
The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs versus 0.18 μs standard deviations), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity. (note)
Koh, T S; Wu, X Y; Cheong, L H; Lim, C C T
2004-12-01
The assessment of tissue perfusion by dynamic contrast-enhanced (DCE) imaging involves a deconvolution process. For analysis of DCE imaging data, we implemented a regression approach to select appropriate regularization parameters for deconvolution using the standard and generalized singular value decomposition methods. Monte Carlo simulation experiments were carried out to study the performance and to compare with other existing methods used for deconvolution analysis of DCE imaging data. The present approach is found to be robust and reliable at the levels of noise commonly encountered in DCE imaging, and for different models of the underlying tissue vasculature. The advantages of the present method, as compared with previous methods, include its efficiency of computation, ability to achieve adequate regularization to reproduce less noisy solutions, and that it does not require prior knowledge of the noise condition. The proposed method is applied on actual patient study cases with brain tumors and ischemic stroke, to illustrate its applicability as a clinical tool for diagnosis and assessment of treatment response.
Rosen, I G; Luczak, Susan E; Weiss, Jordan
2014-03-15
We develop a blind deconvolution scheme for input-output systems described by distributed parameter systems with boundary input and output. An abstract functional analytic theory based on results for the linear quadratic control of infinite dimensional systems with unbounded input and output operators is presented. The blind deconvolution problem is then reformulated as a series of constrained linear and nonlinear optimization problems involving infinite dimensional dynamical systems. A finite dimensional approximation and convergence theory is developed. The theory is applied to the problem of estimating blood or breath alcohol concentration (respectively, BAC or BrAC) from biosensor-measured transdermal alcohol concentration (TAC) in the field. A distributed parameter model with boundary input and output is proposed for the transdermal transport of ethanol from the blood through the skin to the sensor. The problem of estimating BAC or BrAC from the TAC data is formulated as a blind deconvolution problem. A scheme to identify distinct drinking episodes in TAC data based on a Hodrick Prescott filter is discussed. Numerical results involving actual patient data are presented.
Choi, Yun Seok; Alkhalifah, Tariq Ali
2017-01-01
Full waveform inversion (FWI) suffers from the cycle-skipping problem when the available frequency-band of data is not low enough. We apply an exponential damping to the data to generate artificial low frequencies, which helps FWI avoid cycle skipping. In this case, the least-square misfit function does not properly deal with the exponentially damped wavefield in FWI, because the amplitude of traces decays almost exponentially with increasing offset in a damped wavefield. Thus, we use a deconvolution-based objective function for FWI of the exponentially damped wavefield. The deconvolution filter includes inherently a normalization between the modeled and observed data, thus it can address the unbalanced amplitude of a damped wavefield. We, specifically, normalize the modeled data with the observed data in the frequency-domain to estimate the deconvolution filter and selectively choose a frequency-band for normalization that mainly includes the artificial low frequencies. We calculate the gradient of the objective function using the adjoint-state method. The synthetic and benchmark data examples show that our FWI algorithm generates a convergent long wavelength structure without low frequency information in the recorded data.
2014-01-01
We propose a smooth approximation l 0-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l 0-norm (SL0) penalty on the coefficients into the standard APA cost function, which gives rise to a zero attractor that promotes the sparsity of the channel taps in the channel estimation and hence accelerates the convergence speed and reduces the steady-state error when the channel is sparse. The simulation results demonstrate that our proposed SL0-APA is superior to the standard APA and its sparsity-aware algorithms in terms of both the convergence speed and the steady-state behavior in a designated sparse channel. Furthermore, SL0-APA is shown to have smaller steady-state error than the previously proposed sparsity-aware algorithms when the number of nonzero taps in the sparse channel increases. PMID:24790588
Indian Academy of Sciences (India)
Science and Automation at ... the Reed-Solomon code contained 223 bytes of data, (a byte ... then you have a data storage system with error correction, that ..... practical codes, storing such a table is infeasible, as it is generally too large.
Indian Academy of Sciences (India)
Home; Journals; Resonance – Journal of Science Education; Volume 2; Issue 3. Error Correcting Codes - Reed Solomon Codes. Priti Shankar. Series Article Volume 2 Issue 3 March ... Author Affiliations. Priti Shankar1. Department of Computer Science and Automation, Indian Institute of Science, Bangalore 560 012, India ...
International Nuclear Information System (INIS)
D’Amore, L; Campagna, R; Murli, A; Galletti, A; Marcellino, L
2012-01-01
The scientific and application-oriented interest in the Laplace transform and its inversion is testified by more than 1000 publications in the last century. Most of the inversion algorithms available in the literature assume that the Laplace transform function is available everywhere. Unfortunately, such an assumption is not fulfilled in the applications of the Laplace transform. Very often, one only has a finite set of data and one wants to recover an estimate of the inverse Laplace function from that. We propose a fitting model of data. More precisely, given a finite set of measurements on the real axis, arising from an unknown Laplace transform function, we construct a dth degree generalized polynomial smoothing spline, where d = 2m − 1, such that internally to the data interval it is a dth degree polynomial complete smoothing spline minimizing a regularization functional, and outside the data interval, it mimics the Laplace transform asymptotic behavior, i.e. it is a rational or an exponential function (the end behavior model), and at the boundaries of the data set it joins with regularity up to order m − 1, with the end behavior model. We analyze in detail the generalized polynomial smoothing spline of degree d = 3. This choice was motivated by the (ill)conditioning of the numerical computation which strongly depends on the degree of the complete spline. We prove existence and uniqueness of this spline. We derive the approximation error and give a priori and computable bounds of it on the whole real axis. In such a way, the generalized polynomial smoothing spline may be used in any real inversion algorithm to compute an approximation of the inverse Laplace function. Experimental results concerning Laplace transform approximation, numerical inversion of the generalized polynomial smoothing spline and comparisons with the exponential smoothing spline conclude the work. (paper)
Directory of Open Access Journals (Sweden)
Xian Peng
2017-01-01
Full Text Available The use of maximum length sequence (m-sequence has been found beneficial for recovering both linear and nonlinear components at rapid stimulation. Since m-sequence is fully characterized by a primitive polynomial of different orders, the selection of polynomial order can be problematic in practice. Usually, the m-sequence is repetitively delivered in a looped fashion. Ensemble averaging is carried out as the first step and followed by the cross-correlation analysis to deconvolve linear/nonlinear responses. According to the classical noise reduction property based on additive noise model, theoretical equations have been derived in measuring noise attenuation ratios (NARs after the averaging and correlation processes in the present study. A computer simulation experiment was conducted to test the derived equations, and a nonlinear deconvolution experiment was also conducted using order 7 and 9 m-sequences to address this issue with real data. Both theoretical and experimental results show that the NAR is essentially independent of the m-sequence order and is decided by the total length of valid data, as well as stimulation rate. The present study offers a guideline for m-sequence selections, which can be used to estimate required recording time and signal-to-noise ratio in designing m-sequence experiments.
International Nuclear Information System (INIS)
Vanhaelewyn, G.; Callens, F.; Gruen, R.
2000-01-01
In order to determine the components which give rise to the EPR spectrum around g = 2 we have applied Maximum Likelihood Common Factor Analysis (MLCFA) on the EPR spectra of enamel sample 1126 which has previously been analysed by continuous wave and pulsed EPR as well as EPR microscopy. MLCFA yielded agreeing results on three sets of X-band spectra and the following components were identified: an orthorhombic component attributed to CO - 2 , an axial component CO 3- 3 , as well as four isotropic components, three of which could be attributed to SO - 2 , a tumbling CO - 2 and a central line of a dimethyl radical. The X-band results were confirmed by analysis of Q-band spectra where three additional isotropic lines were found, however, these three components could not be attributed to known radicals. The orthorhombic component was used to establish dose response curves for the assessment of the past radiation dose, D E . The results appear to be more reliable than those based on conventional peak-to-peak EPR intensity measurements or simple Gaussian deconvolution methods
Digital high-pass filter deconvolution by means of an infinite impulse response filter
Energy Technology Data Exchange (ETDEWEB)
Födisch, P., E-mail: p.foedisch@hzdr.de [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Wohsmann, J. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany); Lange, B. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Schönherr, J. [Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany); Enghardt, W. [OncoRay - National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Fetscherstr. 74, PF 41, 01307 Dresden (Germany); Helmholtz-Zentrum Dresden - Rossendorf, Institute of Radiooncology, Bautzner Landstr. 400, 01328 Dresden (Germany); German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg (Germany); Kaever, P. [Helmholtz-Zentrum Dresden - Rossendorf, Department of Research Technology, Bautzner Landstr. 400, 01328 Dresden (Germany); Dresden University of Applied Sciences, Faculty of Electrical Engineering, Friedrich-List-Platz 1, 01069 Dresden (Germany)
2016-09-11
In the application of semiconductor detectors, the charge-sensitive amplifier is widely used in front-end electronics. The output signal is shaped by a typical exponential decay. Depending on the feedback network, this type of front-end electronics suffers from the ballistic deficit problem, or an increased rate of pulse pile-ups. Moreover, spectroscopy applications require a correction of the pulse-height, while a shortened pulse-width is desirable for high-throughput applications. For both objectives, digital deconvolution of the exponential decay is convenient. With a general method and the signals of our custom charge-sensitive amplifier for cadmium zinc telluride detectors, we show how the transfer function of an amplifier is adapted to an infinite impulse response (IIR) filter. This paper investigates different design methods for an IIR filter in the discrete-time domain and verifies the obtained filter coefficients with respect to the equivalent continuous-time frequency response. Finally, the exponential decay is shaped to a step-like output signal that is exploited by a forward-looking pulse processing.
Directory of Open Access Journals (Sweden)
Ang Cui
Full Text Available Gene expression-based signatures help identify pathways relevant to diseases and treatments, but are challenging to construct when there is a diversity of disease mechanisms and treatments in patients with complex diseases. To overcome this challenge, we present a new application of an in silico gene expression deconvolution method, ISOpure-S1, and apply it to identify a common gene expression signature corresponding to response to treatment in 33 juvenile idiopathic arthritis (JIA patients. Using pre- and post-treatment gene expression profiles only, we found a gene expression signature that significantly correlated with a reduction in the number of joints with active arthritis, a measure of clinical outcome (Spearman rho = 0.44, p = 0.040, Bonferroni correction. This signature may be associated with a decrease in T-cells, monocytes, neutrophils and platelets. The products of most differentially expressed genes include known biomarkers for JIA such as major histocompatibility complexes and interleukins, as well as novel biomarkers including α-defensins. This method is readily applicable to expression datasets of other complex diseases to uncover shared mechanistic patterns in heterogeneous samples.
Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN.
Hao, Jie; Liebeke, Manuel; Astle, William; De Iorio, Maria; Bundy, Jacob G; Ebbels, Timothy M D
2014-01-01
Data processing for 1D NMR spectra is a key bottleneck for metabolomic and other complex-mixture studies, particularly where quantitative data on individual metabolites are required. We present a protocol for automated metabolite deconvolution and quantification from complex NMR spectra by using the Bayesian automated metabolite analyzer for NMR (BATMAN) R package. BATMAN models resonances on the basis of a user-controllable set of templates, each of which specifies the chemical shifts, J-couplings and relative peak intensities for a single metabolite. Peaks are allowed to shift position slightly between spectra, and peak widths are allowed to vary by user-specified amounts. NMR signals not captured by the templates are modeled non-parametrically by using wavelets. The protocol covers setting up user template libraries, optimizing algorithmic input parameters, improving prior information on peak positions, quality control and evaluation of outputs. The outputs include relative concentration estimates for named metabolites together with associated Bayesian uncertainty estimates, as well as the fit of the remainder of the spectrum using wavelets. Graphical diagnostics allow the user to examine the quality of the fit for multiple spectra simultaneously. This approach offers a workflow to analyze large numbers of spectra and is expected to be useful in a wide range of metabolomics studies.
Stovin, V R; Guymer, I; Chappell, M J; Hattersley, J G
2010-01-01
Mixing and dispersion processes affect the timing and concentration of contaminants transported within urban drainage systems. Hence, methods of characterising the mixing effects of specific hydraulic structures are of interest to drainage network modellers. Previous research, focusing on surcharged manholes, utilised the first-order Advection-Dispersion Equation (ADE) and Aggregated Dead Zone (ADZ) models to characterise dispersion. However, although systematic variations in travel time as a function of discharge and surcharge depth have been identified, the first order ADE and ADZ models do not provide particularly good fits to observed manhole data, which means that the derived parameter values are not independent of the upstream temporal concentration profile. An alternative, more robust, approach utilises the system's Cumulative Residence Time Distribution (CRTD), and the solute transport characteristics of a surcharged manhole have been shown to be characterised by just two dimensionless CRTDs, one for pre- and the other for post-threshold surcharge depths. Although CRTDs corresponding to instantaneous upstream injections can easily be generated using Computational Fluid Dynamics (CFD) models, the identification of CRTD characteristics from non-instantaneous and noisy laboratory data sets has been hampered by practical difficulties. This paper shows how a deconvolution approach derived from systems theory may be applied to identify the CRTDs associated with urban drainage structures.
Poletto, Flavio; Schleifer, Andrea; Zgauc, Franco; Meneghini, Fabio; Petronio, Lorenzo
2016-12-01
We present the results of a novel borehole-seismic experiment in which we used different types of onshore-transient-impulsive and non-impulsive-surface sources together with direct ground-force recordings. The ground-force signals were obtained by baseplate load cells located beneath the sources, and by buried soil-stress sensors installed in the very shallow-subsurface together with accelerometers. The aim was to characterize the source's emission by its complex impedance, function of the near-field vibrations and soil stress components, and above all to obtain appropriate deconvolution operators to remove the signature of the sources in the far-field seismic signals. The data analysis shows the differences in the reference measurements utilized to deconvolve the source signature. As downgoing waves, we process the signals of vertical seismic profiles (VSP) recorded in the far-field approximation by an array of permanent geophones cemented at shallow-medium depth outside the casing of an instrumented well. We obtain a significant improvement in the waveform of the radiated seismic-vibrator signals deconvolved by ground force, similar to that of the seismograms generated by the impulsive sources, and demonstrates that the results obtained by different sources present low values in their repeatability norm. The comparison evidences the potentiality of the direct ground-force measurement approach to effectively remove the far-field source signature in VSP onshore data, and to increase the performance of permanent acquisition installations for time-lapse application purposes.
Wapenaar, Kees; van der Neut, Joost; Ruigrok, Elmer; Draganov, Deyan; Hunziker, Jürg; Slob, Evert; Thorbecke, Jan; Snieder, Roel
2011-06-01
Seismic interferometry, also known as Green's function retrieval by crosscorrelation, has a wide range of applications, ranging from surface-wave tomography using ambient noise, to creating virtual sources for improved reflection seismology. Despite its successful applications, the crosscorrelation approach also has its limitations. The main underlying assumptions are that the medium is lossless and that the wavefield is equipartitioned. These assumptions are in practice often violated: the medium of interest is often illuminated from one side only, the sources may be irregularly distributed, and losses may be significant. These limitations may partly be overcome by reformulating seismic interferometry as a multidimensional deconvolution (MDD) process. We present a systematic analysis of seismic interferometry by crosscorrelation and by MDD. We show that for the non-ideal situations mentioned above, the correlation function is proportional to a Green's function with a blurred source. The source blurring is quantified by a so-called interferometric point-spread function which, like the correlation function, can be derived from the observed data (i.e. without the need to know the sources and the medium). The source of the Green's function obtained by the correlation method can be deblurred by deconvolving the correlation function for the point-spread function. This is the essence of seismic interferometry by MDD. We illustrate the crosscorrelation and MDD methods for controlled-source and passive-data applications with numerical examples and discuss the advantages and limitations of both methods.
Broggini, Filippo; Wapenaar, Kees; van der Neut, Joost; Snieder, Roel
2014-01-01
An iterative method is presented that allows one to retrieve the Green's function originating from a virtual source located inside a medium using reflection data measured only at the acquisition surface. In addition to the reflection response, an estimate of the travel times corresponding to the direct arrivals is required. However, no detailed information about the heterogeneities in the medium is needed. The iterative scheme generalizes the Marchenko equation for inverse scattering to the seismic reflection problem. To give insight in the mechanism of the iterative method, its steps for a simple layered medium are analyzed using physical arguments based on the stationary phase method. The retrieved Green's wavefield is shown to correctly contain the multiples due to the inhomogeneities present in the medium. Additionally, a variant of the iterative scheme enables decomposition of the retrieved wavefield into its downgoing and upgoing components. These wavefields then enable creation of a ghost-free image of the medium with either cross correlation or multidimensional deconvolution, presenting an advantage over standard prestack migration.
International Nuclear Information System (INIS)
Jimenez-Ruiz, A.; Carnerero, J. M.; Castillo, P. M.; Prado-Gotor, R.
2017-01-01
Low-generation polyamidoamine (PAMAM) dendrimers are known to adsorb on the surface of gold nanoparticles (AuNPs) causing aggregation and color changes. In this paper, a thorough study of this affinity using absorption spectroscopy, colorimetric, and emission methods has been carried out. Results show that, for citrate-capped gold nanoparticles, interaction with the dendrimer is not only of an electrostatic character but instead occurs, at least in part, through the dendrimer’s uncharged internal amino groups. The possibilities of the CIELab chromaticity system parameters’ evolution have also been explored in order to quantify dendrimer interaction with the red-colored nanoparticles. By measuring and quantifying 17 nm citrate-capped AuNP color changes, which are strongly dependant on their aggregation state, binding free energies are obtained for the first time for these systems. Results are confirmed via an alternate fitting method which makes use of deconvolution parameters from absorbance spectra. Binding free energies obtained through the use of both means are in good agreement with each other.
Enhancing the accuracy of subcutaneous glucose sensors: a real-time deconvolution-based approach.
Guerra, Stefania; Facchinetti, Andrea; Sparacino, Giovanni; Nicolao, Giuseppe De; Cobelli, Claudio
2012-06-01
Minimally invasive continuous glucose monitoring (CGM) sensors can greatly help diabetes management. Most of these sensors consist of a needle electrode, placed in the subcutaneous tissue, which measures an electrical current exploiting the glucose-oxidase principle. This current is then transformed to glucose levels after calibrating the sensor on the basis of one, or more, self-monitoring blood glucose (SMBG) samples. In this study, we design and test a real-time signal-enhancement module that, cascaded to the CGM device, improves the quality of its output by a proper postprocessing of the CGM signal. In fact, CGM sensors measure glucose in the interstitium rather than in the blood compartment. We show that this distortion can be compensated by means of a regularized deconvolution procedure relying on a linear regression model that can be updated whenever a pair of suitably sampled SMBG references is collected. Tests performed both on simulated and real data demonstrate a significant accuracy improvement of the CGM signal. Simulation studies also demonstrate the robustness of the method against departures from nominal conditions, such as temporal misplacement of the SMBG samples and uncertainty in the blood-to-interstitium glucose kinetic model. Thanks to its online capabilities, the proposed signal-enhancement algorithm can be used to improve the performance of CGM-based real-time systems such as the hypo/hyper glycemic alert generators or the artificial pancreas.
INTRAVAL project phase 2. Analysis of STRIPA 3D data by a deconvolution technique
International Nuclear Information System (INIS)
Ilvonen, M.; Hautojaervi, A.; Paatero, P.
1994-09-01
The data analysed in this report were obtained in tracer experiments performed from a specially excavated drift in good granite rock at the level of 360 m below the ground in the Stripa mine. Tracer transport paths from the injection points to the collecting sheets at the tunnel walls were tens of meters long. Data for six tracers that arrived in measurable concentrations were elaborated by different means of data analysis to reveal the transport behaviour of solutes in the rock fractures. Techniques like direct inversion of the data, Fourier analysis, Singular Value Decomposition (SVD) and non-negative least squares fitting (NNLS) were employed. A newly developed code based on a general-purpose approach for solving deconvolution-type or integral equation problems, Extreme Value Estimation (EVE), proved to be a very helpful tool in deconvolving impulse responses from the injection flow rates and break-through curves of tracers and assessing the physical confidence of the results. (23 refs., 33 figs.)
Energy Technology Data Exchange (ETDEWEB)
Jimenez-Ruiz, A., E-mail: ailjimrui@alum.us.es; Carnerero, J. M.; Castillo, P. M.; Prado-Gotor, R., E-mail: pradogotor@us.es [University of Seville, The Department of Physical Chemistry (Spain)
2017-01-15
Low-generation polyamidoamine (PAMAM) dendrimers are known to adsorb on the surface of gold nanoparticles (AuNPs) causing aggregation and color changes. In this paper, a thorough study of this affinity using absorption spectroscopy, colorimetric, and emission methods has been carried out. Results show that, for citrate-capped gold nanoparticles, interaction with the dendrimer is not only of an electrostatic character but instead occurs, at least in part, through the dendrimer’s uncharged internal amino groups. The possibilities of the CIELab chromaticity system parameters’ evolution have also been explored in order to quantify dendrimer interaction with the red-colored nanoparticles. By measuring and quantifying 17 nm citrate-capped AuNP color changes, which are strongly dependant on their aggregation state, binding free energies are obtained for the first time for these systems. Results are confirmed via an alternate fitting method which makes use of deconvolution parameters from absorbance spectra. Binding free energies obtained through the use of both means are in good agreement with each other.
International Nuclear Information System (INIS)
Salas C, P.; Estrada G, R.; Gonzalez M, P.R.; Mendoza A, D.
2003-01-01
In this work, we present a mathematical analysis of the behavior of the thermoluminescent curve (Tl) induced by gamma radiation in samples made of zirconium oxide doped with different amounts of graphite. In accordance with the results gamma radiation induces a Tl curve with two maximum of emission localized in the temperatures at 139 and 250 C, the area under the curve is increasing as a function of the time of exposition to the radiation. The analysis of curve deconvolution, in accordance with the theory which indicates that this behavior must be obey a Boltzmann distribution, we found that each one of them has a different growth velocity as the time of exposition increase. In the same way, we observed that after the irradiation was suspended each one of the maximum decrease with different velocity. The behaviour observed in the samples is very interesting because the zirconium oxide has attracted the interest of many research groups, this material has demonstrated to have many applications in thermoluminescent dosimetry and it can be used in the quantification of radiation. (Author)
Deconvolution analysis of sup(99m)Tc-methylene diphosphonate kinetics in metabolic bone disease
International Nuclear Information System (INIS)
Knop, J.; Kroeger, E.; Stritzke, P.; Schneider, C.; Kruse, H.P.; Hamburg Univ.
1981-01-01
The kinetics of sup(99m)Tc-methylene diphosphonate (MDP) and 47 Ca were studied in three patients with osteoporosis, three patients with hyperparathyroidism, and two patients with osteomalacia. The activities of sup(99m)Tc-MDP were recorded in the lumbar spine, paravertebral soft tissues, and in venous blood samples for 1 h after injection. The results were submitted to deconvolution analysis to determine regional bone accumulation rates. 47 Ca kinetics were analysed by a linear two-compartment model quantitating short-term mineral exchange, exchangeable bone calcium, and calcium accretion. The sup(99m)Tc-MDP accumulation rates were small in osteoporosis, greater in hyperparathyroidism, and greatest in osteomalacia. No correlations were obtained between sup(99m)Tc-MDP bone accumulation rates and the results of 47 Ca kinetics. However, there was a significant relationship between the level of serum alkaline phosphatase and bone accumulation rates (R = 0.71, P 47 Ca kinetics might suggest a preferential binding of sup(99m)Tc-MDP to the organic matrix of the bone, as has been suggested by other authors on the basis of experimental and clinical investigations. (orig.)
Challenge and Error: Critical Events and Attention-Related Errors
Cheyne, James Allan; Carriere, Jonathan S. A.; Solman, Grayden J. F.; Smilek, Daniel
2011-01-01
Attention lapses resulting from reactivity to task challenges and their consequences constitute a pervasive factor affecting everyday performance errors and accidents. A bidirectional model of attention lapses (error [image omitted] attention-lapse: Cheyne, Solman, Carriere, & Smilek, 2009) argues that errors beget errors by generating attention…
Team errors: definition and taxonomy
International Nuclear Information System (INIS)
Sasou, Kunihide; Reason, James
1999-01-01
In error analysis or error management, the focus is usually upon individuals who have made errors. In large complex systems, however, most people work in teams or groups. Considering this working environment, insufficient emphasis has been given to 'team errors'. This paper discusses the definition of team errors and its taxonomy. These notions are also applied to events that have occurred in the nuclear power industry, aviation industry and shipping industry. The paper also discusses the relations between team errors and Performance Shaping Factors (PSFs). As a result, the proposed definition and taxonomy are found to be useful in categorizing team errors. The analysis also reveals that deficiencies in communication, resource/task management, excessive authority gradient, excessive professional courtesy will cause team errors. Handling human errors as team errors provides an opportunity to reduce human errors
Nodular smooth muscle metaplasia in multiple peritoneal endometriosis
Kim, Hyun-Soo; Yoon, Gun; Ha, Sang Yun; Song, Sang Yong
2015-01-01
We report here an unusual presentation of peritoneal endometriosis with smooth muscle metaplasia as multiple protruding masses on the lateral pelvic wall. Smooth muscle metaplasia is a common finding in rectovaginal endometriosis, whereas in peritoneal endometriosis, smooth muscle metaplasia is uncommon and its nodular presentation on the pelvic wall is even rarer. To the best of our knowledge, this is the first case of nodular smooth muscle metaplasia occurring in peritoneal endometriosis. A...
International Nuclear Information System (INIS)
Kirov, A S; Schmidtlein, C R; Piao, J Z
2008-01-01
Correcting positron emission tomography (PET) images for the partial volume effect (PVE) due to the limited resolution of PET has been a long-standing challenge. Various approaches including incorporation of the system response function in the reconstruction have been previously tested. We present a post-reconstruction PVE correction based on iterative deconvolution using a 3D maximum likelihood expectation-maximization (MLEM) algorithm. To achieve convergence we used a one step late (OSL) regularization procedure based on the assumption of local monotonic behavior of the PET signal following Alenius et al. This technique was further modified to selectively control variance depending on the local topology of the PET image. No prior 'anatomic' information is needed in this approach. An estimate of the noise properties of the image is used instead. The procedure was tested for symmetric and isotropic deconvolution functions with Gaussian shape and full width at half-maximum (FWHM) ranging from 6.31 mm to infinity. The method was applied to simulated and experimental scans of the NEMA NU 2 image quality phantom with the GE Discovery LS PET/CT scanner. The phantom contained uniform activity spheres with diameters ranging from 1 cm to 3.7 cm within uniform background. The optimal sphere activity to variance ratio was obtained when the deconvolution function was replaced by a step function few voxels wide. In this case, the deconvolution method converged in ∼3-5 iterations for most points on both the simulated and experimental images. For the 1 cm diameter sphere, the contrast recovery improved from 12% to 36% in the simulated and from 21% to 55% in the experimental data. Recovery coefficients between 80% and 120% were obtained for all larger spheres, except for the 13 mm diameter sphere in the simulated scan (68%). No increase in variance was observed except for a few voxels neighboring strong activity gradients and inside the largest spheres. Testing the method for
Glass, Edmund R; Dozmorov, Mikhail G
2016-10-06
The goal of many human disease-oriented studies is to detect molecular mechanisms different between healthy controls and patients. Yet, commonly used gene expression measurements from blood samples suffer from variability of cell composition. This variability hinders the detection of differentially expressed genes and is often ignored. Combined with cell counts, heterogeneous gene expression may provide deeper insights into the gene expression differences on the cell type-specific level. Published computational methods use linear regression to estimate cell type-specific differential expression, and a global cutoff to judge significance, such as False Discovery Rate (FDR). Yet, they do not consider many artifacts hidden in high-dimensional gene expression data that may negatively affect linear regression. In this paper we quantify the parameter space affecting the performance of linear regression (sensitivity of cell type-specific differential expression detection) on a per-gene basis. We evaluated the effect of sample sizes, cell type-specific proportion variability, and mean squared error on sensitivity of cell type-specific differential expression detection using linear regression. Each parameter affected variability of cell type-specific expression estimates and, subsequently, the sensitivity of differential expression detection. We provide the R package, LRCDE, which performs linear regression-based cell type-specific differential expression (deconvolution) detection on a gene-by-gene basis. Accounting for variability around cell type-specific gene expression estimates, it computes per-gene t-statistics of differential detection, p-values, t-statistic-based sensitivity, group-specific mean squared error, and several gene-specific diagnostic metrics. The sensitivity of linear regression-based cell type-specific differential expression detection differed for each gene as a function of mean squared error, per group sample sizes, and variability of the proportions
Radial Basis Function Based Quadrature over Smooth Surfaces
2016-03-24
Radial Basis Functions φ(r) Piecewise Smooth (Conditionally Positive Definite) MN Monomial |r|2m+1 TPS thin plate spline |r|2mln|r| Infinitely Smooth...smooth surfaces using polynomial interpolants, while [27] couples Thin - Plate Spline interpolation (see table 1) with Green’s integral formula [29
Smoothing-Norm Preconditioning for Regularizing Minimum-Residual Methods
DEFF Research Database (Denmark)
Hansen, Per Christian; Jensen, Toke Koldborg
2006-01-01
take into account a smoothing norm for the solution. This technique is well established for CGLS, but it does not immediately carry over to minimum-residual methods when the smoothing norm is a seminorm or a Sobolev norm. We develop a new technique which works for any smoothing norm of the form $\\|L...
Neurophysiology and Neuroanatomy of Smooth Pursuit in Humans
Lencer, Rebekka; Trillenberg, Peter
2008-01-01
Smooth pursuit eye movements enable us to focus our eyes on moving objects by utilizing well-established mechanisms of visual motion processing, sensorimotor transformation and cognition. Novel smooth pursuit tasks and quantitative measurement techniques can help unravel the different smooth pursuit components and complex neural systems involved…
Technical Note: Interference errors in infrared remote sounding of the atmosphere
Directory of Open Access Journals (Sweden)
R. Sussmann
2007-07-01
Full Text Available Classical error analysis in remote sounding distinguishes between four classes: "smoothing errors," "model parameter errors," "forward model errors," and "retrieval noise errors". For infrared sounding "interference errors", which, in general, cannot be described by these four terms, can be significant. Interference errors originate from spectral residuals due to "interfering species" whose spectral features overlap with the signatures of the target species. A general method for quantification of interference errors is presented, which covers all possible algorithmic implementations, i.e., fine-grid retrievals of the interfering species or coarse-grid retrievals, and cases where the interfering species are not retrieved. In classical retrieval setups interference errors can exceed smoothing errors and can vary by orders of magnitude due to state dependency. An optimum strategy is suggested which practically eliminates interference errors by systematically minimizing the regularization strength applied to joint profile retrieval of the interfering species. This leads to an interfering-species selective deweighting of the retrieval. Details of microwindow selection are no longer critical for this optimum retrieval and widened microwindows even lead to reduced overall (smoothing and interference errors. Since computational power will increase, more and more operational algorithms will be able to utilize this optimum strategy in the future. The findings of this paper can be applied to soundings of all infrared-active atmospheric species, which include more than two dozen different gases relevant to climate and ozone. This holds for all kinds of infrared remote sounding systems, i.e., retrievals from ground-based, balloon-borne, airborne, or satellite spectroradiometers.
Rieger, Martina; Martinez, Fanny; Wenke, Dorit
2011-01-01
Using a typing task we investigated whether insufficient imagination of errors and error corrections is related to duration differences between execution and imagination. In Experiment 1 spontaneous error imagination was investigated, whereas in Experiment 2 participants were specifically instructed to imagine errors. Further, in Experiment 2 we…
Correction of refractive errors
Directory of Open Access Journals (Sweden)
Vladimir Pfeifer
2005-10-01
Full Text Available Background: Spectacles and contact lenses are the most frequently used, the safest and the cheapest way to correct refractive errors. The development of keratorefractive surgery has brought new opportunities for correction of refractive errors in patients who have the need to be less dependent of spectacles or contact lenses. Until recently, RK was the most commonly performed refractive procedure for nearsighted patients.Conclusions: The introduction of excimer laser in refractive surgery has given the new opportunities of remodelling the cornea. The laser energy can be delivered on the stromal surface like in PRK or deeper on the corneal stroma by means of lamellar surgery. In LASIK flap is created with microkeratome in LASEK with ethanol and in epi-LASIK the ultra thin flap is created mechanically.
1989-01-01
001 is an integrated tool suited for automatically developing ultra reliable models, simulations and software systems. Developed and marketed by Hamilton Technologies, Inc. (HTI), it has been applied in engineering, manufacturing, banking and software tools development. The software provides the ability to simplify the complex. A system developed with 001 can be a prototype or fully developed with production quality code. It is free of interface errors, consistent, logically complete and has no data or control flow errors. Systems can be designed, developed and maintained with maximum productivity. Margaret Hamilton, President of Hamilton Technologies, also directed the research and development of USE.IT, an earlier product which was the first computer aided software engineering product in the industry to concentrate on automatically supporting the development of an ultrareliable system throughout its life cycle. Both products originated in NASA technology developed under a Johnson Space Center contract.
Smooth and non-smooth travelling waves in a nonlinearly dispersive Boussinesq equation
International Nuclear Information System (INIS)
Shen Jianwei; Xu Wei; Lei Youming
2005-01-01
The dynamical behavior and special exact solutions of nonlinear dispersive Boussinesq equation (B(m,n) equation), u tt -u xx -a(u n ) xx +b(u m ) xxxx =0, is studied by using bifurcation theory of dynamical system. As a result, all possible phase portraits in the parametric space for the travelling wave system, solitary wave, kink and anti-kink wave solutions and uncountably infinite many smooth and non-smooth periodic wave solutions are obtained. It can be shown that the existence of singular straight line in the travelling wave system is the reason why smooth waves converge to cusp waves, finally. When parameter are varied, under different parametric conditions, various sufficient conditions guarantee the existence of the above solutions are given
Minimum Tracking Error Volatility
Luca RICCETTI
2010-01-01
Investors assign part of their funds to asset managers that are given the task of beating a benchmark. The risk management department usually imposes a maximum value of the tracking error volatility (TEV) in order to keep the risk of the portfolio near to that of the selected benchmark. However, risk management does not establish a rule on TEV which enables us to understand whether the asset manager is really active or not and, in practice, asset managers sometimes follow passively the corres...
Hinds, Erold W. (Principal Investigator)
1996-01-01
This report describes the progress made towards the completion of a specific task on error-correcting coding. The proposed research consisted of investigating the use of modulation block codes as the inner code of a concatenated coding system in order to improve the overall space link communications performance. The study proposed to identify and analyze candidate codes that will complement the performance of the overall coding system which uses the interleaved RS (255,223) code as the outer code.
Satellite Photometric Error Determination
2015-10-18
Satellite Photometric Error Determination Tamara E. Payne, Philip J. Castro, Stephen A. Gregory Applied Optimization 714 East Monument Ave, Suite...advocate the adoption of new techniques based on in-frame photometric calibrations enabled by newly available all-sky star catalogs that contain highly...filter systems will likely be supplanted by the Sloan based filter systems. The Johnson photometric system is a set of filters in the optical
International Nuclear Information System (INIS)
Dixon, M.; Wright, A.C.; Hutchinson, P.
1977-01-01
The application of fast Fourier transformation techniques to the analysis of experimental X-ray and neutron diffraction patterns from amorphous materials is discussed and compared with conventional techniques using Filon's quadrature. The fast Fourier transform package described also includes cubic spline smoothing and has been extensively tested, using model data to which statistical errors have been added by means of a pseudo-random number generator with Gaussian shaper. Neither cubic spline nor hand smoothing has much effect on the resulting transform since the noise removed is of too high a frequency. (Auth.)
Video Error Correction Using Steganography
Robie, David L.; Mersereau, Russell M.
2002-12-01
The transmission of any data is always subject to corruption due to errors, but video transmission, because of its real time nature must deal with these errors without retransmission of the corrupted data. The error can be handled using forward error correction in the encoder or error concealment techniques in the decoder. This MPEG-2 compliant codec uses data hiding to transmit error correction information and several error concealment techniques in the decoder. The decoder resynchronizes more quickly with fewer errors than traditional resynchronization techniques. It also allows for perfect recovery of differentially encoded DCT-DC components and motion vectors. This provides for a much higher quality picture in an error-prone environment while creating an almost imperceptible degradation of the picture in an error-free environment.
Video Error Correction Using Steganography
Directory of Open Access Journals (Sweden)
Robie David L
2002-01-01
Full Text Available The transmission of any data is always subject to corruption due to errors, but video transmission, because of its real time nature must deal with these errors without retransmission of the corrupted data. The error can be handled using forward error correction in the encoder or error concealment techniques in the decoder. This MPEG-2 compliant codec uses data hiding to transmit error correction information and several error concealment techniques in the decoder. The decoder resynchronizes more quickly with fewer errors than traditional resynchronization techniques. It also allows for perfect recovery of differentially encoded DCT-DC components and motion vectors. This provides for a much higher quality picture in an error-prone environment while creating an almost imperceptible degradation of the picture in an error-free environment.
ASIC PROTEINS REGULATE SMOOTH MUSCLE CELL MIGRATION
Grifoni, Samira C.; Jernigan, Nikki L.; Hamilton, Gina; Drummond, Heather A.
2007-01-01
The purpose of the present study was to investigate Acid Sensing Ion Channel (ASIC) protein expression and importance in cellular migration. We recently demonstrated Epithelial Na+ Channel (ENaC) proteins are required for vascular smooth muscle cell (VSMC) migration, however the role of the closely related ASIC proteins has not been addressed. We used RT-PCR and immunolabeling to determine expression of ASIC1, ASIC2, ASIC3 and ASIC4 in A10 cells. We used small interference RNA to silence indi...
A smooth exit from eternal inflation?
Hawking, S. W.; Hertog, Thomas
2018-04-01
The usual theory of inflation breaks down in eternal inflation. We derive a dual description of eternal inflation in terms of a deformed Euclidean CFT located at the threshold of eternal inflation. The partition function gives the amplitude of different geometries of the threshold surface in the no-boundary state. Its local and global behavior in dual toy models shows that the amplitude is low for surfaces which are not nearly conformal to the round three-sphere and essentially zero for surfaces with negative curvature. Based on this we conjecture that the exit from eternal inflation does not produce an infinite fractal-like multiverse, but is finite and reasonably smooth.
On spaces of functions of smoothness zero
International Nuclear Information System (INIS)
Besov, Oleg V
2012-01-01
The paper is concerned with the new spaces B-bar p,q 0 of functions of smoothness zero defined on the n-dimensional Euclidean space R n or on a subdomain G of R n . These spaces are compared with the spaces B p,q 0 (R n ) and bmo(R n ). The embedding theorems for Sobolev spaces are refined in terms of the space B-bar p,q 0 with the limiting exponent. Bibliography: 8 titles.
Smooth Nanowire/Polymer Composite Transparent Electrodes
Gaynor, Whitney; Burkhard, George F.; McGehee, Michael D.; Peumans, Peter
2011-01-01
Smooth composite transparent electrodes are fabricated via lamination of silver nanowires into the polymer poly-(4,3-ethylene dioxythiophene): poly(styrene-sulfonate) (PEDOT:PSS). The surface roughness is dramatically reduced compared to bare nanowires. High-efficiency P3HT:PCBM organic photovoltaic cells can be fabricated using these composites, reproducing the performance of cells on indium tin oxide (ITO) on glass and improving the performance of cells on ITO on plastic. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Workshop on advances in smooth particle hydrodynamics
Energy Technology Data Exchange (ETDEWEB)
Wingate, C.A.; Miller, W.A.
1993-12-31
This proceedings contains viewgraphs presented at the 1993 workshop held at Los Alamos National Laboratory. Discussed topics include: negative stress, reactive flow calculations, interface problems, boundaries and interfaces, energy conservation in viscous flows, linked penetration calculations, stability and consistency of the SPH method, instabilities, wall heating and conservative smoothing, tensors, tidal disruption of stars, breaking the 10,000,000 particle limit, modelling relativistic collapse, SPH without H, relativistic KSPH avoidance of velocity based kernels, tidal compression and disruption of stars near a supermassive rotation black hole, and finally relativistic SPH viscosity and energy.
Smooth Nanowire/Polymer Composite Transparent Electrodes
Gaynor, Whitney
2011-04-29
Smooth composite transparent electrodes are fabricated via lamination of silver nanowires into the polymer poly-(4,3-ethylene dioxythiophene): poly(styrene-sulfonate) (PEDOT:PSS). The surface roughness is dramatically reduced compared to bare nanowires. High-efficiency P3HT:PCBM organic photovoltaic cells can be fabricated using these composites, reproducing the performance of cells on indium tin oxide (ITO) on glass and improving the performance of cells on ITO on plastic. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Quantum key distribution with finite resources: Smooth Min entropy vs. Smooth Renyi entropy
Energy Technology Data Exchange (ETDEWEB)
Mertz, Markus; Abruzzo, Silvestre; Bratzik, Sylvia; Kampermann, Hermann; Bruss, Dagmar [Institut fuer Theoretische Physik III, Duesseldorf (Germany)
2010-07-01
We consider different entropy measures that play an important role in the analysis of the security of QKD with finite resources. The smooth min entropy leads to an optimal bound for the length of a secure key. Another bound on the secure key length was derived by using Renyi entropies. Unfortunately, it is very hard or even impossible to calculate these entropies for realistic QKD scenarios. To estimate the security rate it becomes important to find computable bounds on these entropies. Here, we compare a lower bound for the smooth min entropy with a bound using Renyi entropies. We compare these entropies for the six-state protocol with symmetric attacks.
Error-related brain activity and error awareness in an error classification paradigm.
Di Gregorio, Francesco; Steinhauser, Marco; Maier, Martin E
2016-10-01
Error-related brain activity has been linked to error detection enabling adaptive behavioral adjustments. However, it is still unclear which role error awareness plays in this process. Here, we show that the error-related negativity (Ne/ERN), an event-related potential reflecting early error monitoring, is dissociable from the degree of error awareness. Participants responded to a target while ignoring two different incongruent distractors. After responding, they indicated whether they had committed an error, and if so, whether they had responded to one or to the other distractor. This error classification paradigm allowed distinguishing partially aware errors, (i.e., errors that were noticed but misclassified) and fully aware errors (i.e., errors that were correctly classified). The Ne/ERN was larger for partially aware errors than for fully aware errors. Whereas this speaks against the idea that the Ne/ERN foreshadows the degree of error awareness, it confirms the prediction of a computational model, which relates the Ne/ERN to post-response conflict. This model predicts that stronger distractor processing - a prerequisite of error classification in our paradigm - leads to lower post-response conflict and thus a smaller Ne/ERN. This implies that the relationship between Ne/ERN and error awareness depends on how error awareness is related to response conflict in a specific task. Our results further indicate that the Ne/ERN but not the degree of error awareness determines adaptive performance adjustments. Taken together, we conclude that the Ne/ERN is dissociable from error awareness and foreshadows adaptive performance adjustments. Our results suggest that the relationship between the Ne/ERN and error awareness is correlative and mediated by response conflict. Copyright © 2016 Elsevier Inc. All rights reserved.
Smoothed Bootstrap und seine Anwendung in parametrischen Testverfahren
Directory of Open Access Journals (Sweden)
Handschuh, Dmitri
2015-03-01
Full Text Available In empirical research, the distribution of observations is usually unknown. This creates a problem if parametric methods are to be employed. The functionality of parametric methods relies on strong parametric assumptions. If these are violated the result of using classical parametric methods is questionable. Therefore, modifications of the parametric methods are required, if the appropriateness of their assumptions is in doubt. In this article, a modification of the smoothed bootstrap is presented (using the linear interpolation to approximate the distribution law suggested by the data. The application of this modification to statistical parametric methods allows taking into account deviations of the observed data distributions from the classical distribution assumptions without changing to other hypotheses, which often is implicit in using nonparametric methods. The approach is based on Monte Carlo method and is presented using one-way ANOVA as an example. The original and the modified statistical methods lead to identical outcomes when the assumptions of the original method are satisfied. For strong violations of the distributional assumptions, the modified version of the method is generally preferable. All procedures have been implemented in SAS. Test characteristics (type 1 error, the operating characteristic curve of the modified ANOVA are calculated.
Isotropic Growth of Graphene toward Smoothing Stitching.
Zeng, Mengqi; Tan, Lifang; Wang, Lingxiang; Mendes, Rafael G; Qin, Zhihui; Huang, Yaxin; Zhang, Tao; Fang, Liwen; Zhang, Yanfeng; Yue, Shuanglin; Rümmeli, Mark H; Peng, Lianmao; Liu, Zhongfan; Chen, Shengli; Fu, Lei
2016-07-26
The quality of graphene grown via chemical vapor deposition still has very great disparity with its theoretical property due to the inevitable formation of grain boundaries. The design of single-crystal substrate with an anisotropic twofold symmetry for the unidirectional alignment of graphene seeds would be a promising way for eliminating the grain boundaries at the wafer scale. However, such a delicate process will be easily terminated by the obstruction of defects or impurities. Here we investigated the isotropic growth behavior of graphene single crystals via melting the growth substrate to obtain an amorphous isotropic surface, which will not offer any specific grain orientation induction or preponderant growth rate toward a certain direction in the graphene growth process. The as-obtained graphene grains are isotropically round with mixed edges that exhibit high activity. The orientation of adjacent grains can be easily self-adjusted to smoothly match each other over a liquid catalyst with facile atom delocalization due to the low rotation steric hindrance of the isotropic grains, thus achieving the smoothing stitching of the adjacent graphene. Therefore, the adverse effects of grain boundaries will be eliminated and the excellent transport performance of graphene will be more guaranteed. What is more, such an isotropic growth mode can be extended to other types of layered nanomaterials such as hexagonal boron nitride and transition metal chalcogenides for obtaining large-size intrinsic film with low defect.
Smooth Tubercle Bacilli: Neglected Opportunistic Tropical Pathogens
Directory of Open Access Journals (Sweden)
Djaltou eAboubaker
2016-01-01
Full Text Available Smooth tubercle bacilli (STB including ‘‘Mycobacterium canettii’’ are members of the Mycobacterium tuberculosis complex (MTBC which cause non-contagious tuberculosis in human. This group comprises less than one hundred isolates characterized by smooth colonies and cordless organisms. Most STB isolates have been obtained from patients exposed to the Republic of Djibouti but seven isolates, including the three seminal ones obtained by Georges Canetti between 1968 and 1970, were recovered from patients in France, Madagascar, Sub-Sahara East Africa and French Polynesia. STB form a genetically heterogeneous group of MTBC organisms with large 4.48 ± 0.05 Mb genomes which may link Mycobacterium kansasii to MTBC organisms. Lack of inter-human transmission suggested a yet unknown environmental reservoir. Clinical data indicate a respiratory tract route of contamination and the digestive tract as an alternative route of contamination. Further epidemiological and clinical studies are warranted to elucidate areas of uncertainty regarding these unusual mycobacteria and the tuberculosis they cause.
Snap evaporation of droplets on smooth topographies.
Wells, Gary G; Ruiz-Gutiérrez, Élfego; Le Lirzin, Youen; Nourry, Anthony; Orme, Bethany V; Pradas, Marc; Ledesma-Aguilar, Rodrigo
2018-04-11
Droplet evaporation on solid surfaces is important in many applications including printing, micro-patterning and cooling. While seemingly simple, the configuration of evaporating droplets on solids is difficult to predict and control. This is because evaporation typically proceeds as a "stick-slip" sequence-a combination of pinning and de-pinning events dominated by static friction or "pinning", caused by microscopic surface roughness. Here we show how smooth, pinning-free, solid surfaces of non-planar topography promote a different process called snap evaporation. During snap evaporation a droplet follows a reproducible sequence of configurations, consisting of a quasi-static phase-change controlled by mass diffusion interrupted by out-of-equilibrium snaps. Snaps are triggered by bifurcations of the equilibrium droplet shape mediated by the underlying non-planar solid. Because the evolution of droplets during snap evaporation is controlled by a smooth topography, and not by surface roughness, our ideas can inspire programmable surfaces that manage liquids in heat- and mass-transfer applications.
Directory of Open Access Journals (Sweden)
Roerdink Jos BTM
2008-04-01
Full Text Available Abstract Background We present a simple, data-driven method to extract haemodynamic response functions (HRF from functional magnetic resonance imaging (fMRI time series, based on the Fourier-wavelet regularised deconvolution (ForWaRD technique. HRF data are required for many fMRI applications, such as defining region-specific HRFs, effciently representing a general HRF, or comparing subject-specific HRFs. Results ForWaRD is applied to fMRI time signals, after removing low-frequency trends by a wavelet-based method, and the output of ForWaRD is a time series of volumes, containing the HRF in each voxel. Compared to more complex methods, this extraction algorithm requires few assumptions (separability of signal and noise in the frequency and wavelet domains and the general linear model and it is fast (HRF extraction from a single fMRI data set takes about the same time as spatial resampling. The extraction method is tested on simulated event-related activation signals, contaminated with noise from a time series of real MRI images. An application for HRF data is demonstrated in a simple event-related experiment: data are extracted from a region with significant effects of interest in a first time series. A continuous-time HRF is obtained by fitting a nonlinear function to the discrete HRF coeffcients, and is then used to analyse a later time series. Conclusion With the parameters used in this paper, the extraction method presented here is very robust to changes in signal properties. Comparison of analyses with fitted HRFs and with a canonical HRF shows that a subject-specific, regional HRF significantly improves detection power. Sensitivity and specificity increase not only in the region from which the HRFs are extracted, but also in other regions of interest.
Directory of Open Access Journals (Sweden)
J M Portegies
Full Text Available We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI data. Both methods are based on the same PDE framework, defined in the coupled space of positions and orientations, associated with a stochastic process describing the enhancement of elongated structures while preserving crossing structures. In the first method we use the enhancement PDE for contextual regularization of a fiber orientation distribution (FOD that is obtained on individual voxels from high angular resolution diffusion imaging (HARDI data via constrained spherical deconvolution (CSD. Thereby we improve the FOD as input for subsequent tractography. Secondly, we introduce the fiber to bundle coherence (FBC, a measure for quantification of fiber alignment. The FBC is computed from a tractography result using the same PDE framework and provides a criterion for removing the spurious fibers. We validate the proposed combination of CSD and enhancement on phantom data and on human data, acquired with different scanning protocols. On the phantom data we find that PDE enhancements improve both local metrics and global metrics of tractography results, compared to CSD without enhancements. On the human data we show that the enhancements allow for a better reconstruction of crossing fiber bundles and they reduce the variability of the tractography output with respect to the acquisition parameters. Finally, we show that both the enhancement of the FODs and the use of the FBC measure on the tractography improve the stability with respect to different stochastic realizations of probabilistic tractography. This is shown in a clinical application: the reconstruction of the optic radiation for epilepsy surgery planning.
Barcaru, A; Mol, H G J; Tienstra, M; Vivó-Truyols, G
2017-08-29
A novel probabilistic Bayesian strategy is proposed to resolve highly coeluting peaks in high-resolution GC-MS (Orbitrap) data. Opposed to a deterministic approach, we propose to solve the problem probabilistically, using a complete pipeline. First, the retention time(s) for a (probabilistic) number of compounds for each mass channel are estimated. The statistical dependency between m/z channels was implied by including penalties in the model objective function. Second, Bayesian Information Criterion (BIC) is used as Occam's razor for the probabilistic assessment of the number of components. Third, a probabilistic set of resolved spectra, and their associated retention times are estimated. Finally, a probabilistic library search is proposed, computing the spectral match with a high resolution library. More specifically, a correlative measure was used that included the uncertainties in the least square fitting, as well as the probability for different proposals for the number of compounds in the mixture. The method was tested on simulated high resolution data, as well as on a set of pesticides injected in a GC-Orbitrap with high coelution. The proposed pipeline was able to detect accurately the retention times and the spectra of the peaks. For our case, with extremely high coelution situation, 5 out of the 7 existing compounds under the selected region of interest, were correctly assessed. Finally, the comparison with the classical methods of deconvolution (i.e., MCR and AMDIS) indicates a better performance of the proposed algorithm in terms of the number of correctly resolved compounds. Copyright © 2017 Elsevier B.V. All rights reserved.
Lu, Jonathan; Trnka, Michael J; Roh, Soung-Hun; Robinson, Philip J J; Shiau, Carrie; Fujimori, Danica Galonic; Chiu, Wah; Burlingame, Alma L; Guan, Shenheng
2015-12-01
Native electrospray-ionization mass spectrometry (native MS) measures biomolecules under conditions that preserve most aspects of protein tertiary and quaternary structure, enabling direct characterization of large intact protein assemblies. However, native spectra derived from these assemblies are often partially obscured by low signal-to-noise as well as broad peak shapes because of residual solvation and adduction after the electrospray process. The wide peak widths together with the fact that sequential charge state series from highly charged ions are closely spaced means that native spectra containing multiple species often suffer from high degrees of peak overlap or else contain highly interleaved charge envelopes. This situation presents a challenge for peak detection, correct charge state and charge envelope assignment, and ultimately extraction of the relevant underlying mass values of the noncovalent assemblages being investigated. In this report, we describe a comprehensive algorithm developed for addressing peak detection, peak overlap, and charge state assignment in native mass spectra, called PeakSeeker. Overlapped peaks are detected by examination of the second derivative of the raw mass spectrum. Charge state distributions of the molecular species are determined by fitting linear combinations of charge envelopes to the overall experimental mass spectrum. This software is capable of deconvoluting heterogeneous, complex, and noisy native mass spectra of large protein assemblies as demonstrated by analysis of (1) synthetic mononucleosomes containing severely overlapping peaks, (2) an RNA polymerase II/α-amanitin complex with many closely interleaved ion signals, and (3) human TriC complex containing high levels of background noise. Graphical Abstract ᅟ.
Al-Jumaily, Ahmed; Chen, Leizhi
2012-10-07
This paper presents a novel approach to estimate stiffness changes in airway smooth muscles due to external oscillation. Artificial neural networks are used to model the stiffness changes due to cyclic stretches of the smooth muscles. The nonlinear relationship between stiffness ratios and oscillation frequencies is modeled by a feed-forward neural network (FNN) model. The structure of the FNN is selected through the training and validation using literature data from 11 experiments with different muscle lengths, muscle masses, oscillation frequencies and amplitudes. Data pre-processing methods are used to improve the robustness of the neural network model to match the non-linearity. The validation results show that the FNN model can predict the stiffness ratio changes with a mean square error of 0.0042. Copyright © 2012 Elsevier Ltd. All rights reserved.
On Shear Stress Distributions for Flow in Smooth or Partially Rough Annuli
Energy Technology Data Exchange (ETDEWEB)
Kjellstroem, B; Hedberg, S
1966-08-15
It is commonly assumed that for turbulent flow in annuli the radii of zero shear and maximum velocity are coincident. By inspection of the differential equations for such flow and by an integral analysis it is shown that this is not necessarily true. To check whether important differences could occur, experiments were made in which velocity and shear stress distributions were measured in one smooth and two partially rough annuli. The results show no difference in the radii for the smooth annulus, but for the partially rough annuli there was a small but significant difference. This difference explains the breakdown of Hall's transformation theory reported by other investigators. The error introduced by use of Hall's theory is however small, of the order of 10 % or less.
On Shear Stress Distributions for Flow in Smooth or Partially Rough Annuli
International Nuclear Information System (INIS)
Kjellstroem, B.; Hedberg, S.
1966-08-01
It is commonly assumed that for turbulent flow in annuli the radii of zero shear and maximum velocity are coincident. By inspection of the differential equations for such flow and by an integral analysis it is shown that this is not necessarily true. To check whether important differences could occur, experiments were made in which velocity and shear stress distributions were measured in one smooth and two partially rough annuli. The results show no difference in the radii for the smooth annulus, but for the partially rough annuli there was a small but significant difference. This difference explains the breakdown of Hall's transformation theory reported by other investigators. The error introduced by use of Hall's theory is however small, of the order of 10 % or less
Diagnostic errors in pediatric radiology
International Nuclear Information System (INIS)
Taylor, George A.; Voss, Stephan D.; Melvin, Patrice R.; Graham, Dionne A.
2011-01-01
Little information is known about the frequency, types and causes of diagnostic errors in imaging children. Our goals were to describe the patterns and potential etiologies of diagnostic error in our subspecialty. We reviewed 265 cases with clinically significant diagnostic errors identified during a 10-year period. Errors were defined as a diagnosis that was delayed, wrong or missed; they were classified as perceptual, cognitive, system-related or unavoidable; and they were evaluated by imaging modality and level of training of the physician involved. We identified 484 specific errors in the 265 cases reviewed (mean:1.8 errors/case). Most discrepancies involved staff (45.5%). Two hundred fifty-eight individual cognitive errors were identified in 151 cases (mean = 1.7 errors/case). Of these, 83 cases (55%) had additional perceptual or system-related errors. One hundred sixty-five perceptual errors were identified in 165 cases. Of these, 68 cases (41%) also had cognitive or system-related errors. Fifty-four system-related errors were identified in 46 cases (mean = 1.2 errors/case) of which all were multi-factorial. Seven cases were unavoidable. Our study defines a taxonomy of diagnostic errors in a large academic pediatric radiology practice and suggests that most are multi-factorial in etiology. Further study is needed to define effective strategies for improvement. (orig.)
Bayesian multi-scale smoothing of photon-limited images with applications to astronomy and medicine
White, John
Multi-scale models for smoothing Poisson signals or images have gained much attention over the past decade. A new Bayesian model is developed using the concept of the Chinese restaurant process to find structures in two-dimensional images when performing image reconstruction or smoothing. This new model performs very well when compared to other leading methodologies for the same problem. It is developed and evaluated theoretically and empirically throughout Chapter 2. The newly developed Bayesian model is extended to three-dimensional images in Chapter 3. The third dimension has numerous different applications, such as different energy spectra, another spatial index, or possibly a temporal dimension. Empirically, this method shows promise in reducing error with the use of simulation studies. A further development removes background noise in the image. This removal can further reduce the error and is done using a modeling adjustment and post-processing techniques. These details are given in Chapter 4. Applications to real world problems are given throughout. Photon-based images are common in astronomical imaging due to the collection of different types of energy such as X-Rays. Applications to real astronomical images are given, and these consist of X-ray images from the Chandra X-ray observatory satellite. Diagnostic medicine uses many types of imaging such as magnetic resonance imaging and computed tomography that can also benefit from smoothing techniques such as the one developed here. Reducing the amount of radiation a patient takes will make images more noisy, but this can be mitigated through the use of image smoothing techniques. Both types of images represent the potential real world use for these methods.
Directory of Open Access Journals (Sweden)
Rajeev D S Raizada
Full Text Available Spatial smoothness is helpful when averaging fMRI signals across multiple subjects, as it allows different subjects' corresponding brain areas to be pooled together even if they are slightly misaligned. However, smoothing is usually not applied when performing multivoxel pattern-based analyses (MVPA, as it runs the risk of blurring away the information that fine-grained spatial patterns contain. It would therefore be desirable, if possible, to carry out pattern-based analyses which take unsmoothed data as their input but which produce smooth images as output. We show here that the Gaussian Naive Bayes (GNB classifier does precisely this, when it is used in "searchlight" pattern-based analyses. We explain why this occurs, and illustrate the effect in real fMRI data. Moreover, we show that analyses using GNBs produce results at the multi-subject level which are statistically robust, neurally plausible, and which replicate across two independent data sets. By contrast, SVM classifiers applied to the same data do not generate a replication, even if the SVM-derived searchlight maps have smoothing applied to them. An additional advantage of GNB classifiers for searchlight analyses is that they are orders of magnitude faster to compute than more complex alternatives such as SVMs. Collectively, these results suggest that Gaussian Naive Bayes classifiers may be a highly non-naive choice for multi-subject pattern-based fMRI studies.
Minimum Error Entropy Classification
Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A
2013-01-01
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
International Nuclear Information System (INIS)
RAVELONJATO, R.H.M.
2010-01-01
The aim of this work is to develop a method for gamma ray spectrum deconvolution from NaI(Tl) detector. Deconvolution programs edited with Matlab 7.6 using Nelder-Mead method were developed to determine multiplet shape parameters. The simulation parameters were: centroid distance/FWHM ratio, Signal/Continuum ratio and counting rate. The test using synthetic spectrum was built with 3σ uncertainty. The tests gave suitable results for centroid distance/FWHM ratio≥2, Signal/Continuum ratio ≥2 and counting level 100 counts. The technique was applied to measure the activity of soils and rocks samples from the Anosy region. The rock activity varies from (140±8) Bq.kg -1 to (190±17)Bq.kg -1 for potassium-40; from (343±7)Bq.Kg -1 to (881±6)Bq.kg -1 for thorium-213 and from (100±3)Bq.kg -1 to (164 ±4) Bq.kg -1 for uranium-238. The soil activity varies from (148±1) Bq.kg -1 to (652±31)Bq.kg -1 for potassium-40; from (1100±11)Bq.kg -1 to (5700 ± 40)Bq.kg -1 for thorium-232 and from (190 ±2) Bq.kg -1 to (779 ±15) Bq -1 for uranium -238. Among 11 samples, the activity value discrepancies compared to high resolution HPGe detector varies from 0.62% to 42.86%. The fitting residuals are between -20% and +20%. The Figure of Merit values are around 5%. These results show that the method developed is reliable for such activity range and the convergence is good. So, NaI(Tl) detector combined with deconvolution method developed may replace HPGe detector within an acceptable limit, if the identification of each nuclides in the radioactive series is not required [fr
FEM for time-fractional diffusion equations, novel optimal error analyses
Mustapha, Kassem
2016-01-01
A semidiscrete Galerkin finite element method applied to time-fractional diffusion equations with time-space dependent diffusivity on bounded convex spatial domains will be studied. The main focus is on achieving optimal error results with respect to both the convergence order of the approximate solution and the regularity of the initial data. By using novel energy arguments, for each fixed time $t$, optimal error bounds in the spatial $L^2$- and $H^1$-norms are derived for both cases: smooth...
Energy Technology Data Exchange (ETDEWEB)
Mandlik, Nandkumar, E-mail: ntmandlik@gmail.com [Department of Physics, University of Pune, Ganeshkhind, Pune -411007, India and Department of Physics, Fergusson College, Pune- 411004 (India); Patil, B. J.; Bhoraskar, V. N.; Dhole, S. D. [Department of Physics, University of Pune, Ganeshkhind, Pune -411007 (India); Sahare, P. D. [Department of Physics and Astrophysics, University of Delhi, Delhi- 110007 (India)
2014-04-24
Nanorods of CaSO{sub 4}: Dy having diameter 20 nm and length 200 nm have been synthesized by the chemical coprecipitation method. These samples were irradiated with gamma radiation for the dose varying from 0.1 Gy to 50 kGy and their TL characteristics have been studied. TL dose response shows a linear behavior up to 5 kGy and further saturates with increase in the dose. A Computerized Glow Curve Deconvolution (CGCD) program was used for the analysis of TL glow curves. Trapping parameters for various peaks have been calculated by using CGCD program.
DECONVOLUTION OF IMAGES FROM BLAST 2005: INSIGHT INTO THE K3-50 AND IC 5146 STAR-FORMING REGIONS
International Nuclear Information System (INIS)
Roy, Arabindo; Netterfield, Calvin B.; Ade, Peter A. R.; Griffin, Matthew; Hargrave, Peter C.; Mauskopf, Philip; Bock, James J.; Brunt, Christopher M.; Chapin, Edward L.; Gibb, Andrew G.; Halpern, Mark; Marsden, Gaelen; Devlin, Mark J.; Dicker, Simon R.; Klein, Jeff; France, Kevin; Gundersen, Joshua O.; Hughes, David H.; Martin, Peter G.; Olmi, Luca
2011-01-01
We present an implementation of the iterative flux-conserving Lucy-Richardson (L-R) deconvolution method of image restoration for maps produced by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Compared to the direct Fourier transform method of deconvolution, the L-R operation restores images with better-controlled background noise and increases source detectability. Intermediate iterated images are useful for studying extended diffuse structures, while the later iterations truly enhance point sources to near the designed diffraction limit of the telescope. The L-R method of deconvolution is efficient in resolving compact sources in crowded regions while simultaneously conserving their respective flux densities. We have analyzed its performance and convergence extensively through simulations and cross-correlations of the deconvolved images with available high-resolution maps. We present new science results from two BLAST surveys, in the Galactic regions K3-50 and IC 5146, further demonstrating the benefits of performing this deconvolution. We have resolved three clumps within a radius of 4.'5 inside the star-forming molecular cloud containing K3-50. Combining the well-resolved dust emission map with available multi-wavelength data, we have constrained the spectral energy distributions (SEDs) of five clumps to obtain masses (M), bolometric luminosities (L), and dust temperatures (T). The L-M diagram has been used as a diagnostic tool to estimate the evolutionary stages of the clumps. There are close relationships between dust continuum emission and both 21 cm radio continuum and 12 CO molecular line emission. The restored extended large-scale structures in the Northern Streamer of IC 5146 have a strong spatial correlation with both SCUBA and high-resolution extinction images. A dust temperature of 12 K has been obtained for the central filament. We report physical properties of ten compact sources, including six associated protostars, by fitting
Smooth function approximation using neural networks.
Ferrari, Silvia; Stengel, Robert F
2005-01-01
An algebraic approach for representing multidimensional nonlinear functions by feedforward neural networks is presented. In this paper, the approach is implemented for the approximation of smooth batch data containing the function's input, output, and possibly, gradient information. The training set is associated to the network adjustable parameters by nonlinear weight equations. The cascade structure of these equations reveals that they can be treated as sets of linear systems. Hence, the training process and the network approximation properties can be investigated via linear algebra. Four algorithms are developed to achieve exact or approximate matching of input-output and/or gradient-based training sets. Their application to the design of forward and feedback neurocontrollers shows that algebraic training is characterized by faster execution speeds and better generalization properties than contemporary optimization techniques.
Smooth driving of Moessbauer electromechanical transducers
Energy Technology Data Exchange (ETDEWEB)
Veiga, A., E-mail: veiga@fisica.unlp.edu.ar; Mayosky, M. A. [Universidad Nacional de La Plata, Facultad de Ingenieria (Argentina); Martinez, N.; Mendoza Zelis, P.; Pasquevich, G. A.; Sanchez, F. H. [Instituto de Fisica La Plata, CONICET (Argentina)
2011-11-15
Quality of Moessbauer spectra is strongly related to the performance of source velocity modulator. Traditional electromechanical driving techniques demand hard-edged square or triangular velocity waveforms that introduce long settling times and demand careful driver tuning. For this work, the behavior of commercial velocity transducers and drive units was studied under different working conditions. Different velocity reference waveforms in constant-acceleration, constant-velocity and programmable-velocity techniques were tested. Significant improvement in spectrometer efficiency and accuracy was achieved by replacing triangular and square hard edges with continuous smooth-shaped transitions. A criterion for best waveform selection and synchronization is presented and attainable enhancements are evaluated. In order to fully exploit this driving technique, a compact microprocessor-based architecture is proposed and a suitable data acquisition system implementation is presented. System linearity and efficiency characterization are also shown.
Smooth muscle cell phenotypic switching in stroke.
Poittevin, Marine; Lozeron, Pierre; Hilal, Rose; Levy, Bernard I; Merkulova-Rainon, Tatiana; Kubis, Nathalie
2014-06-01
Disruption of cerebral blood flow after stroke induces cerebral tissue injury through multiple mechanisms that are not yet fully understood. Smooth muscle cells (SMCs) in blood vessel walls play a key role in cerebral blood flow control. Cerebral ischemia triggers these cells to switch to a phenotype that will be either detrimental or beneficial to brain repair. Moreover, SMC can be primarily affected genetically or by toxic metabolic molecules. After stroke, this pathological phenotype has an impact on the incidence, pattern, severity, and outcome of the cerebral ischemic disease. Although little research has been conducted on the pathological role and molecular mechanisms of SMC in cerebrovascular ischemic diseases, some therapeutic targets have already been identified and could be considered for further pharmacological development. We examine these different aspects in this review.
Smoothed Particle Hydrodynamics Coupled with Radiation Transfer
Susa, Hajime
2006-04-01
We have constructed a brand-new radiation hydrodynamics solver based upon Smoothed Particle Hydrodynamics, which works on a parallel computer system. The code is designed to investigate the formation and evolution of first-generation objects at z ≳ 10, where the radiative feedback from various sources plays important roles. The code can compute the fraction of chemical species e, H+, H, H-, H2, and H+2 by by fully implicit time integration. It also can deal with multiple sources of ionizing radiation, as well as radiation at Lyman-Werner band. We compare the results for a few test calculations with the results of one-dimensional simulations, in which we find good agreements with each other. We also evaluate the speedup by parallelization, which is found to be almost ideal, as long as the number of sources is comparable to the number of processors.
Viscoplastic augmentation of the smooth cap model
International Nuclear Information System (INIS)
Schwer, Leonard E.
1994-01-01
The most common numerical viscoplastic implementations are formulations attributed to Perzyna. Although Perzyna-type algorithms are popular, they have several disadvantages relating to the lack of enforcement of the consistency condition in plasticity. The present work adapts a relatively unknown viscoplastic formulation attributed to Duvaut and Lions and generalized to multi-surface plasticity by Simo et al. The attraction of the Duvaut-Lions formulation is its ease of numerical implementation in existing elastoplastic algorithms. The present work provides a motivation for the Duvaut-Lions viscoplastic formulation, derivation of the algorithm and comparison with the Perzyna algorithm. A simple uniaxial strain numerical simulation is used to compare the results of the Duvaut-Lions algorithm, as adapted to the ppercase[dyna3d] smooth cap model with results from a Perzyna algorithm adapted by Katona and Muleret to an implicit code. ((orig.))
Contruction of a smoothed DEA frontier
Directory of Open Access Journals (Sweden)
Mello João Carlos Correia Baptista Soares de
2002-01-01
Full Text Available It is known that the DEA multipliers model does not allow a unique solution for the weights. This is due to the absence of unique derivatives in the extreme-efficient points, which is a consequence of the piecewise linear nature of the frontier. In this paper we propose a method to solve this problem, consisting of changing the original DEA frontier for a new one, smooth (with continuous derivatives at every point and closest to the original frontier. We present the theoretical development for the general case, exemplified with the particular case of the BCC model with one input and one output. The 3-dimensional problem is briefly discussed. Some uses of the model are summarised, and one of them, a new Cross-Evaluation model, is presented.
Diffusion tensor smoothing through weighted Karcher means
Carmichael, Owen; Chen, Jun; Paul, Debashis; Peng, Jie
2014-01-01
Diffusion tensor magnetic resonance imaging (MRI) quantifies the spatial distribution of water Diffusion at each voxel on a regular grid of locations in a biological specimen by Diffusion tensors– 3 × 3 positive definite matrices. Removal of noise from DTI is an important problem due to the high scientific relevance of DTI and relatively low signal to noise ratio it provides. Leading approaches to this problem amount to estimation of weighted Karcher means of Diffusion tensors within spatial neighborhoods, under various metrics imposed on the space of tensors. However, it is unclear how the behavior of these estimators varies with the magnitude of DTI sensor noise (the noise resulting from the thermal e!ects of MRI scanning) as well as the geometric structure of the underlying Diffusion tensor neighborhoods. In this paper, we combine theoretical analysis, empirical analysis of simulated DTI data, and empirical analysis of real DTI scans to compare the noise removal performance of three kernel-based DTI smoothers that are based on Euclidean, log-Euclidean, and affine-invariant metrics. The results suggest, contrary to conventional wisdom, that imposing a simplistic Euclidean metric may in fact provide comparable or superior noise removal, especially in relatively unstructured regions and/or in the presence of moderate to high levels of sensor noise. On the contrary, log-Euclidean and affine-invariant metrics may lead to better noise removal in highly structured anatomical regions, especially when the sensor noise is of low magnitude. These findings emphasize the importance of considering the interplay of sensor noise magnitude and tensor field geometric structure when assessing Diffusion tensor smoothing options. They also point to the necessity for continued development of smoothing methods that perform well across a large range of scenarios. PMID:25419264
Standard Errors for Matrix Correlations.
Ogasawara, Haruhiko
1999-01-01
Derives the asymptotic standard errors and intercorrelations for several matrix correlations assuming multivariate normality for manifest variables and derives the asymptotic standard errors of the matrix correlations for two factor-loading matrices. (SLD)
Error forecasting schemes of error correction at receiver
International Nuclear Information System (INIS)
Bhunia, C.T.
2007-08-01
To combat error in computer communication networks, ARQ (Automatic Repeat Request) techniques are used. Recently Chakraborty has proposed a simple technique called the packet combining scheme in which error is corrected at the receiver from the erroneous copies. Packet Combining (PC) scheme fails: (i) when bit error locations in erroneous copies are the same and (ii) when multiple bit errors occur. Both these have been addressed recently by two schemes known as Packet Reversed Packet Combining (PRPC) Scheme, and Modified Packet Combining (MPC) Scheme respectively. In the letter, two error forecasting correction schemes are reported, which in combination with PRPC offer higher throughput. (author)
Evaluating a medical error taxonomy.
Brixey, Juliana; Johnson, Todd R.; Zhang, Jiajie
2002-01-01
Healthcare has been slow in using human factors principles to reduce medical errors. The Center for Devices and Radiological Health (CDRH) recognizes that a lack of attention to human factors during product development may lead to errors that have the potential for patient injury, or even death. In response to the need for reducing medication errors, the National Coordinating Council for Medication Errors Reporting and Prevention (NCC MERP) released the NCC MERP taxonomy that provides a stand...
Uncertainty quantification and error analysis
Energy Technology Data Exchange (ETDEWEB)
Higdon, Dave M [Los Alamos National Laboratory; Anderson, Mark C [Los Alamos National Laboratory; Habib, Salman [Los Alamos National Laboratory; Klein, Richard [Los Alamos National Laboratory; Berliner, Mark [OHIO STATE UNIV.; Covey, Curt [LLNL; Ghattas, Omar [UNIV OF TEXAS; Graziani, Carlo [UNIV OF CHICAGO; Seager, Mark [LLNL; Sefcik, Joseph [LLNL; Stark, Philip [UC/BERKELEY; Stewart, James [SNL
2010-01-01
UQ studies all sources of error and uncertainty, including: systematic and stochastic measurement error; ignorance; limitations of theoretical models; limitations of numerical representations of those models; limitations on the accuracy and reliability of computations, approximations, and algorithms; and human error. A more precise definition for UQ is suggested below.
Error Patterns in Problem Solving.
Babbitt, Beatrice C.
Although many common problem-solving errors within the realm of school mathematics have been previously identified, a compilation of such errors is not readily available within learning disabilities textbooks, mathematics education texts, or teacher's manuals for school mathematics texts. Using data on error frequencies drawn from both the Fourth…
Performance, postmodernity and errors
DEFF Research Database (Denmark)
Harder, Peter
2013-01-01
speaker’s competency (note the –y ending!) reflects adaptation to the community langue, including variations. This reversal of perspective also reverses our understanding of the relationship between structure and deviation. In the heyday of structuralism, it was tempting to confuse the invariant system...... with the prestige variety, and conflate non-standard variation with parole/performance and class both as erroneous. Nowadays the anti-structural sentiment of present-day linguistics makes it tempting to confuse the rejection of ideal abstract structure with a rejection of any distinction between grammatical...... as deviant from the perspective of function-based structure and discuss to what extent the recognition of a community langue as a source of adaptive pressure may throw light on different types of deviation, including language handicaps and learner errors....
Zhou, Zhongxing; Gao, Feng; Zhao, Huijuan; Zhang, Lixin
2012-11-21
New x-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source size and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the blurred x-ray phase contrast images. In this study, three different deconvolution techniques, including Wiener filtering, Tikhonov regularization and Fourier-wavelet regularized deconvolution (ForWaRD), were applied to the simulated and experimental free space propagation x-ray phase contrast images of simple geometric phantoms. These algorithms were evaluated in terms of phase contrast improvement and signal-to-noise ratio. The results demonstrate that the ForWaRD algorithm is most appropriate for phase contrast image restoration among above-mentioned methods; it can effectively restore the lost information of phase contrast fringes while reduce the amplified noise during Fourier regularization.
Bifurcation theory for finitely smooth planar autonomous differential systems
Han, Maoan; Sheng, Lijuan; Zhang, Xiang
2018-03-01
In this paper we establish bifurcation theory of limit cycles for planar Ck smooth autonomous differential systems, with k ∈ N. The key point is to study the smoothness of bifurcation functions which are basic and important tool on the study of Hopf bifurcation at a fine focus or a center, and of Poincaré bifurcation in a period annulus. We especially study the smoothness of the first order Melnikov function in degenerate Hopf bifurcation at an elementary center. As we know, the smoothness problem was solved for analytic and C∞ differential systems, but it was not tackled for finitely smooth differential systems. Here, we present their optimal regularity of these bifurcation functions and their asymptotic expressions in the finite smooth case.
Errors in causal inference: an organizational schema for systematic error and random error.
Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji
2016-11-01
To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.
Isotropic non-white matter partial volume effects in constrained spherical deconvolution
Directory of Open Access Journals (Sweden)
Timo eRoine
2014-03-01
Full Text Available Diffusion-weighted (DW magnetic resonance imaging (MRI is a noninvasive imaging method, which can be used to investigate neural tracts in the white matter (WM of the brain. Significant partial volume effects (PVE are present in the DW signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM and cerebrospinal fluid (CSF, and by multiple nonparallel WM fiber populations. High angular resolution diffusion imaging (HARDI methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD. Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNR, fiber configurations, and tissue fractions.Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50 % of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50 % GM volume for maximum spherical harmonics orders of 8 and below, and already with 25 % GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm2, reasonable SNR (~30 and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs
Isotropic non-white matter partial volume effects in constrained spherical deconvolution.
Roine, Timo; Jeurissen, Ben; Perrone, Daniele; Aelterman, Jan; Leemans, Alexander; Philips, Wilfried; Sijbers, Jan
2014-01-01
Diffusion-weighted (DW) magnetic resonance imaging (MRI) is a non-invasive imaging method, which can be used to investigate neural tracts in the white matter (WM) of the brain. Significant partial volume effects (PVEs) are present in the DW signal due to relatively large voxel sizes. These PVEs can be caused by both non-WM tissue, such as gray matter (GM) and cerebrospinal fluid (CSF), and by multiple non-parallel WM fiber populations. High angular resolution diffusion imaging (HARDI) methods have been developed to correctly characterize complex WM fiber configurations, but to date, many of the HARDI methods do not account for non-WM PVEs. In this work, we investigated the isotropic PVEs caused by non-WM tissue in WM voxels on fiber orientations extracted with constrained spherical deconvolution (CSD). Experiments were performed on simulated and real DW-MRI data. In particular, simulations were performed to demonstrate the effects of varying the diffusion weightings, signal-to-noise ratios (SNRs), fiber configurations, and tissue fractions. Our results show that the presence of non-WM tissue signal causes a decrease in the precision of the detected fiber orientations and an increase in the detection of false peaks in CSD. We estimated 35-50% of WM voxels to be affected by non-WM PVEs. For HARDI sequences, which typically have a relatively high degree of diffusion weighting, these adverse effects are most pronounced in voxels with GM PVEs. The non-WM PVEs become severe with 50% GM volume for maximum spherical harmonics orders of 8 and below, and already with 25% GM volume for higher orders. In addition, a low diffusion weighting or SNR increases the effects. The non-WM PVEs may cause problems in connectomics, where reliable fiber tracking at the WM-GM interface is especially important. We suggest acquiring data with high diffusion-weighting 2500-3000 s/mm(2), reasonable SNR (~30) and using lower SH orders in GM contaminated regions to minimize the non-WM PVEs in CSD.
Imaging of stellar surfaces with the Occamian approach and the least-squares deconvolution technique
Järvinen, S. P.; Berdyugina, S. V.
2010-10-01
Context. We present in this paper a new technique for the indirect imaging of stellar surfaces (Doppler imaging, DI), when low signal-to-noise spectral data have been improved by the least-squares deconvolution (LSD) method and inverted into temperature maps with the Occamian approach. We apply this technique to both simulated and real data and investigate its applicability for different stellar rotation rates and noise levels in data. Aims: Our goal is to boost the signal of spots in spectral lines and to reduce the effect of photon noise without loosing the temperature information in the lines. Methods: We simulated data from a test star, to which we added different amounts of noise, and employed the inversion technique based on the Occamian approach with and without LSD. In order to be able to infer a temperature map from LSD profiles, we applied the LSD technique for the first time to both the simulated observations and theoretical local line profiles, which remain dependent on temperature and limb angles. We also investigated how the excitation energy of individual lines effects the obtained solution by using three submasks that have lines with low, medium, and high excitation energy levels. Results: We show that our novel approach enables us to overcome the limitations of the two-temperature approximation, which was previously employed for LSD profiles, and to obtain true temperature maps with stellar atmosphere models. The resulting maps agree well with those obtained using the inversion code without LSD, provided the data are noiseless. However, using LSD is only advisable for poor signal-to-noise data. Further, we show that the Occamian technique, both with and without LSD, approaches the surface temperature distribution reasonably well for an adequate spatial resolution. Thus, the stellar rotation rate has a great influence on the result. For instance, in a slowly rotating star, closely situated spots are usually recovered blurred and unresolved, which