Testing the inverse-square law of gravity: Error and design with the upward continuation integral
International Nuclear Information System (INIS)
Thomas, J.
1989-01-01
It has been reported that the inverse-square law of gravity is violated over a range of a few hundred meters. I present a different method for the analysis of the data from that experiment. In this method, the experimental error can be evaluated analytically and I confirm the previous analysis but show that it is a 2σ effect. The method can also be used to design new experiments that will yield minimum errors for a fixed number of data points
Some Results on Mean Square Error for Factor Score Prediction
Krijnen, Wim P.
2006-01-01
For the confirmatory factor model a series of inequalities is given with respect to the mean square error (MSE) of three main factor score predictors. The eigenvalues of these MSE matrices are a monotonic function of the eigenvalues of the matrix gamma[subscript rho] = theta[superscript 1/2] lambda[subscript rho] 'psi[subscript rho] [superscript…
Directory of Open Access Journals (Sweden)
Nazelie Kassabian
2014-06-01
Full Text Available Railway signaling is a safety system that has evolved over the last couple of centuries towards autonomous functionality. Recently, great effort is being devoted in this field, towards the use and exploitation of Global Navigation Satellite System (GNSS signals and GNSS augmentation systems in view of lower railway track equipments and maintenance costs, that is a priority to sustain the investments for modernizing the local and regional lines most of which lack automatic train protection systems and are still manually operated. The objective of this paper is to assess the sensitivity of the Linear Minimum Mean Square Error (LMMSE algorithm to modeling errors in the spatial correlation function that characterizes true pseudorange Differential Corrections (DCs. This study is inspired by the railway application; however, it applies to all transportation systems, including the road sector, that need to be complemented by an augmentation system in order to deliver accurate and reliable positioning with integrity specifications. A vector of noisy pseudorange DC measurements are simulated, assuming a Gauss-Markov model with a decay rate parameter inversely proportional to the correlation distance that exists between two points of a certain environment. The LMMSE algorithm is applied on this vector to estimate the true DC, and the estimation error is compared to the noise added during simulation. The results show that for large enough correlation distance to Reference Stations (RSs distance separation ratio values, the LMMSE brings considerable advantage in terms of estimation error accuracy and precision. Conversely, the LMMSE algorithm may deteriorate the quality of the DC measurements whenever the ratio falls below a certain threshold.
ERROR HANDLING IN INTEGRATION WORKFLOWS
Directory of Open Access Journals (Sweden)
Alexey M. Nazarenko
2017-01-01
Full Text Available Simulation experiments performed while solving multidisciplinary engineering and scientific problems require joint usage of multiple software tools. Further, when following a preset plan of experiment or searching for optimum solu- tions, the same sequence of calculations is run multiple times with various simulation parameters, input data, or conditions while overall workflow does not change. Automation of simulations like these requires implementing of a workflow where tool execution and data exchange is usually controlled by a special type of software, an integration environment or plat- form. The result is an integration workflow (a platform-dependent implementation of some computing workflow which, in the context of automation, is a composition of weakly coupled (in terms of communication intensity typical subtasks. These compositions can then be decomposed back into a few workflow patterns (types of subtasks interaction. The pat- terns, in their turn, can be interpreted as higher level subtasks.This paper considers execution control and data exchange rules that should be imposed by the integration envi- ronment in the case of an error encountered by some integrated software tool. An error is defined as any abnormal behavior of a tool that invalidates its result data thus disrupting the data flow within the integration workflow. The main requirementto the error handling mechanism implemented by the integration environment is to prevent abnormal termination of theentire workflow in case of missing intermediate results data. Error handling rules are formulated on the basic pattern level and on the level of a composite task that can combine several basic patterns as next level subtasks. The cases where workflow behavior may be different, depending on user's purposes, when an error takes place, and possible error handling op- tions that can be specified by the user are also noted in the work.
Gao, J.
2014-12-01
Reducing modeling error is often a major concern of empirical geophysical models. However, modeling errors can be defined in different ways: When the response variable is continuous, the most commonly used metrics are squared (SQ) and absolute (ABS) errors. For most applications, ABS error is the more natural, but SQ error is mathematically more tractable, so is often used as a substitute with little scientific justification. Existing literature has not thoroughly investigated the implications of using SQ error in place of ABS error, especially not geospatially. This study compares the two metrics through the lens of bias-variance decomposition (BVD). BVD breaks down the expected modeling error of each model evaluation point into bias (systematic error), variance (model sensitivity), and noise (observation instability). It offers a way to probe the composition of various error metrics. I analytically derived the BVD of ABS error and compared it with the well-known SQ error BVD, and found that not only the two metrics measure the characteristics of the probability distributions of modeling errors differently, but also the effects of these characteristics on the overall expected error are different. Most notably, under SQ error all bias, variance, and noise increase expected error, while under ABS error certain parts of the error components reduce expected error. Since manipulating these subtractive terms is a legitimate way to reduce expected modeling error, SQ error can never capture the complete story embedded in ABS error. I then empirically compared the two metrics with a supervised remote sensing model for mapping surface imperviousness. Pair-wise spatially-explicit comparison for each error component showed that SQ error overstates all error components in comparison to ABS error, especially variance-related terms. Hence, substituting ABS error with SQ error makes model performance appear worse than it actually is, and the analyst would more likely accept a
On the mean squared error of the ridge estimator of the covariance and precision matrix
van Wieringen, Wessel N.
2017-01-01
For a suitably chosen ridge penalty parameter, the ridge regression estimator uniformly dominates the maximum likelihood regression estimator in terms of the mean squared error. Analogous results for the ridge maximum likelihood estimators of covariance and precision matrix are presented.
Directory of Open Access Journals (Sweden)
Mardawia M Panrereng
2015-06-01
Full Text Available Dalam beberapa tahun terakhir, sistem komunikasi akustik bawah air banyak dikembangkan oleh beberapa peneliti. Besarnya tantangan yang dihadapi membuat para peneliti semakin tertarik untuk mengembangkan penelitian dibidang ini. Kanal bawah air merupakan media komunikasi yang sulit karena adanya attenuasi, absorption, dan multipath yang disebabkan oleh gerakan gelombang air setiap saat. Untuk perairan dangkal, multipath disebabkan adanya pantulan dari permukaan dan dasar laut. Kebutuhan pengiriman data cepat dengan bandwidth terbatas menjadikan Ortogonal Frequency Division Multiplexing (OFDM sebagai solusi untuk komunikasi transmisi tinggi dengan modulasi menggunakan Binary Phase-Shift Keying (BPSK. Estimasi kanal bertujuan untuk mengetahui karakteristik respon impuls kanal propagasi dengan mengirimkan pilot simbol. Pada estimasi kanal menggunakan metode Least Square (LS nilai Mean Square Error (MSE yang diperoleh cenderung lebih besar dari metode estimasi kanal menggunakan metode Minimum Mean Square (MMSE. Hasil kinerja estimasi kanal berdasarkan perhitungan Bit Error Rate (BER untuk estimasi kanal menggunakan metode LS dan metode MMSE tidak menunjukkan perbedaan yang signifikan yaitu berselisih satu SNR untuk setiap metode estimasi kanal yang digunakan.
Suliman, Mohamed Abdalla Elhag
2016-12-19
This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model matrix. This perturbation is introduced to enhance the singular-value (SV) structure of the matrix and hence to provide a better solution. The proposed approach is derived to select the regularization parameter in a way that minimizes the mean-squared error (MSE) of the estimator. Numerical results demonstrate that the proposed approach outperforms a set of benchmark methods in most cases when applied to different scenarios of discrete ill-posed problems. Jointly, the proposed approach enjoys the lowest run-time and offers the highest level of robustness amongst all the tested methods.
Optical pattern recognition architecture implementing the mean-square error correlation algorithm
Molley, Perry A.
1991-01-01
An optical architecture implementing the mean-square error correlation algorithm, MSE=.SIGMA.[I-R].sup.2 for discriminating the presence of a reference image R in an input image scene I by computing the mean-square-error between a time-varying reference image signal s.sub.1 (t) and a time-varying input image signal s.sub.2 (t) includes a laser diode light source which is temporally modulated by a double-sideband suppressed-carrier source modulation signal I.sub.1 (t) having the form I.sub.1 (t)=A.sub.1 [1+.sqroot.2m.sub.1 s.sub.1 (t)cos (2.pi.f.sub.o t)] and the modulated light output from the laser diode source is diffracted by an acousto-optic deflector. The resultant intensity of the +1 diffracted order from the acousto-optic device is given by: I.sub.2 (t)=A.sub.2 [+2m.sub.2.sup.2 s.sub.2.sup.2 (t)-2.sqroot.2m.sub.2 (t) cos (2.pi.f.sub.o t] The time integration of the two signals I.sub.1 (t) and I.sub.2 (t) on the CCD deflector plane produces the result R(.tau.) of the mean-square error having the form: R(.tau.)=A.sub.1 A.sub.2 {[T]+[2m.sub.2.sup.2.multidot..intg.s.sub.2.sup.2 (t-.tau.)dt]-[2m.sub.1 m.sub.2 cos (2.tau.f.sub.o .tau.).multidot..intg.s.sub.1 (t)s.sub.2 (t-.tau.)dt]} where: s.sub.1 (t) is the signal input to the diode modulation source: s.sub.2 (t) is the signal input to the AOD modulation source; A.sub.1 is the light intensity; A.sub.2 is the diffraction efficiency; m.sub.1 and m.sub.2 are constants that determine the signal-to-bias ratio; f.sub.o is the frequency offset between the oscillator at f.sub.c and the modulation at f.sub.c +f.sub.o ; and a.sub.o and a.sub.1 are constant chosen to bias the diode source and the acousto-optic deflector into their respective linear operating regions so that the diode source exhibits a linear intensity characteristic and the AOD exhibits a linear amplitude characteristic.
Error propagation of partial least squares for parameters optimization in NIR modeling.
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-05
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models. Copyright © 2017. Published by Elsevier B.V.
Error propagation of partial least squares for parameters optimization in NIR modeling
Du, Chenzhao; Dai, Shengyun; Qiao, Yanjiang; Wu, Zhisheng
2018-03-01
A novel methodology is proposed to determine the error propagation of partial least-square (PLS) for parameters optimization in near-infrared (NIR) modeling. The parameters include spectral pretreatment, latent variables and variable selection. In this paper, an open source dataset (corn) and a complicated dataset (Gardenia) were used to establish PLS models under different modeling parameters. And error propagation of modeling parameters for water quantity in corn and geniposide quantity in Gardenia were presented by both type І and type II error. For example, when variable importance in the projection (VIP), interval partial least square (iPLS) and backward interval partial least square (BiPLS) variable selection algorithms were used for geniposide in Gardenia, compared with synergy interval partial least squares (SiPLS), the error weight varied from 5% to 65%, 55% and 15%. The results demonstrated how and what extent the different modeling parameters affect error propagation of PLS for parameters optimization in NIR modeling. The larger the error weight, the worse the model. Finally, our trials finished a powerful process in developing robust PLS models for corn and Gardenia under the optimal modeling parameters. Furthermore, it could provide a significant guidance for the selection of modeling parameters of other multivariate calibration models.
Autcha Araveeporn
2013-01-01
This paper compares a Least-Squared Random Coefficient Autoregressive (RCA) model with a Least-Squared RCA model based on Autocorrelated Errors (RCA-AR). We looked at only the first order models, denoted RCA(1) and RCA(1)-AR(1). The efficiency of the Least-Squared method was checked by applying the models to Brownian motion and Wiener process, and the efficiency followed closely the asymptotic properties of a normal distribution. In a simulation study, we compared the performance of RCA(1) an...
Angular truncation errors in integrating nephelometry
International Nuclear Information System (INIS)
Moosmueller, Hans; Arnott, W. Patrick
2003-01-01
Ideal integrating nephelometers integrate light scattered by particles over all directions. However, real nephelometers truncate light scattered in near-forward and near-backward directions below a certain truncation angle (typically 7 deg. ). This results in truncation errors, with the forward truncation error becoming important for large particles. Truncation errors are commonly calculated using Mie theory, which offers little physical insight and no generalization to nonspherical particles. We show that large particle forward truncation errors can be calculated and understood using geometric optics and diffraction theory. For small truncation angles (i.e., <10 deg. ) as typical for modern nephelometers, diffraction theory by itself is sufficient. Forward truncation errors are, by nearly a factor of 2, larger for absorbing particles than for nonabsorbing particles because for large absorbing particles most of the scattered light is due to diffraction as transmission is suppressed. Nephelometers calibration procedures are also discussed as they influence the effective truncation error
Error analysis of some Galerkin - least squares methods for the elasticity equations
International Nuclear Information System (INIS)
Franca, L.P.; Stenberg, R.
1989-05-01
We consider the recent technique of stabilizing mixed finite element methods by augmenting the Galerkin formulation with least squares terms calculated separately on each element. The error analysis is performed in a unified manner yielding improved results for some methods introduced earlier. In addition, a new formulation is introduced and analyzed [pt
Minimum Mean-Square Error Estimation of Mel-Frequency Cepstral Features
DEFF Research Database (Denmark)
Jensen, Jesper; Tan, Zheng-Hua
2015-01-01
In this work we consider the problem of feature enhancement for noise-robust automatic speech recognition (ASR). We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features, which is based on a minimum number of well-established, theoretically consistent......-of-the-art MFCC feature enhancement algorithms within this class of algorithms, while theoretically suboptimal or based on theoretically inconsistent assumptions, perform close to optimally in the MMSE sense....
Some Modified Integrated Squared Error Procedures for Multivariate Normal Data.
1982-06-01
p-dimensional Gaussian. There are a number of measures of qualitative robustness but the most important is the influence function . Most of the other...measures are derived from the influence function . The influence function is simply proportional to the score function (Huber, 1981, p. 45 ). The... influence function at the p-variate Gaussian distribution Np (UV) is as -1P IC(x; ,N) = IE&) ;-") sD=XV = (I+c) (p+2)(x-p) exp(- ! (x-p) TV-.1-)) (3.6
Lu, Xinjiang; Liu, Wenbo; Zhou, Chuang; Huang, Minghui
2017-06-13
The least-squares support vector machine (LS-SVM) is a popular data-driven modeling method and has been successfully applied to a wide range of applications. However, it has some disadvantages, including being ineffective at handling non-Gaussian noise as well as being sensitive to outliers. In this paper, a robust LS-SVM method is proposed and is shown to have more reliable performance when modeling a nonlinear system under conditions where Gaussian or non-Gaussian noise is present. The construction of a new objective function allows for a reduction of the mean of the modeling error as well as the minimization of its variance, and it does not constrain the mean of the modeling error to zero. This differs from the traditional LS-SVM, which uses a worst-case scenario approach in order to minimize the modeling error and constrains the mean of the modeling error to zero. In doing so, the proposed method takes the modeling error distribution information into consideration and is thus less conservative and more robust in regards to random noise. A solving method is then developed in order to determine the optimal parameters for the proposed robust LS-SVM. An additional analysis indicates that the proposed LS-SVM gives a smaller weight to a large-error training sample and a larger weight to a small-error training sample, and is thus more robust than the traditional LS-SVM. The effectiveness of the proposed robust LS-SVM is demonstrated using both artificial and real life cases.
Analysis of S-box in Image Encryption Using Root Mean Square Error Method
Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan
2012-07-01
The use of substitution boxes (S-boxes) in encryption applications has proven to be an effective nonlinear component in creating confusion and randomness. The S-box is evolving and many variants appear in literature, which include advanced encryption standard (AES) S-box, affine power affine (APA) S-box, Skipjack S-box, Gray S-box, Lui J S-box, residue prime number S-box, Xyi S-box, and S8 S-box. These S-boxes have algebraic and statistical properties which distinguish them from each other in terms of encryption strength. In some circumstances, the parameters from algebraic and statistical analysis yield results which do not provide clear evidence in distinguishing an S-box for an application to a particular set of data. In image encryption applications, the use of S-boxes needs special care because the visual analysis and perception of a viewer can sometimes identify artifacts embedded in the image. In addition to existing algebraic and statistical analysis already used for image encryption applications, we propose an application of root mean square error technique, which further elaborates the results and enables the analyst to vividly distinguish between the performances of various S-boxes. While the use of the root mean square error analysis in statistics has proven to be effective in determining the difference in original data and the processed data, its use in image encryption has shown promising results in estimating the strength of the encryption method. In this paper, we show the application of the root mean square error analysis to S-box image encryption. The parameters from this analysis are used in determining the strength of S-boxes
Suliman, Mohamed Abdalla Elhag; Ballal, Tarig; Kammoun, Abla; Al-Naffouri, Tareq Y.
2016-01-01
This paper proposes a new approach to find the regularization parameter for linear least-squares discrete ill-posed problems. In the proposed approach, an artificial perturbation matrix with a bounded norm is forced into the discrete ill-posed model
International Nuclear Information System (INIS)
Gillet, M.
1986-07-01
This thesis presents a study for the surveillance of the ''primary coolant circuit inventory monitoring'' of a pressurized water reactor. A reference model is developed in view of an automatic system ensuring detection and diagnostic in real time. The methods used for the present application are statistical tests and a method related to pattern recognition. The estimation of failures detected, difficult owing to the non-linearity of the problem, is treated by the least error squares method of the predictor or corrector type, and by filtering. It is in this frame that a new optimized method with superlinear convergence is developed, and that a segmented linearization of the model is introduced, in view of a multiple filtering [fr
Square-integrable wave packets from the Volkov solutions
International Nuclear Information System (INIS)
Zakowicz, Stephan
2005-01-01
Rigorous mathematical proofs of some properties of the Volkov solutions are presented, which describe the motion of a relativistic charged Dirac particle in a classical, plane electromagnetic wave. The Volkov solutions are first rewritten in a convenient form, which clearly reveals some of the symmetries of the underlying Dirac equation. Assuming continuity and boundedness of the electromagnetic vector potential, it is shown how one may construct square-integrable wave packets from momentum distributions in the space C 0 ∞ (R 3 ) 4 . If, in addition, the vector potential is C 1 and the derivative is bounded, these wave packets decay in space faster than any polynomial and fulfill the Dirac equation. The mapping which takes momentum distributions into wave packets is shown to be isometric with respect to the L 2 (R 3 ) 4 norm and may therefore be continuously extended to a mapping from L 2 (R 3 ) 4 . For a momentum function in L 1 (R 3 ) 4 intersection L 2 (R 3 ) 4 , an integral representation of this extension is presented
Gupta, Hoshin V.; Kling, Harald; Yilmaz, Koray K.; Martinez-Baquero, Guillermo F.
2009-01-01
The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. The analysis is illustrated by calibrating a simple conceptual precipitation-runoff model to daily data for a number of Austrian basins having a broad range of hydro-meteorological characteristics. Evaluation of the results clearly demonstrates the problems that can be associated with any calibration based on the NSE (or MSE) criterion. While we propose and test an alternative criterion that can help to reduce model calibration problems, the primary purpose of this study is not to present an improved measure of model performance. Instead, we seek to show that there are systematic problems inherent with any optimization based on formulations related to the MSE. The analysis and results have implications to the manner in which we calibrate and evaluate environmental models; we discuss these and suggest possible ways forward that may move us towards an improved and diagnostically meaningful approach to model performance evaluation and identification.
Bai, Mingsian R; Hsieh, Ping-Ju; Hur, Kur-Nan
2009-02-01
The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms.
Sinha, Mrinal
2015-08-19
We propose an interferometric least-squares migration method that can significantly reduce migration artifacts due to statics and errors in the near-surface velocity model. We first choose a reference reflector whose topography is well known from the, e.g., well logs. Reflections from this reference layer are correlated with the traces associated with reflections from deeper interfaces to get crosscorrelograms. These crosscorrelograms are then migrated using interferometric least-squares migration (ILSM). In this way statics and velocity errors at the near surface are largely eliminated for the examples in our paper.
Square-Integrable Wave Packets from the Volkov Solutions
Zakowicz, S
2004-01-01
Rigorous mathematical proofs of some properties of the Volkov solutions are presented, which describe the motion of a relativistic charged Dirac particle in a classical, plane electromagnetic wave. The Volkov solutions are first rewritten in a convenient form, which clearly reveals some of the symmetries of the underlying Dirac equation. Assuming continuity and boundedness of the electromagnetic vector potential, it is shown how one may construct square-integrable wave packets from momentum distributions in the space $\\mathcal{C}^{\\infty}_0(\\mathbb{R}^3)^4$. If, in addition, the vector potential is $\\mathcal{C}^1$ and the derivative is bounded, these wave packets decay in space faster than any polynomial and fulfill the Dirac equation. The mapping which takes momentum distributions into wave packets is shown to be isometric with respect to the $L^2(\\mathbb{R}^3)^4$ norm and may therefore be continuously extended to a mapping from $L^2(\\mathbb{R}^3)^4$. For a momen! tum function in $L^1(\\mathbb{R}^3)^4 \\cap L^...
Set-Valued Stochastic Equation with Set-Valued Square Integrable Martingale
Directory of Open Access Journals (Sweden)
Li Jun-Gang
2017-01-01
Full Text Available In this paper, we shall introduce the stochastic integral of a stochastic process with respect to set-valued square integrable martingale. Then we shall give the Aumann integral measurable theorem, and give the set-valued stochastic Lebesgue integral and set-valued square integrable martingale integral equation. The existence and uniqueness of solution to set-valued stochastic integral equation are proved. The discussion will be useful in optimal control and mathematical finance in psychological factors.
DEFF Research Database (Denmark)
Ni, Ronggang; Xu, Dianguo; Blaabjerg, Frede
2017-01-01
relationship with the magnetic field distortion. Position estimation errors caused by higher order harmonic inductances and voltage harmonics generated by the SVPWM are also discussed. Both simulations and experiments are carried out based on a commercial PMSM to verify the superiority of the proposed method......Rotor position estimated with high-frequency (HF) voltage injection methods can be distorted by voltage errors due to inverter nonlinearities, motor resistance, and rotational voltage drops, etc. This paper proposes an improved HF square-wave voltage injection algorithm, which is robust to voltage...... errors without any compensations meanwhile has less fluctuation in the position estimation error. The average position estimation error is investigated based on the analysis of phase harmonic inductances, and deduced in the form of the phase shift of the second-order harmonic inductances to derive its...
International Nuclear Information System (INIS)
Shuke, Noriyuki
1991-01-01
In hepatobiliary scintigraphy, kinetic model analysis, which provides kinetic parameters like hepatic extraction or excretion rate, have been done for quantitative evaluation of liver function. In this analysis, unknown model parameters are usually determined using nonlinear least square regression method (NLS method) where iterative calculation and initial estimate for unknown parameters are required. As a simple alternative to NLS method, direct integral linear least square regression method (DILS method), which can determine model parameters by a simple calculation without initial estimate, is proposed, and tested the applicability to analysis of hepatobiliary scintigraphy. In order to see whether DILS method could determine model parameters as good as NLS method, or to determine appropriate weight for DILS method, simulated theoretical data based on prefixed parameters were fitted to 1 compartment model using both DILS method with various weightings and NLS method. The parameter values obtained were then compared with prefixed values which were used for data generation. The effect of various weights on the error of parameter estimate was examined, and inverse of time was found to be the best weight to make the error minimum. When using this weight, DILS method could give parameter values close to those obtained by NLS method and both parameter values were very close to prefixed values. With appropriate weighting, the DILS method could provide reliable parameter estimate which is relatively insensitive to the data noise. In conclusion, the DILS method could be used as a simple alternative to NLS method, providing reliable parameter estimate. (author)
ERF/ERFC, Calculation of Error Function, Complementary Error Function, Probability Integrals
International Nuclear Information System (INIS)
Vogel, J.E.
1983-01-01
1 - Description of problem or function: ERF and ERFC are used to compute values of the error function and complementary error function for any real number. They may be used to compute other related functions such as the normal probability integrals. 4. Method of solution: The error function and complementary error function are approximated by rational functions. Three such rational approximations are used depending on whether - x .GE.4.0. In the first region the error function is computed directly and the complementary error function is computed via the identity erfc(x)=1.0-erf(x). In the other two regions the complementary error function is computed directly and the error function is computed from the identity erf(x)=1.0-erfc(x). The error function and complementary error function are real-valued functions of any real argument. The range of the error function is (-1,1). The range of the complementary error function is (0,2). 5. Restrictions on the complexity of the problem: The user is cautioned against using ERF to compute the complementary error function by using the identity erfc(x)=1.0-erf(x). This subtraction may cause partial or total loss of significance for certain values of x
Hoel, Hakon
2016-06-13
A formal mean square error expansion (MSE) is derived for Euler-Maruyama numerical solutions of stochastic differential equations (SDE). The error expansion is used to construct a pathwise, a posteriori, adaptive time-stepping Euler-Maruyama algorithm for numerical solutions of SDE, and the resulting algorithm is incorporated into a multilevel Monte Carlo (MLMC) algorithm for weak approximations of SDE. This gives an efficient MSE adaptive MLMC algorithm for handling a number of low-regularity approximation problems. In low-regularity numerical example problems, the developed adaptive MLMC algorithm is shown to outperform the uniform time-stepping MLMC algorithm by orders of magnitude, producing output whose error with high probability is bounded by TOL > 0 at the near-optimal MLMC cost rate б(TOL log(TOL)) that is achieved when the cost of sample generation is б(1).
Rotational error in path integration: encoding and execution errors in angle reproduction.
Chrastil, Elizabeth R; Warren, William H
2017-06-01
Path integration is fundamental to human navigation. When a navigator leaves home on a complex outbound path, they are able to keep track of their approximate position and orientation and return to their starting location on a direct homebound path. However, there are several sources of error during path integration. Previous research has focused almost exclusively on encoding error-the error in registering the outbound path in memory. Here, we also consider execution error-the error in the response, such as turning and walking a homebound trajectory. In two experiments conducted in ambulatory virtual environments, we examined the contribution of execution error to the rotational component of path integration using angle reproduction tasks. In the reproduction tasks, participants rotated once and then rotated again to face the original direction, either reproducing the initial turn or turning through the supplementary angle. One outstanding difficulty in disentangling encoding and execution error during a typical angle reproduction task is that as the encoding angle increases, so does the required response angle. In Experiment 1, we dissociated these two variables by asking participants to report each encoding angle using two different responses: by turning to walk on a path parallel to the initial facing direction in the same (reproduction) or opposite (supplementary angle) direction. In Experiment 2, participants reported the encoding angle by turning both rightward and leftward onto a path parallel to the initial facing direction, over a larger range of angles. The results suggest that execution error, not encoding error, is the predominant source of error in angular path integration. These findings also imply that the path integrator uses an intrinsic (action-scaled) rather than an extrinsic (objective) metric.
DEFF Research Database (Denmark)
Tscherning, Carl Christian
2015-01-01
outside the data area. On the other hand, a comparison of predicted quantities with observed values show that the error also varies depending on the local data standard deviation. This quantity may be (and has been) estimated using the GOCE second order vertical derivative, Tzz, in the area covered...... by the satellite. The ratio between the nearly constant standard deviations of a predicted quantity (e.g. in a 25° × 25° area) and the standard deviations of Tzz in smaller cells (e.g., 1° × 1°) have been used as a scale factor in order to obtain more realistic error estimates. This procedure has been applied...
Approximate calculation method for integral of mean square value of nonstationary response
International Nuclear Information System (INIS)
Aoki, Shigeru; Fukano, Azusa
2010-01-01
The response of the structure subjected to nonstationary random vibration such as earthquake excitation is nonstationary random vibration. Calculating method for statistical characteristics of such a response is complicated. Mean square value of the response is usually used to evaluate random response. Integral of mean square value of the response corresponds to total energy of the response. In this paper, a simplified calculation method to obtain integral of mean square value of the response is proposed. As input excitation, nonstationary white noise and nonstationary filtered white noise are used. Integrals of mean square value of the response are calculated for various values of parameters. It is found that the proposed method gives exact value of integral of mean square value of the response.
A class of integrals on squares, cubes and hypercubes
McCartney, Mark
2014-04-01
In this note, a class of integrals on the unit hypercube are considered and series solutions presented. The material is at a level appropriate for use with undergraduates, either as part of a course on multivariable calculus, or as a short independent research project. Suitable exercises for use in these contexts are given.
DEFF Research Database (Denmark)
Nolte, Ingmar; Voev, Valeri
The expected value of sums of squared intraday returns (realized variance) gives rise to a least squares regression which adapts itself to the assumptions of the noise process and allows for a joint inference on integrated volatility (IV), noise moments and price-noise relations. In the iid noise...
Soury, Hamza
2013-07-01
This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.
Stability and square integrability of solutions of nonlinear fourth order differential equations
Directory of Open Access Journals (Sweden)
Moussadek Remili
2016-05-01
Full Text Available The aim of the present paper is to establish a new result, which guarantees the asymptotic stability of zero solution and square integrability of solutions and their derivatives to nonlinear differential equations of fourth order.
Use and Subtleties of Saddlepoint Approximation for Minimum Mean-Square Error Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas; Nuttall, Albert H.; Hansen, Lars Kai
2008-01-01
integral representation. However, the examples also demonstrate that when two saddle points are close or coalesce, then saddle-point approximation based on isolated saddle points is not valid. A saddle-point approximation based on two close or coalesced saddle points is derived and in the examples......, the validity and accuracy of the derivation is demonstrated...
Energy Technology Data Exchange (ETDEWEB)
Nygaard, K
1968-09-15
From the point of view that no mathematical method can ever minimise or alter errors already made in a physical measurement, the classical least squares method has severe limitations which makes it unsuitable for the statistical analysis of many physical measurements. Based on the assumptions that the experimental errors are characteristic for each single experiment and that the errors must be properly estimated rather than minimised, a new method for solving large systems of linear equations is developed. The new method exposes the entire range of possible solutions before the decision is taken which of the possible solutions should be chosen as a representative one. The choice is based on physical considerations which (in two examples, curve fitting and unfolding of a spectrum) are presented in such a form that a computer is able to make the decision, A description of the computation is given. The method described is a tool for removing uncertainties due to conventional mathematical formulations (zero determinant, linear dependence) and which are not inherent in the physical problem as such. The method is therefore especially well fitted for unfolding of spectra.
International Nuclear Information System (INIS)
Nygaard, K.
1968-09-01
From the point of view that no mathematical method can ever minimise or alter errors already made in a physical measurement, the classical least squares method has severe limitations which makes it unsuitable for the statistical analysis of many physical measurements. Based on the assumptions that the experimental errors are characteristic for each single experiment and that the errors must be properly estimated rather than minimised, a new method for solving large systems of linear equations is developed. The new method exposes the entire range of possible solutions before the decision is taken which of the possible solutions should be chosen as a representative one. The choice is based on physical considerations which (in two examples, curve fitting and unfolding of a spectrum) are presented in such a form that a computer is able to make the decision, A description of the computation is given. The method described is a tool for removing uncertainties due to conventional mathematical formulations (zero determinant, linear dependence) and which are not inherent in the physical problem as such. The method is therefore especially well fitted for unfolding of spectra
DEFF Research Database (Denmark)
Jensen, Jesper; Tan, Zheng-Hua
2014-01-01
We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features for noise robust automatic speech recognition (ASR). The method is based on a minimum number of well-established statistical assumptions; no assumptions are made which are inconsistent with others....... The strength of the proposed method is that it allows MMSE estimation of mel-frequency cepstral coefficients (MFCC's), cepstral mean-subtracted MFCC's (CMS-MFCC's), velocity, and acceleration coefficients. Furthermore, the method is easily modified to take into account other compressive non-linearities than...... the logarithmic which is usually used for MFCC computation. The proposed method shows estimation performance which is identical to or better than state-of-the-art methods. It further shows comparable ASR performance, where the advantage of being able to use mel-frequency speech features based on a power non...
Nolte, Ingmar; Voev, Valeri
2009-01-01
The expected value of sums of squared intraday returns (realized variance)gives rise to a least squares regression which adapts itself to the assumptions ofthe noise process and allows for a joint inference on integrated volatility (IV),noise moments and price-noise relations. In the iid noise case we derive theasymptotic variance of the regression parameter estimating the IV, show thatit is consistent and compare its asymptotic efficiency against alternative consistentIV measures. In case of...
THERP and HEART integrated methodology for human error assessment
Castiglia, Francesco; Giardina, Mariarosa; Tomarchio, Elio
2015-11-01
THERP and HEART integrated methodology is proposed to investigate accident scenarios that involve operator errors during high-dose-rate (HDR) treatments. The new approach has been modified on the basis of fuzzy set concept with the aim of prioritizing an exhaustive list of erroneous tasks that can lead to patient radiological overexposures. The results allow for the identification of human errors that are necessary to achieve a better understanding of health hazards in the radiotherapy treatment process, so that it can be properly monitored and appropriately managed.
Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C
2017-08-22
The calibration performance of Partial Least Squares regression (PLS) can be improved by eliminating uninformative variables. For PLS, many variable elimination methods have been developed. One is the Uninformative-Variable Elimination for PLS (UVE-PLS). However, the number of variables retained by UVE-PLS is usually still large. In UVE-PLS, variable elimination is repeated as long as the root mean squared error of cross validation (RMSECV) is decreasing. The set of variables in this first local minimum is retained. In this paper, a modification of UVE-PLS is proposed and investigated, in which UVE is repeated until no further reduction in variables is possible, followed by a search for the global RMSECV minimum. The method is called Global-Minimum Error Uninformative-Variable Elimination for PLS, denoted as GME-UVE-PLS or simply GME-UVE. After each iteration, the predictive ability of the PLS model, built with the remaining variable set, is assessed by RMSECV. The variable set with the global RMSECV minimum is then finally selected. The goal is to obtain smaller sets of variables with similar or improved predictability than those from the classical UVE-PLS method. The performance of the GME-UVE-PLS method is investigated using four data sets, i.e. a simulated set, NIR and NMR spectra, and a theoretical molecular descriptors set, resulting in twelve profile-response (X-y) calibrations. The selective and predictive performances of the models resulting from GME-UVE-PLS are statistically compared to those from UVE-PLS and 1-step UVE, one-sided paired t-tests. The results demonstrate that variable reduction with the proposed GME-UVE-PLS method, usually eliminates significantly more variables than the classical UVE-PLS, while the predictive abilities of the resulting models are better. With GME-UVE-PLS, a lower number of uninformative variables, without a chemical meaning for the response, may be retained than with UVE-PLS. The selectivity of the classical UVE method
Korkmaz, Erdal
2017-01-01
In this paper, we give sufficient conditions for the boundedness, uniform asymptotic stability and square integrability of the solutions to a certain fourth order non-autonomous differential equations with delay by using Lyapunov's second method. The results obtained essentially improve, include and complement the results in the literature.
Directory of Open Access Journals (Sweden)
Erdal Korkmaz
2017-06-01
Full Text Available Abstract In this paper, we give sufficient conditions for the boundedness, uniform asymptotic stability and square integrability of the solutions to a certain fourth order non-autonomous differential equations with delay by using Lyapunov’s second method. The results obtained essentially improve, include and complement the results in the literature.
Nair, S. P.; Righetti, R.
2015-05-01
Recent elastography techniques focus on imaging information on properties of materials which can be modeled as viscoelastic or poroelastic. These techniques often require the fitting of temporal strain data, acquired from either a creep or stress-relaxation experiment to a mathematical model using least square error (LSE) parameter estimation. It is known that the strain versus time relationships for tissues undergoing creep compression have a non-linear relationship. In non-linear cases, devising a measure of estimate reliability can be challenging. In this article, we have developed and tested a method to provide non linear LSE parameter estimate reliability: which we called Resimulation of Noise (RoN). RoN provides a measure of reliability by estimating the spread of parameter estimates from a single experiment realization. We have tested RoN specifically for the case of axial strain time constant parameter estimation in poroelastic media. Our tests show that the RoN estimated precision has a linear relationship to the actual precision of the LSE estimator. We have also compared results from the RoN derived measure of reliability against a commonly used reliability measure: the correlation coefficient (CorrCoeff). Our results show that CorrCoeff is a poor measure of estimate reliability for non-linear LSE parameter estimation. While the RoN is specifically tested only for axial strain time constant imaging, a general algorithm is provided for use in all LSE parameter estimation.
International Nuclear Information System (INIS)
Pollock, D.; Kim, K.; Gunst, R.; Schucany, W.
1993-05-01
Linear estimation of cold magnetic field quality based on warm multipole measurements is being considered as a quality control method for SSC production magnet acceptance. To investigate prediction uncertainties associated with such an approach, axial-scan (Z-scan) magnetic measurements from SSC Prototype Collider Dipole Magnets (CDM's) have been studied. This paper presents a preliminary evaluation of the explanatory ability of warm measurement multipole variation on the prediction of cold magnet multipoles. Two linear estimation methods are presented: least-squares regression, which uses the assumption of fixed independent variable (xi) observations, and the measurement error model, which includes measurement error in the xi's. The influence of warm multipole measurement errors on predicted cold magnet multipole averages is considered. MSD QA is studying warm/cold correlation to answer several magnet quality control questions. How well do warm measurements predict cold (2kA) multipoles? Does sampling error significantly influence estimates of the linear coefficients (slope, intercept and residual standard error)? Is estimation error for the predicted cold magnet average small compared to typical variation along the Z-Axis? What fraction of the multipole RMS tolerance is accounted for by individual magnet prediction uncertainty?
Ronan, R. S.; Mickey, D. L.; Orrall, F. Q.
1987-01-01
The results of two methods for deriving photospheric vector magnetic fields from the Zeeman effect, as observed in the Fe I line at 6302.5 A at high spectral resolution (45 mA), are compared. The first method does not take magnetooptical effects into account, but determines the vector magnetic field from the integral properties of the Stokes profiles. The second method is an iterative least-squares fitting technique which fits the observed Stokes profiles to the profiles predicted by the Unno-Rachkovsky solution to the radiative transfer equation. For sunspot fields above about 1500 gauss, the two methods are found to agree in derived azimuthal and inclination angles to within about + or - 20 deg.
Zhang, Yunju; Chen, Zhongyi; Guo, Ming; Lin, Shunsheng; Yan, Yinyang
2018-01-01
With the large capacity of the power system, the development trend of the large unit and the high voltage, the scheduling operation is becoming more frequent and complicated, and the probability of operation error increases. This paper aims at the problem of the lack of anti-error function, single scheduling function and low working efficiency for technical support system in regional regulation and integration, the integrated construction of the error prevention of the integrated architecture of the system of dispatching anti - error of dispatching anti - error of power network based on cloud computing has been proposed. Integrated system of error prevention of Energy Management System, EMS, and Operation Management System, OMS have been constructed either. The system architecture has good scalability and adaptability, which can improve the computational efficiency, reduce the cost of system operation and maintenance, enhance the ability of regional regulation and anti-error checking with broad development prospects.
DEFF Research Database (Denmark)
Rahimi, Maryam; Nielsen, Jesper Ødum; Pedersen, Troels
2014-01-01
A comparison in data achievement between two well-known algorithms with simulated and real measured data is presented. The algorithms maximise the data rate in cooperative base stations (BS) multiple-input-single-output scenario. Weighted sum-minimum mean square error algorithm could be used...... in multiple-input-multiple-output scenarios, but it has lower performance than virtual signal-to-interference plus noise ratio algorithm in theory and practice. A real measurement environment consisting of two BS and two users have been studied to evaluate the simulation results....
Mao, Jiening; Gao, Zhen; Wu, Yongpeng; Alouini, Mohamed-Slim
2018-01-01
Hybrid precoding design is challenging for millimeter-wave (mmWave) massive MIMO. Most prior hybrid precoding schemes are designed to maximize the sum spectral efficiency (SSE), while seldom investigate the bit-error-rate (BER). Therefore, this letter designs an over-sampling codebook (OSC)-based hybrid minimum sum-mean-square-error (min-SMSE) precoding to optimize the BER. Specifically, given the effective baseband channel consisting of the real channel and analog precoding, we first design the digital precoder/combiner based on min-SMSE criterion to optimize the BER. To further reduce the SMSE between the transmit and receive signals, we propose an OSC-based joint analog precoder/combiner (JAPC) design. Simulation results show that the proposed scheme can achieve the better performance than its conventional counterparts.
Mao, Jiening
2018-05-23
Abstract: Hybrid precoding design is challenging for millimeter-wave (mmWave) massive MIMO. Most prior hybrid precoding schemes are designed to maximize the sum spectral efficiency (SSE), while seldom investigate the bit-error-rate (BER). Therefore, this letter designs an over-sampling codebook (OSC)-based hybrid minimum sum-mean-square-error (min-SMSE) precoding to optimize the BER. Specifically, given the effective baseband channel consisting of the real channel and analog precoding, we first design the digital precoder/combiner based on min-SMSE criterion to optimize the BER. To further reduce the SMSE between the transmit and receive signals, we propose an OSC-based joint analog precoder/combiner (JAPC) design. Simulation results show that the proposed scheme can achieve the better performance than its conventional counterparts.
Behnabian, Behzad; Mashhadi Hossainali, Masoud; Malekzadeh, Ahad
2018-02-01
The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the
Kiani, M A; Sim, K S; Nia, M E; Tso, C P
2015-05-01
A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.
Yee, Ng Kin; Lam, Toh Tin
2008-01-01
This paper reports on students' errors in performing integration of rational functions, a topic of calculus in the pre-university mathematics classrooms. Generally the errors could be classified as those due to the students' weak algebraic concepts and their lack of understanding of the concept of integration. With the students' inability to link…
Energy Technology Data Exchange (ETDEWEB)
Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov
2016-02-25
Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
Integral transform solution of natural convection in a square cavity with volumetric heat generation
Directory of Open Access Journals (Sweden)
C. An
2013-12-01
Full Text Available The generalized integral transform technique (GITT is employed to obtain a hybrid numerical-analytical solution of natural convection in a cavity with volumetric heat generation. The hybrid nature of this approach allows for the establishment of benchmark results in the solution of non-linear partial differential equation systems, including the coupled set of heat and fluid flow equations that govern the steady natural convection problem under consideration. Through performing the GITT, the resulting transformed ODE system is then numerically solved by making use of the subroutine DBVPFD from the IMSL Library. Therefore, numerical results under user prescribed accuracy are obtained for different values of Rayleigh numbers, and the convergence behavior of the proposed eigenfunction expansions is illustrated. Critical comparisons against solutions produced by ANSYS CFX 12.0 are then conducted, which demonstrate excellent agreement. Several sets of reference results for natural convection with volumetric heat generation in a bi-dimensional square cavity are also provided for future verification of numerical results obtained by other researchers.
International Nuclear Information System (INIS)
Hao, Ming; Wang, Yanli; Bryant, Stephen H.
2016-01-01
Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
Ishkhanyan, Tigran A.; Krainov, Vladimir P.; Ishkhanyan, Artur M.
2018-05-01
We present a conditionally integrable potential, belonging to the bi-confluent Heun class, for which the Schrödinger equation is solved in terms of the confluent hypergeometric functions. The potential involves an attractive inverse square root term x-1/2 with arbitrary strength and a repulsive centrifugal barrier core x-2 with the strength fixed to a constant. This is a potential well defined on the half-axis. Each of the fundamental solutions composing the general solution of the Schrödinger equation is written as an irreducible linear combination, with non-constant coefficients, of two confluent hypergeometric functions. We present the explicit solution in terms of the non-integer order Hermite functions of scaled and shifted argument and discuss the bound states supported by the potential. We derive the exact equation for the energy spectrum and approximate that by a highly accurate transcendental equation involving trigonometric functions. Finally, we construct an accurate approximation for the bound-state energy levels.
Directory of Open Access Journals (Sweden)
M. Omidalizarandi
2013-09-01
Full Text Available Sensor fusion is to combine different sensor data from different sources in order to make a more accurate model. In this research, different sensors (Optical Speed Sensor, Bosch Sensor, Odometer, XSENS, Silicon and GPS receiver have been utilized to obtain different kinds of datasets to implement the multi-sensor system and comparing the accuracy of the each sensor with other sensors. The scope of this research is to estimate the current position and orientation of the Van. The Van's position can also be estimated by integrating its velocity and direction over time. To make these components work, it needs an interface that can bridge each other in a data acquisition module. The interface of this research has been developed based on using Labview software environment. Data have been transferred to PC via A/D convertor (LabJack and make a connection to PC. In order to synchronize all the sensors, calibration parameters of each sensor is determined in preparatory step. Each sensor delivers result in a sensor specific coordinate system that contains different location on the object, different definition of coordinate axes and different dimensions and units. Different test scenarios (Straight line approach and Circle approach with different algorithms (Kalman Filter, Least square Adjustment have been examined and the results of the different approaches are compared together.
Development of an integrated system for estimating human error probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, J.L.; Hahn, H.A.; Morzinski, J.A.
1998-12-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). This project had as its main objective the development of a Human Reliability Analysis (HRA), knowledge-based expert system that would provide probabilistic estimates for potential human errors within various risk assessments, safety analysis reports, and hazard assessments. HRA identifies where human errors are most likely, estimates the error rate for individual tasks, and highlights the most beneficial areas for system improvements. This project accomplished three major tasks. First, several prominent HRA techniques and associated databases were collected and translated into an electronic format. Next, the project started a knowledge engineering phase where the expertise, i.e., the procedural rules and data, were extracted from those techniques and compiled into various modules. Finally, these modules, rules, and data were combined into a nearly complete HRA expert system.
Interaction and Representational Integration: Evidence from Speech Errors
Goldrick, Matthew; Baker, H. Ross; Murphy, Amanda; Baese-Berk, Melissa
2011-01-01
We examine the mechanisms that support interaction between lexical, phonological and phonetic processes during language production. Studies of the phonetics of speech errors have provided evidence that partially activated lexical and phonological representations influence phonetic processing. We examine how these interactive effects are modulated…
Interaction and representational integration: Evidence from speech errors
Goldrick, Matthew; Baker, H. Ross; Murphy, Amanda; Baese-Berk, Melissa
2011-01-01
We examine the mechanisms that support interaction between lexical, phonological and phonetic processes during language production. Studies of the phonetics of speech errors have provided evidence that partially activated lexical and phonological representations influence phonetic processing. We examine how these interactive effects are modulated by lexical frequency. Previous research has demonstrated that during lexical access, the processing of high frequency words is facilitated; in contr...
Duong, Minh V; Nguyen, Hieu T; Mai, Tam V-T; Huynh, Lam K
2018-01-03
Master equation/Rice-Ramsperger-Kassel-Marcus (ME/RRKM) has shown to be a powerful framework for modeling kinetic and dynamic behaviors of a complex gas-phase chemical system on a complicated multiple-species and multiple-channel potential energy surface (PES) for a wide range of temperatures and pressures. Derived from the ME time-resolved species profiles, the macroscopic or phenomenological rate coefficients are essential for many reaction engineering applications including those in combustion and atmospheric chemistry. Therefore, in this study, a least-squares-based approach named Global Minimum Profile Error (GMPE) was proposed and implemented in the MultiSpecies-MultiChannel (MSMC) code (Int. J. Chem. Kinet., 2015, 47, 564) to extract macroscopic rate coefficients for such a complicated system. The capability and limitations of the new approach were discussed in several well-defined test cases.
Directory of Open Access Journals (Sweden)
Lie-Liang Yang
2008-01-01
Full Text Available In wireless communications, multicarrier direct-sequence code-division multiple access (MC DS-CDMA constitutes one of the highly flexible multiple access schemes. MC DS-CDMA employs a high number of degrees-of-freedom, which are beneficial to design and reconfiguration for communications in dynamic communications environments, such as in the cognitive radios. In this contribution, we consider the multiuser detection (MUD in MC DS-CDMA, which motivates lowcomplexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments. Specifically, a range of low-complexity MUDs are derived based on the zero-forcing (ZF, minimum mean-square error (MMSE, and interference cancellation (IC principles. The bit-error rate (BER performance of the MC DS-CDMA aided by the proposed MUDs is investigated by simulation approaches. Our study shows that, in addition to the advantages provided by a general ZF, MMSE, or IC-assisted MUD, the proposed MUD schemes can be implemented using modular structures, where most modules are independent of each other. Due to the independent modular structure, in the proposed MUDs one module may be reconfigured without yielding impact on the others. Therefore, the MC DS-CDMA, in conjunction with the proposed MUDs, constitutes one of the promising multiple access schemes for communications in the dynamic communications environments such as in the cognitive radios.
Directory of Open Access Journals (Sweden)
Wang Li-Chun
2008-01-01
Full Text Available Abstract In wireless communications, multicarrier direct-sequence code-division multiple access (MC DS-CDMA constitutes one of the highly flexible multiple access schemes. MC DS-CDMA employs a high number of degrees-of-freedom, which are beneficial to design and reconfiguration for communications in dynamic communications environments, such as in the cognitive radios. In this contribution, we consider the multiuser detection (MUD in MC DS-CDMA, which motivates lowcomplexity, high flexibility, and robustness so that the MUD schemes are suitable for deployment in dynamic communications environments. Specifically, a range of low-complexity MUDs are derived based on the zero-forcing (ZF, minimum mean-square error (MMSE, and interference cancellation (IC principles. The bit-error rate (BER performance of the MC DS-CDMA aided by the proposed MUDs is investigated by simulation approaches. Our study shows that, in addition to the advantages provided by a general ZF, MMSE, or IC-assisted MUD, the proposed MUD schemes can be implemented using modular structures, where most modules are independent of each other. Due to the independent modular structure, in the proposed MUDs one module may be reconfigured without yielding impact on the others. Therefore, the MC DS-CDMA, in conjunction with the proposed MUDs, constitutes one of the promising multiple access schemes for communications in the dynamic communications environments such as in the cognitive radios.
Square well model and the functional form for the resonance integral
International Nuclear Information System (INIS)
Raina, V.; Srivastava, P.K.; Sane, K.V.
1975-01-01
It is shown that the relation β = eta(Z 1 Z 2 )/sup 1/2/ exp/broken bracket/ -X(Z 1 + Z 2 )R/broken bracket//R can be derived by assuming that the effective potential in π-electron systems can be approximated by a three-dimensional square well form. (U.S.)
An integrity measure to benchmark quantum error correcting memories
Xu, Xiaosi; de Beaudrap, Niel; O'Gorman, Joe; Benjamin, Simon C.
2018-02-01
Rapidly developing experiments across multiple platforms now aim to realise small quantum codes, and so demonstrate a memory within which a logical qubit can be protected from noise. There is a need to benchmark the achievements in these diverse systems, and to compare the inherent power of the codes they rely upon. We describe a recently introduced performance measure called integrity, which relates to the probability that an ideal agent will successfully ‘guess’ the state of a logical qubit after a period of storage in the memory. Integrity is straightforward to evaluate experimentally without state tomography and it can be related to various established metrics such as the logical fidelity and the pseudo-threshold. We offer a set of experimental milestones that are steps towards demonstrating unconditionally superior encoded memories. Using intensive numerical simulations we compare memories based on the five-qubit code, the seven-qubit Steane code, and a nine-qubit code which is the smallest instance of a surface code; we assess both the simple and fault-tolerant implementations of each. While the ‘best’ code upon which to base a memory does vary according to the nature and severity of the noise, nevertheless certain trends emerge.
Integration of error tolerance into the design of control rooms of nuclear power plants
International Nuclear Information System (INIS)
Sepanloo, Kamran
1998-08-01
Many complex technological systems' failures have been attributed to human errors. Today, based on extensive research on the role of human element in technological systems it is known that human error can not totally be eliminated in modern, flexible, or changing work environments by conventional style design strategies(e.g. defence in depth), or better instructions nor should they be. Instead, the operators' ability to explore degrees of freedom should be supported and means for recovering from the effects of errors should be included. This calls for innovative error tolerant design of technological systems. Integration of error tolerant concept into the design, construction, startup, and operation of nuclear power plants provides an effective means of reducing human error occurrence during all stages of life of it and therefore leads to considerable enhancement of plant's safety
He, Yan-Lin; Xu, Yuan; Geng, Zhi-Qiang; Zhu, Qun-Xiong
2016-03-01
In this paper, a hybrid robust model based on an improved functional link neural network integrating with partial least square (IFLNN-PLS) is proposed. Firstly, an improved functional link neural network with small norm of expanded weights and high input-output correlation (SNEWHIOC-FLNN) was proposed for enhancing the generalization performance of FLNN. Unlike the traditional FLNN, the expanded variables of the original inputs are not directly used as the inputs in the proposed SNEWHIOC-FLNN model. The original inputs are attached to some small norm of expanded weights. As a result, the correlation coefficient between some of the expanded variables and the outputs is enhanced. The larger the correlation coefficient is, the more relevant the expanded variables tend to be. In the end, the expanded variables with larger correlation coefficient are selected as the inputs to improve the performance of the traditional FLNN. In order to test the proposed SNEWHIOC-FLNN model, three UCI (University of California, Irvine) regression datasets named Housing, Concrete Compressive Strength (CCS), and Yacht Hydro Dynamics (YHD) are selected. Then a hybrid model based on the improved FLNN integrating with partial least square (IFLNN-PLS) was built. In IFLNN-PLS model, the connection weights are calculated using the partial least square method but not the error back propagation algorithm. Lastly, IFLNN-PLS was developed as an intelligent measurement model for accurately predicting the key variables in the Purified Terephthalic Acid (PTA) process and the High Density Polyethylene (HDPE) process. Simulation results illustrated that the IFLNN-PLS could significant improve the prediction performance. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Calvo, Roque; D’Amato, Roberto; Gómez, Emilio; Domingo, Rosario
2016-01-01
The development of an error compensation model for coordinate measuring machines (CMMs) and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included. PMID:27690052
Directory of Open Access Journals (Sweden)
Roque Calvo
2016-09-01
Full Text Available The development of an error compensation model for coordinate measuring machines (CMMs and its integration into feature measurement is presented. CMMs are widespread and dependable instruments in industry and laboratories for dimensional measurement. From the tip probe sensor to the machine display, there is a complex transformation of probed point coordinates through the geometrical feature model that makes the assessment of accuracy and uncertainty measurement results difficult. Therefore, error compensation is not standardized, conversely to other simpler instruments. Detailed coordinate error compensation models are generally based on CMM as a rigid-body and it requires a detailed mapping of the CMM’s behavior. In this paper a new model type of error compensation is proposed. It evaluates the error from the vectorial composition of length error by axis and its integration into the geometrical measurement model. The non-explained variability by the model is incorporated into the uncertainty budget. Model parameters are analyzed and linked to the geometrical errors and uncertainty of CMM response. Next, the outstanding measurement models of flatness, angle, and roundness are developed. The proposed models are useful for measurement improvement with easy integration into CMM signal processing, in particular in industrial environments where built-in solutions are sought. A battery of implementation tests are presented in Part II, where the experimental endorsement of the model is included.
Sinha, Mrinal
2016-05-23
Imaging seismic data with an erroneous migration velocity can lead to defocused migration images. To mitigate this problem, we first choose a reference reflector whose topography is well-known from the well logs, for example. Reflections from this reference layer are correlated with the traces associated with reflections from deeper interfaces to get crosscorrelograms. Interferometric least-squares migration (ILSM) is then used to get the migration image that maximizes the crosscorrelation between the observed and the predicted crosscorrelograms. Deeper reference reflectors are used to image deeper parts of the subsurface with a greater accuracy. Results on synthetic and field data show that defocusing caused by velocity errors is largely suppressed by ILSM. We have also determined that ILSM can be used for 4D surveys in which environmental conditions and acquisition parameters are significantly different from one survey to the next. The limitations of ILSM are that it requires prior knowledge of a reference reflector in the subsurface and the velocity model below the reference reflector should be accurate.
Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans
International Nuclear Information System (INIS)
Siebers, Jeffrey V.; Keall, Paul J.; Wu Qiuwen; Williamson, Jeffrey F.; Schmidt-Ullrich, Rupert K.
2005-01-01
Purpose: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. Methods and Materials: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errors of σ = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with Σ = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for σ = Σ = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D 98 ), clinical target volume (CTV) D 90 , nodes D 90 , cord D 2 , and parotid D 50 and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. Results: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error σ exceeded 3 mm. Simulated systematic setup errors with Σ = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a Σ = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error
Study on Network Error Analysis and Locating based on Integrated Information Decision System
Yang, F.; Dong, Z. H.
2017-10-01
Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.
Therapeutic self-disclosure in integrative psychotherapy: When is this a clinical error?
Ziv-Beiman, Sharon; Shahar, Golan
2016-09-01
Ascending to prominence in virtually all forms of psychotherapy, therapist self-disclosure (TSD) has recently been identified as a primarily integrative intervention (Ziv-Beiman, 2013). In the present article, we discuss various instances in which using TSD in integrative psychotherapy might constitute a clinical error. First, we briefly review extant theory and empirical research on TSD, followed by our preferred version of integrative psychotherapy (i.e., a version of Wachtel's Cyclical Psychodynamics [Wachtel, 1977, 1997, 2014]), which we title cognitive existential psychodynamics. Next, we provide and discuss three examples in which implementing TSD constitutes a clinical error. In essence, we submit that using TSD constitutes an error when patients, constrained by their representational structures (object relations), experience the subjectivity of the other as impinging, and thus propels them to "react" instead of "emerge." (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Fractional Order Differentiation by Integration and Error Analysis in Noisy Environment
Liu, Dayan; Gibaru, Olivier; Perruquetti, Wilfrid; Laleg-Kirati, Taous-Meriem
2015-01-01
respectively. Exact and simple formulae for these differentiators are given by integral expressions. Hence, they can be used for both continuous-time and discrete-time models in on-line or off-line applications. Secondly, some error bounds are provided
Kuzishchin, V. F.; Merzlikina, E. I.; Van Va, Hoang
2017-11-01
The problem of PID and PI-algorithms tuning by means of the approximation by the least square method of the frequency response of a linear algorithm to the sub-optimal algorithm is considered. The advantage of the method is that the parameter values are obtained through one cycle of calculation. Recommendations how to choose the parameters of the least square method taking into consideration the plant dynamics are given. The parameters mentioned are the time constant of the filter, the approximation frequency range and the correction coefficient for the time delay parameter. The problem is considered for integrating plants for some practical cases (the level control system in a boiler drum). The transfer function of the suboptimal algorithm is determined relating to the disturbance that acts in the point of the control impact input, it is typical for thermal plants. In the recommendations it is taken into consideration that the overregulation for the transient process when the setpoint is changed is also limited. In order to compare the results the systems under consideration are also calculated by the classical method with the limited frequency oscillation index. The results given in the paper can be used by specialists dealing with tuning systems with the integrating plants.
International Nuclear Information System (INIS)
Halepoto, I.A.; Uqaili, M.A.
2014-01-01
Nowadays, due to power crisis, electricity demand forecasting is deemed an important area for socioeconomic development and proper anticipation of the load forecasting is considered essential step towards efficient power system operation, scheduling and planning. In this paper, we present STLF (Short Term Load Forecasting) using multiple regression techniques (i.e. linear, multiple linear, quadratic and exponential) by considering hour by hour load model based on specific targeted day approach with temperature variant parameter. The proposed work forecasts the future load demand correlation with linear and non-linear parameters (i.e. considering temperature in our case) through different regression approaches. The overall load forecasting error is 2.98% which is very much acceptable. From proposed regression techniques, Quadratic Regression technique performs better compared to than other techniques because it can optimally fit broad range of functions and data sets. The work proposed in this paper, will pave a path to effectively forecast the specific day load with multiple variance factors in a way that optimal accuracy can be maintained. (author)
Integrating NOE and RDC using sum-of-squares relaxation for protein structure determination.
Khoo, Y; Singer, A; Cowburn, D
2017-07-01
We revisit the problem of protein structure determination from geometrical restraints from NMR, using convex optimization. It is well-known that the NP-hard distance geometry problem of determining atomic positions from pairwise distance restraints can be relaxed into a convex semidefinite program (SDP). However, often the NOE distance restraints are too imprecise and sparse for accurate structure determination. Residual dipolar coupling (RDC) measurements provide additional geometric information on the angles between atom-pair directions and axes of the principal-axis-frame. The optimization problem involving RDC is highly non-convex and requires a good initialization even within the simulated annealing framework. In this paper, we model the protein backbone as an articulated structure composed of rigid units. Determining the rotation of each rigid unit gives the full protein structure. We propose solving the non-convex optimization problems using the sum-of-squares (SOS) hierarchy, a hierarchy of convex relaxations with increasing complexity and approximation power. Unlike classical global optimization approaches, SOS optimization returns a certificate of optimality if the global optimum is found. Based on the SOS method, we proposed two algorithms-RDC-SOS and RDC-NOE-SOS, that have polynomial time complexity in the number of amino-acid residues and run efficiently on a standard desktop. In many instances, the proposed methods exactly recover the solution to the original non-convex optimization problem. To the best of our knowledge this is the first time SOS relaxation is introduced to solve non-convex optimization problems in structural biology. We further introduce a statistical tool, the Cramér-Rao bound (CRB), to provide an information theoretic bound on the highest resolution one can hope to achieve when determining protein structure from noisy measurements using any unbiased estimator. Our simulation results show that when the RDC measurements are
Tyo, J Scott; LaCasse, Charles F; Ratliff, Bradley M
2009-10-15
Microgrid polarimeters operate by integrating a focal plane array with an array of micropolarizers. The Stokes parameters are estimated by comparing polarization measurements from pixels in a neighborhood around the point of interest. The main drawback is that the measurements used to estimate the Stokes vector are made at different locations, leading to a false polarization signature owing to instantaneous field-of-view (IFOV) errors. We demonstrate for the first time, to our knowledge, that spatially band limited polarization images can be ideally reconstructed with no IFOV error by using a linear system framework.
Errors prevention in manufacturing process through integration of Poka Yoke and TRIZ
Helmi, Syed Ahmad; Nordin, Nur Nashwa; Hisjam, Muhammad
2017-11-01
Integration of Poka Yoke and TRIZ is a method of solving problems by using a different approach. Poka Yoke is a trial and error method while TRIZ is using a systematic approach. The main purpose of this technique is to get rid of product defects by preventing or correcting errors as soon as possible. Blame the workers for their mistakes is not the best way, but the work process should be reviewed so that every workers behavior or movement may not cause errors. This study is to demonstrate the importance of using both of these methods in which everyone in the industry needs to improve quality, increase productivity and at the same time reducing production cost.
A comparison between different error modeling of MEMS applied to GPS/INS integrated systems.
Quinchia, Alex G; Falco, Gianluca; Falletti, Emanuela; Dovis, Fabio; Ferrer, Carles
2013-07-24
Advances in the development of micro-electromechanical systems (MEMS) have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS) and the inertial navigation system (INS) integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs), stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV) and the power spectral density (PSD) techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR) filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade) presents error sources with short-term (high-frequency) and long-term (low-frequency) components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF) of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways.
A Comparison between Different Error Modeling of MEMS Applied to GPS/INS Integrated Systems
Directory of Open Access Journals (Sweden)
Fabio Dovis
2013-07-01
Full Text Available Advances in the development of micro-electromechanical systems (MEMS have made possible the fabrication of cheap and small dimension accelerometers and gyroscopes, which are being used in many applications where the global positioning system (GPS and the inertial navigation system (INS integration is carried out, i.e., identifying track defects, terrestrial and pedestrian navigation, unmanned aerial vehicles (UAVs, stabilization of many platforms, etc. Although these MEMS sensors are low-cost, they present different errors, which degrade the accuracy of the navigation systems in a short period of time. Therefore, a suitable modeling of these errors is necessary in order to minimize them and, consequently, improve the system performance. In this work, the most used techniques currently to analyze the stochastic errors that affect these sensors are shown and compared: we examine in detail the autocorrelation, the Allan variance (AV and the power spectral density (PSD techniques. Subsequently, an analysis and modeling of the inertial sensors, which combines autoregressive (AR filters and wavelet de-noising, is also achieved. Since a low-cost INS (MEMS grade presents error sources with short-term (high-frequency and long-term (low-frequency components, we introduce a method that compensates for these error terms by doing a complete analysis of Allan variance, wavelet de-nosing and the selection of the level of decomposition for a suitable combination between these techniques. Eventually, in order to assess the stochastic models obtained with these techniques, the Extended Kalman Filter (EKF of a loosely-coupled GPS/INS integration strategy is augmented with different states. Results show a comparison between the proposed method and the traditional sensor error models under GPS signal blockages using real data collected in urban roadways.
Observability analysis of a MEMS INS/GPS integration system with gyroscope G-sensitivity errors.
Fan, Chen; Hu, Xiaoping; He, Xiaofeng; Tang, Kanghua; Luo, Bing
2014-08-28
Gyroscopes based on micro-electromechanical system (MEMS) technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS) and the Global Positioning System (GPS). The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously.
Observability Analysis of a MEMS INS/GPS Integration System with Gyroscope G-Sensitivity Errors
Directory of Open Access Journals (Sweden)
Chen Fan
2014-08-01
Full Text Available Gyroscopes based on micro-electromechanical system (MEMS technology suffer in high-dynamic applications due to obvious g-sensitivity errors. These errors can induce large biases in the gyroscope, which can directly affect the accuracy of attitude estimation in the integration of the inertial navigation system (INS and the Global Positioning System (GPS. The observability determines the existence of solutions for compensating them. In this paper, we investigate the observability of the INS/GPS system with consideration of the g-sensitivity errors. In terms of two types of g-sensitivity coefficients matrix, we add them as estimated states to the Kalman filter and analyze the observability of three or nine elements of the coefficient matrix respectively. A global observable condition of the system is presented and validated. Experimental results indicate that all the estimated states, which include position, velocity, attitude, gyro and accelerometer bias, and g-sensitivity coefficients, could be made observable by maneuvering based on the conditions. Compared with the integration system without compensation for the g-sensitivity errors, the attitude accuracy is raised obviously.
Energy Technology Data Exchange (ETDEWEB)
Olama, Mohammed M [ORNL; Matalgah, Mustafa M [ORNL; Bobrek, Miljko [ORNL
2015-01-01
Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subject to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).
Directory of Open Access Journals (Sweden)
Ghisalberti Giorgio
2010-12-01
Full Text Available Numerous biomolecular data are available, but they are scattered in many databases and only some of them are curated by experts. Most available data are computationally derived and include errors and inconsistencies. Effective use of available data in order to derive new knowledge hence requires data integration and quality improvement. Many approaches for data integration have been proposed. Data warehousing seams to be the most adequate when comprehensive analysis of integrated data is required. This makes it the most suitable also to implement comprehensive quality controls on integrated data. We previously developed GFINDer (http://www.bioinformatics.polimi.it/GFINDer/, a web system that supports scientists in effectively using available information. It allows comprehensive statistical analysis and mining of functional and phenotypic annotations of gene lists, such as those identified by high-throughput biomolecular experiments. GFINDer backend is composed of a multi-organism genomic and proteomic data warehouse (GPDW. Within the GPDW, several controlled terminologies and ontologies, which describe gene and gene product related biomolecular processes, functions and phenotypes, are imported and integrated, together with their associations with genes and proteins of several organisms. In order to ease maintaining updated the GPDW and to ensure the best possible quality of data integrated in subsequent updating of the data warehouse, we developed several automatic procedures. Within them, we implemented numerous data quality control techniques to test the integrated data for a variety of possible errors and inconsistencies. Among other features, the implemented controls check data structure and completeness, ontological data consistency, ID format and evolution, unexpected data quantification values, and consistency of data from single and multiple sources. We use the implemented controls to analyze the quality of data available from several
Fractional Order Differentiation by Integration and Error Analysis in Noisy Environment
Liu, Dayan
2015-03-31
The integer order differentiation by integration method based on the Jacobi orthogonal polynomials for noisy signals was originally introduced by Mboup, Join and Fliess. We propose to extend this method from the integer order to the fractional order to estimate the fractional order derivatives of noisy signals. Firstly, two fractional order differentiators are deduced from the Jacobi orthogonal polynomial filter, using the Riemann-Liouville and the Caputo fractional order derivative definitions respectively. Exact and simple formulae for these differentiators are given by integral expressions. Hence, they can be used for both continuous-time and discrete-time models in on-line or off-line applications. Secondly, some error bounds are provided for the corresponding estimation errors. These bounds allow to study the design parameters\\' influence. The noise error contribution due to a large class of stochastic processes is studied in discrete case. The latter shows that the differentiator based on the Caputo fractional order derivative can cope with a class of noises, whose mean value and variance functions are polynomial time-varying. Thanks to the design parameters analysis, the proposed fractional order differentiators are significantly improved by admitting a time-delay. Thirdly, in order to reduce the calculation time for on-line applications, a recursive algorithm is proposed. Finally, the proposed differentiator based on the Riemann-Liouville fractional order derivative is used to estimate the state of a fractional order system and numerical simulations illustrate the accuracy and the robustness with respect to corrupting noises.
IMPACT OF TRADE OPENNESS ON OUTPUT GROWTH: CO INTEGRATION AND ERROR CORRECTION MODEL APPROACH
Directory of Open Access Journals (Sweden)
Asma Arif
2012-01-01
Full Text Available This study analyzed the long run relationship between trade openness and output growth for Pakistan using annual time series data for 1972-2010. This study follows the Engle and Granger co integration analysis and error correction approach to analyze the long run relationship between the two variables. The Error Correction Term (ECT for output growth and trade openness is significant at 5% level of significance and indicates a positive long run relation between the variables. This study has also analyzed the causality between trade openness and output growth by using granger causality test. The results of granger causality show that there is a bi-directional significant relationship between trade openness and economic growth.
Karamat, Tashfeen B; Atia, Mohamed M; Noureldin, Aboelmagd
2015-09-22
Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers' measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer's errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories' data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance.
Modeling the cosmic-ray-induced soft-error rate in integrated circuits: An overview
International Nuclear Information System (INIS)
Srinivasan, G.R.
1996-01-01
This paper is an overview of the concepts and methodologies used to predict soft-error rates (SER) due to cosmic and high-energy particle radiation in integrated circuit chips. The paper emphasizes the need for the SER simulation using the actual chip circuit model which includes device, process, and technology parameters as opposed to using either the discrete device simulation or generic circuit simulation that is commonly employed in SER modeling. Concepts such as funneling, event-by-event simulation, nuclear history files, critical charge, and charge sharing are examined. Also discussed are the relative importance of elastic and inelastic nuclear collisions, rare event statistics, and device vs. circuit simulations. The semi-empirical methodologies used in the aerospace community to arrive at SERs [also referred to as single-event upset (SEU) rates] in integrated circuit chips are reviewed. This paper is one of four in this special issue relating to SER modeling. Together, they provide a comprehensive account of this modeling effort, which has resulted in a unique modeling tool called the Soft-Error Monte Carlo Model, or SEMM
Liu, Ying; Hu, Huijing; Jones, Jeffery A; Guo, Zhiqiang; Li, Weifeng; Chen, Xi; Liu, Peng; Liu, Hanjun
2015-08-01
Speakers rapidly adjust their ongoing vocal productions to compensate for errors they hear in their auditory feedback. It is currently unclear what role attention plays in these vocal compensations. This event-related potential (ERP) study examined the influence of selective and divided attention on the vocal and cortical responses to pitch errors heard in auditory feedback regarding ongoing vocalisations. During the production of a sustained vowel, participants briefly heard their vocal pitch shifted up two semitones while they actively attended to auditory or visual events (selective attention), or both auditory and visual events (divided attention), or were not told to attend to either modality (control condition). The behavioral results showed that attending to the pitch perturbations elicited larger vocal compensations than attending to the visual stimuli. Moreover, ERPs were likewise sensitive to the attentional manipulations: P2 responses to pitch perturbations were larger when participants attended to the auditory stimuli compared to when they attended to the visual stimuli, and compared to when they were not explicitly told to attend to either the visual or auditory stimuli. By contrast, dividing attention between the auditory and visual modalities caused suppressed P2 responses relative to all the other conditions and caused enhanced N1 responses relative to the control condition. These findings provide strong evidence for the influence of attention on the mechanisms underlying the auditory-vocal integration in the processing of pitch feedback errors. In addition, selective attention and divided attention appear to modulate the neurobehavioral processing of pitch feedback errors in different ways. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Wei, Jingwen; Dong, Guangzhong; Chen, Zonghai
2017-10-01
With the rapid development of battery-powered electric vehicles, the lithium-ion battery plays a critical role in the reliability of vehicle system. In order to provide timely management and protection for battery systems, it is necessary to develop a reliable battery model and accurate battery parameters estimation to describe battery dynamic behaviors. Therefore, this paper focuses on an on-board adaptive model for state-of-charge (SOC) estimation of lithium-ion batteries. Firstly, a first-order equivalent circuit battery model is employed to describe battery dynamic characteristics. Then, the recursive least square algorithm and the off-line identification method are used to provide good initial values of model parameters to ensure filter stability and reduce the convergence time. Thirdly, an extended-Kalman-filter (EKF) is applied to on-line estimate battery SOC and model parameters. Considering that the EKF is essentially a first-order Taylor approximation of battery model, which contains inevitable model errors, thus, a proportional integral-based error adjustment technique is employed to improve the performance of EKF method and correct model parameters. Finally, the experimental results on lithium-ion batteries indicate that the proposed EKF with proportional integral-based error adjustment method can provide robust and accurate battery model and on-line parameter estimation.
DeTemple, Duane
2010-01-01
Purely combinatorial proofs are given for the sum of squares formula, 1[superscript 2] + 2[superscript 2] + ... + n[superscript 2] = n(n + 1) (2n + 1) / 6, and the sum of sums of squares formula, 1[superscript 2] + (1[superscript 2] + 2[superscript 2]) + ... + (1[superscript 2] + 2[superscript 2] + ... + n[superscript 2]) = n(n + 1)[superscript 2]…
Ihssen, Niklas; Mussweiler, Thomas; Linden, David E J
2016-08-01
Reward properties of stimuli can undergo sudden changes, and the detection of these 'reversals' is often made difficult by the probabilistic nature of rewards/punishments. Here we tested whether and how humans use social information (someone else's choices) to overcome uncertainty during reversal learning. We show a substantial social influence during reversal learning, which was modulated by the type of observed behavior. Participants frequently followed observed conservative choices (no switches after punishment) made by the (fictitious) other player but ignored impulsive choices (switches), even though the experiment was set up so that both types of response behavior would be similarly beneficial/detrimental (Study 1). Computational modeling showed that participants integrated the observed choices as a 'social prediction error' instead of ignoring or blindly following the other player. Modeling also confirmed higher learning rates for 'conservative' versus 'impulsive' social prediction errors. Importantly, this 'conservative bias' was boosted by interpersonal similarity, which in conjunction with the lack of effects observed in a non-social control experiment (Study 2) confirmed its social nature. A third study suggested that relative weighting of observed impulsive responses increased with increased volatility (frequency of reversals). Finally, simulations showed that in the present paradigm integrating social and reward information was not necessarily more adaptive to maximize earnings than learning from reward alone. Moreover, integrating social information increased accuracy only when conservative and impulsive choices were weighted similarly during learning. These findings suggest that to guide decisions in choice contexts that involve reward reversals humans utilize social cues conforming with their preconceptions more strongly than cues conflicting with them, especially when the other is similar. Copyright © 2016 The Authors. Published by Elsevier B
Square-root measurement for pure states
International Nuclear Information System (INIS)
Huang Siendong
2005-01-01
Square-root measurement is a very useful suboptimal measurement in many applications. It was shown that the square-root measurement minimizes the squared error for pure states. In this paper, the least squared error problem is reformulated and a new proof is provided. It is found that the least squared error depends only on the average density operator of the input states. The properties of the least squared error are then discussed, and it is shown that if the input pure states are uniformly distributed, the average probability of error has an upper bound depending on the least squared error, the rank of the average density operator, and the number of the input states. The aforementioned properties help explain why the square-root measurement can be effective in decoding processes
International Nuclear Information System (INIS)
Chudnovsky, David; Chudnovsky, G.V.
1978-01-01
The relations between many particle problem with inverse square potential on the line and meromorphic eigenfunctions of Schroedinger operator are presented. This gives new type of Backlund transformations for many particle problem [fr
DEFF Research Database (Denmark)
Forchhammer, Søren; Kim, Chul E
1988-01-01
Digital squares are defined and their geometric properties characterized. A linear time algorithm is presented that considers a convex digital region and determines whether or not it is a digital square. The algorithm also determines the range of the values of the parameter set of its preimages....... The analysis involves transforming the boundary of a digital region into parameter space of slope and y-intercept...
International Nuclear Information System (INIS)
Esmaeilzadeh, Hamid; Arzi, Ezatollah; Légaré, François; Hassani, Alireza
2013-01-01
In this paper, using the boundary integral method (BIM), we simulate the effect of temperature fluctuation on the sensitivity of microstructured optical fibre (MOF) surface plasmon resonance (SPR) sensors. The final results indicate that, as the temperature increases, the refractometry sensitivity of our sensor decreases from 1300 nm/RIU at 0 °C to 1200 nm/RIU at 50 °C, leading to ∼7.7% sensitivity reduction and the sensitivity temperature error of 0.15% °C −1 for this case. These results can be used for biosensing temperature-error adjustment in MOF SPR sensors, since biomaterials detection usually happens in this temperature range. Moreover, the signal-to-noise ratio (SNR) of our sensor decreases from 0.265 at 0 °C to 0.154 at 100 °C with the average reduction rate of ∼0.42% °C −1 . The results suggest that at lower temperatures the sensor has a higher SNR. (paper)
A channel-by-channel method of reducing the errors associated with peak area integration
International Nuclear Information System (INIS)
Luedeke, T.P.; Tripard, G.E.
1996-01-01
A new method of reducing the errors associated with peak area integration has been developed. This method utilizes the signal content of each channel as an estimate of the overall peak area. These individual estimates can then be weighted according to the precision with which each estimate is known, producing an overall area estimate. Experimental measurements were performed on a small peak sitting on a large background, and the results compared to those obtained from a commercial software program. Results showed a marked decrease in the spread of results around the true value (obtained by counting for a long period of time), and a reduction in the statistical uncertainty associated with the peak area. (orig.)
Camporese, Matteo; Botto, Anna
2017-04-01
Data assimilation is becoming increasingly popular in hydrological and earth system modeling, as it allows us to integrate multisource observation data in modeling predictions and, in doing so, to reduce uncertainty. For this reason, data assimilation has been recently the focus of much attention also for physically-based integrated hydrological models, whereby multiple terrestrial compartments (e.g., snow cover, surface water, groundwater) are solved simultaneously, in an attempt to tackle environmental problems in a holistic approach. Recent examples include the joint assimilation of water table, soil moisture, and river discharge measurements in catchment models of coupled surface-subsurface flow using the ensemble Kalman filter (EnKF). One of the typical assumptions in these studies is that the measurement errors are uncorrelated, whereas in certain situations it is reasonable to believe that some degree of correlation occurs, due for example to the fact that a pair of sensors share the same soil type. The goal of this study is to show if and how the measurement error correlations between different observation data play a significant role on assimilation results in a real-world application of an integrated hydrological model. The model CATHY (CATchment HYdrology) is applied to reproduce the hydrological dynamics observed in an experimental hillslope. The physical model, located in the Department of Civil, Environmental and Architectural Engineering of the University of Padova (Italy), consists of a reinforced concrete box containing a soil prism with maximum height of 3.5 m, length of 6 m, and width of 2 m. The hillslope is equipped with sensors to monitor the pressure head and soil moisture responses to a series of generated rainfall events applied onto a 60 cm thick sand layer overlying a sandy clay soil. The measurement network is completed by two tipping bucket flow gages to measure the two components (subsurface and surface) of the outflow. By collecting
Indian Academy of Sciences (India)
Admin
2012-09-07
Sep 7, 2012 ... must first talk of permutations and Latin squares. A permutation of a finite set of objects is a linear arrange- ment of ... with a special element 1 ... Of course, this has .... tion method to disprove Euler's conjecture for infinitely.
DEFF Research Database (Denmark)
Mahmoudinezhad, Mahvash; Mirzazadeh, Abolfazl; Ghoreishi, Maryam
2017-01-01
of the manufacturer is not perfect and makes inspection errors of Type 1 and Type 2. The second-stage inspection of the manufacturer is at the end of production period without inspection errors. Also, the demand is linear function of time. Once the retailer receives the lot, a 100% screening process of the lot......In this article, an integrated production–distribution model is presented for a manufacturer and retailer supply chain under inflationary conditions, permissible delay in payments, deterioration, imperfect production process and inspection errors. We assume that the first-stage inspection...
Podio, Fernando; Vollrath, William; Williams, Joel; Kobler, Ben; Crouse, Don
1998-01-01
Sophisticated network storage management applications are rapidly evolving to satisfy a market demand for highly reliable data storage systems with large data storage capacities and performance requirements. To preserve a high degree of data integrity, these applications must rely on intelligent data storage devices that can provide reliable indicators of data degradation. Error correction activity generally occurs within storage devices without notification to the host. Early indicators of degradation and media error monitoring 333 and reporting (MEMR) techniques implemented in data storage devices allow network storage management applications to notify system administrators of these events and to take appropriate corrective actions before catastrophic errors occur. Although MEMR techniques have been implemented in data storage devices for many years, until 1996 no MEMR standards existed. In 1996 the American National Standards Institute (ANSI) approved the only known (world-wide) industry standard specifying MEMR techniques to verify stored data on optical disks. This industry standard was developed under the auspices of the Association for Information and Image Management (AIIM). A recently formed AIIM Optical Tape Subcommittee initiated the development of another data integrity standard specifying a set of media error monitoring tools and media error monitoring information (MEMRI) to verify stored data on optical tape media. This paper discusses the need for intelligent storage devices that can provide data integrity metadata, the content of the existing data integrity standard for optical disks, and the content of the MEMRI standard being developed by the AIIM Optical Tape Subcommittee.
Lyon, Betty Clayton
1990-01-01
One method of making magic squares using a prolongated square is illustrated. Discussed are third-order magic squares, fractional magic squares, fifth-order magic squares, decimal magic squares, and even magic squares. (CW)
DEFF Research Database (Denmark)
Rose, Jeremy; Sæbø, Øystein
2005-01-01
On-line political communities, such as the Norwegian site Demokratitorget (Democracy Square), are often designed according to a set of un-reflected assumptions about the political interests of their potential members. In political science, democracy is not taken as given in this way, but can...... be represented by different models which characterize different relationships between politicians and the citizens they represent. This paper uses quantitative and qualitative content analysis to analyze the communication mediated by the Democracy Square discussion forum in the first ten months of its life......-Republican model. In the qualitative analysis the discourse is analysed as repeating genres – patterns in the communication form which also reflect the conflict of interest between citizens and politicians. Though the analysis gives insight into the nature of the discourse the site supports, little is known about...
1972-01-01
With the existing Systems for using the accelerated protons, it is possible to supply only one slow ejected beam (feeding the East Hall) and, at the same time, to have only a small percentage of the beam on an internal target (feeding the South Hall). The arrangement will be replaced by a new System called SQUARE (Semi- QUAdrupole Resonant Extraction) which will give greater flexibility in supplying the three areas.
International Nuclear Information System (INIS)
Althuwaynee, Omar F; Pradhan, Biswajeet; Ahmad, Noordin
2014-01-01
This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies
Althuwaynee, Omar F.; Pradhan, Biswajeet; Ahmad, Noordin
2014-06-01
This article uses methodology based on chi-squared automatic interaction detection (CHAID), as a multivariate method that has an automatic classification capacity to analyse large numbers of landslide conditioning factors. This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). The main objective of this article is to use CHi-squared automatic interaction detection (CHAID) method to perform the best classification fit for each conditioning factor, then, combining it with logistic regression (LR). LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. Clustered locations were used as model training data with 14 landslide conditioning factors such as; topographic derived parameters, lithology, NDVI, land use and land cover maps. Pearson chi-squared value was used to find the best classification fit between the dependent variable and conditioning factors. Finally the relationship between conditioning factors were assessed and the landslide susceptibility map (LSM) was produced. An area under the curve (AUC) was used to test the model reliability and prediction capability with the training and validation landslide locations respectively. This study proved the efficiency and reliability of decision tree (DT) model in landslide susceptibility mapping. Also it provided a valuable scientific basis for spatial decision making in planning and urban management studies.
Sigurdardottir, Dorotea H.; Stearns, Jett; Glisic, Branko
2017-07-01
The deformed shape is a consequence of loading the structure and it is defined by the shape of the centroid line of the beam after deformation. The deformed shape is a universal parameter of beam-like structures. It is correlated with the curvature of the cross-section; therefore, any unusual behavior that affects the curvature is reflected through the deformed shape. Excessive deformations cause user discomfort, damage to adjacent structural members, and may ultimately lead to issues in structural safety. However, direct long-term monitoring of the deformed shape in real-life settings is challenging, and an alternative is indirect determination of the deformed shape based on curvature monitoring. The challenge of the latter is an accurate evaluation of error in the deformed shape determination, which is directly correlated with the number of sensors needed to achieve the desired accuracy. The aim of this paper is to study the deformed shape evaluated by numerical double integration of the monitored curvature distribution along the beam, and create a method to predict the associated errors and suggest the number of sensors needed to achieve the desired accuracy. The error due to the accuracy in the curvature measurement is evaluated within the scope of this work. Additionally, the error due to the numerical integration is evaluated. This error depends on the load case (i.e., the shape of the curvature diagram), the magnitude of curvature, and the density of the sensor network. The method is tested on a laboratory specimen and a real structure. In a laboratory setting, the double integration is in excellent agreement with the beam theory solution which was within the predicted error limits of the numerical integration. Consistent results are also achieved on a real structure—Streicker Bridge on Princeton University campus.
Energy Technology Data Exchange (ETDEWEB)
Santos-Villalobos, Hector J [ORNL; Gregor, Jens [University of Tennessee, Knoxville (UTK); Bingham, Philip R [ORNL
2014-01-01
At the present, neutron sources cannot be fabricated small and powerful enough in order to achieve high resolution radiography while maintaining an adequate flux. One solution is to employ computational imaging techniques such as a Magnified Coded Source Imaging (CSI) system. A coded-mask is placed between the neutron source and the object. The system resolution is increased by reducing the size of the mask holes and the flux is increased by increasing the size of the coded-mask and/or the number of holes. One limitation of such system is that the resolution of current state-of-the-art scintillator-based detectors caps around 50um. To overcome this challenge, the coded-mask and object are magnified by making the distance from the coded-mask to the object much smaller than the distance from object to detector. In previous work, we have shown via synthetic experiments that our least squares method outperforms other methods in image quality and reconstruction precision because of the modeling of the CSI system components. However, the validation experiments were limited to simplistic neutron sources. In this work, we aim to model the flux distribution of a real neutron source and incorporate such a model in our least squares computational system. We provide a full description of the methodology used to characterize the neutron source and validate the method with synthetic experiments.
Aronstein, David L.; Smith, J. Scott; Zielinski, Thomas P.; Telfer, Randal; Tournois, Severine C.; Moore, Dustin B.; Fienup, James R.
2016-01-01
The science instruments (SIs) comprising the James Webb Space Telescope (JWST) Integrated Science Instrument Module (ISIM) were tested in three cryogenic-vacuum test campaigns in the NASA Goddard Space Flight Center (GSFC)'s Space Environment Simulator (SES). In this paper, we describe the results of optical wavefront-error performance characterization of the SIs. The wavefront error is determined using image-based wavefront sensing (also known as phase retrieval), and the primary data used by this process are focus sweeps, a series of images recorded by the instrument under test in its as-used configuration, in which the focal plane is systematically changed from one image to the next. High-precision determination of the wavefront error also requires several sources of secondary data, including 1) spectrum, apodization, and wavefront-error characterization of the optical ground-support equipment (OGSE) illumination module, called the OTE Simulator (OSIM), 2) plate scale measurements made using a Pseudo-Nonredundant Mask (PNRM), and 3) pupil geometry predictions as a function of SI and field point, which are complicated because of a tricontagon-shaped outer perimeter and small holes that appear in the exit pupil due to the way that different light sources are injected into the optical path by the OGSE. One set of wavefront-error tests, for the coronagraphic channel of the Near-Infrared Camera (NIRCam) Longwave instruments, was performed using data from transverse translation diversity sweeps instead of focus sweeps, in which a sub-aperture is translated andor rotated across the exit pupil of the system.Several optical-performance requirements that were verified during this ISIM-level testing are levied on the uncertainties of various wavefront-error-related quantities rather than on the wavefront errors themselves. This paper also describes the methodology, based on Monte Carlo simulations of the wavefront-sensing analysis of focus-sweep data, used to establish the
A Monte Carlo Application to Approximate the Integral from a to b of e Raised to the x Squared.
Easterday, Kenneth; Smith, Tommy
1992-01-01
Proposes an alternative means of approximating the value of complex integrals, the Monte Carlo procedure. Incorporating a discrete approach and probability, an approximation is obtained from the ratio of computer-generated points falling under the curve to the number of points generated in a predetermined rectangle. (MDH)
Demonstration Integrated Knowledge-Based System for Estimating Human Error Probabilities
Energy Technology Data Exchange (ETDEWEB)
Auflick, Jack L.
1999-04-21
Human Reliability Analysis (HRA) is currently comprised of at least 40 different methods that are used to analyze, predict, and evaluate human performance in probabilistic terms. Systematic HRAs allow analysts to examine human-machine relationships, identify error-likely situations, and provide estimates of relative frequencies for human errors on critical tasks, highlighting the most beneficial areas for system improvements. Unfortunately, each of HRA's methods has a different philosophical approach, thereby producing estimates of human error probabilities (HEPs) that area better or worse match to the error likely situation of interest. Poor selection of methodology, or the improper application of techniques can produce invalid HEP estimates, where that erroneous estimation of potential human failure could have potentially severe consequences in terms of the estimated occurrence of injury, death, and/or property damage.
Round-off error in long-term orbital integrations using multistep methods
Quinlan, Gerald D.
1994-01-01
Techniques for reducing roundoff error are compared by testing them on high-order Stormer and summetric multistep methods. The best technique for most applications is to write the equation in summed, function-evaluation form and to store the coefficients as rational numbers. A larger error reduction can be achieved by writing the equation in backward-difference form and performing some of the additions in extended precision, but this entails a larger central processing unit (cpu) cost.
Tensor hypercontraction. II. Least-squares renormalization
Parrish, Robert M.; Hohenstein, Edward G.; Martínez, Todd J.; Sherrill, C. David
2012-12-01
The least-squares tensor hypercontraction (LS-THC) representation for the electron repulsion integral (ERI) tensor is presented. Recently, we developed the generic tensor hypercontraction (THC) ansatz, which represents the fourth-order ERI tensor as a product of five second-order tensors [E. G. Hohenstein, R. M. Parrish, and T. J. Martínez, J. Chem. Phys. 137, 044103 (2012)], 10.1063/1.4732310. Our initial algorithm for the generation of the THC factors involved a two-sided invocation of overlap-metric density fitting, followed by a PARAFAC decomposition, and is denoted PARAFAC tensor hypercontraction (PF-THC). LS-THC supersedes PF-THC by producing the THC factors through a least-squares renormalization of a spatial quadrature over the otherwise singular 1/r12 operator. Remarkably, an analytical and simple formula for the LS-THC factors exists. Using this formula, the factors may be generated with O(N^5) effort if exact integrals are decomposed, or O(N^4) effort if the decomposition is applied to density-fitted integrals, using any choice of density fitting metric. The accuracy of LS-THC is explored for a range of systems using both conventional and density-fitted integrals in the context of MP2. The grid fitting error is found to be negligible even for extremely sparse spatial quadrature grids. For the case of density-fitted integrals, the additional error incurred by the grid fitting step is generally markedly smaller than the underlying Coulomb-metric density fitting error. The present results, coupled with our previously published factorizations of MP2 and MP3, provide an efficient, robust O(N^4) approach to both methods. Moreover, LS-THC is generally applicable to many other methods in quantum chemistry.
A parallel row-based algorithm for standard cell placement with integrated error control
Sargent, Jeff S.; Banerjee, Prith
1989-01-01
A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel approaches to control error in parallel cell-placement algorithms: (1) Heuristic Cell-Coloring; (2) Adaptive Sequence Length Control.
International Nuclear Information System (INIS)
Schenter, R.E.; Oliver, B.M.; Farrar, H. IV
1987-01-01
Spectrum integrated cross sections for /sup 6/Li and /sup 10/B from five benchmark fast reactor neutron fields are compared with calculated values obtained using the ENDF/B-V Cross Section Files. The benchmark fields include the Coupled Fast Reactivity Measurements Facility (CFRMF) at the Idaho National Engineering Laboratory, the 10% Enriched U-235 Critical Assembly (BIG-10) at Los Alamos National Laboratory, the Sigma Sigma and Fission Cavity fields of the BR-1 reactor at CEN/SCK, and the Intermediate-Energy Standard Neutron Field (ISNF) at the National Bureau of Standards. Results from least square analyses using the FERRET computer code to obtain adjusted cross section values and their uncertainties are presented. Input to these calculations include the above five benchmark data sets. These analyses indicate a need for revision in the ENDF/B-V files for the /sup 10/B cross section for energies above 50 keV
International Nuclear Information System (INIS)
Schenter, R.E.; Oliver, B.M.; Farrar, H. IV.
1986-06-01
Spectrum integrated cross sections for 6 Li and 10 B from five benchmark fast reactor neutron fields are compared with calculated values obtained using the ENDF/B-V Cross Section Files. The benchmark fields include the Coupled Fast Reactivity Measurements Facility (CFRMF) at the Idaho National Engineering Laboratory, the 10% Enriched U-235 Critical Assembly (BIG-10) at Los Alamos National Laboratory, the Sigma-Sigma and Fission Cavity fields of the BR-1 reactor at CEN/SCK, and the Intermediate Energy Standard Neutron Field (ISNF) at the National Bureau of Standards. Results from least square analyses using the FERRET computer code to obtain adjusted cross section values and their uncertainties are presented. Input to these calculations include the above five benchmark data sets. These analyses indicate a need for revision in the ENDF/B-V files for the 10 B and 6 Li cross sections for energies above 50 keV
Directory of Open Access Journals (Sweden)
Peng Wang
2018-01-01
Full Text Available In recent years, the integrated modular avionics (IMA concept has been introduced to replace the traditional federated avionics. Different avionics functions are hosted in a shared IMA platform, and IMA adopts partition technologies to provide a logical isolation among different functions. The IMA architecture can provide more sophisticated and powerful avionics functionality; meanwhile, the failure propagation patterns in IMA are more complex. The feature of resource sharing introduces some unintended interconnections among different functions, which makes the failure propagation modes more complex. Therefore, this paper proposes an architecture analysis and design language- (AADL- based method to establish the reliability model of IMA platform. The single software and hardware error behavior in IMA system is modeled. The corresponding AADL error model of failure propagation among components, between software and hardware, is given. Finally, the display function of IMA platform is taken as an example to illustrate the effectiveness of the proposed method.
Karamat, Tashfeen B.; Atia, Mohamed M.; Noureldin, Aboelmagd
2015-01-01
Reduced inertial sensor systems (RISS) have been introduced by many researchers as a low-cost, low-complexity sensor assembly that can be integrated with GPS to provide a robust integrated navigation system for land vehicles. In earlier works, the developed error models were simplified based on the assumption that the vehicle is mostly moving on a flat horizontal plane. Another limitation is the simplified estimation of the horizontal tilt angles, which is based on simple averaging of the accelerometers’ measurements without modelling their errors or tilt angle errors. In this paper, a new error model is developed for RISS that accounts for the effect of tilt angle errors and the accelerometer’s errors. Additionally, it also includes important terms in the system dynamic error model, which were ignored during the linearization process in earlier works. An augmented extended Kalman filter (EKF) is designed to incorporate tilt angle errors and transversal accelerometer errors. The new error model and the augmented EKF design are developed in a tightly-coupled RISS/GPS integrated navigation system. The proposed system was tested on real trajectories’ data under degraded GPS environments, and the results were compared to earlier works on RISS/GPS systems. The findings demonstrated that the proposed enhanced system introduced significant improvements in navigational performance. PMID:26402680
Radiation effects and soft errors in integrated circuits and electronic devices
Fleetwood, D M
2004-01-01
This book provides a detailed treatment of radiation effects in electronic devices, including effects at the material, device, and circuit levels. The emphasis is on transient effects caused by single ionizing particles (single-event effects and soft errors) and effects produced by the cumulative energy deposited by the radiation (total ionizing dose effects). Bipolar (Si and SiGe), metal-oxide-semiconductor (MOS), and compound semiconductor technologies are discussed. In addition to considering the specific issues associated with high-performance devices and technologies, the book includes th
Abarbanel, Saul; Gottlieb, David; Carpenter, Mark H.
1994-01-01
It has been previously shown that the temporal integration of hyperbolic partial differential equations (PDE's) may, because of boundary conditions, lead to deterioration of accuracy of the solution. A procedure for removal of this error in the linear case has been established previously. In the present paper we consider hyperbolic (PDE's) (linear and non-linear) whose boundary treatment is done via the SAT-procedure. A methodology is present for recovery of the full order of accuracy, and has been applied to the case of a 4th order explicit finite difference scheme.
Rößler, Thomas; Stein, Olaf; Heng, Yi; Baumeister, Paul; Hoffmann, Lars
2018-02-01
The accuracy of trajectory calculations performed by Lagrangian particle dispersion models (LPDMs) depends on various factors. The optimization of numerical integration schemes used to solve the trajectory equation helps to maximize the computational efficiency of large-scale LPDM simulations. We analyzed global truncation errors of six explicit integration schemes of the Runge-Kutta family, which we implemented in the Massive-Parallel Trajectory Calculations (MPTRAC) advection module. The simulations were driven by wind fields from operational analysis and forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) at T1279L137 spatial resolution and 3 h temporal sampling. We defined separate test cases for 15 distinct regions of the atmosphere, covering the polar regions, the midlatitudes, and the tropics in the free troposphere, in the upper troposphere and lower stratosphere (UT/LS) region, and in the middle stratosphere. In total, more than 5000 different transport simulations were performed, covering the months of January, April, July, and October for the years 2014 and 2015. We quantified the accuracy of the trajectories by calculating transport deviations with respect to reference simulations using a fourth-order Runge-Kutta integration scheme with a sufficiently fine time step. Transport deviations were assessed with respect to error limits based on turbulent diffusion. Independent of the numerical scheme, the global truncation errors vary significantly between the different regions. Horizontal transport deviations in the stratosphere are typically an order of magnitude smaller compared with the free troposphere. We found that the truncation errors of the six numerical schemes fall into three distinct groups, which mostly depend on the numerical order of the scheme. Schemes of the same order differ little in accuracy, but some methods need less computational time, which gives them an advantage in efficiency. The selection of the integration
Directory of Open Access Journals (Sweden)
Emerson José de Paiva
2010-03-01
Full Text Available Encontrar um conjunto ótimo de parâmetros para um processo de soldagem é uma tarefa pouco trivial, face às múltiplas características exigíveis ou desejáveis que devem ser analisadas. Além disso, a negligência da estrutura de variância-covariância destas características na otimização pode conduzir a ótimos inadequados. Com o intuito de auxiliar na busca desses parâmetros, um método para otimização multiobjetiva, desenvolvido para o estudo do processo de soldagem FCAW (do inglês Flux Cored Arc Welding, utilizando-se arames tubulares, baseado no conceito de Erro Quadrático Médio Multivariado, será apresentado. Trata-se de uma abordagem combinada da Metodologia de Superfície de Resposta, Projeto de Experimentos e Análise de Componentes Principais, na tentativa de localizar valores próximos a alvos especificados, para cada uma das características estudadas (Penetração, Taxa de deposição, Rendimento, Índice de convexidade e Diluição, considerando-se as variáveis de processo expressas em função da tensão (V, velocidade de alimentação do arame (Va e da distância do bico de contato-peça (d. Os resultados obtidos apontam para uma boa adequação desta proposta.The optimization of welding processes is not a trivial task, mainly due to the great number of exigible and desirable characteristics that must be analyzed. Moreover, the optimization of a welding process with multiple characteristics without to consider the variance-covariance structure, may lead to inadequate optimum. To help in this task, a method of multiobjective optimization based in the Multivariate Mean Square Error applied in the study of multiple correlated characteristics of a FCAW (Flux Cored Arc Welding welding process will be presented. This method characterized by a combined approach based in the Response Surface Methodology, Design of Experiments and Principal Components Analysis consisted in an attempt to achieve the nearest values to
Energy Technology Data Exchange (ETDEWEB)
Boehnke, E McKenzie; DeMarco, J; Steers, J; Fraass, B [Cedars-Sinai Medical Center, Los Angeles, CA (United States)
2016-06-15
Purpose: To examine both the IQM’s sensitivity and false positive rate to varying MLC errors. By balancing these two characteristics, an optimal tolerance value can be derived. Methods: An un-modified SBRT Liver IMRT plan containing 7 fields was randomly selected as a representative clinical case. The active MLC positions for all fields were perturbed randomly from a square distribution of varying width (±1mm to ±5mm). These unmodified and modified plans were measured multiple times each by the IQM (a large area ion chamber mounted to a TrueBeam linac head). Measurements were analyzed relative to the initial, unmodified measurement. IQM readings are analyzed as a function of control points. In order to examine sensitivity to errors along a field’s delivery, each measured field was divided into 5 groups of control points, and the maximum error in each group was recorded. Since the plans have known errors, we compared how well the IQM is able to differentiate between unmodified and error plans. ROC curves and logistic regression were used to analyze this, independent of thresholds. Results: A likelihood-ratio Chi-square test showed that the IQM could significantly predict whether a plan had MLC errors, with the exception of the beginning and ending control points. Upon further examination, we determined there was ramp-up occurring at the beginning of delivery. Once the linac AFC was tuned, the subsequent measurements (relative to a new baseline) showed significant (p <0.005) abilities to predict MLC errors. Using the area under the curve, we show the IQM’s ability to detect errors increases with increasing MLC error (Spearman’s Rho=0.8056, p<0.0001). The optimal IQM count thresholds from the ROC curves are ±3%, ±2%, and ±7% for the beginning, middle 3, and end segments, respectively. Conclusion: The IQM has proven to be able to detect not only MLC errors, but also differences in beam tuning (ramp-up). Partially supported by the Susan Scott Foundation.
Saga, R. S.; Jauhari, W. A.; Laksono, P. W.
2017-11-01
This paper presents an integrated inventory model which consists of single vendor and buyer. The buyer managed its inventory periodically and orders products from the vendor to satisfy the end customer’s demand, where the annual demand and the ordering cost were in the fuzzy environment. The buyer used a service level constraint instead of the stock-out cost term, so that the stock-out level per cycle was bounded. Then, the vendor produced and delivered products to the buyer. The vendor had a choice to commit an investment to reduce the setup cost. However, the vendor’s production process was imperfect, thus the lot delivered contained some defective products. Moreover, the buyer’s inspection process was not error-free since the inspector could be mistaken in categorizing the product’s quality. The objective was to find the optimum value for the review period, the setup cost, and the number of deliveries in one production cycle which might minimize the joint total cost. Furthermore, the algorithm and numerical example were provided to illustrate the application of the model.
Watson, Gale A.
2003-01-01
Demonstrates the transformations that are possible to construct a variety of magic squares, including modifications to challenge students from elementary grades through algebra. Presents an example of using magic squares with students who have special needs. (YDS)
Weighted conditional least-squares estimation
International Nuclear Information System (INIS)
Booth, J.G.
1987-01-01
A two-stage estimation procedure is proposed that generalizes the concept of conditional least squares. The method is instead based upon the minimization of a weighted sum of squares, where the weights are inverses of estimated conditional variance terms. Some general conditions are given under which the estimators are consistent and jointly asymptotically normal. More specific details are given for ergodic Markov processes with stationary transition probabilities. A comparison is made with the ordinary conditional least-squares estimators for two simple branching processes with immigration. The relationship between weighted conditional least squares and other, more well-known, estimators is also investigated. In particular, it is shown that in many cases estimated generalized least-squares estimators can be obtained using the weighted conditional least-squares approach. Applications to stochastic compartmental models, and linear models with nested error structures are considered
Moreno, Carlos J
2005-01-01
Introduction Prerequisites Outline of Chapters 2 - 8 Elementary Methods Introduction Some Lemmas Two Fundamental Identities Euler's Recurrence for Sigma(n)More Identities Sums of Two Squares Sums of Four Squares Still More Identities Sums of Three Squares An Alternate Method Sums of Polygonal Numbers Exercises Bernoulli Numbers Overview Definition of the Bernoulli Numbers The Euler-MacLaurin Sum Formula The Riemann Zeta Function Signs of Bernoulli Numbers Alternate The von Staudt-Clausen Theorem Congruences of Voronoi and Kummer Irregular Primes Fractional Parts of Bernoulli Numbers Exercises Examples of Modular Forms Introduction An Example of Jacobi and Smith An Example of Ramanujan and Mordell An Example of Wilton: t (n) Modulo 23 An Example of Hamburger Exercises Hecke's Theory of Modular FormsIntroduction Modular Group ? and its Subgroup ? 0 (N) Fundamental Domains For ? and ? 0 (N) Integral Modular Forms Modular Forms of Type Mk(? 0(N);chi) and Euler-Poincare series Hecke Operators Dirichlet Series and ...
Misiurewicz, Michal
2013-01-01
If students are presented the standard proof of irrationality of [square root]2, can they generalize it to a proof of the irrationality of "[square root]p", "p" a prime if, instead of considering divisibility by "p", they cling to the notions of even and odd used in the standard proof?
Colins, Karen; Li, Liqian; Liu, Yu
2017-05-01
Mass production of widely used semiconductor digital integrated circuits (ICs) has lowered unit costs to the level of ordinary daily consumables of a few dollars. It is therefore reasonable to contemplate the idea of an engineered system that consumes unshielded low-cost ICs for the purpose of measuring gamma radiation dose. Underlying the idea is the premise of a measurable correlation between an observable property of ICs and radiation dose. Accumulation of radiation-damage-induced state changes or error events is such a property. If correct, the premise could make possible low-cost wide-area radiation dose measurement systems, instantiated as wireless sensor networks (WSNs) with unshielded consumable ICs as nodes, communicating error events to a remote base station. The premise has been investigated quantitatively for the first time in laboratory experiments and related analyses performed at the Canadian Nuclear Laboratories. State changes or error events were recorded in real time during irradiation of samples of ICs of different types in a 60Co gamma cell. From the error-event sequences, empirical distribution functions of dose were generated. The distribution functions were inverted and probabilities scaled by total error events, to yield plots of the relationship between dose and error tallies. Positive correlation was observed, and discrete functional dependence of dose quantiles on error tallies was measured, demonstrating the correctness of the premise. The idea of an engineered system that consumes unshielded low-cost ICs in a WSN, for the purpose of measuring gamma radiation dose over wide areas, is therefore tenable.
Energy Technology Data Exchange (ETDEWEB)
Chengqiang, L; Yin, Y; Chen, L [Shandong Cancer Hospital and Institute, 440 Jiyan Road, Jinan, 250117 (China)
2015-06-15
Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans. Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.
Latin square three dimensional gage master
Jones, Lynn L.
1982-01-01
A gage master for coordinate measuring machines has an nxn array of objects distributed in the Z coordinate utilizing the concept of a Latin square experimental design. Using analysis of variance techniques, the invention may be used to identify sources of error in machine geometry and quantify machine accuracy.
Iterative methods for weighted least-squares
Energy Technology Data Exchange (ETDEWEB)
Bobrovnikova, E.Y.; Vavasis, S.A. [Cornell Univ., Ithaca, NY (United States)
1996-12-31
A weighted least-squares problem with a very ill-conditioned weight matrix arises in many applications. Because of round-off errors, the standard conjugate gradient method for solving this system does not give the correct answer even after n iterations. In this paper we propose an iterative algorithm based on a new type of reorthogonalization that converges to the solution.
Quantized kernel least mean square algorithm.
Chen, Badong; Zhao, Songlin; Zhu, Pingping; Príncipe, José C
2012-01-01
In this paper, we propose a quantization approach, as an alternative of sparsification, to curb the growth of the radial basis function structure in kernel adaptive filtering. The basic idea behind this method is to quantize and hence compress the input (or feature) space. Different from sparsification, the new approach uses the "redundant" data to update the coefficient of the closest center. In particular, a quantized kernel least mean square (QKLMS) algorithm is developed, which is based on a simple online vector quantization method. The analytical study of the mean square convergence has been carried out. The energy conservation relation for QKLMS is established, and on this basis we arrive at a sufficient condition for mean square convergence, and a lower and upper bound on the theoretical value of the steady-state excess mean square error. Static function estimation and short-term chaotic time-series prediction examples are presented to demonstrate the excellent performance.
International Nuclear Information System (INIS)
Akita, Junji; Honma, Toei.
1975-01-01
Object: To provide a square through tube involving thermal movement in pipelines such as water supply pump driving turbine exhaust pipe (square-shaped), which is wide in freedom with respect to shape and dimension thereof for efficient installation at site. Structure: In a through tube to be airtightly retained for purpose of decontamination in an atomic power plant, comprising a seal rubber plate, a band and a bolt and a nut for securing said plate, the seal rubber plate being worked into the desired shape so that it may be placed in intimate contact with the concrete floor surface by utilization of elasticity of rubber, thereby providing airtightness at a corner portion of the square tube. (Kamimura, M.)
DEFF Research Database (Denmark)
Guo, Xiaoqiang; Guerrero, Josep M.
2016-01-01
Current regulation is crucial for operating single-phase grid-connected inverters. The challenge of the current controller is how to fast and precisely tracks the current with zero steady-state error. This paper proposes a novel feedback mechanism for the conventional PI controller. It allows...... done indicates that the widely used PR (P+Resonant) control is just a special case of the proposed control solution. The time-domain simulation in Matlab/Simulink and experimental results from a TMS320F2812 DSP based laboratory prototypes are in good agreement, which verify the effectiveness...
BIOMECHANICS. Why the seahorse tail is square.
Porter, Michael M; Adriaens, Dominique; Hatton, Ross L; Meyers, Marc A; McKittrick, Joanna
2015-07-03
Whereas the predominant shapes of most animal tails are cylindrical, seahorse tails are square prisms. Seahorses use their tails as flexible grasping appendages, in spite of a rigid bony armor that fully encases their bodies. We explore the mechanics of two three-dimensional-printed models that mimic either the natural (square prism) or hypothetical (cylindrical) architecture of a seahorse tail to uncover whether or not the square geometry provides any functional advantages. Our results show that the square prism is more resilient when crushed and provides a mechanism for preserving articulatory organization upon extensive bending and twisting, as compared with its cylindrical counterpart. Thus, the square architecture is better than the circular one in the context of two integrated functions: grasping ability and crushing resistance. Copyright © 2015, American Association for the Advancement of Science.
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,
Minimum Mean-Square Error Single-Channel Signal Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas
2008-01-01
This topic of this thesis is MMSE signal estimation for hearing aids when only one microphone is available. The research is relevant for noise reduction systems in hearing aids. To fully benefit from the amplification provided by a hearing aid, noise reduction functionality is important as hearin...... algorithm. Although performance of the two algorithms is found comparable then the particle filter algorithm is doing a much better job tracking the noise.......-impaired persons in some noisy situations need a higher signal to noise ratio for speech to be intelligible when compared to normal-hearing persons. In this thesis two different methods to approach the MMSE signal estimation problem is examined. The methods differ in the way that models for the signal and noise...... inference is performed by particle filtering. The speech model is a time-varying auto-regressive model reparameterized by formant frequencies and bandwidths. The noise is assumed non-stationary and white. Compared to the case of using the AR coefficients directly then it is found very beneficial to perform...
Mean-Square Error Due to Gradiometer Field Measuring Devices
1991-06-01
convolving the gradiometer data with the inverse transform of I /T(a, 13), applying an ap- Hence (2) may be expressed in the transform domain as propriate... inverse transform of I / T(ot, 1) will not be possible quency measurements," Superconductor Applications: SQUID’s and because its inverse does not exist...and because it is a high- Machines, B. B. Schwartz and S. Foner, Eds. New York: Plenum pass function its use in an inverse transform technique Press
Regularized plane-wave least-squares Kirchhoff migration
Wang, Xin; Dai, Wei; Schuster, Gerard T.
2013-01-01
A Kirchhoff least-squares migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images. A regularization term is included that accounts for mispositioning of reflectors due to errors in the velocity
Error analysis of stochastic gradient descent ranking.
Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan
2013-06-01
Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.
Smith, Amber R.; Williams, Paul H.; McGee, Seth A.; Dósa, Katalin; Pfammatter, Jesse
2014-01-01
Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question “What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev),” we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students’ cognitive structures before and after the unit and explanations in students’ final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on “variation” as a proposed threshold concept and primary goal for students’ explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from “plug and play,” this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. PMID:25185225
Batzli, Janet M; Smith, Amber R; Williams, Paul H; McGee, Seth A; Dósa, Katalin; Pfammatter, Jesse
2014-01-01
Genetics instruction in introductory biology is often confined to Mendelian genetics and avoids the complexities of variation in quantitative traits. Given the driving question "What determines variation in phenotype (Pv)? (Pv=Genotypic variation Gv + environmental variation Ev)," we developed a 4-wk unit for an inquiry-based laboratory course focused on the inheritance and expression of a quantitative trait in varying environments. We utilized Brassica rapa Fast Plants as a model organism to study variation in the phenotype anthocyanin pigment intensity. As an initial curriculum assessment, we used free word association to examine students' cognitive structures before and after the unit and explanations in students' final research posters with particular focus on variation (Pv = Gv + Ev). Comparison of pre- and postunit word frequency revealed a shift in words and a pattern of co-occurring concepts indicative of change in cognitive structure, with particular focus on "variation" as a proposed threshold concept and primary goal for students' explanations. Given review of 53 posters, we found ∼50% of students capable of intermediate to high-level explanations combining both Gv and Ev influence on expression of anthocyanin intensity (Pv). While far from "plug and play," this conceptually rich, inquiry-based unit holds promise for effective integration of quantitative and Mendelian genetics. © 2014 J. M. Batzli et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
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.)
Least-squares model-based halftoning
Pappas, Thrasyvoulos N.; Neuhoff, David L.
1992-08-01
A least-squares model-based approach to digital halftoning is proposed. It exploits both a printer model and a model for visual perception. It attempts to produce an 'optimal' halftoned reproduction, by minimizing the squared error between the response of the cascade of the printer and visual models to the binary image and the response of the visual model to the original gray-scale image. Conventional methods, such as clustered ordered dither, use the properties of the eye only implicitly, and resist printer distortions at the expense of spatial and gray-scale resolution. In previous work we showed that our printer model can be used to modify error diffusion to account for printer distortions. The modified error diffusion algorithm has better spatial and gray-scale resolution than conventional techniques, but produces some well known artifacts and asymmetries because it does not make use of an explicit eye model. Least-squares model-based halftoning uses explicit eye models and relies on printer models that predict distortions and exploit them to increase, rather than decrease, both spatial and gray-scale resolution. We have shown that the one-dimensional least-squares problem, in which each row or column of the image is halftoned independently, can be implemented with the Viterbi's algorithm. Unfortunately, no closed form solution can be found in two dimensions. The two-dimensional least squares solution is obtained by iterative techniques. Experiments show that least-squares model-based halftoning produces more gray levels and better spatial resolution than conventional techniques. We also show that the least- squares approach eliminates the problems associated with error diffusion. Model-based halftoning can be especially useful in transmission of high quality documents using high fidelity gray-scale image encoders. As we have shown, in such cases halftoning can be performed at the receiver, just before printing. Apart from coding efficiency, this approach
Cuba: Multidimensional numerical integration library
Hahn, Thomas
2016-08-01
The Cuba library offers four independent routines for multidimensional numerical integration: Vegas, Suave, Divonne, and Cuhre. The four algorithms work by very different methods, and can integrate vector integrands and have very similar Fortran, C/C++, and Mathematica interfaces. Their invocation is very similar, making it easy to cross-check by substituting one method by another. For further safeguarding, the output is supplemented by a chi-square probability which quantifies the reliability of the error estimate.
International Nuclear Information System (INIS)
Dory, R.A.; Uckan, N.A.; Ard, W.B.
1986-10-01
The ELMO Bumpy Square (EBS) concept consists of four straight magnetic mirror arrays linked by four high-field corner coils. Extensive calculations show that this configuration offers major improvements over the ELMO Bumpy Torus (EBT) in particle confinement, heating, transport, ring production, and stability. The components of the EBT device at Oak Ridge National Laboratory can be reconfigured into a square arrangement having straight sides composed of EBT coils, with new microwave cavities and high-field corners designed and built for this application. The elimination of neoclassical convection, identified as the dominant mechanism for the limited confinement in EBT, will give the EBS device substantially improved confinement and the flexibility to explore the concepts that produce this improvement. The primary goals of the EBS program are twofold: first, to improve the physics of confinement in toroidal systems by developing the concepts of plasma stabilization using the effects of energetic electrons and confinement optimization using magnetic field shaping and electrostatic potential control to limit particle drift, and second, to develop bumpy toroid devices as attractive candidates for fusion reactors. This report presents a brief review of the physics analyses that support the EBS concept, discussions of the design and expected performance of the EBS device, a description of the EBS experimental program, and a review of the reactor potential of bumpy toroid configurations. Detailed information is presented in the appendices
Improved linear least squares estimation using bounded data uncertainty
Ballal, Tarig
2015-04-01
This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.
Improved linear least squares estimation using bounded data uncertainty
Ballal, Tarig; Al-Naffouri, Tareq Y.
2015-01-01
This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.
Directory of Open Access Journals (Sweden)
Jorge L. Soriano García
2007-08-01
indirectos. Conclusiones: Constituye el primer reporte de un sistema integrado de prevención de errores en los antineoplásicos en países con recursos limitados y puede, por su sencillez y factibilidad, ser aplicado en cualquiera de estos países.Justification: Medication mistakes in case of chemotherapy or adjuvant treatment used in any stage of drug application process: prescription, transcription, preparation, dispense or administration, are a frequent cause of side effects of antineoplastic drugs. Methods: Main sourses of information were meetings to analyze application of quality guarantee program in Oncology in services and the revision of medical literature published in from 1995 to January 2006, appeared in MEDLINE. Searching strategy was performed under headings “mediction errors” and “chemotherapy”. Additional searches were performed under headings “safety patient”, “antineoplastic drugs”, “preventing medications errors”, and were combined each other. Results: Experience of Oncology Service from “Hermanos Ameijeiras” Clinical Surgical Hospital was exposed as for application of work strategy related to error prevention in administration of drugs in above service from year 2000. To date, some novel features has been applied: forms for chemotherapeutic treatment, standardized suggestions in pre-printed sheets, drugs dilution tables, new organizing nursing systems, and report sheets in case of patient toxicity. Application of above strategy involves antineoplastic chemotherapy, and global survival of patients. It contributes to reduct direct health expenses (decrease in complications and treatment derived from it, real time of staff in different phases of drug use process, and consumption of cytostatic sera and indirect charges. Conclusions: This is the first report from aa integrated system of error prevention in antineoplastic drugs in countries with limites resources, and by its simplicity and feasibility, may be applied in any of these
Directory of Open Access Journals (Sweden)
A. V. Fomichev
2015-01-01
Full Text Available In accordance with the structural features of small-size unmanned aerial vehicle (UAV, and considering the feasibility of this project, the article studies an integrated inertial-satellite navigation system (INS. The INS algorithm development is based on the method of indirect filtration and principle of loosely coupled combination of output data on UAV positions and velocity. Data on position and velocity are provided from the strapdown inertial navigation system (SINS and satellite navigation system (GPS. A difference between the output flows of measuring data on position and velocity provided from the SINS and GPS is used to evaluate SINS errors by means of the basic algorithm of Kalman filtering. Then the outputs of SINS are revised. The INS possesses the following advantages: a simpler mathematical model of Kalman filtering, high reliability, two independently operating navigation systems, and high redundancy of available navigation information.But in case of loosely coupled scheme, INS can meet the challenge of high precision and reliability of navigation only when the SINS and GPS operating conditions are normal all the time. The proposed INS is used with UAV moving in complex environment due to obstacles available, severe natural climatic conditions, etc. This case expects that it is impossible for UAV to receive successful GPS-signals frequently. In order to solve this problem, was developed an algorithm for rapid compensation for errors of INS information, which could effectively solve the problem of failure of the navigation system in case there are no GPS-signals .Since it is almost impossible to obtain the data of the real trajectory in practice, in the course of simulation in accordance with the kinematic model of the UAV and the complex environment of the terrain, the flight path generator is used to produce the flight path. The errors of positions and velocities are considered as an indicator of the INS effectiveness. The results
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.)
Williams, Horace E.
1974-01-01
A method for generating 3x3 magic squares is developed. A series of questions relating to these magic squares is posed. An invesitgation using matrix methods is suggested with some questions for consideration. (LS)
Weighted least-squares criteria for electrical impedance tomography
International Nuclear Information System (INIS)
Kallman, J.S.; Berryman, J.G.
1992-01-01
Methods are developed for design of electrical impedance tomographic reconstruction algorithms with specified properties. Assuming a starting model with constant conductivity or some other specified background distribution, an algorithm with the following properties is found: (1) the optimum constant for the starting model is determined automatically; (2) the weighted least-squares error between the predicted and measured power dissipation data is as small as possible; (3) the variance of the reconstructed conductivity from the starting model is minimized; (4) potential distributions with the largest volume integral of gradient squared have the least influence on the reconstructed conductivity, and therefore distributions most likely to be corrupted by contact impedance effects are deemphasized; (5) cells that dissipate the most power during the current injection tests tend to deviate least from the background value. The resulting algorithm maps the reconstruction problem into a vector space where the contribution to the inversion from the background conductivity remains invariant, while the optimum contributions in orthogonal directions are found. For a starting model with nonconstant conductivity, the reconstruction algorithm has analogous properties
Motyer, R E; Liddy, S; Torreggiani, W C; Buckley, O
2016-11-01
Voice recognition (VR) dictation of radiology reports has become the mainstay of reporting in many institutions worldwide. Despite benefit, such software is not without limitations, and transcription errors have been widely reported. Evaluate the frequency and nature of non-clinical transcription error using VR dictation software. Retrospective audit of 378 finalised radiology reports. Errors were counted and categorised by significance, error type and sub-type. Data regarding imaging modality, report length and dictation time was collected. 67 (17.72 %) reports contained ≥1 errors, with 7 (1.85 %) containing 'significant' and 9 (2.38 %) containing 'very significant' errors. A total of 90 errors were identified from the 378 reports analysed, with 74 (82.22 %) classified as 'insignificant', 7 (7.78 %) as 'significant', 9 (10 %) as 'very significant'. 68 (75.56 %) errors were 'spelling and grammar', 20 (22.22 %) 'missense' and 2 (2.22 %) 'nonsense'. 'Punctuation' error was most common sub-type, accounting for 27 errors (30 %). Complex imaging modalities had higher error rates per report and sentence. Computed tomography contained 0.040 errors per sentence compared to plain film with 0.030. Longer reports had a higher error rate, with reports >25 sentences containing an average of 1.23 errors per report compared to 0-5 sentences containing 0.09. These findings highlight the limitations of VR dictation software. While most error was deemed insignificant, there were occurrences of error with potential to alter report interpretation and patient management. Longer reports and reports on more complex imaging had higher error rates and this should be taken into account by the reporting radiologist.
Effect of Numerical Error on Gravity Field Estimation for GRACE and Future Gravity Missions
McCullough, Christopher; Bettadpur, Srinivas
2015-04-01
In recent decades, gravity field determination from low Earth orbiting satellites, such as the Gravity Recovery and Climate Experiment (GRACE), has become increasingly more effective due to the incorporation of high accuracy measurement devices. Since instrumentation quality will only increase in the near future and the gravity field determination process is computationally and numerically intensive, numerical error from the use of double precision arithmetic will eventually become a prominent error source. While using double-extended or quadruple precision arithmetic will reduce these errors, the numerical limitations of current orbit determination algorithms and processes must be accurately identified and quantified in order to adequately inform the science data processing techniques of future gravity missions. The most obvious numerical limitation in the orbit determination process is evident in the comparison of measured observables with computed values, derived from mathematical models relating the satellites' numerically integrated state to the observable. Significant error in the computed trajectory will corrupt this comparison and induce error in the least squares solution of the gravitational field. In addition, errors in the numerically computed trajectory propagate into the evaluation of the mathematical measurement model's partial derivatives. These errors amalgamate in turn with numerical error from the computation of the state transition matrix, computed using the variational equations of motion, in the least squares mapping matrix. Finally, the solution of the linearized least squares system, computed using a QR factorization, is also susceptible to numerical error. Certain interesting combinations of each of these numerical errors are examined in the framework of GRACE gravity field determination to analyze and quantify their effects on gravity field recovery.
Constrained least squares regularization in PET
International Nuclear Information System (INIS)
Choudhury, K.R.; O'Sullivan, F.O.
1996-01-01
Standard reconstruction methods used in tomography produce images with undesirable negative artifacts in background and in areas of high local contrast. While sophisticated statistical reconstruction methods can be devised to correct for these artifacts, their computational implementation is excessive for routine operational use. This work describes a technique for rapid computation of approximate constrained least squares regularization estimates. The unique feature of the approach is that it involves no iterative projection or backprojection steps. This contrasts with the familiar computationally intensive algorithms based on algebraic reconstruction (ART) or expectation-maximization (EM) methods. Experimentation with the new approach for deconvolution and mixture analysis shows that the root mean square error quality of estimators based on the proposed algorithm matches and usually dominates that of more elaborate maximum likelihood, at a fraction of the computational effort
Dancoff Correction in Square and Hexagonal Lattices
Energy Technology Data Exchange (ETDEWEB)
Carlvik, I
1966-11-15
This report presents the results of a series of calculations of Dancoff corrections for square and hexagonal rod lattices. The tables cover a wide range of volume ratios and moderator cross sections. The results were utilized for checking the approximative formula of Sauer and also the modification of Bonalumi to Sauer's formula. The modified formula calculates the Dancoff correction with an accuracy of 0.01 - 0.02 in cases of practical interest. Calculations have also been performed on square lattices with an empty gap surrounding the rods. The results demonstrate the error involved in treating this kind of geometry by means of homogenizing the gap and the moderator. The calculations were made on the Ferranti Mercury computer of AB Atomenergi before it was closed down. Since then FORTRAN routines for Dancoff corrections have been written, and a subroutine DASQHE is included in the report.
A hybrid least squares support vector machines and GMDH approach for river flow forecasting
Samsudin, R.; Saad, P.; Shabri, A.
2010-06-01
This paper proposes a novel hybrid forecasting model, which combines the group method of data handling (GMDH) and the least squares support vector machine (LSSVM), known as GLSSVM. The GMDH is used to determine the useful input variables for LSSVM model and the LSSVM model which works as time series forecasting. In this study the application of GLSSVM for monthly river flow forecasting of Selangor and Bernam River are investigated. The results of the proposed GLSSVM approach are compared with the conventional artificial neural network (ANN) models, Autoregressive Integrated Moving Average (ARIMA) model, GMDH and LSSVM models using the long term observations of monthly river flow discharge. The standard statistical, the root mean square error (RMSE) and coefficient of correlation (R) are employed to evaluate the performance of various models developed. Experiment result indicates that the hybrid model was powerful tools to model discharge time series and can be applied successfully in complex hydrological modeling.
Fulkerson, David E.
2010-02-01
This paper describes a new methodology for characterizing the electrical behavior and soft error rate (SER) of CMOS and SiGe HBT integrated circuits that are struck by ions. A typical engineering design problem is to calculate the SER of a critical path that commonly includes several circuits such as an input buffer, several logic gates, logic storage, clock tree circuitry, and an output buffer. Using multiple 3D TCAD simulations to solve this problem is too costly and time-consuming for general engineering use. The new and simple methodology handles the problem with ease by simple SPICE simulations. The methodology accurately predicts the measured threshold linear energy transfer (LET) of a bulk CMOS SRAM. It solves for circuit currents and voltage spikes that are close to those predicted by expensive 3D TCAD simulations. It accurately predicts the measured event cross-section vs. LET curve of an experimental SiGe HBT flip-flop. The experimental cross section vs. frequency behavior and other subtle effects are also accurately predicted.
Two Enhancements of the Logarithmic Least-Squares Method for Analyzing Subjective Comparisons
1989-03-25
error term. 1 For this model, the total sum of squares ( SSTO ), defined as n 2 SSTO = E (yi y) i=1 can be partitioned into error and regression sums...of the regression line around the mean value. Mathematically, for the model given by equation A.4, SSTO = SSE + SSR (A.6) A-4 where SSTO is the total...sum of squares (i.e., the variance of the yi’s), SSE is error sum of squares, and SSR is the regression sum of squares. SSTO , SSE, and SSR are given
Optimally weighted least-squares steganalysis
Ker, Andrew D.
2007-02-01
Quantitative steganalysis aims to estimate the amount of payload in a stego object, and such estimators seem to arise naturally in steganalysis of Least Significant Bit (LSB) replacement in digital images. However, as with all steganalysis, the estimators are subject to errors, and their magnitude seems heavily dependent on properties of the cover. In very recent work we have given the first derivation of estimation error, for a certain method of steganalysis (the Least-Squares variant of Sample Pairs Analysis) of LSB replacement steganography in digital images. In this paper we make use of our theoretical results to find an improved estimator and detector. We also extend the theoretical analysis to another (more accurate) steganalysis estimator (Triples Analysis) and hence derive an improved version of that estimator too. Experimental results show that the new steganalyzers have improved accuracy, particularly in the difficult case of never-compressed covers.
Least square regularized regression in sum space.
Xu, Yong-Li; Chen, Di-Rong; Li, Han-Xiong; Liu, Lu
2013-04-01
This paper proposes a least square regularized regression algorithm in sum space of reproducing kernel Hilbert spaces (RKHSs) for nonflat function approximation, and obtains the solution of the algorithm by solving a system of linear equations. This algorithm can approximate the low- and high-frequency component of the target function with large and small scale kernels, respectively. The convergence and learning rate are analyzed. We measure the complexity of the sum space by its covering number and demonstrate that the covering number can be bounded by the product of the covering numbers of basic RKHSs. For sum space of RKHSs with Gaussian kernels, by choosing appropriate parameters, we tradeoff the sample error and regularization error, and obtain a polynomial learning rate, which is better than that in any single RKHS. The utility of this method is illustrated with two simulated data sets and five real-life databases.
Proportionate-type normalized last mean square algorithms
Wagner, Kevin
2013-01-01
The topic of this book is proportionate-type normalized least mean squares (PtNLMS) adaptive filtering algorithms, which attempt to estimate an unknown impulse response by adaptively giving gains proportionate to an estimate of the impulse response and the current measured error. These algorithms offer low computational complexity and fast convergence times for sparse impulse responses in network and acoustic echo cancellation applications. New PtNLMS algorithms are developed by choosing gains that optimize user-defined criteria, such as mean square error, at all times. PtNLMS algorithms ar
On root mean square approximation by exponential functions
Sharipov, Ruslan
2014-01-01
The problem of root mean square approximation of a square integrable function by finite linear combinations of exponential functions is considered. It is subdivided into linear and nonlinear parts. The linear approximation problem is solved. Then the nonlinear problem is studied in some particular example.
Comparison of Prediction-Error-Modelling Criteria
DEFF Research Database (Denmark)
Jørgensen, John Bagterp; Jørgensen, Sten Bay
2007-01-01
Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...
From Square Dance to Mathematics
Bremer, Zoe
2010-01-01
In this article, the author suggests a cross-curricular idea that can link with PE, dance, music and history. Teacher David Schmitz, a maths teacher in Illinois who was also a square dance caller, had developed a maths course that used the standard square dance syllabus to teach mathematical principles. He presents an intensive, two-week course…
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.
Latin-square three-dimensional gage master
Jones, L.
1981-05-12
A gage master for coordinate measuring machines has an nxn array of objects distributed in the Z coordinate utilizing the concept of a Latin square experimental design. Using analysis of variance techniques, the invention may be used to identify sources of error in machine geometry and quantify machine accuracy.
Noninteracting Fermi gas in a square-well potential.
Nash, C. E.
1971-01-01
The problem of a noninteracting Fermi gas in a finite square-well potential is solved analytically in the limit that the well becomes infinitely wide. The errors of previous authors using this model as a first approximation to the problem of a simple metal with surfaces are pointed out.
Counting Triangles to Sum Squares
DeMaio, Joe
2012-01-01
Counting complete subgraphs of three vertices in complete graphs, yields combinatorial arguments for identities for sums of squares of integers, odd integers, even integers and sums of the triangular numbers.
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
See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.
2018-04-01
This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.
A Weighted Least Squares Approach To Robustify Least Squares Estimates.
Lin, Chowhong; Davenport, Ernest C., Jr.
This study developed a robust linear regression technique based on the idea of weighted least squares. In this technique, a subsample of the full data of interest is drawn, based on a measure of distance, and an initial set of regression coefficients is calculated. The rest of the data points are then taken into the subsample, one after another,…
International Nuclear Information System (INIS)
Kiyko, V V; Kislov, V I; Ofitserov, E N
2015-01-01
In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)
Energy Technology Data Exchange (ETDEWEB)
Kiyko, V V; Kislov, V I; Ofitserov, E N [A M Prokhorov General Physics Institute, Russian Academy of Sciences, Moscow (Russian Federation)
2015-08-31
In the framework of a statistical model of an adaptive optics system (AOS) of phase conjugation, three algorithms based on an integrated mathematical approach are considered, each of them intended for minimisation of one of the following characteristics: the sensor error (in the case of an ideal corrector), the corrector error (in the case of ideal measurements) and the compensation error (with regard to discreteness and measurement noises and to incompleteness of a system of response functions of the corrector actuators). Functional and statistical relationships between the algorithms are studied and a relation is derived to ensure calculation of the mean-square compensation error as a function of the errors of the sensor and corrector with an accuracy better than 10%. Because in adjusting the AOS parameters, it is reasonable to proceed from the equality of the sensor and corrector errors, in the case the Hartmann sensor is used as a wavefront sensor, the required number of actuators in the absence of the noise component in the sensor error turns out 1.5 – 2.5 times less than the number of counts, and that difference grows with increasing measurement noise. (adaptive optics)
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.
Computational logic with square rings of nanomagnets
Arava, Hanu; Derlet, Peter M.; Vijayakumar, Jaianth; Cui, Jizhai; Bingham, Nicholas S.; Kleibert, Armin; Heyderman, Laura J.
2018-06-01
Nanomagnets are a promising low-power alternative to traditional computing. However, the successful implementation of nanomagnets in logic gates has been hindered so far by a lack of reliability. Here, we present a novel design with dipolar-coupled nanomagnets arranged on a square lattice to (i) support transfer of information and (ii) perform logic operations. We introduce a thermal protocol, using thermally active nanomagnets as a means to perform computation. Within this scheme, the nanomagnets are initialized by a global magnetic field and thermally relax on raising the temperature with a resistive heater. We demonstrate error-free transfer of information in chains of up to 19 square rings and we show a high level of reliability with successful gate operations of ∼94% across more than 2000 logic gates. Finally, we present a functionally complete prototype NAND/NOR logic gate that could be implemented for advanced logic operations. Here we support our experiments with simulations of the thermally averaged output and determine the optimal gate parameters. Our approach provides a new pathway to a long standing problem concerning reliability in the use of nanomagnets for computation.
Graphs whose complement and square are isomorphic
DEFF Research Database (Denmark)
Pedersen, Anders Sune
2014-01-01
We study square-complementary graphs, that is, graphs whose complement and square are isomorphic. We prove several necessary conditions for a graph to be square-complementary, describe ways of building new square-complementary graphs from existing ones, construct infinite families of square-compl...
Agglomerative clustering of growing squares
Castermans, Thom; Speckmann, Bettina; Staals, Frank; Verbeek, Kevin; Bender, M.A.; Farach-Colton, M.; Mosteiro, M.A.
2018-01-01
We study an agglomerative clustering problem motivated by interactive glyphs in geo-visualization. Consider a set of disjoint square glyphs on an interactive map. When the user zooms out, the glyphs grow in size relative to the map, possibly with different speeds. When two glyphs intersect, we wish
Multilevel weighted least squares polynomial approximation
Haji-Ali, Abdul-Lateef
2017-06-30
Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required to achieve quasi-optimal approximation in a given polynomial subspace scales, up to a logarithmic factor, linearly in the dimension of this space. However, in many applications, the computation of samples includes a numerical discretization error. Thus, obtaining polynomial approximations with a single level method can become prohibitively expensive, as it requires a sufficiently large number of samples, each computed with a sufficiently small discretization error. As a solution to this problem, we propose a multilevel method that utilizes samples computed with different accuracies and is able to match the accuracy of single-level approximations with reduced computational cost. We derive complexity bounds under certain assumptions about polynomial approximability and sample work. Furthermore, we propose an adaptive algorithm for situations where such assumptions cannot be verified a priori. Finally, we provide an efficient algorithm for the sampling from optimal distributions and an analysis of computationally favorable alternative distributions. Numerical experiments underscore the practical applicability of our method.
Radiation Field of a Square, Helical Beam Antenna
DEFF Research Database (Denmark)
Knudsen, Hans Lottrup
1952-01-01
square helices are used. Further, in connection with corresponding rigorous formulas for the field from a circular, helical antenna with a uniformly progressing current wave of constant amplitude the present formulas may be used for an investigation of the magnitude of the error introduced in Kraus......' approximate calculation of the field from a circular, helical antenna by replacing this antenna with an ``equivalent'' square helix. This investigation is carried out by means of a numerical example. The investigation shows that Kraus' approximate method of calculation yields results in fair agreement...
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.
On the Spatial and Temporal Sampling Errors of Remotely Sensed Precipitation Products
Directory of Open Access Journals (Sweden)
Ali Behrangi
2017-11-01
Full Text Available Observation with coarse spatial and temporal sampling can cause large errors in quantification of the amount, intensity, and duration of precipitation events. In this study, the errors resulting from temporal and spatial sampling of precipitation events were quantified and examined using the latest version (V4 of the Global Precipitation Measurement (GPM mission integrated multi-satellite retrievals for GPM (IMERG, which is available since spring of 2014. Relative mean square error was calculated at 0.1° × 0.1° every 0.5 h between the degraded (temporally and spatially and original IMERG products. The temporal and spatial degradation was performed by producing three-hour (T3, six-hour (T6, 0.5° × 0.5° (S5, and 1.0° × 1.0° (S10 maps. The results show generally larger errors over land than ocean, especially over mountainous regions. The relative error of T6 is almost 20% larger than T3 over tropical land, but is smaller in higher latitudes. Over land relative error of T6 is larger than S5 across all latitudes, while T6 has larger relative error than S10 poleward of 20°S–20°N. Similarly, the relative error of T3 exceeds S5 poleward of 20°S–20°N, but does not exceed S10, except in very high latitudes. Similar results are also seen over ocean, but the error ratios are generally less sensitive to seasonal changes. The results also show that the spatial and temporal relative errors are not highly correlated. Overall, lower correlations between the spatial and temporal relative errors are observed over ocean than over land. Quantification of such spatiotemporal effects provides additional insights into evaluation studies, especially when different products are cross-compared at a range of spatiotemporal scales.
Wilson, Celia M.
2010-01-01
Research pertaining to the distortion of the squared canonical correlation coefficient has traditionally been limited to the effects of sampling error and associated correction formulas. The purpose of this study was to compare the degree of attenuation of the squared canonical correlation coefficient under varying conditions of score reliability.…
Galerkin v. least-squares Petrov–Galerkin projection in nonlinear model reduction
International Nuclear Information System (INIS)
Carlberg, Kevin Thomas; Barone, Matthew F.; Antil, Harbir
2016-01-01
Least-squares Petrov–Galerkin (LSPG) model-reduction techniques such as the Gauss–Newton with Approximated Tensors (GNAT) method have shown promise, as they have generated stable, accurate solutions for large-scale turbulent, compressible flow problems where standard Galerkin techniques have failed. Furthermore, there has been limited comparative analysis of the two approaches. This is due in part to difficulties arising from the fact that Galerkin techniques perform optimal projection associated with residual minimization at the time-continuous level, while LSPG techniques do so at the time-discrete level. This work provides a detailed theoretical and computational comparison of the two techniques for two common classes of time integrators: linear multistep schemes and Runge–Kutta schemes. We present a number of new findings, including conditions under which the LSPG ROM has a time-continuous representation, conditions under which the two techniques are equivalent, and time-discrete error bounds for the two approaches. Perhaps most surprisingly, we demonstrate both theoretically and computationally that decreasing the time step does not necessarily decrease the error for the LSPG ROM; instead, the time step should be ‘matched’ to the spectral content of the reduced basis. In numerical experiments carried out on a turbulent compressible-flow problem with over one million unknowns, we show that increasing the time step to an intermediate value decreases both the error and the simulation time of the LSPG reduced-order model by an order of magnitude.
A FORTRAN program for a least-square fitting
International Nuclear Information System (INIS)
Yamazaki, Tetsuo
1978-01-01
A practical FORTRAN program for a least-squares fitting is presented. Although the method is quite usual, the program calculates not only the most satisfactory set of values of unknowns but also the plausible errors associated with them. As an example, a measured lateral absorbed-dose distribution in water for a narrow 25-MeV electron beam is fitted to a Gaussian distribution. (auth.)
Conjugate descent formulation of backpropagation error in ...
African Journals Online (AJOL)
The feedforward neural network architecture uses backpropagation learning to determine optimal weights between dierent interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to ...
DEFF Research Database (Denmark)
Emerek, Ruth
2004-01-01
Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration......Bidraget diskuterer de forskellige intergrationsopfattelse i Danmark - og hvad der kan forstås ved vellykket integration...
Fullwood, James; Wang, Dongxu
2018-01-01
We introduce a class of F-theory vacua whose smooth elliptic fibers admit a vanishing $j$-invariant, and construct a weak coupling limit associated with such vacua which we view as the `square' of the Sen limit. We find that while Sen's limit is naturally viewed as an orientifold theory, the universal tadpole relation which equates the D3 charge between the associated F-theory compactification and the limit we construct suggests that perhaps the limiting theory is in fact an oriented theory c...
Renaming Zagreb Streets and Squares
Directory of Open Access Journals (Sweden)
Jelena Stanić
2009-06-01
Full Text Available The paper deals with changes in street names in the city of Zagreb. Taking the Lower Town (Donji grad city area as an example, the first part of the paper analyses diachronic street name changes commencing from the systematic naming of streets in 1878. Analysis of official changes in street names throughout Zagreb’s history resulted in categorisation of five periods of ideologically motivated naming/name-changing: 1. the Croatia modernisation period, when the first official naming was put into effect, with a marked tendency towards politicisation and nationalisation of the urban landscape; 2. the period of the Kingdom of the Serbs, Croatians and Slovenians/Yugoslavia, when symbols of the new monarchy, the idea of the fellowship of the Southern Slavs, Slavenophilism and the pro-Slavic geopolitical orientation were incorporated into the street names, and when the national idea was highly evident and remained so in that process; 3. the period of the NDH, the Independent State of Croatia, with decanonisation of the tokens of the Yugoslavian monarchy and the Southern Slavic orientation, and reference to the Ustashi and the German Nazi and Italian Fascist movement; 4. the period of Socialism, embedding the ideals and heroes of the workers’ movement and the War of National Liberation into the canonical system; and, 5. the period following the democratic changes in 1990, when almost all the signs of Socialism and the Communist/Antifascist struggle were erased, with the prominent presence of a process of installing new references to early national culture and historical tradition. The closing part of the paper deals with public discussions connected with the selection of a location for a square to bear the name of the first president of independent Croatia, Franjo Tuđman. Analysis of these public polemics shows two opposing discourses: the right-wing political option, which supports a central position for the square and considers the chosen area to
Latin squares and their applications
Keedwell, A Donald
2015-01-01
Latin Squares and Their Applications Second edition offers a long-awaited update and reissue of this seminal account of the subject. The revision retains foundational, original material from the frequently-cited 1974 volume but is completely updated throughout. As with the earlier version, the author hopes to take the reader 'from the beginnings of the subject to the frontiers of research'. By omitting a few topics which are no longer of current interest, the book expands upon active and emerging areas. Also, the present state of knowledge regarding the 73 then-unsolved problems given at the
Fang, Fang; Ni, Bing-Jie; Yu, Han-Qing
2009-06-01
In this study, weighted non-linear least-squares analysis and accelerating genetic algorithm are integrated to estimate the kinetic parameters of substrate consumption and storage product formation of activated sludge. A storage product formation equation is developed and used to construct the objective function for the determination of its production kinetics. The weighted least-squares analysis is employed to calculate the differences in the storage product concentration between the model predictions and the experimental data as the sum of squared weighted errors. The kinetic parameters for the substrate consumption and the storage product formation are estimated to be the maximum heterotrophic growth rate of 0.121/h, the yield coefficient of 0.44 mg CODX/mg CODS (COD, chemical oxygen demand) and the substrate half saturation constant of 16.9 mg/L, respectively, by minimizing the objective function using a real-coding-based accelerating genetic algorithm. Also, the fraction of substrate electrons diverted to the storage product formation is estimated to be 0.43 mg CODSTO/mg CODS. The validity of our approach is confirmed by the results of independent tests and the kinetic parameter values reported in literature, suggesting that this approach could be useful to evaluate the product formation kinetics of mixed cultures like activated sludge. More importantly, as this integrated approach could estimate the kinetic parameters rapidly and accurately, it could be applied to other biological processes.
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...
Energy Technology Data Exchange (ETDEWEB)
Menemenlis, N.; Huneault, M. [IREQ, Varennes, QC (Canada); Robitaille, A. [Dir. Plantif. de la Production Eolienne, Montreal, QC (Canada). HQ Production; Holttinen, H. [VTT Technical Research Centre of Finland, VTT (Finland)
2012-07-01
This In this paper we define and characterize the two random variables, variability and forecast error, over which uncertainty in power systems operations is characterized and mitigated. We show that the characterization of both these variables can be carried out with the same mathematical tools. Furthermore, this common characterization of random variables lends itself to a common methodology for the calculation of non-contingency reserves required to mitigate their effects. A parallel comparison of these two variables demonstrates similar inherent statistical properties. They depend on imminent conditions, evolve with time and can be asymmetric. Correlation is an important factor when aggregating individual wind farm characteristics in forming the distribution of the total wind generation for imminent conditions. (orig.)
Applying Intelligent Algorithms to Automate the Identification of Error Factors.
Jin, Haizhe; Qu, Qingxing; Munechika, Masahiko; Sano, Masataka; Kajihara, Chisato; Duffy, Vincent G; Chen, Han
2018-05-03
Medical errors are the manifestation of the defects occurring in medical processes. Extracting and identifying defects as medical error factors from these processes are an effective approach to prevent medical errors. However, it is a difficult and time-consuming task and requires an analyst with a professional medical background. The issues of identifying a method to extract medical error factors and reduce the extraction difficulty need to be resolved. In this research, a systematic methodology to extract and identify error factors in the medical administration process was proposed. The design of the error report, extraction of the error factors, and identification of the error factors were analyzed. Based on 624 medical error cases across four medical institutes in both Japan and China, 19 error-related items and their levels were extracted. After which, they were closely related to 12 error factors. The relational model between the error-related items and error factors was established based on a genetic algorithm (GA)-back-propagation neural network (BPNN) model. Additionally, compared to GA-BPNN, BPNN, partial least squares regression and support vector regression, GA-BPNN exhibited a higher overall prediction accuracy, being able to promptly identify the error factors from the error-related items. The combination of "error-related items, their different levels, and the GA-BPNN model" was proposed as an error-factor identification technology, which could automatically identify medical error factors.
Forecasting Error Calculation with Mean Absolute Deviation and Mean Absolute Percentage Error
Khair, Ummul; Fahmi, Hasanul; Hakim, Sarudin Al; Rahim, Robbi
2017-12-01
Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.
Gómez Rodríguez, Rafael Ángel
2014-01-01
To say that someone possesses integrity is to claim that that person is almost predictable about responses to specific situations, that he or she can prudentially judge and to act correctly. There is a closed interrelationship between integrity and autonomy, and the autonomy rests on the deeper moral claim of all humans to integrity of the person. Integrity has two senses of significance for medical ethic: one sense refers to the integrity of the person in the bodily, psychosocial and intellectual elements; and in the second sense, the integrity is the virtue. Another facet of integrity of the person is la integrity of values we cherish and espouse. The physician must be a person of integrity if the integrity of the patient is to be safeguarded. The autonomy has reduced the violations in the past, but the character and virtues of the physician are the ultimate safeguard of autonomy of patient. A field very important in medicine is the scientific research. It is the character of the investigator that determines the moral quality of research. The problem arises when legitimate self-interests are replaced by selfish, particularly when human subjects are involved. The final safeguard of moral quality of research is the character and conscience of the investigator. Teaching must be relevant in the scientific field, but the most effective way to teach virtue ethics is through the example of the a respected scientist.
Regularized plane-wave least-squares Kirchhoff migration
Wang, Xin
2013-09-22
A Kirchhoff least-squares migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images. A regularization term is included that accounts for mispositioning of reflectors due to errors in the velocity model. Both synthetic and field results show that: 1) LSM with a reflectivity model common for all the plane-wave gathers provides the best image when the migration velocity model is accurate, but it is more sensitive to the velocity errors, 2) the regularized plane-wave LSM is more robust in the presence of velocity errors, and 3) LSM achieves both computational and IO saving by plane-wave encoding compared to shot-domain LSM for the models tested.
Elastic least-squares reverse time migration
Feng, Zongcai
2017-03-08
We use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P- and S-wave impedances. Elastic LSRTMsolves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and amplitude balancing, fewer artifacts, and less crosstalk compared with the elastic RTM images. The images are also better focused and have better reflector continuity for steeply dipping events compared to the acoustic LSRTM images. Similar to conventional leastsquares migration, elastic LSRTM also requires an accurate estimation of the P- and S-wave migration velocity models. However, the problem remains that, when there are moderate errors in the velocity model and strong multiples, LSRTMwill produce migration noise stronger than that seen in the RTM images.
Elastic least-squares reverse time migration
Feng, Zongcai; Schuster, Gerard T.
2017-01-01
We use elastic least-squares reverse time migration (LSRTM) to invert for the reflectivity images of P- and S-wave impedances. Elastic LSRTMsolves the linearized elastic-wave equations for forward modeling and the adjoint equations for backpropagating the residual wavefield at each iteration. Numerical tests on synthetic data and field data reveal the advantages of elastic LSRTM over elastic reverse time migration (RTM) and acoustic LSRTM. For our examples, the elastic LSRTM images have better resolution and amplitude balancing, fewer artifacts, and less crosstalk compared with the elastic RTM images. The images are also better focused and have better reflector continuity for steeply dipping events compared to the acoustic LSRTM images. Similar to conventional leastsquares migration, elastic LSRTM also requires an accurate estimation of the P- and S-wave migration velocity models. However, the problem remains that, when there are moderate errors in the velocity model and strong multiples, LSRTMwill produce migration noise stronger than that seen in the RTM images.
Squares of Random Linear Codes
DEFF Research Database (Denmark)
Cascudo Pueyo, Ignacio; Cramer, Ronald; Mirandola, Diego
2015-01-01
a positive answer, for codes of dimension $k$ and length roughly $\\frac{1}{2}k^2$ or smaller. Moreover, the convergence speed is exponential if the difference $k(k+1)/2-n$ is at least linear in $k$. The proof uses random coding and combinatorial arguments, together with algebraic tools involving the precise......Given a linear code $C$, one can define the $d$-th power of $C$ as the span of all componentwise products of $d$ elements of $C$. A power of $C$ may quickly fill the whole space. Our purpose is to answer the following question: does the square of a code ``typically'' fill the whole space? We give...
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.
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...
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.
36 CFR 910.67 - Square guidelines.
2010-07-01
... 36 Parks, Forests, and Public Property 3 2010-07-01 2010-07-01 false Square guidelines. 910.67... GUIDELINES AND UNIFORM STANDARDS FOR URBAN PLANNING AND DESIGN OF DEVELOPMENT WITHIN THE PENNSYLVANIA AVENUE DEVELOPMENT AREA Glossary of Terms § 910.67 Square guidelines. Square Guidelines establish the Corporation's...
Learning mechanisms to limit medication administration errors.
Drach-Zahavy, Anat; Pud, Dorit
2010-04-01
This paper is a report of a study conducted to identify and test the effectiveness of learning mechanisms applied by the nursing staff of hospital wards as a means of limiting medication administration errors. Since the influential report ;To Err Is Human', research has emphasized the role of team learning in reducing medication administration errors. Nevertheless, little is known about the mechanisms underlying team learning. Thirty-two hospital wards were randomly recruited. Data were collected during 2006 in Israel by a multi-method (observations, interviews and administrative data), multi-source (head nurses, bedside nurses) approach. Medication administration error was defined as any deviation from procedures, policies and/or best practices for medication administration, and was identified using semi-structured observations of nurses administering medication. Organizational learning was measured using semi-structured interviews with head nurses, and the previous year's reported medication administration errors were assessed using administrative data. The interview data revealed four learning mechanism patterns employed in an attempt to learn from medication administration errors: integrated, non-integrated, supervisory and patchy learning. Regression analysis results demonstrated that whereas the integrated pattern of learning mechanisms was associated with decreased errors, the non-integrated pattern was associated with increased errors. Supervisory and patchy learning mechanisms were not associated with errors. Superior learning mechanisms are those that represent the whole cycle of team learning, are enacted by nurses who administer medications to patients, and emphasize a system approach to data analysis instead of analysis of individual cases.
Multisource Least-squares Reverse Time Migration
Dai, Wei
2012-12-01
Least-squares migration has been shown to be able to produce high quality migration images, but its computational cost is considered to be too high for practical imaging. In this dissertation, a multisource least-squares reverse time migration algorithm (LSRTM) is proposed to increase by up to 10 times the computational efficiency by utilizing the blended sources processing technique. There are three main chapters in this dissertation. In Chapter 2, the multisource LSRTM algorithm is implemented with random time-shift and random source polarity encoding functions. Numerical tests on the 2D HESS VTI data show that the multisource LSRTM algorithm suppresses migration artifacts, balances the amplitudes, improves image resolution, and reduces crosstalk noise associated with the blended shot gathers. For this example, multisource LSRTM is about three times faster than the conventional RTM method. For the 3D example of the SEG/EAGE salt model, with comparable computational cost, multisource LSRTM produces images with more accurate amplitudes, better spatial resolution, and fewer migration artifacts compared to conventional RTM. The empirical results suggest that the multisource LSRTM can produce more accurate reflectivity images than conventional RTM does with similar or less computational cost. The caveat is that LSRTM image is sensitive to large errors in the migration velocity model. In Chapter 3, the multisource LSRTM algorithm is implemented with frequency selection encoding strategy and applied to marine streamer data, for which traditional random encoding functions are not applicable. The frequency-selection encoding functions are delta functions in the frequency domain, so that all the encoded shots have unique non-overlapping frequency content. Therefore, the receivers can distinguish the wavefield from each shot according to the frequencies. With the frequency-selection encoding method, the computational efficiency of LSRTM is increased so that its cost is
A method based on moving least squares for XRII image distortion correction
International Nuclear Information System (INIS)
Yan Shiju; Wang Chengtao; Ye Ming
2007-01-01
This paper presents a novel integrated method to correct geometric distortions of XRII (x-ray image intensifier) images. The method has been compared, in terms of mean-squared residual error measured at control and intermediate points, with two traditional local methods and a traditional global methods. The proposed method is based on the methods of moving least squares (MLS) and polynomial fitting. Extensive experiments were performed on simulated and real XRII images. In simulation, the effect of pincushion distortion, sigmoidal distortion, local distortion, noise, and the number of control points was tested. The traditional local methods were sensitive to pincushion and sigmoidal distortion. The traditional global method was only sensitive to sigmoidal distortion. The proposed method was found neither sensitive to pincushion distortion nor sensitive to sigmoidal distortion. The sensitivity of the proposed method to local distortion was lower than or comparable with that of the traditional global method. The sensitivity of the proposed method to noise was higher than that of all three traditional methods. Nevertheless, provided the standard deviation of noise was not greater than 0.1 pixels, accuracy of the proposed method is still higher than the traditional methods. The sensitivity of the proposed method to the number of control points was greatly lower than that of the traditional methods. Provided that a proper cutoff radius is chosen, accuracy of the proposed method is higher than that of the traditional methods. Experiments on real images, carried out by using a 9 in. XRII, showed that residual error of the proposed method (0.2544±0.2479 pixels) is lower than that of the traditional global method (0.4223±0.3879 pixels) and local methods (0.4555±0.3518 pixels and 0.3696±0.4019 pixels, respectively)
Quantifying and handling errors in instrumental measurements using the measurement error theory
DEFF Research Database (Denmark)
Andersen, Charlotte Møller; Bro, R.; Brockhoff, P.B.
2003-01-01
. This is a new way of using the measurement error theory. Reliability ratios illustrate that the models for the two fish species are influenced differently by the error. However, the error seems to influence the predictions of the two reference measures in the same way. The effect of using replicated x...... measurements. A new general formula is given for how to correct the least squares regression coefficient when a different number of replicated x-measurements is used for prediction than for calibration. It is shown that the correction should be applied when the number of replicates in prediction is less than...
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.
Migliorati, Giovanni
2015-08-28
We study the accuracy of the discrete least-squares approximation on a finite dimensional space of a real-valued target function from noisy pointwise evaluations at independent random points distributed according to a given sampling probability measure. The convergence estimates are given in mean-square sense with respect to the sampling measure. The noise may be correlated with the location of the evaluation and may have nonzero mean (offset). We consider both cases of bounded or square-integrable noise / offset. We prove conditions between the number of sampling points and the dimension of the underlying approximation space that ensure a stable and accurate approximation. Particular focus is on deriving estimates in probability within a given confidence level. We analyze how the best approximation error and the noise terms affect the convergence rate and the overall confidence level achieved by the convergence estimate. The proofs of our convergence estimates in probability use arguments from the theory of large deviations to bound the noise term. Finally we address the particular case of multivariate polynomial approximation spaces with any density in the beta family, including uniform and Chebyshev.
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.
Estimating Frequency by Interpolation Using Least Squares Support Vector Regression
Directory of Open Access Journals (Sweden)
Changwei Ma
2015-01-01
Full Text Available Discrete Fourier transform- (DFT- based maximum likelihood (ML algorithm is an important part of single sinusoid frequency estimation. As signal to noise ratio (SNR increases and is above the threshold value, it will lie very close to Cramer-Rao lower bound (CRLB, which is dependent on the number of DFT points. However, its mean square error (MSE performance is directly proportional to its calculation cost. As a modified version of support vector regression (SVR, least squares SVR (LS-SVR can not only still keep excellent capabilities for generalizing and fitting but also exhibit lower computational complexity. In this paper, therefore, LS-SVR is employed to interpolate on Fourier coefficients of received signals and attain high frequency estimation accuracy. Our results show that the proposed algorithm can make a good compromise between calculation cost and MSE performance under the assumption that the sample size, number of DFT points, and resampling points are already known.
Square pulse linear transformer driver
Directory of Open Access Journals (Sweden)
A. A. Kim
2012-04-01
Full Text Available The linear transformer driver (LTD technological approach can result in relatively compact devices that can deliver fast, high current, and high-voltage pulses straight out of the LTD cavity without any complicated pulse forming and pulse compression network. Through multistage inductively insulated voltage adders, the output pulse, increased in voltage amplitude, can be applied directly to the load. The usual LTD architecture [A. A. Kim, M. G. Mazarakis, V. A. Sinebryukhov, B. M. Kovalchuk, V. A. Vizir, S. N Volkov, F. Bayol, A. N. Bastrikov, V. G. Durakov, S. V. Frolov, V. M. Alexeenko, D. H. McDaniel, W. E. Fowler, K. LeCheen, C. Olson, W. A. Stygar, K. W. Struve, J. Porter, and R. M. Gilgenbach, Phys. Rev. ST Accel. Beams 12, 050402 (2009PRABFM1098-440210.1103/PhysRevSTAB.12.050402; M. G. Mazarakis, W. E. Fowler, A. A. Kim, V. A. Sinebryukhov, S. T. Rogowski, R. A. Sharpe, D. H. McDaniel, C. L. Olson, J. L. Porter, K. W. Struve, W. A. Stygar, and J. R. Woodworth, Phys. Rev. ST Accel. Beams 12, 050401 (2009PRABFM1098-440210.1103/PhysRevSTAB.12.050401] provides sine shaped output pulses that may not be well suited for some applications like z-pinch drivers, flash radiography, high power microwaves, etc. A more suitable power pulse would have a flat or trapezoidal (rising or falling top. In this paper, we present the design and first test results of an LTD cavity that generates such a type of output pulse by including within its circular array a number of third harmonic bricks in addition to the main bricks. A voltage adder made out of a square pulse cavity linear array will produce the same shape output pulses provided that the timing of each cavity is synchronized with the propagation of the electromagnetic pulse.
Zhang, Ling; Cai, Yunlong; Li, Chunguang; de Lamare, Rodrigo C.
2017-12-01
In this work, we present low-complexity variable forgetting factor (VFF) techniques for diffusion recursive least squares (DRLS) algorithms. Particularly, we propose low-complexity VFF-DRLS algorithms for distributed parameter and spectrum estimation in sensor networks. For the proposed algorithms, they can adjust the forgetting factor automatically according to the posteriori error signal. We develop detailed analyses in terms of mean and mean square performance for the proposed algorithms and derive mathematical expressions for the mean square deviation (MSD) and the excess mean square error (EMSE). The simulation results show that the proposed low-complexity VFF-DRLS algorithms achieve superior performance to the existing DRLS algorithm with fixed forgetting factor when applied to scenarios of distributed parameter and spectrum estimation. Besides, the simulation results also demonstrate a good match for our proposed analytical expressions.
Child- and elder-friendly urban public places in Fatahillah Square Historical District
Srinaga, F.; LKatoppo, M.; Hidayat, J.
2018-03-01
Fatahillah square as an important historical urban square in Jakarta has problems in eye level area integrative processing. Visitors cannot enjoy their time while in the square regarding their visuals, feelings, space, and bodies comfort. These also lead to other problems in which the square is lack of friendly and convenient places for children, the elderly and also the disabled, especially people with limited moving space. The research will attempt in proposing design inception for the Fatahillah Square that is using inclusive user-centered design approach, while in the same time incorporate theoretical studies of children and elderly-design considerations. The first stage of this research was building inclusive design parameter; begin with a context-led research which assesses the quality of Fatahillah square through three basic components of urban space: hardware, software and orgware. The second stage of this research is to propose inclusive design inception for the Fatahillah square.
Wang, Weijie; Lu, Yanmin
2018-03-01
Most existing Collaborative Filtering (CF) algorithms predict a rating as the preference of an active user toward a given item, which is always a decimal fraction. Meanwhile, the actual ratings in most data sets are integers. In this paper, we discuss and demonstrate why rounding can bring different influences to these two metrics; prove that rounding is necessary in post-processing of the predicted ratings, eliminate of model prediction bias, improving the accuracy of the prediction. In addition, we also propose two new rounding approaches based on the predicted rating probability distribution, which can be used to round the predicted rating to an optimal integer rating, and get better prediction accuracy compared to the Basic Rounding approach. Extensive experiments on different data sets validate the correctness of our analysis and the effectiveness of our proposed rounding approaches.
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.
Application of square-root filtering for spacecraft attitude control
Sorensen, J. A.; Schmidt, S. F.; Goka, T.
1978-01-01
Suitable digital algorithms are developed and tested for providing on-board precision attitude estimation and pointing control for potential use in the Landsat-D spacecraft. These algorithms provide pointing accuracy of better than 0.01 deg. To obtain necessary precision with efficient software, a six state-variable square-root Kalman filter combines two star tracker measurements to update attitude estimates obtained from processing three gyro outputs. The validity of the estimation and control algorithms are established, and the sensitivity of their performance to various error sources and software parameters are investigated by detailed digital simulation. Spacecraft computer memory, cycle time, and accuracy requirements are estimated.
Positive Scattering Cross Sections using Constrained Least Squares
International Nuclear Information System (INIS)
Dahl, J.A.; Ganapol, B.D.; Morel, J.E.
1999-01-01
A method which creates a positive Legendre expansion from truncated Legendre cross section libraries is presented. The cross section moments of order two and greater are modified by a constrained least squares algorithm, subject to the constraints that the zeroth and first moments remain constant, and that the standard discrete ordinate scattering matrix is positive. A method using the maximum entropy representation of the cross section which reduces the error of these modified moments is also presented. These methods are implemented in PARTISN, and numerical results from a transport calculation using highly anisotropic scattering cross sections with the exponential discontinuous spatial scheme is presented
Bhadra, Anindya; Carroll, Raymond J
2016-07-01
In truncated polynomial spline or B-spline models where the covariates are measured with error, a fully Bayesian approach to model fitting requires the covariates and model parameters to be sampled at every Markov chain Monte Carlo iteration. Sampling the unobserved covariates poses a major computational problem and usually Gibbs sampling is not possible. This forces the practitioner to use a Metropolis-Hastings step which might suffer from unacceptable performance due to poor mixing and might require careful tuning. In this article we show for the cases of truncated polynomial spline or B-spline models of degree equal to one, the complete conditional distribution of the covariates measured with error is available explicitly as a mixture of double-truncated normals, thereby enabling a Gibbs sampling scheme. We demonstrate via a simulation study that our technique performs favorably in terms of computational efficiency and statistical performance. Our results indicate up to 62 and 54 % increase in mean integrated squared error efficiency when compared to existing alternatives while using truncated polynomial splines and B-splines respectively. Furthermore, there is evidence that the gain in efficiency increases with the measurement error variance, indicating the proposed method is a particularly valuable tool for challenging applications that present high measurement error. We conclude with a demonstration on a nutritional epidemiology data set from the NIH-AARP study and by pointing out some possible extensions of the current work.
Sets of Mutually Orthogonal Sudoku Latin Squares
Vis, Timothy; Petersen, Ryan M.
2009-01-01
A Latin square of order "n" is an "n" x "n" array using n symbols, such that each symbol appears exactly once in each row and column. A set of Latin squares is c ordered pairs of symbols appearing in the cells of the array are distinct. The popular puzzle Sudoku involves Latin squares with n = 9, along with the added condition that each of the 9…
The Square Light Clock and Special Relativity
Galli, J. Ronald; Amiri, Farhang
2012-01-01
A thought experiment that includes a square light clock is similar to the traditional vertical light beam and mirror clock, except it is made up of four mirrors placed at a 45[degree] angle at each corner of a square of length L[subscript 0], shown in Fig. 1. Here we have shown the events as measured in the rest frame of the square light clock. By…
International Nuclear Information System (INIS)
Hughes, T.J.R.; Hulbert, G.M.; Franca, L.P.
1988-10-01
Galerkin/least-squares finite element methods are presented for advective-diffusive equations. Galerkin/least-squares represents a conceptual simplification of SUPG, and is in fact applicable to a wide variety of other problem types. A convergence analysis and error estimates are presented. (author) [pt
International Nuclear Information System (INIS)
Leng Ling; Zhang Tianyi; Kleinman, Lawrence; Zhu Wei
2007-01-01
Regression analysis, especially the ordinary least squares method which assumes that errors are confined to the dependent variable, has seen a fair share of its applications in aerosol science. The ordinary least squares approach, however, could be problematic due to the fact that atmospheric data often does not lend itself to calling one variable independent and the other dependent. Errors often exist for both measurements. In this work, we examine two regression approaches available to accommodate this situation. They are orthogonal regression and geometric mean regression. Comparisons are made theoretically as well as numerically through an aerosol study examining whether the ratio of organic aerosol to CO would change with age
Analysis of total least squares in estimating the parameters of a mortar trajectory
Energy Technology Data Exchange (ETDEWEB)
Lau, D.L.; Ng, L.C.
1994-12-01
Least Squares (LS) is a method of curve fitting used with the assumption that error exists in the observation vector. The method of Total Least Squares (TLS) is more useful in cases where there is error in the data matrix as well as the observation vector. This paper describes work done in comparing the LS and TLS results for parameter estimation of a mortar trajectory based on a time series of angular observations. To improve the results, we investigated several derivations of the LS and TLS methods, and early findings show TLS provided slightly, 10%, improved results over the LS method.
Dose rate from the square volume radiation source
International Nuclear Information System (INIS)
Karpov, V.I.
1978-01-01
The expression for determining the dose rate from a three-dimensional square flat-parallel source of any dimensions is obtained. A simplified method for integrating the resultant expression is proposed. A comparison of the calculation results with the results by the Monte Carlo method has shown them to coincide within 6-8%. Since buildings and structures consist of rectangular elements, the method is recommended for practical calculations of dose rates in residential buildings
Comparing implementations of penalized weighted least-squares sinogram restoration
International Nuclear Information System (INIS)
Forthmann, Peter; Koehler, Thomas; Defrise, Michel; La Riviere, Patrick
2010-01-01
Purpose: A CT scanner measures the energy that is deposited in each channel of a detector array by x rays that have been partially absorbed on their way through the object. The measurement process is complex and quantitative measurements are always and inevitably associated with errors, so CT data must be preprocessed prior to reconstruction. In recent years, the authors have formulated CT sinogram preprocessing as a statistical restoration problem in which the goal is to obtain the best estimate of the line integrals needed for reconstruction from the set of noisy, degraded measurements. The authors have explored both penalized Poisson likelihood (PL) and penalized weighted least-squares (PWLS) objective functions. At low doses, the authors found that the PL approach outperforms PWLS in terms of resolution-noise tradeoffs, but at standard doses they perform similarly. The PWLS objective function, being quadratic, is more amenable to computational acceleration than the PL objective. In this work, the authors develop and compare two different methods for implementing PWLS sinogram restoration with the hope of improving computational performance relative to PL in the standard-dose regime. Sinogram restoration is still significant in the standard-dose regime since it can still outperform standard approaches and it allows for correction of effects that are not usually modeled in standard CT preprocessing. Methods: The authors have explored and compared two implementation strategies for PWLS sinogram restoration: (1) A direct matrix-inversion strategy based on the closed-form solution to the PWLS optimization problem and (2) an iterative approach based on the conjugate-gradient algorithm. Obtaining optimal performance from each strategy required modifying the naive off-the-shelf implementations of the algorithms to exploit the particular symmetry and sparseness of the sinogram-restoration problem. For the closed-form approach, the authors subdivided the large matrix
DEFF Research Database (Denmark)
Olwig, Karen Fog
2011-01-01
, while the countries have adopted disparate policies and ideologies, differences in the actual treatment and attitudes towards immigrants and refugees in everyday life are less clear, due to parallel integration programmes based on strong similarities in the welfare systems and in cultural notions...... of equality in the three societies. Finally, it shows that family relations play a central role in immigrants’ and refugees’ establishment of a new life in the receiving societies, even though the welfare society takes on many of the social and economic functions of the family....
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.
Distribution of squares modulo a composite number
Aryan, Farzad
2015-01-01
In this paper we study the distribution of squares modulo a square-free number $q$. We also look at inverse questions for the large sieve in the distribution aspect and we make improvements on existing results on the distribution of $s$-tuples of reduced residues.
Some Theoretical Essences of Lithuania Squares Formation
Directory of Open Access Journals (Sweden)
Gintautas Tiškus
2016-04-01
Full Text Available In the Lithuanian acts of law and in the scientific literature there are no clear criteria and notions to define a square. The unbuilt city space places or the gaps between buildings are often defined as the squares, which do not have clear limits or destination. The mandatory attributes of the place which is called the square are indicated in the article, the notion of square is defined. The article deals with Lithuanian squares theme, analyses the differences between representation and representativeness. The article aims to indicate an influence of city environmental context and monument in the square on its function. The square is an independent element of city plan structure, but it is not an independent element of city spatial structure. The space and environment of the square are related to each other not only by physical, aesthetical relations, but as well as by causalities, which may be named as the essences of squares’ formation. The interdisciplinary discourse analysis method is applied in the article.
Entrywise Squared Transforms for GAMP Supplementary Material
DEFF Research Database (Denmark)
2016-01-01
Supplementary material for a study on Entrywise Squared Transforms for Generalized Approximate Message Passing (GAMP). See the README file for the details.......Supplementary material for a study on Entrywise Squared Transforms for Generalized Approximate Message Passing (GAMP). See the README file for the details....
Lagrange’s Four-Square Theorem
Directory of Open Access Journals (Sweden)
Watase Yasushige
2015-02-01
Full Text Available This article provides a formalized proof of the so-called “the four-square theorem”, namely any natural number can be expressed by a sum of four squares, which was proved by Lagrange in 1770. An informal proof of the theorem can be found in the number theory literature, e.g. in [14], [1] or [23].
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...
Directory of Open Access Journals (Sweden)
Ming Yang
2018-03-01
Full Text Available In this paper, an on-line parameter identification algorithm to iteratively compute the numerical values of inertia and load torque is proposed. Since inertia and load torque are strongly coupled variables due to the degenerate-rank problem, it is hard to estimate relatively accurate values for them in the cases such as when load torque variation presents or one cannot obtain a relatively accurate priori knowledge of inertia. This paper eliminates this problem and realizes ideal online inertia identification regardless of load condition and initial error. The algorithm in this paper integrates a full-order Kalman Observer and Recursive Least Squares, and introduces adaptive controllers to enhance the robustness. It has a better performance when iteratively computing load torque and moment of inertia. Theoretical sensitivity analysis of the proposed algorithm is conducted. Compared to traditional methods, the validity of the proposed algorithm is proved by simulation and experiment results.
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.)
Plane-wave least-squares reverse-time migration
Dai, Wei
2013-06-03
A plane-wave least-squares reverse-time migration (LSRTM) is formulated with a new parameterization, where the migration image of each shot gather is updated separately and an ensemble of prestack images is produced along with common image gathers. The merits of plane-wave prestack LSRTM are the following: (1) plane-wave prestack LSRTM can sometimes offer stable convergence even when the migration velocity has bulk errors of up to 5%; (2) to significantly reduce computation cost, linear phase-shift encoding is applied to hundreds of shot gathers to produce dozens of plane waves. Unlike phase-shift encoding with random time shifts applied to each shot gather, plane-wave encoding can be effectively applied to data with a marine streamer geometry. (3) Plane-wave prestack LSRTM can provide higher-quality images than standard reverse-time migration. Numerical tests on the Marmousi2 model and a marine field data set are performed to illustrate the benefits of plane-wave LSRTM. Empirical results show that LSRTM in the plane-wave domain, compared to standard reversetime migration, produces images efficiently with fewer artifacts and better spatial resolution. Moreover, the prestack image ensemble accommodates more unknowns to makes it more robust than conventional least-squares migration in the presence of migration velocity errors. © 2013 Society of Exploration Geophysicists.
Testing and tuning symplectic integrators for the hybrid Monte Carlo algorithm in lattice QCD
International Nuclear Information System (INIS)
Takaishi, Tetsuya; Forcrand, Philippe de
2006-01-01
We examine a new second-order integrator recently found by Omelyan et al. The integration error of the new integrator measured in the root mean square of the energy difference, 2 > 1/2 , is about 10 times smaller than that of the standard second-order leapfrog (2LF) integrator. As a result, the step size of the new integrator can be made about three times larger. Taking into account a factor 2 increase in cost, the new integrator is about 50% more efficient than the 2LF integrator. Integrating over positions first, then momenta, is slightly more advantageous than the reverse. Further parameter tuning is possible. We find that the optimal parameter for the new integrator is slightly different from the value obtained by Omelyan et al., and depends on the simulation parameters. This integrator could also be advantageous for the Trotter-Suzuki decomposition in quantum Monte Carlo
Regularization Techniques for Linear Least-Squares Problems
Suliman, Mohamed
2016-04-01
Linear estimation is a fundamental branch of signal processing that deals with estimating the values of parameters from a corrupted measured data. Throughout the years, several optimization criteria have been used to achieve this task. The most astonishing attempt among theses is the linear least-squares. Although this criterion enjoyed a wide popularity in many areas due to its attractive properties, it appeared to suffer from some shortcomings. Alternative optimization criteria, as a result, have been proposed. These new criteria allowed, in one way or another, the incorporation of further prior information to the desired problem. Among theses alternative criteria is the regularized least-squares (RLS). In this thesis, we propose two new algorithms to find the regularization parameter for linear least-squares problems. In the constrained perturbation regularization algorithm (COPRA) for random matrices and COPRA for linear discrete ill-posed problems, an artificial perturbation matrix with a bounded norm is forced into the model matrix. This perturbation is introduced to enhance the singular value structure of the matrix. As a result, the new modified model is expected to provide a better stabilize substantial solution when used to estimate the original signal through minimizing the worst-case residual error function. Unlike many other regularization algorithms that go in search of minimizing the estimated data error, the two new proposed algorithms are developed mainly to select the artifcial perturbation bound and the regularization parameter in a way that approximately minimizes the mean-squared error (MSE) between the original signal and its estimate under various conditions. The first proposed COPRA method is developed mainly to estimate the regularization parameter when the measurement matrix is complex Gaussian, with centered unit variance (standard), and independent and identically distributed (i.i.d.) entries. Furthermore, the second proposed COPRA
Weighted Littlewood-Paley theory and exponential-square integrability
Wilson, Michael
2008-01-01
Littlewood-Paley theory is an essential tool of Fourier analysis, with applications and connections to PDEs, signal processing, and probability. It extends some of the benefits of orthogonality to situations where orthogonality doesn’t really make sense. It does so by letting us control certain oscillatory infinite series of functions in terms of infinite series of non-negative functions. Beginning in the 1980s, it was discovered that this control could be made much sharper than was previously suspected. The present book tries to give a gentle, well-motivated introduction to those discoveries, the methods behind them, their consequences, and some of their applications.
Manufacturing Squares: An Integrative Statistical Process Control Exercise
Coy, Steven P.
2016-01-01
In the exercise, students in a junior-level operations management class are asked to manufacture a simple product. Given product specifications, they must design a production process, create roles and design jobs for each team member, and develop a statistical process control plan that efficiently and effectively controls quality during…
Efficient orbit integration by manifold correction methods.
Fukushima, Toshio
2005-12-01
Triggered by a desire to investigate, numerically, the planetary precession through a long-term numerical integration of the solar system, we developed a new formulation of numerical integration of orbital motion named manifold correct on methods. The main trick is to rigorously retain the consistency of physical relations, such as the orbital energy, the orbital angular momentum, or the Laplace integral, of a binary subsystem. This maintenance is done by applying a correction to the integrated variables at each integration step. Typical methods of correction are certain geometric transformations, such as spatial scaling and spatial rotation, which are commonly used in the comparison of reference frames, or mathematically reasonable operations, such as modularization of angle variables into the standard domain [-pi, pi). The form of the manifold correction methods finally evolved are the orbital longitude methods, which enable us to conduct an extremely precise integration of orbital motions. In unperturbed orbits, the integration errors are suppressed at the machine epsilon level for an indefinitely long period. In perturbed cases, on the other hand, the errors initially grow in proportion to the square root of time and then increase more rapidly, the onset of which depends on the type and magnitude of the perturbations. This feature is also realized for highly eccentric orbits by applying the same idea as used in KS-regularization. In particular, the introduction of time elements greatly enhances the performance of numerical integration of KS-regularized orbits, whether the scaling is applied or not.
Multi-source least-squares reverse time migration
Dai, Wei
2012-06-15
Least-squares migration has been shown to improve image quality compared to the conventional migration method, but its computational cost is often too high to be practical. In this paper, we develop two numerical schemes to implement least-squares migration with the reverse time migration method and the blended source processing technique to increase computation efficiency. By iterative migration of supergathers, which consist in a sum of many phase-encoded shots, the image quality is enhanced and the crosstalk noise associated with the encoded shots is reduced. Numerical tests on 2D HESS VTI data show that the multisource least-squares reverse time migration (LSRTM) algorithm suppresses migration artefacts, balances the amplitudes, improves image resolution and reduces crosstalk noise associated with the blended shot gathers. For this example, the multisource LSRTM is about three times faster than the conventional RTM method. For the 3D example of the SEG/EAGE salt model, with a comparable computational cost, multisource LSRTM produces images with more accurate amplitudes, better spatial resolution and fewer migration artefacts compared to conventional RTM. The empirical results suggest that multisource LSRTM can produce more accurate reflectivity images than conventional RTM does with a similar or less computational cost. The caveat is that the LSRTM image is sensitive to large errors in the migration velocity model. © 2012 European Association of Geoscientists & Engineers.
Bounded Perturbation Regularization for Linear Least Squares Estimation
Ballal, Tarig
2017-10-18
This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is allowed into the linear transformation matrix to improve the singular-value structure. Following this, the problem is formulated as a min-max optimization problem. Next, the min-max problem is converted to an equivalent minimization problem to estimate the unknown vector quantity. The solution of the minimization problem is shown to converge to that of the ℓ2 -regularized least squares problem, with the unknown regularizer related to the norm bound of the introduced perturbation through a nonlinear constraint. A procedure is proposed that combines the constraint equation with the mean squared error (MSE) criterion to develop an approximately optimal regularization parameter selection algorithm. Both direct and indirect applications of the proposed method are considered. Comparisons with different Tikhonov regularization parameter selection methods, as well as with other relevant methods, are carried out. Numerical results demonstrate that the proposed method provides significant improvement over state-of-the-art methods.
Decision-Directed Recursive Least Squares MIMO Channels Tracking
Directory of Open Access Journals (Sweden)
Karami Ebrahim
2006-01-01
Full Text Available A new approach for joint data estimation and channel tracking for multiple-input multiple-output (MIMO channels is proposed based on the decision-directed recursive least squares (DD-RLS algorithm. RLS algorithm is commonly used for equalization and its application in channel estimation is a novel idea. In this paper, after defining the weighted least squares cost function it is minimized and eventually the RLS MIMO channel estimation algorithm is derived. The proposed algorithm combined with the decision-directed algorithm (DDA is then extended for the blind mode operation. From the computational complexity point of view being versus the number of transmitter and receiver antennas, the proposed algorithm is very efficient. Through various simulations, the mean square error (MSE of the tracking of the proposed algorithm for different joint detection algorithms is compared with Kalman filtering approach which is one of the most well-known channel tracking algorithms. It is shown that the performance of the proposed algorithm is very close to Kalman estimator and that in the blind mode operation it presents a better performance with much lower complexity irrespective of the need to know the channel model.
Multi-source least-squares reverse time migration
Dai, Wei; Fowler, Paul J.; Schuster, Gerard T.
2012-01-01
Least-squares migration has been shown to improve image quality compared to the conventional migration method, but its computational cost is often too high to be practical. In this paper, we develop two numerical schemes to implement least-squares migration with the reverse time migration method and the blended source processing technique to increase computation efficiency. By iterative migration of supergathers, which consist in a sum of many phase-encoded shots, the image quality is enhanced and the crosstalk noise associated with the encoded shots is reduced. Numerical tests on 2D HESS VTI data show that the multisource least-squares reverse time migration (LSRTM) algorithm suppresses migration artefacts, balances the amplitudes, improves image resolution and reduces crosstalk noise associated with the blended shot gathers. For this example, the multisource LSRTM is about three times faster than the conventional RTM method. For the 3D example of the SEG/EAGE salt model, with a comparable computational cost, multisource LSRTM produces images with more accurate amplitudes, better spatial resolution and fewer migration artefacts compared to conventional RTM. The empirical results suggest that multisource LSRTM can produce more accurate reflectivity images than conventional RTM does with a similar or less computational cost. The caveat is that the LSRTM image is sensitive to large errors in the migration velocity model. © 2012 European Association of Geoscientists & Engineers.
Sequential Ensembles Tolerant to Synthetic Aperture Radar (SAR Soil Moisture Retrieval Errors
Directory of Open Access Journals (Sweden)
Ju Hyoung Lee
2016-04-01
Full Text Available Due to complicated and undefined systematic errors in satellite observation, data assimilation integrating model states with satellite observations is more complicated than field measurements-based data assimilation at a local scale. In the case of Synthetic Aperture Radar (SAR soil moisture, the systematic errors arising from uncertainties in roughness conditions are significant and unavoidable, but current satellite bias correction methods do not resolve the problems very well. Thus, apart from the bias correction process of satellite observation, it is important to assess the inherent capability of satellite data assimilation in such sub-optimal but more realistic observational error conditions. To this end, time-evolving sequential ensembles of the Ensemble Kalman Filter (EnKF is compared with stationary ensemble of the Ensemble Optimal Interpolation (EnOI scheme that does not evolve the ensembles over time. As the sensitivity analysis demonstrated that the surface roughness is more sensitive to the SAR retrievals than measurement errors, it is a scope of this study to monitor how data assimilation alters the effects of roughness on SAR soil moisture retrievals. In results, two data assimilation schemes all provided intermediate values between SAR overestimation, and model underestimation. However, under the same SAR observational error conditions, the sequential ensembles approached a calibrated model showing the lowest Root Mean Square Error (RMSE, while the stationary ensemble converged towards the SAR observations exhibiting the highest RMSE. As compared to stationary ensembles, sequential ensembles have a better tolerance to SAR retrieval errors. Such inherent nature of EnKF suggests an operational merit as a satellite data assimilation system, due to the limitation of bias correction methods currently available.
Kedir, Jafer; Girma, Abonesh
2014-10-01
Refractive error is one of the major causes of blindness and visual impairment in children; but community based studies are scarce especially in rural parts of Ethiopia. So, this study aims to assess the prevalence of refractive error and its magnitude as a cause of visual impairment among school-age children of rural community. This community-based cross-sectional descriptive study was conducted from March 1 to April 30, 2009 in rural villages of Goro district of Gurage Zone, found south west of Addis Ababa, the capital of Ethiopia. A multistage cluster sampling method was used with simple random selection of representative villages in the district. Chi-Square and t-tests were used in the data analysis. A total of 570 school-age children (age 7-15) were evaluated, 54% boys and 46% girls. The prevalence of refractive error was 3.5% (myopia 2.6% and hyperopia 0.9%). Refractive error was the major cause of visual impairment accounting for 54% of all causes in the study group. No child was found wearing corrective spectacles during the study period. Refractive error was the commonest cause of visual impairment in children of the district, but no measures were taken to reduce the burden in the community. So, large scale community level screening for refractive error should be conducted and integrated with regular school eye screening programs. Effective strategies need to be devised to provide low cost corrective spectacles in the rural community.
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…
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.
Around and Beyond the Square of Opposition
Béziau, Jean-Yves
2012-01-01
aiThe theory of oppositions based on Aristotelian foundations of logic has been pictured in a striking square diagram which can be understood and applied in many different ways having repercussions in various fields: epistemology, linguistics, mathematics, psychology. The square can also be generalized in other two-dimensional or multi-dimensional objects extending in breadth and depth the original theory of oppositions of Aristotle. The square of opposition is a very attractive theme which has been going through centuries without evaporating. Since 10 years there is a new growing interest for
Partial update least-square adaptive filtering
Xie, Bei
2014-01-01
Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity (O(N)) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster a
Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor.
Zhao, Yanzhi; Cao, Yachao; Zhang, Caifeng; Zhang, Dan; Zhang, Jie
2017-09-29
By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint) parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H) method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments.
Error Modeling and Experimental Study of a Flexible Joint 6-UPUR Parallel Six-Axis Force Sensor
Directory of Open Access Journals (Sweden)
Yanzhi Zhao
2017-09-01
Full Text Available By combining a parallel mechanism with integrated flexible joints, a large measurement range and high accuracy sensor is realized. However, the main errors of the sensor involve not only assembly errors, but also deformation errors of its flexible leg. Based on a flexible joint 6-UPUR (a kind of mechanism configuration where U-universal joint, P-prismatic joint, R-revolute joint parallel six-axis force sensor developed during the prephase, assembly and deformation error modeling and analysis of the resulting sensors with a large measurement range and high accuracy are made in this paper. First, an assembly error model is established based on the imaginary kinematic joint method and the Denavit-Hartenberg (D-H method. Next, a stiffness model is built to solve the stiffness matrix. The deformation error model of the sensor is obtained. Then, the first order kinematic influence coefficient matrix when the synthetic error is taken into account is solved. Finally, measurement and calibration experiments of the sensor composed of the hardware and software system are performed. Forced deformation of the force-measuring platform is detected by using laser interferometry and analyzed to verify the correctness of the synthetic error model. In addition, the first order kinematic influence coefficient matrix in actual circumstances is calculated. By comparing the condition numbers and square norms of the coefficient matrices, the conclusion is drawn theoretically that it is very important to take into account the synthetic error for design stage of the sensor and helpful to improve performance of the sensor in order to meet needs of actual working environments.
Minimum mean square error estimation and approximation of the Bayesian update
Litvinenko, Alexander; Matthies, Hermann G.; Zander, Elmar
2015-01-01
Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(w), a measurement operator Y (u(q); q), where u(q; w) uncertain solution. Aim: to identify q(w). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(w) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a functional approximation, e.g. polynomial chaos expansion (PCE). New: We derive linear, quadratic etc approximation of full Bayesian update.
Progressive decrement PWM algorithm for minimum mean square error inverter output voltage
International Nuclear Information System (INIS)
Ghaeb, J.A.; Smadi, M.A.; Ababneh, M.
2011-01-01
Highlights: → The main contribution of this work is to provide a better performance for the power inverter operation. → The proposed technique splits the determined original pulse-width of an inverter operation in to many pulses. → The new approach extends the central pulse and shrinks the exterior pulses. → This is leading to an inverter output cycle close to the sinusoidal form of fewer harmonics. - Abstract: The paper proposes two modulation techniques for the power inverter. These new techniques are named progressive decrement PWM algorithm (PDPA) and progressive increment PWM algorithm (PIPA). Both techniques take the determined original pulse-width of an inverter operation and split it to many pulses. In the PDPA technique, the largest width is given to the middle pulse and the width of the boundary pulses is reduced progressively starting from the first boundary-pulse toward the last boundary-pulse. In the PIPA technique, there is a gradual increment instead of decrement. The two techniques have been proved that it can maintain the original pulse-width of the inverter operation. The new approach PDPA extends the central pulse and shrinks the exterior pulses, leading to an inverter output cycle close to the sinusoidal form of fewer harmonic contents. Simulation results are performed to evaluate the performances of the proposed techniques: PDPA and PIPA and to compare them with the well known methods. The main contribution of the proposed PDPA technique is that it provides a better performance for the most harmonic orders compared to the well established sinusoidal PWM technique.
Minimum mean square error estimation and approximation of the Bayesian update
Litvinenko, Alexander
2015-01-07
Given: a physical system modeled by a PDE or ODE with uncertain coefficient q(w), a measurement operator Y (u(q); q), where u(q; w) uncertain solution. Aim: to identify q(w). The mapping from parameters to observations is usually not invertible, hence this inverse identification problem is generally ill-posed. To identify q(w) we derived non-linear Bayesian update from the variational problem associated with conditional expectation. To reduce cost of the Bayesian update we offer a functional approximation, e.g. polynomial chaos expansion (PCE). New: We derive linear, quadratic etc approximation of full Bayesian update.
The Effects of Discrete-Trial Training Commission Errors on Learner Outcomes: An Extension
Jenkins, Sarah R.; Hirst, Jason M.; DiGennaro Reed, Florence D.
2015-01-01
We conducted a parametric analysis of treatment integrity errors during discrete-trial training and investigated the effects of three integrity conditions (0, 50, or 100 % errors of commission) on performance in the presence and absence of programmed errors. The presence of commission errors impaired acquisition for three of four participants.…
Nonlinear Least Square Based on Control Direction by Dual Method and Its Application
Directory of Open Access Journals (Sweden)
Zhengqing Fu
2016-01-01
Full Text Available A direction controlled nonlinear least square (NLS estimation algorithm using the primal-dual method is proposed. The least square model is transformed into the primal-dual model; then direction of iteration can be controlled by duality. The iterative algorithm is designed. The Hilbert morbid matrix is processed by the new model and the least square estimate and ridge estimate. The main research method is to combine qualitative analysis and quantitative analysis. The deviation between estimated values and the true value and the estimated residuals fluctuation of different methods are used for qualitative analysis. The root mean square error (RMSE is used for quantitative analysis. The results of experiment show that the model has the smallest residual error and the minimum root mean square error. The new estimate model has effectiveness and high precision. The genuine data of Jining area in unwrapping experiments are used and the comparison with other classical unwrapping algorithms is made, so better results in precision aspects can be achieved through the proposed algorithm.
Performance of the S - [chi][squared] Statistic for Full-Information Bifactor Models
Li, Ying; Rupp, Andre A.
2011-01-01
This study investigated the Type I error rate and power of the multivariate extension of the S - [chi][squared] statistic using unidimensional and multidimensional item response theory (UIRT and MIRT, respectively) models as well as full-information bifactor (FI-bifactor) models through simulation. Manipulated factors included test length, sample…
Stable Galerkin versus equal-order Galerkin least-squares elements for the stokes flow problem
International Nuclear Information System (INIS)
Franca, L.P.; Frey, S.L.; Sampaio, R.
1989-11-01
Numerical experiments are performed for the stokes flow problem employing a stable Galerkin method and a Galerkin/Least-squares method with equal-order elements. Error estimates for the methods tested herein are reviewed. The numerical results presented attest the good stability properties of all methods examined herein. (A.C.A.S.) [pt
Mean-square performance of a convex combination of two adaptive filters
DEFF Research Database (Denmark)
Garcia, Jeronimo; Figueiras-Vidal, A.R.; Sayed, A.H.
2006-01-01
Combination approaches provide an interesting way to improve adaptive filter performance. In this paper, we study the mean-square performance of a convex combination of two transversal filters. The individual filters are independently adapted using their own error signals, while the combination i...
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.
Elmo bumpy square plasma confinement device
Owen, L.W.
1985-01-01
The invention is an Elmo bumpy type plasma confinement device having a polygonal configuration of closed magnet field lines for improved plasma confinement. In the preferred embodiment, the device is of a square configuration which is referred to as an Elmo bumpy square (EBS). The EBS is formed by four linear magnetic mirror sections each comprising a plurality of axisymmetric assemblies connected in series and linked by 90/sup 0/ sections of a high magnetic field toroidal solenoid type field generating coils. These coils provide corner confinement with a minimum of radial dispersion of the confined plasma to minimize the detrimental effects of the toroidal curvature of the magnetic field. Each corner is formed by a plurality of circular or elliptical coils aligned about the corner radius to provide maximum continuity in the closing of the magnetic field lines about the square configuration confining the plasma within a vacuum vessel located within the various coils forming the square configuration confinement geometry.
Anomalous structural transition of confined hard squares.
Gurin, Péter; Varga, Szabolcs; Odriozola, Gerardo
2016-11-01
Structural transitions are examined in quasi-one-dimensional systems of freely rotating hard squares, which are confined between two parallel walls. We find two competing phases: one is a fluid where the squares have two sides parallel to the walls, while the second one is a solidlike structure with a zigzag arrangement of the squares. Using transfer matrix method we show that the configuration space consists of subspaces of fluidlike and solidlike phases, which are connected with low probability microstates of mixed structures. The existence of these connecting states makes the thermodynamic quantities continuous and precludes the possibility of a true phase transition. However, thermodynamic functions indicate strong tendency for the phase transition and our replica exchange Monte Carlo simulation study detects several important markers of the first order phase transition. The distinction of a phase transition from a structural change is practically impossible with simulations and experiments in such systems like the confined hard squares.
The inverse square law of gravitation
International Nuclear Information System (INIS)
Cook, A.H.
1987-01-01
The inverse square law of gravitation is very well established over the distances of celestial mechanics, while in electrostatics the law has been shown to be followed to very high precision. However, it is only within the last century that any laboratory experiments have been made to test the inverse square law for gravitation, and all but one has been carried out in the last ten years. At the same time, there has been considerable interest in the possibility of deviations from the inverse square law, either because of a possible bearing on unified theories of forces, including gravitation or, most recently, because of a possible additional fifth force of nature. In this article the various lines of evidence for the inverse square law are summarized, with emphasis upon the recent laboratory experiments. (author)
Applications of square-related theorems
Srinivasan, V. K.
2014-04-01
The square centre of a given square is the point of intersection of its two diagonals. When two squares of different side lengths share the same square centre, there are in general four diagonals that go through the same square centre. The Two Squares Theorem developed in this paper summarizes some nice theoretical conclusions that can be obtained when two squares of different side lengths share the same square centre. These results provide the theoretical basis for two of the constructions given in the book of H.S. Hall and F.H. Stevens , 'A Shorter School Geometry, Part 1, Metric Edition'. In page 134 of this book, the authors present, in exercise 4, a practical construction which leads to a verification of the Pythagorean theorem. Subsequently in Theorems 29 and 30, the authors present the standard proofs of the Pythagorean theorem and its converse. In page 140, the authors present, in exercise 15, what amounts to a geometric construction, whose verification involves a simple algebraic identity. Both the constructions are of great importance and can be replicated by using the standard equipment provided in a 'geometry toolbox' carried by students in high schools. The author hopes that the results proved in this paper, in conjunction with the two constructions from the above-mentioned book, would provide high school students an appreciation of the celebrated theorem of Pythagoras. The diagrams that accompany this document are based on the free software GeoGebra. The author formally acknowledges his indebtedness to the creators of this free software at the end of this document.
Power Efficient Division and Square Root Unit
DEFF Research Database (Denmark)
Liu, Wei; Nannarelli, Alberto
2012-01-01
Although division and square root are not frequent operations, most processors implement them in hardware to not compromise the overall performance. Two classes of algorithms implement division or square root: digit-recurrence and multiplicative (e.g., Newton-Raphson) algorithms. Previous work....... The proposed unit is compared to similar solutions based on the digit-recurrence algorithm and it is compared to a unit based on the multiplicative Newton-Raphson algorithm....
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
Estimasi Model Seemingly Unrelated Regression (SUR dengan Metode Generalized Least Square (GLS
Directory of Open Access Journals (Sweden)
Ade Widyaningsih
2015-04-01
Full Text Available Regression analysis is a statistical tool that is used to determine the relationship between two or more quantitative variables so that one variable can be predicted from the other variables. A method that can used to obtain a good estimation in the regression analysis is ordinary least squares method. The least squares method is used to estimate the parameters of one or more regression but relationships among the errors in the response of other estimators are not allowed. One way to overcome this problem is Seemingly Unrelated Regression model (SUR in which parameters are estimated using Generalized Least Square (GLS. In this study, the author applies SUR model using GLS method on world gasoline demand data. The author obtains that SUR using GLS is better than OLS because SUR produce smaller errors than the OLS.
Estimasi Model Seemingly Unrelated Regression (SUR dengan Metode Generalized Least Square (GLS
Directory of Open Access Journals (Sweden)
Ade Widyaningsih
2014-06-01
Full Text Available Regression analysis is a statistical tool that is used to determine the relationship between two or more quantitative variables so that one variable can be predicted from the other variables. A method that can used to obtain a good estimation in the regression analysis is ordinary least squares method. The least squares method is used to estimate the parameters of one or more regression but relationships among the errors in the response of other estimators are not allowed. One way to overcome this problem is Seemingly Unrelated Regression model (SUR in which parameters are estimated using Generalized Least Square (GLS. In this study, the author applies SUR model using GLS method on world gasoline demand data. The author obtains that SUR using GLS is better than OLS because SUR produce smaller errors than the OLS.
Newton-Gauss Algorithm of Robust Weighted Total Least Squares Model
Directory of Open Access Journals (Sweden)
WANG Bin
2015-06-01
Full Text Available Based on the Newton-Gauss iterative algorithm of weighted total least squares (WTLS, a robust WTLS (RWTLS model is presented. The model utilizes the standardized residuals to construct the weight factor function and the square root of the variance component estimator with robustness is obtained by introducing the median method. Therefore, the robustness in both the observation and structure spaces can be simultaneously achieved. To obtain standardized residuals, the linearly approximate cofactor propagation law is employed to derive the expression of the cofactor matrix of WTLS residuals. The iterative calculation steps for RWTLS are also described. The experiment indicates that the model proposed in this paper exhibits satisfactory robustness for gross errors handling problem of WTLS, the obtained parameters have no significant difference with the results of WTLS without gross errors. Therefore, it is superior to the robust weighted total least squares model directly constructed with residuals.
Credit Risk Evaluation Using a C-Variable Least Squares Support Vector Classification Model
Yu, Lean; Wang, Shouyang; Lai, K. K.
Credit risk evaluation is one of the most important issues in financial risk management. In this paper, a C-variable least squares support vector classification (C-VLSSVC) model is proposed for credit risk analysis. The main idea of this model is based on the prior knowledge that different classes may have different importance for modeling and more weights should be given to those classes with more importance. The C-VLSSVC model can be constructed by a simple modification of the regularization parameter in LSSVC, whereby more weights are given to the lease squares classification errors with important classes than the lease squares classification errors with unimportant classes while keeping the regularized terms in its original form. For illustration purpose, a real-world credit dataset is used to test the effectiveness of the C-VLSSVC model.
Space-time least-squares Petrov-Galerkin projection in nonlinear model reduction.
Energy Technology Data Exchange (ETDEWEB)
Choi, Youngsoo [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.; Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Carlberg, Kevin Thomas [Sandia National Laboratories (SNL-CA), Livermore, CA (United States). Extreme-scale Data Science and Analytics Dept.
2017-09-01
Our work proposes a space-time least-squares Petrov-Galerkin (ST-LSPG) projection method for model reduction of nonlinear dynamical systems. In contrast to typical nonlinear model-reduction methods that first apply Petrov-Galerkin projection in the spatial dimension and subsequently apply time integration to numerically resolve the resulting low-dimensional dynamical system, the proposed method applies projection in space and time simultaneously. To accomplish this, the method first introduces a low-dimensional space-time trial subspace, which can be obtained by computing tensor decompositions of state-snapshot data. The method then computes discrete-optimal approximations in this space-time trial subspace by minimizing the residual arising after time discretization over all space and time in a weighted ℓ^{2}-norm. This norm can be de ned to enable complexity reduction (i.e., hyper-reduction) in time, which leads to space-time collocation and space-time GNAT variants of the ST-LSPG method. Advantages of the approach relative to typical spatial-projection-based nonlinear model reduction methods such as Galerkin projection and least-squares Petrov-Galerkin projection include: (1) a reduction of both the spatial and temporal dimensions of the dynamical system, (2) the removal of spurious temporal modes (e.g., unstable growth) from the state space, and (3) error bounds that exhibit slower growth in time. Numerical examples performed on model problems in fluid dynamics demonstrate the ability of the method to generate orders-of-magnitude computational savings relative to spatial-projection-based reduced-order models without sacrificing accuracy.
$L^{p}$-square function estimates on spaces of homogeneous type and on uniformly rectifiable sets
Hofmann, Steve; Mitrea, Marius; Morris, Andrew J
2017-01-01
The authors establish square function estimates for integral operators on uniformly rectifiable sets by proving a local T(b) theorem and applying it to show that such estimates are stable under the so-called big pieces functor. More generally, they consider integral operators associated with Ahlfors-David regular sets of arbitrary codimension in ambient quasi-metric spaces. The local T(b) theorem is then used to establish an inductive scheme in which square function estimates on so-called big pieces of an Ahlfors-David regular set are proved to be sufficient for square function estimates to hold on the entire set. Extrapolation results for L^p and Hardy space versions of these estimates are also established. Moreover, the authors prove square function estimates for integral operators associated with variable coefficient kernels, including the Schwartz kernels of pseudodifferential operators acting between vector bundles on subdomains with uniformly rectifiable boundaries on manifolds.
Least squares orthogonal polynomial approximation in several independent variables
International Nuclear Information System (INIS)
Caprari, R.S.
1992-06-01
This paper begins with an exposition of a systematic technique for generating orthonormal polynomials in two independent variables by application of the Gram-Schmidt orthogonalization procedure of linear algebra. It is then demonstrated how a linear least squares approximation for experimental data or an arbitrary function can be generated from these polynomials. The least squares coefficients are computed without recourse to matrix arithmetic, which ensures both numerical stability and simplicity of implementation as a self contained numerical algorithm. The Gram-Schmidt procedure is then utilised to generate a complete set of orthogonal polynomials of fourth degree. A theory for the transformation of the polynomial representation from an arbitrary basis into the familiar sum of products form is presented, together with a specific implementation for fourth degree polynomials. Finally, the computational integrity of this algorithm is verified by reconstructing arbitrary fourth degree polynomials from their values at randomly chosen points in their domain. 13 refs., 1 tab
Mean value estimates of the error terms of Lehmer problem
Indian Academy of Sciences (India)
Mean value estimates of the error terms of Lehmer problem. DONGMEI REN1 and YAMING ... For further properties of N(a,p) in [6], he studied the mean square value of the error term. E(a, p) = N(a,p) − 1. 2 (p − 1) ..... [1] Apostol Tom M, Introduction to Analytic Number Theory (New York: Springer-Verlag). (1976). [2] Guy R K ...
Sabol, T. A.; Topping, D. J.; Griffiths, R. E.
2011-12-01
Accurate measurements of suspended-sediment concentration require suspended-sediment samplers to operate isokinetically with an intake-efficiency of 1.0 ± 0.10. Results from 1940s Federal Interagency Sedimentation Project (FISP) laboratory experiments show that when the intake efficiency does not equal 1.0, suspended-sediment samplers either under- or oversample sediment relative to water, leading to biases in suspended-sediment concentration. The majority of recent FISP sampler development and testing has been conducted under uniform flow conditions using flume and slack-water tow tests, with little testing in actual turbulent rivers. Recent work has focused on the hydraulic characteristics and intake efficiencies of these samplers, without field investigations of the accuracy of the suspended-sediment data collected with these samplers. When depth-integrating suspended-sediment samplers are deployed under the non-uniform and turbulent conditions that exist in rivers, multiple factors may contribute to departures from isokinetic sampling. This introduces errors into the suspended-sediment data that may not be predictable on the basis of flume and tow tests alone. This study (1) evaluates the intake efficiencies of the older US D-77 bag-type and newer, FISP-approved US D-96 samplers at multiple river cross sections under a range of flow conditions; (2) examines if water temperature and sampling duration explain measured differences in intake efficiency between samplers and between laboratory and field tests; (3) models and predicts the directions and magnitudes of errors in measured suspended-sand concentration; and (4) determines if the relative differences in suspended-sediment concentration in a variety of size classes are consistent with the differences expected on the basis of the 1940s FISP-laboratory experiments. Results indicate that under river conditions, the intake efficiency of the US D-96 sampler is superior to that of the US D-77 bag-type sampler and
... 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...
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....
Conjugate descent formulation of backpropagation error in feedforward neural networks
Directory of Open Access Journals (Sweden)
NK Sharma
2009-06-01
Full Text Available The feedforward neural network architecture uses backpropagation learning to determine optimal weights between different interconnected layers. This learning procedure uses a gradient descent technique applied to a sum-of-squares error function for the given input-output pattern. It employs an iterative procedure to minimise the error function for a given set of patterns, by adjusting the weights of the network. The first derivates of the error with respect to the weights identify the local error surface in the descent direction. Hence the network exhibits a different local error surface for every different pattern presented to it, and weights are iteratively modified in order to minimise the current local error. The determination of an optimal weight vector is possible only when the total minimum error (mean of the minimum local errors for all patterns from the training set may be minimised. In this paper, we present a general mathematical formulation for the second derivative of the error function with respect to the weights (which represents a conjugate descent for arbitrary feedforward neural network topologies, and we use this derivative information to obtain the optimal weight vector. The local error is backpropagated among the units of hidden layers via the second order derivative of the error with respect to the weights of the hidden and output layers independently and also in combination. The new total minimum error point may be evaluated with the help of the current total minimum error and the current minimised local error. The weight modification processes is performed twice: once with respect to the present local error and once more with respect to the current total or mean error. We present some numerical evidence that our proposed method yields better network weights than those determined via a conventional gradient descent approach.
Forecast Combination under Heavy-Tailed Errors
Directory of Open Access Journals (Sweden)
Gang Cheng
2015-11-01
Full Text Available Forecast combination has been proven to be a very important technique to obtain accurate predictions for various applications in economics, finance, marketing and many other areas. In many applications, forecast errors exhibit heavy-tailed behaviors for various reasons. Unfortunately, to our knowledge, little has been done to obtain reliable forecast combinations for such situations. The familiar forecast combination methods, such as simple average, least squares regression or those based on the variance-covariance of the forecasts, may perform very poorly due to the fact that outliers tend to occur, and they make these methods have unstable weights, leading to un-robust forecasts. To address this problem, in this paper, we propose two nonparametric forecast combination methods. One is specially proposed for the situations in which the forecast errors are strongly believed to have heavy tails that can be modeled by a scaled Student’s t-distribution; the other is designed for relatively more general situations when there is a lack of strong or consistent evidence on the tail behaviors of the forecast errors due to a shortage of data and/or an evolving data-generating process. Adaptive risk bounds of both methods are developed. They show that the resulting combined forecasts yield near optimal mean forecast errors relative to the candidate forecasts. Simulations and a real example demonstrate their superior performance in that they indeed tend to have significantly smaller prediction errors than the previous combination methods in the presence of forecast outliers.
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.
Least Squares Estimate of the Initial Phases in STFT based Speech Enhancement
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Krawczyk-Becker, Martin; Gerkmann, Timo
2015-01-01
In this paper, we consider single-channel speech enhancement in the short time Fourier transform (STFT) domain. We suggest to improve an STFT phase estimate by estimating the initial phases. The method is based on the harmonic model and a model for the phase evolution over time. The initial phases...... are estimated by setting up a least squares problem between the noisy phase and the model for phase evolution. Simulations on synthetic and speech signals show a decreased error on the phase when an estimate of the initial phase is included compared to using the noisy phase as an initialisation. The error...... on the phase is decreased at input SNRs from -10 to 10 dB. Reconstructing the signal using the clean amplitude, the mean squared error is decreased and the PESQ score is increased....
Sabol, Thomas A.; Topping, David J.
2013-01-01
Accurate measurements of suspended-sediment concentration require suspended-sediment samplers to operate isokinetically, within an intake-efficiency range of 1.0 ± 0.10, where intake efficiency is defined as the ratio of the velocity of the water through the sampler intake to the local ambient stream velocity. Local ambient stream velocity is defined as the velocity of the water in the river at the location of the nozzle, unaffected by the presence of the sampler. Results from Federal Interagency Sedimentation Project (FISP) laboratory experiments published in the early 1940s show that when the intake efficiency is less than 1.0, suspended-sediment samplers tend to oversample sediment relative to water, leading to potentially large positive biases in suspended-sediment concentration that are positively correlated with grain size. Conversely, these experiments show that, when the intake efficiency is greater than 1.0, suspended‑sediment samplers tend to undersample sediment relative to water, leading to smaller negative biases in suspended-sediment concentration that become slightly more negative as grain size increases. The majority of FISP sampler development and testing since the early 1990s has been conducted under highly uniform flow conditions via flume and slack-water tow tests, with relatively little work conducted under the greater levels of turbulence that exist in actual rivers. Additionally, all of this recent work has been focused on the hydraulic characteristics and intake efficiencies of these samplers, with no field investigations conducted on the accuracy of the suspended-sediment data collected with these samplers. When depth-integrating suspended-sediment samplers are deployed under the more nonuniform and turbulent conditions that exist in rivers, multiple factors may contribute to departures from isokinetic sampling, thus introducing errors into the suspended-sediment data collected by these samplers that may not be predictable on the basis
Yuan, Rui; Zhu, Rui; Qu, Jianhua; Wu, Jun; You, Xincai; Sun, Yuqiu; Zhou, Yuanquan (Nancy)
2018-05-01
The Mahu Depression is an important hydrocarbon-bearing foreland sag located at the northwestern margin of the Junggar Basin, China. On the northern slope of the depression, large coarse-grained proximal fan-delta depositional systems developed in the Lower Triassic Baikouquan Formation (T1b). Some lithologic hydrocarbon reservoirs have been found in the conglomerates of the formation since recent years. However, the rapid vertical and horizontal lithology variations make it is difficult to divide the base-level cycle of the formation using the conventional methods. Spectral analysis technologies, such as Integrated Prediction Error Filter Analysis (INPEFA), provide another effective way to overcome this difficultly. In this paper, processed by INPEFA, conventional resistivity logs are utilized to study the base-level cycle of the fan-delta depositional systems. The negative trend of the INPEFA curve indicates the base-level fall semi-cycles, adversely, positive trend suggests the rise semi-cycles. Base-level cycles of Baikouquan Formation are divided in single and correlation wells. One long-term base-level rise semi-cycle, including three medium-term base-level cycles, is identified overall the Baikouquan Formation. The medium-term base-level cycles are characterized as rise semi-cycles mainly in the fan-delta plain, symmetric cycles in the fan-delta front and fall semi-cycles mainly in the pro-fan-delta. The short-term base-level rise semi-cycles most developed in the braided channels, sub-aqueous distributary channels and sheet sands. While, the interdistributary bays and pro-fan-delta mud indicate short-term base-level fall semi-cycles. Finally, based on the method of INPEFA, sequence filling model of Baikouquan formation is established.
Directory of Open Access Journals (Sweden)
I PUTU EKA IRAWAN
2013-11-01
Full Text Available Principal Component Regression is a method to overcome multicollinearity techniques by combining principal component analysis with regression analysis. The calculation of classical principal component analysis is based on the regular covariance matrix. The covariance matrix is optimal if the data originated from a multivariate normal distribution, but is very sensitive to the presence of outliers. Alternatives are used to overcome this problem the method of Least Median Square-Minimum Covariance Determinant (LMS-MCD. The purpose of this research is to conduct a comparison between Principal Component Regression (RKU and Method of Least Median Square - Minimum Covariance Determinant (LMS-MCD in dealing with outliers. In this study, Method of Least Median Square - Minimum Covariance Determinant (LMS-MCD has a bias and mean square error (MSE is smaller than the parameter RKU. Based on the difference of parameter estimators, still have a test that has a difference of parameter estimators method LMS-MCD greater than RKU method.
Least-squares finite element discretizations of neutron transport equations in 3 dimensions
Energy Technology Data Exchange (ETDEWEB)
Manteuffel, T.A [Univ. of Colorado, Boulder, CO (United States); Ressel, K.J. [Interdisciplinary Project Center for Supercomputing, Zurich (Switzerland); Starkes, G. [Universtaet Karlsruhe (Germany)
1996-12-31
The least-squares finite element framework to the neutron transport equation introduced in is based on the minimization of a least-squares functional applied to the properly scaled neutron transport equation. Here we report on some practical aspects of this approach for neutron transport calculations in three space dimensions. The systems of partial differential equations resulting from a P{sub 1} and P{sub 2} approximation of the angular dependence are derived. In the diffusive limit, the system is essentially a Poisson equation for zeroth moment and has a divergence structure for the set of moments of order 1. One of the key features of the least-squares approach is that it produces a posteriori error bounds. We report on the numerical results obtained for the minimum of the least-squares functional augmented by an additional boundary term using trilinear finite elements on a uniform tesselation into cubes.
Sequential least-square reconstruction of instantaneous pressure field around a body from TR-PIV
Jeon, Young Jin; Gomit, G.; Earl, T.; Chatellier, L.; David, L.
2018-02-01
A procedure is introduced to obtain an instantaneous pressure field around a wing from time-resolved particle image velocimetry (TR-PIV) and particle image accelerometry (PIA). The instantaneous fields of velocity and material acceleration are provided by the recently introduced multi-frame PIV method, fluid trajectory evaluation based on ensemble-averaged cross-correlation (FTEE). The integration domain is divided into several subdomains in accordance with the local reliability. The near-edge and near-body regions are determined based on the recorded image of the wing. The instantaneous wake region is assigned by a combination of a self-defined criterion and binary morphological processes. The pressure is reconstructed from a minimization process of the difference between measured and reconstructed pressure gradients in a least-square sense. This is solved sequentially according to a decreasing order of reliability of each subdomain to prevent a propagation of error from the less reliable near-body region to the free-stream. The present procedure is numerically assessed by synthetically generated 2D particle images based on a numerical simulation. Volumetric pressure fields are then evaluated from tomographic TR-PIV of a flow around a 30-degree-inclined NACA0015 airfoil. A possibility of using a different scheme to evaluate material acceleration for a specific subdomain is presented. Moreover, this 3D application allows the investigation of the effect of the third component of the pressure gradient by which the wake region seems to be affected.
Least Squares Adjustment: Linear and Nonlinear Weighted Regression Analysis
DEFF Research Database (Denmark)
Nielsen, Allan Aasbjerg
2007-01-01
This note primarily describes the mathematics of least squares regression analysis as it is often used in geodesy including land surveying and satellite positioning applications. In these fields regression is often termed adjustment. The note also contains a couple of typical land surveying...... and satellite positioning application examples. In these application areas we are typically interested in the parameters in the model typically 2- or 3-D positions and not in predictive modelling which is often the main concern in other regression analysis applications. Adjustment is often used to obtain...... the clock error) and to obtain estimates of the uncertainty with which the position is determined. Regression analysis is used in many other fields of application both in the natural, the technical and the social sciences. Examples may be curve fitting, calibration, establishing relationships between...
Robust Homography Estimation Based on Nonlinear Least Squares Optimization
Directory of Open Access Journals (Sweden)
Wei Mou
2014-01-01
Full Text Available The homography between image pairs is normally estimated by minimizing a suitable cost function given 2D keypoint correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts to filter out these erroneous correspondences, but it is unlikely to always achieve perfect matching. To deal with this problem, we propose a nonlinear least squares optimization approach to compute homography such that false matches have no or little effect on computed homography. Unlike normal homography computation algorithms, our method formulates not only the keypoints’ geometric relationship but also their descriptor similarity into cost function. Moreover, the cost function is parametrized in such a way that incorrect correspondences can be simultaneously identified while the homography is computed. Experiments show that the proposed approach can perform well even with the presence of a large number of outliers.
Non-spill control squared cascade
International Nuclear Information System (INIS)
Kai, Tsunetoshi; Inoue, Yoshiya; Oya, Akio; Suemori, Nobuo.
1974-01-01
Object: To reduce a mixed loss thus enhancing separating efficiency by the provision of a simple arrangement wherein a reflux portion in a conventional spill control squared cascade is replaced by a special stage including centrifugal separators. Structure: Steps in the form of a square cascade, in which a plurality of centrifugal separators are connected by pipe lines, are accumulated in multistage fashion to form a squared cascade. Between the adjoining steps is disposed a special stage including a centrifugal separator which receives both lean flow from the upper step and rich flow from the lower step. The centrifugal separator in the special stage has its rich side connected to the upper step and its lean side connected to the lower step. Special stages are each disposed at the upper side of the uppermost step and at the lower side of the lowermost step. (Kamimura, M.)
Least Squares Data Fitting with Applications
DEFF Research Database (Denmark)
Hansen, Per Christian; Pereyra, Víctor; Scherer, Godela
As one of the classical statistical regression techniques, and often the first to be taught to new students, least squares fitting can be a very effective tool in data analysis. Given measured data, we establish a relationship between independent and dependent variables so that we can use the data....... In a number of applications, the accuracy and efficiency of the least squares fit is central, and Per Christian Hansen, Víctor Pereyra, and Godela Scherer survey modern computational methods and illustrate them in fields ranging from engineering and environmental sciences to geophysics. Anyone working...... with problems of linear and nonlinear least squares fitting will find this book invaluable as a hands-on guide, with accessible text and carefully explained problems. Included are • an overview of computational methods together with their properties and advantages • topics from statistical regression analysis...
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.
Common Errors in Ecological Data Sharing
Directory of Open Access Journals (Sweden)
Robert B. Cook
2013-04-01
Full Text Available Objectives: (1 to identify common errors in data organization and metadata completeness that would preclude a “reader” from being able to interpret and re-use the data for a new purpose; and (2 to develop a set of best practices derived from these common errors that would guide researchers in creating more usable data products that could be readily shared, interpreted, and used.Methods: We used directed qualitative content analysis to assess and categorize data and metadata errors identified by peer reviewers of data papers published in the Ecological Society of America’s (ESA Ecological Archives. Descriptive statistics provided the relative frequency of the errors identified during the peer review process.Results: There were seven overarching error categories: Collection & Organization, Assure, Description, Preserve, Discover, Integrate, and Analyze/Visualize. These categories represent errors researchers regularly make at each stage of the Data Life Cycle. Collection & Organization and Description errors were some of the most common errors, both of which occurred in over 90% of the papers.Conclusions: Publishing data for sharing and reuse is error prone, and each stage of the Data Life Cycle presents opportunities for mistakes. The most common errors occurred when the researcher did not provide adequate metadata to enable others to interpret and potentially re-use the data. Fortunately, there are ways to minimize these mistakes through carefully recording all details about study context, data collection, QA/ QC, and analytical procedures from the beginning of a research project and then including this descriptive information in the metadata.
Shan, Peng; Peng, Silong; Zhao, Yuhui; Tang, Liang
2016-03-01
An analysis of binary mixtures of hydroxyl compound by Attenuated Total Reflection Fourier transform infrared spectroscopy (ATR FT-IR) and classical least squares (CLS) yield large model error due to the presence of unmodeled components such as H-bonded components. To accommodate these spectral variations, polynomial-based least squares (LSP) and polynomial-based total least squares (TLSP) are proposed to capture the nonlinear absorbance-concentration relationship. LSP is based on assuming that only absorbance noise exists; while TLSP takes both absorbance noise and concentration noise into consideration. In addition, based on different solving strategy, two optimization algorithms (limited-memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) algorithm and Levenberg-Marquardt (LM) algorithm) are combined with TLSP and then two different TLSP versions (termed as TLSP-LBFGS and TLSP-LM) are formed. The optimum order of each nonlinear model is determined by cross-validation. Comparison and analyses of the four models are made from two aspects: absorbance prediction and concentration prediction. The results for water-ethanol solution and ethanol-ethyl lactate solution show that LSP, TLSP-LBFGS, and TLSP-LM can, for both absorbance prediction and concentration prediction, obtain smaller root mean square error of prediction than CLS. Additionally, they can also greatly enhance the accuracy of estimated pure component spectra. However, from the view of concentration prediction, the Wilcoxon signed rank test shows that there is no statistically significant difference between each nonlinear model and CLS. © The Author(s) 2016.
Good Filtrations and the Steinberg Square
DEFF Research Database (Denmark)
Kildetoft, Tobias
that tensoring the Steinberg module with a simple module of restricted highest weight gives a module with a good filtration. This result was first proved by Andersen when the characteristic is large enough. In this dissertation, generalizations of those results, which are joint work with Daniel Nakano......, the socle completely determines how a Steinberg square decomposes. The dissertation also investigates the socle of the Steinberg square for a finite group of Lie type, again providing formulas which describe how to find the multiplicity of a simple module in the socle, given information about...
Mackie's Error Theory and Reasons | Farland | South African Journal ...
African Journals Online (AJOL)
The error theory has, for some time, served as a last resort for those who would like to take moral realism seriously but who cannot countenance the thought that moral properties might be non-natural. As soon as their attempts to 'square' moral properties with natural properties appear to be in trouble, such philosophers ...
Analysis of Students' Error in Learning of Quadratic Equations
Zakaria, Effandi; Ibrahim; Maat, Siti Mistima
2010-01-01
The purpose of the study was to determine the students' error in learning quadratic equation. The samples were 30 form three students from a secondary school in Jambi, Indonesia. Diagnostic test was used as the instrument of this study that included three components: factorization, completing the square and quadratic formula. Diagnostic interview…
Making the most out of least-squares migration
Huang, Yunsong
2014-09-01
Standard migration images can suffer from (1) migration artifacts caused by an undersampled acquisition geometry, (2) poor resolution resulting from a limited recording aperture, (3) ringing artifacts caused by ripples in the source wavelet, and (4) weak amplitudes resulting from geometric spreading, attenuation, and defocusing. These problems can be remedied in part by least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), which aims to linearly invert seismic data for the reflectivity distribution. Given a sufficiently accurate migration velocity model, LSM can mitigate many of the above problems and can produce more resolved migration images, sometimes with more than twice the spatial resolution of standard migration. However, LSM faces two challenges: The computational cost can be an order of magnitude higher than that of standard migration, and the resulting image quality can fail to improve for migration velocity errors of about 5% or more. It is possible to obtain the most from least-squares migration by reducing the cost and velocity sensitivity of LSM.
Making the most out of the least (squares migration)
Dutta, Gaurav
2014-08-05
Standard migration images can suffer from migration artifacts due to 1) poor source-receiver sampling, 2) weak amplitudes caused by geometric spreading, 3) attenuation, 4) defocusing, 5) poor resolution due to limited source-receiver aperture, and 6) ringiness caused by a ringy source wavelet. To partly remedy these problems, least-squares migration (LSM), also known as linearized seismic inversion or migration deconvolution (MD), proposes to linearly invert seismic data for the reflectivity distribution. If the migration velocity model is sufficiently accurate, then LSM can mitigate many of the above problems and lead to a more resolved migration image, sometimes with twice the spatial resolution. However, there are two problems with LSM: the cost can be an order of magnitude more than standard migration and the quality of the LSM image is no better than the standard image for velocity errors of 5% or more. We now show how to get the most from least-squares migration by reducing the cost and velocity sensitivity of LSM.
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
Multilevel weighted least squares polynomial approximation
Haji-Ali, Abdul-Lateef; Nobile, Fabio; Tempone, Raul; Wolfers, Sö ren
2017-01-01
, obtaining polynomial approximations with a single level method can become prohibitively expensive, as it requires a sufficiently large number of samples, each computed with a sufficiently small discretization error. As a solution to this problem, we propose
Evaluation of Data with Systematic Errors
International Nuclear Information System (INIS)
Froehner, F. H.
2003-01-01
Application-oriented evaluated nuclear data libraries such as ENDF and JEFF contain not only recommended values but also uncertainty information in the form of 'covariance' or 'error files'. These can neither be constructed nor utilized properly without a thorough understanding of uncertainties and correlations. It is shown how incomplete information about errors is described by multivariate probability distributions or, more summarily, by covariance matrices, and how correlations are caused by incompletely known common errors. Parameter estimation for the practically most important case of the Gaussian distribution with common errors is developed in close analogy to the more familiar case without. The formalism shows that, contrary to widespread belief, common ('systematic') and uncorrelated ('random' or 'statistical') errors are to be added in quadrature. It also shows explicitly that repetition of a measurement reduces mainly the statistical uncertainties but not the systematic ones. While statistical uncertainties are readily estimated from the scatter of repeatedly measured data, systematic uncertainties can only be inferred from prior information about common errors and their propagation. The optimal way to handle error-affected auxiliary quantities ('nuisance parameters') in data fitting and parameter estimation is to adjust them on the same footing as the parameters of interest and to integrate (marginalize) them out of the joint posterior distribution afterward
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.
Integrating bathymetric and topographic data
Teh, Su Yean; Koh, Hock Lye; Lim, Yong Hui; Tan, Wai Kiat
2017-11-01
The quality of bathymetric and topographic resolution significantly affect the accuracy of tsunami run-up and inundation simulation. However, high resolution gridded bathymetric and topographic data sets for Malaysia are not freely available online. It is desirable to have seamless integration of high resolution bathymetric and topographic data. The bathymetric data available from the National Hydrographic Centre (NHC) of the Royal Malaysian Navy are in scattered form; while the topographic data from the Department of Survey and Mapping Malaysia (JUPEM) are given in regularly spaced grid systems. Hence, interpolation is required to integrate the bathymetric and topographic data into regularly-spaced grid systems for tsunami simulation. The objective of this research is to analyze the most suitable interpolation methods for integrating bathymetric and topographic data with minimal errors. We analyze four commonly used interpolation methods for generating gridded topographic and bathymetric surfaces, namely (i) Kriging, (ii) Multiquadric (MQ), (iii) Thin Plate Spline (TPS) and (iv) Inverse Distance to Power (IDP). Based upon the bathymetric and topographic data for the southern part of Penang Island, our study concluded, via qualitative visual comparison and Root Mean Square Error (RMSE) assessment, that the Kriging interpolation method produces an interpolated bathymetric and topographic surface that best approximate the admiralty nautical chart of south Penang Island.
Self-diffusion of particles interacting through a square-well or square-shoulder potential
Wilbertz, H.; Michels, J.; Beijeren, H. van; Leegwater, J.A.
1988-01-01
The diffusion coefficient and velocity autocorrelation function for a fluid of particles interacting through a square-well or square-shoulder potential are calculated from a kinetic theory similar to the Davis-Rice-Sengers theory and the results are compared to those of computer simulations. At low
Multiples least-squares reverse time migration
Zhang, Dongliang; Zhan, Ge; Dai, Wei; Schuster, Gerard T.
2013-01-01
To enhance the image quality, we propose multiples least-squares reverse time migration (MLSRTM) that transforms each hydrophone into a virtual point source with a time history equal to that of the recorded data. Since each recorded trace is treated
Least-squares variance component estimation
Teunissen, P.J.G.; Amiri-Simkooei, A.R.
2007-01-01
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight
Square root approximation to the poisson channel
Tsiatmas, A.; Willems, F.M.J.; Baggen, C.P.M.J.
2013-01-01
Starting from the Poisson model we present a channel model for optical communications, called the Square Root (SR) Channel, in which the noise is additive Gaussian with constant variance. Initially, we prove that for large peak or average power, the transmission rate of a Poisson Channel when coding
Time Scale in Least Square Method
Directory of Open Access Journals (Sweden)
Özgür Yeniay
2014-01-01
Full Text Available Study of dynamic equations in time scale is a new area in mathematics. Time scale tries to build a bridge between real numbers and integers. Two derivatives in time scale have been introduced and called as delta and nabla derivative. Delta derivative concept is defined as forward direction, and nabla derivative concept is defined as backward direction. Within the scope of this study, we consider the method of obtaining parameters of regression equation of integer values through time scale. Therefore, we implemented least squares method according to derivative definition of time scale and obtained coefficients related to the model. Here, there exist two coefficients originating from forward and backward jump operators relevant to the same model, which are different from each other. Occurrence of such a situation is equal to total number of values of vertical deviation between regression equations and observation values of forward and backward jump operators divided by two. We also estimated coefficients for the model using ordinary least squares method. As a result, we made an introduction to least squares method on time scale. We think that time scale theory would be a new vision in least square especially when assumptions of linear regression are violated.
Group-wise partial least square regression
Camacho, José; Saccenti, Edoardo
2018-01-01
This paper introduces the group-wise partial least squares (GPLS) regression. GPLS is a new sparse PLS technique where the sparsity structure is defined in terms of groups of correlated variables, similarly to what is done in the related group-wise principal component analysis. These groups are
Clar sextets in square graphene antidot lattices
DEFF Research Database (Denmark)
Petersen, Rene; Pedersen, Thomas Garm; Jauho, Antti-Pekka
2011-01-01
A periodic array of holes transforms graphene from a semimetal into a semiconductor with a band gap tuneable by varying the parameters of the lattice. In earlier work only hexagonal lattices have been treated. Using atomistic models we here investigate the size of the band gap of a square lattice...
Deformation analysis with Total Least Squares
Directory of Open Access Journals (Sweden)
M. Acar
2006-01-01
Full Text Available Deformation analysis is one of the main research fields in geodesy. Deformation analysis process comprises measurement and analysis phases. Measurements can be collected using several techniques. The output of the evaluation of the measurements is mainly point positions. In the deformation analysis phase, the coordinate changes in the point positions are investigated. Several models or approaches can be employed for the analysis. One approach is based on a Helmert or similarity coordinate transformation where the displacements and the respective covariance matrix are transformed into a unique datum. Traditionally a Least Squares (LS technique is used for the transformation procedure. Another approach that could be introduced as an alternative methodology is the Total Least Squares (TLS that is considerably a new approach in geodetic applications. In this study, in order to determine point displacements, 3-D coordinate transformations based on the Helmert transformation model were carried out individually by the Least Squares (LS and the Total Least Squares (TLS, respectively. The data used in this study was collected by GPS technique in a landslide area located nearby Istanbul. The results obtained from these two approaches have been compared.
Optimistic semi-supervised least squares classification
DEFF Research Database (Denmark)
Krijthe, Jesse H.; Loog, Marco
2017-01-01
The goal of semi-supervised learning is to improve supervised classifiers by using additional unlabeled training examples. In this work we study a simple self-learning approach to semi-supervised learning applied to the least squares classifier. We show that a soft-label and a hard-label variant ...
International Nuclear Information System (INIS)
Wang, Jianzhou; Hu, Jianming
2015-01-01
With the increasing importance of wind power as a component of power systems, the problems induced by the stochastic and intermittent nature of wind speed have compelled system operators and researchers to search for more reliable techniques to forecast wind speed. This paper proposes a combination model for probabilistic short-term wind speed forecasting. In this proposed hybrid approach, EWT (Empirical Wavelet Transform) is employed to extract meaningful information from a wind speed series by designing an appropriate wavelet filter bank. The GPR (Gaussian Process Regression) model is utilized to combine independent forecasts generated by various forecasting engines (ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM)) in a nonlinear way rather than the commonly used linear way. The proposed approach provides more probabilistic information for wind speed predictions besides improving the forecasting accuracy for single-value predictions. The effectiveness of the proposed approach is demonstrated with wind speed data from two wind farms in China. The results indicate that the individual forecasting engines do not consistently forecast short-term wind speed for the two sites, and the proposed combination method can generate a more reliable and accurate forecast. - Highlights: • The proposed approach can make probabilistic modeling for wind speed series. • The proposed approach adapts to the time-varying characteristic of the wind speed. • The hybrid approach can extract the meaningful components from the wind speed series. • The proposed method can generate adaptive, reliable and more accurate forecasting results. • The proposed model combines four independent forecasting engines in a nonlinear way.
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 ...
BER analysis of regularized least squares for BPSK recovery
Ben Atitallah, Ismail; Thrampoulidis, Christos; Kammoun, Abla; Al-Naffouri, Tareq Y.; Hassibi, Babak; Alouini, Mohamed-Slim
2017-01-01
This paper investigates the problem of recovering an n-dimensional BPSK signal x
BER analysis of regularized least squares for BPSK recovery
Ben Atitallah, Ismail
2017-06-20
This paper investigates the problem of recovering an n-dimensional BPSK signal x
Stock price estimation using ensemble Kalman Filter square root method
Karya, D. F.; Katias, P.; Herlambang, T.
2018-04-01
Shares are securities as the possession or equity evidence of an individual or corporation over an enterprise, especially public companies whose activity is stock trading. Investment in stocks trading is most likely to be the option of investors as stocks trading offers attractive profits. In determining a choice of safe investment in the stocks, the investors require a way of assessing the stock prices to buy so as to help optimize their profits. An effective method of analysis which will reduce the risk the investors may bear is by predicting or estimating the stock price. Estimation is carried out as a problem sometimes can be solved by using previous information or data related or relevant to the problem. The contribution of this paper is that the estimates of stock prices in high, low, and close categorycan be utilized as investors’ consideration for decision making in investment. In this paper, stock price estimation was made by using the Ensemble Kalman Filter Square Root method (EnKF-SR) and Ensemble Kalman Filter method (EnKF). The simulation results showed that the resulted estimation by applying EnKF method was more accurate than that by the EnKF-SR, with an estimation error of about 0.2 % by EnKF and an estimation error of 2.6 % by EnKF-SR.
A general approach to error propagation
International Nuclear Information System (INIS)
Sanborn, J.B.
1987-01-01
A computational approach to error propagation is explained. It is shown that the application of the first-order Taylor theory to a fairly general expression representing an inventory or inventory-difference quantity leads naturally to a data structure that is useful for structuring error-propagation calculations. This data structure incorporates six types of data entities: (1) the objects in the material balance, (2) numerical parameters that describe these objects, (3) groups or sets of objects, (4) the terms which make up the material-balance equation, (5) the errors or sources of variance and (6) the functions or subroutines that represent Taylor partial derivatives. A simple algorithm based on this data structure can be defined using formulas that are sums of squares of sums. The data structures and algorithms described above have been implemented as computer software in FORTRAN for IBM PC-type machines. A free-form data-entry format allows users to separate data as they wish into separate files and enter data using a text editor. The program has been applied to the computation of limits of error for inventory differences (LEIDs) within the DOE complex. 1 ref., 3 figs
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Study of the convergence behavior of the complex kernel least mean square algorithm.
Paul, Thomas K; Ogunfunmi, Tokunbo
2013-09-01
The complex kernel least mean square (CKLMS) algorithm is recently derived and allows for online kernel adaptive learning for complex data. Kernel adaptive methods can be used in finding solutions for neural network and machine learning applications. The derivation of CKLMS involved the development of a modified Wirtinger calculus for Hilbert spaces to obtain the cost function gradient. We analyze the convergence of the CKLMS with different kernel forms for complex data. The expressions obtained enable us to generate theory-predicted mean-square error curves considering the circularity of the complex input signals and their effect on nonlinear learning. Simulations are used for verifying the analysis results.
Square Root Unscented Kalman Filters for State Estimation of Induction Motor Drives
DEFF Research Database (Denmark)
Lascu, Cristian; Jafarzadeh, Saeed; Fadali, M.Sami
2013-01-01
This paper investigates the application, design, and implementation of the square root unscented Kalman filter (UKF) (SRUKF) for induction motor (IM) sensorless drives. The UKF uses nonlinear unscented transforms (UTs) in the prediction step in order to preserve the stochastic characteristics...... of a nonlinear system. The advantage of using the UT is its ability to capture the nonlinear behavior of the system, unlike the extended Kalman filter (EKF) that uses linearized models. The SRUKF implements the UKF using square root filtering to reduce computational errors. We discuss the theoretical aspects...
Robust analysis of trends in noisy tokamak confinement data using geodesic least squares regression
Energy Technology Data Exchange (ETDEWEB)
Verdoolaege, G., E-mail: geert.verdoolaege@ugent.be [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium); Laboratory for Plasma Physics, Royal Military Academy, B-1000 Brussels (Belgium); Shabbir, A. [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium); Max Planck Institute for Plasma Physics, Boltzmannstr. 2, 85748 Garching (Germany); Hornung, G. [Department of Applied Physics, Ghent University, B-9000 Ghent (Belgium)
2016-11-15
Regression analysis is a very common activity in fusion science for unveiling trends and parametric dependencies, but it can be a difficult matter. We have recently developed the method of geodesic least squares (GLS) regression that is able to handle errors in all variables, is robust against data outliers and uncertainty in the regression model, and can be used with arbitrary distribution models and regression functions. We here report on first results of application of GLS to estimation of the multi-machine scaling law for the energy confinement time in tokamaks, demonstrating improved consistency of the GLS results compared to standard least squares.
Zeb, Salman; Yousaf, Muhammad
2017-01-01
In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.
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…
Energy Technology Data Exchange (ETDEWEB)
Aid, R.
1998-01-07
This work comes from an industrial problem of validating numerical solutions of ordinary differential equations modeling power systems. This problem is solved using asymptotic estimators of the global error. Four techniques are studied: Richardson estimator (RS), Zadunaisky's techniques (ZD), integration of the variational equation (EV), and Solving for the correction (SC). We give some precisions on the relative order of SC w.r.t. the order of the numerical method. A new variant of ZD is proposed that uses the Modified Equation. In the case of variable step-size, it is shown that under suitable restriction, on the hypothesis of the step-size selection, ZD and SC are still valid. Moreover, some Runge-Kutta methods are shown to need less hypothesis on the step-sizes to exhibit a valid order of convergence for ZD and SC. Numerical tests conclude this analysis. Industrial cases are given. Finally, an algorithm to avoid the a priori specification of the integration path for complex time differential equations is proposed. (author)
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
Mathematical Construction of Magic Squares Utilizing Base-N Arithmetic
O'Brien, Thomas D.
2006-01-01
Magic squares have been of interest as a source of recreation for over 4,500 years. A magic square consists of a square array of n[squared] positive and distinct integers arranged so that the sum of any column, row, or main diagonal is the same. In particular, an array of consecutive integers from 1 to n[squared] forming an nxn magic square is…
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.
Regularization by truncated total least squares
DEFF Research Database (Denmark)
Hansen, Per Christian; Fierro, R.D; Golub, G.H
1997-01-01
The total least squares (TLS) method is a successful method for noise reduction in linear least squares problems in a number of applications. The TLS method is suited to problems in which both the coefficient matrix and the right-hand side are not precisely known. This paper focuses on the use...... schemes for relativistic hydrodynamical equations. Such an approximate Riemann solver is presented in this paper which treats all waves emanating from an initial discontinuity as themselves discontinuous. Therefore, jump conditions for shocks are approximately used for rarefaction waves. The solver...... is easy to implement in a Godunov scheme and converges rapidly for relativistic hydrodynamics. The fast convergence of the solver indicates the potential of a higher performance of a Godunov scheme in which the solver is used....
Total least squares for anomalous change detection
Theiler, James; Matsekh, Anna M.
2010-04-01
A family of subtraction-based anomalous change detection algorithms is derived from a total least squares (TLSQ) framework. This provides an alternative to the well-known chronochrome algorithm, which is derived from ordinary least squares. In both cases, the most anomalous changes are identified with the pixels that exhibit the largest residuals with respect to the regression of the two images against each other. The family of TLSQbased anomalous change detectors is shown to be equivalent to the subspace RX formulation for straight anomaly detection, but applied to the stacked space. However, this family is not invariant to linear coordinate transforms. On the other hand, whitened TLSQ is coordinate invariant, and special cases of it are equivalent to canonical correlation analysis and optimized covariance equalization. What whitened TLSQ offers is a generalization of these algorithms with the potential for better performance.
Classical square-plus-triangle well fluid
International Nuclear Information System (INIS)
Boghdadi, M.
1984-01-01
A simplified model for the intermolecular-potential function which consists of a hard core and a square-plus-triangle well is proposed. The square width is taken to be lambda 1 -1 and the triangle width is lambda 2 -lambda 1 , where the diameter of the molecules is assumed to be epsilon. Under the restriction that the area under the potential well should be equal to 0.5epsilon, which has its own reason, it is shown that the appropriate choice of lambda 1 and lambda 2 that best mimics the Lennard-Jones (LJ) cut-off results is 1.15 and 1.85 respectively. With this choice for lambda 1 and lambda 2 , the proposed model is effective and satisfactory
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
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.
Elastic least-squares reverse time migration
Feng, Zongcai; Schuster, Gerard T.
2016-01-01
Elastic least-squares reverse time migration (LSRTM) is used to invert synthetic particle-velocity data and crosswell pressure field data. The migration images consist of both the P- and Svelocity perturbation images. Numerical tests on synthetic and field data illustrate the advantages of elastic LSRTM over elastic reverse time migration (RTM). In addition, elastic LSRTM images are better focused and have better reflector continuity than do the acoustic LSRTM images.
Elastic least-squares reverse time migration
Feng, Zongcai
2016-09-06
Elastic least-squares reverse time migration (LSRTM) is used to invert synthetic particle-velocity data and crosswell pressure field data. The migration images consist of both the P- and Svelocity perturbation images. Numerical tests on synthetic and field data illustrate the advantages of elastic LSRTM over elastic reverse time migration (RTM). In addition, elastic LSRTM images are better focused and have better reflector continuity than do the acoustic LSRTM images.
Natural convective heat transfer from square cylinder
Energy Technology Data Exchange (ETDEWEB)
Novomestský, Marcel, E-mail: marcel.novomestsky@fstroj.uniza.sk; Smatanová, Helena, E-mail: helena.smatanova@fstroj.uniza.sk; Kapjor, Andrej, E-mail: andrej.kapjor@fstroj.uniza.sk [University of Žilina, Faculty of Mechanical Engineering, Department of Power Engineering, Univerzitná 1, 010 26 Žilina (Slovakia)
2016-06-30
This article is concerned with natural convective heat transfer from square cylinder mounted on a plane adiabatic base, the cylinders having an exposed cylinder surface according to different horizontal angle. The cylinder receives heat from a radiating heater which results in a buoyant flow. There are many industrial applications, including refrigeration, ventilation and the cooling of electrical components, for which the present study may be applicable.
Least Squares Problems with Absolute Quadratic Constraints
Directory of Open Access Journals (Sweden)
R. Schöne
2012-01-01
Full Text Available This paper analyzes linear least squares problems with absolute quadratic constraints. We develop a generalized theory following Bookstein's conic-fitting and Fitzgibbon's direct ellipse-specific fitting. Under simple preconditions, it can be shown that a minimum always exists and can be determined by a generalized eigenvalue problem. This problem is numerically reduced to an eigenvalue problem by multiplications of Givens' rotations. Finally, four applications of this approach are presented.
A least-squares computational ''tool kit''
International Nuclear Information System (INIS)
Smith, D.L.
1993-04-01
The information assembled in this report is intended to offer a useful computational ''tool kit'' to individuals who are interested in a variety of practical applications for the least-squares method of parameter estimation. The fundamental principles of Bayesian analysis are outlined first and these are applied to development of both the simple and the generalized least-squares conditions. Formal solutions that satisfy these conditions are given subsequently. Their application to both linear and non-linear problems is described in detail. Numerical procedures required to implement these formal solutions are discussed and two utility computer algorithms are offered for this purpose (codes LSIOD and GLSIOD written in FORTRAN). Some simple, easily understood examples are included to illustrate the use of these algorithms. Several related topics are then addressed, including the generation of covariance matrices, the role of iteration in applications of least-squares procedures, the effects of numerical precision and an approach that can be pursued in developing data analysis packages that are directed toward special applications
Advancing Astrophysics with the Square Kilometre Array
Fender, Rob; Govoni, Federica; Green, Jimi; Hoare, Melvin; Jarvis, Matt; Johnston-Hollitt, Melanie; Keane, Evan; Koopmans, Leon; Kramer, Michael; Maartens, Roy; Macquart, Jean-Pierre; Mellema, Garrelt; Oosterloo, Tom; Prandoni, Isabella; Pritchard, Jonathan; Santos, Mario; Seymour, Nick; Stappers, Ben; Staveley-Smith, Lister; Tian, Wen Wu; Umana, Grazia; Wagg, Jeff; Bourke, Tyler L; AASKA14
2015-01-01
In 2014 it was 10 years since the publication of the comprehensive ‘Science with the Square Kilometre Array’ book and 15 years since the first such volume appeared in 1999. In that time numerous and unexpected advances have been made in the fields of astronomy and physics relevant to the capabilities of the Square Kilometre Array (SKA). The SKA itself progressed from an idea to a developing reality with a baselined Phase 1 design (SKA1) and construction planned from 2017. To facilitate the publication of a new, updated science book, which will be relevant to the current astrophysical context, the meeting "Advancing Astrophysics with the Square Kilometre Array" was held in Giardina Naxos, Sicily. Articles were solicited from the community for that meeting to document the scientific advances enabled by the first phase of the SKA and those pertaining to future SKA deployments, with expected gains of 5 times the Phase 1 sensitivity below 350 MHz, about 10 times the Phase 1 sensitivity above 350 MHz and with f...
A negative-norm least-squares method for time-harmonic Maxwell equations
Copeland, Dylan M.
2012-04-01
This paper presents and analyzes a negative-norm least-squares finite element discretization method for the dimension-reduced time-harmonic Maxwell equations in the case of axial symmetry. The reduced equations are expressed in cylindrical coordinates, and the analysis consequently involves weighted Sobolev spaces based on the degenerate radial weighting. The main theoretical results established in this work include existence and uniqueness of the continuous and discrete formulations and error estimates for simple finite element functions. Numerical experiments confirm the error estimates and efficiency of the method for piecewise constant coefficients. © 2011 Elsevier Inc.
Commutative discrete filtering on unstructured grids based on least-squares techniques
International Nuclear Information System (INIS)
Haselbacher, Andreas; Vasilyev, Oleg V.
2003-01-01
The present work is concerned with the development of commutative discrete filters for unstructured grids and contains two main contributions. First, building on the work of Marsden et al. [J. Comp. Phys. 175 (2002) 584], a new commutative discrete filter based on least-squares techniques is constructed. Second, a new analysis of the discrete commutation error is carried out. The analysis indicates that the discrete commutation error is not only dependent on the number of vanishing moments of the filter weights, but also on the order of accuracy of the discrete gradient operator. The results of the analysis are confirmed by grid-refinement studies
Error Control for Network-on-Chip Links
Fu, Bo
2012-01-01
As technology scales into nanoscale regime, it is impossible to guarantee the perfect hardware design. Moreover, if the requirement of 100% correctness in hardware can be relaxed, the cost of manufacturing, verification, and testing will be significantly reduced. Many approaches have been proposed to address the reliability problem of on-chip communications. This book focuses on the use of error control codes (ECCs) to improve on-chip interconnect reliability. Coverage includes detailed description of key issues in NOC error control faced by circuit and system designers, as well as practical error control techniques to minimize the impact of these errors on system performance. Provides a detailed background on the state of error control methods for on-chip interconnects; Describes the use of more complex concatenated codes such as Hamming Product Codes with Type-II HARQ, while emphasizing integration techniques for on-chip interconnect links; Examines energy-efficient techniques for integrating multiple error...
Error threshold ghosts in a simple hypercycle with error prone self-replication
International Nuclear Information System (INIS)
Sardanyes, Josep
2008-01-01
A delayed transition because of mutation processes is shown to happen in a simple hypercycle composed by two indistinguishable molecular species with error prone self-replication. The appearance of a ghost near the hypercycle error threshold causes a delay in the extinction and thus in the loss of information of the mutually catalytic replicators, in a kind of information memory. The extinction time, τ, scales near bifurcation threshold according to the universal square-root scaling law i.e. τ ∼ (Q hc - Q) -1/2 , typical of dynamical systems close to a saddle-node bifurcation. Here, Q hc represents the bifurcation point named hypercycle error threshold, involved in the change among the asymptotic stability phase and the so-called Random Replication State (RRS) of the hypercycle; and the parameter Q is the replication quality factor. The ghost involves a longer transient towards extinction once the saddle-node bifurcation has occurred, being extremely long near the bifurcation threshold. The role of this dynamical effect is expected to be relevant in fluctuating environments. Such a phenomenon should also be found in larger hypercycles when considering the hypercycle species in competition with their error tail. The implications of the ghost in the survival and evolution of error prone self-replicating molecules with hypercyclic organization are discussed
From least squares to multilevel modeling: A graphical introduction to Bayesian inference
Loredo, Thomas J.
2016-01-01
This tutorial presentation will introduce some of the key ideas and techniques involved in applying Bayesian methods to problems in astrostatistics. The focus will be on the big picture: understanding the foundations (interpreting probability, Bayes's theorem, the law of total probability and marginalization), making connections to traditional methods (propagation of errors, least squares, chi-squared, maximum likelihood, Monte Carlo simulation), and highlighting problems where a Bayesian approach can be particularly powerful (Poisson processes, density estimation and curve fitting with measurement error). The "graphical" component of the title reflects an emphasis on pictorial representations of some of the math, but also on the use of graphical models (multilevel or hierarchical models) for analyzing complex data. Code for some examples from the talk will be available to participants, in Python and in the Stan probabilistic programming language.
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.
XAFS study of copper(II) complexes with square planar and square pyramidal coordination geometries
Gaur, A.; Klysubun, W.; Nitin Nair, N.; Shrivastava, B. D.; Prasad, J.; Srivastava, K.
2016-08-01
X-ray absorption fine structure of six Cu(II) complexes, Cu2(Clna)4 2H2O (1), Cu2(ac)4 2H2O (2), Cu2(phac)4 (pyz) (3), Cu2(bpy)2(na)2 H2O (ClO4) (4), Cu2(teen)4(OH)2(ClO4)2 (5) and Cu2(tmen)4(OH)2(ClO4)2 (6) (where ac, phac, pyz, bpy, na, teen, tmen = acetate, phenyl acetate, pyrazole, bipyridine, nicotinic acid, tetraethyethylenediamine, tetramethylethylenediamine, respectively), which were supposed to have square pyramidal and square planar coordination geometries have been investigated. The differences observed in the X-ray absorption near edge structure (XANES) features of the standard compounds having four, five and six coordination geometry points towards presence of square planar and square pyramidal geometry around Cu centre in the studied complexes. The presence of intense pre-edge feature in the spectra of four complexes, 1-4, indicates square pyramidal coordination. Another important XANES feature, present in complexes 5 and 6, is prominent shoulder in the rising part of edge whose intensity decreases in the presence of axial ligands and thus indicates four coordination in these complexes. Ab initio calculations were carried out for square planar and square pyramidal Cu centres to observe the variation of 4p density of states in the presence and absence of axial ligands. To determine the number and distance of scattering atoms around Cu centre in the complexes, EXAFS analysis has been done using the paths obtained from Cu(II) oxide model and an axial Cu-O path from model of a square pyramidal complex. The results obtained from EXAFS analysis have been reported which confirmed the inference drawn from XANES features. Thus, it has been shown that these paths from model of a standard compound can be used to determine the structural parameters for complexes having unknown structure.
Lax-pair operators for squared-sum and squared-difference eigenfunctions
International Nuclear Information System (INIS)
Ichikawa, Yoshihiko; Iino, Kazuhiro.
1984-10-01
Inter-relationship between various representations of the inverse scattering transformation is established by examining eigenfunctions of Lax-pair operators of the sine-Gordon equation and the modified Korteweg-de Vries equation. In particular, it is shown explicitly that there exists Lax-pair operators for the squared-sum and squared-difference eigenfunctions of the Ablowitz-Kaup-Newell-Segur inverse scattering transformation. (author)
Schaffrin, Burkhard; Felus, Yaron A.
2008-06-01
The multivariate total least-squares (MTLS) approach aims at estimating a matrix of parameters, Ξ, from a linear model ( Y- E Y = ( X- E X ) · Ξ) that includes an observation matrix, Y, another observation matrix, X, and matrices of randomly distributed errors, E Y and E X . Two special cases of the MTLS approach include the standard multivariate least-squares approach where only the observation matrix, Y, is perturbed by random errors and, on the other hand, the data least-squares approach where only the coefficient matrix X is affected by random errors. In a previous contribution, the authors derived an iterative algorithm to solve the MTLS problem by using the nonlinear Euler-Lagrange conditions. In this contribution, new lemmas are developed to analyze the iterative algorithm, modify it, and compare it with a new ‘closed form’ solution that is based on the singular-value decomposition. For an application, the total least-squares approach is used to estimate the affine transformation parameters that convert cadastral data from the old to the new Israeli datum. Technical aspects of this approach, such as scaling the data and fixing the columns in the coefficient matrix are investigated. This case study illuminates the issue of “symmetry” in the treatment of two sets of coordinates for identical point fields, a topic that had already been emphasized by Teunissen (1989, Festschrift to Torben Krarup, Geodetic Institute Bull no. 58, Copenhagen, Denmark, pp 335-342). The differences between the standard least-squares and the TLS approach are analyzed in terms of the estimated variance component and a first-order approximation of the dispersion matrix of the estimated parameters.
A weak Galerkin least-squares finite element method for div-curl systems
Li, Jichun; Ye, Xiu; Zhang, Shangyou
2018-06-01
In this paper, we introduce a weak Galerkin least-squares method for solving div-curl problem. This finite element method leads to a symmetric positive definite system and has the flexibility to work with general meshes such as hybrid mesh, polytopal mesh and mesh with hanging nodes. Error estimates of the finite element solution are derived. The numerical examples demonstrate the robustness and flexibility of the proposed method.
Feasibility study on the least square method for fitting non-Gaussian noise data
Xu, Wei; Chen, Wen; Liang, Yingjie
2018-02-01
This study is to investigate the feasibility of least square method in fitting non-Gaussian noise data. We add different levels of the two typical non-Gaussian noises, Lévy and stretched Gaussian noises, to exact value of the selected functions including linear equations, polynomial and exponential equations, and the maximum absolute and the mean square errors are calculated for the different cases. Lévy and stretched Gaussian distributions have many applications in fractional and fractal calculus. It is observed that the non-Gaussian noises are less accurately fitted than the Gaussian noise, but the stretched Gaussian cases appear to perform better than the Lévy noise cases. It is stressed that the least-squares method is inapplicable to the non-Gaussian noise cases when the noise level is larger than 5%.
Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines
International Nuclear Information System (INIS)
Niazi, Ali; Jameh-Bozorghi, Saeed; Nori-Shargh, Davood
2008-01-01
A quantitative structure-property relationship (QSPR) study is suggested for the prediction of toxicity (IGC 50 ) of nitrobenzenes. Ab initio theory was used to calculate some quantum chemical descriptors including electrostatic potentials and local charges at each atom, HOMO and LUMO energies, etc. Modeling of the IGC 50 of nitrobenzenes as a function of molecular structures was established by means of the least squares support vector machines (LS-SVM). This model was applied for the prediction of the toxicity (IGC 50 ) of nitrobenzenes, which were not in the modeling procedure. The resulted model showed high prediction ability with root mean square error of prediction of 0.0049 for LS-SVM. Results have shown that the introduction of LS-SVM for quantum chemical descriptors drastically enhances the ability of prediction in QSAR studies superior to multiple linear regression and partial least squares
State Estimation of Permanent Magnet Synchronous Motor Using Improved Square Root UKF
Directory of Open Access Journals (Sweden)
Bo Xu
2016-06-01
Full Text Available This paper focuses on an improved square root unscented Kalman filter (SRUKF and its application for rotor speed and position estimation of permanent magnet synchronous motor (PMSM. The approach, which combines the SRUKF and strong tracking filter, uses the minimal skew simplex transformation to reduce the number of the sigma points, and utilizes the square root filtering to reduce computational errors. The time-varying fading factor and softening factor are introduced to self-adjust the gain matrices and the state forecast covariance square root matrix, which can realize the residuals orthogonality and force the SRUKF to track the real state rapidly. The theoretical analysis of the improved SRUKF and implementation details for PMSM state estimation are examined. The simulation results show that the improved SRUKF has higher nonlinear approximation accuracy, stronger numerical stability and computational efficiency, and it is an effective and powerful tool for PMSM state estimation under the conditions of step response or load disturbance.
Metering error quantification under voltage and current waveform distortion
Wang, Tao; Wang, Jia; Xie, Zhi; Zhang, Ran
2017-09-01
With integration of more and more renewable energies and distortion loads into power grid, the voltage and current waveform distortion results in metering error in the smart meters. Because of the negative effects on the metering accuracy and fairness, it is an important subject to study energy metering combined error. In this paper, after the comparing between metering theoretical value and real recorded value under different meter modes for linear and nonlinear loads, a quantification method of metering mode error is proposed under waveform distortion. Based on the metering and time-division multiplier principles, a quantification method of metering accuracy error is proposed also. Analyzing the mode error and accuracy error, a comprehensive error analysis method is presented which is suitable for new energy and nonlinear loads. The proposed method has been proved by simulation.
Prevalence of Refractive Error and Visual Impairment among Rural ...
African Journals Online (AJOL)
Refractive error was the major cause of visual impairment accounting for 54% of all causes in the study group. No child was found wearing ... So, large scale community level screening for refractive error should be conducted and integrated with regular school eye screening programs. Effective strategies need to be devised ...
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.)
Filter Tuning Using the Chi-Squared Statistic
Lilly-Salkowski, Tyler
2017-01-01
The Goddard Space Flight Center (GSFC) Flight Dynamics Facility (FDF) performs orbit determination (OD) for the Aqua and Aura satellites. Both satellites are located in low Earth orbit (LEO), and are part of what is considered the A-Train satellite constellation. Both spacecraft are currently in the science phase of their respective missions. The FDF has recently been tasked with delivering definitive covariance for each satellite.The main source of orbit determination used for these missions is the Orbit Determination Toolkit developed by Analytical Graphics Inc. (AGI). This software uses an Extended Kalman Filter (EKF) to estimate the states of both spacecraft. The filter incorporates force modelling, ground station and space network measurements to determine spacecraft states. It also generates a covariance at each measurement. This covariance can be useful for evaluating the overall performance of the tracking data measurements and the filter itself. An accurate covariance is also useful for covariance propagation which is utilized in collision avoidance operations. It is also valuable when attempting to determine if the current orbital solution will meet mission requirements in the future.This paper examines the use of the Chi-square statistic as a means of evaluating filter performance. The Chi-square statistic is calculated to determine the realism of a covariance based on the prediction accuracy and the covariance values at a given point in time. Once calculated, it is the distribution of this statistic that provides insight on the accuracy of the covariance.For the EKF to correctly calculate the covariance, error models associated with tracking data measurements must be accurately tuned. Over estimating or under estimating these error values can have detrimental effects on the overall filter performance. The filter incorporates ground station measurements, which can be tuned based on the accuracy of the individual ground stations. It also includes
Composite Gauss-Legendre Quadrature with Error Control
Prentice, J. S. C.
2011-01-01
We describe composite Gauss-Legendre quadrature for determining definite integrals, including a means of controlling the approximation error. We compare the form and performance of the algorithm with standard Newton-Cotes quadrature. (Contains 1 table.)
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.
Angular discretization errors in transport theory
International Nuclear Information System (INIS)
Nelson, P.; Yu, F.
1992-01-01
Elements of the information-based complexity theory are computed for several types of information and associated algorithms for angular approximations in the setting of a on-dimensional model problem. For point-evaluation information, the local and global radii of information are computed, a (trivial) optimal algorithm is determined, and the local and global error of a discrete ordinates algorithm are shown to be infinite. For average cone-integral information, the local and global radii of information are computed, the local and global error tends to zero as the underlying partition is indefinitely refined. A central algorithm for such information and an optimal partition (of given cardinality) are described. It is further shown that the analytic first-collision source method has zero error (for the purely absorbing model problem). Implications of the restricted problem domains suitable for the various types of information are discussed
Frequent methodological errors in clinical research.
Silva Aycaguer, L C
2018-03-07
Several errors that are frequently present in clinical research are listed, discussed and illustrated. A distinction is made between what can be considered an "error" arising from ignorance or neglect, from what stems from a lack of integrity of researchers, although it is recognized and documented that it is not easy to establish when we are in a case and when in another. The work does not intend to make an exhaustive inventory of such problems, but focuses on those that, while frequent, are usually less evident or less marked in the various lists that have been published with this type of problems. It has been a decision to develop in detail the examples that illustrate the problems identified, instead of making a list of errors accompanied by an epidermal description of their characteristics. Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.
Are Low-order Covariance Estimates Useful in Error Analyses?
Baker, D. F.; Schimel, D.
2005-12-01
Atmospheric trace gas inversions, using modeled atmospheric transport to infer surface sources and sinks from measured concentrations, are most commonly done using least-squares techniques that return not only an estimate of the state (the surface fluxes) but also the covariance matrix describing the uncertainty in that estimate. Besides allowing one to place error bars around the estimate, the covariance matrix may be used in simulation studies to learn what uncertainties would be expected from various hypothetical observing strategies. This error analysis capability is routinely used in designing instrumentation, measurement campaigns, and satellite observing strategies. For example, Rayner, et al (2002) examined the ability of satellite-based column-integrated CO2 measurements to constrain monthly-average CO2 fluxes for about 100 emission regions using this approach. Exact solutions for both state vector and covariance matrix become computationally infeasible, however, when the surface fluxes are solved at finer resolution (e.g., daily in time, under 500 km in space). It is precisely at these finer scales, however, that one would hope to be able to estimate fluxes using high-density satellite measurements. Non-exact estimation methods such as variational data assimilation or the ensemble Kalman filter could be used, but they achieve their computational savings by obtaining an only approximate state estimate and a low-order approximation of the true covariance. One would like to be able to use this covariance matrix to do the same sort of error analyses as are done with the full-rank covariance, but is it correct to do so? Here we compare uncertainties and `information content' derived from full-rank covariance matrices obtained from a direct, batch least squares inversion to those from the incomplete-rank covariance matrices given by a variational data assimilation approach solved with a variable metric minimization technique (the Broyden-Fletcher- Goldfarb
Leonardo Pisano (Fibonacci) the book of squares
Sigler, L E
1987-01-01
The Book of Squares by Fibonacci is a gem in the mathematical literature and one of the most important mathematical treatises written in the Middle Ages. It is a collection of theorems on indeterminate analysis and equations of second degree which yield, among other results, a solution to a problem proposed by Master John of Palermo to Leonardo at the Court of Frederick II. The book was dedicated and presented to the Emperor at Pisa in 1225. Dating back to the 13th century the book exhibits the early and continued fascination of men with our number system and the relationship among numbers
Least Squares Methods for Equidistant Tree Reconstruction
Fahey, Conor; Hosten, Serkan; Krieger, Nathan; Timpe, Leslie
2008-01-01
UPGMA is a heuristic method identifying the least squares equidistant phylogenetic tree given empirical distance data among $n$ taxa. We study this classic algorithm using the geometry of the space of all equidistant trees with $n$ leaves, also known as the Bergman complex of the graphical matroid for the complete graph $K_n$. We show that UPGMA performs an orthogonal projection of the data onto a maximal cell of the Bergman complex. We also show that the equidistant tree with the least (Eucl...
Magnetics calculations for an ELMO Bumpy square
International Nuclear Information System (INIS)
Santoro, R.T.; Uckan, N.A.; Schmidt, R.J.
1985-01-01
Advanced ELMO Bumpy Torus (EBT) concepts have been studied in an effort to determine the potential for new and different concepts as confinement experiments or as reactors. Several magnetic configurations based on the EBT confinement concept were developed including the ELMO Bumpy Square (EBS). The EBS was selected as a possible candidate for near-term study because of its potential for resolving critical EBT issues, for its desirability as a reactor, and for anticipated contributions to the physics and technology of fusion. This paper summarizes magnetics calculations that were carried out in support of studies to assess the merits of an EBS
Square tracking sensor for autonomous helicopter hover stabilization
Oertel, Carl-Henrik
1995-06-01
Sensors for synthetic vision are needed to extend the mission profiles of helicopters. A special task for various applications is the autonomous position hold of a helicopter above a ground fixed or moving target. As a proof of concept for a general synthetic vision solution a restricted machine vision system, which is capable of locating and tracking a special target, was developed by the Institute of Flight Mechanics of Deutsche Forschungsanstalt fur Luft- und Raumfahrt e.V. (i.e., German Aerospace Research Establishment). This sensor, which is specialized to detect and track a square, was integrated in the fly-by-wire helicopter ATTHeS (i.e., Advanced Technology Testing Helicopter System). An existing model following controller for the forward flight condition was adapted for the hover and low speed requirements of the flight vehicle. The special target, a black square with a length of one meter, was mounted on top of a car. Flight tests demonstrated the automatic stabilization of the helicopter above the moving car by synthetic vision.
Federal Laboratory Consortium — Located near the center of the 586-square-mile Hanford Site is the Integrated Disposal Facility, also known as the IDF.This facility is a landfill similar in concept...
Polynomial fuzzy observer designs: a sum-of-squares approach.
Tanaka, Kazuo; Ohtake, Hiroshi; Seo, Toshiaki; Tanaka, Motoyasu; Wang, Hua O
2012-10-01
This paper presents a sum-of-squares (SOS) approach to polynomial fuzzy observer designs for three classes of polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi-Sugeno (T-S) fuzzy controller and observer designs. First, we briefly summarize previous results with respect to a polynomial fuzzy system that is a more general representation of the well-known T-S fuzzy system. Next, we propose polynomial fuzzy observers to estimate states in three classes of polynomial fuzzy systems and derive SOS conditions to design polynomial fuzzy controllers and observers. A remarkable feature of the SOS design conditions for the first two classes (Classes I and II) is that they realize the so-called separation principle, i.e., the polynomial fuzzy controller and observer for each class can be separately designed without lack of guaranteeing the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. Although, for the last class (Class III), the separation principle does not hold, we propose an algorithm to design polynomial fuzzy controller and observer satisfying the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. All the design conditions in the proposed approach can be represented in terms of SOS and are symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. To illustrate the validity and applicability of the proposed approach, three design examples are provided. The examples demonstrate the advantages of the SOS-based approaches for the existing LMI approaches to T-S fuzzy observer designs.
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)
Mikuls, Ted R; Curtis, Jeffrey R; Allison, Jeroan J; Hicks, Rodney W; Saag, Kenneth G
2006-03-01
To more closely assess medication errors in gout care, we examined data from a national, Internet-accessible error reporting program over a 5-year reporting period. We examined data from the MEDMARX database, covering the period from January 1, 1999 through December 31, 2003. For allopurinol and colchicine, we examined error severity, source, type, contributing factors, and healthcare personnel involved in errors, and we detailed errors resulting in patient harm. Causes of error and the frequency of other error characteristics were compared for gout medications versus other musculoskeletal treatments using the chi-square statistic. Gout medication errors occurred in 39% (n = 273) of facilities participating in the MEDMARX program. Reported errors were predominantly from the inpatient hospital setting and related to the use of allopurinol (n = 524), followed by colchicine (n = 315), probenecid (n = 50), and sulfinpyrazone (n = 2). Compared to errors involving other musculoskeletal treatments, allopurinol and colchicine errors were more often ascribed to problems with physician prescribing (7% for other therapies versus 23-39% for allopurinol and colchicine, p < 0.0001) and less often due to problems with drug administration or nursing error (50% vs 23-27%, p < 0.0001). Our results suggest that inappropriate prescribing practices are characteristic of errors occurring with the use of allopurinol and colchicine. Physician prescribing practices are a potential target for quality improvement interventions in gout care.
Edge maps: Representing flow with bounded error
Bhatia, Harsh
2011-03-01
Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Many analysis techniques rely on computing streamlines, a task often hampered by numerical instabilities. Approaches that ignore the resulting errors can lead to inconsistencies that may produce unreliable visualizations and ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with linear maps defined on its boundary. This representation, called edge maps, is equivalent to computing all possible streamlines at a user defined error threshold. In spite of this error, all the streamlines computed using edge maps will be pairwise disjoint. Furthermore, our representation stores the error explicitly, and thus can be used to produce more informative visualizations. Given a piecewise-linear interpolated vector field, a recent result [15] shows that there are only 23 possible map classes for a triangle, permitting a concise description of flow behaviors. This work describes the details of computing edge maps, provides techniques to quantify and refine edge map error, and gives qualitative and visual comparisons to more traditional techniques. © 2011 IEEE.
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...
Triple-Error-Correcting Codec ASIC
Jones, Robert E.; Segallis, Greg P.; Boyd, Robert
1994-01-01
Coder/decoder constructed on single integrated-circuit chip. Handles data in variety of formats at rates up to 300 Mbps, correcting up to 3 errors per data block of 256 to 512 bits. Helps reduce cost of transmitting data. Useful in many high-data-rate, bandwidth-limited communication systems such as; personal communication networks, cellular telephone networks, satellite communication systems, high-speed computing networks, broadcasting, and high-reliability data-communication links.
Olivares, A.; Górriz, J. M.; Ramírez, J.; Olivares, G.
2011-02-01
Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed.
International Nuclear Information System (INIS)
Olivares, A; Olivares, G; Górriz, J M; Ramírez, J
2011-01-01
Inertial sensors are widely used in human body motion monitoring systems since they permit us to determine the position of the subject's limbs. Limb angle measurement is carried out through the integration of the angular velocity measured by a rate sensor and the decomposition of the components of static gravity acceleration measured by an accelerometer. Different factors derived from the sensors' nature, such as the angle random walk and dynamic bias, lead to erroneous measurements. Dynamic bias effects can be reduced through the use of adaptive filtering based on sensor fusion concepts. Most existing published works use a Kalman filtering sensor fusion approach. Our aim is to perform a comparative study among different adaptive filters. Several least mean squares (LMS), recursive least squares (RLS) and Kalman filtering variations are tested for the purpose of finding the best method leading to a more accurate and robust limb angle measurement. A new angle wander compensation sensor fusion approach based on LMS and RLS filters has been developed
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....
Vapor-liquid equilibrium and critical asymmetry of square well and short square well chain fluids.
Li, Liyan; Sun, Fangfang; Chen, Zhitong; Wang, Long; Cai, Jun
2014-08-07
The critical behavior of square well fluids with variable interaction ranges and of short square well chain fluids have been investigated by grand canonical ensemble Monte Carlo simulations. The critical temperatures and densities were estimated by a finite-size scaling analysis with the help of histogram reweighting technique. The vapor-liquid coexistence curve in the near-critical region was determined using hyper-parallel tempering Monte Carlo simulations. The simulation results for coexistence diameters show that the contribution of |t|(1-α) to the coexistence diameter dominates the singular behavior in all systems investigated. The contribution of |t|(2β) to the coexistence diameter is larger for the system with a smaller interaction range λ. While for short square well chain fluids, longer the chain length, larger the contribution of |t|(2β). The molecular configuration greatly influences the critical asymmetry: a short soft chain fluid shows weaker critical asymmetry than a stiff chain fluid with same chain length.
Cichocki, A; Unbehauen, R
1994-01-01
In this paper a new class of simplified low-cost analog artificial neural networks with on chip adaptive learning algorithms are proposed for solving linear systems of algebraic equations in real time. The proposed learning algorithms for linear least squares (LS), total least squares (TLS) and data least squares (DLS) problems can be considered as modifications and extensions of well known algorithms: the row-action projection-Kaczmarz algorithm and/or the LMS (Adaline) Widrow-Hoff algorithms. The algorithms can be applied to any problem which can be formulated as a linear regression problem. The correctness and high performance of the proposed neural networks are illustrated by extensive computer simulation results.
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.
The possibilities of least-squares migration of internally scattered seismic energy
Aldawood, Ali
2015-05-26
Approximate images of the earth’s subsurface structures are usually obtained by migrating surface seismic data. Least-squares migration, under the single-scattering assumption, is used as an iterative linearized inversion scheme to suppress migration artifacts, deconvolve the source signature, mitigate the acquisition fingerprint, and enhance the spatial resolution of migrated images. The problem with least-squares migration of primaries, however, is that it may not be able to enhance events that are mainly illuminated by internal multiples, such as vertical and nearly vertical faults or salt flanks. To alleviate this problem, we adopted a linearized inversion framework to migrate internally scattered energy. We apply the least-squares migration of first-order internal multiples to image subsurface vertical fault planes. Tests on synthetic data demonstrated the ability of the proposed method to resolve vertical fault planes, which are poorly illuminated by the least-squares migration of primaries only. The proposed scheme is robust in the presence of white Gaussian observational noise and in the case of imaging the fault planes using inaccurate migration velocities. Our results suggested that the proposed least-squares imaging, under the double-scattering assumption, still retrieved the vertical fault planes when imaging the scattered data despite a slight defocusing of these events due to the presence of noise or velocity errors.
The possibilities of least-squares migration of internally scattered seismic energy
Aldawood, Ali; Hoteit, Ibrahim; Zuberi, Mohammad; Turkiyyah, George; Alkhalifah, Tariq Ali
2015-01-01
Approximate images of the earth’s subsurface structures are usually obtained by migrating surface seismic data. Least-squares migration, under the single-scattering assumption, is used as an iterative linearized inversion scheme to suppress migration artifacts, deconvolve the source signature, mitigate the acquisition fingerprint, and enhance the spatial resolution of migrated images. The problem with least-squares migration of primaries, however, is that it may not be able to enhance events that are mainly illuminated by internal multiples, such as vertical and nearly vertical faults or salt flanks. To alleviate this problem, we adopted a linearized inversion framework to migrate internally scattered energy. We apply the least-squares migration of first-order internal multiples to image subsurface vertical fault planes. Tests on synthetic data demonstrated the ability of the proposed method to resolve vertical fault planes, which are poorly illuminated by the least-squares migration of primaries only. The proposed scheme is robust in the presence of white Gaussian observational noise and in the case of imaging the fault planes using inaccurate migration velocities. Our results suggested that the proposed least-squares imaging, under the double-scattering assumption, still retrieved the vertical fault planes when imaging the scattered data despite a slight defocusing of these events due to the presence of noise or velocity errors.
Maggin, Daniel M.; Swaminathan, Hariharan; Rogers, Helen J.; O'Keeffe, Breda V.; Sugai, George; Horner, Robert H.
2011-01-01
A new method for deriving effect sizes from single-case designs is proposed. The strategy is applicable to small-sample time-series data with autoregressive errors. The method uses Generalized Least Squares (GLS) to model the autocorrelation of the data and estimate regression parameters to produce an effect size that represents the magnitude of…
Statistical error of spin transfer to hyperon at RHIC energy
International Nuclear Information System (INIS)
Han Ran; Mao Yajun
2009-01-01
From the RHIC/PHENIX experiment data, it is found that the statistical error of spin transfer is few times larger than the statistical error of the single spin asymmetry. In order to verify the difference between σDLL and σAL, the linear least squares method was used to check it first, and then a simple Monte-Carlo simulation to test this factor again. The simulation is consistent with the calculation result which indicates that the few times difference is reasonable. (authors)
DEM4-26, Least Square Fit for IBM PC by Deming Method
International Nuclear Information System (INIS)
Rinard, P.M.; Bosler, G.E.
1989-01-01
1 - Description of program or function: DEM4-26 is a generalized least square fitting program based on Deming's method. Functions built into the program for fitting include linear, quadratic, cubic, power, Howard's, exponential, and Gaussian; others can easily be added. The program has the following capabilities: (1) entry, editing, and saving of data; (2) fitting of any of the built-in functions or of a user-supplied function; (3) plotting the data and fitted function on the display screen, with error limits if requested, and with the option of copying the plot to the printer; (4) interpolation of x or y values from the fitted curve with error estimates based on error limits selected by the user; and (5) plotting the residuals between the y data values and the fitted curve, with the option copying the plot to the printer. 2 - Method of solution: Deming's method
Error review: Can this improve reporting performance?
International Nuclear Information System (INIS)
Tudor, Gareth R.; Finlay, David B.
2001-01-01
AIM: This study aimed to assess whether error review can improve radiologists' reporting performance. MATERIALS AND METHODS: Ten Consultant Radiologists reported 50 plain radiographs, in which the diagnoses were established. Eighteen of the radiographs were normal, 32 showed an abnormality. The radiologists were shown their errors and then re-reported the series of radiographs after an interval of 4-5 months. The accuracy of the reports to the established diagnoses was assessed. Chi-square test was used to calculate the difference between the viewings. RESULTS: On re-reporting the radiographs, seven radiologists improved their accuracy score, two had a lower score and one radiologist showed no score difference. Mean accuracy pre-education was 82.2%, (range 78-92%) and post-education was 88%, (range 76-96%). Individually, two of the radiologists showed a statistically significant improvement post-education (P < 0.01,P < 0.05). Assessing the group as a whole, there was a trend for improvement post-education but this did not reach statistical significance. Assessing only the radiographs where errors were made on the initial viewing, for the group as a whole there was a 63% improvement post-education. CONCLUSION: We suggest that radiologists benefit from error review, although there was not a statistically significant improvement for the series of radiographs in total. This is partly explained by the fact that some radiologists gave incorrect responses post-education that had initially been correct, thus masking the effect of the educational intervention. Tudor, G.R. and Finlay, D.B. (2001
Modified Firefly Algorithm based controller design for integrating and unstable delay processes
Directory of Open Access Journals (Sweden)
A. Gupta
2016-03-01
Full Text Available In this paper, Modified Firefly Algorithm has been used for optimizing the controller parameters of Smith predictor structure. The proposed algorithm modifies the position formula of the standard Firefly Algorithm in order to achieve faster convergence rate. Performance criteria Integral Square Error (ISE is optimized using this optimization technique. Simulation results show high performance for Modified Firefly Algorithm as compared to conventional Firefly Algorithm in terms of convergence rate. Integrating and unstable delay processes are taken as examples to indicate the performance of the proposed method.
Short-range inverse-square law experiment in space
International Nuclear Information System (INIS)
Strayer, D.M.; Paik, H.J.; Moody, M.V.
2003-01-01
The objective of ISLES (inverse-square law experiment in space) is to perform a null test of Newton's law on the ISS with a resolution of one part in 10 5 at ranges from 100 mm to 1 mm. ISLES will be sensitive enough to detect axions with the strongest allowed coupling and to test the string-theory prediction with R>= 5 μm. To accomplish these goals on the rather noisy International Space Station, the experiment is set up to provide immunity from the vibrations and other common-mode accelerations. The measures to be applied for reducing the effects of disturbances will be described in this presentation. As designed, the experiment will be cooled to less than 2 K in NASA's low temperature facility the LTMPF, allowing superconducting magnetic levitation in microgravity to obtain very soft, low-loss suspension of the test masses. The low-damping magnetic levitation, combined with a low-noise SQUID, leads to extremely low intrinsic noise in the detector. To minimize Newtonian errors, ISLES employs a near-null source of gravity, a circular disk of large diameter-to-thickness ratio. Two test masses, also disk-shaped, are suspended on the two sides of the source mass at a distance of 100 μm to 1 mm. The signal is detected by a superconducting differential accelerometer, making a highly sensitive sensor of the gravity force generated by the source mass
3D plane-wave least-squares Kirchhoff migration
Wang, Xin
2014-08-05
A three dimensional least-squares Kirchhoff migration (LSM) is developed in the prestack plane-wave domain to increase the quality of migration images and the computational efficiency. Due to the limitation of current 3D marine acquisition geometries, a cylindrical-wave encoding is adopted for the narrow azimuth streamer data. To account for the mispositioning of reflectors due to errors in the velocity model, a regularized LSM is devised so that each plane-wave or cylindrical-wave gather gives rise to an individual migration image, and a regularization term is included to encourage the similarities between the migration images of similar encoding schemes. Both synthetic and field results show that: 1) plane-wave or cylindrical-wave encoding LSM can achieve both computational and IO saving, compared to shot-domain LSM, however, plane-wave LSM is still about 5 times more expensive than plane-wave migration; 2) the regularized LSM is more robust compared to LSM with one reflectivity model common for all the plane-wave or cylindrical-wave gathers.
Antena Cerdas untuk Mitigasi Interferensi dengan Algoritma Least Mean Square
Directory of Open Access Journals (Sweden)
Rahmad Hidayat
2017-06-01
Full Text Available Antena cerdas pada dasarnya merupakan susunan antena dengan kemampuan pemrosesan sinyal untuk mengirim/menerima informasi secara adaptif. Kemampuan ini harus terus didalami untuk dicarikan algoritma adaptif terbaik bagi kemampuan beamforming yang diinginkan. Tulisan ini bertujuan untuk memberikan kajian dan analisis pengaruh algoritma Least Mean Square (LMS pada pengaturan nulling beam pola radiasi susunan antena cerdas dalam perannya terhadap mitigasi interferensi. Simulasi kinerja beamformer untuk sebanyak 250 iterasi dilakukan dengan tool Matlab pada kanal AWGN (Additional White Noise Gaussian dan parameter simulasi diubah untuk membandingkan dua buah harga step size m pada algoritma LMS untuk beberapa jumlah elemen antena. Pengaruh nilai step size m, terlihat pada jumlah iterasi yang dilangsungkan sebelum error noise minimum diperoleh, dimana dengan naiknya nilai step size ini maka semakin mengurangi jumlah iterasi, rata-rata menjadi 60. Dari pola respon amplitudo setelah proses beamforming , posisi sinyal utama (0 dB tepat di sudut 30° dan dihasilkan 15 posisi nulling untuk 16 elemen antena. Sumber interferensi dihilangkan / ditutup dengan menempatkan ’nulls’ dalam arah sumber interferensi tersebut di posisi 60° dan -40° dengan masing-masing level diperoleh berkisar sebesar -115 dB
Performance analysis of different tuning rules for an isothermal CSTR using integrated EPC and SPC
Roslan, A. H.; Karim, S. F. Abd; Hamzah, N.
2018-03-01
This paper demonstrates the integration of Engineering Process Control (EPC) and Statistical Process Control (SPC) for the control of product concentration of an isothermal CSTR. The objectives of this study are to evaluate the performance of Ziegler-Nichols (Z-N), Direct Synthesis, (DS) and Internal Model Control (IMC) tuning methods and determine the most effective method for this process. The simulation model was obtained from past literature and re-constructed using SIMULINK MATLAB to evaluate the process response. Additionally, the process stability, capability and normality were analyzed using Process Capability Sixpack reports in Minitab. Based on the results, DS displays the best response for having the smallest rise time, settling time, overshoot, undershoot, Integral Time Absolute Error (ITAE) and Integral Square Error (ISE). Also, based on statistical analysis, DS yields as the best tuning method as it exhibits the highest process stability and capability.
Quantum mechanical streamlines. I - Square potential barrier
Hirschfelder, J. O.; Christoph, A. C.; Palke, W. E.
1974-01-01
Exact numerical calculations are made for scattering of quantum mechanical particles hitting a square two-dimensional potential barrier (an exact analog of the Goos-Haenchen optical experiments). Quantum mechanical streamlines are plotted and found to be smooth and continuous, to have continuous first derivatives even through the classical forbidden region, and to form quantized vortices around each of the nodal points. A comparison is made between the present numerical calculations and the stationary wave approximation, and good agreement is found between both the Goos-Haenchen shifts and the reflection coefficients. The time-independent Schroedinger equation for real wavefunctions is reduced to solving a nonlinear first-order partial differential equation, leading to a generalization of the Prager-Hirschfelder perturbation scheme. Implications of the hydrodynamical formulation of quantum mechanics are discussed, and cases are cited where quantum and classical mechanical motions are identical.
Square well approximation to the optical potential
International Nuclear Information System (INIS)
Jain, A.K.; Gupta, M.C.; Marwadi, P.R.
1976-01-01
Approximations for obtaining T-matrix elements for a sum of several potentials in terms of T-matrices for individual potentials are studied. Based on model calculations for S-wave for a sum of two separable non-local potentials of Yukawa type form factors and a sum of two delta function potentials, it is shown that the T-matrix for a sum of several potentials can be approximated satisfactorily over all the energy regions by the sum of T-matrices for individual potentials. Based on this, an approximate method for finding T-matrix for any local potential by approximating it by a sum of suitable number of square wells is presented. This provides an interesting way to calculate the T-matrix for any arbitary potential in terms of Bessel functions to a good degree of accuracy. The method is applied to the Saxon-Wood potentials and good agreement with exact results is found. (author)
ANYOLS, Least Square Fit by Stepwise Regression
International Nuclear Information System (INIS)
Atwoods, C.L.; Mathews, S.
1986-01-01
Description of program or function: ANYOLS is a stepwise program which fits data using ordinary or weighted least squares. Variables are selected for the model in a stepwise way based on a user- specified input criterion or a user-written subroutine. The order in which variables are entered can be influenced by user-defined forcing priorities. Instead of stepwise selection, ANYOLS can try all possible combinations of any desired subset of the variables. Automatic output for the final model in a stepwise search includes plots of the residuals, 'studentized' residuals, and leverages; if the model is not too large, the output also includes partial regression and partial leverage plots. A data set may be re-used so that several selection criteria can be tried. Flexibility is increased by allowing the substitution of user-written subroutines for several default subroutines
The Square Kilometre Array: An Engineering Perspective
Hall, Peter J
2005-01-01
This volume is an up-to-date and comprehensive overview of the engineering of the Square Kilometre Array (SKA), a revolutionary instrument which will be the world’s largest radio telescope. Expected to be completed by 2020, the SKA will be a pre-eminent tool in probing the Early Universe and in enhancing greatly the discovery potential of radio astronomy in many other fields. This book, containing 36 refereed papers written by leaders in SKA engineering, has been compiled by the International SKA Project Office and is the only contemporary compendium available. It features papers dealing with pivotal technologies such as antennas, RF systems and data transport. As well, overviews of important SKA demonstrator instruments and key system design issues are included. Practising professionals, and students interested in next-generation telescopes, will find this book an invaluable reference.
Multiples least-squares reverse time migration
Zhang, Dongliang
2013-01-01
To enhance the image quality, we propose multiples least-squares reverse time migration (MLSRTM) that transforms each hydrophone into a virtual point source with a time history equal to that of the recorded data. Since each recorded trace is treated as a virtual source, knowledge of the source wavelet is not required. Numerical tests on synthetic data for the Sigsbee2B model and field data from Gulf of Mexico show that MLSRTM can improve the image quality by removing artifacts, balancing amplitudes, and suppressing crosstalk compared to standard migration of the free-surface multiples. The potential liability of this method is that multiples require several roundtrips between the reflector and the free surface, so that high frequencies in the multiples are attenuated compared to the primary reflections. This can lead to lower resolution in the migration image compared to that computed from primaries.
An Empirical State Error Covariance Matrix Orbit Determination Example
Frisbee, Joseph H., Jr.
2015-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Controlling errors in unidosis carts
Directory of Open Access Journals (Sweden)
Inmaculada Díaz Fernández
2010-01-01
Full Text Available Objective: To identify errors in the unidosis system carts. Method: For two months, the Pharmacy Service controlled medication either returned or missing from the unidosis carts both in the pharmacy and in the wards. Results: Uncorrected unidosis carts show a 0.9% of medication errors (264 versus 0.6% (154 which appeared in unidosis carts previously revised. In carts not revised, the error is 70.83% and mainly caused when setting up unidosis carts. The rest are due to a lack of stock or unavailability (21.6%, errors in the transcription of medical orders (6.81% or that the boxes had not been emptied previously (0.76%. The errors found in the units correspond to errors in the transcription of the treatment (3.46%, non-receipt of the unidosis copy (23.14%, the patient did not take the medication (14.36%or was discharged without medication (12.77%, was not provided by nurses (14.09%, was withdrawn from the stocks of the unit (14.62%, and errors of the pharmacy service (17.56% . Conclusions: It is concluded the need to redress unidosis carts and a computerized prescription system to avoid errors in transcription.Discussion: A high percentage of medication errors is caused by human error. If unidosis carts are overlooked before sent to hospitalization units, the error diminishes to 0.3%.
Integrated parallel reception, excitation, and shimming (iPRES).
Han, Hui; Song, Allen W; Truong, Trong-Kha
2013-07-01
To develop a new concept for a hardware platform that enables integrated parallel reception, excitation, and shimming. This concept uses a single coil array rather than separate arrays for parallel excitation/reception and B0 shimming. It relies on a novel design that allows a radiofrequency current (for excitation/reception) and a direct current (for B0 shimming) to coexist independently in the same coil. Proof-of-concept B0 shimming experiments were performed with a two-coil array in a phantom, whereas B0 shimming simulations were performed with a 48-coil array in the human brain. Our experiments show that individually optimized direct currents applied in each coil can reduce the B0 root-mean-square error by 62-81% and minimize distortions in echo-planar images. The simulations show that dynamic shimming with the 48-coil integrated parallel reception, excitation, and shimming array can reduce the B0 root-mean-square error in the prefrontal and temporal regions by 66-79% as compared with static second-order spherical harmonic shimming and by 12-23% as compared with dynamic shimming with a 48-coil conventional shim array. Our results demonstrate the feasibility of the integrated parallel reception, excitation, and shimming concept to perform parallel excitation/reception and B0 shimming with a unified coil system as well as its promise for in vivo applications. Copyright © 2013 Wiley Periodicals, Inc.
Prioritising interventions against medication errors
DEFF Research Database (Denmark)
Lisby, Marianne; Pape-Larsen, Louise; Sørensen, Ann Lykkegaard
errors are therefore needed. Development of definition: A definition of medication errors including an index of error types for each stage in the medication process was developed from existing terminology and through a modified Delphi-process in 2008. The Delphi panel consisted of 25 interdisciplinary......Abstract Authors: Lisby M, Larsen LP, Soerensen AL, Nielsen LP, Mainz J Title: Prioritising interventions against medication errors – the importance of a definition Objective: To develop and test a restricted definition of medication errors across health care settings in Denmark Methods: Medication...... errors constitute a major quality and safety problem in modern healthcare. However, far from all are clinically important. The prevalence of medication errors ranges from 2-75% indicating a global problem in defining and measuring these [1]. New cut-of levels focusing the clinical impact of medication...
Social aspects of clinical errors.
Richman, Joel; Mason, Tom; Mason-Whitehead, Elizabeth; McIntosh, Annette; Mercer, Dave
2009-08-01
Clinical errors, whether committed by doctors, nurses or other professions allied to healthcare, remain a sensitive issue requiring open debate and policy formulation in order to reduce them. The literature suggests that the issues underpinning errors made by healthcare professionals involve concerns about patient safety, professional disclosure, apology, litigation, compensation, processes of recording and policy development to enhance quality service. Anecdotally, we are aware of narratives of minor errors, which may well have been covered up and remain officially undisclosed whilst the major errors resulting in damage and death to patients alarm both professionals and public with resultant litigation and compensation. This paper attempts to unravel some of these issues by highlighting the historical nature of clinical errors and drawing parallels to contemporary times by outlining the 'compensation culture'. We then provide an overview of what constitutes a clinical error and review the healthcare professional strategies for managing such errors.
Multiplier less high-speed squaring circuit for binary numbers
Sethi, Kabiraj; Panda, Rutuparna
2015-03-01
The squaring operation is important in many applications in signal processing, cryptography etc. In general, squaring circuits reported in the literature use fast multipliers. A novel idea of a squaring circuit without using multipliers is proposed in this paper. Ancient Indian method used for squaring decimal numbers is extended here for binary numbers. The key to our success is that no multiplier is used. Instead, one squaring circuit is used. The hardware architecture of the proposed squaring circuit is presented. The design is coded in VHDL and synthesised and simulated in Xilinx ISE Design Suite 10.1 (Xilinx Inc., San Jose, CA, USA). It is implemented in Xilinx Vertex 4vls15sf363-12 device (Xilinx Inc.). The results in terms of time delay and area is compared with both modified Booth's algorithm and squaring circuit using Vedic multipliers. Our proposed squaring circuit seems to have better performance in terms of both speed and area.
Evaluating Outlier Identification Tests: Mahalanobis "D" Squared and Comrey "Dk."
Rasmussen, Jeffrey Lee
1988-01-01
A Monte Carlo simulation was used to compare the Mahalanobis "D" Squared and the Comrey "Dk" methods of detecting outliers in data sets. Under the conditions investigated, the "D" Squared technique was preferable as an outlier removal statistic. (SLD)
Proportionate Minimum Error Entropy Algorithm for Sparse System Identification
Directory of Open Access Journals (Sweden)
Zongze Wu
2015-08-01
Full Text Available Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS algorithm, as a popular tool, achieves excellent performance for sparse system identification. In previous studies, most of the cost functions used in proportionate-type sparse adaptive algorithms are based on the mean square error (MSE criterion, which is optimal only when the measurement noise is Gaussian. However, this condition does not hold in most real-world environments. In this work, we use the minimum error entropy (MEE criterion, an alternative to the conventional MSE criterion, to develop the proportionate minimum error entropy (PMEE algorithm for sparse system identification, which may achieve much better performance than the MSE based methods especially in heavy-tailed non-Gaussian situations. Moreover, we analyze the convergence of the proposed algorithm and derive a sufficient condition that ensures the mean square convergence. Simulation results confirm the excellent performance of the new algorithm.
Errors in clinical laboratories or errors in laboratory medicine?
Plebani, Mario
2006-01-01
Laboratory testing is a highly complex process and, although laboratory services are relatively safe, they are not as safe as they could or should be. Clinical laboratories have long focused their attention on quality control methods and quality assessment programs dealing with analytical aspects of testing. However, a growing body of evidence accumulated in recent decades demonstrates that quality in clinical laboratories cannot be assured by merely focusing on purely analytical aspects. The more recent surveys on errors in laboratory medicine conclude that in the delivery of laboratory testing, mistakes occur more frequently before (pre-analytical) and after (post-analytical) the test has been performed. Most errors are due to pre-analytical factors (46-68.2% of total errors), while a high error rate (18.5-47% of total errors) has also been found in the post-analytical phase. Errors due to analytical problems have been significantly reduced over time, but there is evidence that, particularly for immunoassays, interference may have a serious impact on patients. A description of the most frequent and risky pre-, intra- and post-analytical errors and advice on practical steps for measuring and reducing the risk of errors is therefore given in the present paper. Many mistakes in the Total Testing Process are called "laboratory errors", although these may be due to poor communication, action taken by others involved in the testing process (e.g., physicians, nurses and phlebotomists), or poorly designed processes, all of which are beyond the laboratory's control. Likewise, there is evidence that laboratory information is only partially utilized. A recent document from the International Organization for Standardization (ISO) recommends a new, broader definition of the term "laboratory error" and a classification of errors according to different criteria. In a modern approach to total quality, centered on patients' needs and satisfaction, the risk of errors and mistakes
Errors in abdominal computed tomography
International Nuclear Information System (INIS)
Stephens, S.; Marting, I.; Dixon, A.K.
1989-01-01
Sixty-nine patients are presented in whom a substantial error was made on the initial abdominal computed tomography report. Certain features of these errors have been analysed. In 30 (43.5%) a lesion was simply not recognised (error of observation); in 39 (56.5%) the wrong conclusions were drawn about the nature of normal or abnormal structures (error of interpretation). The 39 errors of interpretation were more complex; in 7 patients an abnormal structure was noted but interpreted as normal, whereas in four a normal structure was thought to represent a lesion. Other interpretive errors included those where the wrong cause for a lesion had been ascribed (24 patients), and those where the abnormality was substantially under-reported (4 patients). Various features of these errors are presented and discussed. Errors were made just as often in relation to small and large lesions. Consultants made as many errors as senior registrar radiologists. It is like that dual reporting is the best method of avoiding such errors and, indeed, this is widely practised in our unit. (Author). 9 refs.; 5 figs.; 1 tab
Testing the gravitational inverse-square law
International Nuclear Information System (INIS)
Adelberger, Eric; Heckel, B.; Hoyle, C.D.
2005-01-01
If the universe contains more than three spatial dimensions, as many physicists believe, our current laws of gravity should break down at small distances. When Isaac Newton realized that the acceleration of the Moon as it orbited around the Earth could be related to the acceleration of an apple as it fell to the ground, it was the first time that two seemingly unrelated physical phenomena had been 'unified'. The quest to unify all the forces of nature is one that still keeps physicists busy today. Newton showed that the gravitational attraction between two point bodies is proportional to the product of their masses and inversely proportional to the square of the distance between them. Newton's theory, which assumes that the gravitational force acts instantaneously, remained essentially unchallenged for roughly two centuries until Einstein proposed the general theory of relativity in 1915. Einstein's radical new theory made gravity consistent with the two basic ideas of relativity: the world is 4D - the three directions of space combined with time - and no physical effect can travel faster than light. The theory of general relativity states that gravity is not a force in the usual sense but a consequence of the curvature of this space-time produced by mass or energy. However, in the limit of low velocities and weak gravitational fields, Einstein's theory still predicts that the gravitational force between two point objects obeys an inverse-square law. One of the outstanding challenges in physics is to finish what Newton started and achieve the ultimate 'grand unification' - to unify gravity with the other three fundamental forces (the electromagnetic force, and the strong and weak nuclear forces) into a single quantum theory. In string theory - one of the leading candidates for an ultimate theory - the fundamental entities of nature are 1D strings and higher-dimensional objects called 'branes', rather than the point-like particles we are familiar with. String
Delayed ripple counter simplifies square-root computation
Cliff, R.
1965-01-01
Ripple subtract technique simplifies the logic circuitry required in a binary computing device to derive the square root of a number. Successively higher numbers are subtracted from a register containing the number out of which the square root is to be extracted. The last number subtracted will be the closest integer to the square root of the number.
Directory of Open Access Journals (Sweden)
Mohammad Ali Ahmadi
2016-06-01
Full Text Available Applying chemical flooding in petroleum reservoirs turns into interesting subject of the recent researches. Developing strategies of the aforementioned method are more robust and precise when they consider both economical point of views (net present value (NPV and technical point of views (recovery factor (RF. In the present study huge attempts are made to propose predictive model for specifying efficiency of chemical flooding in oil reservoirs. To gain this goal, the new type of support vector machine method which evolved by Suykens and Vandewalle was employed. Also, high precise chemical flooding data banks reported in previous works were employed to test and validate the proposed vector machine model. According to the mean square error (MSE, correlation coefficient and average absolute relative deviation, the suggested LSSVM model has acceptable reliability; integrity and robustness. Thus, the proposed intelligent based model can be considered as an alternative model to monitor the efficiency of chemical flooding in oil reservoir when the required experimental data are not available or accessible.
Laboratory errors and patient safety.
Miligy, Dawlat A
2015-01-01
Laboratory data are extensively used in medical practice; consequently, laboratory errors have a tremendous impact on patient safety. Therefore, programs designed to identify and reduce laboratory errors, as well as, setting specific strategies are required to minimize these errors and improve patient safety. The purpose of this paper is to identify part of the commonly encountered laboratory errors throughout our practice in laboratory work, their hazards on patient health care and some measures and recommendations to minimize or to eliminate these errors. Recording the encountered laboratory errors during May 2008 and their statistical evaluation (using simple percent distribution) have been done in the department of laboratory of one of the private hospitals in Egypt. Errors have been classified according to the laboratory phases and according to their implication on patient health. Data obtained out of 1,600 testing procedure revealed that the total number of encountered errors is 14 tests (0.87 percent of total testing procedures). Most of the encountered errors lay in the pre- and post-analytic phases of testing cycle (representing 35.7 and 50 percent, respectively, of total errors). While the number of test errors encountered in the analytic phase represented only 14.3 percent of total errors. About 85.7 percent of total errors were of non-significant implication on patients health being detected before test reports have been submitted to the patients. On the other hand, the number of test errors that have been already submitted to patients and reach the physician represented 14.3 percent of total errors. Only 7.1 percent of the errors could have an impact on patient diagnosis. The findings of this study were concomitant with those published from the USA and other countries. This proves that laboratory problems are universal and need general standardization and bench marking measures. Original being the first data published from Arabic countries that
Dopamine reward prediction error coding.
Schultz, Wolfram
2016-03-01
Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.
International Nuclear Information System (INIS)
Castillo, Edward; Guerrero, Thomas; Castillo, Richard; White, Benjamin; Rojo, Javier
2012-01-01
Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. (paper)
Statistical errors in Monte Carlo estimates of systematic errors
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k2. The specific terms unisim and multisim were coined by Peter Meyers and Steve Brice, respectively, for the MiniBooNE experiment. However, the concepts have been developed over time and have been in general use for some time.
Statistical errors in Monte Carlo estimates of systematic errors
Energy Technology Data Exchange (ETDEWEB)
Roe, Byron P. [Department of Physics, University of Michigan, Ann Arbor, MI 48109 (United States)]. E-mail: byronroe@umich.edu
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k{sup 2}.
Statistical errors in Monte Carlo estimates of systematic errors
International Nuclear Information System (INIS)
Roe, Byron P.
2007-01-01
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, the systematic parameters are varied one at a time by one standard deviation, each parameter corresponding to a MC run. In the multisim method (see ), each MC run has all of the parameters varied; the amount of variation is chosen from the expected distribution of each systematic parameter, usually assumed to be a normal distribution. The variance of the overall systematic error determination is derived for each of the two methods and comparisons are made between them. If one focuses not on the error in the prediction of an individual systematic error, but on the overall error due to all systematic errors in the error matrix element in data bin m, the number of events needed is strongly reduced because of the averaging effect over all of the errors. For simple models presented here the multisim model was far better if the statistical error in the MC samples was larger than an individual systematic error, while for the reverse case, the unisim model was better. Exact formulas and formulas for the simple toy models are presented so that realistic calculations can be made. The calculations in the present note are valid if the errors are in a linear region. If that region extends sufficiently far, one can have the unisims or multisims correspond to k standard deviations instead of one. This reduces the number of events required by a factor of k 2
Skeletonized Least Squares Wave Equation Migration
Zhan, Ge
2010-10-17
The theory for skeletonized least squares wave equation migration (LSM) is presented. The key idea is, for an assumed velocity model, the source‐side Green\\'s function and the geophone‐side Green\\'s function are computed by a numerical solution of the wave equation. Only the early‐arrivals of these Green\\'s functions are saved and skeletonized to form the migration Green\\'s function (MGF) by convolution. Then the migration image is obtained by a dot product between the recorded shot gathers and the MGF for every trial image point. The key to an efficient implementation of iterative LSM is that at each conjugate gradient iteration, the MGF is reused and no new finitedifference (FD) simulations are needed to get the updated migration image. It is believed that this procedure combined with phase‐encoded multi‐source technology will allow for the efficient computation of wave equation LSM images in less time than that of conventional reverse time migration (RTM).
Architecture design for soft errors
Mukherjee, Shubu
2008-01-01
This book provides a comprehensive description of the architetural techniques to tackle the soft error problem. It covers the new methodologies for quantitative analysis of soft errors as well as novel, cost-effective architectural techniques to mitigate them. To provide readers with a better grasp of the broader problem deffinition and solution space, this book also delves into the physics of soft errors and reviews current circuit and software mitigation techniques.
Dopamine reward prediction error coding
Schultz, Wolfram
2016-01-01
Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards?an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less...
Identifying Error in AUV Communication
National Research Council Canada - National Science Library
Coleman, Joseph; Merrill, Kaylani; O'Rourke, Michael; Rajala, Andrew G; Edwards, Dean B
2006-01-01
Mine Countermeasures (MCM) involving Autonomous Underwater Vehicles (AUVs) are especially susceptible to error, given the constraints on underwater acoustic communication and the inconstancy of the underwater communication channel...
Human Errors in Decision Making
Mohamad, Shahriari; Aliandrina, Dessy; Feng, Yan
2005-01-01
The aim of this paper was to identify human errors in decision making process. The study was focused on a research question such as: what could be the human error as a potential of decision failure in evaluation of the alternatives in the process of decision making. Two case studies were selected from the literature and analyzed to find the human errors contribute to decision fail. Then the analysis of human errors was linked with mental models in evaluation of alternative step. The results o...
Finding beam focus errors automatically
International Nuclear Information System (INIS)
Lee, M.J.; Clearwater, S.H.; Kleban, S.D.
1987-01-01
An automated method for finding beam focus errors using an optimization program called COMFORT-PLUS. The steps involved in finding the correction factors using COMFORT-PLUS has been used to find the beam focus errors for two damping rings at the SLAC Linear Collider. The program is to be used as an off-line program to analyze actual measured data for any SLC system. A limitation on the application of this procedure is found to be that it depends on the magnitude of the machine errors. Another is that the program is not totally automated since the user must decide a priori where to look for errors
Heuristic errors in clinical reasoning.
Rylander, Melanie; Guerrasio, Jeannette
2016-08-01
Errors in clinical reasoning contribute to patient morbidity and mortality. The purpose of this study was to determine the types of heuristic errors made by third-year medical students and first-year residents. This study surveyed approximately 150 clinical educators inquiring about the types of heuristic errors they observed in third-year medical students and first-year residents. Anchoring and premature closure were the two most common errors observed amongst third-year medical students and first-year residents. There was no difference in the types of errors observed in the two groups. Errors in clinical reasoning contribute to patient morbidity and mortality Clinical educators perceived that both third-year medical students and first-year residents committed similar heuristic errors, implying that additional medical knowledge and clinical experience do not affect the types of heuristic errors made. Further work is needed to help identify methods that can be used to reduce heuristic errors early in a clinician's education. © 2015 John Wiley & Sons Ltd.
Phase transition in a modified square Josephson-junction array
Han, J
1999-01-01
We study the phase transition in a modified square proximity-coupled Josephson-junction array with small superconducting islands at the center of each plaquette. We find that the modified square array undergoes a Kosterlitz-Thouless-Berezinskii-like phase transition, but at a lower temperature than the simple square array with the same single-junction critical current. The IV characteristics, as well as the phase transition, resemble qualitatively those of a disordered simple square array. The effects of the presence of the center islands in the modified square array are discussed.
A Hybrid Unequal Error Protection / Unequal Error Resilience ...
African Journals Online (AJOL)
The quality layers are then assigned an Unequal Error Resilience to synchronization loss by unequally allocating the number of headers available for synchronization to them. Following that Unequal Error Protection against channel noise is provided to the layers by the use of Rate Compatible Punctured Convolutional ...
Measurement Error in Income and Schooling and the Bias of Linear Estimators
DEFF Research Database (Denmark)
Bingley, Paul; Martinello, Alessandro
2017-01-01
and Retirement in Europe data with Danish administrative registers. Contrary to most validation studies, we find that measurement error in income is classical once we account for imperfect validation data. We find nonclassical measurement error in schooling, causing a 38% amplification bias in IV estimators......We propose a general framework for determining the extent of measurement error bias in ordinary least squares and instrumental variable (IV) estimators of linear models while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing...
Error studies for SNS Linac. Part 1: Transverse errors
International Nuclear Information System (INIS)
Crandall, K.R.
1998-01-01
The SNS linac consist of a radio-frequency quadrupole (RFQ), a drift-tube linac (DTL), a coupled-cavity drift-tube linac (CCDTL) and a coupled-cavity linac (CCL). The RFQ and DTL are operated at 402.5 MHz; the CCDTL and CCL are operated at 805 MHz. Between the RFQ and DTL is a medium-energy beam-transport system (MEBT). This error study is concerned with the DTL, CCDTL and CCL, and each will be analyzed separately. In fact, the CCL is divided into two sections, and each of these will be analyzed separately. The types of errors considered here are those that affect the transverse characteristics of the beam. The errors that cause the beam center to be displaced from the linac axis are quad displacements and quad tilts. The errors that cause mismatches are quad gradient errors and quad rotations (roll)
Espin, Sherry; Levinson, Wendy; Regehr, Glenn; Baker, G Ross; Lingard, Lorelei
2006-01-01
Calls abound for a culture change in health care to improve patient safety. However, effective change cannot proceed without a clear understanding of perceptions and beliefs about error. In this study, we describe and compare operative team members' and patients' perceptions of error, reporting of error, and disclosure of error. Thirty-nine interviews of team members (9 surgeons, 9 nurses, 10 anesthesiologists) and patients (11) were conducted at 2 teaching hospitals using 4 scenarios as prompts. Transcribed responses to open questions were analyzed by 2 researchers for recurrent themes using the grounded-theory method. Yes/no answers were compared across groups using chi-square analyses. Team members and patients agreed on what constitutes an error. Deviation from standards and negative outcome were emphasized as definitive features. Patients and nurse professionals differed significantly in their perception of whether errors should be reported. Nurses were willing to report only events within their disciplinary scope of practice. Although most patients strongly advocated full disclosure of errors (what happened and how), team members preferred to disclose only what happened. When patients did support partial disclosure, their rationales varied from that of team members. Both operative teams and patients define error in terms of breaking the rules and the concept of "no harm no foul." These concepts pose challenges for treating errors as system failures. A strong culture of individualism pervades nurses' perception of error reporting, suggesting that interventions are needed to foster collective responsibility and a constructive approach to error identification.
Stochastic Least-Squares Petrov--Galerkin Method for Parameterized Linear Systems
Energy Technology Data Exchange (ETDEWEB)
Lee, Kookjin [Univ. of Maryland, College Park, MD (United States). Dept. of Computer Science; Carlberg, Kevin [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Elman, Howard C. [Univ. of Maryland, College Park, MD (United States). Dept. of Computer Science and Inst. for Advanced Computer Studies
2018-03-29
Here, we consider the numerical solution of parameterized linear systems where the system matrix, the solution, and the right-hand side are parameterized by a set of uncertain input parameters. We explore spectral methods in which the solutions are approximated in a chosen finite-dimensional subspace. It has been shown that the stochastic Galerkin projection technique fails to minimize any measure of the solution error. As a remedy for this, we propose a novel stochatic least-squares Petrov--Galerkin (LSPG) method. The proposed method is optimal in the sense that it produces the solution that minimizes a weighted $\\ell^2$-norm of the residual over all solutions in a given finite-dimensional subspace. Moreover, the method can be adapted to minimize the solution error in different weighted $\\ell^2$-norms by simply applying a weighting function within the least-squares formulation. In addition, a goal-oriented seminorm induced by an output quantity of interest can be minimized by defining a weighting function as a linear functional of the solution. We establish optimality and error bounds for the proposed method, and extensive numerical experiments show that the weighted LSPG method outperforms other spectral methods in minimizing corresponding target weighted norms.
Error begat error: design error analysis and prevention in social infrastructure projects.
Love, Peter E D; Lopez, Robert; Edwards, David J; Goh, Yang M
2012-09-01
Design errors contribute significantly to cost and schedule growth in social infrastructure projects and to engineering failures, which can result in accidents and loss of life. Despite considerable research that has addressed their error causation in construction projects they still remain prevalent. This paper identifies the underlying conditions that contribute to design errors in social infrastructure projects (e.g. hospitals, education, law and order type buildings). A systemic model of error causation is propagated and subsequently used to develop a learning framework for design error prevention. The research suggests that a multitude of strategies should be adopted in congruence to prevent design errors from occurring and so ensure that safety and project performance are ameliorated. Copyright © 2011. Published by Elsevier Ltd.
Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?
Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander
2016-01-01
Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.
An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction
Directory of Open Access Journals (Sweden)
Yong Zhu
2015-01-01
Full Text Available After summarizing the advantages and disadvantages of current integral methods, a novel vibration signal integral method based on feature information extraction was proposed. This method took full advantage of the self-adaptive filter characteristic and waveform correction feature of ensemble empirical mode decomposition in dealing with nonlinear and nonstationary signals. This research merged the superiorities of kurtosis, mean square error, energy, and singular value decomposition on signal feature extraction. The values of the four indexes aforementioned were combined into a feature vector. Then, the connotative characteristic components in vibration signal were accurately extracted by Euclidean distance search, and the desired integral signals were precisely reconstructed. With this method, the interference problem of invalid signal such as trend item and noise which plague traditional methods is commendably solved. The great cumulative error from the traditional time-domain integral is effectively overcome. Moreover, the large low-frequency error from the traditional frequency-domain integral is successfully avoided. Comparing with the traditional integral methods, this method is outstanding at removing noise and retaining useful feature information and shows higher accuracy and superiority.
Propagation of angular errors in two-axis rotation systems
Torrington, Geoffrey K.
2003-10-01
Two-Axis Rotation Systems, or "goniometers," are used in diverse applications including telescope pointing, automotive headlamp testing, and display testing. There are three basic configurations in which a goniometer can be built depending on the orientation and order of the stages. Each configuration has a governing set of equations which convert motion between the system "native" coordinates to other base systems, such as direction cosines, optical field angles, or spherical-polar coordinates. In their simplest form, these equations neglect errors present in real systems. In this paper, a statistical treatment of error source propagation is developed which uses only tolerance data, such as can be obtained from the system mechanical drawings prior to fabrication. It is shown that certain error sources are fully correctable, partially correctable, or uncorrectable, depending upon the goniometer configuration and zeroing technique. The system error budget can be described by a root-sum-of-squares technique with weighting factors describing the sensitivity of each error source. This paper tabulates weighting factors at 67% (k=1) and 95% (k=2) confidence for various levels of maximum travel for each goniometer configuration. As a practical example, this paper works through an error budget used for the procurement of a system at Sandia National Laboratories.
Directory of Open Access Journals (Sweden)
Mohd Idrus Mohd Nazrul Effendy
2018-01-01
Full Text Available Near infrared spectroscopy (NIRS is a reliable technique that widely used in medical fields. Partial least square was developed to predict blood hemoglobin concentration using NIRS. The aims of this paper are (i to develop predictive model for near infrared spectroscopic analysis in blood hemoglobin prediction, (ii to establish relationship between blood hemoglobin and near infrared spectrum using a predictive model, (iii to evaluate the predictive accuracy of a predictive model based on root mean squared error (RMSE and coefficient of determination rp2. Partial least square with first order Savitzky Golay (SG derivative preprocessing (PLS-SGd1 showed the higher performance of predictions with RMSE = 0.7965 and rp2= 0.9206 in K-fold cross validation. Optimum number of latent variable (LV and frame length (f were 32 and 27 nm, respectively. These findings suggest that the relationship between blood hemoglobin and near infrared spectrum is strong, and the partial least square with first order SG derivative is able to predict the blood hemoglobin using near infrared spectral data.
Spectral/hp least-squares finite element formulation for the Navier-Stokes equations
International Nuclear Information System (INIS)
Pontaza, J.P.; Reddy, J.N.
2003-01-01
We consider the application of least-squares finite element models combined with spectral/hp methods for the numerical solution of viscous flow problems. The paper presents the formulation, validation, and application of a spectral/hp algorithm to the numerical solution of the Navier-Stokes equations governing two- and three-dimensional stationary incompressible and low-speed compressible flows. The Navier-Stokes equations are expressed as an equivalent set of first-order equations by introducing vorticity or velocity gradients as additional independent variables and the least-squares method is used to develop the finite element model. High-order element expansions are used to construct the discrete model. The discrete model thus obtained is linearized by Newton's method, resulting in a linear system of equations with a symmetric positive definite coefficient matrix that is solved in a fully coupled manner by a preconditioned conjugate gradient method. Spectral convergence of the L 2 least-squares functional and L 2 error norms is verified using smooth solutions to the two-dimensional stationary Poisson and incompressible Navier-Stokes equations. Numerical results for flow over a backward-facing step, steady flow past a circular cylinder, three-dimensional lid-driven cavity flow, and compressible buoyant flow inside a square enclosure are presented to demonstrate the predictive capability and robustness of the proposed formulation
Dual Processing and Diagnostic Errors
Norman, Geoff
2009-01-01
In this paper, I review evidence from two theories in psychology relevant to diagnosis and diagnostic errors. "Dual Process" theories of thinking, frequently mentioned with respect to diagnostic error, propose that categorization decisions can be made with either a fast, unconscious, contextual process called System 1 or a slow, analytical,…
Barriers to medical error reporting
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Jalal Poorolajal
2015-01-01
Full Text Available Background: This study was conducted to explore the prevalence of medical error underreporting and associated barriers. Methods: This cross-sectional study was performed from September to December 2012. Five hospitals, affiliated with Hamadan University of Medical Sciences, in Hamedan,Iran were investigated. A self-administered questionnaire was used for data collection. Participants consisted of physicians, nurses, midwives, residents, interns, and staffs of radiology and laboratory departments. Results: Overall, 50.26% of subjects had committed but not reported medical errors. The main reasons mentioned for underreporting were lack of effective medical error reporting system (60.0%, lack of proper reporting form (51.8%, lack of peer supporting a person who has committed an error (56.0%, and lack of personal attention to the importance of medical errors (62.9%. The rate of committing medical errors was higher in men (71.4%, age of 50-40 years (67.6%, less-experienced personnel (58.7%, educational level of MSc (87.5%, and staff of radiology department (88.9%. Conclusions: This study outlined the main barriers to reporting medical errors and associated factors that may be helpful for healthcare organizations in improving medical error reporting as an essential component for patient safety enhancement.
Doppler-shift estimation of flat underwater channel using data-aided least-square approach
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Weiqiang Pan
2015-03-01
Full Text Available In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.
Least-squares Minimization Approaches to Interpret Total Magnetic Anomalies Due to Spheres
Abdelrahman, E. M.; El-Araby, T. M.; Soliman, K. S.; Essa, K. S.; Abo-Ezz, E. R.
2007-05-01
We have developed three different least-squares approaches to determine successively: the depth, magnetic angle, and amplitude coefficient of a buried sphere from a total magnetic anomaly. By defining the anomaly value at the origin and the nearest zero-anomaly distance from the origin on the profile, the problem of depth determination is transformed into the problem of finding a solution of a nonlinear equation of the form f(z)=0. Knowing the depth and applying the least-squares method, the magnetic angle and amplitude coefficient are determined using two simple linear equations. In this way, the depth, magnetic angle, and amplitude coefficient are determined individually from all observed total magnetic data. The method is applied to synthetic examples with and without random errors and tested on a field example from Senegal, West Africa. In all cases, the depth solutions are in good agreement with the actual ones.
Doppler-shift estimation of flat underwater channel using data-aided least-square approach
Pan, Weiqiang; Liu, Ping; Chen, Fangjiong; Ji, Fei; Feng, Jing
2015-06-01
In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.
An improved partial least-squares regression method for Raman spectroscopy
Momenpour Tehran Monfared, Ali; Anis, Hanan
2017-10-01
It is known that the performance of partial least-squares (PLS) regression analysis can be improved using the backward variable selection method (BVSPLS). In this paper, we further improve the BVSPLS based on a novel selection mechanism. The proposed method is based on sorting the weighted regression coefficients, and then the importance of each variable of the sorted list is evaluated using root mean square errors of prediction (RMSEP) criterion in each iteration step. Our Improved BVSPLS (IBVSPLS) method has been applied to leukemia and heparin data sets and led to an improvement in limit of detection of Raman biosensing ranged from 10% to 43% compared to PLS. Our IBVSPLS was also compared to the jack-knifing (simpler) and Genetic Algorithm (more complex) methods. Our method was consistently better than the jack-knifing method and showed either a similar or a better performance compared to the genetic algorithm.
Strong source heat transfer simulations based on a GalerKin/Gradient - least - squares method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do.
1989-05-01
Heat conduction problems with temperature-dependent strong sources are modeled by an equation with a laplacian term, a linear term and a given source distribution term. When the linear-temperature-dependent source term is much larger than the laplacian term, we have a singular perturbation problem. In this case, boundary layers are formed to satisfy the Dirichlet boundary conditions. Although this is an elliptic equation, the standard Galerkin method solution is contaminated by spurious oscillations in the neighborhood of the boundary layers. Herein we employ a Galerkin/Gradient-least-squares method which eliminates all pathological phenomena of the Galerkin method. The method is constructed by adding to the Galerkin method a mesh-dependent term obtained by the least-squares form of the gradient of the Euler-Lagrange equation. Error estimates, numerical simulations in one-and multi-dimensions are given that attest the good stability and accuracy properties of the method [pt
Mcruer, D. T.; Clement, W. F.; Allen, R. W.
1981-01-01
Human errors tend to be treated in terms of clinical and anecdotal descriptions, from which remedial measures are difficult to derive. Correction of the sources of human error requires an attempt to reconstruct underlying and contributing causes of error from the circumstantial causes cited in official investigative reports. A comprehensive analytical theory of the cause-effect relationships governing propagation of human error is indispensable to a reconstruction of the underlying and contributing causes. A validated analytical theory of the input-output behavior of human operators involving manual control, communication, supervisory, and monitoring tasks which are relevant to aviation, maritime, automotive, and process control operations is highlighted. This theory of behavior, both appropriate and inappropriate, provides an insightful basis for investigating, classifying, and quantifying the needed cause-effect relationships governing propagation of human error.
Correcting AUC for Measurement Error.
Rosner, Bernard; Tworoger, Shelley; Qiu, Weiliang
2015-12-01
Diagnostic biomarkers are used frequently in epidemiologic and clinical work. The ability of a diagnostic biomarker to discriminate between subjects who develop disease (cases) and subjects who do not (controls) is often measured by the area under the receiver operating characteristic curve (AUC). The diagnostic biomarkers are usually measured with error. Ignoring measurement error can cause biased estimation of AUC, which results in misleading interpretation of the efficacy of a diagnostic biomarker. Several methods have been proposed to correct AUC for measurement error, most of which required the normality assumption for the distributions of diagnostic biomarkers. In this article, we propose a new method to correct AUC for measurement error and derive approximate confidence limits for the corrected AUC. The proposed method does not require the normality assumption. Both real data analyses and simulation studies show good performance of the proposed measurement error correction method.
Cognitive aspect of diagnostic errors.
Phua, Dong Haur; Tan, Nigel C K
2013-01-01
Diagnostic errors can result in tangible harm to patients. Despite our advances in medicine, the mental processes required to make a diagnosis exhibits shortcomings, causing diagnostic errors. Cognitive factors are found to be an important cause of diagnostic errors. With new understanding from psychology and social sciences, clinical medicine is now beginning to appreciate that our clinical reasoning can take the form of analytical reasoning or heuristics. Different factors like cognitive biases and affective influences can also impel unwary clinicians to make diagnostic errors. Various strategies have been proposed to reduce the effect of cognitive biases and affective influences when clinicians make diagnoses; however evidence for the efficacy of these methods is still sparse. This paper aims to introduce the reader to the cognitive aspect of diagnostic errors, in the hope that clinicians can use this knowledge to improve diagnostic accuracy and patient outcomes.
Least-squares methods for identifying biochemical regulatory networks from noisy measurements
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Heslop-Harrison Pat
2007-01-01
Full Text Available Abstract Background We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS. The Total Least Squares (TLS technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks. Results The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and mdm2 messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL-6 and (IL-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL-6 and (IL-12b by ATF3. Conclusion The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable
Directory of Open Access Journals (Sweden)
Lin Hu
2011-01-01
Full Text Available A class of drift-implicit one-step schemes are proposed for the neutral stochastic delay differential equations (NSDDEs driven by Poisson processes. A general framework for mean-square convergence of the methods is provided. It is shown that under certain conditions global error estimates for a method can be inferred from estimates on its local error. The applicability of the mean-square convergence theory is illustrated by the stochastic θ-methods and the balanced implicit methods. It is derived from Theorem 3.1 that the order of the mean-square convergence of both of them for NSDDEs with jumps is 1/2. Numerical experiments illustrate the theoretical results. It is worth noting that the results of mean-square convergence of the stochastic θ-methods and the balanced implicit methods are also new.
Error analysis of nuclear power plant operator cognitive behavior
International Nuclear Information System (INIS)
He Xuhong; Zhao Bingquan; Chen Yulong
2001-01-01
Nuclear power plant is a complex human-machine system integrated with many advanced machines, electron devices and automatic controls. It demands operators to have high cognitive ability and correct analysis skill. The author divides operator's cognitive process into five stages to analysis. With this cognitive model, operator's cognitive error is analysed to get the root causes and stages that error happens. The results of the analysis serve as a basis in design of control rooms and training and evaluation of operators
Liao, Xiang; Wang, Qing; Fu, Ji-hong; Tang, Jun
2015-09-01
This work was undertaken to establish a quantitative analysis model which can rapid determinate the content of linalool, linalyl acetate of Xinjiang lavender essential oil. Totally 165 lavender essential oil samples were measured by using near infrared absorption spectrum (NIR), after analyzing the near infrared spectral absorption peaks of all samples, lavender essential oil have abundant chemical information and the interference of random noise may be relatively low on the spectral intervals of 7100~4500 cm(-1). Thus, the PLS models was constructed by using this interval for further analysis. 8 abnormal samples were eliminated. Through the clustering method, 157 lavender essential oil samples were divided into 105 calibration set samples and 52 validation set samples. Gas chromatography mass spectrometry (GC-MS) was used as a tool to determine the content of linalool and linalyl acetate in lavender essential oil. Then the matrix was established with the GC-MS raw data of two compounds in combination with the original NIR data. In order to optimize the model, different pretreatment methods were used to preprocess the raw NIR spectral to contrast the spectral filtering effect, after analysizing the quantitative model results of linalool and linalyl acetate, the root mean square error prediction (RMSEP) of orthogonal signal transformation (OSC) was 0.226, 0.558, spectrally, it was the optimum pretreatment method. In addition, forward interval partial least squares (FiPLS) method was used to exclude the wavelength points which has nothing to do with determination composition or present nonlinear correlation, finally 8 spectral intervals totally 160 wavelength points were obtained as the dataset. Combining the data sets which have optimized by OSC-FiPLS with partial least squares (PLS) to establish a rapid quantitative analysis model for determining the content of linalool and linalyl acetate in Xinjiang lavender essential oil, numbers of hidden variables of two
New approach to breast cancer CAD using partial least squares and kernel-partial least squares
Land, Walker H., Jr.; Heine, John; Embrechts, Mark; Smith, Tom; Choma, Robert; Wong, Lut
2005-04-01
Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of breast cancer, its positive predictive value (PPV) is low, resulting in biopsies that are only 15-34% likely to reveal malignancy. This paper explores the use of two novel approaches called Partial Least Squares (PLS) and Kernel-PLS (K-PLS) to the diagnosis of breast cancer. The approach is based on optimization for the partial least squares (PLS) algorithm for linear regression and the K-PLS algorithm for non-linear regression. Preliminary results show that both the PLS and K-PLS paradigms achieved comparable results with three separate support vector learning machines (SVLMs), where these SVLMs were known to have been trained to a global minimum. That is, the average performance of the three separate SVLMs were Az = 0.9167927, with an average partial Az (Az90) = 0.5684283. These results compare favorably with the K-PLS paradigm, which obtained an Az = 0.907 and partial Az = 0.6123. The PLS paradigm provided comparable results. Secondly, both the K-PLS and PLS paradigms out performed the ANN in that the Az index improved by about 14% (Az ~ 0.907 compared to the ANN Az of ~ 0.8). The "Press R squared" value for the PLS and K-PLS machine learning algorithms were 0.89 and 0.9, respectively, which is in good agreement with the other MOP values.
DEFF Research Database (Denmark)
Garcia, Emanuel; Klaas, Ilka Christine; Amigo Rubio, Jose Manuel
2014-01-01
Lameness is prevalent in dairy herds. It causes decreased animal welfare and leads to higher production costs. This study explored data from an automatic milking system (AMS) to model on-farm gait scoring from a commercial farm. A total of 88 cows were gait scored once per week, for 2 5-wk periods......). The reference gait scoring error was estimated in the first week of the study and was, on average, 15%. Two partial least squares discriminant analysis models were fitted to parity 1 and parity 2 groups, respectively, to assign the lameness class according to the predicted probability of being lame (score 3...
And still, a new beginning: the Galerkin least-squares gradient method
International Nuclear Information System (INIS)
Franca, L.P.; Carmo, E.G.D. do
1988-08-01
A finite element method is proposed to solve a scalar singular diffusion problem. The method is constructed by adding to the standard Galerkin a mesh-dependent term obtained by taking the gradient of the Euler-lagrange equation and multiplying it by its least-squares. For the one-dimensional homogeneous problem the method is designed to develop nodal exact solution. An error estimate shows that the method converges optimaly for any value of the singular parameter. Numerical results demonstrate the good stability and accuracy properties of the method. (author) [pt
SECOND ORDER LEAST SQUARE ESTIMATION ON ARCH(1 MODEL WITH BOX-COX TRANSFORMED DEPENDENT VARIABLE
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Herni Utami
2014-03-01
Full Text Available Box-Cox transformation is often used to reduce heterogeneity and to achieve a symmetric distribution of response variable. In this paper, we estimate the parameters of Box-Cox transformed ARCH(1 model using second-order leastsquare method and then we study the consistency and asymptotic normality for second-order least square (SLS estimators. The SLS estimation was introduced byWang (2003, 2004 to estimate the parameters of nonlinear regression models with independent and identically distributed errors
Fault Estimation for Fuzzy Delay Systems: A Minimum Norm Least Squares Solution Approach.
Huang, Sheng-Juan; Yang, Guang-Hong
2017-09-01
This paper mainly focuses on the problem of fault estimation for a class of Takagi-Sugeno fuzzy systems with state delays. A minimum norm least squares solution (MNLSS) approach is first introduced to establish a fault estimation compensator, which is able to optimize the fault estimator. Compared with most of the existing fault estimation methods, the MNLSS-based fault estimation method can effectively decrease the effect of state errors on the accuracy of fault estimation. Finally, three examples are given to illustrate the effectiveness and merits of the proposed method.
Obtention of the parameters of the Voigt function using the least square fit method
International Nuclear Information System (INIS)
Flores Ll, H.; Cabral P, A.; Jimenez D, H.
1990-01-01
The fundamental parameters of the Voigt function are determined: lorentzian wide (Γ L ) and gaussian wide (Γ G ) with an error for almost all the cases inferior to 1% in the intervals 0.01 ≤ Γ L / Γ G ≤1 and 0.3 ≤ Γ G / Γ L ≤1. This is achieved using the least square fit method with an algebraic function, being obtained a simple method to obtain the fundamental parameters of the Voigt function used in many spectroscopies. (Author)
Multigrid for the Galerkin least squares method in linear elasticity: The pure displacement problem
Energy Technology Data Exchange (ETDEWEB)
Yoo, Jaechil [Univ. of Wisconsin, Madison, WI (United States)
1996-12-31
Franca and Stenberg developed several Galerkin least squares methods for the solution of the problem of linear elasticity. That work concerned itself only with the error estimates of the method. It did not address the related problem of finding effective methods for the solution of the associated linear systems. In this work, we prove the convergence of a multigrid (W-cycle) method. This multigrid is robust in that the convergence is uniform as the parameter, v, goes to 1/2 Computational experiments are included.
REGULAR METHOD FOR SYNTHESIS OF BASIC BENT-SQUARES OF RANDOM ORDER
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A. V. Sokolov
2016-01-01
Full Text Available The paper is devoted to the class construction of the most non-linear Boolean bent-functions of any length N = 2k (k = 2, 4, 6…, on the basis of their spectral representation – Agievich bent squares. These perfect algebraic constructions are used as a basis to build many new cryptographic primitives, such as generators of pseudo-random key sequences, crypto graphic S-boxes, etc. Bent-functions also find their application in the construction of C-codes in the systems with code division multiple access (CDMA to provide the lowest possible value of Peak-to-Average Power Ratio (PAPR k = 1, as well as for the construction of error-correcting codes and systems of orthogonal biphasic signals. All the numerous applications of bent-functions relate to the theory of their synthesis. However, regular methods for complete class synthesis of bent-functions of any length N = 2k are currently unknown. The paper proposes a regular synthesis method for the basic Agievich bent squares of any order n, based on a regular operator of dyadic shift. Classification for a complete set of spectral vectors of lengths (l = 8, 16, … based on a criterion of the maximum absolute value and set of absolute values of spectral components has been carried out in the paper. It has been shown that any spectral vector can be a basis for building bent squares. Results of the synthesis for the Agievich bent squares of order n = 8 have been generalized and it has been revealed that there are only 3 basic bent squares for this order, while the other 5 can be obtained with help the operation of step-cyclic shift. All the basic bent squares of order n = 16 have been synthesized that allows to construct the bent-functions of length N = 256. The obtained basic bent squares can be used either for direct synthesis of bent-functions and their practical application or for further research in order to synthesize new structures of bent squares of orders n = 16, 32, 64, …
Analyzing the installation angle error of a SAW torque sensor
International Nuclear Information System (INIS)
Fan, Yanping; Ji, Xiaojun; Cai, Ping
2014-01-01
When a torque is applied to a shaft, normal strain oriented at ±45° direction to the shaft axis is at its maximum, which requires two one-port SAW resonators to be bonded to the shaft at ±45° to the shaft axis. In order to make the SAW torque sensitivity high enough, the installation angle error of two SAW resonators must be confined within ±5° according to our design requirement. However, there are few studies devoted to the installation angle analysis of a SAW torque sensor presently and the angle error was usually obtained by a manual method. Hence, we propose an approximation method to analyze the angle error. First, according to the sensitive mechanism of the SAW device to torque, the SAW torque sensitivity is deduced based on the linear piezoelectric constitutive equation and the perturbation theory. Then, when a torque is applied to the tested shaft, the stress condition of two SAW resonators mounted with an angle deviating from ±45° to the shaft axis, is analyzed. The angle error is obtained by means of the torque sensitivities of two orthogonal SAW resonators. Finally, the torque measurement system is constructed and the loading and unloading experiments are performed twice. The torque sensitivities of two SAW resonators are obtained by applying average and least square method to the experimental results. Based on the derived angle error estimation function, the angle error is estimated about 3.447°, which is close to the actual angle error 2.915°. The difference between the estimated angle and the actual angle is discussed. The validity of the proposed angle error analysis method is testified to by the experimental results. (technical design note)
Caimmi, R.
2011-08-01
Concerning bivariate least squares linear regression, the classical approach pursued for functional models in earlier attempts ( York, 1966, 1969) is reviewed using a new formalism in terms of deviation (matrix) traces which, for unweighted data, reduce to usual quantities leaving aside an unessential (but dimensional) multiplicative factor. Within the framework of classical error models, the dependent variable relates to the independent variable according to the usual additive model. The classes of linear models considered are regression lines in the general case of correlated errors in X and in Y for weighted data, and in the opposite limiting situations of (i) uncorrelated errors in X and in Y, and (ii) completely correlated errors in X and in Y. The special case of (C) generalized orthogonal regression is considered in detail together with well known subcases, namely: (Y) errors in X negligible (ideally null) with respect to errors in Y; (X) errors in Y negligible (ideally null) with respect to errors in X; (O) genuine orthogonal regression; (R) reduced major-axis regression. In the limit of unweighted data, the results determined for functional models are compared with their counterparts related to extreme structural models i.e. the instrumental scatter is negligible (ideally null) with respect to the intrinsic scatter ( Isobe et al., 1990; Feigelson and Babu, 1992). While regression line slope and intercept estimators for functional and structural models necessarily coincide, the contrary holds for related variance estimators even if the residuals obey a Gaussian distribution, with the exception of Y models. An example of astronomical application is considered, concerning the [O/H]-[Fe/H] empirical relations deduced from five samples related to different stars and/or different methods of oxygen abundance determination. For selected samples and assigned methods, different regression models yield consistent results within the errors (∓ σ) for both
Neutron diffraction determination of mean-square atomic displacements
International Nuclear Information System (INIS)
Tibballs, J.E.; Feteris, S.M.; Barnea, Z.
1981-01-01
Integrated intensities for Bragg reflection of neutrons from single crystals of the III-V compounds, InAs and GaSb, have been measured at room temperature. The data were collected at two wavelengths, 0.947 A and 1.241 A, in order to establish the adequacy of a correction for moderate to severe anisotropic extinction. Data were also obtained for InAs at four temperatures from 408 K to 933 K. Corrections for thermal diffuse scattering were applied. The results were analysed in the one-particle potential approximation with terms to fourth-order in the atomic displacements u = (u 1 , u 2 , u 3 ). At 296 K, the mean-square components were determined for In, 0.0116(2)A 2 and As, 0.0102 (1)A 2 ; for Ga, 0.0120(3)A 2 and Sb, 0.0107(3)A 2 . The third-order coefficients for InAs are comparable with those for Si and Ge, those for GaSb with those for zinc chalcogenides. Non-harmonic behaviour in InAs is observed below 400 K
Turbulence and secondary motions in square duct flow
Pirozzoli, Sergio; Modesti, Davide; Orlandi, Paolo; Grasso, Francesco
2017-11-01
We study turbulent flows in pressure-driven ducts with square cross-section through DNS up to Reτ 1050 . Numerical simulations are carried out over extremely long integration times to get adequate convergence of the flow statistics, and specifically high-fidelity representation of the secondary motions which arise. The intensity of the latter is found to be in the order of 1-2% of the bulk velocity, and unaffected by Reynolds number variations. The smallness of the mean convection terms in the streamwise vorticity equation points to a simple characterization of the secondary flows, which in the asymptotic high-Re regime are found to be approximated with good accuracy by eigenfunctions of the Laplace operator. Despite their effect of redistributing the wall shear stress along the duct perimeter, we find that secondary motions do not have large influence on the mean velocity field, which can be characterized with good accuracy as that resulting from the concurrent effect of four independent flat walls, each controlling a quarter of the flow domain. As a consequence, we find that parametrizations based on the hydraulic diameter concept, and modifications thereof, are successful in predicting the duct friction coefficient. This research was carried out using resources from PRACE EU Grants.
Baseline configuration for GNSS attitude determination with an analytical least-squares solution
International Nuclear Information System (INIS)
Chang, Guobin; Wang, Qianxin; Xu, Tianhe
2016-01-01
The GNSS attitude determination using carrier phase measurements with 4 antennas is studied on condition that the integer ambiguities have been resolved. The solution to the nonlinear least-squares is often obtained iteratively, however an analytical solution can exist for specific baseline configurations. The main aim of this work is to design this class of configurations. Both single and double difference measurements are treated which refer to the dedicated and non-dedicated receivers respectively. More realistic error models are employed in which the correlations between different measurements are given full consideration. The desired configurations are worked out. The configurations are rotation and scale equivariant and can be applied to both the dedicated and non-dedicated receivers. For these configurations, the analytical and optimal solution for the attitude is also given together with its error variance–covariance matrix. (paper)
A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality
Cheung, KW; So, HC; Ma, W.-K.; Chan, YT
2006-12-01
The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.
Methods for reduction of scattered x-ray in measuring MTF with the square chart
International Nuclear Information System (INIS)
Hatagawa, Masakatsu; Yoshida, Rie
1982-01-01
A square wave chart has been used to measure the MTF of a screen-film system. The problem is that the scattered X-ray from the chart may give rise to measurement errors. In this paper, the authors proposed two methods to reduce the scattered X-ray: the first method is the use of a Pb mask and second is to provide for an air gap between the chart and the screen-film system. In these methods, the scattered X-ray from the chart was reduced. MTFs were measured by both of the new methods and the conventional method, and MTF values of the new methods were in good agreement while that of the conventional method was not. It was concluded that these new methods are able to reduce errors in the measurement of MTF. (author)
Directory of Open Access Journals (Sweden)
Victor Aredo
2017-01-01
Full Text Available The aim of this study was to build a model to predict the beef marbling using HSI and Partial Least Squares Regression (PLSR. Totally 58 samples of longissmus dorsi muscle were scanned by a HSI system (400 - 1000 nm in reflectance mode, using 44 samples to build t he PLSR model and 14 samples to model validation. The Japanese Beef Marbling Standard (BMS was used as reference by 15 middle - trained judges for the samples evaluation. The scores were assigned as continuous values and varied from 1.2 to 5.3 BMS. The PLSR model showed a high correlation coefficient in the prediction (r = 0.95, a low Standard Error of Calibration (SEC of 0.2 BMS score, and a low Standard Error of Prediction (SEP of 0.3 BMS score.
Directory of Open Access Journals (Sweden)
Eldad Kepten
Full Text Available Single particle tracking is an essential tool in the study of complex systems and biophysics and it is commonly analyzed by the time-averaged mean square displacement (MSD of the diffusive trajectories. However, past work has shown that MSDs are susceptible to significant errors and biases, preventing the comparison and assessment of experimental studies. Here, we attempt to extract practical guidelines for the estimation of anomalous time averaged MSDs through the simulation of multiple scenarios with fractional Brownian motion as a representative of a large class of fractional ergodic processes. We extract the precision and accuracy of the fitted MSD for various anomalous exponents and measurement errors with respect to measurement length and maximum time lags. Based on the calculated precision maps, we present guidelines to improve accuracy in single particle studies. Importantly, we find that in some experimental conditions, the time averaged MSD should not be used as an estimator.
Errors, error detection, error correction and hippocampal-region damage: data and theories.
MacKay, Donald G; Johnson, Laura W
2013-11-01
This review and perspective article outlines 15 observational constraints on theories of errors, error detection, and error correction, and their relation to hippocampal-region (HR) damage. The core observations come from 10 studies with H.M., an amnesic with cerebellar and HR damage but virtually no neocortical damage. Three studies examined the detection of errors planted in visual scenes (e.g., a bird flying in a fish bowl in a school classroom) and sentences (e.g., I helped themselves to the birthday cake). In all three experiments, H.M. detected reliably fewer errors than carefully matched memory-normal controls. Other studies examined the detection and correction of self-produced errors, with controls for comprehension of the instructions, impaired visual acuity, temporal factors, motoric slowing, forgetting, excessive memory load, lack of motivation, and deficits in visual scanning or attention. In these studies, H.M. corrected reliably fewer errors than memory-normal and cerebellar controls, and his uncorrected errors in speech, object naming, and reading aloud exhibited two consistent features: omission and anomaly. For example, in sentence production tasks, H.M. omitted one or more words in uncorrected encoding errors that rendered his sentences anomalous (incoherent, incomplete, or ungrammatical) reliably more often than controls. Besides explaining these core findings, the theoretical principles discussed here explain H.M.'s retrograde amnesia for once familiar episodic and semantic information; his anterograde amnesia for novel information; his deficits in visual cognition, sentence comprehension, sentence production, sentence reading, and object naming; and effects of aging on his ability to read isolated low frequency words aloud. These theoretical principles also explain a wide range of other data on error detection and correction and generate new predictions for future test. Copyright © 2013 Elsevier Ltd. All rights reserved.
Space and protest: A tale of two Egyptian squares
Mohamed, A.A.; Van Nes, A.; Salheen, M.A.
2015-01-01
Protests and revolts take place in public space. How they can be controlled or how protests develop depend on the physical layout of the built environment. This study reveals the relationship between urban space and protest for two Egyptian squares: Tahrir Square and Rabaa Al-Adawiya in Cairo. For analysis, the research uses space syntax method. The results of this analysis are then compared with descriptions of the protest behaviour. As it turns out, the spatial properties of Tahrir square s...
Human errors in NPP operations
International Nuclear Information System (INIS)
Sheng Jufang
1993-01-01
Based on the operational experiences of nuclear power plants (NPPs), the importance of studying human performance problems is described. Statistical analysis on the significance or frequency of various root-causes and error-modes from a large number of human-error-related events demonstrate that the defects in operation/maintenance procedures, working place factors, communication and training practices are primary root-causes, while omission, transposition, quantitative mistake are the most frequent among the error-modes. Recommendations about domestic research on human performance problem in NPPs are suggested
Linear network error correction coding
Guang, Xuan
2014-01-01
There are two main approaches in the theory of network error correction coding. In this SpringerBrief, the authors summarize some of the most important contributions following the classic approach, which represents messages by sequences?similar to algebraic coding,?and also briefly discuss the main results following the?other approach,?that uses the theory of rank metric codes for network error correction of representing messages by subspaces. This book starts by establishing the basic linear network error correction (LNEC) model and then characterizes two equivalent descriptions. Distances an