Monte Carlo simulation of errors in the anisotropy of magnetic susceptibility - A second-rank symmetric tensor. [for grains in sedimentary and volcanic rocks

NASA Technical Reports Server (NTRS)

Lienert, Barry R.

1991-01-01

Monte Carlo perturbations of synthetic tensors to evaluate the Hext/Jelinek elliptical confidence regions for anisotropy of magnetic susceptibility (AMS) eigenvectors are used. When the perturbations are 33 percent of the minimum anisotropy, both the shapes and probability densities of the resulting eigenvector distributions agree with the elliptical distributions predicted by the Hext/Jelinek equations. When the perturbation size is increased to 100 percent of the minimum eigenvalue difference, the major axis of the 95 percent confidence ellipse underestimates the observed eigenvector dispersion by about 10 deg. The observed distributions of the principal susceptibilities (eigenvalues) are close to being normal, with standard errors that agree well with the calculated Hext/Jelinek errors. The Hext/Jelinek ellipses are also able to describe the AMS dispersions due to instrumental noise and provide reasonable limits for the AMS dispersions observed in two Hawaiian basaltic dikes. It is concluded that the Hext/Jelinek method provides a satisfactory description of the errors in AMS data and should be a standard part of any AMS data analysis.

Improving Conceptual Models Using AEM Data and Probability Distributions

NASA Astrophysics Data System (ADS)

Davis, A. C.; Munday, T. J.; Christensen, N. B.

2012-12-01

With emphasis being placed on uncertainty in groundwater modelling and prediction, coupled with questions concerning the value of geophysical methods in hydrogeology, it is important to ask meaningful questions of hydrogeophysical data and inversion results. For example, to characterise aquifers using electromagnetic (EM) data, we ask questions such as "Given that the electrical conductivity of aquifer 'A' is less than x, where is that aquifer elsewhere in the survey area?" The answer may be given by examining inversion models, selecting locations and layers that satisfy the condition 'conductivity <= x', and labelling them as aquifer 'A'. One difficulty with this approach is that the inversion model result often be considered to be the only model for the data. In reality it is just one image of the subsurface that, given the method and the regularisation imposed in the inversion, agrees with measured data within a given error bound. We have no idea whether the final model realised by the inversion satisfies the global minimum error, or whether it is simply in a local minimum. There is a distribution of inversion models that satisfy the error tolerance condition: the final model is not the only one, nor is it necessarily the correct one. AEM inversions are often linearised in the calculation of the parameter sensitivity: we rely on the second derivatives in the Taylor expansion, thus the minimum model has all layer parameters distributed about their mean parameter value with well-defined variance. We investigate the validity of the minimum model, and its uncertainty, by examining the full posterior covariance matrix. We ask questions of the minimum model, and answer them in a probabilistically. The simplest question we can pose is "What is the probability that all layer resistivity values are <= a cut-off value?" We can calculate through use of the erf or the erfc functions. The covariance values of the inversion become marginalised in the integration: only the main diagonal is used. Complications arise when we ask more specific questions, such as "What is the probability that the resistivity of layer 2 <= x, given that layer 1 <= y?" The probability then becomes conditional, calculation includes covariance terms, the integration is taken over many dimensions, and the cross-correlation of parameters becomes important. To illustrate, we examine the inversion results of a Tempest AEM survey over the Uley Basin aquifers in the Eyre Peninsula, South Australia. Key aquifers include the unconfined Bridgewater Formation that overlies the Uley and Wanilla Formations, which contain Tertiary clays and Tertiary sandstone. These Formations overlie weathered basement which define the lower bound of the Uley Basin aquifer systems. By correlating the conductivity of the sub-surface Formation types, we pose questions such as: "What is the probability-depth of the Bridgewater Formation in the Uley South Basin?", "What is the thickness of the Uley Formation?" and "What is the most probable depth to basement?" We use these questions to generate improved conceptual hydrogeological models of the Uley Basin in order to develop better estimates of aquifer extent and the available groundwater resource.

Multiclass Bayes error estimation by a feature space sampling technique

NASA Technical Reports Server (NTRS)

Mobasseri, B. G.; Mcgillem, C. D.

1979-01-01

A general Gaussian M-class N-feature classification problem is defined. An algorithm is developed that requires the class statistics as its only input and computes the minimum probability of error through use of a combined analytical and numerical integration over a sequence simplifying transformations of the feature space. The results are compared with those obtained by conventional techniques applied to a 2-class 4-feature discrimination problem with results previously reported and 4-class 4-feature multispectral scanner Landsat data classified by training and testing of the available data.

Simulating future uncertainty to guide the selection of survey designs for long-term monitoring

USGS Publications Warehouse

Garman, Steven L.; Schweiger, E. William; Manier, Daniel J.; Gitzen, Robert A.; Millspaugh, Joshua J.; Cooper, Andrew B.; Licht, Daniel S.

2012-01-01

A goal of environmental monitoring is to provide sound information on the status and trends of natural resources (Messer et al. 1991, Theobald et al. 2007, Fancy et al. 2009). When monitoring observations are acquired by measuring a subset of the population of interest, probability sampling as part of a well-constructed survey design provides the most reliable and legally defensible approach to achieve this goal (Cochran 1977, Olsen et al. 1999, Schreuder et al. 2004; see Chapters 2, 5, 6, 7). Previous works have described the fundamentals of sample surveys (e.g. Hansen et al. 1953, Kish 1965). Interest in survey designs and monitoring over the past 15 years has led to extensive evaluations and new developments of sample selection methods (Stevens and Olsen 2004), of strategies for allocating sample units in space and time (Urquhart et al. 1993, Overton and Stehman 1996, Urquhart and Kincaid 1999), and of estimation (Lesser and Overton 1994, Overton and Stehman 1995) and variance properties (Larsen et al. 1995, Stevens and Olsen 2003) of survey designs. Carefully planned, “scientific” (Chapter 5) survey designs have become a standard in contemporary monitoring of natural resources. Based on our experience with the long-term monitoring program of the US National Park Service (NPS; Fancy et al. 2009; Chapters 16, 22), operational survey designs tend to be selected using the following procedures. For a monitoring indicator (i.e. variable or response), a minimum detectable trend requirement is specified, based on the minimum level of change that would result in meaningful change (e.g. degradation). A probability of detecting this trend (statistical power) and an acceptable level of uncertainty (Type I error; see Chapter 2) within a specified time frame (e.g. 10 years) are specified to ensure timely detection. Explicit statements of the minimum detectable trend, the time frame for detecting the minimum trend, power, and acceptable probability of Type I error (α) collectively form the quantitative sampling objective.

The effect of covariate mean differences on the standard error and confidence interval for the comparison of treatment means.

PubMed

Liu, Xiaofeng Steven

2011-05-01

The use of covariates is commonly believed to reduce the unexplained error variance and the standard error for the comparison of treatment means, but the reduction in the standard error is neither guaranteed nor uniform over different sample sizes. The covariate mean differences between the treatment conditions can inflate the standard error of the covariate-adjusted mean difference and can actually produce a larger standard error for the adjusted mean difference than that for the unadjusted mean difference. When the covariate observations are conceived of as randomly varying from one study to another, the covariate mean differences can be related to a Hotelling's T(2) . Using this Hotelling's T(2) statistic, one can always find a minimum sample size to achieve a high probability of reducing the standard error and confidence interval width for the adjusted mean difference. ©2010 The British Psychological Society.

Numerical and analytical bounds on threshold error rates for hypergraph-product codes

NASA Astrophysics Data System (ADS)

Kovalev, Alexey A.; Prabhakar, Sanjay; Dumer, Ilya; Pryadko, Leonid P.

2018-06-01

We study analytically and numerically decoding properties of finite-rate hypergraph-product quantum low density parity-check codes obtained from random (3,4)-regular Gallager codes, with a simple model of independent X and Z errors. Several nontrivial lower and upper bounds for the decodable region are constructed analytically by analyzing the properties of the homological difference, equal minus the logarithm of the maximum-likelihood decoding probability for a given syndrome. Numerical results include an upper bound for the decodable region from specific heat calculations in associated Ising models and a minimum-weight decoding threshold of approximately 7 % .

Tomography of a displacement photon counter for discrimination of single-rail optical qubits

NASA Astrophysics Data System (ADS)

Izumi, Shuro; Neergaard-Nielsen, Jonas S.; Andersen, Ulrik L.

2018-04-01

We investigate the performance of a detection strategy composed of a displacement operation and a photon counter, which is known as a beneficial tool in optical coherent communications, to the quantum state discrimination of the two superpositions of vacuum and single photon states corresponding to the {\\hat{σ }}x eigenstates in the single-rail encoding of photonic qubits. We experimentally characterize the detection strategy in vacuum-single photon two-dimensional space using quantum detector tomography and evaluate the achievable discrimination error probability from the reconstructed measurement operators. We furthermore derive the minimum error rate obtainable with Gaussian transformations and homodyne detection. Our proof-of-principle experiment shows that the proposed scheme can achieve a discrimination error surpassing homodyne detection.

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

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

Optimization of an optically implemented on-board FDMA demultiplexer

NASA Technical Reports Server (NTRS)

Fargnoli, J.; Riddle, L.

1991-01-01

Performance of a 30 GHz frequency division multiple access (FDMA) uplink to a processing satellite is modelled for the case where the onboard demultiplexer is implemented optically. Included in the performance model are the effects of adjacent channel interference, intersymbol interference, and spurious signals associated with the optical implementation. Demultiplexer parameters are optimized to provide the minimum bit error probability at a given bandwidth efficiency when filtered QPSK modulation is employed.

Three-dimensional holoscopic image coding scheme using high-efficiency video coding with kernel-based minimum mean-square-error estimation

NASA Astrophysics Data System (ADS)

Liu, Deyang; An, Ping; Ma, Ran; Yang, Chao; Shen, Liquan; Li, Kai

2016-07-01

Three-dimensional (3-D) holoscopic imaging, also known as integral imaging, light field imaging, or plenoptic imaging, can provide natural and fatigue-free 3-D visualization. However, a large amount of data is required to represent the 3-D holoscopic content. Therefore, efficient coding schemes for this particular type of image are needed. A 3-D holoscopic image coding scheme with kernel-based minimum mean square error (MMSE) estimation is proposed. In the proposed scheme, the coding block is predicted by an MMSE estimator under statistical modeling. In order to obtain the signal statistical behavior, kernel density estimation (KDE) is utilized to estimate the probability density function of the statistical modeling. As bandwidth estimation (BE) is a key issue in the KDE problem, we also propose a BE method based on kernel trick. The experimental results demonstrate that the proposed scheme can achieve a better rate-distortion performance and a better visual rendering quality.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1977-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1978-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Discriminating two nonorthogonal states against a noise channel by feed-forward control

NASA Astrophysics Data System (ADS)

Guo, Li-Sha; Xu, Bao-Ming; Zou, Jian; Wang, Chao-Quan; Li, Hai; Li, Jun-Gang; Shao, Bin

2015-02-01

We propose a scheme by using the feed-forward control (FFC) to realize a better effect of discrimination of two nonorthogonal states after passing a noise channel based on the minimum-error (ME) discrimination. We show that the application of our scheme can highly improve the effect of discrimination compared with the ME discrimination without the FFC for any pair of nonorthogonal states and any degree of amplitude damping. Especially, the effect of our optimal discrimination can reach that of the two initial nonorthogonal pure states in the presence of the noise channel in a deterministic way for equal a priori probabilities or even be better than that in a probabilistic way for unequal a priori probabilities.

Cost of remembering a bit of information

NASA Astrophysics Data System (ADS)

Chiuchiù; , D.; López-Suárez, M.; Neri, I.; Diamantini, M. C.; Gammaitoni, L.

2018-05-01

In 1961, Landauer [R. Landauer, IBM J. Res. Develop. 5, 183 (1961), 10.1147/rd.53.0183] pointed out that resetting a binary memory requires a minimum energy of kBT ln(2 ) . However, once written, any memory is doomed to lose its content if no action is taken. To avoid memory losses, a refresh procedure is periodically performed. We present a theoretical model and an experiment on a microelectromechanical system to evaluate the minimum energy required to preserve one bit of information over time. Two main conclusions are drawn: (i) in principle, the energetic cost to preserve information for a fixed time duration with a given error probability can be arbitrarily reduced if the refresh procedure is performed often enough, and (ii) the Heisenberg uncertainty principle sets an upper bound on the memory lifetime.

Discriminating quantum-optical beam-splitter channels with number-diagonal signal states: Applications to quantum reading and target detection

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

Nair, Ranjith

2011-09-15

We consider the problem of distinguishing, with minimum probability of error, two optical beam-splitter channels with unequal complex-valued reflectivities using general quantum probe states entangled over M signal and M' idler mode pairs of which the signal modes are bounced off the beam splitter while the idler modes are retained losslessly. We obtain a lower bound on the output state fidelity valid for any pure input state. We define number-diagonal signal (NDS) states to be input states whose density operator in the signal modes is diagonal in the multimode number basis. For such input states, we derive series formulas formore » the optimal error probability, the output state fidelity, and the Chernoff-type upper bounds on the error probability. For the special cases of quantum reading of a classical digital memory and target detection (for which the reflectivities are real valued), we show that for a given input signal photon probability distribution, the fidelity is minimized by the NDS states with that distribution and that for a given average total signal energy N{sub s}, the fidelity is minimized by any multimode Fock state with N{sub s} total signal photons. For reading of an ideal memory, it is shown that Fock state inputs minimize the Chernoff bound. For target detection under high-loss conditions, a no-go result showing the lack of appreciable quantum advantage over coherent state transmitters is derived. A comparison of the error probability performance for quantum reading of number state and two-mode squeezed vacuum state (or EPR state) transmitters relative to coherent state transmitters is presented for various values of the reflectances. While the nonclassical states in general perform better than the coherent state, the quantitative performance gains differ depending on the values of the reflectances. The experimental outlook for realizing nonclassical gains from number state transmitters with current technology at moderate to high values of the reflectances is argued to be good.« less

Fast converging minimum probability of error neural network receivers for DS-CDMA communications.

PubMed

Matyjas, John D; Psaromiligkos, Ioannis N; Batalama, Stella N; Medley, Michael J

2004-03-01

We consider a multilayer perceptron neural network (NN) receiver architecture for the recovery of the information bits of a direct-sequence code-division-multiple-access (DS-CDMA) user. We develop a fast converging adaptive training algorithm that minimizes the bit-error rate (BER) at the output of the receiver. The adaptive algorithm has three key features: i) it incorporates the BER, i.e., the ultimate performance evaluation measure, directly into the learning process, ii) it utilizes constraints that are derived from the properties of the optimum single-user decision boundary for additive white Gaussian noise (AWGN) multiple-access channels, and iii) it embeds importance sampling (IS) principles directly into the receiver optimization process. Simulation studies illustrate the BER performance of the proposed scheme.

Designing an efficient LT-code with unequal error protection for image transmission

NASA Astrophysics Data System (ADS)

S. Marques, F.; Schwartz, C.; Pinho, M. S.; Finamore, W. A.

2015-10-01

The use of images from earth observation satellites is spread over different applications, such as a car navigation systems and a disaster monitoring. In general, those images are captured by on board imaging devices and must be transmitted to the Earth using a communication system. Even though a high resolution image can produce a better Quality of Service, it leads to transmitters with high bit rate which require a large bandwidth and expend a large amount of energy. Therefore, it is very important to design efficient communication systems. From communication theory, it is well known that a source encoder is crucial in an efficient system. In a remote sensing satellite image transmission, this efficiency is achieved by using an image compressor, to reduce the amount of data which must be transmitted. The Consultative Committee for Space Data Systems (CCSDS), a multinational forum for the development of communications and data system standards for space flight, establishes a recommended standard for a data compression algorithm for images from space systems. Unfortunately, in the satellite communication channel, the transmitted signal is corrupted by the presence of noise, interference signals, etc. Therefore, the receiver of a digital communication system may fail to recover the transmitted bit. Actually, a channel code can be used to reduce the effect of this failure. In 2002, the Luby Transform code (LT-code) was introduced and it was shown that it was very efficient when the binary erasure channel model was used. Since the effect of the bit recovery failure depends on the position of the bit in the compressed image stream, in the last decade many e orts have been made to develop LT-code with unequal error protection. In 2012, Arslan et al. showed improvements when LT-codes with unequal error protection were used in images compressed by SPIHT algorithm. The techniques presented by Arslan et al. can be adapted to work with the algorithm for image compression recommended by CCSDS. In fact, to design a LT-code with an unequal error protection, the bit stream produced by the algorithm recommended by CCSDS must be partitioned in M disjoint sets of bits. Using the weighted approach, the LT-code produces M different failure probabilities for each set of bits, p1, ..., pM leading to a total probability of failure, p which is an average of p1, ..., pM. In general, the parameters of the LT-code with unequal error protection is chosen using a heuristic procedure. In this work, we analyze the problem of choosing the LT-code parameters to optimize two figure of merits: (a) the probability of achieving a minimum acceptable PSNR, and (b) the mean of PSNR, given that the minimum acceptable PSNR has been achieved. Given the rate-distortion curve achieved by CCSDS recommended algorithm, this work establishes a closed form of the mean of PSNR (given that the minimum acceptable PSNR has been achieved) as a function of p1, ..., pM. The main contribution of this work is the study of a criteria to select the parameters p1, ..., pM to optimize the performance of image transmission.

Upper bounds on the error probabilities and asymptotic error exponents in quantum multiple state discrimination

NASA Astrophysics Data System (ADS)

Audenaert, Koenraad M. R.; Mosonyi, Milán

2014-10-01

We consider the multiple hypothesis testing problem for symmetric quantum state discrimination between r given states σ1, …, σr. By splitting up the overall test into multiple binary tests in various ways we obtain a number of upper bounds on the optimal error probability in terms of the binary error probabilities. These upper bounds allow us to deduce various bounds on the asymptotic error rate, for which it has been hypothesized that it is given by the multi-hypothesis quantum Chernoff bound (or Chernoff divergence) C(σ1, …, σr), as recently introduced by Nussbaum and Szkoła in analogy with Salikhov's classical multi-hypothesis Chernoff bound. This quantity is defined as the minimum of the pairwise binary Chernoff divergences min _{j

Applicability of AgMERRA Forcing Dataset to Fill Gaps in Historical in-situ Meteorological Data

NASA Astrophysics Data System (ADS)

Bannayan, M.; Lashkari, A.; Zare, H.; Asadi, S.; Salehnia, N.

2015-12-01

Integrated assessment studies of food production systems use crop models to simulate the effects of climate and socio-economic changes on food security. Climate forcing data is one of those key inputs of crop models. This study evaluated the performance of AgMERRA climate forcing dataset to fill gaps in historical in-situ meteorological data for different climatic regions of Iran. AgMERRA dataset intercompared with in- situ observational dataset for daily maximum and minimum temperature and precipitation during 1980-2010 periods via Root Mean Square error (RMSE), Mean Absolute Error (MAE) and Mean Bias Error (MBE) for 17 stations in four climatic regions included humid and moderate, cold, dry and arid, hot and humid. Moreover, probability distribution function and cumulative distribution function compared between model and observed data. The results of measures of agreement between AgMERRA data and observed data demonstrated that there are small errors in model data for all stations. Except for stations which are located in cold regions, model data in the other stations illustrated under-prediction for daily maximum temperature and precipitation. However, it was not significant. In addition, probability distribution function and cumulative distribution function showed the same trend for all stations between model and observed data. Therefore, the reliability of AgMERRA dataset is high to fill gaps in historical observations in different climatic regions of Iran as well as it could be applied as a basis for future climate scenarios.

Achieving minimum-error discrimination of an arbitrary set of laser-light pulses

NASA Astrophysics Data System (ADS)

da Silva, Marcus P.; Guha, Saikat; Dutton, Zachary

2013-05-01

Laser light is widely used for communication and sensing applications, so the optimal discrimination of coherent states—the quantum states of light emitted by an ideal laser—has immense practical importance. Due to fundamental limits imposed by quantum mechanics, such discrimination has a finite minimum probability of error. While concrete optical circuits for the optimal discrimination between two coherent states are well known, the generalization to larger sets of coherent states has been challenging. In this paper, we show how to achieve optimal discrimination of any set of coherent states using a resource-efficient quantum computer. Our construction leverages a recent result on discriminating multicopy quantum hypotheses [Blume-Kohout, Croke, and Zwolak, arXiv:1201.6625]. As illustrative examples, we analyze the performance of discriminating a ternary alphabet and show how the quantum circuit of a receiver designed to discriminate a binary alphabet can be reused in discriminating multimode hypotheses. Finally, we show that our result can be used to achieve the quantum limit on the rate of classical information transmission on a lossy optical channel, which is known to exceed the Shannon rate of all conventional optical receivers.

ON COMPUTING UPPER LIMITS TO SOURCE INTENSITIES

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

Kashyap, Vinay L.; Siemiginowska, Aneta; Van Dyk, David A.

2010-08-10

A common problem in astrophysics is determining how bright a source could be and still not be detected in an observation. Despite the simplicity with which the problem can be stated, the solution involves complicated statistical issues that require careful analysis. In contrast to the more familiar confidence bound, this concept has never been formally analyzed, leading to a great variety of often ad hoc solutions. Here we formulate and describe the problem in a self-consistent manner. Detection significance is usually defined by the acceptable proportion of false positives (background fluctuations that are claimed as detections, or Type I error),more » and we invoke the complementary concept of false negatives (real sources that go undetected, or Type II error), based on the statistical power of a test, to compute an upper limit to the detectable source intensity. To determine the minimum intensity that a source must have for it to be detected, we first define a detection threshold and then compute the probabilities of detecting sources of various intensities at the given threshold. The intensity that corresponds to the specified Type II error probability defines that minimum intensity and is identified as the upper limit. Thus, an upper limit is a characteristic of the detection procedure rather than the strength of any particular source. It should not be confused with confidence intervals or other estimates of source intensity. This is particularly important given the large number of catalogs that are being generated from increasingly sensitive surveys. We discuss, with examples, the differences between these upper limits and confidence bounds. Both measures are useful quantities that should be reported in order to extract the most science from catalogs, though they answer different statistical questions: an upper bound describes an inference range on the source intensity, while an upper limit calibrates the detection process. We provide a recipe for computing upper limits that applies to all detection algorithms.« less

Anti-D immunoglobulin preparations: the stability of anti-D concentrations and the error of the assay of anti-D.

PubMed

Hughes-Jones, N C; Hunt, V A; Maycock, W D; Wesley, E D; Vallet, L

1978-01-01

An analysis of the assay of 28 preparations of anti-D immunoglobulin using a radioisotope method carried out at 6-montly intervals for 2--4.5 years showed an average fall in anti-D concentration of 10.6% each year, with 99% confidence limits of 6.8--14.7%. The fall in anti-D concentration after storage at 37 degrees C for 1 month was less than 8%, the minimum change that could be detected. No significant change in physical characteristics of the immunoglobulin were detected. The error of a single estimate of anti-D by the radioisotope method (125I-labelled anti-IgG) used here was calculated to be such that the true value probably (p = 0.95) lay between 66 and 150% of the estimated value.

Empirically Estimable Classification Bounds Based on a Nonparametric Divergence Measure

PubMed Central

Berisha, Visar; Wisler, Alan; Hero, Alfred O.; Spanias, Andreas

2015-01-01

Information divergence functions play a critical role in statistics and information theory. In this paper we show that a non-parametric f-divergence measure can be used to provide improved bounds on the minimum binary classification probability of error for the case when the training and test data are drawn from the same distribution and for the case where there exists some mismatch between training and test distributions. We confirm the theoretical results by designing feature selection algorithms using the criteria from these bounds and by evaluating the algorithms on a series of pathological speech classification tasks. PMID:26807014

Maximum-likelihood block detection of noncoherent continuous phase modulation

NASA Technical Reports Server (NTRS)

Simon, Marvin K.; Divsalar, Dariush

1993-01-01

This paper examines maximum-likelihood block detection of uncoded full response CPM over an additive white Gaussian noise (AWGN) channel. Both the maximum-likelihood metrics and the bit error probability performances of the associated detection algorithms are considered. The special and popular case of minimum-shift-keying (MSK) corresponding to h = 0.5 and constant amplitude frequency pulse is treated separately. The many new receiver structures that result from this investigation can be compared to the traditional ones that have been used in the past both from the standpoint of simplicity of implementation and optimality of performance.

Minimum-error quantum distinguishability bounds from matrix monotone functions: A comment on 'Two-sided estimates of minimum-error distinguishability of mixed quantum states via generalized Holevo-Curlander bounds' [J. Math. Phys. 50, 032106 (2009)

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

Tyson, Jon

2009-06-15

Matrix monotonicity is used to obtain upper bounds on minimum-error distinguishability of arbitrary ensembles of mixed quantum states. This generalizes one direction of a two-sided bound recently obtained by the author [J. Tyson, J. Math. Phys. 50, 032106 (2009)]. It is shown that the previously obtained special case has unique properties.

Performance of concatenated Reed-Solomon/Viterbi channel coding

NASA Technical Reports Server (NTRS)

Divsalar, D.; Yuen, J. H.

1982-01-01

The concatenated Reed-Solomon (RS)/Viterbi coding system is reviewed. The performance of the system is analyzed and results are derived with a new simple approach. A functional model for the input RS symbol error probability is presented. Based on this new functional model, we compute the performance of a concatenated system in terms of RS word error probability, output RS symbol error probability, bit error probability due to decoding failure, and bit error probability due to decoding error. Finally we analyze the effects of the noisy carrier reference and the slow fading on the system performance.

Estimation of proportions in mixed pixels through their region characterization

NASA Technical Reports Server (NTRS)

Chittineni, C. B. (Principal Investigator)

1981-01-01

A region of mixed pixels can be characterized through the probability density function of proportions of classes in the pixels. Using information from the spectral vectors of a given set of pixels from the mixed pixel region, expressions are developed for obtaining the maximum likelihood estimates of the parameters of probability density functions of proportions. The proportions of classes in the mixed pixels can then be estimated. If the mixed pixels contain objects of two classes, the computation can be reduced by transforming the spectral vectors using a transformation matrix that simultaneously diagonalizes the covariance matrices of the two classes. If the proportions of the classes of a set of mixed pixels from the region are given, then expressions are developed for obtaining the estmates of the parameters of the probability density function of the proportions of mixed pixels. Development of these expressions is based on the criterion of the minimum sum of squares of errors. Experimental results from the processing of remotely sensed agricultural multispectral imagery data are presented.

The statistical significance of error probability as determined from decoding simulations for long codes

NASA Technical Reports Server (NTRS)

Massey, J. L.

1976-01-01

The very low error probability obtained with long error-correcting codes results in a very small number of observed errors in simulation studies of practical size and renders the usual confidence interval techniques inapplicable to the observed error probability. A natural extension of the notion of a 'confidence interval' is made and applied to such determinations of error probability by simulation. An example is included to show the surprisingly great significance of as few as two decoding errors in a very large number of decoding trials.

Image data compression having minimum perceptual error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1995-01-01

A method for performing image compression that eliminates redundant and invisible image components is described. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Method and Apparatus for Powered Descent Guidance

NASA Technical Reports Server (NTRS)

Acikmese, Behcet (Inventor); Blackmore, James C. L. (Inventor); Scharf, Daniel P. (Inventor)

2013-01-01

A method and apparatus for landing a spacecraft having thrusters with non-convex constraints is described. The method first computes a solution to a minimum error landing problem for a convexified constraints, then applies that solution to a minimum fuel landing problem for convexified constraints. The result is a solution that is a minimum error and minimum fuel solution that is also a feasible solution to the analogous system with non-convex thruster constraints.

Image Data Compression Having Minimum Perceptual Error

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1997-01-01

A method is presented for performing color or grayscale image compression that eliminates redundant and invisible image components. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The quantization matrix comprises visual masking by luminance and contrast technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

Selecting a restoration technique to minimize OCR error.

PubMed

Cannon, M; Fugate, M; Hush, D R; Scovel, C

2003-01-01

This paper introduces a learning problem related to the task of converting printed documents to ASCII text files. The goal of the learning procedure is to produce a function that maps documents to restoration techniques in such a way that on average the restored documents have minimum optical character recognition error. We derive a general form for the optimal function and use it to motivate the development of a nonparametric method based on nearest neighbors. We also develop a direct method of solution based on empirical error minimization for which we prove a finite sample bound on estimation error that is independent of distribution. We show that this empirical error minimization problem is an extension of the empirical optimization problem for traditional M-class classification with general loss function and prove computational hardness for this problem. We then derive a simple iterative algorithm called generalized multiclass ratchet (GMR) and prove that it produces an optimal function asymptotically (with probability 1). To obtain the GMR algorithm we introduce a new data map that extends Kesler's construction for the multiclass problem and then apply an algorithm called Ratchet to this mapped data, where Ratchet is a modification of the Pocket algorithm . Finally, we apply these methods to a collection of documents and report on the experimental results.

Automatic Recognition of Phonemes Using a Syntactic Processor for Error Correction.

DTIC Science & Technology

1980-12-01

OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS AFIT/GE/EE/8D-45 Robert B. ’Taylor 2Lt USAF Approved for public release...distribution unlimilted. AbP AFIT/GE/EE/ 80D-45 AUTOMATIC RECOGNITION OF PHONEMES USING A SYNTACTIC PROCESSOR FOR ERROR CORRECTION THESIS Presented to the...Testing ..................... 37 Bayes Decision Rule for Minimum Error ........... 37 Bayes Decision Rule for Minimum Risk ............ 39 Mini Max Test

About an adaptively weighted Kaplan-Meier estimate.

PubMed

Plante, Jean-François

2009-09-01

The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier estimate. The proposed estimate is smoother than the usual Kaplan-Meier estimate and converges uniformly in probability to the target distribution. Simulations show that the performances of the weighted Kaplan-Meier estimate on finite samples exceed that of the usual Kaplan-Meier estimate. A case study is also presented.

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

Dall'Arno, Michele; ICFO-Institut de Ciencies Fotoniques, E-08860 Castelldefels; Quit Group, Dipartimento di Fisica, via Bassi 6, I-27100 Pavia

We address the problem of quantum reading of optical memories, namely the retrieving of classical information stored in the optical properties of a media with minimum energy. We present optimal strategies for ambiguous and unambiguous quantum reading of unitary optical memories, namely when one's task is to minimize the probability of errors in the retrieved information and when perfect retrieving of information is achieved probabilistically, respectively. A comparison of the optimal strategy with coherent probes and homodyne detection shows that the former saves orders of magnitude of energy when achieving the same performances. Experimental proposals for quantum reading which aremore » feasible with present quantum optical technology are reported.« less

Robust parameter design for automatically controlled systems and nanostructure synthesis

NASA Astrophysics Data System (ADS)

Dasgupta, Tirthankar

2007-12-01

This research focuses on developing comprehensive frameworks for developing robust parameter design methodology for dynamic systems with automatic control and for synthesis of nanostructures. In many automatically controlled dynamic processes, the optimal feedback control law depends on the parameter design solution and vice versa and therefore an integrated approach is necessary. A parameter design methodology in the presence of feedback control is developed for processes of long duration under the assumption that experimental noise factors are uncorrelated over time. Systems that follow a pure-gain dynamic model are considered and the best proportional-integral and minimum mean squared error control strategies are developed by using robust parameter design. The proposed method is illustrated using a simulated example and a case study in a urea packing plant. This idea is also extended to cases with on-line noise factors. The possibility of integrating feedforward control with a minimum mean squared error feedback control scheme is explored. To meet the needs of large scale synthesis of nanostructures, it is critical to systematically find experimental conditions under which the desired nanostructures are synthesized reproducibly, at large quantity and with controlled morphology. The first part of the research in this area focuses on modeling and optimization of existing experimental data. Through a rigorous statistical analysis of experimental data, models linking the probabilities of obtaining specific morphologies to the process variables are developed. A new iterative algorithm for fitting a Multinomial GLM is proposed and used. The optimum process conditions, which maximize the above probabilities and make the synthesis process less sensitive to variations of process variables around set values, are derived from the fitted models using Monte-Carlo simulations. The second part of the research deals with development of an experimental design methodology, tailor-made to address the unique phenomena associated with nanostructure synthesis. A sequential space filling design called Sequential Minimum Energy Design (SMED) for exploring best process conditions for synthesis of nanowires. The SMED is a novel approach to generate sequential designs that are model independent, can quickly "carve out" regions with no observable nanostructure morphology, and allow for the exploration of complex response surfaces.

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

PubMed Central

Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

Variable Selection for Confounder Control, Flexible Modeling and Collaborative Targeted Minimum Loss-Based Estimation in Causal Inference.

PubMed

Schnitzer, Mireille E; Lok, Judith J; Gruber, Susan

2016-05-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010 [27]) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low- and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Array coding for large data memories

NASA Technical Reports Server (NTRS)

Tranter, W. H.

1982-01-01

It is pointed out that an array code is a convenient method for storing large quantities of data. In a typical application, the array consists of N data words having M symbols in each word. The probability of undetected error is considered, taking into account three symbol error probabilities which are of interest, and a formula for determining the probability of undetected error. Attention is given to the possibility of reading data into the array using a digital communication system with symbol error probability p. Two different schemes are found to be of interest. The conducted analysis of array coding shows that the probability of undetected error is very small even for relatively large arrays.

Design Considerations of Polishing Lap for Computer-Controlled Cylindrical Polishing Process

NASA Technical Reports Server (NTRS)

Khan, Gufran S.; Gubarev, Mikhail; Arnold, William; Ramsey, Brian D.

2009-01-01

This paper establishes a relationship between the polishing process parameters and the generation of mid spatial-frequency error. The consideration of the polishing lap design to optimize the process in order to keep residual errors to a minimum and optimization of the process (speeds, stroke, etc.) and to keep the residual mid spatial-frequency error to a minimum, is also presented.

Potential benefit of electronic pharmacy claims data to prevent medication history errors and resultant inpatient order errors

PubMed Central

Palmer, Katherine A; Shane, Rita; Wu, Cindy N; Bell, Douglas S; Diaz, Frank; Cook-Wiens, Galen; Jackevicius, Cynthia A

2016-01-01

Objective We sought to assess the potential of a widely available source of electronic medication data to prevent medication history errors and resultant inpatient order errors. Methods We used admission medication history (AMH) data from a recent clinical trial that identified 1017 AMH errors and 419 resultant inpatient order errors among 194 hospital admissions of predominantly older adult patients on complex medication regimens. Among the subset of patients for whom we could access current Surescripts electronic pharmacy claims data (SEPCD), two pharmacists independently assessed error severity and our main outcome, which was whether SEPCD (1) was unrelated to the medication error; (2) probably would not have prevented the error; (3) might have prevented the error; or (4) probably would have prevented the error. Results Seventy patients had both AMH errors and current, accessible SEPCD. SEPCD probably would have prevented 110 (35%) of 315 AMH errors and 46 (31%) of 147 resultant inpatient order errors. When we excluded the least severe medication errors, SEPCD probably would have prevented 99 (47%) of 209 AMH errors and 37 (61%) of 61 resultant inpatient order errors. SEPCD probably would have prevented at least one AMH error in 42 (60%) of 70 patients. Conclusion When current SEPCD was available for older adult patients on complex medication regimens, it had substantial potential to prevent AMH errors and resultant inpatient order errors, with greater potential to prevent more severe errors. Further study is needed to measure the benefit of SEPCD in actual use at hospital admission. PMID:26911817

Microwave-photonics direction finding system for interception of low probability of intercept radio frequency signals

NASA Astrophysics Data System (ADS)

Pace, Phillip Eric; Tan, Chew Kung; Ong, Chee K.

2018-02-01

Direction finding (DF) systems are fundamental electronic support measures for electronic warfare. A number of DF techniques have been developed over the years; however, these systems are limited in bandwidth and resolution and suffer from a complex design for frequency downconversion. The design of a photonic DF technique for the detection and DF of low probability of intercept (LPI) signals is investigated. Key advantages of this design include a small baseline, wide bandwidth, high resolution, minimal space, weight, and power requirement. A robust postprocessing algorithm that utilizes the minimum Euclidean distance detector provides consistence and accurate estimation of angle of arrival (AoA) for a wide range of LPI waveforms. Experimental tests using frequency modulation continuous wave (FMCW) and P4 modulation signals were conducted in an anechoic chamber to verify the system design. Test results showed that the photonic DF system is capable of measuring the AoA of the LPI signals with 1-deg resolution over a 180 deg field-of-view. For an FMCW signal, the AoA was determined with a RMS error of 0.29 deg at 1-deg resolution. For a P4 coded signal, the RMS error in estimating the AoA is 0.32 deg at 1-deg resolution.

Robust linear discriminant models to solve financial crisis in banking sectors

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Idris, Faoziah; Ali, Hazlina; Omar, Zurni

2014-12-01

Linear discriminant analysis (LDA) is a widely-used technique in patterns classification via an equation which will minimize the probability of misclassifying cases into their respective categories. However, the performance of classical estimators in LDA highly depends on the assumptions of normality and homoscedasticity. Several robust estimators in LDA such as Minimum Covariance Determinant (MCD), S-estimators and Minimum Volume Ellipsoid (MVE) are addressed by many authors to alleviate the problem of non-robustness of the classical estimates. In this paper, we investigate on the financial crisis of the Malaysian banking institutions using robust LDA and classical LDA methods. Our objective is to distinguish the "distress" and "non-distress" banks in Malaysia by using the LDA models. Hit ratio is used to validate the accuracy predictive of LDA models. The performance of LDA is evaluated by estimating the misclassification rate via apparent error rate. The results and comparisons show that the robust estimators provide a better performance than the classical estimators for LDA.

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; The Map and Related Decoding Algirithms

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

In a coded communication system with equiprobable signaling, MLD minimizes the word error probability and delivers the most likely codeword associated with the corresponding received sequence. This decoding has two drawbacks. First, minimization of the word error probability is not equivalent to minimization of the bit error probability. Therefore, MLD becomes suboptimum with respect to the bit error probability. Second, MLD delivers a hard-decision estimate of the received sequence, so that information is lost between the input and output of the ML decoder. This information is important in coded schemes where the decoded sequence is further processed, such as concatenated coding schemes, multi-stage and iterative decoding schemes. In this chapter, we first present a decoding algorithm which both minimizes bit error probability, and provides the corresponding soft information at the output of the decoder. This algorithm is referred to as the MAP (maximum aposteriori probability) decoding algorithm.

Statistical learning from nonrecurrent experience with discrete input variables and recursive-error-minimization equations

NASA Astrophysics Data System (ADS)

Carter, Jeffrey R.; Simon, Wayne E.

1990-08-01

Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and

Implementation of projective measurements with linear optics and continuous photon counting

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

Takeoka, Masahiro; Sasaki, Masahide; Loock, Peter van

2005-02-01

We investigate the possibility of implementing a given projection measurement using linear optics and arbitrarily fast feedforward based on the continuous detection of photons. In particular, we systematically derive the so-called Dolinar scheme that achieves the minimum-error discrimination of binary coherent states. Moreover, we show that the Dolinar-type approach can also be applied to projection measurements in the regime of photonic-qubit signals. Our results demonstrate that for implementing a projection measurement with linear optics, in principle, unit success probability may be approached even without the use of expensive entangled auxiliary states, as they are needed in all known (near-)deterministic linear-opticsmore » proposals.« less

SPAR-H Step-by-Step Guidance

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

W. J. Galyean; A. M. Whaley; D. L. Kelly

This guide provides step-by-step guidance on the use of the SPAR-H method for quantifying Human Failure Events (HFEs). This guide is intended to be used with the worksheets provided in: 'The SPAR-H Human Reliability Analysis Method,' NUREG/CR-6883, dated August 2005. Each step in the process of producing a Human Error Probability (HEP) is discussed. These steps are: Step-1, Categorizing the HFE as Diagnosis and/or Action; Step-2, Rate the Performance Shaping Factors; Step-3, Calculate PSF-Modified HEP; Step-4, Accounting for Dependence, and; Step-5, Minimum Value Cutoff. The discussions on dependence are extensive and include an appendix that describes insights obtained from themore » psychology literature.« less

Analysis of randomly time varying systems by gaussian closure technique

NASA Astrophysics Data System (ADS)

Dash, P. K.; Iyengar, R. N.

1982-07-01

The Gaussian probability closure technique is applied to study the random response of multidegree of freedom stochastically time varying systems under non-Gaussian excitations. Under the assumption that the response, the coefficient and the excitation processes are jointly Gaussian, deterministic equations are derived for the first two response moments. It is further shown that this technique leads to the best Gaussian estimate in a minimum mean square error sense. An example problem is solved which demonstrates the capability of this technique for handling non-linearity, stochastic system parameters and amplitude limited responses in a unified manner. Numerical results obtained through the Gaussian closure technique compare well with the exact solutions.

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds.

PubMed

Ferrie, Christopher; Blume-Kohout, Robin

2016-03-04

A minimax estimator has the minimum possible error ("risk") in the worst case. We construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O(1/sqrt[N])-in contrast to that of classical probability estimation, which is O(1/N)-where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. This makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.

Object aggregation using Neyman-Pearson analysis

NASA Astrophysics Data System (ADS)

Bai, Li; Hinman, Michael L.

2003-04-01

This paper presents a novel approach to: 1) distinguish military vehicle groups, and 2) identify names of military vehicle convoys in the level-2 fusion process. The data is generated from a generic Ground Moving Target Indication (GMTI) simulator that utilizes Matlab and Microsoft Access. This data is processed to identify the convoys and number of vehicles in the convoy, using the minimum timed distance variance (MTDV) measurement. Once the vehicle groups are formed, convoy association is done using hypothesis techniques based upon Neyman Pearson (NP) criterion. One characteristic of NP is the low error probability when a-priori information is unknown. The NP approach was demonstrated with this advantage over a Bayesian technique.

Investigating the Relationship between Conceptual and Procedural Errors in the Domain of Probability Problem-Solving.

ERIC Educational Resources Information Center

O'Connell, Ann Aileen

The relationships among types of errors observed during probability problem solving were studied. Subjects were 50 graduate students in an introductory probability and statistics course. Errors were classified as text comprehension, conceptual, procedural, and arithmetic. Canonical correlation analysis was conducted on the frequencies of specific…

Approximate error conjugation gradient minimization methods

DOEpatents

Kallman, Jeffrey S

2013-05-21

In one embodiment, a method includes selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, calculating an approximate error using the subset of rays, and calculating a minimum in a conjugate gradient direction based on the approximate error. In another embodiment, a system includes a processor for executing logic, logic for selecting a subset of rays from a set of all rays to use in an error calculation for a constrained conjugate gradient minimization problem, logic for calculating an approximate error using the subset of rays, and logic for calculating a minimum in a conjugate gradient direction based on the approximate error. In other embodiments, computer program products, methods, and systems are described capable of using approximate error in constrained conjugate gradient minimization problems.

Fisher classifier and its probability of error estimation

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

Computationally efficient expressions are derived for estimating the probability of error using the leave-one-out method. The optimal threshold for the classification of patterns projected onto Fisher's direction is derived. A simple generalization of the Fisher classifier to multiple classes is presented. Computational expressions are developed for estimating the probability of error of the multiclass Fisher classifier.

Measurement of the Errors of Service Altimeter Installations During Landing-Approach and Take-Off Operations

NASA Technical Reports Server (NTRS)

Gracey, William; Jewel, Joseph W., Jr.; Carpenter, Gene T.

1960-01-01

The overall errors of the service altimeter installations of a variety of civil transport, military, and general-aviation airplanes have been experimentally determined during normal landing-approach and take-off operations. The average height above the runway at which the data were obtained was about 280 feet for the landings and about 440 feet for the take-offs. An analysis of the data obtained from 196 airplanes during 415 landing approaches and from 70 airplanes during 152 take-offs showed that: 1. The overall error of the altimeter installations in the landing- approach condition had a probable value (50 percent probability) of +/- 36 feet and a maximum probable value (99.7 percent probability) of +/- 159 feet with a bias of +10 feet. 2. The overall error in the take-off condition had a probable value of +/- 47 feet and a maximum probable value of +/- 207 feet with a bias of -33 feet. 3. The overall errors of the military airplanes were generally larger than those of the civil transports in both the landing-approach and take-off conditions. In the landing-approach condition the probable error and the maximum probable error of the military airplanes were +/- 43 and +/- 189 feet, respectively, with a bias of +15 feet, whereas those for the civil transports were +/- 22 and +/- 96 feet, respectively, with a bias of +1 foot. 4. The bias values of the error distributions (+10 feet for the landings and -33 feet for the take-offs) appear to represent a measure of the hysteresis characteristics (after effect and recovery) and friction of the instrument and the pressure lag of the tubing-instrument system.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on "failure modes and effects analysis".

PubMed

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of "failure modes and effects analysis" (FMEA). In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members' decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors.

Identification and assessment of common errors in the admission process of patients in Isfahan Fertility and Infertility Center based on “failure modes and effects analysis”

PubMed Central

Dehghan, Ashraf; Abumasoudi, Rouhollah Sheikh; Ehsanpour, Soheila

2016-01-01

Background: Infertility and errors in the process of its treatment have a negative impact on infertile couples. The present study was aimed to identify and assess the common errors in the reception process by applying the approach of “failure modes and effects analysis” (FMEA). Materials and Methods: In this descriptive cross-sectional study, the admission process of fertility and infertility center of Isfahan was selected for evaluation of its errors based on the team members’ decision. At first, the admission process was charted through observations and interviewing employees, holding multiple panels, and using FMEA worksheet, which has been used in many researches all over the world and also in Iran. Its validity was evaluated through content and face validity, and its reliability was evaluated through reviewing and confirmation of the obtained information by the FMEA team, and eventually possible errors, causes, and three indicators of severity of effect, probability of occurrence, and probability of detection were determined and corrective actions were proposed. Data analysis was determined by the number of risk priority (RPN) which is calculated by multiplying the severity of effect, probability of occurrence, and probability of detection. Results: Twenty-five errors with RPN ≥ 125 was detected through the admission process, in which six cases of error had high priority in terms of severity and occurrence probability and were identified as high-risk errors. Conclusions: The team-oriented method of FMEA could be useful for assessment of errors and also to reduce the occurrence probability of errors. PMID:28194208

Design and performance evaluation of a master controller for endovascular catheterization.

PubMed

Guo, Jin; Guo, Shuxiang; Tamiya, Takashi; Hirata, Hideyuki; Ishihara, Hidenori

2016-01-01

It is difficult to manipulate a flexible catheter to target a position within a patient's complicated and delicate vessels. However, few researchers focused on the controller designs with much consideration of the natural catheter manipulation skills obtained from manual catheterization. Also, the existing catheter motion measurement methods probably lead to the difficulties in designing the force feedback device. Additionally, the commercially available systems are too expensive which makes them cost prohibitive to most hospitals. This paper presents a simple and cost-effective master controller for endovascular catheterization that can allow the interventionalists to apply the conventional pull, push and twist of the catheter used in current practice. A catheter-sensing unit (used to measure the motion of the catheter) and a force feedback unit (used to provide a sense of resistance force) are both presented. A camera was used to allow a contactless measurement avoiding additional friction, and the force feedback in the axial direction was provided by the magnetic force generated between the permanent magnets and the powered coil. Performance evaluation of the controller was evaluated by first conducting comparison experiments to quantify the accuracy of the catheter-sensing unit, and then conducting several experiments to evaluate the force feedback unit. From the experimental results, the minimum and the maximum errors of translational displacement were 0.003 mm (0.01 %) and 0.425 mm (1.06 %), respectively. The average error was 0.113 mm (0.28 %). In terms of rotational angles, the minimum and the maximum errors were 0.39°(0.33 %) and 7.2°(6 %), respectively. The average error was 3.61°(3.01 %). The force resolution was approximately 25 mN and a maximum current of 3A generated an approximately 1.5 N force. Based on analysis of requirements and state-of-the-art computer-assisted and robot-assisted training systems for endovascular catheterization, a new master controller with force feedback interface was proposed to maintain the natural endovascular catheterization skills of the interventionalists.

Does a better model yield a better argument? An info-gap analysis

NASA Astrophysics Data System (ADS)

Ben-Haim, Yakov

2017-04-01

Theories, models and computations underlie reasoned argumentation in many areas. The possibility of error in these arguments, though of low probability, may be highly significant when the argument is used in predicting the probability of rare high-consequence events. This implies that the choice of a theory, model or computational method for predicting rare high-consequence events must account for the probability of error in these components. However, error may result from lack of knowledge or surprises of various sorts, and predicting the probability of error is highly uncertain. We show that the putatively best, most innovative and sophisticated argument may not actually have the lowest probability of error. Innovative arguments may entail greater uncertainty than more standard but less sophisticated methods, creating an innovation dilemma in formulating the argument. We employ info-gap decision theory to characterize and support the resolution of this problem and present several examples.

Navigator alignment using radar scan

DOEpatents

Doerry, Armin W.; Marquette, Brandeis

2016-04-05

The various technologies presented herein relate to the determination of and correction of heading error of platform. Knowledge of at least one of a maximum Doppler frequency or a minimum Doppler bandwidth pertaining to a plurality of radar echoes can be utilized to facilitate correction of the heading error. Heading error can occur as a result of component drift. In an ideal situation, a boresight direction of an antenna or the front of an aircraft will have associated therewith at least one of a maximum Doppler frequency or a minimum Doppler bandwidth. As the boresight direction of the antenna strays from a direction of travel at least one of the maximum Doppler frequency or a minimum Doppler bandwidth will shift away, either left or right, from the ideal situation.

Synthetic Aperture Sonar Processing with MMSE Estimation of Image Sample Values

DTIC Science & Technology

2016-12-01

UNCLASSIFIED/UNLIMITED 13. SUPPLEMENTARY NOTES 14. ABSTRACT MMSE (minimum mean- square error) target sample estimation using non-orthogonal basis...orthogonal, they can still be used in a minimum mean‐ square  error (MMSE)  estimator that models the object echo as a weighted sum of the multi‐aspect basis...problem.                     3    Introduction      Minimum mean‐ square  error (MMSE) estimation is applied to target imaging with synthetic aperture

Error Patterns in Ordering Fractions among At-Risk Fourth-Grade Students

PubMed Central

Malone, Amelia S.; Fuchs, Lynn S.

2016-01-01

The 3 purposes of this study were to: (a) describe fraction ordering errors among at-risk 4th-grade students; (b) assess the effect of part-whole understanding and accuracy of fraction magnitude estimation on the probability of committing errors; and (c) examine the effect of students' ability to explain comparing problems on the probability of committing errors. Students (n = 227) completed a 9-item ordering test. A high proportion (81%) of problems were completed incorrectly. Most (65% of) errors were due to students misapplying whole number logic to fractions. Fraction-magnitude estimation skill, but not part-whole understanding, significantly predicted the probability of committing this type of error. Implications for practice are discussed. PMID:26966153

Sensitivity of peptide conformational dynamics on clustering of a classical molecular dynamics trajectory

NASA Astrophysics Data System (ADS)

Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.

2008-03-01

We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.

Human Error Analysis in a Permit to Work System: A Case Study in a Chemical Plant

PubMed Central

Jahangiri, Mehdi; Hoboubi, Naser; Rostamabadi, Akbar; Keshavarzi, Sareh; Hosseini, Ali Akbar

2015-01-01

Background A permit to work (PTW) is a formal written system to control certain types of work which are identified as potentially hazardous. However, human error in PTW processes can lead to an accident. Methods This cross-sectional, descriptive study was conducted to estimate the probability of human errors in PTW processes in a chemical plant in Iran. In the first stage, through interviewing the personnel and studying the procedure in the plant, the PTW process was analyzed using the hierarchical task analysis technique. In doing so, PTW was considered as a goal and detailed tasks to achieve the goal were analyzed. In the next step, the standardized plant analysis risk-human (SPAR-H) reliability analysis method was applied for estimation of human error probability. Results The mean probability of human error in the PTW system was estimated to be 0.11. The highest probability of human error in the PTW process was related to flammable gas testing (50.7%). Conclusion The SPAR-H method applied in this study could analyze and quantify the potential human errors and extract the required measures for reducing the error probabilities in PTW system. Some suggestions to reduce the likelihood of errors, especially in the field of modifying the performance shaping factors and dependencies among tasks are provided. PMID:27014485

Probability of undetected error after decoding for a concatenated coding scheme

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.

1984-01-01

A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for NASA telecommand system is analyzed.

Target intersection probabilities for parallel-line and continuous-grid types of search

USGS Publications Warehouse

McCammon, R.B.

1977-01-01

The expressions for calculating the probability of intersection of hidden targets of different sizes and shapes for parallel-line and continuous-grid types of search can be formulated by vsing the concept of conditional probability. When the prior probability of the orientation of a widden target is represented by a uniform distribution, the calculated posterior probabilities are identical with the results obtained by the classic methods of probability. For hidden targets of different sizes and shapes, the following generalizations about the probability of intersection can be made: (1) to a first approximation, the probability of intersection of a hidden target is proportional to the ratio of the greatest dimension of the target (viewed in plane projection) to the minimum line spacing of the search pattern; (2) the shape of the hidden target does not greatly affect the probability of the intersection when the largest dimension of the target is small relative to the minimum spacing of the search pattern, (3) the probability of intersecting a target twice for a particular type of search can be used as a lower bound if there is an element of uncertainty of detection for a particular type of tool; (4) the geometry of the search pattern becomes more critical when the largest dimension of the target equals or exceeds the minimum spacing of the search pattern; (5) for elongate targets, the probability of intersection is greater for parallel-line search than for an equivalent continuous square-grid search when the largest dimension of the target is less than the minimum spacing of the search pattern, whereas the opposite is true when the largest dimension exceeds the minimum spacing; (6) the probability of intersection for nonorthogonal continuous-grid search patterns is not greatly different from the probability of intersection for the equivalent orthogonal continuous-grid pattern when the orientation of the target is unknown. The probability of intersection for an elliptically shaped target can be approximated by treating the ellipse as intermediate between a circle and a line. A search conducted along a continuous rectangular grid can be represented as intermediate between a search along parallel lines and along a continuous square grid. On this basis, an upper and lower bound for the probability of intersection of an elliptically shaped target for a continuous rectangular grid can be calculated. Charts have been constructed that permit the values for these probabilities to be obtained graphically. The use of conditional probability allows the explorationist greater flexibility in considering alternate search strategies for locating hidden targets. ?? 1977 Plenum Publishing Corp.

Optimal sequential measurements for bipartite state discrimination

NASA Astrophysics Data System (ADS)

Croke, Sarah; Barnett, Stephen M.; Weir, Graeme

2017-05-01

State discrimination is a useful test problem with which to clarify the power and limitations of different classes of measurement. We consider the problem of discriminating between given states of a bipartite quantum system via sequential measurement of the subsystems, with classical feed-forward of measurement results. Our aim is to understand when sequential measurements, which are relatively easy to implement experimentally, perform as well, or almost as well, as optimal joint measurements, which are in general more technologically challenging. We construct conditions that the optimal sequential measurement must satisfy, analogous to the well-known Helstrom conditions for minimum error discrimination in the unrestricted case. We give several examples and compare the optimal probability of correctly identifying the state via global versus sequential measurement strategies.

Unmodeled observation error induces bias when inferring patterns and dynamics of species occurrence via aural detections

USGS Publications Warehouse

McClintock, Brett T.; Bailey, Larissa L.; Pollock, Kenneth H.; Simons, Theodore R.

2010-01-01

The recent surge in the development and application of species occurrence models has been associated with an acknowledgment among ecologists that species are detected imperfectly due to observation error. Standard models now allow unbiased estimation of occupancy probability when false negative detections occur, but this is conditional on no false positive detections and sufficient incorporation of explanatory variables for the false negative detection process. These assumptions are likely reasonable in many circumstances, but there is mounting evidence that false positive errors and detection probability heterogeneity may be much more prevalent in studies relying on auditory cues for species detection (e.g., songbird or calling amphibian surveys). We used field survey data from a simulated calling anuran system of known occupancy state to investigate the biases induced by these errors in dynamic models of species occurrence. Despite the participation of expert observers in simplified field conditions, both false positive errors and site detection probability heterogeneity were extensive for most species in the survey. We found that even low levels of false positive errors, constituting as little as 1% of all detections, can cause severe overestimation of site occupancy, colonization, and local extinction probabilities. Further, unmodeled detection probability heterogeneity induced substantial underestimation of occupancy and overestimation of colonization and local extinction probabilities. Completely spurious relationships between species occurrence and explanatory variables were also found. Such misleading inferences would likely have deleterious implications for conservation and management programs. We contend that all forms of observation error, including false positive errors and heterogeneous detection probabilities, must be incorporated into the estimation framework to facilitate reliable inferences about occupancy and its associated vital rate parameters.

Adaptive feedforward control of non-minimum phase structural systems

NASA Astrophysics Data System (ADS)

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

1995-06-01

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

Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme

NASA Astrophysics Data System (ADS)

Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim

2014-11-01

In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.

On the timing problem in optical PPM communications.

NASA Technical Reports Server (NTRS)

Gagliardi, R. M.

1971-01-01

Investigation of the effects of imperfect timing in a direct-detection (noncoherent) optical system using pulse-position-modulation bits. Special emphasis is placed on specification of timing accuracy, and an examination of system degradation when this accuracy is not attained. Bit error probabilities are shown as a function of timing errors, from which average error probabilities can be computed for specific synchronization methods. Of significant importance is shown to be the presence of a residual, or irreducible error probability, due entirely to the timing system, that cannot be overcome by the data channel.

Adaptive color halftoning for minimum perceived error using the blue noise mask

NASA Astrophysics Data System (ADS)

Yu, Qing; Parker, Kevin J.

1997-04-01

Color halftoning using a conventional screen requires careful selection of screen angles to avoid Moire patterns. An obvious advantage of halftoning using a blue noise mask (BNM) is that there are no conventional screen angle or Moire patterns produced. However, a simple strategy of employing the same BNM on all color planes is unacceptable in case where a small registration error can cause objectionable color shifts. In a previous paper by Yao and Parker, strategies were presented for shifting or inverting the BNM as well as using mutually exclusive BNMs for different color planes. In this paper, the above schemes will be studied in CIE-LAB color space in terms of root mean square error and variance for luminance channel and chrominance channel respectively. We will demonstrate that the dot-on-dot scheme results in minimum chrominance error, but maximum luminance error and the 4-mask scheme results in minimum luminance error but maximum chrominance error, while the shift scheme falls in between. Based on this study, we proposed a new adaptive color halftoning algorithm that takes colorimetric color reproduction into account by applying 2-mutually exclusive BNMs on two different color planes and applying an adaptive scheme on other planes to reduce color error. We will show that by having one adaptive color channel, we obtain increased flexibility to manipulate the output so as to reduce colorimetric error while permitting customization to specific printing hardware.

Wireless visual sensor network resource allocation using cross-layer optimization

NASA Astrophysics Data System (ADS)

Bentley, Elizabeth S.; Matyjas, John D.; Medley, Michael J.; Kondi, Lisimachos P.

2009-01-01

In this paper, we propose an approach to manage network resources for a Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our approach allows one to determine the capacity of the visual sensor network based on the number of nodes and the quality of video that must be transmitted. For bandwidth-limited applications, one can also determine the minimum bandwidth needed to accommodate a number of nodes with a specific target chip rate. Video captured by a sensor node camera is encoded and decoded using the H.264 video codec by a centralized control unit at the network layer. To reduce the computational complexity of the solution, Universal Rate-Distortion Characteristics (URDCs) are obtained experimentally to relate bit error probabilities to the distortion of corrupted video. Bit error rates are found first by using Viterbi's upper bounds on the bit error probability and second, by simulating nodes transmitting data spread by Total Square Correlation (TSC) codes over a Rayleigh-faded DS-CDMA channel and receiving that data using Auxiliary Vector (AV) filtering.

Sample Size Determination for Rasch Model Tests

ERIC Educational Resources Information Center

Draxler, Clemens

2010-01-01

This paper is concerned with supplementing statistical tests for the Rasch model so that additionally to the probability of the error of the first kind (Type I probability) the probability of the error of the second kind (Type II probability) can be controlled at a predetermined level by basing the test on the appropriate number of observations.…

Exploring the sensitivity of current and future experiments to θ⊙

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Abhijit; Choubey, Sandhya; Goswami, Srubabati

2003-06-01

The first results from the KamLAND experiment in conjunction with the global solar neutrino data have demonstrated the striking ability to constrain the Δm2⊙ (Δm221) very precisely. However the allowed range of θ⊙ (θ12) did not change much with the inclusion of the KamLAND results. In this paper we probe if future data from KamLAND can increase the accuracy of the allowed range in θ⊙ and conclude that even after 3 kton yr of statistics and with the most optimistic error estimates, KamLAND may find it hard to significantly improve the bounds on the mixing angle obtained from the solar neutrino data. We discuss the θ12 sensitivity of the survival probabilities in matter (vacuum) as relevant for the solar (KamLAND) experiments. We find that the presence of matter effects in the survival probabilities for 8B neutrinos gives the solar neutrino experiments SK and SNO an edge over KamLAND, as far as θ12 sensitivity is concerned, particularly near the maximal mixing. Among solar neutrino experiments we identify SNO as a most promising candidate for constraining θ12 and make a projected sensitivity test for the mixing angle by reducing the error in the neutral current measurement at SNO. Finally, we argue that the most accurate bounds on θ12 can be achieved in a reactor experiment, if the corresponding baseline and energy can be tuned to a minimum in the survival probability. We propose a new reactor experiment that can give the value of tan2θ12 to within 14%. We also discuss the future Borexino and LowNu experiments.

P value and the theory of hypothesis testing: an explanation for new researchers.

PubMed

Biau, David Jean; Jolles, Brigitte M; Porcher, Raphaël

2010-03-01

In the 1920s, Ronald Fisher developed the theory behind the p value and Jerzy Neyman and Egon Pearson developed the theory of hypothesis testing. These distinct theories have provided researchers important quantitative tools to confirm or refute their hypotheses. The p value is the probability to obtain an effect equal to or more extreme than the one observed presuming the null hypothesis of no effect is true; it gives researchers a measure of the strength of evidence against the null hypothesis. As commonly used, investigators will select a threshold p value below which they will reject the null hypothesis. The theory of hypothesis testing allows researchers to reject a null hypothesis in favor of an alternative hypothesis of some effect. As commonly used, investigators choose Type I error (rejecting the null hypothesis when it is true) and Type II error (accepting the null hypothesis when it is false) levels and determine some critical region. If the test statistic falls into that critical region, the null hypothesis is rejected in favor of the alternative hypothesis. Despite similarities between the two, the p value and the theory of hypothesis testing are different theories that often are misunderstood and confused, leading researchers to improper conclusions. Perhaps the most common misconception is to consider the p value as the probability that the null hypothesis is true rather than the probability of obtaining the difference observed, or one that is more extreme, considering the null is true. Another concern is the risk that an important proportion of statistically significant results are falsely significant. Researchers should have a minimum understanding of these two theories so that they are better able to plan, conduct, interpret, and report scientific experiments.

78 FR 28597 - State Median Income Estimates for a Four-Person Household: Notice of the Federal Fiscal Year (FFY...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-15

....gov/acs/www/ or contact the Census Bureau's Social, Economic, and Housing Statistics Division at (301...) Sampling Error, which consists of the error that arises from the use of probability sampling to create the... direction; and (2) Sampling Error, which consists of the error that arises from the use of probability...

Sensitivity of feedforward neural networks to weight errors

NASA Technical Reports Server (NTRS)

Stevenson, Maryhelen; Widrow, Bernard; Winter, Rodney

1990-01-01

An analysis is made of the sensitivity of feedforward layered networks of Adaline elements (threshold logic units) to weight errors. An approximation is derived which expresses the probability of error for an output neuron of a large network (a network with many neurons per layer) as a function of the percentage change in the weights. As would be expected, the probability of error increases with the number of layers in the network and with the percentage change in the weights. The probability of error is essentially independent of the number of weights per neuron and of the number of neurons per layer, as long as these numbers are large (on the order of 100 or more).

Type I error probabilities based on design-stage strategies with applications to noninferiority trials.

PubMed

Rothmann, Mark

2005-01-01

When testing the equality of means from two different populations, a t-test or large sample normal test tend to be performed. For these tests, when the sample size or design for the second sample is dependent on the results of the first sample, the type I error probability is altered for each specific possibility in the null hypothesis. We will examine the impact on the type I error probabilities for two confidence interval procedures and procedures using test statistics when the design for the second sample or experiment is dependent on the results from the first sample or experiment (or series of experiments). Ways for controlling a desired maximum type I error probability or a desired type I error rate will be discussed. Results are applied to the setting of noninferiority comparisons in active controlled trials where the use of a placebo is unethical.

Inverse sequential detection of parameter changes in developing time series

NASA Technical Reports Server (NTRS)

Radok, Uwe; Brown, Timothy J.

1992-01-01

Progressive values of two probabilities are obtained for parameter estimates derived from an existing set of values and from the same set enlarged by one or more new values, respectively. One probability is that of erroneously preferring the second of these estimates for the existing data ('type 1 error'), while the second probability is that of erroneously accepting their estimates for the enlarged test ('type 2 error'). A more stable combined 'no change' probability which always falls between 0.5 and 0 is derived from the (logarithmic) width of the uncertainty region of an equivalent 'inverted' sequential probability ratio test (SPRT, Wald 1945) in which the error probabilities are calculated rather than prescribed. A parameter change is indicated when the compound probability undergoes a progressive decrease. The test is explicitly formulated and exemplified for Gaussian samples.

Poster error probability in the Mu-11 Sequential Ranging System

NASA Technical Reports Server (NTRS)

Coyle, C. W.

1981-01-01

An expression is derived for the posterior error probability in the Mu-2 Sequential Ranging System. An algorithm is developed which closely bounds the exact answer and can be implemented in the machine software. A computer simulation is provided to illustrate the improved level of confidence in a ranging acquisition using this figure of merit as compared to that using only the prior probabilities. In a simulation of 20,000 acquisitions with an experimentally determined threshold setting, the algorithm detected 90% of the actual errors and made false indication of errors on 0.2% of the acquisitions.

Application of genetic algorithm in the evaluation of the profile error of archimedes helicoid surface

NASA Astrophysics Data System (ADS)

Zhu, Lianqing; Chen, Yunfang; Chen, Qingshan; Meng, Hao

2011-05-01

According to minimum zone condition, a method for evaluating the profile error of Archimedes helicoid surface based on Genetic Algorithm (GA) is proposed. The mathematic model of the surface is provided and the unknown parameters in the equation of surface are acquired through least square method. Principle of GA is explained. Then, the profile error of Archimedes Helicoid surface is obtained through GA optimization method. To validate the proposed method, the profile error of an Archimedes helicoid surface, Archimedes Cylindrical worm (ZA worm) surface, is evaluated. The results show that the proposed method is capable of correctly evaluating the profile error of Archimedes helicoid surface and satisfy the evaluation standard of the Minimum Zone Method. It can be applied to deal with the measured data of profile error of complex surface obtained by three coordinate measurement machines (CMM).

Cross Validation Through Two-Dimensional Solution Surface for Cost-Sensitive SVM.

PubMed

Gu, Bin; Sheng, Victor S; Tay, Keng Yeow; Romano, Walter; Li, Shuo

2017-06-01

Model selection plays an important role in cost-sensitive SVM (CS-SVM). It has been proven that the global minimum cross validation (CV) error can be efficiently computed based on the solution path for one parameter learning problems. However, it is a challenge to obtain the global minimum CV error for CS-SVM based on one-dimensional solution path and traditional grid search, because CS-SVM is with two regularization parameters. In this paper, we propose a solution and error surfaces based CV approach (CV-SES). More specifically, we first compute a two-dimensional solution surface for CS-SVM based on a bi-parameter space partition algorithm, which can fit solutions of CS-SVM for all values of both regularization parameters. Then, we compute a two-dimensional validation error surface for each CV fold, which can fit validation errors of CS-SVM for all values of both regularization parameters. Finally, we obtain the CV error surface by superposing K validation error surfaces, which can find the global minimum CV error of CS-SVM. Experiments are conducted on seven datasets for cost sensitive learning and on four datasets for imbalanced learning. Experimental results not only show that our proposed CV-SES has a better generalization ability than CS-SVM with various hybrids between grid search and solution path methods, and than recent proposed cost-sensitive hinge loss SVM with three-dimensional grid search, but also show that CV-SES uses less running time.

The influence of the uplink noise on the performance of satellite data transmission systems

NASA Astrophysics Data System (ADS)

Dewal, Vrinda P.

The problem of transmission of binary phase shift keying (BPSK) modulated digital data through a bandlimited nonlinear satellite channel in the presence of uplink, downlink Gaussian noise and intersymbol interface is examined. The satellite transponder is represented by a zero memory bandpass nonlinearity, with AM/AM conversion. The proposed optimum linear receiver structure consists of tapped-delay lines followed by a decision device. The linear receiver is designed to minimize the mean square error that is a function of the intersymbol interface, the uplink and the downlink noise. The minimum mean square error equalizer (MMSE) is derived using the Wiener-Kolmogorov theory. In this receiver, the decision about the transmitted signal is made by taking into account the received sequence of present sample, and the interfering past and future samples, which represent the intersymbol interference (ISI). Illustrative examples of the receiver structures are considered for the nonlinear channels with a symmetrical and asymmetrical frequency responses of the transmitter filter. The transponder nonlinearity is simulated by a polynomial using only the first and the third orders terms. A computer simulation determines the tap gain coefficients of the MMSE equalizer that adapt to the various uplink and downlink noise levels. The performance of the MMSE equalizer is evaluated in terms of an estimate of the average probability of error.

Cost effectiveness of the U.S. Geological Survey's stream-gaging program in Wisconsin

USGS Publications Warehouse

Walker, J.F.; Osen, L.L.; Hughes, P.E.

1987-01-01

A minimum budget of $510,000 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gaging stations. At this minimum budget, the theoretical average standard error of instantaneous discharge is 14.4%. The maximum budget analyzed was $650,000 and resulted in an average standard of error of instantaneous discharge of 7.2%. 

A Quantum Theoretical Explanation for Probability Judgment Errors

ERIC Educational Resources Information Center

Busemeyer, Jerome R.; Pothos, Emmanuel M.; Franco, Riccardo; Trueblood, Jennifer S.

2011-01-01

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector…

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Lin, S.

1985-01-01

A concatenated coding scheme for error contol in data communications was analyzed. The inner code is used for both error correction and detection, however the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughout efficiency of the proposed error control scheme incorporated with a selective repeat ARQ retransmission strategy is analyzed.

An optimization approach for observation association with systemic uncertainty applied to electro-optical systems

NASA Astrophysics Data System (ADS)

Worthy, Johnny L.; Holzinger, Marcus J.; Scheeres, Daniel J.

2018-06-01

The observation to observation measurement association problem for dynamical systems can be addressed by determining if the uncertain admissible regions produced from each observation have one or more points of intersection in state space. An observation association method is developed which uses an optimization based approach to identify local Mahalanobis distance minima in state space between two uncertain admissible regions. A binary hypothesis test with a selected false alarm rate is used to assess the probability that an intersection exists at the point(s) of minimum distance. The systemic uncertainties, such as measurement uncertainties, timing errors, and other parameter errors, define a distribution about a state estimate located at the local Mahalanobis distance minima. If local minima do not exist, then the observations are not associated. The proposed method utilizes an optimization approach defined on a reduced dimension state space to reduce the computational load of the algorithm. The efficacy and efficiency of the proposed method is demonstrated on observation data collected from the Georgia Tech Space Object Research Telescope.

The effect of timing errors in optical digital systems.

NASA Technical Reports Server (NTRS)

Gagliardi, R. M.

1972-01-01

The use of digital transmission with narrow light pulses appears attractive for data communications, but carries with it a stringent requirement on system bit timing. The effects of imperfect timing in direct-detection (noncoherent) optical binary systems are investigated using both pulse-position modulation and on-off keying for bit transmission. Particular emphasis is placed on specification of timing accuracy and an examination of system degradation when this accuracy is not attained. Bit error probabilities are shown as a function of timing errors from which average error probabilities can be computed for specific synchronization methods. Of significance is the presence of a residual or irreducible error probability in both systems, due entirely to the timing system, which cannot be overcome by the data channel.

Minimax Quantum Tomography: Estimators and Relative Entropy Bounds

DOE PAGES

Ferrie, Christopher; Blume-Kohout, Robin

2016-03-04

A minimax estimator has the minimum possible error (“risk”) in the worst case. Here we construct the first minimax estimators for quantum state tomography with relative entropy risk. The minimax risk of nonadaptive tomography scales as O (1/more » $$\\sqrt{N}$$ ) —in contrast to that of classical probability estimation, which is O (1/N) —where N is the number of copies of the quantum state used. We trace this deficiency to sampling mismatch: future observations that determine risk may come from a different sample space than the past data that determine the estimate. Lastly, this makes minimax estimators very biased, and we propose a computationally tractable alternative with similar behavior in the worst case, but superior accuracy on most states.« less

The analytical design of spectral measurements for multispectral remote sensor systems

NASA Technical Reports Server (NTRS)

Wiersma, D. J.; Landgrebe, D. A. (Principal Investigator)

1979-01-01

The author has identified the following significant results. In order to choose a design which will be optimal for the largest class of remote sensing problems, a method was developed which attempted to represent the spectral response function from a scene as accurately as possible. The performance of the overall recognition system was studied relative to the accuracy of the spectral representation. The spectral representation was only one of a set of five interrelated parameter categories which also included the spatial representation parameter, the signal to noise ratio, ancillary data, and information classes. The spectral response functions observed from a stratum were modeled as a stochastic process with a Gaussian probability measure. The criterion for spectral representation was defined by the minimum expected mean-square error.

On the design of classifiers for crop inventories

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

Nematode Damage Functions: The Problems of Experimental and Sampling Error

PubMed Central

Ferris, H.

1984-01-01

The development and use of pest damage functions involves measurement and experimental errors associated with cultural, environmental, and distributional factors. Damage predictions are more valuable if considered with associated probability. Collapsing population densities into a geometric series of population classes allows a pseudo-replication removal of experimental and sampling error in damage function development. Recognition of the nature of sampling error for aggregated populations allows assessment of probability associated with the population estimate. The product of the probabilities incorporated in the damage function and in the population estimate provides a basis for risk analysis of the yield loss prediction and the ensuing management decision. PMID:19295865

More on the decoder error probability for Reed-Solomon codes

NASA Technical Reports Server (NTRS)

Cheung, K.-M.

1987-01-01

The decoder error probability for Reed-Solomon codes (more generally, linear maximum distance separable codes) is examined. McEliece and Swanson offered an upper bound on P sub E (u), the decoder error probability given that u symbol errors occurs. This upper bound is slightly greater than Q, the probability that a completely random error pattern will cause decoder error. By using a combinatoric technique, the principle of inclusion and exclusion, an exact formula for P sub E (u) is derived. The P sub e (u) for the (255, 223) Reed-Solomon Code used by NASA, and for the (31,15) Reed-Solomon code (JTIDS code), are calculated using the exact formula, and the P sub E (u)'s are observed to approach the Q's of the codes rapidly as u gets larger. An upper bound for the expression is derived, and is shown to decrease nearly exponentially as u increases. This proves analytically that P sub E (u) indeed approaches Q as u becomes large, and some laws of large numbers come into play.

A robust approach to chance constrained optimal power flow with renewable generation

DOE PAGES

Lubin, Miles; Dvorkin, Yury; Backhaus, Scott N.

2016-09-01

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved usingmore » a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.« less

Three-class ROC analysis--the equal error utility assumption and the optimality of three-class ROC surface using the ideal observer.

PubMed

He, Xin; Frey, Eric C

2006-08-01

Previously, we have developed a decision model for three-class receiver operating characteristic (ROC) analysis based on decision theory. The proposed decision model maximizes the expected decision utility under the assumption that incorrect decisions have equal utilities under the same hypothesis (equal error utility assumption). This assumption reduced the dimensionality of the "general" three-class ROC analysis and provided a practical figure-of-merit to evaluate the three-class task performance. However, it also limits the generality of the resulting model because the equal error utility assumption will not apply for all clinical three-class decision tasks. The goal of this study was to investigate the optimality of the proposed three-class decision model with respect to several other decision criteria. In particular, besides the maximum expected utility (MEU) criterion used in the previous study, we investigated the maximum-correctness (MC) (or minimum-error), maximum likelihood (ML), and Nyman-Pearson (N-P) criteria. We found that by making assumptions for both MEU and N-P criteria, all decision criteria lead to the previously-proposed three-class decision model. As a result, this model maximizes the expected utility under the equal error utility assumption, maximizes the probability of making correct decisions, satisfies the N-P criterion in the sense that it maximizes the sensitivity of one class given the sensitivities of the other two classes, and the resulting ROC surface contains the maximum likelihood decision operating point. While the proposed three-class ROC analysis model is not optimal in the general sense due to the use of the equal error utility assumption, the range of criteria for which it is optimal increases its applicability for evaluating and comparing a range of diagnostic systems.

Global distortion of GPS networks associated with satellite antenna model errors

NASA Astrophysics Data System (ADS)

Cardellach, E.; Elósegui, P.; Davis, J. L.

2007-07-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by ˜1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PCO errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm yr-1 level, which will impact high-precision crustal deformation studies.

Global Distortion of GPS Networks Associated with Satellite Antenna Model Errors

NASA Technical Reports Server (NTRS)

Cardellach, E.; Elosequi, P.; Davis, J. L.

2007-01-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by approx.1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PC0 errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm/yr level, which will impact high-precision crustal deformation studies.

Neural dynamics of reward probability coding: a Magnetoencephalographic study in humans

PubMed Central

Thomas, Julie; Vanni-Mercier, Giovanna; Dreher, Jean-Claude

2013-01-01

Prediction of future rewards and discrepancy between actual and expected outcomes (prediction error) are crucial signals for adaptive behavior. In humans, a number of fMRI studies demonstrated that reward probability modulates these two signals in a large brain network. Yet, the spatio-temporal dynamics underlying the neural coding of reward probability remains unknown. Here, using magnetoencephalography, we investigated the neural dynamics of prediction and reward prediction error computations while subjects learned to associate cues of slot machines with monetary rewards with different probabilities. We showed that event-related magnetic fields (ERFs) arising from the visual cortex coded the expected reward value 155 ms after the cue, demonstrating that reward value signals emerge early in the visual stream. Moreover, a prediction error was reflected in ERF peaking 300 ms after the rewarded outcome and showing decreasing amplitude with higher reward probability. This prediction error signal was generated in a network including the anterior and posterior cingulate cortex. These findings pinpoint the spatio-temporal characteristics underlying reward probability coding. Together, our results provide insights into the neural dynamics underlying the ability to learn probabilistic stimuli-reward contingencies. PMID:24302894

How to Attain an Ultralow Interfacial Tension and a Three-Phase Behavior with a Surfactant Formulation for Enhanced Oil Recovery: A Review. Part 2. Performance Improvement Trends from Winsor's Premise to Currently Proposed Inter- and Intra-Molecular Mixtures.

PubMed

Salager, Jean-Louis; Forgiarini, Ana M; Márquez, Laura; Manchego, Lisbeth; Bullón, Johnny

2013-01-01

The minimum interfacial tension occurrence along a formulation scan at the so-called optimum formulation is discussed to be related to the interfacial curvature. The attained minimum tension is inversely proportional to the domain size of the bicontinuous microemulsion and to the interfacial layer rigidity, but no accurate prediction is available. The data from a very simple ternary system made of pure products accurately follows the correlation for optimum formulation, and exhibit a linear relationship between the performance index as the logarithm of the minimum tension at optimum, and the formulation variables. This relation is probably too simple when the number of variables is increased as in practical cases. The review of published data for more realistic systems proposed for enhanced oil recovery over the past 30 years indicates a general guidelines following Winsor's basic studies concerning the surfactant-oil-water interfacial interactions. It is well known that the major performance benefits are achieved by blending amphiphilic species at the interface as intermolecular or intramolecular mixtures, sometimes in extremely complex formulations. The complexity is such that a good knowledge of the possible trends and an experienced practical know-how to avoid trial and error are important for the practitioner in enhanced oil recovery.

Magnetic Nanoparticle Thermometer: An Investigation of Minimum Error Transmission Path and AC Bias Error

PubMed Central

Du, Zhongzhou; Su, Rijian; Liu, Wenzhong; Huang, Zhixing

2015-01-01

The signal transmission module of a magnetic nanoparticle thermometer (MNPT) was established in this study to analyze the error sources introduced during the signal flow in the hardware system. The underlying error sources that significantly affected the precision of the MNPT were determined through mathematical modeling and simulation. A transfer module path with the minimum error in the hardware system was then proposed through the analysis of the variations of the system error caused by the significant error sources when the signal flew through the signal transmission module. In addition, a system parameter, named the signal-to-AC bias ratio (i.e., the ratio between the signal and AC bias), was identified as a direct determinant of the precision of the measured temperature. The temperature error was below 0.1 K when the signal-to-AC bias ratio was higher than 80 dB, and other system errors were not considered. The temperature error was below 0.1 K in the experiments with a commercial magnetic fluid (Sample SOR-10, Ocean Nanotechnology, Springdale, AR, USA) when the hardware system of the MNPT was designed with the aforementioned method. PMID:25875188

U.S. Maternally Linked Birth Records May Be Biased for Hispanics and Other Population Groups

PubMed Central

LEISS, JACK K.; GILES, DENISE; SULLIVAN, KRISTIN M.; MATHEWS, RAHEL; SENTELLE, GLENDA; TOMASHEK, KAY M.

2010-01-01

Purpose To advance understanding of linkage error in U.S. maternally linked datasets, and how the error may affect results of studies based on the linked data. Methods North Carolina birth and fetal death records for 1988-1997 were maternally linked (n=1,030,029). The maternal set probability, defined as the probability that all records assigned to the same maternal set do in fact represent events to the same woman, was used to assess differential maternal linkage error across race/ethnic groups. Results Maternal set probabilities were lower for records specifying Asian or Hispanic race/ethnicity, suggesting greater maternal linkage error. The lower probabilities for Hispanics were concentrated in women of Mexican origin who were not born in the United States. Conclusions Differential maternal linkage error may be a source of bias in studies using U.S. maternally linked datasets to make comparisons between Hispanics and other groups or among Hispanic subgroups. Methods to quantify and adjust for this potential bias are needed. PMID:20006273

On the error probability of general tree and trellis codes with applications to sequential decoding

NASA Technical Reports Server (NTRS)

Johannesson, R.

1973-01-01

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

LDPC Codes with Minimum Distance Proportional to Block Size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel; Thorpe, Jeremy

2009-01-01

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low error floors as well as low decoding thresholds. As an example, the illustration shows the protograph (which represents the blueprint for overall construction) of one proposed code family for code rates greater than or equal to 1.2. Any size LDPC code can be obtained by copying the protograph structure N times, then permuting the edges. The illustration also provides Field Programmable Gate Array (FPGA) hardware performance simulations for this code family. In addition, the illustration provides minimum signal-to-noise ratios (Eb/No) in decibels (decoding thresholds) to achieve zero error rates as the code block size goes to infinity for various code rates. In comparison with the codes mentioned in the preceding article, these codes have slightly higher decoding thresholds.

Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization.

PubMed

Ding, Jinliang; Chai, Tianyou; Wang, Hong

2011-03-01

This paper presents a novel offline modeling for product quality prediction of mineral processing which consists of a number of unit processes in series. The prediction of the product quality of the whole mineral process (i.e., the mixed concentrate grade) plays an important role and the establishment of its predictive model is a key issue for the plantwide optimization. For this purpose, a hybrid modeling approach of the mixed concentrate grade prediction is proposed, which consists of a linear model and a nonlinear model. The least-squares support vector machine is adopted to establish the nonlinear model. The inputs of the predictive model are the performance indices of each unit process, while the output is the mixed concentrate grade. In this paper, the model parameter selection is transformed into the shape control of the probability density function (PDF) of the modeling error. In this context, both the PDF-control-based and minimum-entropy-based model parameter selection approaches are proposed. Indeed, this is the first time that the PDF shape control idea is used to deal with system modeling, where the key idea is to turn model parameters so that either the modeling error PDF is controlled to follow a target PDF or the modeling error entropy is minimized. The experimental results using the real plant data and the comparison of the two approaches are discussed. The results show the effectiveness of the proposed approaches.

Error Patterns in Ordering Fractions among At-Risk Fourth-Grade Students

ERIC Educational Resources Information Center

Malone, Amelia Schneider; Fuchs, Lynn S.

2015-01-01

The 3 purposes of this study were to: (a) describe fraction ordering errors among at-risk 4th-grade students; (b) assess the effect of part-whole understanding and accuracy of fraction magnitude estimation on the probability of committing errors; and (c) examine the effect of students' ability to explain comparing problems on the probability of…

Image-adapted visually weighted quantization matrices for digital image compression

NASA Technical Reports Server (NTRS)

Watson, Andrew B. (Inventor)

1994-01-01

A method for performing image compression that eliminates redundant and invisible image components is presented. The image compression uses a Discrete Cosine Transform (DCT) and each DCT coefficient yielded by the transform is quantized by an entry in a quantization matrix which determines the perceived image quality and the bit rate of the image being compressed. The present invention adapts or customizes the quantization matrix to the image being compressed. The quantization matrix comprises visual masking by luminance and contrast techniques and by an error pooling technique all resulting in a minimum perceptual error for any given bit rate, or minimum bit rate for a given perceptual error.

A Method to Estimate the Probability That Any Individual Lightning Stroke Contacted the Surface Within Any Radius of Any Point

NASA Technical Reports Server (NTRS)

Huddleston, Lisa L.; Roeder, William; Merceret, Francis J.

2010-01-01

A technique has been developed to calculate the probability that any nearby lightning stroke is within any radius of any point of interest. In practice, this provides the probability that a nearby lightning stroke was within a key distance of a facility, rather than the error ellipses centered on the stroke. This process takes the current bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to get the probability that the stroke is inside any specified radius. This new facility-centric technique will be much more useful to the space launch customers and may supersede the lightning error ellipse approach discussed in [5], [6].

Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)

DTIC Science & Technology

2011-01-01

Minimum Error Bounded Efficient `1 Tracker with Occlusion Detection Xue Mei\\ ∗ Haibin Ling† Yi Wu†[ Erik Blasch‡ Li Bai] \\Assembly Test Technology...proposed BPR-L1 tracker is tested on several challenging benchmark sequences involving chal- lenges such as occlusion and illumination changes. In all...point method de - pends on the value of the regularization parameter λ. In the experiments, we found that the total number of PCG is a few hundred. The

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

The random coding bound is tight for the average code.

NASA Technical Reports Server (NTRS)

Gallager, R. G.

1973-01-01

The random coding bound of information theory provides a well-known upper bound to the probability of decoding error for the best code of a given rate and block length. The bound is constructed by upperbounding the average error probability over an ensemble of codes. The bound is known to give the correct exponential dependence of error probability on block length for transmission rates above the critical rate, but it gives an incorrect exponential dependence at rates below a second lower critical rate. Here we derive an asymptotic expression for the average error probability over the ensemble of codes used in the random coding bound. The result shows that the weakness of the random coding bound at rates below the second critical rate is due not to upperbounding the ensemble average, but rather to the fact that the best codes are much better than the average at low rates.

MO-FG-CAMPUS-TeP2-04: Optimizing for a Specified Target Coverage Probability

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

Fredriksson, A

2016-06-15

Purpose: The purpose of this work is to develop a method for inverse planning of radiation therapy margins. When using this method the user specifies a desired target coverage probability and the system optimizes to meet the demand without any explicit specification of margins to handle setup uncertainty. Methods: The method determines which voxels to include in an optimization function promoting target coverage in order to achieve a specified target coverage probability. Voxels are selected in a way that retains the correlation between them: The target is displaced according to the setup errors and the voxels to include are selectedmore » as the union of the displaced target regions under the x% best scenarios according to some quality measure. The quality measure could depend on the dose to the considered structure alone or could depend on the dose to multiple structures in order to take into account correlation between structures. Results: A target coverage function was applied to the CTV of a prostate case with prescription 78 Gy and compared to conventional planning using a DVH function on the PTV. Planning was performed to achieve 90% probability of CTV coverage. The plan optimized using the coverage probability function had P(D98 > 77.95 Gy) = 0.97 for the CTV. The PTV plan using a constraint on minimum DVH 78 Gy at 90% had P(D98 > 77.95) = 0.44 for the CTV. To match the coverage probability optimization, the DVH volume parameter had to be increased to 97% which resulted in 0.5 Gy higher average dose to the rectum. Conclusion: Optimizing a target coverage probability is an easily used method to find a margin that achieves the desired coverage probability. It can lead to reduced OAR doses at the same coverage probability compared to planning with margins and DVH functions.« less

75 FR 26780 - State Median Income Estimate for a Four-Person Family: Notice of the Federal Fiscal Year (FFY...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-12

... Household Economic Statistics Division at (301) 763-3243. Under the advice of the Census Bureau, HHS..., which consists of the error that arises from the use of probability sampling to create the sample. For...) Sampling Error, which consists of the error that arises from the use of probability sampling to create the...

A concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Kasami, T.; Fujiwara, T.; Lin, S.

1986-01-01

In this paper, a concatenated coding scheme for error control in data communications is presented and analyzed. In this scheme, the inner code is used for both error correction and detection; however, the outer code is used only for error detection. A retransmission is requested if either the inner code decoder fails to make a successful decoding or the outer code decoder detects the presence of errors after the inner code decoding. Probability of undetected error (or decoding error) of the proposed scheme is derived. An efficient method for computing this probability is presented. Throughput efficiency of the proposed error control scheme incorporated with a selective-repeat ARQ retransmission strategy is also analyzed. Three specific examples are presented. One of the examples is proposed for error control in the NASA Telecommand System.

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

A Framework of Covariance Projection on Constraint Manifold for Data Fusion.

PubMed

Bakr, Muhammad Abu; Lee, Sukhan

2018-05-17

A general framework of data fusion is presented based on projecting the probability distribution of true states and measurements around the predicted states and actual measurements onto the constraint manifold. The constraint manifold represents the constraints to be satisfied among true states and measurements, which is defined in the extended space with all the redundant sources of data such as state predictions and measurements considered as independent variables. By the general framework, we mean that it is able to fuse any correlated data sources while directly incorporating constraints and identifying inconsistent data without any prior information. The proposed method, referred to here as the Covariance Projection (CP) method, provides an unbiased and optimal solution in the sense of minimum mean square error (MMSE), if the projection is based on the minimum weighted distance on the constraint manifold. The proposed method not only offers a generalization of the conventional formula for handling constraints and data inconsistency, but also provides a new insight into data fusion in terms of a geometric-algebraic point of view. Simulation results are provided to show the effectiveness of the proposed method in handling constraints and data inconsistency.

Estimating Controller Intervention Probabilities for Optimized Profile Descent Arrivals

NASA Technical Reports Server (NTRS)

Meyn, Larry A.; Erzberger, Heinz; Huynh, Phu V.

2011-01-01

Simulations of arrival traffic at Dallas/Fort-Worth and Denver airports were conducted to evaluate incorporating scheduling and separation constraints into advisories that define continuous descent approaches. The goal was to reduce the number of controller interventions required to ensure flights maintain minimum separation distances of 5 nmi horizontally and 1000 ft vertically. It was shown that simply incorporating arrival meter fix crossing-time constraints into the advisory generation could eliminate over half of the all predicted separation violations and more than 80% of the predicted violations between two arrival flights. Predicted separation violations between arrivals and non-arrivals were 32% of all predicted separation violations at Denver and 41% at Dallas/Fort-Worth. A probabilistic analysis of meter fix crossing-time errors is included which shows that some controller interventions will still be required even when the predicted crossing-times of the advisories are set to add a 1 or 2 nmi buffer above the minimum in-trail separation of 5 nmi. The 2 nmi buffer was shown to increase average flight delays by up to 30 sec when compared to the 1 nmi buffer, but it only resulted in a maximum decrease in average arrival throughput of one flight per hour.

Stitching-error reduction in gratings by shot-shifted electron-beam lithography

NASA Technical Reports Server (NTRS)

Dougherty, D. J.; Muller, R. E.; Maker, P. D.; Forouhar, S.

2001-01-01

Calculations of the grating spatial-frequency spectrum and the filtering properties of multiple-pass electron-beam writing demonstrate a tradeoff between stitching-error suppression and minimum pitch separation. High-resolution measurements of optical-diffraction patterns show a 25-dB reduction in stitching-error side modes.

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

Treesearch

Bernard R. Parresol

1993-01-01

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

Invariance of the bit error rate in the ancilla-assisted homodyne detection

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

Yoshida, Yuhsuke; Takeoka, Masahiro; Sasaki, Masahide

2010-11-15

We investigate the minimum achievable bit error rate of the discrimination of binary coherent states with the help of arbitrary ancillary states. We adopt homodyne measurement with a common phase of the local oscillator and classical feedforward control. After one ancillary state is measured, its outcome is referred to the preparation of the next ancillary state and the tuning of the next mixing with the signal. It is shown that the minimum bit error rate of the system is invariant under the following operations: feedforward control, deformations, and introduction of any ancillary state. We also discuss the possible generalization ofmore » the homodyne detection scheme.« less

Performance analysis of the word synchronization properties of the outer code in a TDRSS decoder

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.

1984-01-01

A self-synchronizing coding scheme for NASA's TDRSS satellite system is a concatenation of a (2,1,7) inner convolutional code with a (255,223) Reed-Solomon outer code. Both symbol and word synchronization are achieved without requiring that any additional symbols be transmitted. An important parameter which determines the performance of the word sync procedure is the ratio of the decoding failure probability to the undetected error probability. Ideally, the former should be as small as possible compared to the latter when the error correcting capability of the code is exceeded. A computer simulation of a (255,223) Reed-Solomon code as carried out. Results for decoding failure probability and for undetected error probability are tabulated and compared.

Fundamental Physical Limits for the Size of Future Planetary Surface Exploration Systems

NASA Astrophysics Data System (ADS)

Andrews, F.; Hobbs, S. E.; Honstvet, I.; Snelling, M.

2004-04-01

With the current interest in the potential use of Nanotechnology for spacecraft, it becomes increasingly likely that environmental sensor probes, such as the "lab-on-a-chip" concept, will take advantage of this technology and become orders of magnitude smaller than current sensor systems. This paper begins to investigate how small these systems could theoretically become, and what are the governing laws and limiting factors that determine that minimum size. The investigation focuses on the three primary subsystems for a sensor network of this nature Sensing, Information Processing and Communication. In general, there are few fundamental physical laws that limit the size of the sensor system. Limits tend to be driven by factors other than the laws of physics. These include user requirements, such as the acceptable probability of error, and the potential external environment.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

PubMed

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

Stochastic reservoir simulation for the modeling of uncertainty in coal seam degasification

USGS Publications Warehouse

Karacan, C. Özgen; Olea, Ricardo A.

2015-01-01

The study helped to determine the realization bundle that consisted of the spatial maps of coal properties, which resulted in minimum error. In addition, it was shown that both E-type and the average of realizations that gave the best match for invidual approximated the same properties resonably. Moreover, the determined realization bundle showed that the study field initially had 151.5 million m3 (cubic meter) of gas and 1.04 million m3 water in the coal, corresponding to Q90 of the entire range of probability for gas and close to Q75 for water. In 2013, in-place fluid amounts decreased to 138.9 million m3 and 0.997 million m3 for gas and water, respectively.

Transferring Error Characteristics of Satellite Rainfall Data from Ground Validation (gauged) into Non-ground Validation (ungauged)

NASA Astrophysics Data System (ADS)

Tang, L.; Hossain, F.

2009-12-01

Understanding the error characteristics of satellite rainfall data at different spatial/temporal scales is critical, especially when the scheduled Global Precipitation Mission (GPM) plans to provide High Resolution Precipitation Products (HRPPs) at global scales. Satellite rainfall data contain errors which need ground validation (GV) data for characterization, while satellite rainfall data will be most useful in the regions that are lacking in GV. Therefore, a critical step is to develop a spatial interpolation scheme for transferring the error characteristics of satellite rainfall data from GV regions to Non-GV regions. As a prelude to GPM, The TRMM Multi-satellite Precipitation Analysis (TMPA) products of 3B41RT and 3B42RT (Huffman et al., 2007) over the US spanning a record of 6 years are used as a representative example of satellite rainfall data. Next Generation Radar (NEXRAD) Stage IV rainfall data are used as the reference for GV data. Initial work by the authors (Tang et al., 2009, GRL) has shown promise in transferring error from GV to Non-GV regions, based on a six-year climatologic average of satellite rainfall data assuming only 50% of GV coverage. However, this transfer of error characteristics needs to be investigated for a range of GV data coverage. In addition, it is also important to investigate if proxy-GV data from an accurate space-borne sensor, such as the TRMM PR (or the GPM DPR), can be leveraged for the transfer of error at sparsely gauged regions. The specific question we ask in this study is, “what is the minimum coverage of GV data required for error transfer scheme to be implemented at acceptable accuracy in hydrological relevant scale?” Three geostatistical interpolation methods are compared: ordinary kriging, indicator kriging and disjunctive kriging. Various error metrics are assessed for transfer such as, Probability of Detection for rain and no rain, False Alarm Ratio, Frequency Bias, Critical Success Index, RMSE etc. Understanding the proper space-time scales at which these metrics can be reasonably transferred is also explored in this study. Keyword: Satellite rainfall, error transfer, spatial interpolation, kriging methods.

Statistical analysis of nonlinearly reconstructed near-infrared tomographic images: Part I--Theory and simulations.

PubMed

Pogue, Brian W; Song, Xiaomei; Tosteson, Tor D; McBride, Troy O; Jiang, Shudong; Paulsen, Keith D

2002-07-01

Near-infrared (NIR) diffuse tomography is an emerging method for imaging the interior of tissues to quantify concentrations of hemoglobin and exogenous chromophores non-invasively in vivo. It often exploits an optical diffusion model-based image reconstruction algorithm to estimate spatial property values from measurements of the light flux at the surface of the tissue. In this study, mean-squared error (MSE) over the image is used to evaluate methods for regularizing the ill-posed inverse image reconstruction problem in NIR tomography. Estimates of image bias and image standard deviation were calculated based upon 100 repeated reconstructions of a test image with randomly distributed noise added to the light flux measurements. It was observed that the bias error dominates at high regularization parameter values while variance dominates as the algorithm is allowed to approach the optimal solution. This optimum does not necessarily correspond to the minimum projection error solution, but typically requires further iteration with a decreasing regularization parameter to reach the lowest image error. Increasing measurement noise causes a need to constrain the minimum regularization parameter to higher values in order to achieve a minimum in the overall image MSE.

Analysis of the impact of error detection on computer performance

NASA Technical Reports Server (NTRS)

Shin, K. C.; Lee, Y. H.

1983-01-01

Conventionally, reliability analyses either assume that a fault/error is detected immediately following its occurrence, or neglect damages caused by latent errors. Though unrealistic, this assumption was imposed in order to avoid the difficulty of determining the respective probabilities that a fault induces an error and the error is then detected in a random amount of time after its occurrence. As a remedy for this problem a model is proposed to analyze the impact of error detection on computer performance under moderate assumptions. Error latency, the time interval between occurrence and the moment of detection, is used to measure the effectiveness of a detection mechanism. This model is used to: (1) predict the probability of producing an unreliable result, and (2) estimate the loss of computation due to fault and/or error.

Triangulation Error Analysis for the Barium Ion Cloud Experiment. M.S. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Long, S. A. T.

1973-01-01

The triangulation method developed specifically for the Barium Ion Cloud Project is discussed. Expression for the four displacement errors, the three slope errors, and the curvature error in the triangulation solution due to a probable error in the lines-of-sight from the observation stations to points on the cloud are derived. The triangulation method is then used to determine the effect of the following on these different errors in the solution: the number and location of the stations, the observation duration, east-west cloud drift, the number of input data points, and the addition of extra cameras to one of the stations. The pointing displacement errors, and the pointing slope errors are compared. The displacement errors in the solution due to a probable error in the position of a moving station plus the weighting factors for the data from the moving station are also determined.

Radial orbit error reduction and sea surface topography determination using satellite altimetry

NASA Technical Reports Server (NTRS)

Engelis, Theodossios

1987-01-01

A method is presented in satellite altimetry that attempts to simultaneously determine the geoid and sea surface topography with minimum wavelengths of about 500 km and to reduce the radial orbit error caused by geopotential errors. The modeling of the radial orbit error is made using the linearized Lagrangian perturbation theory. Secular and second order effects are also included. After a rather extensive validation of the linearized equations, alternative expressions of the radial orbit error are derived. Numerical estimates for the radial orbit error and geoid undulation error are computed using the differences of two geopotential models as potential coefficient errors, for a SEASAT orbit. To provide statistical estimates of the radial distances and the geoid, a covariance propagation is made based on the full geopotential covariance. Accuracy estimates for the SEASAT orbits are given which agree quite well with already published results. Observation equations are develped using sea surface heights and crossover discrepancies as observables. A minimum variance solution with prior information provides estimates of parameters representing the sea surface topography and corrections to the gravity field that is used for the orbit generation. The simulation results show that the method can be used to effectively reduce the radial orbit error and recover the sea surface topography.

Force and Directional Force Modulation Effects on Accuracy and Variability in Low-Level Pinch Force Tracking.

PubMed

Park, Sangsoo; Spirduso, Waneen; Eakin, Tim; Abraham, Lawrence

2018-01-01

The authors investigated how varying the required low-level forces and the direction of force change affect accuracy and variability of force production in a cyclic isometric pinch force tracking task. Eighteen healthy right-handed adult volunteers performed the tracking task over 3 different force ranges. Root mean square error and coefficient of variation were higher at lower force levels and during minimum reversals compared with maximum reversals. Overall, the thumb showed greater root mean square error and coefficient of variation scores than did the index finger during maximum reversals, but not during minimum reversals. The observed impaired performance during minimum reversals might originate from history-dependent mechanisms of force production and highly coupled 2-digit performance.

Validation of the Kp Geomagnetic Index Forecast at CCMC

NASA Astrophysics Data System (ADS)

Frechette, B. P.; Mays, M. L.

2017-12-01

The Community Coordinated Modeling Center (CCMC) Space Weather Research Center (SWRC) sub-team provides space weather services to NASA robotic mission operators and science campaigns and prototypes new models, forecasting techniques, and procedures. The Kp index is a measure of geomagnetic disturbances for space weather in the magnetosphere such as geomagnetic storms and substorms. In this study, we performed validation on the Newell et al. (2007) Kp prediction equation from December 2010 to July 2017. The purpose of this research is to understand the Kp forecast performance because it's critical for NASA missions to have confidence in the space weather forecast. This research was done by computing the Kp error for each forecast (average, minimum, maximum) and each synoptic period. Then to quantify forecast performance we computed the mean error, mean absolute error, root mean square error, multiplicative bias and correlation coefficient. A contingency table was made for each forecast and skill scores were computed. The results are compared to the perfect score and reference forecast skill score. In conclusion, the skill score and error results show that the minimum of the predicted Kp over each synoptic period from the Newell et al. (2007) Kp prediction equation performed better than the maximum or average of the prediction. However, persistence (reference forecast) outperformed all of the Kp forecasts (minimum, maximum, and average). Overall, the Newell Kp prediction still predicts within a range of 1, even though persistence beats it.

Support Minimized Inversion of Acoustic and Elastic Wave Scattering

NASA Astrophysics Data System (ADS)

Safaeinili, Ali

Inversion of limited data is common in many areas of NDE such as X-ray Computed Tomography (CT), Ultrasonic and eddy current flaw characterization and imaging. In many applications, it is common to have a bias toward a solution with minimum (L^2)^2 norm without any physical justification. When it is a priori known that objects are compact as, say, with cracks and voids, by choosing "Minimum Support" functional instead of the minimum (L^2)^2 norm, an image can be obtained that is equally in agreement with the available data, while it is more consistent with what is most probably seen in the real world. We have utilized a minimum support functional to find a solution with the smallest volume. This inversion algorithm is most successful in reconstructing objects that are compact like voids and cracks. To verify this idea, we first performed a variational nonlinear inversion of acoustic backscatter data using minimum support objective function. A full nonlinear forward model was used to accurately study the effectiveness of the minimized support inversion without error due to the linear (Born) approximation. After successful inversions using a full nonlinear forward model, a linearized acoustic inversion was developed to increase speed and efficiency in imaging process. The results indicate that by using minimum support functional, we can accurately size and characterize voids and/or cracks which otherwise might be uncharacterizable. An extremely important feature of support minimized inversion is its ability to compensate for unknown absolute phase (zero-of-time). Zero-of-time ambiguity is a serious problem in the inversion of the pulse-echo data. The minimum support inversion was successfully used for the inversion of acoustic backscatter data due to compact scatterers without the knowledge of the zero-of-time. The main drawback to this type of inversion is its computer intensiveness. In order to make this type of constrained inversion available for common use, work needs to be performed in three areas: (1) exploitation of state-of-the-art parallel computation, (2) improvement of theoretical formulation of the scattering process for better computation efficiency, and (3) development of better methods for guiding the non-linear inversion. (Abstract shortened by UMI.).

Performance of cellular frequency-hopped spread-spectrum radio networks

NASA Astrophysics Data System (ADS)

Gluck, Jeffrey W.; Geraniotis, Evaggelos

1989-10-01

Multiple access interference is characterized for cellular mobile networks, in which users are assumed to be Poisson-distributed in the plane and employ frequency-hopped spread-spectrum signaling with transmitter-oriented assignment of frequency-hopping patterns. Exact expressions for the bit error probabilities are derived for binary coherently demodulated systems without coding. Approximations for the packet error probability are derived for coherent and noncoherent systems and these approximations are applied when forward-error-control coding is employed. In all cases, the effects of varying interference power are accurately taken into account according to some propagation law. Numerical results are given in terms of bit error probability for the exact case and throughput for the approximate analyses. Comparisons are made with previously derived bounds and it is shown that these tend to be very pessimistic.

Comparison of rate one-half, equivalent constraint length 24, binary convolutional codes for use with sequential decoding on the deep-space channel

NASA Technical Reports Server (NTRS)

Massey, J. L.

1976-01-01

Virtually all previously-suggested rate 1/2 binary convolutional codes with KE = 24 are compared. Their distance properties are given; and their performance, both in computation and in error probability, with sequential decoding on the deep-space channel is determined by simulation. Recommendations are made both for the choice of a specific KE = 24 code as well as for codes to be included in future coding standards for the deep-space channel. A new result given in this report is a method for determining the statistical significance of error probability data when the error probability is so small that it is not feasible to perform enough decoding simulations to obtain more than a very small number of decoding errors.

Effects of Phasor Measurement Uncertainty on Power Line Outage Detection

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

Chen, Chen; Wang, Jianhui; Zhu, Hao

2014-12-01

Phasor measurement unit (PMU) technology provides an effective tool to enhance the wide-area monitoring systems (WAMSs) in power grids. Although extensive studies have been conducted to develop several PMU applications in power systems (e.g., state estimation, oscillation detection and control, voltage stability analysis, and line outage detection), the uncertainty aspects of PMUs have not been adequately investigated. This paper focuses on quantifying the impact of PMU uncertainty on power line outage detection and identification, in which a limited number of PMUs installed at a subset of buses are utilized to detect and identify the line outage events. Specifically, the linemore » outage detection problem is formulated as a multi-hypothesis test, and a general Bayesian criterion is used for the detection procedure, in which the PMU uncertainty is analytically characterized. We further apply the minimum detection error criterion for the multi-hypothesis test and derive the expected detection error probability in terms of PMU uncertainty. The framework proposed provides fundamental guidance for quantifying the effects of PMU uncertainty on power line outage detection. Case studies are provided to validate our analysis and show how PMU uncertainty influences power line outage detection.« less

Refined energetic ordering for sulphate-water (n = 3-6) clusters using high-level electronic structure calculations

NASA Astrophysics Data System (ADS)

Lambrecht, Daniel S.; McCaslin, Laura; Xantheas, Sotiris S.; Epifanovsky, Evgeny; Head-Gordon, Martin

2012-10-01

This work reports refinements of the energetic ordering of the known low-energy structures of sulphate-water clusters ? (n = 3-6) using high-level electronic structure methods. Coupled cluster singles and doubles with perturbative triples (CCSD(T)) is used in combination with an estimate of basis set effects up to the complete basis set limit using second-order Møller-Plesset theory. Harmonic zero-point energy (ZPE), included at the B3LYP/6-311 + + G(3df,3pd) level, was found to have a significant effect on the energetic ordering. In fact, we show that the energetic ordering is a result of a delicate balance between the electronic and vibrational energies. Limitations of the ZPE calculations, both due to electronic structure errors, and use of the harmonic approximation, probably constitute the largest remaining errors. Due to the often small energy differences between cluster isomers, and the significant role of ZPE, deuteration can alter the relative energies of low-lying structures, and, when it is applied in conjunction with calculated harmonic ZPEs, even alters the global minimum for n = 5. Experiments on deuterated clusters, as well as more sophisticated vibrational calculations, may therefore be quite interesting.

Robust Rate Maximization for Heterogeneous Wireless Networks under Channel Uncertainties

PubMed Central

Xu, Yongjun; Hu, Yuan; Li, Guoquan

2018-01-01

Heterogeneous wireless networks are a promising technology in next generation wireless communication networks, which has been shown to efficiently reduce the blind area of mobile communication and improve network coverage compared with the traditional wireless communication networks. In this paper, a robust power allocation problem for a two-tier heterogeneous wireless networks is formulated based on orthogonal frequency-division multiplexing technology. Under the consideration of imperfect channel state information (CSI), the robust sum-rate maximization problem is built while avoiding sever cross-tier interference to macrocell user and maintaining the minimum rate requirement of each femtocell user. To be practical, both of channel estimation errors from the femtocells to the macrocell and link uncertainties of each femtocell user are simultaneously considered in terms of outage probabilities of users. The optimization problem is analyzed under no CSI feedback with some cumulative distribution function and partial CSI with Gaussian distribution of channel estimation error. The robust optimization problem is converted into the convex optimization problem which is solved by using Lagrange dual theory and subgradient algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm by the impact of channel uncertainties on the system performance. PMID:29466315

Stack Number Influence on the Accuracy of Aster Gdem (V2)

NASA Astrophysics Data System (ADS)

Mirzadeh, S. M. J.; Alizadeh Naeini, A.; Fatemi, S. B.

2017-09-01

In this research, the influence of stack number (STKN) on the accuracy of Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM (GDEM) has been investigated. For this purpose, two data sets of ASTER and Reference DEMs from two study areas with various topography (Bomehen and Tazehabad) were used. The Results show that in both study areas, STKN of 19 results in minimum error so that this minimum error has small difference with other STKN. The analysis of slope, STKN, and error values shows that there is no strong correlation between these parameters in both study areas. For example, the value of mean absolute error increase by changing the topography and the increase of slope values and height on cells but, the changes in STKN has no important effect on error values. Furthermore, according to high values of STKN, effect of slope on elevation accuracy has practically decreased. Also, there is no great correlation between the residual and STKN in ASTER GDEM.

Characterization of the International Linear Collider damping ring optics

NASA Astrophysics Data System (ADS)

Shanks, J.; Rubin, D. L.; Sagan, D.

2014-10-01

A method is presented for characterizing the emittance dilution and dynamic aperture for an arbitrary closed lattice that includes guide field magnet errors, multipole errors and misalignments. This method, developed and tested at the Cornell Electron Storage Ring Test Accelerator (CesrTA), has been applied to the damping ring lattice for the International Linear Collider (ILC). The effectiveness of beam based emittance tuning is limited by beam position monitor (BPM) measurement errors, number of corrector magnets and their placement, and correction algorithm. The specifications for damping ring magnet alignment, multipole errors, number of BPMs, and precision in BPM measurements are shown to be consistent with the required emittances and dynamic aperture. The methodology is then used to determine the minimum number of position monitors that is required to achieve the emittance targets, and how that minimum depends on the location of the BPMs. Similarly, the maximum tolerable multipole errors are evaluated. Finally, the robustness of each BPM configuration with respect to random failures is explored.

Bayesian network models for error detection in radiotherapy plans

NASA Astrophysics Data System (ADS)

Kalet, Alan M.; Gennari, John H.; Ford, Eric C.; Phillips, Mark H.

2015-04-01

The purpose of this study is to design and develop a probabilistic network for detecting errors in radiotherapy plans for use at the time of initial plan verification. Our group has initiated a multi-pronged approach to reduce these errors. We report on our development of Bayesian models of radiotherapy plans. Bayesian networks consist of joint probability distributions that define the probability of one event, given some set of other known information. Using the networks, we find the probability of obtaining certain radiotherapy parameters, given a set of initial clinical information. A low probability in a propagated network then corresponds to potential errors to be flagged for investigation. To build our networks we first interviewed medical physicists and other domain experts to identify the relevant radiotherapy concepts and their associated interdependencies and to construct a network topology. Next, to populate the network’s conditional probability tables, we used the Hugin Expert software to learn parameter distributions from a subset of de-identified data derived from a radiation oncology based clinical information database system. These data represent 4990 unique prescription cases over a 5 year period. Under test case scenarios with approximately 1.5% introduced error rates, network performance produced areas under the ROC curve of 0.88, 0.98, and 0.89 for the lung, brain and female breast cancer error detection networks, respectively. Comparison of the brain network to human experts performance (AUC of 0.90 ± 0.01) shows the Bayes network model performs better than domain experts under the same test conditions. Our results demonstrate the feasibility and effectiveness of comprehensive probabilistic models as part of decision support systems for improved detection of errors in initial radiotherapy plan verification procedures.

Inverse and forward modeling under uncertainty using MRE-based Bayesian approach

NASA Astrophysics Data System (ADS)

Hou, Z.; Rubin, Y.

2004-12-01

A stochastic inverse approach for subsurface characterization is proposed and applied to shallow vadose zone at a winery field site in north California and to a gas reservoir at the Ormen Lange field site in the North Sea. The approach is formulated in a Bayesian-stochastic framework, whereby the unknown parameters are identified in terms of their statistical moments or their probabilities. Instead of the traditional single-valued estimation /prediction provided by deterministic methods, the approach gives a probability distribution for an unknown parameter. This allows calculating the mean, the mode, and the confidence interval, which is useful for a rational treatment of uncertainty and its consequences. The approach also allows incorporating data of various types and different error levels, including measurements of state variables as well as information such as bounds on or statistical moments of the unknown parameters, which may represent prior information. To obtain minimally subjective prior probabilities required for the Bayesian approach, the principle of Minimum Relative Entropy (MRE) is employed. The approach is tested in field sites for flow parameters identification and soil moisture estimation in the vadose zone and for gas saturation estimation at great depth below the ocean floor. Results indicate the potential of coupling various types of field data within a MRE-based Bayesian formalism for improving the estimation of the parameters of interest.

Predicting the Earth encounters of (99942) Apophis

NASA Technical Reports Server (NTRS)

Giorgini, Jon D.; Benner, Lance A. M.; Ostro, Steven J.; Nolan, Michael C.; Busch, Michael W.

2007-01-01

Arecibo delay-Doppler measurements of (99942) Apophis in 2005 and 2006 resulted in a five standard-deviation trajectory correction to the optically predicted close approach distance to Earth in 2029. The radar measurements reduced the volume of the statistical uncertainty region entering the encounter to 7.3% of the pre-radar solution, but increased the trajectory uncertainty growth rate across the encounter by 800% due to the closer predicted approach to the Earth. A small estimated Earth impact probability remained for 2036. With standard-deviation plane-of-sky position uncertainties for 2007-2010 already less than 0.2 arcsec, the best near-term ground-based optical astrometry can only weakly affect the trajectory estimate. While the potential for impact in 2036 will likely be excluded in 2013 (if not 2011) using ground-based optical measurements, approximations within the Standard Dynamical Model (SDM) used to estimate and predict the trajectory from the current era are sufficient to obscure the difference between a predicted impact and a miss in 2036 by altering the dynamics leading into the 2029 encounter. Normal impact probability assessments based on the SDM become problematic without knowledge of the object's physical properties; impact could be excluded while the actual dynamics still permit it. Calibrated position uncertainty intervals are developed to compensate for this by characterizing the minimum and maximum effect of physical parameters on the trajectory. Uncertainty in accelerations related to solar radiation can cause between 82 and 4720 Earth-radii of trajectory change relative to the SDM by 2036. If an actionable hazard exists, alteration by 2-10% of Apophis' total absorption of solar radiation in 2018 could be sufficient to produce a six standard-deviation trajectory change by 2036 given physical characterization; even a 0.5% change could produce a trajectory shift of one Earth-radius by 2036 for all possible spin-poles and likely masses. Planetary ephemeris uncertainties are the next greatest source of systematic error, causing up to 23 Earth-radii of uncertainty. The SDM Earth point-mass assumption introduces an additional 2.9 Earth-radii of prediction error by 2036. Unmodeled asteroid perturbations produce as much as 2.3 Earth-radii of error. We find no future small-body encounters likely to yield an Apophis mass determination prior to 2029. However, asteroid (144898) 2004 VD17, itself having a statistical Earth impact in 2102, will probably encounter Apophis at 6.7 lunar distances in 2034, their uncertainty regions coming as close as 1.6 lunar distances near the center of both SDM probability distributions.

Simplified Approach Charts Improve Data Retrieval Performance

PubMed Central

Stewart, Michael; Laraway, Sean; Jordan, Kevin; Feary, Michael S.

2016-01-01

The effectiveness of different instrument approach charts to deliver minimum visibility and altitude information during airport equipment outages was investigated. Eighteen pilots flew simulated instrument approaches in three conditions: (a) normal operations using a standard approach chart (standard-normal), (b) equipment outage conditions using a standard approach chart (standard-outage), and (c) equipment outage conditions using a prototype decluttered approach chart (prototype-outage). Errors and retrieval times in identifying minimum altitudes and visibilities were measured. The standard-outage condition produced significantly more errors and longer retrieval times versus the standard-normal condition. The prototype-outage condition had significantly fewer errors and shorter retrieval times than did the standard-outage condition. The prototype-outage condition produced significantly fewer errors but similar retrieval times when compared with the standard-normal condition. Thus, changing the presentation of minima may reduce risk and increase safety in instrument approaches, specifically with airport equipment outages. PMID:28491009

Wald Sequential Probability Ratio Test for Analysis of Orbital Conjunction Data

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Markley, F. Landis; Gold, Dara

2013-01-01

We propose a Wald Sequential Probability Ratio Test for analysis of commonly available predictions associated with spacecraft conjunctions. Such predictions generally consist of a relative state and relative state error covariance at the time of closest approach, under the assumption that prediction errors are Gaussian. We show that under these circumstances, the likelihood ratio of the Wald test reduces to an especially simple form, involving the current best estimate of collision probability, and a similar estimate of collision probability that is based on prior assumptions about the likelihood of collision.

Optimal plane search method in blood flow measurements by magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Bargiel, Pawel; Orkisz, Maciej; Przelaskowski, Artur; Piatkowska-Janko, Ewa; Bogorodzki, Piotr; Wolak, Tomasz

2004-07-01

This paper offers an algorithm for determining the blood flow parameters in the neck vessel segments using a single (optimal) measurement plane instead of the usual approach involving four planes orthogonal to the artery axis. This new approach aims at significantly shortening the time required to complete measurements using Nuclear Magnetic Resonance techniques. Based on a defined error function, the algorithm scans the solution space to find the minimum of the error function, and thus to determine a single plane characterized by a minimum measurement error, which allows for an accurate measurement of blood flow in the four carotid arteries. The paper also comprises a practical implementation of this method (as a module of a larger imaging-measuring system), including preliminary research results.

Hydrologic characterization of desert soils with varying degrees of pedogenesis: 2. Inverse modeling for eff ective properties

USGS Publications Warehouse

Mirus, B.B.; Perkins, K.S.; Nimmo, J.R.; Singha, K.

2009-01-01

To understand their relation to pedogenic development, soil hydraulic properties in the Mojave Desert were investi- gated for three deposit types: (i) recently deposited sediments in an active wash, (ii) a soil of early Holocene age, and (iii) a highly developed soil of late Pleistocene age. Eff ective parameter values were estimated for a simplifi ed model based on Richards' equation using a fl ow simulator (VS2D), an inverse algorithm (UCODE-2005), and matric pressure and water content data from three ponded infi ltration experiments. The inverse problem framework was designed to account for the eff ects of subsurface lateral spreading of infi ltrated water. Although none of the inverse problems converged on a unique, best-fi t parameter set, a minimum standard error of regression was reached for each deposit type. Parameter sets from the numerous inversions that reached the minimum error were used to develop probability distribu tions for each parameter and deposit type. Electrical resistance imaging obtained for two of the three infi ltration experiments was used to independently test fl ow model performance. Simulations for the active wash and Holocene soil successfully depicted the lateral and vertical fl uxes. Simulations of the more pedogenically developed Pleistocene soil did not adequately replicate the observed fl ow processes, which would require a more complex conceptual model to include smaller scale heterogeneities. The inverse-modeling results, however, indicate that with increasing age, the steep slope of the soil water retention curve shitis toward more negative matric pressures. Assigning eff ective soil hydraulic properties based on soil age provides a promising framework for future development of regional-scale models of soil moisture dynamics in arid environments for land-management applications. ?? Soil Science Society of America.

Weighted Fuzzy Risk Priority Number Evaluation of Turbine and Compressor Blades Considering Failure Mode Correlations

NASA Astrophysics Data System (ADS)

Gan, Luping; Li, Yan-Feng; Zhu, Shun-Peng; Yang, Yuan-Jian; Huang, Hong-Zhong

2014-06-01

Failure mode, effects and criticality analysis (FMECA) and Fault tree analysis (FTA) are powerful tools to evaluate reliability of systems. Although single failure mode issue can be efficiently addressed by traditional FMECA, multiple failure modes and component correlations in complex systems cannot be effectively evaluated. In addition, correlated variables and parameters are often assumed to be precisely known in quantitative analysis. In fact, due to the lack of information, epistemic uncertainty commonly exists in engineering design. To solve these problems, the advantages of FMECA, FTA, fuzzy theory, and Copula theory are integrated into a unified hybrid method called fuzzy probability weighted geometric mean (FPWGM) risk priority number (RPN) method. The epistemic uncertainty of risk variables and parameters are characterized by fuzzy number to obtain fuzzy weighted geometric mean (FWGM) RPN for single failure mode. Multiple failure modes are connected using minimum cut sets (MCS), and Boolean logic is used to combine fuzzy risk priority number (FRPN) of each MCS. Moreover, Copula theory is applied to analyze the correlation of multiple failure modes in order to derive the failure probabilities of each MCS. Compared to the case where dependency among multiple failure modes is not considered, the Copula modeling approach eliminates the error of reliability analysis. Furthermore, for purpose of quantitative analysis, probabilities importance weight from failure probabilities are assigned to FWGM RPN to reassess the risk priority, which generalize the definition of probability weight and FRPN, resulting in a more accurate estimation than that of the traditional models. Finally, a basic fatigue analysis case drawn from turbine and compressor blades in aeroengine is used to demonstrate the effectiveness and robustness of the presented method. The result provides some important insights on fatigue reliability analysis and risk priority assessment of structural system under failure correlations.

Autonomous learning derived from experimental modeling of physical laws.

PubMed

Grabec, Igor

2013-05-01

This article deals with experimental description of physical laws by probability density function of measured data. The Gaussian mixture model specified by representative data and related probabilities is utilized for this purpose. The information cost function of the model is described in terms of information entropy by the sum of the estimation error and redundancy. A new method is proposed for searching the minimum of the cost function. The number of the resulting prototype data depends on the accuracy of measurement. Their adaptation resembles a self-organized, highly non-linear cooperation between neurons in an artificial NN. A prototype datum corresponds to the memorized content, while the related probability corresponds to the excitability of the neuron. The method does not include any free parameters except objectively determined accuracy of the measurement system and is therefore convenient for autonomous execution. Since representative data are generally less numerous than the measured ones, the method is applicable for a rather general and objective compression of overwhelming experimental data in automatic data-acquisition systems. Such compression is demonstrated on analytically determined random noise and measured traffic flow data. The flow over a day is described by a vector of 24 components. The set of 365 vectors measured over one year is compressed by autonomous learning to just 4 representative vectors and related probabilities. These vectors represent the flow in normal working days and weekends or holidays, while the related probabilities correspond to relative frequencies of these days. This example reveals that autonomous learning yields a new basis for interpretation of representative data and the optimal model structure. Copyright © 2012 Elsevier Ltd. All rights reserved.

45 CFR 286.205 - How will we determine if a Tribe fails to meet the minimum work participation rate(s)?

Code of Federal Regulations, 2012 CFR

2012-10-01

..., financial records, and automated data systems; (ii) The data are free from computational errors and are... records, financial records, and automated data systems; (ii) The data are free from computational errors... records, and automated data systems; (ii) The data are free from computational errors and are internally...

Probabilistic performance estimators for computational chemistry methods: The empirical cumulative distribution function of absolute errors

NASA Astrophysics Data System (ADS)

Pernot, Pascal; Savin, Andreas

2018-06-01

Benchmarking studies in computational chemistry use reference datasets to assess the accuracy of a method through error statistics. The commonly used error statistics, such as the mean signed and mean unsigned errors, do not inform end-users on the expected amplitude of prediction errors attached to these methods. We show that, the distributions of model errors being neither normal nor zero-centered, these error statistics cannot be used to infer prediction error probabilities. To overcome this limitation, we advocate for the use of more informative statistics, based on the empirical cumulative distribution function of unsigned errors, namely, (1) the probability for a new calculation to have an absolute error below a chosen threshold and (2) the maximal amplitude of errors one can expect with a chosen high confidence level. Those statistics are also shown to be well suited for benchmarking and ranking studies. Moreover, the standard error on all benchmarking statistics depends on the size of the reference dataset. Systematic publication of these standard errors would be very helpful to assess the statistical reliability of benchmarking conclusions.

Generalizing boundaries for triangular designs, and efficacy estimation at extended follow-ups.

PubMed

Allison, Annabel; Edwards, Tansy; Omollo, Raymond; Alves, Fabiana; Magirr, Dominic; E Alexander, Neal D

2015-11-16

Visceral leishmaniasis (VL) is a parasitic disease transmitted by sandflies and is fatal if left untreated. Phase II trials of new treatment regimens for VL are primarily carried out to evaluate safety and efficacy, while pharmacokinetic data are also important to inform future combination treatment regimens. The efficacy of VL treatments is evaluated at two time points, initial cure, when treatment is completed and definitive cure, commonly 6 months post end of treatment, to allow for slow response to treatment and detection of relapses. This paper investigates a generalization of the triangular design to impose a minimum sample size for pharmacokinetic or other analyses, and methods to estimate efficacy at extended follow-up accounting for the sequential design and changes in cure status during extended follow-up. We provided R functions that generalize the triangular design to impose a minimum sample size before allowing stopping for efficacy. For estimation of efficacy at a second, extended, follow-up time, the performance of a shrinkage estimator (SHE), a probability tree estimator (PTE) and the maximum likelihood estimator (MLE) for estimation was assessed by simulation. The SHE and PTE are viable approaches to estimate an extended follow-up although the SHE performed better than the PTE: the bias and root mean square error were lower and coverage probabilities higher. Generalization of the triangular design is simple to implement for adaptations to meet requirements for pharmacokinetic analyses. Using the simple MLE approach to estimate efficacy at extended follow-up will lead to biased results, generally over-estimating treatment success. The SHE is recommended in trials of two or more treatments. The PTE is an acceptable alternative for one-arm trials or where use of the SHE is not possible due to computational complexity. NCT01067443 , February 2010.

Enhancing interferometer phase estimation, sensing sensitivity, and resolution using robust entangled states

NASA Astrophysics Data System (ADS)

Smith, James F.

2017-11-01

With the goal of designing interferometers and interferometer sensors, e.g., LADARs with enhanced sensitivity, resolution, and phase estimation, states using quantum entanglement are discussed. These states include N00N states, plain M and M states (PMMSs), and linear combinations of M and M states (LCMMS). Closed form expressions for the optimal detection operators; visibility, a measure of the state's robustness to loss and noise; a resolution measure; and phase estimate error, are provided in closed form. The optimal resolution for the maximum visibility and minimum phase error are found. For the visibility, comparisons between PMMSs, LCMMS, and N00N states are provided. For the minimum phase error, comparisons between LCMMS, PMMSs, N00N states, separate photon states (SPSs), the shot noise limit (SNL), and the Heisenberg limit (HL) are provided. A representative collection of computational results illustrating the superiority of LCMMS when compared to PMMSs and N00N states is given. It is found that for a resolution 12 times the classical result LCMMS has visibility 11 times that of N00N states and 4 times that of PMMSs. For the same case, the minimum phase error for LCMMS is 10.7 times smaller than that of PMMS and 29.7 times smaller than that of N00N states.

Modulation/demodulation techniques for satellite communications. Part 1: Background

NASA Technical Reports Server (NTRS)

Omura, J. K.; Simon, M. K.

1981-01-01

Basic characteristics of digital data transmission systems described include the physical communication links, the notion of bandwidth, FCC regulations, and performance measurements such as bit rates, bit error probabilities, throughputs, and delays. The error probability performance and spectral characteristics of various modulation/demodulation techniques commonly used or proposed for use in radio and satellite communication links are summarized. Forward error correction with block or convolutional codes is also discussed along with the important coding parameter, channel cutoff rate.

Plans for a sensitivity analysis of bridge-scour computations

USGS Publications Warehouse

Dunn, David D.; Smith, Peter N.

1993-01-01

Plans for an analysis of the sensitivity of Level 2 bridge-scour computations are described. Cross-section data from 15 bridge sites in Texas are modified to reflect four levels of field effort ranging from no field surveys to complete surveys. Data from United States Geological Survey (USGS) topographic maps will be used to supplement incomplete field surveys. The cross sections are used to compute the water-surface profile through each bridge for several T-year recurrence-interval design discharges. The effect of determining the downstream energy grade-line slope from topographic maps is investigated by systematically varying the starting slope of each profile. The water-surface profile analyses are then used to compute potential scour resulting from each of the design discharges. The planned results will be presented in the form of exceedance-probability versus scour-depth plots with the maximum and minimum scour depths at each T-year discharge presented as error bars.

From information processing to decisions: Formalizing and comparing psychologically plausible choice models.

PubMed

Heck, Daniel W; Hilbig, Benjamin E; Moshagen, Morten

2017-08-01

Decision strategies explain how people integrate multiple sources of information to make probabilistic inferences. In the past decade, increasingly sophisticated methods have been developed to determine which strategy explains decision behavior best. We extend these efforts to test psychologically more plausible models (i.e., strategies), including a new, probabilistic version of the take-the-best (TTB) heuristic that implements a rank order of error probabilities based on sequential processing. Within a coherent statistical framework, deterministic and probabilistic versions of TTB and other strategies can directly be compared using model selection by minimum description length or the Bayes factor. In an experiment with inferences from given information, only three of 104 participants were best described by the psychologically plausible, probabilistic version of TTB. Similar as in previous studies, most participants were classified as users of weighted-additive, a strategy that integrates all available information and approximates rational decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

The Differences in Error Rate and Type between IELTS Writing Bands and Their Impact on Academic Workload

ERIC Educational Resources Information Center

Müller, Amanda

2015-01-01

This paper attempts to demonstrate the differences in writing between International English Language Testing System (IELTS) bands 6.0, 6.5 and 7.0. An analysis of exemplars provided from the IELTS test makers reveals that IELTS 6.0, 6.5 and 7.0 writers can make a minimum of 206 errors, 96 errors and 35 errors per 1000 words. The following section…

The calculation of average error probability in a digital fibre optical communication system

NASA Astrophysics Data System (ADS)

Rugemalira, R. A. M.

1980-03-01

This paper deals with the problem of determining the average error probability in a digital fibre optical communication system, in the presence of message dependent inhomogeneous non-stationary shot noise, additive Gaussian noise and intersymbol interference. A zero-forcing equalization receiver filter is considered. Three techniques for error rate evaluation are compared. The Chernoff bound and the Gram-Charlier series expansion methods are compared to the characteristic function technique. The latter predicts a higher receiver sensitivity

Minimum requirements for predictive pore-network modeling of solute transport in micromodels

NASA Astrophysics Data System (ADS)

Mehmani, Yashar; Tchelepi, Hamdi A.

2017-10-01

Pore-scale models are now an integral part of analyzing fluid dynamics in porous materials (e.g., rocks, soils, fuel cells). Pore network models (PNM) are particularly attractive due to their computational efficiency. However, quantitative predictions with PNM have not always been successful. We focus on single-phase transport of a passive tracer under advection-dominated regimes and compare PNM with high-fidelity direct numerical simulations (DNS) for a range of micromodel heterogeneities. We identify the minimum requirements for predictive PNM of transport. They are: (a) flow-based network extraction, i.e., discretizing the pore space based on the underlying velocity field, (b) a Lagrangian (particle tracking) simulation framework, and (c) accurate transfer of particles from one pore throat to the next. We develop novel network extraction and particle tracking PNM methods that meet these requirements. Moreover, we show that certain established PNM practices in the literature can result in first-order errors in modeling advection-dominated transport. They include: all Eulerian PNMs, networks extracted based on geometric metrics only, and flux-based nodal transfer probabilities. Preliminary results for a 3D sphere pack are also presented. The simulation inputs for this work are made public to serve as a benchmark for the research community.

Probability shapes perceptual precision: A study in orientation estimation.

PubMed

Jabar, Syaheed B; Anderson, Britt

2015-12-01

Probability is known to affect perceptual estimations, but an understanding of mechanisms is lacking. Moving beyond binary classification tasks, we had naive participants report the orientation of briefly viewed gratings where we systematically manipulated contingent probability. Participants rapidly developed faster and more precise estimations for high-probability tilts. The shapes of their error distributions, as indexed by a kurtosis measure, also showed a distortion from Gaussian. This kurtosis metric was robust, capturing probability effects that were graded, contextual, and varying as a function of stimulus orientation. Our data can be understood as a probability-induced reduction in the variability or "shape" of estimation errors, as would be expected if probability affects the perceptual representations. As probability manipulations are an implicit component of many endogenous cuing paradigms, changes at the perceptual level could account for changes in performance that might have traditionally been ascribed to "attention." (c) 2015 APA, all rights reserved).

Effects of preparation time and trial type probability on performance of anti- and pro-saccades.

PubMed

Pierce, Jordan E; McDowell, Jennifer E

2016-02-01

Cognitive control optimizes responses to relevant task conditions by balancing bottom-up stimulus processing with top-down goal pursuit. It can be investigated using the ocular motor system by contrasting basic prosaccades (look toward a stimulus) with complex antisaccades (look away from a stimulus). Furthermore, the amount of time allotted between trials, the need to switch task sets, and the time allowed to prepare for an upcoming saccade all impact performance. In this study the relative probabilities of anti- and pro-saccades were manipulated across five blocks of interleaved trials, while the inter-trial interval and trial type cue duration were varied across subjects. Results indicated that inter-trial interval had no significant effect on error rates or reaction times (RTs), while a shorter trial type cue led to more antisaccade errors and faster overall RTs. Responses following a shorter cue duration also showed a stronger effect of trial type probability, with more antisaccade errors in blocks with a low antisaccade probability and slower RTs for each saccade task when its trial type was unlikely. A longer cue duration yielded fewer errors and slower RTs, with a larger switch cost for errors compared to a short cue duration. Findings demonstrated that when the trial type cue duration was shorter, visual motor responsiveness was faster and subjects relied upon the implicit trial probability context to improve performance. When the cue duration was longer, increased fixation-related activity may have delayed saccade motor preparation and slowed responses, guiding subjects to respond in a controlled manner regardless of trial type probability. Copyright © 2016 Elsevier B.V. All rights reserved.

Simulation of rare events in quantum error correction

NASA Astrophysics Data System (ADS)

Bravyi, Sergey; Vargo, Alexander

2013-12-01

We consider the problem of calculating the logical error probability for a stabilizer quantum code subject to random Pauli errors. To access the regime of large code distances where logical errors are extremely unlikely we adopt the splitting method widely used in Monte Carlo simulations of rare events and Bennett's acceptance ratio method for estimating the free energy difference between two canonical ensembles. To illustrate the power of these methods in the context of error correction, we calculate the logical error probability PL for the two-dimensional surface code on a square lattice with a pair of holes for all code distances d≤20 and all error rates p below the fault-tolerance threshold. Our numerical results confirm the expected exponential decay PL˜exp[-α(p)d] and provide a simple fitting formula for the decay rate α(p). Both noiseless and noisy syndrome readout circuits are considered.

Inflight fuel tank temperature survey data

NASA Technical Reports Server (NTRS)

Pasion, A. J.

1979-01-01

Statistical summaries of the fuel and air temperature data for twelve different routes and for different aircraft models (B747, B707, DC-10 and DC-8), are given. The minimum fuel, total air and static air temperature expected for a 0.3% probability were summarized in table form. Minimum fuel temperature extremes agreed with calculated predictions and the minimum fuel temperature did not necessarily equal the minimum total air temperature even for extreme weather, long range flights.

Analytic barrage attack model. Final report, January 1986-January 1989

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

St Ledger, J.W.; Naegeli, R.E.; Dowden, N.A.

An analytic model is developed for a nuclear barrage attack, assuming weapons with no aiming error and a cookie-cutter damage function. The model is then extended with approximations for the effects of aiming error and distance damage sigma. The final result is a fast running model which calculates probability of damage for a barrage attack. The probability of damage is accurate to within seven percent or better, for weapon reliabilities of 50 to 100 percent, distance damage sigmas of 0.5 or less, and zero to very large circular error probabilities. FORTRAN 77 coding is included in the report for themore » analytic model and for a numerical model used to check the analytic results.« less

[Comparison study on sampling methods of Oncomelania hupensis snail survey in marshland schistosomiasis epidemic areas in China].

PubMed

An, Zhao; Wen-Xin, Zhang; Zhong, Yao; Yu-Kuan, Ma; Qing, Liu; Hou-Lang, Duan; Yi-di, Shang

2016-06-29

To optimize and simplify the survey method of Oncomelania hupensis snail in marshland endemic region of schistosomiasis and increase the precision, efficiency and economy of the snail survey. A quadrate experimental field was selected as the subject of 50 m×50 m size in Chayegang marshland near Henghu farm in the Poyang Lake region and a whole-covered method was adopted to survey the snails. The simple random sampling, systematic sampling and stratified random sampling methods were applied to calculate the minimum sample size, relative sampling error and absolute sampling error. The minimum sample sizes of the simple random sampling, systematic sampling and stratified random sampling methods were 300, 300 and 225, respectively. The relative sampling errors of three methods were all less than 15%. The absolute sampling errors were 0.221 7, 0.302 4 and 0.047 8, respectively. The spatial stratified sampling with altitude as the stratum variable is an efficient approach of lower cost and higher precision for the snail survey.

Estimating parameters for probabilistic linkage of privacy-preserved datasets.

PubMed

Brown, Adrian P; Randall, Sean M; Ferrante, Anna M; Semmens, James B; Boyd, James H

2017-07-10

Probabilistic record linkage is a process used to bring together person-based records from within the same dataset (de-duplication) or from disparate datasets using pairwise comparisons and matching probabilities. The linkage strategy and associated match probabilities are often estimated through investigations into data quality and manual inspection. However, as privacy-preserved datasets comprise encrypted data, such methods are not possible. In this paper, we present a method for estimating the probabilities and threshold values for probabilistic privacy-preserved record linkage using Bloom filters. Our method was tested through a simulation study using synthetic data, followed by an application using real-world administrative data. Synthetic datasets were generated with error rates from zero to 20% error. Our method was used to estimate parameters (probabilities and thresholds) for de-duplication linkages. Linkage quality was determined by F-measure. Each dataset was privacy-preserved using separate Bloom filters for each field. Match probabilities were estimated using the expectation-maximisation (EM) algorithm on the privacy-preserved data. Threshold cut-off values were determined by an extension to the EM algorithm allowing linkage quality to be estimated for each possible threshold. De-duplication linkages of each privacy-preserved dataset were performed using both estimated and calculated probabilities. Linkage quality using the F-measure at the estimated threshold values was also compared to the highest F-measure. Three large administrative datasets were used to demonstrate the applicability of the probability and threshold estimation technique on real-world data. Linkage of the synthetic datasets using the estimated probabilities produced an F-measure that was comparable to the F-measure using calculated probabilities, even with up to 20% error. Linkage of the administrative datasets using estimated probabilities produced an F-measure that was higher than the F-measure using calculated probabilities. Further, the threshold estimation yielded results for F-measure that were only slightly below the highest possible for those probabilities. The method appears highly accurate across a spectrum of datasets with varying degrees of error. As there are few alternatives for parameter estimation, the approach is a major step towards providing a complete operational approach for probabilistic linkage of privacy-preserved datasets.

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

DOE PAGES

Butler, Troy; Wildey, Timothy

2018-01-01

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

Utilizing Adjoint-Based Error Estimates for Surrogate Models to Accurately Predict Probabilities of Events

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

Butler, Troy; Wildey, Timothy

In thist study, we develop a procedure to utilize error estimates for samples of a surrogate model to compute robust upper and lower bounds on estimates of probabilities of events. We show that these error estimates can also be used in an adaptive algorithm to simultaneously reduce the computational cost and increase the accuracy in estimating probabilities of events using computationally expensive high-fidelity models. Specifically, we introduce the notion of reliability of a sample of a surrogate model, and we prove that utilizing the surrogate model for the reliable samples and the high-fidelity model for the unreliable samples gives preciselymore » the same estimate of the probability of the output event as would be obtained by evaluation of the original model for each sample. The adaptive algorithm uses the additional evaluations of the high-fidelity model for the unreliable samples to locally improve the surrogate model near the limit state, which significantly reduces the number of high-fidelity model evaluations as the limit state is resolved. Numerical results based on a recently developed adjoint-based approach for estimating the error in samples of a surrogate are provided to demonstrate (1) the robustness of the bounds on the probability of an event, and (2) that the adaptive enhancement algorithm provides a more accurate estimate of the probability of the QoI event than standard response surface approximation methods at a lower computational cost.« less

The Gulliver Effect: The Impact of Error in an Elephantine Subpopulation on Estimates for Lilliputian Subpopulations

ERIC Educational Resources Information Center

Micceri, Theodore; Parasher, Pradnya; Waugh, Gordon W.; Herreid, Charlene

2009-01-01

An extensive review of the research literature and a study comparing over 36,000 survey responses with archival true scores indicated that one should expect a minimum of at least three percent random error for the least ambiguous of self-report measures. The Gulliver Effect occurs when a small proportion of error in a sizable subpopulation exerts…

On the sensitivity of TG-119 and IROC credentialing to TPS commissioning errors.

PubMed

McVicker, Drew; Yin, Fang-Fang; Adamson, Justus D

2016-01-08

We investigate the sensitivity of IMRT commissioning using the TG-119 C-shape phantom and credentialing with the IROC head and neck phantom to treatment planning system commissioning errors. We introduced errors into the various aspects of the commissioning process for a 6X photon energy modeled using the analytical anisotropic algorithm within a commercial treatment planning system. Errors were implemented into the various components of the dose calculation algorithm including primary photons, secondary photons, electron contamination, and MLC parameters. For each error we evaluated the probability that it could be committed unknowingly during the dose algorithm commissioning stage, and the probability of it being identified during the verification stage. The clinical impact of each commissioning error was evaluated using representative IMRT plans including low and intermediate risk prostate, head and neck, mesothelioma, and scalp; the sensitivity of the TG-119 and IROC phantoms was evaluated by comparing dosimetric changes to the dose planes where film measurements occur and change in point doses where dosimeter measurements occur. No commissioning errors were found to have both a low probability of detection and high clinical severity. When errors do occur, the IROC credentialing and TG 119 commissioning criteria are generally effective at detecting them; however, for the IROC phantom, OAR point-dose measurements are the most sensitive despite being currently excluded from IROC analysis. Point-dose measurements with an absolute dose constraint were the most effective at detecting errors, while film analysis using a gamma comparison and the IROC film distance to agreement criteria were less effective at detecting the specific commissioning errors implemented here.

A Bayesian Framework of Uncertainties Integration in 3D Geological Model

NASA Astrophysics Data System (ADS)

Liang, D.; Liu, X.

2017-12-01

3D geological model can describe complicated geological phenomena in an intuitive way while its application may be limited by uncertain factors. Great progress has been made over the years, lots of studies decompose the uncertainties of geological model to analyze separately, while ignored the comprehensive impacts of multi-source uncertainties. Great progress has been made over the years, while lots of studies ignored the comprehensive impacts of multi-source uncertainties when analyzed them item by item from each source. To evaluate the synthetical uncertainty, we choose probability distribution to quantify uncertainty, and propose a bayesian framework of uncertainties integration. With this framework, we integrated data errors, spatial randomness, and cognitive information into posterior distribution to evaluate synthetical uncertainty of geological model. Uncertainties propagate and cumulate in modeling process, the gradual integration of multi-source uncertainty is a kind of simulation of the uncertainty propagation. Bayesian inference accomplishes uncertainty updating in modeling process. Maximum entropy principle makes a good effect on estimating prior probability distribution, which ensures the prior probability distribution subjecting to constraints supplied by the given information with minimum prejudice. In the end, we obtained a posterior distribution to evaluate synthetical uncertainty of geological model. This posterior distribution represents the synthetical impact of all the uncertain factors on the spatial structure of geological model. The framework provides a solution to evaluate synthetical impact on geological model of multi-source uncertainties and a thought to study uncertainty propagation mechanism in geological modeling.

Multi-level bandwidth efficient block modulation codes

NASA Technical Reports Server (NTRS)

Lin, Shu

1989-01-01

The multilevel technique is investigated for combining block coding and modulation. There are four parts. In the first part, a formulation is presented for signal sets on which modulation codes are to be constructed. Distance measures on a signal set are defined and their properties are developed. In the second part, a general formulation is presented for multilevel modulation codes in terms of component codes with appropriate Euclidean distances. The distance properties, Euclidean weight distribution and linear structure of multilevel modulation codes are investigated. In the third part, several specific methods for constructing multilevel block modulation codes with interdependency among component codes are proposed. Given a multilevel block modulation code C with no interdependency among the binary component codes, the proposed methods give a multilevel block modulation code C which has the same rate as C, a minimum squared Euclidean distance not less than that of code C, a trellis diagram with the same number of states as that of C and a smaller number of nearest neighbor codewords than that of C. In the last part, error performance of block modulation codes is analyzed for an AWGN channel based on soft-decision maximum likelihood decoding. Error probabilities of some specific codes are evaluated based on their Euclidean weight distributions and simulation results.

Adaptive Quadrature Detection for Multicarrier Continuous-Variable Quantum Key Distribution

NASA Astrophysics Data System (ADS)

Gyongyosi, Laszlo; Imre, Sandor

2015-03-01

We propose the adaptive quadrature detection for multicarrier continuous-variable quantum key distribution (CVQKD). A multicarrier CVQKD scheme uses Gaussian subcarrier continuous variables for the information conveying and Gaussian sub-channels for the transmission. The proposed multicarrier detection scheme dynamically adapts to the sub-channel conditions using a corresponding statistics which is provided by our sophisticated sub-channel estimation procedure. The sub-channel estimation phase determines the transmittance coefficients of the sub-channels, which information are used further in the adaptive quadrature decoding process. We define the technique called subcarrier spreading to estimate the transmittance conditions of the sub-channels with a theoretical error-minimum in the presence of a Gaussian noise. We introduce the terms of single and collective adaptive quadrature detection. We also extend the results for a multiuser multicarrier CVQKD scenario. We prove the achievable error probabilities, the signal-to-noise ratios, and quantify the attributes of the framework. The adaptive detection scheme allows to utilize the extra resources of multicarrier CVQKD and to maximize the amount of transmittable information. This work was partially supported by the GOP-1.1.1-11-2012-0092 (Secure quantum key distribution between two units on optical fiber network) project sponsored by the EU and European Structural Fund, and by the COST Action MP1006.

On a stronger-than-best property for best prediction

NASA Astrophysics Data System (ADS)

Teunissen, P. J. G.

2008-03-01

The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors. In case of linear predictors, it has the advantage that no further distributional assumptions need to be made, other then about the first- and second-order moments. In the spatial and Earth sciences, it is the best linear unbiased predictor (BLUP) that is used most often. Despite the fact that in this case only the first- and second-order moments need to be known, one often still makes statements about the complete distribution, in particular when statistical testing is involved. For such cases, one can do better than the BLUP, as shown in Teunissen (J Geod. doi: 10.1007/s00190-007-0140-6, 2006), and thus devise predictors that have a smaller MMSE than the BLUP. Hence, these predictors are to be preferred over the BLUP, if one really values the MMSE-criterion. In the present contribution, we will show, however, that the BLUP has another optimality property than the MMSE-property, provided that the distribution is Gaussian. It will be shown that in the Gaussian case, the prediction error of the BLUP has the highest possible probability of all linear unbiased predictors of being bounded in the weighted squared norm sense. This is a stronger property than the often advertised MMSE-property of the BLUP.

Quantization of high dimensional Gaussian vector using permutation modulation with application to information reconciliation in continuous variable QKD

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal-to-Noise Ratio (SNR) exasperating the problem. Quantization over higher dimensions is advantageous since it allows for fractional bit per sample accuracy which may be needed at very low SNR conditions whereby the achievable secret key rate is significantly less than one bit per sample. In this paper, we propose to use Permutation Modulation (PM) for quantization of Gaussian vectors potentially containing thousands of samples. PM is applied to the magnitudes of the Gaussian samples and we explore the dependence of the sign error probability on the magnitude of the samples. At very low SNR, we may transmit the entire label of the PM code from Bob to Alice in Reverse Reconciliation (RR) over public channel. The side information extracted from this label can then be used by Alice to characterize the sign error probability of her individual samples. Forward Error Correction (FEC) coding can be used by Bob on each subset of samples with similar sign error probability to aid Alice in error correction. This can be done for different subsets of samples with similar sign error probabilities leading to an Unequal Error Protection (UEP) coding paradigm.

Publisher Correction: Polymorphic design of DNA origami structures through mechanical control of modular components.

PubMed

Lee, Chanseok; Lee, Jae Young; Kim, Do-Nyun

2018-02-07

The originally published version of this Article contained an error in Figure 5. In panel f, the right y-axis 'Strain energy (kbT)' was labelled 'Probability' and the left y-axis 'Probability' was labelled 'Strain energy (kbT)'. This error has now been corrected in both the PDF and HTML versions of the Article.

A contemporary approach to the problem of determining physical parameters according to the results of measurements

NASA Technical Reports Server (NTRS)

Elyasberg, P. Y.

1979-01-01

The shortcomings of the classical approach are set forth, and the newer methods resulting from these shortcomings are explained. The problem was approached with the assumption that the probabilities of error were known, as well as without knowledge of the distribution of the probabilities of error. The advantages of the newer approach are discussed.

Minimum constitutive relation error based static identification of beams using force method

NASA Astrophysics Data System (ADS)

Guo, Jia; Takewaki, Izuru

2017-05-01

A new static identification approach based on the minimum constitutive relation error (CRE) principle for beam structures is introduced. The exact stiffness and the exact bending moment are shown to make the CRE minimal for given displacements to beam damages. A two-step substitution algorithm—a force-method step for the bending moment and a constitutive-relation step for the stiffness—is developed and its convergence is rigorously derived. Identifiability is further discussed and the stiffness in the undeformed region is found to be unidentifiable. An extra set of static measurements is complemented to remedy the drawback. Convergence and robustness are finally verified through numerical examples.

An Upper Bound on High Speed Satellite Collision Probability When Only One Object has Position Uncertainty Information

NASA Technical Reports Server (NTRS)

Frisbee, Joseph H., Jr.

2015-01-01

Upper bounds on high speed satellite collision probability, PC †, have been investigated. Previous methods assume an individual position error covariance matrix is available for each object. The two matrices being combined into a single, relative position error covariance matrix. Components of the combined error covariance are then varied to obtain a maximum PC. If error covariance information for only one of the two objects was available, either some default shape has been used or nothing could be done. An alternative is presented that uses the known covariance information along with a critical value of the missing covariance to obtain an approximate but potentially useful Pc upper bound.

The decline and fall of Type II error rates

Treesearch

Steve Verrill; Mark Durst

2005-01-01

For general linear models with normally distributed random errors, the probability of a Type II error decreases exponentially as a function of sample size. This potentially rapid decline reemphasizes the importance of performing power calculations.

Metrics for Business Process Models

NASA Astrophysics Data System (ADS)

Mendling, Jan

Up until now, there has been little research on why people introduce errors in real-world business process models. In a more general context, Simon [404] points to the limitations of cognitive capabilities and concludes that humans act rationally only to a certain extent. Concerning modeling errors, this argument would imply that human modelers lose track of the interrelations of large and complex models due to their limited cognitive capabilities and introduce errors that they would not insert in a small model. A recent study by Mendling et al. [275] explores in how far certain complexity metrics of business process models have the potential to serve as error determinants. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.

Quantum state discrimination bounds for finite sample size

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

Audenaert, Koenraad M. R.; Mosonyi, Milan; Mathematical Institute, Budapest University of Technology and Economics, Egry Jozsef u 1., Budapest 1111

2012-12-15

In the problem of quantum state discrimination, one has to determine by measurements the state of a quantum system, based on the a priori side information that the true state is one of the two given and completely known states, {rho} or {sigma}. In general, it is not possible to decide the identity of the true state with certainty, and the optimal measurement strategy depends on whether the two possible errors (mistaking {rho} for {sigma}, or the other way around) are treated as of equal importance or not. Results on the quantum Chernoff and Hoeffding bounds and the quantum Stein'smore » lemma show that, if several copies of the system are available then the optimal error probabilities decay exponentially in the number of copies, and the decay rate is given by a certain statistical distance between {rho} and {sigma} (the Chernoff distance, the Hoeffding distances, and the relative entropy, respectively). While these results provide a complete solution to the asymptotic problem, they are not completely satisfying from a practical point of view. Indeed, in realistic scenarios one has access only to finitely many copies of a system, and therefore it is desirable to have bounds on the error probabilities for finite sample size. In this paper we provide finite-size bounds on the so-called Stein errors, the Chernoff errors, the Hoeffding errors, and the mixed error probabilities related to the Chernoff and the Hoeffding errors.« less

Understanding seasonal variability of uncertainty in hydrological prediction

NASA Astrophysics Data System (ADS)

Li, M.; Wang, Q. J.

2012-04-01

Understanding uncertainty in hydrological prediction can be highly valuable for improving the reliability of streamflow prediction. In this study, a monthly water balance model, WAPABA, in a Bayesian joint probability with error models are presented to investigate the seasonal dependency of prediction error structure. A seasonal invariant error model, analogous to traditional time series analysis, uses constant parameters for model error and account for no seasonal variations. In contrast, a seasonal variant error model uses a different set of parameters for bias, variance and autocorrelation for each individual calendar month. Potential connection amongst model parameters from similar months is not considered within the seasonal variant model and could result in over-fitting and over-parameterization. A hierarchical error model further applies some distributional restrictions on model parameters within a Bayesian hierarchical framework. An iterative algorithm is implemented to expedite the maximum a posterior (MAP) estimation of a hierarchical error model. Three error models are applied to forecasting streamflow at a catchment in southeast Australia in a cross-validation analysis. This study also presents a number of statistical measures and graphical tools to compare the predictive skills of different error models. From probability integral transform histograms and other diagnostic graphs, the hierarchical error model conforms better to reliability when compared to the seasonal invariant error model. The hierarchical error model also generally provides the most accurate mean prediction in terms of the Nash-Sutcliffe model efficiency coefficient and the best probabilistic prediction in terms of the continuous ranked probability score (CRPS). The model parameters of the seasonal variant error model are very sensitive to each cross validation, while the hierarchical error model produces much more robust and reliable model parameters. Furthermore, the result of the hierarchical error model shows that most of model parameters are not seasonal variant except for error bias. The seasonal variant error model is likely to use more parameters than necessary to maximize the posterior likelihood. The model flexibility and robustness indicates that the hierarchical error model has great potential for future streamflow predictions.

Fundamental Bounds for Sequence Reconstruction from Nanopore Sequencers.

PubMed

Magner, Abram; Duda, Jarosław; Szpankowski, Wojciech; Grama, Ananth

2016-06-01

Nanopore sequencers are emerging as promising new platforms for high-throughput sequencing. As with other technologies, sequencer errors pose a major challenge for their effective use. In this paper, we present a novel information theoretic analysis of the impact of insertion-deletion (indel) errors in nanopore sequencers. In particular, we consider the following problems: (i) for given indel error characteristics and rate, what is the probability of accurate reconstruction as a function of sequence length; (ii) using replicated extrusion (the process of passing a DNA strand through the nanopore), what is the number of replicas needed to accurately reconstruct the true sequence with high probability? Our results provide a number of important insights: (i) the probability of accurate reconstruction of a sequence from a single sample in the presence of indel errors tends quickly (i.e., exponentially) to zero as the length of the sequence increases; and (ii) replicated extrusion is an effective technique for accurate reconstruction. We show that for typical distributions of indel errors, the required number of replicas is a slow function (polylogarithmic) of sequence length - implying that through replicated extrusion, we can sequence large reads using nanopore sequencers. Moreover, we show that in certain cases, the required number of replicas can be related to information-theoretic parameters of the indel error distributions.

Accounting for spatiotemporal errors of gauges: A critical step to evaluate gridded precipitation products

NASA Astrophysics Data System (ADS)

Tang, Guoqiang; Behrangi, Ali; Long, Di; Li, Changming; Hong, Yang

2018-04-01

Rain gauge observations are commonly used to evaluate the quality of satellite precipitation products. However, the inherent difference between point-scale gauge measurements and areal satellite precipitation, i.e. a point of space in time accumulation v.s. a snapshot of time in space aggregation, has an important effect on the accuracy and precision of qualitative and quantitative evaluation results. This study aims to quantify the uncertainty caused by various combinations of spatiotemporal scales (0.1°-0.8° and 1-24 h) of gauge network designs in the densely gauged and relatively flat Ganjiang River basin, South China, in order to evaluate the state-of-the-art satellite precipitation, the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG). For comparison with the dense gauge network serving as "ground truth", 500 sparse gauge networks are generated through random combinations of gauge numbers at each set of spatiotemporal scales. Results show that all sparse gauge networks persistently underestimate the performance of IMERG according to most metrics. However, the probability of detection is overestimated because hit and miss events are more likely fewer than the reference numbers derived from dense gauge networks. A nonlinear error function of spatiotemporal scales and the number of gauges in each grid pixel is developed to estimate the errors of using gauges to evaluate satellite precipitation. Coefficients of determination of the fitting are above 0.9 for most metrics. The error function can also be used to estimate the required minimum number of gauges in each grid pixel to meet a predefined error level. This study suggests that the actual quality of satellite precipitation products could be better than conventionally evaluated or expected, and hopefully enables non-subject-matter-expert researchers to have better understanding of the explicit uncertainties when using point-scale gauge observations to evaluate areal products.

A negentropy minimization approach to adaptive equalization for digital communication systems.

PubMed

Choi, Sooyong; Lee, Te-Won

2004-07-01

In this paper, we introduce and investigate a new adaptive equalization method based on minimizing approximate negentropy of the estimation error for a finite-length equalizer. We consider an approximate negentropy using nonpolynomial expansions of the estimation error as a new performance criterion to improve performance of a linear equalizer based on minimizing minimum mean squared error (MMSE). Negentropy includes higher order statistical information and its minimization provides improved converge, performance and accuracy compared to traditional methods such as MMSE in terms of bit error rate (BER). The proposed negentropy minimization (NEGMIN) equalizer has two kinds of solutions, the MMSE solution and the other one, depending on the ratio of the normalization parameters. The NEGMIN equalizer has best BER performance when the ratio of the normalization parameters is properly adjusted to maximize the output power(variance) of the NEGMIN equalizer. Simulation experiments show that BER performance of the NEGMIN equalizer with the other solution than the MMSE one has similar characteristics to the adaptive minimum bit error rate (AMBER) equalizer. The main advantage of the proposed equalizer is that it needs significantly fewer training symbols than the AMBER equalizer. Furthermore, the proposed equalizer is more robust to nonlinear distortions than the MMSE equalizer.

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

PubMed Central

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

2013-01-01

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

Sensitivity to prediction error in reach adaptation

PubMed Central

Haith, Adrian M.; Harran, Michelle D.; Shadmehr, Reza

2012-01-01

It has been proposed that the brain predicts the sensory consequences of a movement and compares it to the actual sensory feedback. When the two differ, an error signal is formed, driving adaptation. How does an error in one trial alter performance in the subsequent trial? Here we show that the sensitivity to error is not constant but declines as a function of error magnitude. That is, one learns relatively less from large errors compared with small errors. We performed an experiment in which humans made reaching movements and randomly experienced an error in both their visual and proprioceptive feedback. Proprioceptive errors were created with force fields, and visual errors were formed by perturbing the cursor trajectory to create a visual error that was smaller, the same size, or larger than the proprioceptive error. We measured single-trial adaptation and calculated sensitivity to error, i.e., the ratio of the trial-to-trial change in motor commands to error size. We found that for both sensory modalities sensitivity decreased with increasing error size. A reanalysis of a number of previously published psychophysical results also exhibited this feature. Finally, we asked how the brain might encode sensitivity to error. We reanalyzed previously published probabilities of cerebellar complex spikes (CSs) and found that this probability declined with increasing error size. From this we posit that a CS may be representative of the sensitivity to error, and not error itself, a hypothesis that may explain conflicting reports about CSs and their relationship to error. PMID:22773782

Asymmetric Memory Circuit Would Resist Soft Errors

NASA Technical Reports Server (NTRS)

Buehler, Martin G.; Perlman, Marvin

1990-01-01

Some nonlinear error-correcting codes more efficient in presence of asymmetry. Combination of circuit-design and coding concepts expected to make integrated-circuit random-access memories more resistant to "soft" errors (temporary bit errors, also called "single-event upsets" due to ionizing radiation). Integrated circuit of new type made deliberately more susceptible to one kind of bit error than to other, and associated error-correcting code adapted to exploit this asymmetry in error probabilities.

On the Probability of Error and Stochastic Resonance in Discrete Memoryless Channels

DTIC Science & Technology

2013-12-01

Information - Driven Doppler Shift Estimation and Compensation Methods for Underwater Wireless Sensor Networks ”, which is to analyze and develop... underwater wireless sensor networks . We formulated an analytic relationship that relates the average probability of error to the systems parameters, the...thesis, we studied the performance of Discrete Memoryless Channels (DMC), arising in the context of cooperative underwater wireless sensor networks

Probability of misclassifying biological elements in surface waters.

PubMed

Loga, Małgorzata; Wierzchołowska-Dziedzic, Anna

2017-11-24

Measurement uncertainties are inherent to assessment of biological indices of water bodies. The effect of these uncertainties on the probability of misclassification of ecological status is the subject of this paper. Four Monte-Carlo (M-C) models were applied to simulate the occurrence of random errors in the measurements of metrics corresponding to four biological elements of surface waters: macrophytes, phytoplankton, phytobenthos, and benthic macroinvertebrates. Long series of error-prone measurement values of these metrics, generated by M-C models, were used to identify cases in which values of any of the four biological indices lay outside of the "true" water body class, i.e., outside the class assigned from the actual physical measurements. Fraction of such cases in the M-C generated series was used to estimate the probability of misclassification. The method is particularly useful for estimating the probability of misclassification of the ecological status of surface water bodies in the case of short sequences of measurements of biological indices. The results of the Monte-Carlo simulations show a relatively high sensitivity of this probability to measurement errors of the river macrophyte index (MIR) and high robustness to measurement errors of the benthic macroinvertebrate index (MMI). The proposed method of using Monte-Carlo models to estimate the probability of misclassification has significant potential for assessing the uncertainty of water body status reported to the EC by the EU member countries according to WFD. The method can be readily applied also in risk assessment of water management decisions before adopting the status dependent corrective actions.

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2011-01-01

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Equalization and detection for digital communication over nonlinear bandlimited satellite communication channels. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gutierrez, Alberto, Jr.

1995-01-01

This dissertation evaluates receiver-based methods for mitigating the effects due to nonlinear bandlimited signal distortion present in high data rate satellite channels. The effects of the nonlinear bandlimited distortion is illustrated for digitally modulated signals. A lucid development of the low-pass Volterra discrete time model for a nonlinear communication channel is presented. In addition, finite-state machine models are explicitly developed for a nonlinear bandlimited satellite channel. A nonlinear fixed equalizer based on Volterra series has previously been studied for compensation of noiseless signal distortion due to a nonlinear satellite channel. This dissertation studies adaptive Volterra equalizers on a downlink-limited nonlinear bandlimited satellite channel. We employ as figure of merits performance in the mean-square error and probability of error senses. In addition, a receiver consisting of a fractionally-spaced equalizer (FSE) followed by a Volterra equalizer (FSE-Volterra) is found to give improvement beyond that gained by the Volterra equalizer. Significant probability of error performance improvement is found for multilevel modulation schemes. Also, it is found that probability of error improvement is more significant for modulation schemes, constant amplitude and multilevel, which require higher signal to noise ratios (i.e., higher modulation orders) for reliable operation. The maximum likelihood sequence detection (MLSD) receiver for a nonlinear satellite channel, a bank of matched filters followed by a Viterbi detector, serves as a probability of error lower bound for the Volterra and FSE-Volterra equalizers. However, this receiver has not been evaluated for a specific satellite channel. In this work, an MLSD receiver is evaluated for a specific downlink-limited satellite channel. Because of the bank of matched filters, the MLSD receiver may be high in complexity. Consequently, the probability of error performance of a more practical suboptimal MLSD receiver, requiring only a single receive filter, is evaluated.

A hybrid machine learning model to estimate nitrate contamination of production zone groundwater in the Central Valley, California

NASA Astrophysics Data System (ADS)

Ransom, K.; Nolan, B. T.; Faunt, C. C.; Bell, A.; Gronberg, J.; Traum, J.; Wheeler, D. C.; Rosecrans, C.; Belitz, K.; Eberts, S.; Harter, T.

2016-12-01

A hybrid, non-linear, machine learning statistical model was developed within a statistical learning framework to predict nitrate contamination of groundwater to depths of approximately 500 m below ground surface in the Central Valley, California. A database of 213 predictor variables representing well characteristics, historical and current field and county scale nitrogen mass balance, historical and current landuse, oxidation/reduction conditions, groundwater flow, climate, soil characteristics, depth to groundwater, and groundwater age were assigned to over 6,000 private supply and public supply wells measured previously for nitrate and located throughout the study area. The machine learning method, gradient boosting machine (GBM) was used to screen predictor variables and rank them in order of importance in relation to the groundwater nitrate measurements. The top five most important predictor variables included oxidation/reduction characteristics, historical field scale nitrogen mass balance, climate, and depth to 60 year old water. Twenty-two variables were selected for the final model and final model errors for log-transformed hold-out data were R squared of 0.45 and root mean square error (RMSE) of 1.124. Modeled mean groundwater age was tested separately for error improvement in the model and when included decreased model RMSE by 0.5% compared to the same model without age and by 0.20% compared to the model with all 213 variables. 1D and 2D partial plots were examined to determine how variables behave individually and interact in the model. Some variables behaved as expected: log nitrate decreased with increasing probability of anoxic conditions and depth to 60 year old water, generally decreased with increasing natural landuse surrounding wells and increasing mean groundwater age, generally increased with increased minimum depth to high water table and with increased base flow index value. Other variables exhibited much more erratic or noisy behavior in the model making them more difficult to interpret but highlighting the usefulness of the non-linear machine learning method. 2D interaction plots show probability of anoxic groundwater conditions largely control estimated nitrate concentrations compared to the other predictors.

Simple, accurate formula for the average bit error probability of multiple-input multiple-output free-space optical links over negative exponential turbulence channels.

PubMed

Peppas, Kostas P; Lazarakis, Fotis; Alexandridis, Antonis; Dangakis, Kostas

2012-08-01

In this Letter we investigate the error performance of multiple-input multiple-output free-space optical communication systems employing intensity modulation/direct detection and operating over strong atmospheric turbulence channels. Atmospheric-induced strong turbulence fading is modeled using the negative exponential distribution. For the considered system, an approximate yet accurate analytical expression for the average bit error probability is derived and an efficient method for its numerical evaluation is proposed. Numerically evaluated and computer simulation results are further provided to demonstrate the validity of the proposed mathematical analysis.

Minimum risk wavelet shrinkage operator for Poisson image denoising.

PubMed

Cheng, Wu; Hirakawa, Keigo

2015-05-01

The pixel values of images taken by an image sensor are said to be corrupted by Poisson noise. To date, multiscale Poisson image denoising techniques have processed Haar frame and wavelet coefficients--the modeling of coefficients is enabled by the Skellam distribution analysis. We extend these results by solving for shrinkage operators for Skellam that minimizes the risk functional in the multiscale Poisson image denoising setting. The minimum risk shrinkage operator of this kind effectively produces denoised wavelet coefficients with minimum attainable L2 error.

Quantifying seining detection probability for fishes of Great Plains sand‐bed rivers

USGS Publications Warehouse

Mollenhauer, Robert; Logue, Daniel R.; Brewer, Shannon K.

2018-01-01

Species detection error (i.e., imperfect and variable detection probability) is an essential consideration when investigators map distributions and interpret habitat associations. When fish detection error that is due to highly variable instream environments needs to be addressed, sand‐bed streams of the Great Plains represent a unique challenge. We quantified seining detection probability for diminutive Great Plains fishes across a range of sampling conditions in two sand‐bed rivers in Oklahoma. Imperfect detection resulted in underestimates of species occurrence using naïve estimates, particularly for less common fishes. Seining detection probability also varied among fishes and across sampling conditions. We observed a quadratic relationship between water depth and detection probability, in which the exact nature of the relationship was species‐specific and dependent on water clarity. Similarly, the direction of the relationship between water clarity and detection probability was species‐specific and dependent on differences in water depth. The relationship between water temperature and detection probability was also species dependent, where both the magnitude and direction of the relationship varied among fishes. We showed how ignoring detection error confounded an underlying relationship between species occurrence and water depth. Despite imperfect and heterogeneous detection, our results support that determining species absence can be accomplished with two to six spatially replicated seine hauls per 200‐m reach under average sampling conditions; however, required effort would be higher under certain conditions. Detection probability was low for the Arkansas River Shiner Notropis girardi, which is federally listed as threatened, and more than 10 seine hauls per 200‐m reach would be required to assess presence across sampling conditions. Our model allows scientists to estimate sampling effort to confidently assess species occurrence, which maximizes the use of available resources. Increased implementation of approaches that consider detection error promote ecological advancements and conservation and management decisions that are better informed.

Computer search for binary cyclic UEP codes of odd length up to 65

NASA Technical Reports Server (NTRS)

Lin, Mao-Chao; Lin, Chi-Chang; Lin, Shu

1990-01-01

Using an exhaustive computation, the unequal error protection capabilities of all binary cyclic codes of odd length up to 65 that have minimum distances at least 3 are found. For those codes that can only have upper bounds on their unequal error protection capabilities computed, an analytic method developed by Dynkin and Togonidze (1976) is used to show that the upper bounds meet the exact unequal error protection capabilities.

Continuous slope-area discharge records in Maricopa County, Arizona, 2004–2012

USGS Publications Warehouse

Wiele, Stephen M.; Heaton, John W.; Bunch, Claire E.; Gardner, David E.; Smith, Christopher F.

2015-12-29

Analyses of sources of errors and the impact stage data errors have on calculated discharge time series are considered, along with issues in data reduction. Steeper, longer stream reaches are generally less sensitive to measurement error. Other issues considered are pressure transducer drawdown, capture of flood peaks with discrete stage data, selection of stage record for development of rating curves, and minimum stages for the calculation of discharge.

A method to compute SEU fault probabilities in memory arrays with error correction

NASA Technical Reports Server (NTRS)

Gercek, Gokhan

1994-01-01

With the increasing packing densities in VLSI technology, Single Event Upsets (SEU) due to cosmic radiations are becoming more of a critical issue in the design of space avionics systems. In this paper, a method is introduced to compute the fault (mishap) probability for a computer memory of size M words. It is assumed that a Hamming code is used for each word to provide single error correction. It is also assumed that every time a memory location is read, single errors are corrected. Memory is read randomly whose distribution is assumed to be known. In such a scenario, a mishap is defined as two SEU's corrupting the same memory location prior to a read. The paper introduces a method to compute the overall mishap probability for the entire memory for a mission duration of T hours.

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

DOE PAGES

Theis, Daniel; Ivanic, Joseph; Windus, Theresa L.; ...

2016-03-10

The metastable ring structure of the ozone 1 1A 1 ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two 1A 1 states. In the present work, valence correlated energies of the 1 1A 1 state and the 2 1A 1 state were calculated at the 1 1A 1 open minimum, the 1 1A 1 ring minimum, themore » transition state between these two minima, the minimum of the 2 1A 1 state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of CorrelationEnergy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 11A1 state, the present calculations yield the estimates of (ring minimum—open minimum) ~45–50 mh and (transition state—open minimum) ~85–90 mh. For the (2 1A 1– 1A 1) excitation energy, the estimate of ~130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2 1A 1– 1A 1) is found to be between 1 and 10 mh. The geometry of the transition state on the 11A1 surface and that of the minimum on the 2 1A 1 surface nearly coincide. More accurate predictions of the energydifferences also require CI expansions to at least sextuple excitations with respect to the valence space. Furthermore, for every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

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

Theis, Daniel; Ivanic, Joseph; Windus, Theresa L.

The metastable ring structure of the ozone 1 1A 1 ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two 1A 1 states. In the present work, valence correlated energies of the 1 1A 1 state and the 2 1A 1 state were calculated at the 1 1A 1 open minimum, the 1 1A 1 ring minimum, themore » transition state between these two minima, the minimum of the 2 1A 1 state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of CorrelationEnergy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 11A1 state, the present calculations yield the estimates of (ring minimum—open minimum) ~45–50 mh and (transition state—open minimum) ~85–90 mh. For the (2 1A 1– 1A 1) excitation energy, the estimate of ~130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2 1A 1– 1A 1) is found to be between 1 and 10 mh. The geometry of the transition state on the 11A1 surface and that of the minimum on the 2 1A 1 surface nearly coincide. More accurate predictions of the energydifferences also require CI expansions to at least sextuple excitations with respect to the valence space. Furthermore, for every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

Multiple statistical tests: Lessons from a d20.

PubMed

Madan, Christopher R

2016-01-01

Statistical analyses are often conducted with α= .05. When multiple statistical tests are conducted, this procedure needs to be adjusted to compensate for the otherwise inflated Type I error. In some instances in tabletop gaming, sometimes it is desired to roll a 20-sided die (or 'd20') twice and take the greater outcome. Here I draw from probability theory and the case of a d20, where the probability of obtaining any specific outcome is (1)/ 20, to determine the probability of obtaining a specific outcome (Type-I error) at least once across repeated, independent statistical tests.

The price of complexity in financial networks

NASA Astrophysics Data System (ADS)

Battiston, Stefano; Caldarelli, Guido; May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

2016-09-01

Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

The price of complexity in financial networks.

PubMed

Battiston, Stefano; Caldarelli, Guido; May, Robert M; Roukny, Tarik; Stiglitz, Joseph E

2016-09-06

Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.

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

McCulloch, M; Cazoulat, G; Polan, D

Purpose: It is well documented that the delivered dose to patients undergoing radiotherapy (RT) is often different from the planned dose due to geometric variability and uncertainties in patient positioning. Recent work suggests that accumulated dose to the GTV is a better predictor of progression compared to the minimum planned dose to the PTV. The purpose of this study is to evaluate if deviations from the planned dose can contributed to tumor progression. Methods: From 2010 to 2014 an in-house Phase II clinical trial of adaptive stereotactic body RT was completed. Of the 90 patients enrolled, 7 patients had amore » local recurrence defined on contrast enhanced CT or MR imaging 3–21 months after completion of RT. Retrospective dose accumulation was performed using a biomechanical model-based deformable image registration algorithm (DIR) to accumulate the dose based on the kV CBCT acquired prior to each fraction for soft tissue alignment of the patient. The DIR algorithm was previously validated for geometric accuracy in the liver (target registration error = 2.0 mm) and dose accumulation in a homogeneous image, similar to a liver CBCT (gamma index = 91%). Following dose accumulation, the minimum dose to 0.5 cc of the GTV was compared between the planned and accumulated dose. Work is ongoing to evaluate the tumor control probability based on the planned and accumulated dose. Results: DIR and dose accumulation was performed on all fractions for 6 patients with local recurrence. The difference in minimum dose to 0.5 cc of the GTV ranged from −0.3–2.3 Gy over 3–5 fractions. One patient had a potentially significant difference in minimum dose of 2.3 Gy. Conclusion: Dose accumulation can reveal tumor underdosage, improving our ability to understand recurrence and tumor progression patterns, and could aid in adaptive re-planning during therapy to correct for this. This work was supported in part by NIH P01CA059827.« less

Dynamic Sensor Tasking for Space Situational Awareness via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Linares, R.; Furfaro, R.

2016-09-01

This paper studies the Sensor Management (SM) problem for optical Space Object (SO) tracking. The tasking problem is formulated as a Markov Decision Process (MDP) and solved using Reinforcement Learning (RL). The RL problem is solved using the actor-critic policy gradient approach. The actor provides a policy which is random over actions and given by a parametric probability density function (pdf). The critic evaluates the policy by calculating the estimated total reward or the value function for the problem. The parameters of the policy action pdf are optimized using gradients with respect to the reward function. Both the critic and the actor are modeled using deep neural networks (multi-layer neural networks). The policy neural network takes the current state as input and outputs probabilities for each possible action. This policy is random, and can be evaluated by sampling random actions using the probabilities determined by the policy neural network's outputs. The critic approximates the total reward using a neural network. The estimated total reward is used to approximate the gradient of the policy network with respect to the network parameters. This approach is used to find the non-myopic optimal policy for tasking optical sensors to estimate SO orbits. The reward function is based on reducing the uncertainty for the overall catalog to below a user specified uncertainty threshold. This work uses a 30 km total position error for the uncertainty threshold. This work provides the RL method with a negative reward as long as any SO has a total position error above the uncertainty threshold. This penalizes policies that take longer to achieve the desired accuracy. A positive reward is provided when all SOs are below the catalog uncertainty threshold. An optimal policy is sought that takes actions to achieve the desired catalog uncertainty in minimum time. This work trains the policy in simulation by letting it task a single sensor to "learn" from its performance. The proposed approach for the SM problem is tested in simulation and good performance is found using the actor-critic policy gradient method.

Original and Mirror Face Images and Minimum Squared Error Classification for Visible Light Face Recognition.

PubMed

Wang, Rong

2015-01-01

In real-world applications, the image of faces varies with illumination, facial expression, and poses. It seems that more training samples are able to reveal possible images of the faces. Though minimum squared error classification (MSEC) is a widely used method, its applications on face recognition usually suffer from the problem of a limited number of training samples. In this paper, we improve MSEC by using the mirror faces as virtual training samples. We obtained the mirror faces generated from original training samples and put these two kinds of samples into a new set. The face recognition experiments show that our method does obtain high accuracy performance in classification.

Permanence analysis of a concatenated coding scheme for error control

NASA Technical Reports Server (NTRS)

Costello, D. J., Jr.; Lin, S.; Kasami, T.

1983-01-01

A concatenated coding scheme for error control in data communications is analyzed. In this scheme, the inner code is used for both error correction and detection, however, the outer code is used only for error detection. A retransmission is requested if the outer code detects the presence of errors after the inner code decoding. Probability of undetected error is derived and bounded. A particular example, proposed for the planetary program, is analyzed.

A Parallel Decoding Algorithm for Short Polar Codes Based on Error Checking and Correcting

PubMed Central

Pan, Xiaofei; Pan, Kegang; Ye, Zhan; Gong, Chao

2014-01-01

We propose a parallel decoding algorithm based on error checking and correcting to improve the performance of the short polar codes. In order to enhance the error-correcting capacity of the decoding algorithm, we first derive the error-checking equations generated on the basis of the frozen nodes, and then we introduce the method to check the errors in the input nodes of the decoder by the solutions of these equations. In order to further correct those checked errors, we adopt the method of modifying the probability messages of the error nodes with constant values according to the maximization principle. Due to the existence of multiple solutions of the error-checking equations, we formulate a CRC-aided optimization problem of finding the optimal solution with three different target functions, so as to improve the accuracy of error checking. Besides, in order to increase the throughput of decoding, we use a parallel method based on the decoding tree to calculate probability messages of all the nodes in the decoder. Numerical results show that the proposed decoding algorithm achieves better performance than that of some existing decoding algorithms with the same code length. PMID:25540813

MASTER: a model to improve and standardize clinical breakpoints for antimicrobial susceptibility testing using forecast probabilities.

PubMed

Blöchliger, Nicolas; Keller, Peter M; Böttger, Erik C; Hombach, Michael

2017-09-01

The procedure for setting clinical breakpoints (CBPs) for antimicrobial susceptibility has been poorly standardized with respect to population data, pharmacokinetic parameters and clinical outcome. Tools to standardize CBP setting could result in improved antibiogram forecast probabilities. We propose a model to estimate probabilities for methodological categorization errors and defined zones of methodological uncertainty (ZMUs), i.e. ranges of zone diameters that cannot reliably be classified. The impact of ZMUs on methodological error rates was used for CBP optimization. The model distinguishes theoretical true inhibition zone diameters from observed diameters, which suffer from methodological variation. True diameter distributions are described with a normal mixture model. The model was fitted to observed inhibition zone diameters of clinical Escherichia coli strains. Repeated measurements for a quality control strain were used to quantify methodological variation. For 9 of 13 antibiotics analysed, our model predicted error rates of < 0.1% applying current EUCAST CBPs. Error rates were > 0.1% for ampicillin, cefoxitin, cefuroxime and amoxicillin/clavulanic acid. Increasing the susceptible CBP (cefoxitin) and introducing ZMUs (ampicillin, cefuroxime, amoxicillin/clavulanic acid) decreased error rates to < 0.1%. ZMUs contained low numbers of isolates for ampicillin and cefuroxime (3% and 6%), whereas the ZMU for amoxicillin/clavulanic acid contained 41% of all isolates and was considered not practical. We demonstrate that CBPs can be improved and standardized by minimizing methodological categorization error rates. ZMUs may be introduced if an intermediate zone is not appropriate for pharmacokinetic/pharmacodynamic or drug dosing reasons. Optimized CBPs will provide a standardized antibiotic susceptibility testing interpretation at a defined level of probability. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Performance of Noncoherent Orthogonal M-FSK in the Presence of Timing and Frequency Errors

NASA Technical Reports Server (NTRS)

Hinedi, Sami; Simon, Marvin K.; Raphaeli, Dan

1993-01-01

Practical M-FSK systems experience a combination of time and frequency offsets (errors). This paper assesses the deleterious effect of these offsets, first individually and then combined, on the average bit error probability performance of the system.

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

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes withmore » the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.« less

Performance analysis of a cascaded coding scheme with interleaved outer code

NASA Technical Reports Server (NTRS)

Lin, S.

1986-01-01

A cascaded coding scheme for a random error channel with a bit-error rate is analyzed. In this scheme, the inner code C sub 1 is an (n sub 1, m sub 1l) binary linear block code which is designed for simultaneous error correction and detection. The outer code C sub 2 is a linear block code with symbols from the Galois field GF (2 sup l) which is designed for correcting both symbol errors and erasures, and is interleaved with a degree m sub 1. A procedure for computing the probability of a correct decoding is presented and an upper bound on the probability of a decoding error is derived. The bound provides much better results than the previous bound for a cascaded coding scheme with an interleaved outer code. Example schemes with inner codes ranging from high rates to very low rates are evaluated. Several schemes provide extremely high reliability even for very high bit-error rates say 10 to the -1 to 10 to the -2 power.

Short version of the Depression Anxiety Stress Scale-21: is it valid for Brazilian adolescents?

PubMed Central

da Silva, Hítalo Andrade; dos Passos, Muana Hiandra Pereira; de Oliveira, Valéria Mayaly Alves; Palmeira, Aline Cabral; Pitangui, Ana Carolina Rodarti; de Araújo, Rodrigo Cappato

2016-01-01

ABSTRACT Objective To evaluate the interday reproducibility, agreement and validity of the construct of short version of the Depression Anxiety Stress Scale-21 applied to adolescents. Methods The sample consisted of adolescents of both sexes, aged between 10 and 19 years, who were recruited from schools and sports centers. The validity of the construct was performed by exploratory factor analysis, and reliability was calculated for each construct using the intraclass correlation coefficient, standard error of measurement and the minimum detectable change. Results The factor analysis combining the items corresponding to anxiety and stress in a single factor, and depression in a second factor, showed a better match of all 21 items, with higher factor loadings in their respective constructs. The reproducibility values for depression were intraclass correlation coefficient with 0.86, standard error of measurement with 0.80, and minimum detectable change with 2.22; and, for anxiety/stress: intraclass correlation coefficient with 0.82, standard error of measurement with 1.80, and minimum detectable change with 4.99. Conclusion The short version of the Depression Anxiety Stress Scale-21 showed excellent values of reliability, and strong internal consistency. The two-factor model with condensation of the constructs anxiety and stress in a single factor was the most acceptable for the adolescent population. PMID:28076595

An intersecting chord method for minimum circumscribed sphere and maximum inscribed sphere evaluations of sphericity error

NASA Astrophysics Data System (ADS)

Liu, Fei; Xu, Guanghua; Zhang, Qing; Liang, Lin; Liu, Dan

2015-11-01

As one of the Geometrical Product Specifications that are widely applied in industrial manufacturing and measurement, sphericity error can synthetically scale a 3D structure and reflects the machining quality of a spherical workpiece. Following increasing demands in the high motion performance of spherical parts, sphericity error is becoming an indispensable component in the evaluation of form error. However, the evaluation of sphericity error is still considered to be a complex mathematical issue, and the related research studies on the development of available models are lacking. In this paper, an intersecting chord method is first proposed to solve the minimum circumscribed sphere and maximum inscribed sphere evaluations of sphericity error. This new modelling method leverages chord relationships to replace the characteristic points, thereby significantly reducing the computational complexity and improving the computational efficiency. Using the intersecting chords to generate a virtual centre, the reference sphere in two concentric spheres is simplified as a space intersecting structure. The position of the virtual centre on the space intersecting structure is determined by characteristic chords, which may reduce the deviation between the virtual centre and the centre of the reference sphere. In addition,two experiments are used to verify the effectiveness of the proposed method with real datasets from the Cartesian coordinates. The results indicate that the estimated errors are in perfect agreement with those of the published methods. Meanwhile, the computational efficiency is improved. For the evaluation of the sphericity error, the use of high performance computing is a remarkable change.

Brief Report: Investigating Uncertainty in the Minimum Mortality Temperature: Methods and Application to 52 Spanish Cities.

PubMed

Tobías, Aurelio; Armstrong, Ben; Gasparrini, Antonio

2017-01-01

The minimum mortality temperature from J- or U-shaped curves varies across cities with different climates. This variation conveys information on adaptation, but ability to characterize is limited by the absence of a method to describe uncertainty in estimated minimum mortality temperatures. We propose an approximate parametric bootstrap estimator of confidence interval (CI) and standard error (SE) for the minimum mortality temperature from a temperature-mortality shape estimated by splines. The coverage of the estimated CIs was close to nominal value (95%) in the datasets simulated, although SEs were slightly high. Applying the method to 52 Spanish provincial capital cities showed larger minimum mortality temperatures in hotter cities, rising almost exactly at the same rate as annual mean temperature. The method proposed for computing CIs and SEs for minimums from spline curves allows comparing minimum mortality temperatures in different cities and investigating their associations with climate properly, allowing for estimation uncertainty.

A Sensitivity Analysis of Circular Error Probable Approximation Techniques

DTIC Science & Technology

1992-03-01

SENSITIVITY ANALYSIS OF CIRCULAR ERROR PROBABLE APPROXIMATION TECHNIQUES THESIS Presented to the Faculty of the School of Engineering of the Air Force...programming skills. Major Paul Auclair patiently advised me in this endeavor, and Major Andy Howell added numerous insightful contributions. I thank my...techniques. The two ret(st accuratec techniiques require numerical integration and can take several hours to run ov a personal comlputer [2:1-2,4-6]. Some

Observation of non-classical correlations in sequential measurements of photon polarization

NASA Astrophysics Data System (ADS)

Suzuki, Yutaro; Iinuma, Masataka; Hofmann, Holger F.

2016-10-01

A sequential measurement of two non-commuting quantum observables results in a joint probability distribution for all output combinations that can be explained in terms of an initial joint quasi-probability of the non-commuting observables, modified by the resolution errors and back-action of the initial measurement. Here, we show that the error statistics of a sequential measurement of photon polarization performed at different measurement strengths can be described consistently by an imaginary correlation between the statistics of resolution and back-action. The experimental setup was designed to realize variable strength measurements with well-controlled imaginary correlation between the statistical errors caused by the initial measurement of diagonal polarizations, followed by a precise measurement of the horizontal/vertical polarization. We perform the experimental characterization of an elliptically polarized input state and show that the same complex joint probability distribution is obtained at any measurement strength.

Protograph based LDPC codes with minimum distance linearly growing with block size

NASA Technical Reports Server (NTRS)

Divsalar, Dariush; Jones, Christopher; Dolinar, Sam; Thorpe, Jeremy

2005-01-01

We propose several LDPC code constructions that simultaneously achieve good threshold and error floor performance. Minimum distance is shown to grow linearly with block size (similar to regular codes of variable degree at least 3) by considering ensemble average weight enumerators. Our constructions are based on projected graph, or protograph, structures that support high-speed decoder implementations. As with irregular ensembles, our constructions are sensitive to the proportion of degree-2 variable nodes. A code with too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code with too many such nodes tends to not exhibit a minimum distance that grows linearly in block length. In this paper we also show that precoding can be used to lower the threshold of regular LDPC codes. The decoding thresholds of the proposed codes, which have linearly increasing minimum distance in block size, outperform that of regular LDPC codes. Furthermore, a family of low to high rate codes, with thresholds that adhere closely to their respective channel capacity thresholds, is presented. Simulation results for a few example codes show that the proposed codes have low error floors as well as good threshold SNFt performance.

Measurement error in earnings data: Using a mixture model approach to combine survey and register data.

PubMed

Meijer, Erik; Rohwedder, Susann; Wansbeek, Tom

2012-01-01

Survey data on earnings tend to contain measurement error. Administrative data are superior in principle, but they are worthless in case of a mismatch. We develop methods for prediction in mixture factor analysis models that combine both data sources to arrive at a single earnings figure. We apply the methods to a Swedish data set. Our results show that register earnings data perform poorly if there is a (small) probability of a mismatch. Survey earnings data are more reliable, despite their measurement error. Predictors that combine both and take conditional class probabilities into account outperform all other predictors.

The Limits of Coding with Joint Constraints on Detected and Undetected Error Rates

NASA Technical Reports Server (NTRS)

Dolinar, Sam; Andrews, Kenneth; Pollara, Fabrizio; Divsalar, Dariush

2008-01-01

We develop a remarkably tight upper bound on the performance of a parameterized family of bounded angle maximum-likelihood (BA-ML) incomplete decoders. The new bound for this class of incomplete decoders is calculated from the code's weight enumerator, and is an extension of Poltyrev-type bounds developed for complete ML decoders. This bound can also be applied to bound the average performance of random code ensembles in terms of an ensemble average weight enumerator. We also formulate conditions defining a parameterized family of optimal incomplete decoders, defined to minimize both the total codeword error probability and the undetected error probability for any fixed capability of the decoder to detect errors. We illustrate the gap between optimal and BA-ML incomplete decoding via simulation of a small code.

Edge Probability and Pixel Relativity-Based Speckle Reducing Anisotropic Diffusion.

PubMed

Mishra, Deepak; Chaudhury, Santanu; Sarkar, Mukul; Soin, Arvinder Singh; Sharma, Vivek

2018-02-01

Anisotropic diffusion filters are one of the best choices for speckle reduction in the ultrasound images. These filters control the diffusion flux flow using local image statistics and provide the desired speckle suppression. However, inefficient use of edge characteristics results in either oversmooth image or an image containing misinterpreted spurious edges. As a result, the diagnostic quality of the images becomes a concern. To alleviate such problems, a novel anisotropic diffusion-based speckle reducing filter is proposed in this paper. A probability density function of the edges along with pixel relativity information is used to control the diffusion flux flow. The probability density function helps in removing the spurious edges and the pixel relativity reduces the oversmoothing effects. Furthermore, the filtering is performed in superpixel domain to reduce the execution time, wherein a minimum of 15% of the total number of image pixels can be used. For performance evaluation, 31 frames of three synthetic images and 40 real ultrasound images are used. In most of the experiments, the proposed filter shows a better performance as compared to the state-of-the-art filters in terms of the speckle region's signal-to-noise ratio and mean square error. It also shows a comparative performance for figure of merit and structural similarity measure index. Furthermore, in the subjective evaluation, performed by the expert radiologists, the proposed filter's outputs are preferred for the improved contrast and sharpness of the object boundaries. Hence, the proposed filtering framework is suitable to reduce the unwanted speckle and improve the quality of the ultrasound images.

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

PubMed Central

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km2. The lake area decreased by -9.3% at an annual rate of -53.7 km2 yr-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability. PMID:27007233

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI.

PubMed

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km(2). The lake area decreased by -9.3% at an annual rate of -53.7 km(2) yr(-1) during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.

Probabilistic confidence for decisions based on uncertain reliability estimates

NASA Astrophysics Data System (ADS)

Reid, Stuart G.

2013-05-01

Reliability assessments are commonly carried out to provide a rational basis for risk-informed decisions concerning the design or maintenance of engineering systems and structures. However, calculated reliabilities and associated probabilities of failure often have significant uncertainties associated with the possible estimation errors relative to the 'true' failure probabilities. For uncertain probabilities of failure, a measure of 'probabilistic confidence' has been proposed to reflect the concern that uncertainty about the true probability of failure could result in a system or structure that is unsafe and could subsequently fail. The paper describes how the concept of probabilistic confidence can be applied to evaluate and appropriately limit the probabilities of failure attributable to particular uncertainties such as design errors that may critically affect the dependability of risk-acceptance decisions. This approach is illustrated with regard to the dependability of structural design processes based on prototype testing with uncertainties attributable to sampling variability.

Uncertainty, imprecision, and the precautionary principle in climate change assessment.

PubMed

Borsuk, M E; Tomassini, L

2005-01-01

Statistical decision theory can provide useful support for climate change decisions made under conditions of uncertainty. However, the probability distributions used to calculate expected costs in decision theory are themselves subject to uncertainty, disagreement, or ambiguity in their specification. This imprecision can be described using sets of probability measures, from which upper and lower bounds on expectations can be calculated. However, many representations, or classes, of probability measures are possible. We describe six of the more useful classes and demonstrate how each may be used to represent climate change uncertainties. When expected costs are specified by bounds, rather than precise values, the conventional decision criterion of minimum expected cost is insufficient to reach a unique decision. Alternative criteria are required, and the criterion of minimum upper expected cost may be desirable because it is consistent with the precautionary principle. Using simple climate and economics models as an example, we determine the carbon dioxide emissions levels that have minimum upper expected cost for each of the selected classes. There can be wide differences in these emissions levels and their associated costs, emphasizing the need for care when selecting an appropriate class.

The price of complexity in financial networks

PubMed Central

May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.

2016-01-01

Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises. PMID:27555583

Gaussian Hypothesis Testing and Quantum Illumination.

PubMed

Wilde, Mark M; Tomamichel, Marco; Lloyd, Seth; Berta, Mario

2017-09-22

Quantum hypothesis testing is one of the most basic tasks in quantum information theory and has fundamental links with quantum communication and estimation theory. In this paper, we establish a formula that characterizes the decay rate of the minimal type-II error probability in a quantum hypothesis test of two Gaussian states given a fixed constraint on the type-I error probability. This formula is a direct function of the mean vectors and covariance matrices of the quantum Gaussian states in question. We give an application to quantum illumination, which is the task of determining whether there is a low-reflectivity object embedded in a target region with a bright thermal-noise bath. For the asymmetric-error setting, we find that a quantum illumination transmitter can achieve an error probability exponent stronger than a coherent-state transmitter of the same mean photon number, and furthermore, that it requires far fewer trials to do so. This occurs when the background thermal noise is either low or bright, which means that a quantum advantage is even easier to witness than in the symmetric-error setting because it occurs for a larger range of parameters. Going forward from here, we expect our formula to have applications in settings well beyond those considered in this paper, especially to quantum communication tasks involving quantum Gaussian channels.

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Network problem threshold

NASA Technical Reports Server (NTRS)

Gejji, Raghvendra, R.

1992-01-01

Network transmission errors such as collisions, CRC errors, misalignment, etc. are statistical in nature. Although errors can vary randomly, a high level of errors does indicate specific network problems, e.g. equipment failure. In this project, we have studied the random nature of collisions theoretically as well as by gathering statistics, and established a numerical threshold above which a network problem is indicated with high probability.

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

PubMed Central

Crawford, Forrest W.; Suchard, Marc A.

2011-01-01

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with n current particles, a new particle is born with instantaneous rate λn and a particle dies with instantaneous rate μn. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics. PMID:21984359

Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

NASA Technical Reports Server (NTRS)

Crosson, William L.; Duchon, Claude E.; Raghavan, Ravikumar; Goodman, Steven J.

1996-01-01

Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are discussed.

Probablilistic evaluation of earthquake detection and location capability for Illinois, Indiana, Kentucky, Ohio, and West Virginia

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

Mauk, F.J.; Christensen, D.H.

1980-09-01

Probabilistic estimations of earthquake detection and location capabilities for the states of Illinois, Indiana, Kentucky, Ohio and West Virginia are presented in this document. The algorithm used in these epicentrality and minimum-magnitude estimations is a version of the program NETWORTH by Wirth, Blandford, and Husted (DARPA Order No. 2551, 1978) which was modified for local array evaluation at the University of Michigan Seismological Observatory. Estimations of earthquake detection capability for the years 1970 and 1980 are presented in four regional minimum m/sub b/ magnitude contour maps. Regional 90% confidence error ellipsoids are included for m/sub b/ magnitude events from 2.0more » through 5.0 at 0.5 m/sub b/ unit increments. The close agreement between these predicted epicentral 90% confidence estimates and the calculated error ellipses associated with actual earthquakes within the studied region suggest that these error determinations can be used to estimate the reliability of epicenter location. 8 refs., 14 figs., 2 tabs.« less

Advancements in dynamic kill calculations for blowout wells

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

Kouba, G.E.; MacDougall, G.R.; Schumacher, B.W.

1993-09-01

This paper addresses the development, interpretation, and use of dynamic kill equations. To this end, three simple calculation techniques are developed for determining the minimum dynamic kill rate. Two techniques contain only single-phase calculations and are independent of reservoir inflow performance. Despite these limitations, these two methods are useful for bracketing the minimum flow rates necessary to kill a blowing well. For the third technique, a simplified mechanistic multiphase-flow model is used to determine a most-probable minimum kill rate.

Hybrid computer technique yields random signal probability distributions

NASA Technical Reports Server (NTRS)

Cameron, W. D.

1965-01-01

Hybrid computer determines the probability distributions of instantaneous and peak amplitudes of random signals. This combined digital and analog computer system reduces the errors and delays of manual data analysis.

In Search of Grid Converged Solutions

NASA Technical Reports Server (NTRS)

Lockard, David P.

2010-01-01

Assessing solution error continues to be a formidable task when numerically solving practical flow problems. Currently, grid refinement is the primary method used for error assessment. The minimum grid spacing requirements to achieve design order accuracy for a structured-grid scheme are determined for several simple examples using truncation error evaluations on a sequence of meshes. For certain methods and classes of problems, obtaining design order may not be sufficient to guarantee low error. Furthermore, some schemes can require much finer meshes to obtain design order than would be needed to reduce the error to acceptable levels. Results are then presented from realistic problems that further demonstrate the challenges associated with using grid refinement studies to assess solution accuracy.

Floating-point system quantization errors in digital control systems

NASA Technical Reports Server (NTRS)

Phillips, C. L.

1973-01-01

The results are reported of research into the effects on system operation of signal quantization in a digital control system. The investigation considered digital controllers (filters) operating in floating-point arithmetic in either open-loop or closed-loop systems. An error analysis technique is developed, and is implemented by a digital computer program that is based on a digital simulation of the system. As an output the program gives the programing form required for minimum system quantization errors (either maximum of rms errors), and the maximum and rms errors that appear in the system output for a given bit configuration. The program can be integrated into existing digital simulations of a system.

A MATLAB implementation of the minimum relative entropy method for linear inverse problems

NASA Astrophysics Data System (ADS)

Neupauer, Roseanna M.; Borchers, Brian

2001-08-01

The minimum relative entropy (MRE) method can be used to solve linear inverse problems of the form Gm= d, where m is a vector of unknown model parameters and d is a vector of measured data. The MRE method treats the elements of m as random variables, and obtains a multivariate probability density function for m. The probability density function is constrained by prior information about the upper and lower bounds of m, a prior expected value of m, and the measured data. The solution of the inverse problem is the expected value of m, based on the derived probability density function. We present a MATLAB implementation of the MRE method. Several numerical issues arise in the implementation of the MRE method and are discussed here. We present the source history reconstruction problem from groundwater hydrology as an example of the MRE implementation.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Type-II generalized family-wise error rate formulas with application to sample size determination.

PubMed

Delorme, Phillipe; de Micheaux, Pierre Lafaye; Liquet, Benoit; Riou, Jérémie

2016-07-20

Multiple endpoints are increasingly used in clinical trials. The significance of some of these clinical trials is established if at least r null hypotheses are rejected among m that are simultaneously tested. The usual approach in multiple hypothesis testing is to control the family-wise error rate, which is defined as the probability that at least one type-I error is made. More recently, the q-generalized family-wise error rate has been introduced to control the probability of making at least q false rejections. For procedures controlling this global type-I error rate, we define a type-II r-generalized family-wise error rate, which is directly related to the r-power defined as the probability of rejecting at least r false null hypotheses. We obtain very general power formulas that can be used to compute the sample size for single-step and step-wise procedures. These are implemented in our R package rPowerSampleSize available on the CRAN, making them directly available to end users. Complexities of the formulas are presented to gain insight into computation time issues. Comparison with Monte Carlo strategy is also presented. We compute sample sizes for two clinical trials involving multiple endpoints: one designed to investigate the effectiveness of a drug against acute heart failure and the other for the immunogenicity of a vaccine strategy against pneumococcus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Multiple symbol partially coherent detection of MPSK

NASA Technical Reports Server (NTRS)

Simon, M. K.; Divsalar, D.

1992-01-01

It is shown that by using the known (or estimated) value of carrier tracking loop signal to noise ratio (SNR) in the decision metric, it is possible to improve the error probability performance of a partially coherent multiple phase-shift-keying (MPSK) system relative to that corresponding to the commonly used ideal coherent decision rule. Using a maximum-likeihood approach, an optimum decision metric is derived and shown to take the form of a weighted sum of the ideal coherent decision metric (i.e., correlation) and the noncoherent decision metric which is optimum for differential detection of MPSK. The performance of a receiver based on this optimum decision rule is derived and shown to provide continued improvement with increasing length of observation interval (data symbol sequence length). Unfortunately, increasing the observation length does not eliminate the error floor associated with the finite loop SNR. Nevertheless, in the limit of infinite observation length, the average error probability performance approaches the algebraic sum of the error floor and the performance of ideal coherent detection, i.e., at any error probability above the error floor, there is no degradation due to the partial coherence. It is shown that this limiting behavior is virtually achievable with practical size observation lengths. Furthermore, the performance is quite insensitive to mismatch between the estimate of loop SNR (e.g., obtained from measurement) fed to the decision metric and its true value. These results may be of use in low-cost Earth-orbiting or deep-space missions employing coded modulations.

Fire behavior simulation in Mediterranean forests using the minimum travel time algorithm

Treesearch

Kostas Kalabokidis; Palaiologos Palaiologou; Mark A. Finney

2014-01-01

Recent large wildfires in Greece exemplify the need for pre-fire burn probability assessment and possible landscape fire flow estimation to enhance fire planning and resource allocation. The Minimum Travel Time (MTT) algorithm, incorporated as FlamMap's version five module, provide valuable fire behavior functions, while enabling multi-core utilization for the...

Low power and type II errors in recent ophthalmology research.

PubMed

Khan, Zainab; Milko, Jordan; Iqbal, Munir; Masri, Moness; Almeida, David R P

2016-10-01

To investigate the power of unpaired t tests in prospective, randomized controlled trials when these tests failed to detect a statistically significant difference and to determine the frequency of type II errors. Systematic review and meta-analysis. We examined all prospective, randomized controlled trials published between 2010 and 2012 in 4 major ophthalmology journals (Archives of Ophthalmology, British Journal of Ophthalmology, Ophthalmology, and American Journal of Ophthalmology). Studies that used unpaired t tests were included. Power was calculated using the number of subjects in each group, standard deviations, and α = 0.05. The difference between control and experimental means was set to be (1) 20% and (2) 50% of the absolute value of the control's initial conditions. Power and Precision version 4.0 software was used to carry out calculations. Finally, the proportion of articles with type II errors was calculated. β = 0.3 was set as the largest acceptable value for the probability of type II errors. In total, 280 articles were screened. Final analysis included 50 prospective, randomized controlled trials using unpaired t tests. The median power of tests to detect a 50% difference between means was 0.9 and was the same for all 4 journals regardless of the statistical significance of the test. The median power of tests to detect a 20% difference between means ranged from 0.26 to 0.9 for the 4 journals. The median power of these tests to detect a 50% and 20% difference between means was 0.9 and 0.5 for tests that did not achieve statistical significance. A total of 14% and 57% of articles with negative unpaired t tests contained results with β > 0.3 when power was calculated for differences between means of 50% and 20%, respectively. A large portion of studies demonstrate high probabilities of type II errors when detecting small differences between means. The power to detect small difference between means varies across journals. It is, therefore, worthwhile for authors to mention the minimum clinically important difference for individual studies. Journals can consider publishing statistical guidelines for authors to use. Day-to-day clinical decisions rely heavily on the evidence base formed by the plethora of studies available to clinicians. Prospective, randomized controlled clinical trials are highly regarded as a robust study and are used to make important clinical decisions that directly affect patient care. The quality of study designs and statistical methods in major clinical journals is improving overtime, 1 and researchers and journals are being more attentive to statistical methodologies incorporated by studies. The results of well-designed ophthalmic studies with robust methodologies, therefore, have the ability to modify the ways in which diseases are managed. Copyright © 2016 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Measurement uncertainty evaluation of conicity error inspected on CMM

NASA Astrophysics Data System (ADS)

Wang, Dongxia; Song, Aiguo; Wen, Xiulan; Xu, Youxiong; Qiao, Guifang

2016-01-01

The cone is widely used in mechanical design for rotation, centering and fixing. Whether the conicity error can be measured and evaluated accurately will directly influence its assembly accuracy and working performance. According to the new generation geometrical product specification(GPS), the error and its measurement uncertainty should be evaluated together. The mathematical model of the minimum zone conicity error is established and an improved immune evolutionary algorithm(IIEA) is proposed to search for the conicity error. In the IIEA, initial antibodies are firstly generated by using quasi-random sequences and two kinds of affinities are calculated. Then, each antibody clone is generated and they are self-adaptively mutated so as to maintain diversity. Similar antibody is suppressed and new random antibody is generated. Because the mathematical model of conicity error is strongly nonlinear and the input quantities are not independent, it is difficult to use Guide to the expression of uncertainty in the measurement(GUM) method to evaluate measurement uncertainty. Adaptive Monte Carlo method(AMCM) is proposed to estimate measurement uncertainty in which the number of Monte Carlo trials is selected adaptively and the quality of the numerical results is directly controlled. The cone parts was machined on lathe CK6140 and measured on Miracle NC 454 Coordinate Measuring Machine(CMM). The experiment results confirm that the proposed method not only can search for the approximate solution of the minimum zone conicity error(MZCE) rapidly and precisely, but also can evaluate measurement uncertainty and give control variables with an expected numerical tolerance. The conicity errors computed by the proposed method are 20%-40% less than those computed by NC454 CMM software and the evaluation accuracy improves significantly.

Probability Theory, Not the Very Guide of Life

ERIC Educational Resources Information Center

Juslin, Peter; Nilsson, Hakan; Winman, Anders

2009-01-01

Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical demonstrations of violations of this norm include the conjunction error and base-rate neglect. Many of these phenomena require multiplicative probability integration, whereas people seem more inclined to linear additive…

Experimental study on an FBG strain sensor

NASA Astrophysics Data System (ADS)

Liu, Hong-lin; Zhu, Zheng-wei; Zheng, Yong; Liu, Bang; Xiao, Feng

2018-01-01

Landslides and other geological disasters occur frequently and often cause high financial and humanitarian cost. The real-time, early-warning monitoring of landslides has important significance in reducing casualties and property losses. In this paper, by taking the high initial precision and high sensitivity advantage of FBG, an FBG strain sensor is designed combining FBGs with inclinometer. The sensor was regarded as a cantilever beam with one end fixed. According to the anisotropic material properties of the inclinometer, a theoretical formula between the FBG wavelength and the deflection of the sensor was established using the elastic mechanics principle. Accuracy of the formula established had been verified through laboratory calibration testing and model slope monitoring experiments. The displacement of landslide could be calculated by the established theoretical formula using the changing values of FBG central wavelength obtained by the demodulation instrument remotely. Results showed that the maximum error at different heights was 9.09%; the average of the maximum error was 6.35%, and its corresponding variance was 2.12; the minimum error was 4.18%; the average of the minimum error was 5.99%, and its corresponding variance was 0.50. The maximum error of the theoretical and the measured displacement decrease gradually, and the variance of the error also decreases gradually. This indicates that the theoretical results are more and more reliable. It also shows that the sensor and the theoretical formula established in this paper can be used for remote, real-time, high precision and early warning monitoring of the slope.

Development of a Methodology to Optimally Allocate Visual Inspection Time

DTIC Science & Technology

1989-06-01

Model and then takes into account the costs of the errors. The purpose of the Alternative Model is to not make 104 costly mistakes while meeting the...James Buck, and Virgil Anderson, AIIE Transactions, Volume 11, No.4, December 1979. 26. "Inspection of Sheet Materials - Model and Data", Colin G. Drury ...worker error, the probability of inspector error, and the cost of system error. Paired comparisons of error phenomena from operational personnel are

Discrepancy-based error estimates for Quasi-Monte Carlo III. Error distributions and central limits

NASA Astrophysics Data System (ADS)

Hoogland, Jiri; Kleiss, Ronald

1997-04-01

In Quasi-Monte Carlo integration, the integration error is believed to be generally smaller than in classical Monte Carlo with the same number of integration points. Using an appropriate definition of an ensemble of quasi-random point sets, we derive various results on the probability distribution of the integration error, which can be compared to the standard Central Limit Theorem for normal stochastic sampling. In many cases, a Gaussian error distribution is obtained.

On the Discriminant Analysis in the 2-Populations Case

NASA Astrophysics Data System (ADS)

Rublík, František

2008-01-01

The empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule.

Optimizing occupancy surveys by maximizing detection probability: application to amphibian monitoring in the Mediterranean region.

PubMed

Petitot, Maud; Manceau, Nicolas; Geniez, Philippe; Besnard, Aurélien

2014-09-01

Setting up effective conservation strategies requires the precise determination of the targeted species' distribution area and, if possible, its local abundance. However, detection issues make these objectives complex for most vertebrates. The detection probability is usually <1 and is highly dependent on species phenology and other environmental variables. The aim of this study was to define an optimized survey protocol for the Mediterranean amphibian community, that is, to determine the most favorable periods and the most effective sampling techniques for detecting all species present on a site in a minimum number of field sessions and a minimum amount of prospecting effort. We visited 49 ponds located in the Languedoc region of southern France on four occasions between February and June 2011. Amphibians were detected using three methods: nighttime call count, nighttime visual encounter, and daytime netting. The detection nondetection data obtained was then modeled using site-occupancy models. The detection probability of amphibians sharply differed between species, the survey method used and the date of the survey. These three covariates also interacted. Thus, a minimum of three visits spread over the breeding season, using a combination of all three survey methods, is needed to reach a 95% detection level for all species in the Mediterranean region. Synthesis and applications: detection nondetection surveys combined to site occupancy modeling approach are powerful methods that can be used to estimate the detection probability and to determine the prospecting effort necessary to assert that a species is absent from a site.

Nonparametric probability density estimation by optimization theoretic techniques

NASA Technical Reports Server (NTRS)

Scott, D. W.

1976-01-01

Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.

Conflict Probability Estimation for Free Flight

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Erzberger, Heinz

1996-01-01

The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.

The Laplace method for probability measures in Banach spaces

NASA Astrophysics Data System (ADS)

Piterbarg, V. I.; Fatalov, V. R.

1995-12-01

Contents §1. Introduction Chapter I. Asymptotic analysis of continual integrals in Banach space, depending on a large parameter §2. The large deviation principle and logarithmic asymptotics of continual integrals §3. Exact asymptotics of Gaussian integrals in Banach spaces: the Laplace method 3.1. The Laplace method for Gaussian integrals taken over the whole Hilbert space: isolated minimum points ([167], I) 3.2. The Laplace method for Gaussian integrals in Hilbert space: the manifold of minimum points ([167], II) 3.3. The Laplace method for Gaussian integrals in Banach space ([90], [174], [176]) 3.4. Exact asymptotics of large deviations of Gaussian norms §4. The Laplace method for distributions of sums of independent random elements with values in Banach space 4.1. The case of a non-degenerate minimum point ([137], I) 4.2. A degenerate isolated minimum point and the manifold of minimum points ([137], II) §5. Further examples 5.1. The Laplace method for the local time functional of a Markov symmetric process ([217]) 5.2. The Laplace method for diffusion processes, a finite number of non-degenerate minimum points ([116]) 5.3. Asymptotics of large deviations for Brownian motion in the Hölder norm 5.4. Non-asymptotic expansion of a strong stable law in Hilbert space ([41]) Chapter II. The double sum method - a version of the Laplace method in the space of continuous functions §6. Pickands' method of double sums 6.1. General situations 6.2. Asymptotics of the distribution of the maximum of a Gaussian stationary process 6.3. Asymptotics of the probability of a large excursion of a Gaussian non-stationary process §7. Probabilities of large deviations of trajectories of Gaussian fields 7.1. Homogeneous fields and fields with constant dispersion 7.2. Finitely many maximum points of dispersion 7.3. Manifold of maximum points of dispersion 7.4. Asymptotics of distributions of maxima of Wiener fields §8. Exact asymptotics of large deviations of the norm of Gaussian vectors and processes with values in the spaces L_k^p and l^2. Gaussian fields with the set of parameters in Hilbert space 8.1 Exact asymptotics of the distribution of the l_k^p-norm of a Gaussian finite-dimensional vector with dependent coordinates, p > 1 8.2. Exact asymptotics of probabilities of high excursions of trajectories of processes of type \\chi^2 8.3. Asymptotics of the probabilities of large deviations of Gaussian processes with a set of parameters in Hilbert space [74] 8.4. Asymptotics of distributions of maxima of the norms of l^2-valued Gaussian processes 8.5. Exact asymptotics of large deviations for the l^2-valued Ornstein-Uhlenbeck process Bibliography

Memorabeatlia: a naturalistic study of long-term memory.

PubMed

Hyman, I E; Rubin, D C

1990-03-01

Seventy-six undergraduates were given the titles and first lines of Beatles' songs and asked to recall the songs. Seven hundred and four different undergraduates were cued with one line from each of 25 Beatles' songs and asked to recall the title. The probability of recalling a line was best predicted by the number of times a line was repeated in the song and how early the line first appeared in the song. The probability of cuing to the title was best predicted by whether the line shared words with the title. Although the subjects recalled only 21% of the lines, there were very few errors in recall, and the errors rarely violated the rhythmic, poetic, or thematic constraints of the songs. Acting together, these constraints can account for the near verbatim recall observed. Fourteen subjects, who transcribed one song, made fewer and different errors than the subjects who had recalled the song, indicating that the errors in recall were not primarily the result of errors in encoding.

The transition from the open minimum to the ring minimum on the ground state and on the lowest excited state of like symmetry in ozone: A configuration interaction study

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

Theis, Daniel; Windus, Theresa L.; Ruedenberg, Klaus

The metastable ring structure of the ozone 1{sup 1}A{sub 1} ground state, which theoretical calculations have shown to exist, has so far eluded experimental detection. An accurate prediction for the energy difference between this isomer and the lower open structure is therefore of interest, as is a prediction for the isomerization barrier between them, which results from interactions between the lowest two {sup 1}A{sub 1} states. In the present work, valence correlated energies of the 1{sup 1}A{sub 1} state and the 2{sup 1}A{sub 1} state were calculated at the 1{sup 1}A{sub 1} open minimum, the 1{sup 1}A{sub 1} ring minimum,more » the transition state between these two minima, the minimum of the 2{sup 1}A{sub 1} state, and the conical intersection between the two states. The geometries were determined at the full-valence multi-configuration self-consistent-field level. Configuration interaction (CI) expansions up to quadruple excitations were calculated with triple-zeta atomic basis sets. The CI expansions based on eight different reference configuration spaces were explored. To obtain some of the quadruple excitation energies, the method of Correlation Energy Extrapolation by Intrinsic Scaling was generalized to the simultaneous extrapolation for two states. This extrapolation method was shown to be very accurate. On the other hand, none of the CI expansions were found to have converged to millihartree (mh) accuracy at the quadruple excitation level. The data suggest that convergence to mh accuracy is probably attained at the sextuple excitation level. On the 1{sup 1}A{sub 1} state, the present calculations yield the estimates of (ring minimum—open minimum) ∼45–50 mh and (transition state—open minimum) ∼85–90 mh. For the (2{sup 1}A{sub 1}–{sup 1}A{sub 1}) excitation energy, the estimate of ∼130–170 mh is found at the open minimum and 270–310 mh at the ring minimum. At the transition state, the difference (2{sup 1}A{sub 1}–{sup 1}A{sub 1}) is found to be between 1 and 10 mh. The geometry of the transition state on the 1{sup 1}A{sub 1} surface and that of the minimum on the 2{sup 1}A{sub 1} surface nearly coincide. More accurate predictions of the energy differences also require CI expansions to at least sextuple excitations with respect to the valence space. For every wave function considered, the omission of the correlations of the 2s oxygen orbitals, which is a widely used approximation, was found to cause errors of about ±10 mh with respect to the energy differences.« less

The minimum area requirements (MAR) for giant panda: an empirical study

PubMed Central

Qing, Jing; Yang, Zhisong; He, Ke; Zhang, Zejun; Gu, Xiaodong; Yang, Xuyu; Zhang, Wen; Yang, Biao; Qi, Dunwu; Dai, Qiang

2016-01-01

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population’s long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km2 based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive. PMID:27929520

The minimum area requirements (MAR) for giant panda: an empirical study.

PubMed

Qing, Jing; Yang, Zhisong; He, Ke; Zhang, Zejun; Gu, Xiaodong; Yang, Xuyu; Zhang, Wen; Yang, Biao; Qi, Dunwu; Dai, Qiang

2016-12-08

Habitat fragmentation can reduce population viability, especially for area-sensitive species. The Minimum Area Requirements (MAR) of a population is the area required for the population's long-term persistence. In this study, the response of occupancy probability of giant pandas against habitat patch size was studied in five of the six mountain ranges inhabited by giant panda, which cover over 78% of the global distribution of giant panda habitat. The probability of giant panda occurrence was positively associated with habitat patch area, and the observed increase in occupancy probability with patch size was higher than that due to passive sampling alone. These results suggest that the giant panda is an area-sensitive species. The MAR for giant panda was estimated to be 114.7 km 2 based on analysis of its occupancy probability. Giant panda habitats appear more fragmented in the three southern mountain ranges, while they are large and more continuous in the other two. Establishing corridors among habitat patches can mitigate habitat fragmentation, but expanding habitat patch sizes is necessary in mountain ranges where fragmentation is most intensive.

Optimizer convergence and local minima errors and their clinical importance

NASA Astrophysics Data System (ADS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R.

2003-09-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Optimizer convergence and local minima errors and their clinical importance.

PubMed

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-09-07

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Fusion of Scores in a Detection Context Based on Alpha Integration.

PubMed

Soriano, Antonio; Vergara, Luis; Ahmed, Bouziane; Salazar, Addisson

2015-09-01

We present a new method for fusing scores corresponding to different detectors (two-hypotheses case). It is based on alpha integration, which we have adapted to the detection context. Three optimization methods are presented: least mean square error, maximization of the area under the ROC curve, and minimization of the probability of error. Gradient algorithms are proposed for the three methods. Different experiments with simulated and real data are included. Simulated data consider the two-detector case to illustrate the factors influencing alpha integration and demonstrate the improvements obtained by score fusion with respect to individual detector performance. Two real data cases have been considered. In the first, multimodal biometric data have been processed. This case is representative of scenarios in which the probability of detection is to be maximized for a given probability of false alarm. The second case is the automatic analysis of electroencephalogram and electrocardiogram records with the aim of reproducing the medical expert detections of arousal during sleeping. This case is representative of scenarios in which probability of error is to be minimized. The general superior performance of alpha integration verifies the interest of optimizing the fusing parameters.

Learn-as-you-go acceleration of cosmological parameter estimates

NASA Astrophysics Data System (ADS)

Aslanyan, Grigor; Easther, Richard; Price, Layne C.

2015-09-01

Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitly describe and model the emulation error and show how this can be propagated into the posterior probabilities. We apply these techniques to the Planck likelihood and the calculation of ΛCDM posterior probabilities. The computation is significantly accelerated without a pre-defined training set and uncertainties in the posterior probabilities are subdominant to statistical fluctuations. We have obtained a speedup factor of 6.5 for Metropolis-Hastings and 3.5 for nested sampling. Finally, we discuss the general requirements for a credible error model and show how to update them on-the-fly.

Learn-as-you-go acceleration of cosmological parameter estimates

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

Aslanyan, Grigor; Easther, Richard; Price, Layne C., E-mail: g.aslanyan@auckland.ac.nz, E-mail: r.easther@auckland.ac.nz, E-mail: lpri691@aucklanduni.ac.nz

2015-09-01

Cosmological analyses can be accelerated by approximating slow calculations using a training set, which is either precomputed or generated dynamically. However, this approach is only safe if the approximations are well understood and controlled. This paper surveys issues associated with the use of machine-learning based emulation strategies for accelerating cosmological parameter estimation. We describe a learn-as-you-go algorithm that is implemented in the Cosmo++ code and (1) trains the emulator while simultaneously estimating posterior probabilities; (2) identifies unreliable estimates, computing the exact numerical likelihoods if necessary; and (3) progressively learns and updates the error model as the calculation progresses. We explicitlymore » describe and model the emulation error and show how this can be propagated into the posterior probabilities. We apply these techniques to the Planck likelihood and the calculation of ΛCDM posterior probabilities. The computation is significantly accelerated without a pre-defined training set and uncertainties in the posterior probabilities are subdominant to statistical fluctuations. We have obtained a speedup factor of 6.5 for Metropolis-Hastings and 3.5 for nested sampling. Finally, we discuss the general requirements for a credible error model and show how to update them on-the-fly.« less

Noise Estimation and Adaptive Encoding for Asymmetric Quantum Error Correcting Codes

NASA Astrophysics Data System (ADS)

Florjanczyk, Jan; Brun, Todd; CenterQuantum Information Science; Technology Team

We present a technique that improves the performance of asymmetric quantum error correcting codes in the presence of biased qubit noise channels. Our study is motivated by considering what useful information can be learned from the statistics of syndrome measurements in stabilizer quantum error correcting codes (QECC). We consider the case of a qubit dephasing channel where the dephasing axis is unknown and time-varying. We are able to estimate the dephasing angle from the statistics of the standard syndrome measurements used in stabilizer QECC's. We use this estimate to rotate the computational basis of the code in such a way that the most likely type of error is covered by the highest distance of the asymmetric code. In particular, we use the [ [ 15 , 1 , 3 ] ] shortened Reed-Muller code which can correct one phase-flip error but up to three bit-flip errors. In our simulations, we tune the computational basis to match the estimated dephasing axis which in turn leads to a decrease in the probability of a phase-flip error. With a sufficiently accurate estimate of the dephasing axis, our memory's effective error is dominated by the much lower probability of four bit-flips. Aro MURI Grant No. W911NF-11-1-0268.

A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

PubMed

Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

2014-07-31

In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly.

A feasibility study in adapting Shamos Bickel and Hodges Lehman estimator into T-Method for normalization

NASA Astrophysics Data System (ADS)

Harudin, N.; Jamaludin, K. R.; Muhtazaruddin, M. Nabil; Ramlie, F.; Muhamad, Wan Zuki Azman Wan

2018-03-01

T-Method is one of the techniques governed under Mahalanobis Taguchi System that developed specifically for multivariate data predictions. Prediction using T-Method is always possible even with very limited sample size. The user of T-Method required to clearly understanding the population data trend since this method is not considering the effect of outliers within it. Outliers may cause apparent non-normality and the entire classical methods breakdown. There exist robust parameter estimate that provide satisfactory results when the data contain outliers, as well as when the data are free of them. The robust parameter estimates of location and scale measure called Shamos Bickel (SB) and Hodges Lehman (HL) which are used as a comparable method to calculate the mean and standard deviation of classical statistic is part of it. Embedding these into T-Method normalize stage feasibly help in enhancing the accuracy of the T-Method as well as analysing the robustness of T-method itself. However, the result of higher sample size case study shows that T-method is having lowest average error percentages (3.09%) on data with extreme outliers. HL and SB is having lowest error percentages (4.67%) for data without extreme outliers with minimum error differences compared to T-Method. The error percentages prediction trend is vice versa for lower sample size case study. The result shows that with minimum sample size, which outliers always be at low risk, T-Method is much better on that, while higher sample size with extreme outliers, T-Method as well show better prediction compared to others. For the case studies conducted in this research, it shows that normalization of T-Method is showing satisfactory results and it is not feasible to adapt HL and SB or normal mean and standard deviation into it since it’s only provide minimum effect of percentages errors. Normalization using T-method is still considered having lower risk towards outlier’s effect.

Multiple-rule bias in the comparison of classification rules

PubMed Central

Yousefi, Mohammadmahdi R.; Hua, Jianping; Dougherty, Edward R.

2011-01-01

Motivation: There is growing discussion in the bioinformatics community concerning overoptimism of reported results. Two approaches contributing to overoptimism in classification are (i) the reporting of results on datasets for which a proposed classification rule performs well and (ii) the comparison of multiple classification rules on a single dataset that purports to show the advantage of a certain rule. Results: This article provides a careful probabilistic analysis of the second issue and the ‘multiple-rule bias’, resulting from choosing a classification rule having minimum estimated error on the dataset. It quantifies this bias corresponding to estimating the expected true error of the classification rule possessing minimum estimated error and it characterizes the bias from estimating the true comparative advantage of the chosen classification rule relative to the others by the estimated comparative advantage on the dataset. The analysis is applied to both synthetic and real data using a number of classification rules and error estimators. Availability: We have implemented in C code the synthetic data distribution model, classification rules, feature selection routines and error estimation methods. The code for multiple-rule analysis is implemented in MATLAB. The source code is available at http://gsp.tamu.edu/Publications/supplementary/yousefi11a/. Supplementary simulation results are also included. Contact: edward@ece.tamu.edu Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:21546390

An all digital phase locked loop for synchronization of a sinusoidal signal embedded in white Gaussian noise

NASA Technical Reports Server (NTRS)

Reddy, C. P.; Gupta, S. C.

1973-01-01

An all digital phase locked loop which tracks the phase of the incoming sinusoidal signal once per carrier cycle is proposed. The different elements and their functions and the phase lock operation are explained in detail. The nonlinear difference equations which govern the operation of the digital loop when the incoming signal is embedded in white Gaussian noise are derived, and a suitable model is specified. The performance of the digital loop is considered for the synchronization of a sinusoidal signal. For this, the noise term is suitably modelled which allows specification of the output probabilities for the two level quantizer in the loop at any given phase error. The loop filter considered increases the probability of proper phase correction. The phase error states in modulo two-pi forms a finite state Markov chain which enables the calculation of steady state probabilities, RMS phase error, transient response and mean time for cycle skipping.

Inference of emission rates from multiple sources using Bayesian probability theory.

PubMed

Yee, Eugene; Flesch, Thomas K

2010-03-01

The determination of atmospheric emission rates from multiple sources using inversion (regularized least-squares or best-fit technique) is known to be very susceptible to measurement and model errors in the problem, rendering the solution unusable. In this paper, a new perspective is offered for this problem: namely, it is argued that the problem should be addressed as one of inference rather than inversion. Towards this objective, Bayesian probability theory is used to estimate the emission rates from multiple sources. The posterior probability distribution for the emission rates is derived, accounting fully for the measurement errors in the concentration data and the model errors in the dispersion model used to interpret the data. The Bayesian inferential methodology for emission rate recovery is validated against real dispersion data, obtained from a field experiment involving various source-sensor geometries (scenarios) consisting of four synthetic area sources and eight concentration sensors. The recovery of discrete emission rates from three different scenarios obtained using Bayesian inference and singular value decomposition inversion are compared and contrasted.

Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error

NASA Astrophysics Data System (ADS)

Jarabo-Amores, María-Pilar; la Mata-Moya, David de; Gil-Pita, Roberto; Rosa-Zurera, Manuel

2013-12-01

The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the validity of the study.

Coherent errors in quantum error correction

NASA Astrophysics Data System (ADS)

Greenbaum, Daniel; Dutton, Zachary

Analysis of quantum error correcting (QEC) 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. We present analytic results for the logical error as a function of concatenation level and code distance for coherent errors under the repetition code. For data-only coherent errors, we find that the logical error is partially coherent and therefore non-Pauli. However, the coherent part of the error is negligible after two or more concatenation levels or at fewer than ɛ - (d - 1) error correction cycles. Here ɛ << 1 is the rotation angle error per cycle for a single physical qubit and d is the code distance. These results support the validity of modeling coherent errors using a Pauli channel under some minimum requirements for code distance and/or concatenation. We discuss extensions to imperfect syndrome extraction and implications for general QEC.

A multistate dynamic site occupancy model for spatially aggregated sessile communities

USGS Publications Warehouse

Fukaya, Keiichi; Royle, J. Andrew; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi

2017-01-01

Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations.We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error.By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account.Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.

Maximizing the probability of satisfying the clinical goals in radiation therapy treatment planning under setup uncertainty

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

Fredriksson, Albin, E-mail: albin.fredriksson@raysearchlabs.com; Hårdemark, Björn; Forsgren, Anders

2015-07-15

Purpose: This paper introduces a method that maximizes the probability of satisfying the clinical goals in intensity-modulated radiation therapy treatments subject to setup uncertainty. Methods: The authors perform robust optimization in which the clinical goals are constrained to be satisfied whenever the setup error falls within an uncertainty set. The shape of the uncertainty set is included as a variable in the optimization. The goal of the optimization is to modify the shape of the uncertainty set in order to maximize the probability that the setup error will fall within the modified set. Because the constraints enforce the clinical goalsmore » to be satisfied under all setup errors within the uncertainty set, this is equivalent to maximizing the probability of satisfying the clinical goals. This type of robust optimization is studied with respect to photon and proton therapy applied to a prostate case and compared to robust optimization using an a priori defined uncertainty set. Results: Slight reductions of the uncertainty sets resulted in plans that satisfied a larger number of clinical goals than optimization with respect to a priori defined uncertainty sets, both within the reduced uncertainty sets and within the a priori, nonreduced, uncertainty sets. For the prostate case, the plans taking reduced uncertainty sets into account satisfied 1.4 (photons) and 1.5 (protons) times as many clinical goals over the scenarios as the method taking a priori uncertainty sets into account. Conclusions: Reducing the uncertainty sets enabled the optimization to find better solutions with respect to the errors within the reduced as well as the nonreduced uncertainty sets and thereby achieve higher probability of satisfying the clinical goals. This shows that asking for a little less in the optimization sometimes leads to better overall plan quality.« less

Void Growth and Coalescence Simulations

DTIC Science & Technology

2013-08-01

distortion and damage, minimum time step, and appropriate material model parameters. Further, a temporal and spatial convergence study was used to...estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we use a Gurson model with Johnson-Cook...spatial convergence study was used to estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we

Neural self-tuning adaptive control of non-minimum phase system

NASA Technical Reports Server (NTRS)

Ho, Long T.; Bialasiewicz, Jan T.; Ho, Hai T.

1993-01-01

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity, if not unstable, closed-loop behavior. Therefore, a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

Estimates of the absolute error and a scheme for an approximate solution to scheduling problems

NASA Astrophysics Data System (ADS)

Lazarev, A. A.

2009-02-01

An approach is proposed for estimating absolute errors and finding approximate solutions to classical NP-hard scheduling problems of minimizing the maximum lateness for one or many machines and makespan is minimized. The concept of a metric (distance) between instances of the problem is introduced. The idea behind the approach is, given the problem instance, to construct another instance for which an optimal or approximate solution can be found at the minimum distance from the initial instance in the metric introduced. Instead of solving the original problem (instance), a set of approximating polynomially/pseudopolynomially solvable problems (instances) are considered, an instance at the minimum distance from the given one is chosen, and the resulting schedule is then applied to the original instance.

Optimizing probability of detection point estimate demonstration

NASA Astrophysics Data System (ADS)

Koshti, Ajay M.

2017-04-01

The paper provides discussion on optimizing probability of detection (POD) demonstration experiments using point estimate method. The optimization is performed to provide acceptable value for probability of passing demonstration (PPD) and achieving acceptable value for probability of false (POF) calls while keeping the flaw sizes in the set as small as possible. POD Point estimate method is used by NASA for qualifying special NDE procedures. The point estimate method uses binomial distribution for probability density. Normally, a set of 29 flaws of same size within some tolerance are used in the demonstration. Traditionally largest flaw size in the set is considered to be a conservative estimate of the flaw size with minimum 90% probability and 95% confidence. The flaw size is denoted as α90/95PE. The paper investigates relationship between range of flaw sizes in relation to α90, i.e. 90% probability flaw size, to provide a desired PPD. The range of flaw sizes is expressed as a proportion of the standard deviation of the probability density distribution. Difference between median or average of the 29 flaws and α90 is also expressed as a proportion of standard deviation of the probability density distribution. In general, it is concluded that, if probability of detection increases with flaw size, average of 29 flaw sizes would always be larger than or equal to α90 and is an acceptable measure of α90/95PE. If NDE technique has sufficient sensitivity and signal-to-noise ratio, then the 29 flaw-set can be optimized to meet requirements of minimum required PPD, maximum allowable POF, requirements on flaw size tolerance about mean flaw size and flaw size detectability requirements. The paper provides procedure for optimizing flaw sizes in the point estimate demonstration flaw-set.

Application of the Maximum Amplitude-Early Rise Correlation to Cycle 23

NASA Technical Reports Server (NTRS)

Willson, Robert M.; Hathaway, David H.

2004-01-01

On the basis of the maximum amplitude-early rise correlation, cycle 23 could have been predicted to be about the size of the mean cycle as early as 12 mo following cycle minimum. Indeed, estimates for the size of cycle 23 throughout its rise consistently suggested a maximum amplitude that would not differ appreciably from the mean cycle, contrary to predictions based on precursor information. Because cycle 23 s average slope during the rising portion of the solar cycle measured 2.4, computed as the difference between the conventional maximum (120.8) and minimum (8) amplitudes divided by the ascent duration in months (47), statistically speaking, it should be a cycle of shorter period. Hence, conventional sunspot minimum for cycle 24 should occur before December 2006, probably near July 2006 (+/-4 mo). However, if cycle 23 proves to be a statistical outlier, then conventional sunspot minimum for cycle 24 would be delayed until after July 2007, probably near December 2007 (+/-4 mo). In anticipation of cycle 24, a chart and table are provided for easy monitoring of the nearness and size of its maximum amplitude once onset has occurred (with respect to the mean cycle and using the updated maximum amplitude-early rise relationship).

On the Determinants of the Conjunction Fallacy: Probability versus Inductive Confirmation

ERIC Educational Resources Information Center

Tentori, Katya; Crupi, Vincenzo; Russo, Selena

2013-01-01

Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such…

Asteroid orbital error analysis: Theory and application

NASA Technical Reports Server (NTRS)

Muinonen, K.; Bowell, Edward

1992-01-01

We present a rigorous Bayesian theory for asteroid orbital error estimation in which the probability density of the orbital elements is derived from the noise statistics of the observations. For Gaussian noise in a linearized approximation the probability density is also Gaussian, and the errors of the orbital elements at a given epoch are fully described by the covariance matrix. The law of error propagation can then be applied to calculate past and future positional uncertainty ellipsoids (Cappellari et al. 1976, Yeomans et al. 1987, Whipple et al. 1991). To our knowledge, this is the first time a Bayesian approach has been formulated for orbital element estimation. In contrast to the classical Fisherian school of statistics, the Bayesian school allows a priori information to be formally present in the final estimation. However, Bayesian estimation does give the same results as Fisherian estimation when no priori information is assumed (Lehtinen 1988, and reference therein).

A Method to Estimate the Probability That Any Individual Cloud-to-Ground Lightning Stroke Was Within Any Radius of Any Point

NASA Technical Reports Server (NTRS)

Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.

2010-01-01

A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station.

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

Simonen, E.P.; Johnson, K.I.; Simonen, F.A.

The Vessel Integrity Simulation Analysis (VISA-II) code was developed to allow calculations of the failure probability of a reactor pressure vessel subject to defined pressure/temperature transients. A version of the code, revised by Pacific Northwest Laboratory for the US Nuclear Regulatory Commission, was used to evaluate the sensitivities of calculated through-wall flaw probability to material, flaw and calculational assumptions. Probabilities were more sensitive to flaw assumptions than to material or calculational assumptions. Alternative flaw assumptions changed the probabilities by one to two orders of magnitude, whereas alternative material assumptions typically changed the probabilities by a factor of two or less.more » Flaw shape, flaw through-wall position and flaw inspection were sensitivities examined. Material property sensitivities included the assumed distributions in copper content and fracture toughness. Methods of modeling flaw propagation that were evaluated included arrest/reinitiation toughness correlations, multiple toughness values along the length of a flaw, flaw jump distance for each computer simulation and added error in estimating irradiated properties caused by the trend curve correlation error.« less

The impact of registration accuracy on imaging validation study design: A novel statistical power calculation.

PubMed

Gibson, Eli; Fenster, Aaron; Ward, Aaron D

2013-10-01

Novel imaging modalities are pushing the boundaries of what is possible in medical imaging, but their signal properties are not always well understood. The evaluation of these novel imaging modalities is critical to achieving their research and clinical potential. Image registration of novel modalities to accepted reference standard modalities is an important part of characterizing the modalities and elucidating the effect of underlying focal disease on the imaging signal. The strengths of the conclusions drawn from these analyses are limited by statistical power. Based on the observation that in this context, statistical power depends in part on uncertainty arising from registration error, we derive a power calculation formula relating registration error, number of subjects, and the minimum detectable difference between normal and pathologic regions on imaging, for an imaging validation study design that accommodates signal correlations within image regions. Monte Carlo simulations were used to evaluate the derived models and test the strength of their assumptions, showing that the model yielded predictions of the power, the number of subjects, and the minimum detectable difference of simulated experiments accurate to within a maximum error of 1% when the assumptions of the derivation were met, and characterizing sensitivities of the model to violations of the assumptions. The use of these formulae is illustrated through a calculation of the number of subjects required for a case study, modeled closely after a prostate cancer imaging validation study currently taking place at our institution. The power calculation formulae address three central questions in the design of imaging validation studies: (1) What is the maximum acceptable registration error? (2) How many subjects are needed? (3) What is the minimum detectable difference between normal and pathologic image regions? Copyright © 2013 Elsevier B.V. All rights reserved.

Quasispecies dynamics on a network of interacting genotypes and idiotypes: formulation of the model

NASA Astrophysics Data System (ADS)

Barbosa, Valmir C.; Donangelo, Raul; Souza, Sergio R.

2015-01-01

A quasispecies is the stationary state of a set of interrelated genotypes that evolve according to the usual principles of selection and mutation. Quasispecies studies have for the most part concentrated on the possibility of errors during genotype replication and their role in promoting either the survival or the demise of the quasispecies. In a previous work, we introduced a network model of quasispecies dynamics, based on a single probability parameter (p) and capable of addressing several plausibility issues of previous models. Here we extend that model by pairing its network with another one aimed at modeling the dynamics of the immune system when confronted with the quasispecies. The new network is based on the idiotypic-network model of immunity and, together with the previous one, constitutes a network model of interacting genotypes and idiotypes. The resulting model requires further parameters and as a consequence leads to a vast phase space. We have focused on a particular niche in which it is possible to observe the trade-offs involved in the quasispecies' survival or destruction. Within this niche, we give simulation results that highlight some key preconditions for quasispecies survival. These include a minimum initial abundance of genotypes relative to that of the idiotypes and a minimum value of p. The latter, in particular, is to be contrasted with the stand-alone quasispecies network of our previous work, in which arbitrarily low values of p constitute a guarantee of quasispecies survival.

Error Patterns in Ordering Fractions among At-Risk Fourth-Grade Students

ERIC Educational Resources Information Center

Malone, Amelia S.; Fuchs, Lynn S.

2017-01-01

The three purposes of this study were to (a) describe fraction ordering errors among at-risk fourth grade students, (b) assess the effect of part-whole understanding and accuracy of fraction magnitude estimation on the probability of committing errors, and (c) examine the effect of students' ability to explain comparing problems on the probability…

Optimization of multimagnetometer systems on a spacecraft

NASA Technical Reports Server (NTRS)

Neubauer, F. M.

1975-01-01

The problem of optimizing the position of magnetometers along a boom of given length to yield a minimized total error is investigated. The discussion is limited to at most four magnetometers, which seems to be a practical limit due to weight, power, and financial considerations. The outlined error analysis is applied to some illustrative cases. The optimal magnetometer locations, for which the total error is minimum, are computed for given boom length, instrument errors, and very conservative magnetic field models characteristic for spacecraft with only a restricted or ineffective magnetic cleanliness program. It is shown that the error contribution by the magnetometer inaccuracy is increased as the number of magnetometers is increased, whereas the spacecraft field uncertainty is diminished by an appreciably larger amount.

Validation of the ICU-DaMa tool for automatically extracting variables for minimum dataset and quality indicators: The importance of data quality assessment.

PubMed

Sirgo, Gonzalo; Esteban, Federico; Gómez, Josep; Moreno, Gerard; Rodríguez, Alejandro; Blanch, Lluis; Guardiola, Juan José; Gracia, Rafael; De Haro, Lluis; Bodí, María

2018-04-01

Big data analytics promise insights into healthcare processes and management, improving outcomes while reducing costs. However, data quality is a major challenge for reliable results. Business process discovery techniques and an associated data model were used to develop data management tool, ICU-DaMa, for extracting variables essential for overseeing the quality of care in the intensive care unit (ICU). To determine the feasibility of using ICU-DaMa to automatically extract variables for the minimum dataset and ICU quality indicators from the clinical information system (CIS). The Wilcoxon signed-rank test and Fisher's exact test were used to compare the values extracted from the CIS with ICU-DaMa for 25 variables from all patients attended in a polyvalent ICU during a two-month period against the gold standard of values manually extracted by two trained physicians. Discrepancies with the gold standard were classified into plausibility, conformance, and completeness errors. Data from 149 patients were included. Although there were no significant differences between the automatic method and the manual method, we detected differences in values for five variables, including one plausibility error and two conformance and completeness errors. Plausibility: 1) Sex, ICU-DaMa incorrectly classified one male patient as female (error generated by the Hospital's Admissions Department). Conformance: 2) Reason for isolation, ICU-DaMa failed to detect a human error in which a professional misclassified a patient's isolation. 3) Brain death, ICU-DaMa failed to detect another human error in which a professional likely entered two mutually exclusive values related to the death of the patient (brain death and controlled donation after circulatory death). Completeness: 4) Destination at ICU discharge, ICU-DaMa incorrectly classified two patients due to a professional failing to fill out the patient discharge form when thepatients died. 5) Length of continuous renal replacement therapy, data were missing for one patient because the CRRT device was not connected to the CIS. Automatic generation of minimum dataset and ICU quality indicators using ICU-DaMa is feasible. The discrepancies were identified and can be corrected by improving CIS ergonomics, training healthcare professionals in the culture of the quality of information, and using tools for detecting and correcting data errors. Copyright © 2018 Elsevier B.V. All rights reserved.

A visual detection model for DCT coefficient quantization

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Watson, Andrew B.

1994-01-01

The discrete cosine transform (DCT) is widely used in image compression and is part of the JPEG and MPEG compression standards. The degree of compression and the amount of distortion in the decompressed image are controlled by the quantization of the transform coefficients. The standards do not specify how the DCT coefficients should be quantized. One approach is to set the quantization level for each coefficient so that the quantization error is near the threshold of visibility. Results from previous work are combined to form the current best detection model for DCT coefficient quantization noise. This model predicts sensitivity as a function of display parameters, enabling quantization matrices to be designed for display situations varying in luminance, veiling light, and spatial frequency related conditions (pixel size, viewing distance, and aspect ratio). It also allows arbitrary color space directions for the representation of color. A model-based method of optimizing the quantization matrix for an individual image was developed. The model described above provides visual thresholds for each DCT frequency. These thresholds are adjusted within each block for visual light adaptation and contrast masking. For given quantization matrix, the DCT quantization errors are scaled by the adjusted thresholds to yield perceptual errors. These errors are pooled nonlinearly over the image to yield total perceptual error. With this model one may estimate the quantization matrix for a particular image that yields minimum bit rate for a given total perceptual error, or minimum perceptual error for a given bit rate. Custom matrices for a number of images show clear improvement over image-independent matrices. Custom matrices are compatible with the JPEG standard, which requires transmission of the quantization matrix.

Analysis of the PLL phase error in presence of simulated ionospheric scintillation events

NASA Astrophysics Data System (ADS)

Forte, B.

2012-01-01

The functioning of standard phase locked loops (PLL), including those used to track radio signals from Global Navigation Satellite Systems (GNSS), is based on a linear approximation which holds in presence of small phase errors. Such an approximation represents a reasonable assumption in most of the propagation channels. However, in presence of a fading channel the phase error may become large, making the linear approximation no longer valid. The PLL is then expected to operate in a non-linear regime. As PLLs are generally designed and expected to operate in their linear regime, whenever the non-linear regime comes into play, they will experience a serious limitation in their capability to track the corresponding signals. The phase error and the performance of a typical PLL embedded into a commercial multiconstellation GNSS receiver were analyzed in presence of simulated ionospheric scintillation. Large phase errors occurred during scintillation-induced signal fluctuations although cycle slips only occurred during the signal re-acquisition after a loss of lock. Losses of lock occurred whenever the signal faded below the minimumC/N0threshold allowed for tracking. The simulations were performed for different signals (GPS L1C/A, GPS L2C, GPS L5 and Galileo L1). L5 and L2C proved to be weaker than L1. It appeared evident that the conditions driving the PLL phase error in the specific case of GPS receivers in presence of scintillation-induced signal perturbations need to be evaluated in terms of the combination of the minimumC/N0 tracking threshold, lock detector thresholds, possible cycle slips in the tracking PLL and accuracy of the observables (i.e. the error propagation onto the observables stage).

14 CFR 29.1323 - Airspeed indicating system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... minimum practicable instrument calibration error when the corresponding pitot and static pressures are... pitot tube or an equivalent means of preventing malfunction due to icing. [Doc. No. 5084, 29 FR 16150...

Robustification and Optimization in Repetitive Control For Minimum Phase and Non-Minimum Phase Systems

NASA Astrophysics Data System (ADS)

Prasitmeeboon, Pitcha

Repetitive control (RC) is a control method that specifically aims to converge to zero tracking error of a control systems that execute a periodic command or have periodic disturbances of known period. It uses the error of one period back to adjust the command in the present period. In theory, RC can completely eliminate periodic disturbance effects. RC has applications in many fields such as high-precision manufacturing in robotics, computer disk drives, and active vibration isolation in spacecraft. The first topic treated in this dissertation develops several simple RC design methods that are somewhat analogous to PID controller design in classical control. From the early days of digital control, emulation methods were developed based on a Forward Rule, a Backward Rule, Tustin's Formula, a modification using prewarping, and a pole-zero mapping method. These allowed one to convert a candidate controller design to discrete time in a simple way. We investigate to what extent they can be used to simplify RC design. A particular design is developed from modification of the pole-zero mapping rules, which is simple and sheds light on the robustness of repetitive control designs. RC convergence requires less than 90 degree model phase error at all frequencies up to Nyquist. A zero-phase cutoff filter is normally used to robustify to high frequency model error when this limit is exceeded. The result is stabilization at the expense of failure to cancel errors above the cutoff. The second topic investigates a series of methods to use data to make real time updates of the frequency response model, allowing one to increase or eliminate the frequency cutoff. These include the use of a moving window employing a recursive discrete Fourier transform (DFT), and use of a real time projection algorithm from adaptive control for each frequency. The results can be used directly to make repetitive control corrections that cancel each error frequency, or they can be used to update a repetitive control FIR compensator. The aim is to reduce the final error level by using real time frequency response model updates to successively increase the cutoff frequency, each time creating the improved model needed to produce convergence zero error up to the higher cutoff. Non-minimum phase systems present a difficult design challenge to the sister field of Iterative Learning Control. The third topic investigates to what extent the same challenges appear in RC. One challenge is that the intrinsic non-minimum phase zero mapped from continuous time is close to the pole of repetitive controller at +1 creating behavior similar to pole-zero cancellation. The near pole-zero cancellation causes slow learning at DC and low frequencies. The Min-Max cost function over the learning rate is presented. The Min-Max can be reformulated as a Quadratically Constrained Linear Programming problem. This approach is shown to be an RC design approach that addresses the main challenge of non-minimum phase systems to have a reasonable learning rate at DC. Although it was illustrated that using the Min-Max objective improves learning at DC and low frequencies compared to other designs, the method requires model accuracy at high frequencies. In the real world, models usually have error at high frequencies. The fourth topic addresses how one can merge the quadratic penalty to the Min-Max cost function to increase robustness at high frequencies. The topic also considers limiting the Min-Max optimization to some frequencies interval and applying an FIR zero-phase low-pass filter to cutoff the learning for frequencies above that interval.

Bolus-dependent dosimetric effect of positioning errors for tangential scalp radiotherapy with helical tomotherapy

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

Lobb, Eric, E-mail: eclobb2@gmail.com

2014-04-01

The dosimetric effect of errors in patient position is studied on-phantom as a function of simulated bolus thickness to assess the need for bolus utilization in scalp radiotherapy with tomotherapy. A treatment plan is generated on a cylindrical phantom, mimicking a radiotherapy technique for the scalp utilizing primarily tangential beamlets. A planning target volume with embedded scalplike clinical target volumes (CTVs) is planned to a uniform dose of 200 cGy. Translational errors in phantom position are introduced in 1-mm increments and dose is recomputed from the original sinogram. For each error the maximum dose, minimum dose, clinical target dose homogeneitymore » index (HI), and dose-volume histogram (DVH) are presented for simulated bolus thicknesses from 0 to 10 mm. Baseline HI values for all bolus thicknesses were in the 5.5 to 7.0 range, increasing to a maximum of 18.0 to 30.5 for the largest positioning errors when 0 to 2 mm of bolus is used. Utilizing 5 mm of bolus resulted in a maximum HI value of 9.5 for the largest positioning errors. Using 0 to 2 mm of bolus resulted in minimum and maximum dose values of 85% to 94% and 118% to 125% of the prescription dose, respectively. When using 5 mm of bolus these values were 98.5% and 109.5%. DVHs showed minimal changes in CTV dose coverage when using 5 mm of bolus, even for the largest positioning errors. CTV dose homogeneity becomes increasingly sensitive to errors in patient position as bolus thickness decreases when treating the scalp with primarily tangential beamlets. Performing a radial expansion of the scalp CTV into 5 mm of bolus material minimizes dosimetric sensitivity to errors in patient position as large as 5 mm and is therefore recommended.« less

Learning time-dependent noise to reduce logical errors: real time error rate estimation in quantum error correction

NASA Astrophysics Data System (ADS)

Huo, Ming-Xia; Li, Ying

2017-12-01

Quantum error correction is important to quantum information processing, which allows us to reliably process information encoded in quantum error correction codes. Efficient quantum error correction benefits from the knowledge of error rates. We propose a protocol for monitoring error rates in real time without interrupting the quantum error correction. Any adaptation of the quantum error correction code or its implementation circuit is not required. The protocol can be directly applied to the most advanced quantum error correction techniques, e.g. surface code. A Gaussian processes algorithm is used to estimate and predict error rates based on error correction data in the past. We find that using these estimated error rates, the probability of error correction failures can be significantly reduced by a factor increasing with the code distance.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.; Marino, J. T., Jr.

1974-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-emperical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. Bit error probabilities for non-optimum threshold detection system were also investigated.

Threshold detection in an on-off binary communications channel with atmospheric scintillation

NASA Technical Reports Server (NTRS)

Webb, W. E.

1975-01-01

The optimum detection threshold in an on-off binary optical communications system operating in the presence of atmospheric turbulence was investigated assuming a poisson detection process and log normal scintillation. The dependence of the probability of bit error on log amplitude variance and received signal strength was analyzed and semi-empirical relationships to predict the optimum detection threshold derived. On the basis of this analysis a piecewise linear model for an adaptive threshold detection system is presented. The bit error probabilities for nonoptimum threshold detection systems were also investigated.

Objective Analysis of Oceanic Data for Coast Guard Trajectory Models Phase II

DTIC Science & Technology

1997-12-01

as outliers depends on the desired probability of false alarm, Pfa values, which is the probability of marking a valid point as an outlier. Table 2-2...constructed to minimize the mean-squared prediction error of the grid point estimate under the constraint that the estimate is unbiased . The...prediction error, e= Zl(S) _oizl(Si)+oC1iZz(S) (2.44) subject to the constraints of unbiasedness , • c/1 = 1,and (2.45) i SCC12 = 0. (2.46) Denoting

Computer program to minimize prediction error in models from experiments with 16 hypercube points and 0 to 6 center points

NASA Technical Reports Server (NTRS)

Holms, A. G.

1982-01-01

A previous report described a backward deletion procedure of model selection that was optimized for minimum prediction error and which used a multiparameter combination of the F - distribution and an order statistics distribution of Cochran's. A computer program is described that applies the previously optimized procedure to real data. The use of the program is illustrated by examples.

Predictive momentum management for a space station measurement and computation requirements

NASA Technical Reports Server (NTRS)

Adams, John Carl

1986-01-01

An analysis is made of the effects of errors and uncertainties in the predicting of disturbance torques on the peak momentum buildup on a space station. Models of the disturbance torques acting on a space station in low Earth orbit are presented, to estimate how accurately they can be predicted. An analysis of the torque and momentum buildup about the pitch axis of the Dual Keel space station configuration is formulated, and a derivation of the Average Torque Equilibrium Attitude (ATEA) is presented, for the case of no MRMS (Mobile Remote Manipulation System) motion, Y vehicle axis MRMS motion, and Z vehicle axis MRMS motion. Results showed the peak momentum buildup to be approximately 20000 N-m-s and to be relatively insensitive to errors in the predicting torque models, for Z axis motion of the MRMS was found to vary significantly with model errors, but not exceed a value of approximately 15000 N-m-s for the Y axis MRMS motion with 1 deg attitude hold error. Minimum peak disturbance momentum was found not to occur at the ATEA angle, but at a slightly smaller angle. However, this minimum peak momentum attitude was found to produce significant disturbance momentum at the end of the predicting time interval.

Construction of type-II QC-LDPC codes with fast encoding based on perfect cyclic difference sets

NASA Astrophysics Data System (ADS)

Li, Ling-xiang; Li, Hai-bing; Li, Ji-bi; Jiang, Hua

2017-09-01

In view of the problems that the encoding complexity of quasi-cyclic low-density parity-check (QC-LDPC) codes is high and the minimum distance is not large enough which leads to the degradation of the error-correction performance, the new irregular type-II QC-LDPC codes based on perfect cyclic difference sets (CDSs) are constructed. The parity check matrices of these type-II QC-LDPC codes consist of the zero matrices with weight of 0, the circulant permutation matrices (CPMs) with weight of 1 and the circulant matrices with weight of 2 (W2CMs). The introduction of W2CMs in parity check matrices makes it possible to achieve the larger minimum distance which can improve the error- correction performance of the codes. The Tanner graphs of these codes have no girth-4, thus they have the excellent decoding convergence characteristics. In addition, because the parity check matrices have the quasi-dual diagonal structure, the fast encoding algorithm can reduce the encoding complexity effectively. Simulation results show that the new type-II QC-LDPC codes can achieve a more excellent error-correction performance and have no error floor phenomenon over the additive white Gaussian noise (AWGN) channel with sum-product algorithm (SPA) iterative decoding.

Cost-effectiveness of the stream-gaging program in North Carolina

USGS Publications Warehouse

Mason, R.R.; Jackson, N.M.

1985-01-01

This report documents the results of a study of the cost-effectiveness of the stream-gaging program in North Carolina. Data uses and funding sources are identified for the 146 gaging stations currently operated in North Carolina with a budget of $777,600 (1984). As a result of the study, eleven stations are nominated for discontinuance and five for conversion from recording to partial-record status. Large parts of North Carolina 's Coastal Plain are identified as having sparse streamflow data. This sparsity should be remedied as funds become available. Efforts should also be directed toward defining the efforts of drainage improvements on local hydrology and streamflow characteristics. The average standard error of streamflow records in North Carolina is 18.6 percent. This level of accuracy could be improved without increasing cost by increasing the frequency of field visits and streamflow measurements at stations with high standard errors and reducing the frequency at stations with low standard errors. A minimum budget of $762,000 is required to operate the 146-gage program. A budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, and with the optimum allocation of field visits, the average standard error is 17.6 percent.

Cost effectiveness of the US Geological Survey's stream-gaging programs in New Hampshire and Vermont

USGS Publications Warehouse

Smath, J.A.; Blackey, F.E.

1986-01-01

Data uses and funding sources were identified for the 73 continuous stream gages currently (1984) being operated. Eight stream gages were identified as having insufficient reason to continue their operation. Parts of New Hampshire and Vermont were identified as needing additional hydrologic data. New gages should be established in these regions as funds become available. Alternative methods for providing hydrologic data at the stream gaging stations currently being operated were found to lack the accuracy that is required for their intended use. The current policy for operation of the stream gages requires a net budget of $297,000/yr. The average standard error of estimation of the streamflow records is 17.9%. This overall level of accuracy could be maintained with a budget of $285,000 if resources were redistributed among gages. Cost-effective analysis indicates that with the present budget, the average standard error could be reduced to 16.6%. A minimum budget of $278,000 is required to operate the present stream gaging program. Below this level, the gages and recorders would not receive the proper service and maintenance. At the minimum budget, the average standard error would be 20.4%. The loss of correlative data is a significant component of the error in streamflow records, especially at lower budgetary levels. (Author 's abstract)

Topology for efficient information dissemination in ad-hoc networking

NASA Technical Reports Server (NTRS)

Jennings, E.; Okino, C. M.

2002-01-01

In this paper, we explore the information dissemination problem in ad-hoc wirless networks. First, we analyze the probability of successful broadcast, assuming: the nodes are uniformly distributed, the available area has a lower bould relative to the total number of nodes, and there is zero knowledge of the overall topology of the network. By showing that the probability of such events is small, we are motivated to extract good graph topologies to minimize the overall transmissions. Three algorithms are used to generate topologies of the network with guaranteed connectivity. These are the minimum radius graph, the relative neighborhood graph and the minimum spanning tree. Our simulation shows that the relative neighborhood graph has certain good graph properties, which makes it suitable for efficient information dissemination.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Force-Time Entropy of Isometric Impulse.

PubMed

Hsieh, Tsung-Yu; Newell, Karl M

2016-01-01

The relation between force and temporal variability in discrete impulse production has been viewed as independent (R. A. Schmidt, H. Zelaznik, B. Hawkins, J. S. Frank, & J. T. Quinn, 1979 ) or dependent on the rate of force (L. G. Carlton & K. M. Newell, 1993 ). Two experiments in an isometric single finger force task investigated the joint force-time entropy with (a) fixed time to peak force and different percentages of force level and (b) fixed percentage of force level and different times to peak force. The results showed that the peak force variability increased either with the increment of force level or through a shorter time to peak force that also reduced timing error variability. The peak force entropy and entropy of time to peak force increased on the respective dimension as the parameter conditions approached either maximum force or a minimum rate of force production. The findings show that force error and timing error are dependent but complementary when considered in the same framework with the joint force-time entropy at a minimum in the middle parameter range of discrete impulse.

Geological Carbon Sequestration: A New Approach for Near-Surface Assurance Monitoring

PubMed Central

Wielopolski, Lucian

2011-01-01

There are two distinct objectives in monitoring geological carbon sequestration (GCS): Deep monitoring of the reservoir’s integrity and plume movement and near-surface monitoring (NSM) to ensure public health and the safety of the environment. However, the minimum detection limits of the current instrumentation for NSM is too high for detecting weak signals that are embedded in the background levels of the natural variations, and the data obtained represents point measurements in space and time. A new approach for NSM, based on gamma-ray spectroscopy induced by inelastic neutron scatterings (INS), offers novel and unique characteristics providing the following: (1) High sensitivity with a reducible error of measurement and detection limits, and, (2) temporal- and spatial-integration of carbon in soil that results from underground CO2 seepage. Preliminary field results validated this approach showing carbon suppression of 14% in the first year and 7% in the second year. In addition the temporal behavior of the error propagation is presented and it is shown that for a signal at the level of the minimum detection level the error asymptotically approaches 47%. PMID:21556180

Effects of structural error on the estimates of parameters of dynamical systems

NASA Technical Reports Server (NTRS)

Hadaegh, F. Y.; Bekey, G. A.

1986-01-01

In this paper, the notion of 'near-equivalence in probability' is introduced for identifying a system in the presence of several error sources. Following some basic definitions, necessary and sufficient conditions for the identifiability of parameters are given. The effects of structural error on the parameter estimates for both the deterministic and stochastic cases are considered.

Position Error Covariance Matrix Validation and Correction

NASA Technical Reports Server (NTRS)

Frisbee, Joe, Jr.

2016-01-01

In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.

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

Morley, Steven

The PyForecastTools package provides Python routines for calculating metrics for model validation, forecast verification and model comparison. For continuous predictands the package provides functions for calculating bias (mean error, mean percentage error, median log accuracy, symmetric signed bias), and for calculating accuracy (mean squared error, mean absolute error, mean absolute scaled error, normalized RMSE, median symmetric accuracy). Convenience routines to calculate the component parts (e.g. forecast error, scaled error) of each metric are also provided. To compare models the package provides: generic skill score; percent better. Robust measures of scale including median absolute deviation, robust standard deviation, robust coefficient ofmore » variation and the Sn estimator are all provided by the package. Finally, the package implements Python classes for NxN contingency tables. In the case of a multi-class prediction, accuracy and skill metrics such as proportion correct and the Heidke and Peirce skill scores are provided as object methods. The special case of a 2x2 contingency table inherits from the NxN class and provides many additional metrics for binary classification: probability of detection, probability of false detection, false alarm ration, threat score, equitable threat score, bias. Confidence intervals for many of these quantities can be calculated using either the Wald method or Agresti-Coull intervals.« less

Modeling the probability distribution of positional errors incurred by residential address geocoding.

PubMed

Zimmerman, Dale L; Fang, Xiangming; Mazumdar, Soumya; Rushton, Gerard

2007-01-10

The assignment of a point-level geocode to subjects' residences is an important data assimilation component of many geographic public health studies. Often, these assignments are made by a method known as automated geocoding, which attempts to match each subject's address to an address-ranged street segment georeferenced within a streetline database and then interpolate the position of the address along that segment. Unfortunately, this process results in positional errors. Our study sought to model the probability distribution of positional errors associated with automated geocoding and E911 geocoding. Positional errors were determined for 1423 rural addresses in Carroll County, Iowa as the vector difference between each 100%-matched automated geocode and its true location as determined by orthophoto and parcel information. Errors were also determined for 1449 60%-matched geocodes and 2354 E911 geocodes. Huge (> 15 km) outliers occurred among the 60%-matched geocoding errors; outliers occurred for the other two types of geocoding errors also but were much smaller. E911 geocoding was more accurate (median error length = 44 m) than 100%-matched automated geocoding (median error length = 168 m). The empirical distributions of positional errors associated with 100%-matched automated geocoding and E911 geocoding exhibited a distinctive Greek-cross shape and had many other interesting features that were not capable of being fitted adequately by a single bivariate normal or t distribution. However, mixtures of t distributions with two or three components fit the errors very well. Mixtures of bivariate t distributions with few components appear to be flexible enough to fit many positional error datasets associated with geocoding, yet parsimonious enough to be feasible for nascent applications of measurement-error methodology to spatial epidemiology.

An Error-Entropy Minimization Algorithm for Tracking Control of Nonlinear Stochastic Systems with Non-Gaussian Variables

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

Liu, Yunlong; Wang, Aiping; Guo, Lei

This paper presents an error-entropy minimization tracking control algorithm for a class of dynamic stochastic system. The system is represented by a set of time-varying discrete nonlinear equations with non-Gaussian stochastic input, where the statistical properties of stochastic input are unknown. By using Parzen windowing with Gaussian kernel to estimate the probability densities of errors, recursive algorithms are then proposed to design the controller such that the tracking error can be minimized. The performance of the error-entropy minimization criterion is compared with the mean-square-error minimization in the simulation results.

Impact of nonzero boresight pointing errors on the performance of a relay-assisted free-space optical communication system over exponentiated Weibull fading channels.

PubMed

Wang, Ping; Liu, Xiaoxia; Cao, Tian; Fu, Huihua; Wang, Ranran; Guo, Lixin

2016-09-20

The impact of nonzero boresight pointing errors on the system performance of decode-and-forward protocol-based multihop parallel optical wireless communication systems is studied. For the aggregated fading channel, the atmospheric turbulence is simulated by an exponentiated Weibull model, and pointing errors are described by one recently proposed statistical model including both boresight and jitter. The binary phase-shift keying subcarrier intensity modulation-based analytical average bit error rate (ABER) and outage probability expressions are achieved for a nonidentically and independently distributed system. The ABER and outage probability are then analyzed with different turbulence strengths, receiving aperture sizes, structure parameters (P and Q), jitter variances, and boresight displacements. The results show that aperture averaging offers almost the same system performance improvement with boresight included or not, despite the values of P and Q. The performance enhancement owing to the increase of cooperative path (P) is more evident with nonzero boresight than that with zero boresight (jitter only), whereas the performance deterioration because of the increasing hops (Q) with nonzero boresight is almost the same as that with zero boresight. Monte Carlo simulation is offered to verify the validity of ABER and outage probability expressions.

Genetic Algorithm-Based Motion Estimation Method using Orientations and EMGs for Robot Controls

PubMed Central

Chae, Jeongsook; Jin, Yong; Sung, Yunsick

2018-01-01

Demand for interactive wearable devices is rapidly increasing with the development of smart devices. To accurately utilize wearable devices for remote robot controls, limited data should be analyzed and utilized efficiently. For example, the motions by a wearable device, called Myo device, can be estimated by measuring its orientation, and calculating a Bayesian probability based on these orientation data. Given that Myo device can measure various types of data, the accuracy of its motion estimation can be increased by utilizing these additional types of data. This paper proposes a motion estimation method based on weighted Bayesian probability and concurrently measured data, orientations and electromyograms (EMG). The most probable motion among estimated is treated as a final estimated motion. Thus, recognition accuracy can be improved when compared to the traditional methods that employ only a single type of data. In our experiments, seven subjects perform five predefined motions. When orientation is measured by the traditional methods, the sum of the motion estimation errors is 37.3%; likewise, when only EMG data are used, the error in motion estimation by the proposed method was also 37.3%. The proposed combined method has an error of 25%. Therefore, the proposed method reduces motion estimation errors by 12%. PMID:29324641

General linear codes for fault-tolerant matrix operations on processor arrays

NASA Technical Reports Server (NTRS)

Nair, V. S. S.; Abraham, J. A.

1988-01-01

Various checksum codes have been suggested for fault-tolerant matrix computations on processor arrays. Use of these codes is limited due to potential roundoff and overflow errors. Numerical errors may also be misconstrued as errors due to physical faults in the system. In this a set of linear codes is identified which can be used for fault-tolerant matrix operations such as matrix addition, multiplication, transposition, and LU-decomposition, with minimum numerical error. Encoding schemes are given for some of the example codes which fall under the general set of codes. With the help of experiments, a rule of thumb for the selection of a particular code for a given application is derived.

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

Reactive Resonances in N+N2 Exchange Reaction

NASA Technical Reports Server (NTRS)

Wang, Dunyou; Huo, Winifred M.; Dateo, Christopher E.; Schwenke, David W.; Stallcop, James R.

2003-01-01

Rich reactive resonances are found in a 3D quantum dynamics study of the N + N2 exchange reaction using a recently developed ab initio potential energy surface. This surface is characterized by a feature in the interaction region called Lake Eyring , that is, two symmetric transition states with a shallow minimum between them. An L2 analysis of the quasibound states associated with the shallow minimum confirms that the quasibound states associated with oscillations in all three degrees of freedom in Lake Eyring are responsible for the reactive resonances in the state-to-state reaction probabilities. The quasibound states, mostly the bending motions, give rise to strong reasonance peaks, whereas other motions contribute to the bumps and shoulders in the resonance structure. The initial state reaction probability further proves that the bending motions are the dominating factors of the reaction probability and have longer life times than the stretching motions. This is the first observation of reactive resonances from a "Lake Eyring" feature in a potential energy surface.

Minimum Winfree loop determines self-sustained oscillations in excitable Erdös-Rényi random networks.

PubMed

Qian, Yu; Cui, Xiaohua; Zheng, Zhigang

2017-07-18

The investigation of self-sustained oscillations in excitable complex networks is very important in understanding various activities in brain systems, among which the exploration of the key determinants of oscillations is a challenging task. In this paper, by investigating the influence of system parameters on self-sustained oscillations in excitable Erdös-Rényi random networks (EERRNs), the minimum Winfree loop (MWL) is revealed to be the key factor in determining the emergence of collective oscillations. Specifically, the one-to-one correspondence between the optimal connection probability (OCP) and the MWL length is exposed. Moreover, many important quantities such as the lower critical connection probability (LCCP), the OCP, and the upper critical connection probability (UCCP) are determined by the MWL. Most importantly, they can be approximately predicted by the network structure analysis, which have been verified in numerical simulations. Our results will be of great importance to help us in understanding the key factors in determining persistent activities in biological systems.

Determination of vigabatrin in plasma by reversed-phase high-performance liquid chromatography.

PubMed

Tsanaclis, L M; Wicks, J; Williams, J; Richens, A

1991-05-01

A method is described for the determination of vigabatrin in 50 microliters of plasma by isocratic high-performance liquid chromatography using fluorescence detection. The procedure involves protein precipitation with methanol followed by precolumn derivatisation with o-phthaldialdehyde reagent. Separation of the derivatised vigabatrin was achieved on a Microsorb C18 column using a mobile phase of 10 mM orthophosphoric acid:acetonitrile:methanol (6:3:1) at a flow rate of 2.0 ml/min. Assay time is 15 min and chromatograms show no interference from commonly coadministered anticonvulsant drugs. The total analytical error within the range of 0.85-85 micrograms/ml was found to be 7.6% with the within-replicates error of 2.76%. The minimum detection limit was 0.08 micrograms/ml and the minimum quantitation limit was 0.54 micrograms/ml.

Metameric MIMO-OOK transmission scheme using multiple RGB LEDs.

PubMed

Bui, Thai-Chien; Cusani, Roberto; Scarano, Gaetano; Biagi, Mauro

2018-05-28

In this work, we propose a novel visible light communication (VLC) scheme utilizing multiple different red green and blue triplets each with a different emission spectrum of red, green and blue for mitigating the effect of interference due to different colors using spatial multiplexing. On-off keying modulation is considered and its effect on light emission in terms of flickering, dimming and color rendering is discussed so as to demonstrate how metameric properties have been considered. At the receiver, multiple photodiodes with color filter-tuned on each transmit light emitting diode (LED) are employed. Three different detection mechanisms of color zero forcing, minimum mean square error estimation and minimum mean square error equalization are then proposed. The system performance of the proposed scheme is evaluated both with computer simulations and tests with an Arduino board implementation.

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

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

Romero, Louis A; Mason, John J.

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

Dual tasking negatively impacts obstacle avoidance abilities in post-stroke individuals with visuospatial neglect: Task complexity matters!

PubMed

Aravind, Gayatri; Lamontagne, Anouk

2017-01-01

Persons with perceptual-attentional deficits due to visuospatial neglect (VSN) after a stroke are at a risk of collisions while walking in the presence of moving obstacles. The attentional burden of performing a dual-task may further compromise their obstacle avoidance performance, putting them at a greater risk of collisions. The objective of this study was to compare the ability of persons with (VSN+) and without VSN (VSN-) to dual task while negotiating moving obstacles. Twenty-six stroke survivors (13 VSN+, 13 VSN-) were assessed on their ability to (a) negotiate moving obstacles while walking (locomotor single task); (b) perform a pitch-discrimination task (cognitive single task) and (c) simultaneously perform the walking and cognitive tasks (dual task). We compared the groups on locomotor (collision rates, minimum distance from obstacle and onset of strategies) and cognitive (error rates) outcomes. For both single and dual task walking, VSN+ individuals showed higher collision rates compared to VSN- individuals. Dual tasking caused deterioration of locomotor (more collisions, delayed onset and smaller minimum distances) and cognitive performances (higher error rate) in VSN+ individuals. Contrastingly, VSN- individuals maintained collision rates, increased minimum distance, but showed more cognitive errors, prioritizing their locomotor performance. Individuals with VSN demonstrate cognitive-locomotor interference under dual task conditions, which could severely compromise safety when ambulating in community environments and may explain the poor recovery of independent community ambulation in these individuals.

A Most Probable Point-Based Method for Reliability Analysis, Sensitivity Analysis and Design Optimization

NASA Technical Reports Server (NTRS)

Hou, Gene J.-W; Newman, Perry A. (Technical Monitor)

2004-01-01

A major step in a most probable point (MPP)-based method for reliability analysis is to determine the MPP. This is usually accomplished by using an optimization search algorithm. The minimum distance associated with the MPP provides a measurement of safety probability, which can be obtained by approximate probability integration methods such as FORM or SORM. The reliability sensitivity equations are derived first in this paper, based on the derivatives of the optimal solution. Examples are provided later to demonstrate the use of these derivatives for better reliability analysis and reliability-based design optimization (RBDO).

Estimating alarm thresholds and the number of components in mixture distributions

NASA Astrophysics Data System (ADS)

Burr, Tom; Hamada, Michael S.

2012-09-01

Mixtures of probability distributions arise in many nuclear assay and forensic applications, including nuclear weapon detection, neutron multiplicity counting, and in solution monitoring (SM) for nuclear safeguards. SM data is increasingly used to enhance nuclear safeguards in aqueous reprocessing facilities having plutonium in solution form in many tanks. This paper provides background for mixture probability distributions and then focuses on mixtures arising in SM data. SM data can be analyzed by evaluating transfer-mode residuals defined as tank-to-tank transfer differences, and wait-mode residuals defined as changes during non-transfer modes. A previous paper investigated impacts on transfer-mode and wait-mode residuals of event marking errors which arise when the estimated start and/or stop times of tank events such as transfers are somewhat different from the true start and/or stop times. Event marking errors contribute to non-Gaussian behavior and larger variation than predicted on the basis of individual tank calibration studies. This paper illustrates evidence for mixture probability distributions arising from such event marking errors and from effects such as condensation or evaporation during non-transfer modes, and pump carryover during transfer modes. A quantitative assessment of the sample size required to adequately characterize a mixture probability distribution arising in any context is included.

Maximum entropy approach to statistical inference for an ocean acoustic waveguide.

PubMed

Knobles, D P; Sagers, J D; Koch, R A

2012-02-01

A conditional probability distribution suitable for estimating the statistical properties of ocean seabed parameter values inferred from acoustic measurements is derived from a maximum entropy principle. The specification of the expectation value for an error function constrains the maximization of an entropy functional. This constraint determines the sensitivity factor (β) to the error function of the resulting probability distribution, which is a canonical form that provides a conservative estimate of the uncertainty of the parameter values. From the conditional distribution, marginal distributions for individual parameters can be determined from integration over the other parameters. The approach is an alternative to obtaining the posterior probability distribution without an intermediary determination of the likelihood function followed by an application of Bayes' rule. In this paper the expectation value that specifies the constraint is determined from the values of the error function for the model solutions obtained from a sparse number of data samples. The method is applied to ocean acoustic measurements taken on the New Jersey continental shelf. The marginal probability distribution for the values of the sound speed ratio at the surface of the seabed and the source levels of a towed source are examined for different geoacoustic model representations. © 2012 Acoustical Society of America

Average BER and outage probability of the ground-to-train OWC link in turbulence with rain

NASA Astrophysics Data System (ADS)

Zhang, Yixin; Yang, Yanqiu; Hu, Beibei; Yu, Lin; Hu, Zheng-Da

2017-09-01

The bit-error rate (BER) and outage probability of optical wireless communication (OWC) link for the ground-to-train of the curved track in turbulence with rain is evaluated. Considering the re-modulation effects of raining fluctuation on optical signal modulated by turbulence, we set up the models of average BER and outage probability in the present of pointing errors, based on the double inverse Gaussian (IG) statistical distribution model. The numerical results indicate that, for the same covered track length, the larger curvature radius increases the outage probability and average BER. The performance of the OWC link in turbulence with rain is limited mainly by the rain rate and pointing errors which are induced by the beam wander and train vibration. The effect of the rain rate on the performance of the link is more severe than the atmospheric turbulence, but the fluctuation owing to the atmospheric turbulence affects the laser beam propagation more greatly than the skewness of the rain distribution. Besides, the turbulence-induced beam wander has a more significant impact on the system in heavier rain. We can choose the size of transmitting and receiving apertures and improve the shockproof performance of the tracks to optimize the communication performance of the system.

Reliable and energy-efficient communications for wireless biomedical implant systems.

PubMed

Ntouni, Georgia D; Lioumpas, Athanasios S; Nikita, Konstantina S

2014-11-01

Implant devices are used to measure biological parameters and transmit their results to remote off-body devices. As implants are characterized by strict requirements on size, reliability, and power consumption, applying the concept of cooperative communications to wireless body area networks offers several benefits. In this paper, we aim to minimize the power consumption of the implant device by utilizing on-body wearable devices, while providing the necessary reliability in terms of outage probability and bit error rate. Taking into account realistic power considerations and wireless propagation environments based on the IEEE P802.l5 channel model, an exact theoretical analysis is conducted for evaluating several communication scenarios with respect to the position of the wearable device and the motion of the human body. The derived closed-form expressions are employed toward minimizing the required transmission power, subject to a minimum quality-of-service requirement. In this way, the complexity and power consumption are transferred from the implant device to the on-body relay, which is an efficient approach since they can be easily replaced, in contrast to the in-body implants.

Cyber-Physical Trade-Offs in Distributed Detection Networks

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

Rao, Nageswara S; Yao, David K. Y.; Chin, J. C.

2010-01-01

We consider a network of sensors that measure the scalar intensity due to the background or a source combined with background, inside a two-dimensional monitoring area. The sensor measurements may be random due to the underlying nature of the source and background or due to sensor errors or both. The detection problem is infer the presence of a source of unknown intensity and location based on sensor measurements. In the conventional approach, detection decisions are made at the individual sensors, which are then combined at the fusion center, for example using the majority rule. With increased communication and computation costs,more » we show that a more complex fusion algorithm based on measurements achieves better detection performance under smooth and non-smooth source intensity functions, Lipschitz conditions on probability ratios and a minimum packing number for the state-space. We show that these conditions for trade-offs between the cyber costs and physical detection performance are applicable for two detection problems: (i) point radiation sources amidst background radiation, and (ii) sources and background with Gaussian distributions.« less

Journal news

USGS Publications Warehouse

Conroy, M.J.; Samuel, M.D.; White, Joanne C.

1995-01-01

Statistical power (and conversely, Type II error) is often ignored by biologists. Power is important to consider in the design of studies, to ensure that sufficient resources are allocated to address a hypothesis under examination. Deter- mining appropriate sample size when designing experiments or calculating power for a statistical test requires an investigator to consider the importance of making incorrect conclusions about the experimental hypothesis and the biological importance of the alternative hypothesis (or the biological effect size researchers are attempting to measure). Poorly designed studies frequently provide results that are at best equivocal, and do little to advance science or assist in decision making. Completed studies that fail to reject Ho should consider power and the related probability of a Type II error in the interpretation of results, particularly when implicit or explicit acceptance of Ho is used to support a biological hypothesis or management decision. Investigators must consider the biological question they wish to answer (Tacha et al. 1982) and assess power on the basis of biologically significant differences (Taylor and Gerrodette 1993). Power calculations are somewhat subjective, because the author must specify either f or the minimum difference that is biologically important. Biologists may have different ideas about what values are appropriate. While determining biological significance is of central importance in power analysis, it is also an issue of importance in wildlife science. Procedures, references, and computer software to compute power are accessible; therefore, authors should consider power. We welcome comments or suggestions on this subject.

Identification of dynamic systems, theory and formulation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1985-01-01

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

Quantum illumination for enhanced detection of Rayleigh-fading targets

NASA Astrophysics Data System (ADS)

Zhuang, Quntao; Zhang, Zheshen; Shapiro, Jeffrey H.

2017-08-01

Quantum illumination (QI) is an entanglement-enhanced sensing system whose performance advantage over a comparable classical system survives its usage in an entanglement-breaking scenario plagued by loss and noise. In particular, QI's error-probability exponent for discriminating between equally likely hypotheses of target absence or presence is 6 dB higher than that of the optimum classical system using the same transmitted power. This performance advantage, however, presumes that the target return, when present, has known amplitude and phase, a situation that seldom occurs in light detection and ranging (lidar) applications. At lidar wavelengths, most target surfaces are sufficiently rough that their returns are speckled, i.e., they have Rayleigh-distributed amplitudes and uniformly distributed phases. QI's optical parametric amplifier receiver—which affords a 3 dB better-than-classical error-probability exponent for a return with known amplitude and phase—fails to offer any performance gain for Rayleigh-fading targets. We show that the sum-frequency generation receiver [Zhuang et al., Phys. Rev. Lett. 118, 040801 (2017), 10.1103/PhysRevLett.118.040801]—whose error-probability exponent for a nonfading target achieves QI's full 6 dB advantage over optimum classical operation—outperforms the classical system for Rayleigh-fading targets. In this case, QI's advantage is subexponential: its error probability is lower than the classical system's by a factor of 1 /ln(M κ ¯NS/NB) , when M κ ¯NS/NB≫1 , with M ≫1 being the QI transmitter's time-bandwidth product, NS≪1 its brightness, κ ¯ the target return's average intensity, and NB the background light's brightness.

Cost effectiveness of the stream-gaging program in South Carolina

USGS Publications Warehouse

Barker, A.C.; Wright, B.C.; Bennett, C.S.

1985-01-01

The cost effectiveness of the stream-gaging program in South Carolina was documented for the 1983 water yr. Data uses and funding sources were identified for the 76 continuous stream gages currently being operated in South Carolina. The budget of $422,200 for collecting and analyzing streamflow data also includes the cost of operating stage-only and crest-stage stations. The streamflow records for one stream gage can be determined by alternate, less costly methods, and should be discontinued. The remaining 75 stations should be maintained in the program for the foreseeable future. The current policy for the operation of the 75 stations including the crest-stage and stage-only stations would require a budget of $417,200/yr. The average standard error of estimation of streamflow records is 16.9% for the present budget with missing record included. However, the standard error of estimation would decrease to 8.5% if complete streamflow records could be obtained. It was shown that the average standard error of estimation of 16.9% could be obtained at the 75 sites with a budget of approximately $395,000 if the gaging resources were redistributed among the gages. A minimum budget of $383,500 is required to operate the program; a budget less than this does not permit proper service and maintenance of the gages and recorders. At the minimum budget, the average standard error is 18.6%. The maximum budget analyzed was $850,000, which resulted in an average standard error of 7.6 %. (Author 's abstract)

Dissociating error-based and reinforcement-based loss functions during sensorimotor learning

PubMed Central

McGregor, Heather R.; Mohatarem, Ayman

2017-01-01

It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode). We then examined how the sensorimotor system uses error feedback and reinforcement feedback, in isolation and combination, when deciding where to aim the hand during a reach. We found that participants compensated differently to the same skewed lateral shift distribution depending on the form of feedback they received. When provided with error feedback, participants compensated based on the mean of the skewed noise. When provided with reinforcement feedback, participants compensated based on the mode. Participants receiving both error and reinforcement feedback continued to compensate based on the mean while repeatedly missing the target, despite receiving auditory, visual and monetary reinforcement feedback that rewarded hitting the target. Our work shows that reinforcement-based and error-based learning are separable and can occur independently. Further, when error and reinforcement feedback are in conflict, the sensorimotor system heavily weights error feedback over reinforcement feedback. PMID:28753634

Dissociating error-based and reinforcement-based loss functions during sensorimotor learning.

PubMed

Cashaback, Joshua G A; McGregor, Heather R; Mohatarem, Ayman; Gribble, Paul L

2017-07-01

It has been proposed that the sensorimotor system uses a loss (cost) function to evaluate potential movements in the presence of random noise. Here we test this idea in the context of both error-based and reinforcement-based learning. In a reaching task, we laterally shifted a cursor relative to true hand position using a skewed probability distribution. This skewed probability distribution had its mean and mode separated, allowing us to dissociate the optimal predictions of an error-based loss function (corresponding to the mean of the lateral shifts) and a reinforcement-based loss function (corresponding to the mode). We then examined how the sensorimotor system uses error feedback and reinforcement feedback, in isolation and combination, when deciding where to aim the hand during a reach. We found that participants compensated differently to the same skewed lateral shift distribution depending on the form of feedback they received. When provided with error feedback, participants compensated based on the mean of the skewed noise. When provided with reinforcement feedback, participants compensated based on the mode. Participants receiving both error and reinforcement feedback continued to compensate based on the mean while repeatedly missing the target, despite receiving auditory, visual and monetary reinforcement feedback that rewarded hitting the target. Our work shows that reinforcement-based and error-based learning are separable and can occur independently. Further, when error and reinforcement feedback are in conflict, the sensorimotor system heavily weights error feedback over reinforcement feedback.

Study on Effects of the Stochastic Delay Probability for 1d CA Model of Traffic Flow

NASA Astrophysics Data System (ADS)

Xue, Yu; Chen, Yan-Hong; Kong, Ling-Jiang

Considering the effects of different factors on the stochastic delay probability, the delay probability has been classified into three cases. The first case corresponding to the brake state has a large delay probability if the anticipant velocity is larger than the gap between the successive cars. The second one corresponding to the following-the-leader rule has intermediate delay probability if the anticipant velocity is equal to the gap. Finally, the third case is the acceleration, which has minimum delay probability. The fundamental diagram obtained by numerical simulation shows the different properties compared to that by the NaSch model, in which there exist two different regions, corresponding to the coexistence state, and jamming state respectively.

Combined-probability space and certainty or uncertainty relations for a finite-level quantum system

NASA Astrophysics Data System (ADS)

Sehrawat, Arun

2017-08-01

The Born rule provides a probability vector (distribution) with a quantum state for a measurement setting. For two settings, we have a pair of vectors from the same quantum state. Each pair forms a combined-probability vector that obeys certain quantum constraints, which are triangle inequalities in our case. Such a restricted set of combined vectors, called the combined-probability space, is presented here for a d -level quantum system (qudit). The combined space is a compact convex subset of a Euclidean space, and all its extreme points come from a family of parametric curves. Considering a suitable concave function on the combined space to estimate the uncertainty, we deliver an uncertainty relation by finding its global minimum on the curves for a qudit. If one chooses an appropriate concave (or convex) function, then there is no need to search for the absolute minimum (maximum) over the whole space; it will be on the parametric curves. So these curves are quite useful for establishing an uncertainty (or a certainty) relation for a general pair of settings. We also demonstrate that many known tight certainty or uncertainty relations for a qubit can be obtained with the triangle inequalities.

Probable flood predictions in ungauged coastal basins of El Salvador

USGS Publications Warehouse

Friedel, M.J.; Smith, M.E.; Chica, A.M.E.; Litke, D.

2008-01-01

A regionalization procedure is presented and used to predict probable flooding in four ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. The flood-prediction problem is sequentially solved for two regions: upstream mountains and downstream alluvial plains. In the upstream mountains, a set of rainfall-runoff parameter values and recurrent peak-flow discharge hydrographs are simultaneously estimated for 20 tributary-basin models. Application of dissimilarity equations among tributary basins (soft prior information) permitted development of a parsimonious parameter structure subject to information content in the recurrent peak-flow discharge values derived using regression equations based on measurements recorded outside the ungauged study basins. The estimated joint set of parameter values formed the basis from which probable minimum and maximum peak-flow discharge limits were then estimated revealing that prediction uncertainty increases with basin size. In the downstream alluvial plain, model application of the estimated minimum and maximum peak-flow hydrographs facilitated simulation of probable 100-year flood-flow depths in confined canyons and across unconfined coastal alluvial plains. The regionalization procedure provides a tool for hydrologic risk assessment and flood protection planning that is not restricted to the case presented herein. ?? 2008 ASCE.

Effect of grid transparency and finite collector size on determining ion temperature and density by the retarding potential analyzer

NASA Technical Reports Server (NTRS)

Troy, B. E., Jr.; Maier, E. J.

1975-01-01

The effects of the grid transparency and finite collector size on the values of thermal ion density and temperature determined by the standard RPA (retarding potential analyzer) analysis method are investigated. The current-voltage curves calculated for varying RPA parameters and a given ion mass, temperature, and density are analyzed by the standard RPA method. It is found that only small errors in temperature and density are introduced for an RPA with typical dimensions, and that even when the density error is substantial for nontypical dimensions, the temperature error remains minimum.

New Syndrome Decoding Techniques for the (n, K) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

This paper presents a new syndrome decoding algorithm for the (n,k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3,1)CC.

Simplified Syndrome Decoding of (n, 1) Convolutional Codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

A new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck is presented. The new algorithm uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). This set of Diophantine solutions is a coset of the CC space. A recursive or Viterbi-like algorithm is developed to find the minimum weight error vector cirumflex E(D) in this error coset. An example illustrating the new decoding algorithm is given for the binary nonsymmetric (2,1)CC.

Method of estimating natural recharge to the Edwards Aquifer in the San Antonio area, Texas

USGS Publications Warehouse

Puente, Celso

1978-01-01

The principal errors in the estimates of annual recharge are related to errors in estimating runoff in ungaged areas, which represent about 30 percent of the infiltration area. The estimated long-term average annual recharge in each basin, however, is probably representative of the actual recharge because the averaging procedure tends to cancel out the major errors.

State space truncation with quantified errors for accurate solutions to discrete Chemical Master Equation

PubMed Central

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-01-01

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEG), we truncate the state space by limiting the total molecular copy numbers in each MEG. We further describe a theoretical framework for analysis of the truncation error in the steady state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of 1) the birth and death model, 2) the single gene expression model, 3) the genetic toggle switch model, and 4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate out theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks. PMID:27105653

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

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

Cao, Youfang; Terebus, Anna; Liang, Jie

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

DOE PAGES

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-04-22

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

A Method to Estimate the Probability that any Individual Cloud-to-Ground Lightning Stroke was Within any Radius of any Point

NASA Technical Reports Server (NTRS)

Huddleston, Lisa L.; Roeder, William P.; Merceret, Francis J.

2011-01-01

A new technique has been developed to estimate the probability that a nearby cloud to ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.

On the determinants of the conjunction fallacy: probability versus inductive confirmation.

PubMed

Tentori, Katya; Crupi, Vincenzo; Russo, Selena

2013-02-01

Major recent interpretations of the conjunction fallacy postulate that people assess the probability of a conjunction according to (non-normative) averaging rules as applied to the constituents' probabilities or represent the conjunction fallacy as an effect of random error in the judgment process. In the present contribution, we contrast such accounts with a different reading of the phenomenon based on the notion of inductive confirmation as defined by contemporary Bayesian theorists. Averaging rule hypotheses along with the random error model and many other existing proposals are shown to all imply that conjunction fallacy rates would rise as the perceived probability of the added conjunct does. By contrast, our account predicts that the conjunction fallacy depends on the added conjunct being perceived as inductively confirmed. Four studies are reported in which the judged probability versus confirmation of the added conjunct have been systematically manipulated and dissociated. The results consistently favor a confirmation-theoretic account of the conjunction fallacy against competing views. Our proposal is also discussed in connection with related issues in the study of human inductive reasoning. 2013 APA, all rights reserved

A Method to Estimate the Probability that Any Individual Cloud-to-Ground Lightning Stroke was Within Any Radius of Any Point

NASA Technical Reports Server (NTRS)

Huddleston, Lisa; Roeder, WIlliam P.; Merceret, Francis J.

2011-01-01

A new technique has been developed to estimate the probability that a nearby cloud-to-ground lightning stroke was within a specified radius of any point of interest. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even within the location error ellipse. This technique is adapted from a method of calculating the probability of debris collision with spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force station. Future applications could include forensic meteorology.

An extended Reed Solomon decoder design

NASA Technical Reports Server (NTRS)

Chen, J.; Owsley, P.; Purviance, J.

1991-01-01

It has previously been shown that the Reed-Solomon (RS) codes can correct errors beyond the Singleton and Rieger Bounds with an arbitrarily small probability of a miscorrect. That is, an (n,k) RS code can correct more than (n-k)/2 errors. An implementation of such an RS decoder is presented in this paper. An existing RS decoder, the AHA4010, is utilized in this work. This decoder is especially useful for errors which are patterned with a long burst plus some random errors.

Assessment of precursory information in seismo-electromagnetic phenomena

NASA Astrophysics Data System (ADS)

Han, P.; Hattori, K.; Zhuang, J.

2017-12-01

Previous statistical studies showed that there were correlations between seismo-electromagnetic phenomena and sizeable earthquakes in Japan. In this study, utilizing Molchan's error diagram, we evaluate whether these phenomena contain precursory information and discuss how they can be used in short-term forecasting of large earthquake events. In practice, for given series of precursory signals and related earthquake events, each prediction strategy is characterized by the leading time of alarms, the length of alarm window, the alarm radius (area) and magnitude. The leading time is the time length between a detected anomaly and its following alarm, and the alarm window is the duration that an alarm lasts. The alarm radius and magnitude are maximum predictable distance and minimum predictable magnitude of earthquake events, respectively. We introduce the modified probability gain (PG') and the probability difference (D') to quantify the forecasting performance and to explore the optimal prediction parameters for a given electromagnetic observation. The above methodology is firstly applied to ULF magnetic data and GPS-TEC data. The results show that the earthquake predictions based on electromagnetic anomalies are significantly better than random guesses, indicating the data contain potential useful precursory information. Meanwhile, we reveal the optimal prediction parameters for both observations. The methodology proposed in this study could be also applied to other pre-earthquake phenomena to find out whether there is precursory information, and then on this base explore the optimal alarm parameters in practical short-term forecast.

Reliability estimation of a N- M-cold-standby redundancy system in a multicomponent stress-strength model with generalized half-logistic distribution

NASA Astrophysics Data System (ADS)

Liu, Yiming; Shi, Yimin; Bai, Xuchao; Zhan, Pei

2018-01-01

In this paper, we study the estimation for the reliability of a multicomponent system, named N- M-cold-standby redundancy system, based on progressive Type-II censoring sample. In the system, there are N subsystems consisting of M statistically independent distributed strength components, and only one of these subsystems works under the impact of stresses at a time and the others remain as standbys. Whenever the working subsystem fails, one from the standbys takes its place. The system fails when the entire subsystems fail. It is supposed that the underlying distributions of random strength and stress both belong to the generalized half-logistic distribution with different shape parameter. The reliability of the system is estimated by using both classical and Bayesian statistical inference. Uniformly minimum variance unbiased estimator and maximum likelihood estimator for the reliability of the system are derived. Under squared error loss function, the exact expression of the Bayes estimator for the reliability of the system is developed by using the Gauss hypergeometric function. The asymptotic confidence interval and corresponding coverage probabilities are derived based on both the Fisher and the observed information matrices. The approximate highest probability density credible interval is constructed by using Monte Carlo method. Monte Carlo simulations are performed to compare the performances of the proposed reliability estimators. A real data set is also analyzed for an illustration of the findings.

Decision-theoretic saliency: computational principles, biological plausibility, and implications for neurophysiology and psychophysics.

PubMed

Gao, Dashan; Vasconcelos, Nuno

2009-01-01

A decision-theoretic formulation of visual saliency, first proposed for top-down processing (object recognition) (Gao & Vasconcelos, 2005a), is extended to the problem of bottom-up saliency. Under this formulation, optimality is defined in the minimum probability of error sense, under a constraint of computational parsimony. The saliency of the visual features at a given location of the visual field is defined as the power of those features to discriminate between the stimulus at the location and a null hypothesis. For bottom-up saliency, this is the set of visual features that surround the location under consideration. Discrimination is defined in an information-theoretic sense and the optimal saliency detector derived for a class of stimuli that complies with known statistical properties of natural images. It is shown that under the assumption that saliency is driven by linear filtering, the optimal detector consists of what is usually referred to as the standard architecture of V1: a cascade of linear filtering, divisive normalization, rectification, and spatial pooling. The optimal detector is also shown to replicate the fundamental properties of the psychophysics of saliency: stimulus pop-out, saliency asymmetries for stimulus presence versus absence, disregard of feature conjunctions, and Weber's law. Finally, it is shown that the optimal saliency architecture can be applied to the solution of generic inference problems. In particular, for the class of stimuli studied, it performs the three fundamental operations of statistical inference: assessment of probabilities, implementation of Bayes decision rule, and feature selection.

Relating Regime Structure to Probability Distribution and Preferred Structure of Small Errors in a Large Atmospheric GCM

NASA Astrophysics Data System (ADS)

Straus, D. M.

2007-12-01

The probability distribution (pdf) of errors is followed in identical twin studies using the COLA T63 AGCM, integrated with observed SST for 15 recent winters. 30 integrations per winter (for 15 winters) are available with initial errors that are extremely small. The evolution of the pdf is tested for multi-modality, and the results interpreted in terms of clusters / regimes found in: (a) the set of 15x30 integrations mentioned, and (b) a larger ensemble of 55x15 integrations made with the same GCM using the same SSTs. The mapping of pdf evolution and clusters is also carried out for each winter separately, using the clusters found in the 55-member ensemble for the same winter alone. This technique yields information on the change in regimes caused by different boundary forcing (Straus and Molteni, 2004; Straus, Corti and Molteni, 2006). Analysis of the growing errors in terms of baroclinic and barotropic components allows for interpretation of the corresponding instabilities.

Performance Analysis of an Inter-Relay Co-operation in FSO Communication System

NASA Astrophysics Data System (ADS)

Khanna, Himanshu; Aggarwal, Mona; Ahuja, Swaran

2018-04-01

In this work, we analyze the outage and error performance of a one-way inter-relay assisted free space optical link. The assumption of the absence of direct link between the source and destination node is being made for the analysis, and the feasibility of such system configuration is studied. We consider the influence of path loss, atmospheric turbulence and pointing error impairments, and investigate the effect of these parameters on the system performance. The turbulence-induced fading is modeled by independent but not necessarily identically distributed gamma-gamma fading statistics. The closed-form expressions for outage probability and probability of error are derived and illustrated by numerical plots. It is concluded that the absence of line of sight path between source and destination nodes does not lead to significant performance degradation. Moreover, for the system model under consideration, interconnected relaying provides better error performance than the non-interconnected relaying and dual-hop serial relaying techniques.

SEC proton prediction model: verification and analysis.

PubMed

Balch, C C

1999-06-01

This paper describes a model that has been used at the NOAA Space Environment Center since the early 1970s as a guide for the prediction of solar energetic particle events. The algorithms for proton event probability, peak flux, and rise time are described. The predictions are compared with observations. The current model shows some ability to distinguish between proton event associated flares and flares that are not associated with proton events. The comparisons of predicted and observed peak flux show considerable scatter, with an rms error of almost an order of magnitude. Rise time comparisons also show scatter, with an rms error of approximately 28 h. The model algorithms are analyzed using historical data and improvements are suggested. Implementation of the algorithm modifications reduces the rms error in the log10 of the flux prediction by 21%, and the rise time rms error by 31%. Improvements are also realized in the probability prediction by deriving the conditional climatology for proton event occurrence given flare characteristics.

The volume-outcome relationship and minimum volume standards--empirical evidence for Germany.

PubMed

Hentschker, Corinna; Mennicken, Roman

2015-06-01

For decades, there is an ongoing discussion about the quality of hospital care leading i.a. to the introduction of minimum volume standards in various countries. In this paper, we analyze the volume-outcome relationship for patients with intact abdominal aortic aneurysm and hip fracture. We define hypothetical minimum volume standards in both conditions and assess consequences for access to hospital services in Germany. The results show clearly that patients treated in hospitals with a higher case volume have on average a significant lower probability of death in both conditions. Furthermore, we show that the hypothetical minimum volume standards do not compromise overall access measured with changes in travel times. Copyright © 2014 John Wiley & Sons, Ltd.

The impact of the minimum wage on health.

PubMed

Andreyeva, Elena; Ukert, Benjamin

2018-03-07

This study evaluates the effect of minimum wage on risky health behaviors, healthcare access, and self-reported health. We use data from the 1993-2015 Behavioral Risk Factor Surveillance System, and employ a difference-in-differences strategy that utilizes time variation in new minimum wage laws across U.S. states. Results suggest that the minimum wage increases the probability of being obese and decreases daily fruit and vegetable intake, but also decreases days with functional limitations while having no impact on healthcare access. Subsample analyses reveal that the increase in weight and decrease in fruit and vegetable intake are driven by the older population, married, and whites. The improvement in self-reported health is especially strong among non-whites, females, and married.

Error-related negativities elicited by monetary loss and cues that predict loss.

PubMed

Dunning, Jonathan P; Hajcak, Greg

2007-11-19

Event-related potential studies have reported error-related negativity following both error commission and feedback indicating errors or monetary loss. The present study examined whether error-related negativities could be elicited by a predictive cue presented prior to both the decision and subsequent feedback in a gambling task. Participants were presented with a cue that indicated the probability of reward on the upcoming trial (0, 50, and 100%). Results showed a negative deflection in the event-related potential in response to loss cues compared with win cues; this waveform shared a similar latency and morphology with the traditional feedback error-related negativity.

Quantum error-correction failure distributions: Comparison of coherent and stochastic error models

NASA Astrophysics Data System (ADS)

Barnes, Jeff P.; Trout, Colin J.; Lucarelli, Dennis; Clader, B. D.

2017-06-01

We compare failure distributions of quantum error correction circuits for stochastic errors and coherent errors. We utilize a fully coherent simulation of a fault-tolerant quantum error correcting circuit for a d =3 Steane and surface code. We find that the output distributions are markedly different for the two error models, showing that no simple mapping between the two error models exists. Coherent errors create very broad and heavy-tailed failure distributions. This suggests that they are susceptible to outlier events and that mean statistics, such as pseudothreshold estimates, may not provide the key figure of merit. This provides further statistical insight into why coherent errors can be so harmful for quantum error correction. These output probability distributions may also provide a useful metric that can be utilized when optimizing quantum error correcting codes and decoding procedures for purely coherent errors.

Human-computer interaction in multitask situations

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1977-01-01

Human-computer interaction in multitask decisionmaking situations is considered, and it is proposed that humans and computers have overlapping responsibilities. Queueing theory is employed to model this dynamic approach to the allocation of responsibility between human and computer. Results of simulation experiments are used to illustrate the effects of several system variables including number of tasks, mean time between arrivals of action-evoking events, human-computer speed mismatch, probability of computer error, probability of human error, and the level of feedback between human and computer. Current experimental efforts are discussed and the practical issues involved in designing human-computer systems for multitask situations are considered.

Outage probability of a relay strategy allowing intra-link errors utilizing Slepian-Wolf theorem

NASA Astrophysics Data System (ADS)

Cheng, Meng; Anwar, Khoirul; Matsumoto, Tad

2013-12-01

In conventional decode-and-forward (DF) one-way relay systems, a data block received at the relay node is discarded, if the information part is found to have errors after decoding. Such errors are referred to as intra-link errors in this article. However, in a setup where the relay forwards data blocks despite possible intra-link errors, the two data blocks, one from the source node and the other from the relay node, are highly correlated because they were transmitted from the same source. In this article, we focus on the outage probability analysis of such a relay transmission system, where source-destination and relay-destination links, Link 1 and Link 2, respectively, are assumed to suffer from the correlated fading variation due to block Rayleigh fading. The intra-link is assumed to be represented by a simple bit-flipping model, where some of the information bits recovered at the relay node are the flipped version of their corresponding original information bits at the source. The correlated bit streams are encoded separately by the source and relay nodes, and transmitted block-by-block to a common destination using different time slots, where the information sequence transmitted over Link 2 may be a noise-corrupted interleaved version of the original sequence. The joint decoding takes place at the destination by exploiting the correlation knowledge of the intra-link (source-relay link). It is shown that the outage probability of the proposed transmission technique can be expressed by a set of double integrals over the admissible rate range, given by the Slepian-Wolf theorem, with respect to the probability density function ( pdf) of the instantaneous signal-to-noise power ratios (SNR) of Link 1 and Link 2. It is found that, with the Slepian-Wolf relay technique, so far as the correlation ρ of the complex fading variation is | ρ|<1, the 2nd order diversity can be achieved only if the two bit streams are fully correlated. This indicates that the diversity order exhibited in the outage curve converges to 1 when the bit streams are not fully correlated. Moreover, the Slepian-Wolf outage probability is proved to be smaller than that of the 2nd order maximum ratio combining (MRC) diversity, if the average SNRs of the two independent links are the same. Exact as well as asymptotic expressions of the outage probability are theoretically derived in the article. In addition, the theoretical outage results are compared with the frame-error-rate (FER) curves, obtained by a series of simulations for the Slepian-Wolf relay system based on bit-interleaved coded modulation with iterative detection (BICM-ID). It is shown that the FER curves exhibit the same tendency as the theoretical results.

Assessment and quantification of patient set-up errors in nasopharyngeal cancer patients and their biological and dosimetric impact in terms of generalized equivalent uniform dose (gEUD), tumour control probability (TCP) and normal tissue complication probability (NTCP).

PubMed

Boughalia, A; Marcie, S; Fellah, M; Chami, S; Mekki, F

2015-06-01

The aim of this study is to assess and quantify patients' set-up errors using an electronic portal imaging device and to evaluate their dosimetric and biological impact in terms of generalized equivalent uniform dose (gEUD) on predictive models, such as the tumour control probability (TCP) and the normal tissue complication probability (NTCP). 20 patients treated for nasopharyngeal cancer were enrolled in the radiotherapy-oncology department of HCA. Systematic and random errors were quantified. The dosimetric and biological impact of these set-up errors on the target volume and the organ at risk (OARs) coverage were assessed using calculation of dose-volume histogram, gEUD, TCP and NTCP. For this purpose, an in-house software was developed and used. The standard deviations (1SDs) of the systematic set-up and random set-up errors were calculated for the lateral and subclavicular fields and gave the following results: ∑ = 0.63 ± (0.42) mm and σ = 3.75 ± (0.79) mm, respectively. Thus a planning organ at risk volume (PRV) margin of 3 mm was defined around the OARs, and a 5-mm margin used around the clinical target volume. The gEUD, TCP and NTCP calculations obtained with and without set-up errors have shown increased values for tumour, where ΔgEUD (tumour) = 1.94% Gy (p = 0.00721) and ΔTCP = 2.03%. The toxicity of OARs was quantified using gEUD and NTCP. The values of ΔgEUD (OARs) vary from 0.78% to 5.95% in the case of the brainstem and the optic chiasm, respectively. The corresponding ΔNTCP varies from 0.15% to 0.53%, respectively. The quantification of set-up errors has a dosimetric and biological impact on the tumour and on the OARs. The developed in-house software using the concept of gEUD, TCP and NTCP biological models has been successfully used in this study. It can be used also to optimize the treatment plan established for our patients. The gEUD, TCP and NTCP may be more suitable tools to assess the treatment plans before treating the patients.

Use of attribute association error probability estimates to evaluate quality of medical record geocodes.

PubMed

Klaus, Christian A; Carrasco, Luis E; Goldberg, Daniel W; Henry, Kevin A; Sherman, Recinda L

2015-09-15

The utility of patient attributes associated with the spatiotemporal analysis of medical records lies not just in their values but also the strength of association between them. Estimating the extent to which a hierarchy of conditional probability exists between patient attribute associations such as patient identifying fields, patient and date of diagnosis, and patient and address at diagnosis is fundamental to estimating the strength of association between patient and geocode, and patient and enumeration area. We propose a hierarchy for the attribute associations within medical records that enable spatiotemporal relationships. We also present a set of metrics that store attribute association error probability (AAEP), to estimate error probability for all attribute associations upon which certainty in a patient geocode depends. A series of experiments were undertaken to understand how error estimation could be operationalized within health data and what levels of AAEP in real data reveal themselves using these methods. Specifically, the goals of this evaluation were to (1) assess if the concept of our error assessment techniques could be implemented by a population-based cancer registry; (2) apply the techniques to real data from a large health data agency and characterize the observed levels of AAEP; and (3) demonstrate how detected AAEP might impact spatiotemporal health research. We present an evaluation of AAEP metrics generated for cancer cases in a North Carolina county. We show examples of how we estimated AAEP for selected attribute associations and circumstances. We demonstrate the distribution of AAEP in our case sample across attribute associations, and demonstrate ways in which disease registry specific operations influence the prevalence of AAEP estimates for specific attribute associations. The effort to detect and store estimates of AAEP is worthwhile because of the increase in confidence fostered by the attribute association level approach to the assessment of uncertainty in patient geocodes, relative to existing geocoding related uncertainty metrics.

Almost Perfect Teleportation Using 4-PARTITE Entangled States

NASA Astrophysics Data System (ADS)

Prakash, H.; Chandra, N.; Prakash, R.; Shivani

In a recent paper N. Ba An (Phys. Rev. A 68, 022321 (2003)) proposed a scheme to teleport a single particle state, which is superposition of coherent states |α> and |-α> using a 4-partite state, a beam splitter, and phase shifters and concluded that the probability for successful teleportation is only 1/4 in the limit |α| → 0 and 1/2 in the limit |α| → ∞. In this paper, we modify this scheme and find that an almost perfect success can be achieved if |α|2 is appreciable. For example, for |α|2 = 5, the minimum of average fidelity for teleportation, which is the minimum of sum of the product of probability for occurrence of any case and the corresponding fidelity evaluated for an arbitrary chosen information state, is 0.9999.

Cost effectiveness of a pharmacist-led information technology intervention for reducing rates of clinically important errors in medicines management in general practices (PINCER).

PubMed

Elliott, Rachel A; Putman, Koen D; Franklin, Matthew; Annemans, Lieven; Verhaeghe, Nick; Eden, Martin; Hayre, Jasdeep; Rodgers, Sarah; Sheikh, Aziz; Avery, Anthony J

2014-06-01

We recently showed that a pharmacist-led information technology-based intervention (PINCER) was significantly more effective in reducing medication errors in general practices than providing simple feedback on errors, with cost per error avoided at £79 (US$131). We aimed to estimate cost effectiveness of the PINCER intervention by combining effectiveness in error reduction and intervention costs with the effect of the individual errors on patient outcomes and healthcare costs, to estimate the effect on costs and QALYs. We developed Markov models for each of six medication errors targeted by PINCER. Clinical event probability, treatment pathway, resource use and costs were extracted from literature and costing tariffs. A composite probabilistic model combined patient-level error models with practice-level error rates and intervention costs from the trial. Cost per extra QALY and cost-effectiveness acceptability curves were generated from the perspective of NHS England, with a 5-year time horizon. The PINCER intervention generated £2,679 less cost and 0.81 more QALYs per practice [incremental cost-effectiveness ratio (ICER): -£3,037 per QALY] in the deterministic analysis. In the probabilistic analysis, PINCER generated 0.001 extra QALYs per practice compared with simple feedback, at £4.20 less per practice. Despite this extremely small set of differences in costs and outcomes, PINCER dominated simple feedback with a mean ICER of -£3,936 (standard error £2,970). At a ceiling 'willingness-to-pay' of £20,000/QALY, PINCER reaches 59 % probability of being cost effective. PINCER produced marginal health gain at slightly reduced overall cost. Results are uncertain due to the poor quality of data to inform the effect of avoiding errors.

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

Yan, H; Chen, Z; Nath, R

Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertaintymore » through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the tumor is within the margin or initialize motion compensation if it is out of the margin.« less

Cost-effectiveness of the Federal stream-gaging program in Virginia

USGS Publications Warehouse

Carpenter, D.H.

1985-01-01

Data uses and funding sources were identified for the 77 continuous stream gages currently being operated in Virginia by the U.S. Geological Survey with a budget of $446,000. Two stream gages were identified as not being used sufficiently to warrant continuing their operation. Operation of these stations should be considered for discontinuation. Data collected at two other stations were identified as having uses primarily related to short-term studies; these stations should also be considered for discontinuation at the end of the data collection phases of the studies. The remaining 73 stations should be kept in the program for the foreseeable future. The current policy for operation of the 77-station program requires a budget of $446,000/yr. The average standard error of estimation of streamflow records is 10.1%. It was shown that this overall level of accuracy at the 77 sites could be maintained with a budget of $430,500 if resources were redistributed among the gages. A minimum budget of $428,500 is required to operate the 77-gage program; a smaller budget would not permit proper service and maintenance of the gages and recorders. At the minimum budget, with optimized operation, the average standard error would be 10.4%. The maximum budget analyzed was $650,000, which resulted in an average standard error of 5.5%. The study indicates that a major component of error is caused by lost or missing data. If perfect equipment were available, the standard error for the current program and budget could be reduced to 7.6%. This also can be interpreted to mean that the streamflow data have a standard error of this magnitude during times when the equipment is operating properly. (Author 's abstract)

Augmented GNSS Differential Corrections Minimum Mean Square Error Estimation Sensitivity to Spatial Correlation Modeling Errors

PubMed Central

Kassabian, Nazelie; Presti, Letizia Lo; Rispoli, Francesco

2014-01-01

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. PMID:24922454

Retrieving air humidity, global solar radiation, and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

NASA Astrophysics Data System (ADS)

Lobit, P.; López Pérez, L.; Lhomme, J. P.; Gómez Tagle, A.

2017-07-01

This study evaluates the dew point method (Allen et al. 1998) to estimate atmospheric vapor pressure from minimum temperature, and proposes an improved model to estimate it from maximum and minimum temperature. Both methods were evaluated on 786 weather stations in Mexico. The dew point method induced positive bias in dry areas but also negative bias in coastal areas, and its average root mean square error for all evaluated stations was 0.38 kPa. The improved model assumed a bi-linear relation between estimated vapor pressure deficit (difference between saturated vapor pressure at minimum and average temperature) and measured vapor pressure deficit. The parameters of these relations were estimated from historical annual median values of relative humidity. This model removed bias and allowed for a root mean square error of 0.31 kPa. When no historical measurements of relative humidity were available, empirical relations were proposed to estimate it from latitude and altitude, with only a slight degradation on the model accuracy (RMSE = 0.33 kPa, bias = -0.07 kPa). The applicability of the method to other environments is discussed.

Mining of high utility-probability sequential patterns from uncertain databases

PubMed Central

Zhang, Binbin; Fournier-Viger, Philippe; Li, Ting

2017-01-01

High-utility sequential pattern mining (HUSPM) has become an important issue in the field of data mining. Several HUSPM algorithms have been designed to mine high-utility sequential patterns (HUPSPs). They have been applied in several real-life situations such as for consumer behavior analysis and event detection in sensor networks. Nonetheless, most studies on HUSPM have focused on mining HUPSPs in precise data. But in real-life, uncertainty is an important factor as data is collected using various types of sensors that are more or less accurate. Hence, data collected in a real-life database can be annotated with existing probabilities. This paper presents a novel pattern mining framework called high utility-probability sequential pattern mining (HUPSPM) for mining high utility-probability sequential patterns (HUPSPs) in uncertain sequence databases. A baseline algorithm with three optional pruning strategies is presented to mine HUPSPs. Moroever, to speed up the mining process, a projection mechanism is designed to create a database projection for each processed sequence, which is smaller than the original database. Thus, the number of unpromising candidates can be greatly reduced, as well as the execution time for mining HUPSPs. Substantial experiments both on real-life and synthetic datasets show that the designed algorithm performs well in terms of runtime, number of candidates, memory usage, and scalability for different minimum utility and minimum probability thresholds. PMID:28742847

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

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

Finding Useful Questions: On Bayesian Diagnosticity, Probability, Impact, and Information Gain

ERIC Educational Resources Information Center

Nelson, Jonathan D.

2005-01-01

Several norms for how people should assess a question's usefulness have been proposed, notably Bayesian diagnosticity, information gain (mutual information), Kullback-Liebler distance, probability gain (error minimization), and impact (absolute change). Several probabilistic models of previous experiments on categorization, covariation assessment,…

Teaching Uncertainties

ERIC Educational Resources Information Center

Duerdoth, Ian

2009-01-01

The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…

Topology Trivialization and Large Deviations for the Minimum in the Simplest Random Optimization

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.; Le Doussal, Pierre

2014-01-01

Finding the global minimum of a cost function given by the sum of a quadratic and a linear form in N real variables over (N-1)-dimensional sphere is one of the simplest, yet paradigmatic problems in Optimization Theory known as the "trust region subproblem" or "constraint least square problem". When both terms in the cost function are random this amounts to studying the ground state energy of the simplest spherical spin glass in a random magnetic field. We first identify and study two distinct large-N scaling regimes in which the linear term (magnetic field) leads to a gradual topology trivialization, i.e. reduction in the total number {N}_{tot} of critical (stationary) points in the cost function landscape. In the first regime {N}_{tot} remains of the order N and the cost function (energy) has generically two almost degenerate minima with the Tracy-Widom (TW) statistics. In the second regime the number of critical points is of the order of unity with a finite probability for a single minimum. In that case the mean total number of extrema (minima and maxima) of the cost function is given by the Laplace transform of the TW density, and the distribution of the global minimum energy is expected to take a universal scaling form generalizing the TW law. Though the full form of that distribution is not yet known to us, one of its far tails can be inferred from the large deviation theory for the global minimum. In the rest of the paper we show how to use the replica method to obtain the probability density of the minimum energy in the large-deviation approximation by finding both the rate function and the leading pre-exponential factor.

Prediction of obliteration after gamma knife surgery for cerebral arteriovenous malformations.

PubMed

Karlsson, B; Lindquist, C; Steiner, L

1997-03-01

To define the factors of importance for the obliteration of cerebral arteriovenous malformations (AVMs), thus making a prediction of the probability for obliteration possible. In 945 AVMs of a series of 1319 patients treated with the gamma knife during 1970 to 1990, the relationship between patient, AVMs, and treatment parameters on the one hand and the obliteration of the nidus on the other was analyzed. The obliteration rate increased both with increased minimum (lowest periphery) and average dose and decreased with increased AVM volume. The minimum dose to the AVMs was the decisive dose factor for the treatment result. The higher the minimum dose, the higher the chance for total obliteration. The curve illustrating this relation increased logarithmically to a value of 87%. A higher average dose shortened the latency to AVM obliteration. For the obliterated cases, the larger the malformation, the lower the minimum dose used. This prompted us to relate the obliteration rate to the product minimum dose (AVM volume)1/3 (K index). The obliteration rate increased linearly with the K index up to a value of approximately 27, and for higher K values, the obliteration rate had a constant value of approximately 80%. For the group of 273 cases treated with a minimum dose of at least 25 Gy, the obliteration rate at the study end point (defined as 2-yr latency) was 80% (95% confidence interval = 75-85%). If obliterations that occurred beyond the end point are included, the obliteration rate increased to 85% (81-89%). The probability of obliteration of AVMs after gamma knife surgery is related both to the lowest dose to the AVMs and the AVM volume, and it can be predicted using the K index.

Circular Probable Error for Circular and Noncircular Gaussian Impacts

DTIC Science & Technology

2012-09-01

1M simulated impacts ph(k)=mean(imp(:,1).^2+imp(:,2).^2<=CEP^2); % hit frequency on CEP end phit (j)=mean(ph...avg 100 hit frequencies to “incr n” end % GRAPHICS plot(i, phit ,’r-’); % error exponent versus Ph estimate

Theoretical Analysis of Rain Attenuation Probability

NASA Astrophysics Data System (ADS)

Roy, Surendra Kr.; Jha, Santosh Kr.; Jha, Lallan

2007-07-01

Satellite communication technologies are now highly developed and high quality, distance-independent services have expanded over a very wide area. As for the system design of the Hokkaido integrated telecommunications(HIT) network, it must first overcome outages of satellite links due to rain attenuation in ka frequency bands. In this paper theoretical analysis of rain attenuation probability on a slant path has been made. The formula proposed is based Weibull distribution and incorporates recent ITU-R recommendations concerning the necessary rain rates and rain heights inputs. The error behaviour of the model was tested with the loading rain attenuation prediction model recommended by ITU-R for large number of experiments at different probability levels. The novel slant path rain attenuastion prediction model compared to the ITU-R one exhibits a similar behaviour at low time percentages and a better root-mean-square error performance for probability levels above 0.02%. The set of presented models exhibits the advantage of implementation with little complexity and is considered useful for educational and back of the envelope computations.

Surveillance system and method having an adaptive sequential probability fault detection test

NASA Technical Reports Server (NTRS)

Herzog, James P. (Inventor); Bickford, Randall L. (Inventor)

2005-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Surveillance system and method having an adaptive sequential probability fault detection test

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2006-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor); Herzog, James P. (Inventor)

2008-01-01

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Distributed Immune Systems for Wireless Network Information Assurance

DTIC Science & Technology

2010-04-26

ratio test (SPRT), where the goal is to optimize a hypothesis testing problem given a trade-off between the probability of errors and the...using cumulative sum (CUSUM) and Girshik-Rubin-Shiryaev (GRSh) statistics. In sequential versions of the problem the sequential probability ratio ...the more complicated problems, in particular those where no clear mean can be established. We developed algorithms based on the sequential probability

Quantizing and sampling considerations in digital phased-locked loops

NASA Technical Reports Server (NTRS)

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

1974-01-01

The quantizer problem is first considered. The conditions under which the uniform white sequence model for the quantizer error is valid are established independent of the sampling rate. An equivalent spectral density is defined for the quantizer error resulting in an effective SNR value. This effective SNR may be used to determine quantized performance from infinitely fine quantized results. Attention is given to sampling rate considerations. Sampling rate characteristics of the digital phase-locked loop (DPLL) structure are investigated for the infinitely fine quantized system. The predicted phase error variance equation is examined as a function of the sampling rate. Simulation results are presented and a method is described which enables the minimum required sampling rate to be determined from the predicted phase error variance equations.

78 FR 17155 - Standards for the Growing, Harvesting, Packing, and Holding of Produce for Human Consumption...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-20

...The Food and Drug Administration (FDA or we) is correcting the preamble to a proposed rule that published in the Federal Register of January 16, 2013. That proposed rule would establish science-based minimum standards for the safe growing, harvesting, packing, and holding of produce, meaning fruits and vegetables grown for human consumption. FDA proposed these standards as part of our implementation of the FDA Food Safety Modernization Act. The document published with several technical errors, including some errors in cross references, as well as several errors in reference numbers cited throughout the document. This document corrects those errors. We are also placing a corrected copy of the proposed rule in the docket.

Global minimum profile error (GMPE) - a least-squares-based approach for extracting macroscopic rate coefficients for complex gas-phase chemical reactions.

PubMed

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.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

Use of modeling to identify vulnerabilities to human error in laparoscopy.

PubMed

Funk, Kenneth H; Bauer, James D; Doolen, Toni L; Telasha, David; Nicolalde, R Javier; Reeber, Miriam; Yodpijit, Nantakrit; Long, Myra

2010-01-01

This article describes an exercise to investigate the utility of modeling and human factors analysis in understanding surgical processes and their vulnerabilities to medical error. A formal method to identify error vulnerabilities was developed and applied to a test case of Veress needle insertion during closed laparoscopy. A team of 2 surgeons, a medical assistant, and 3 engineers used hierarchical task analysis and Integrated DEFinition language 0 (IDEF0) modeling to create rich models of the processes used in initial port creation. Using terminology from a standardized human performance database, detailed task descriptions were written for 4 tasks executed in the process of inserting the Veress needle. Key terms from the descriptions were used to extract from the database generic errors that could occur. Task descriptions with potential errors were translated back into surgical terminology. Referring to the process models and task descriptions, the team used a modified failure modes and effects analysis (FMEA) to consider each potential error for its probability of occurrence, its consequences if it should occur and be undetected, and its probability of detection. The resulting likely and consequential errors were prioritized for intervention. A literature-based validation study confirmed the significance of the top error vulnerabilities identified using the method. Ongoing work includes design and evaluation of procedures to correct the identified vulnerabilities and improvements to the modeling and vulnerability identification methods. Copyright 2010 AAGL. Published by Elsevier Inc. All rights reserved.

Power and type I error results for a bias-correction approach recently shown to provide accurate odds ratios of genetic variants for the secondary phenotypes associated with primary diseases.

PubMed

Wang, Jian; Shete, Sanjay

2011-11-01

We recently proposed a bias correction approach to evaluate accurate estimation of the odds ratio (OR) of genetic variants associated with a secondary phenotype, in which the secondary phenotype is associated with the primary disease, based on the original case-control data collected for the purpose of studying the primary disease. As reported in this communication, we further investigated the type I error probabilities and powers of the proposed approach, and compared the results to those obtained from logistic regression analysis (with or without adjustment for the primary disease status). We performed a simulation study based on a frequency-matching case-control study with respect to the secondary phenotype of interest. We examined the empirical distribution of the natural logarithm of the corrected OR obtained from the bias correction approach and found it to be normally distributed under the null hypothesis. On the basis of the simulation study results, we found that the logistic regression approaches that adjust or do not adjust for the primary disease status had low power for detecting secondary phenotype associated variants and highly inflated type I error probabilities, whereas our approach was more powerful for identifying the SNP-secondary phenotype associations and had better-controlled type I error probabilities. © 2011 Wiley Periodicals, Inc.

Spatial and temporal variability of the overall error of National Atmospheric Deposition Program measurements determined by the USGS collocated-sampler program, water years 1989-2001

USGS Publications Warehouse

Wetherbee, G.A.; Latysh, N.E.; Gordon, J.D.

2005-01-01

Data from the U.S. Geological Survey (USGS) collocated-sampler program for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) are used to estimate the overall error of NADP/NTN measurements. Absolute errors are estimated by comparison of paired measurements from collocated instruments. Spatial and temporal differences in absolute error were identified and are consistent with longitudinal distributions of NADP/NTN measurements and spatial differences in precipitation characteristics. The magnitude of error for calcium, magnesium, ammonium, nitrate, and sulfate concentrations, specific conductance, and sample volume is of minor environmental significance to data users. Data collected after a 1994 sample-handling protocol change are prone to less absolute error than data collected prior to 1994. Absolute errors are smaller during non-winter months than during winter months for selected constituents at sites where frozen precipitation is common. Minimum resolvable differences are estimated for different regions of the USA to aid spatial and temporal watershed analyses.

Simulating a transmon implementation of the surface code, Part I

NASA Astrophysics Data System (ADS)

Tarasinski, Brian; O'Brien, Thomas; Rol, Adriaan; Bultink, Niels; Dicarlo, Leo

Current experimental efforts aim to realize Surface-17, a distance-3 surface-code logical qubit, using transmon qubits in a circuit QED architecture. Following experimental proposals for this device, and currently achieved fidelities on physical qubits, we define a detailed error model that takes experimentally relevant error sources into account, such as amplitude and phase damping, imperfect gate pulses, and coherent errors due to low-frequency flux noise. Using the GPU-accelerated software package 'quantumsim', we simulate the density matrix evolution of the logical qubit under this error model. Combining the simulation results with a minimum-weight matching decoder, we obtain predictions for the error rate of the resulting logical qubit when used as a quantum memory, and estimate the contribution of different error sources to the logical error budget. Research funded by the Foundation for Fundamental Research on Matter (FOM), the Netherlands Organization for Scientific Research (NWO/OCW), IARPA, an ERC Synergy Grant, the China Scholarship Council, and Intel Corporation.

New syndrome decoder for (n, 1) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1983-01-01

The letter presents a new syndrome decoding algorithm for the (n, 1) convolutional codes (CC) that is different and simpler than the previous syndrome decoding algorithm of Schalkwijk and Vinck. The new technique uses the general solution of the polynomial linear Diophantine equation for the error polynomial vector E(D). A recursive, Viterbi-like, algorithm is developed to find the minimum weight error vector E(D). An example is given for the binary nonsystematic (2, 1) CC.

Minimum savings requirements in shared savings provider payment.

PubMed

Pope, Gregory C; Kautter, John

2012-11-01

Payer (insurer) sharing of savings is a way of motivating providers of medical services to reduce cost growth. A Medicare shared savings program is established for accountable care organizations in the 2010 Patient Protection and Affordable Care Act. However, savings created by providers cannot be distinguished from the normal (random) variation in medical claims costs, setting up a classic principal-agent problem. To lessen the likelihood of paying undeserved bonuses, payers may pay bonuses only if observed savings exceed minimum levels. We study the trade-off between two types of errors in setting minimum savings requirements: paying bonuses when providers do not create savings and not paying bonuses when providers create savings. Copyright © 2011 John Wiley & Sons, Ltd.

LOOP- SIMULATION OF THE AUTOMATIC FREQUENCY CONTROL SUBSYSTEM OF A DIFFERENTIAL MINIMUM SHIFT KEYING RECEIVER

NASA Technical Reports Server (NTRS)

Davarian, F.

1994-01-01

The LOOP computer program was written to simulate the Automatic Frequency Control (AFC) subsystem of a Differential Minimum Shift Keying (DMSK) receiver with a bit rate of 2400 baud. The AFC simulated by LOOP is a first order loop configuration with a first order R-C filter. NASA has been investigating the concept of mobile communications based on low-cost, low-power terminals linked via geostationary satellites. Studies have indicated that low bit rate transmission is suitable for this application, particularly from the frequency and power conservation point of view. A bit rate of 2400 BPS is attractive due to its applicability to the linear predictive coding of speech. Input to LOOP includes the following: 1) the initial frequency error; 2) the double-sided loop noise bandwidth; 3) the filter time constants; 4) the amount of intersymbol interference; and 5) the bit energy to noise spectral density. LOOP output includes: 1) the bit number and the frequency error of that bit; 2) the computed mean of the frequency error; and 3) the standard deviation of the frequency error. LOOP is written in MS SuperSoft FORTRAN 77 for interactive execution and has been implemented on an IBM PC operating under PC DOS with a memory requirement of approximately 40K of 8 bit bytes. This program was developed in 1986.

Reciprocally-Benefited Secure Transmission for Spectrum Sensing-Based Cognitive Radio Sensor Networks

PubMed Central

Wang, Dawei; Ren, Pinyi; Du, Qinghe; Sun, Li; Wang, Yichen

2016-01-01

The rapid proliferation of independently-designed and -deployed wireless sensor networks extremely crowds the wireless spectrum and promotes the emergence of cognitive radio sensor networks (CRSN). In CRSN, the sensor node (SN) can make full use of the unutilized licensed spectrum, and the spectrum efficiency is greatly improved. However, inevitable spectrum sensing errors will adversely interfere with the primary transmission, which may result in primary transmission outage. To compensate the adverse effect of spectrum sensing errors, we propose a reciprocally-benefited secure transmission strategy, in which SN’s interference to the eavesdropper is employed to protect the primary confidential messages while the CRSN is also rewarded with a loose spectrum sensing error probability constraint. Specifically, according to the spectrum sensing results and primary users’ activities, there are four system states in this strategy. For each state, we analyze the primary secrecy rate and the SN’s transmission rate by taking into account the spectrum sensing errors. Then, the SN’s transmit power is optimally allocated for each state so that the average transmission rate of CRSN is maximized under the constraint of the primary maximum permitted secrecy outage probability. In addition, the performance tradeoff between the transmission rate of CRSN and the primary secrecy outage probability is investigated. Moreover, we analyze the primary secrecy rate for the asymptotic scenarios and derive the closed-form expression of the SN’s transmission outage probability. Simulation results show that: (1) the performance of the SN’s average throughput in the proposed strategy outperforms the conventional overlay strategy; (2) both the primary network and CRSN benefit from the proposed strategy. PMID:27897988

Investigation of an Optimum Detection Scheme for a Star-Field Mapping System

NASA Technical Reports Server (NTRS)

Aldridge, M. D.; Credeur, L.

1970-01-01

An investigation was made to determine the optimum detection scheme for a star-field mapping system that uses coded detection resulting from starlight shining through specially arranged multiple slits of a reticle. The computer solution of equations derived from a theoretical model showed that the greatest probability of detection for a given star and background intensity occurred with the use of a single transparent slit. However, use of multiple slits improved the system's ability to reject the detection of undesirable lower intensity stars, but only by decreasing the probability of detection for lower intensity stars to be mapped. Also, it was found that the coding arrangement affected the root-mean-square star-position error and that detection is possible with error in the system's detected spin rate, though at a reduced probability.

Discrete coding of stimulus value, reward expectation, and reward prediction error in the dorsal striatum.

PubMed

Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N; Iijima, Toshio; Tsutsui, Ken-Ichiro

2015-11-01

To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. Copyright © 2015 the American Physiological Society.

Discrete coding of stimulus value, reward expectation, and reward prediction error in the dorsal striatum

PubMed Central

Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N.; Iijima, Toshio

2015-01-01

To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. PMID:26378201

Multiplicity Control in Structural Equation Modeling

ERIC Educational Resources Information Center

Cribbie, Robert A.

2007-01-01

Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

Probabilities of Occurrence of Baro-Fuze System Errors More Than 1000 Feet Too Low Due to Ignoring the Meteorological Forecast

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

Charles, B.N.

1955-05-12

Charts of the geographical distribution of the annual and seasonal D-values and their standard deviations at altitudes of 4500, 6000, and 7000 feeet over Eurasia are derived, which are used to estimate the frequency of baro system errors.

Rewriting evolution--"been there, done that".

PubMed

Penny, David

2013-01-01

A recent paper by a science journalist in Nature shows major errors in understanding phylogenies, in this case of placental mammals. The underlying unrooted tree is probably correct, but the placement of the root just reflects a well-known error from the acceleration in the rate of evolution among some myomorph rodents.

Causal inference with measurement error in outcomes: Bias analysis and estimation methods.

PubMed

Shu, Di; Yi, Grace Y

2017-01-01

Inverse probability weighting estimation has been popularly used to consistently estimate the average treatment effect. Its validity, however, is challenged by the presence of error-prone variables. In this paper, we explore the inverse probability weighting estimation with mismeasured outcome variables. We study the impact of measurement error for both continuous and discrete outcome variables and reveal interesting consequences of the naive analysis which ignores measurement error. When a continuous outcome variable is mismeasured under an additive measurement error model, the naive analysis may still yield a consistent estimator; when the outcome is binary, we derive the asymptotic bias in a closed-form. Furthermore, we develop consistent estimation procedures for practical scenarios where either validation data or replicates are available. With validation data, we propose an efficient method for estimation of average treatment effect; the efficiency gain is substantial relative to usual methods of using validation data. To provide protection against model misspecification, we further propose a doubly robust estimator which is consistent even when either the treatment model or the outcome model is misspecified. Simulation studies are reported to assess the performance of the proposed methods. An application to a smoking cessation dataset is presented.

Joint Transmitter and Receiver Power Allocation under Minimax MSE Criterion with Perfect and Imperfect CSI for MC-CDMA Transmissions

NASA Astrophysics Data System (ADS)

Kotchasarn, Chirawat; Saengudomlert, Poompat

We investigate the problem of joint transmitter and receiver power allocation with the minimax mean square error (MSE) criterion for uplink transmissions in a multi-carrier code division multiple access (MC-CDMA) system. The objective of power allocation is to minimize the maximum MSE among all users each of which has limited transmit power. This problem is a nonlinear optimization problem. Using the Lagrange multiplier method, we derive the Karush-Kuhn-Tucker (KKT) conditions which are necessary for a power allocation to be optimal. Numerical results indicate that, compared to the minimum total MSE criterion, the minimax MSE criterion yields a higher total MSE but provides a fairer treatment across the users. The advantages of the minimax MSE criterion are more evident when we consider the bit error rate (BER) estimates. Numerical results show that the minimax MSE criterion yields a lower maximum BER and a lower average BER. We also observe that, with the minimax MSE criterion, some users do not transmit at full power. For comparison, with the minimum total MSE criterion, all users transmit at full power. In addition, we investigate robust joint transmitter and receiver power allocation where the channel state information (CSI) is not perfect. The CSI error is assumed to be unknown but bounded by a deterministic value. This problem is formulated as a semidefinite programming (SDP) problem with bilinear matrix inequality (BMI) constraints. Numerical results show that, with imperfect CSI, the minimax MSE criterion also outperforms the minimum total MSE criterion in terms of the maximum and average BERs.

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects.

PubMed

Sollmann, Nico; Hauck, Theresa; Tussis, Lorena; Ille, Sebastian; Maurer, Stefanie; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-10-24

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated. Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7-30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0-26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9-27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0-24.2 mm) were measured. According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

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

USGS Publications Warehouse

Moss, Marshall E.; Gilroy, Edward J.

1980-01-01

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

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications

PubMed Central

Kim, Changhwa; Shin, DongHyun

2017-01-01

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss. PMID:28498312

A Formal Approach to the Selection by Minimum Error and Pattern Method for Sensor Data Loss Reduction in Unstable Wireless Sensor Network Communications.

PubMed

Kim, Changhwa; Shin, DongHyun

2017-05-12

There are wireless networks in which typically communications are unsafe. Most terrestrial wireless sensor networks belong to this category of networks. Another example of an unsafe communication network is an underwater acoustic sensor network (UWASN). In UWASNs in particular, communication failures occur frequently and the failure durations can range from seconds up to a few hours, days, or even weeks. These communication failures can cause data losses significant enough to seriously damage human life or property, depending on their application areas. In this paper, we propose a framework to reduce sensor data loss during communication failures and we present a formal approach to the Selection by Minimum Error and Pattern (SMEP) method that plays the most important role for the reduction in sensor data loss under the proposed framework. The SMEP method is compared with other methods to validate its effectiveness through experiments using real-field sensor data sets. Moreover, based on our experimental results and performance comparisons, the SMEP method has been validated to be better than others in terms of the average sensor data value error rate caused by sensor data loss.

Minimum-norm cortical source estimation in layered head models is robust against skull conductivity error☆☆☆

PubMed Central

Stenroos, Matti; Hauk, Olaf

2013-01-01

The conductivity profile of the head has a major effect on EEG signals, but unfortunately the conductivity for the most important compartment, skull, is only poorly known. In dipole modeling studies, errors in modeled skull conductivity have been considered to have a detrimental effect on EEG source estimation. However, as dipole models are very restrictive, those results cannot be generalized to other source estimation methods. In this work, we studied the sensitivity of EEG and combined MEG + EEG source estimation to errors in skull conductivity using a distributed source model and minimum-norm (MN) estimation. We used a MEG/EEG modeling set-up that reflected state-of-the-art practices of experimental research. Cortical surfaces were segmented and realistically-shaped three-layer anatomical head models were constructed, and forward models were built with Galerkin boundary element method while varying the skull conductivity. Lead-field topographies and MN spatial filter vectors were compared across conductivities, and the localization and spatial spread of the MN estimators were assessed using intuitive resolution metrics. The results showed that the MN estimator is robust against errors in skull conductivity: the conductivity had a moderate effect on amplitudes of lead fields and spatial filter vectors, but the effect on corresponding morphologies was small. The localization performance of the EEG or combined MEG + EEG MN estimator was only minimally affected by the conductivity error, while the spread of the estimate varied slightly. Thus, the uncertainty with respect to skull conductivity should not prevent researchers from applying minimum norm estimation to EEG or combined MEG + EEG data. Comparing our results to those obtained earlier with dipole models shows that general judgment on the performance of an imaging modality should not be based on analysis with one source estimation method only. PMID:23639259

Macular Ganglion Cell and Retinal Nerve Fiber Layer Thickness in Children With Refractive Errors-An Optical Coherence Tomography Study.

PubMed

Goh, Jody P; Koh, Victor; Chan, Yiong Huak; Ngo, Cheryl

2017-07-01

To study the distribution of macular ganglion cell-inner plexiform layer (GC-IPL) thickness and peripapillary retinal nerve fiber layer (RNFL) thickness in children with refractive errors. Two hundred forty-three healthy eyes from 139 children with refractive error ranging from -10.00 to +5.00 D were recruited from the National University Hospital Eye Surgery outpatient clinic. After a comprehensive ocular examination, refraction, and axial length (AL) measurement (IOLMaster), macular GC-IPL and RNFL thickness values were obtained with a spectral domain Cirrus high definition optical coherence tomography system (Carl Zeiss Meditec Inc.). Only scans with signal strength of >6/10 were included. Correlation between variables was calculated using the Pearson correlation coefficient. A multivariate analysis using mixed models was done to adjust for confounders. The mean spherical equivalent refraction was -3.20±3.51 D and mean AL was 24.39±1.72 mm. Average, minimum, superior, and inferior GC-IPL were 82.59±6.29, 77.17±9.65, 83.68±6.96, and 81.64±6.70 μm, respectively. Average, superior, and inferior peripapillary RNFL were 99.00±11.45, 123.20±25.81, and 124.24±22.23 μm, respectively. Average, superior, and inferior GC-IPL were correlated with AL (β=-2.056, P-value 0.000; β=-2.383, P-value 0.000; β=-1.721, P-value 0.000), but minimum GC-IPL was not (β=-1.056, P-value 0.115). None of the RNFL parameters were correlated with AL. This study establishes normative macular GC-IPL and RNFL thickness in children with refractive errors. Our results suggest that high definition optical coherence tomography RNFL parameters and minimum GC-IPL are not affected by AL or myopia in children, and therefore warrants further evaluation in pediatric glaucoma patients.

Performance optimization of dense-array concentrator photovoltaic system considering effects of circumsolar radiation and slope error.

PubMed

Wong, Chee-Woon; Chong, Kok-Keong; Tan, Ming-Hui

2015-07-27

This paper presents an approach to optimize the electrical performance of dense-array concentrator photovoltaic system comprised of non-imaging dish concentrator by considering the circumsolar radiation and slope error effects. Based on the simulated flux distribution, a systematic methodology to optimize the layout configuration of solar cells interconnection circuit in dense array concentrator photovoltaic module has been proposed by minimizing the current mismatch caused by non-uniformity of concentrated sunlight. An optimized layout of interconnection solar cells circuit with minimum electrical power loss of 6.5% can be achieved by minimizing the effects of both circumsolar radiation and slope error.

New syndrome decoding techniques for the (n, k) convolutional codes

NASA Technical Reports Server (NTRS)

Reed, I. S.; Truong, T. K.

1984-01-01

This paper presents a new syndrome decoding algorithm for the (n, k) convolutional codes (CC) which differs completely from an earlier syndrome decoding algorithm of Schalkwijk and Vinck. The new algorithm is based on the general solution of the syndrome equation, a linear Diophantine equation for the error polynomial vector E(D). The set of Diophantine solutions is a coset of the CC. In this error coset a recursive, Viterbi-like algorithm is developed to find the minimum weight error vector (circumflex)E(D). An example, illustrating the new decoding algorithm, is given for the binary nonsystemmatic (3, 1)CC. Previously announced in STAR as N83-34964

The effects of recall errors and of selection bias in epidemiologic studies of mobile phone use and cancer risk.

PubMed

Vrijheid, Martine; Deltour, Isabelle; Krewski, Daniel; Sanchez, Marie; Cardis, Elisabeth

2006-07-01

This paper examines the effects of systematic and random errors in recall and of selection bias in case-control studies of mobile phone use and cancer. These sensitivity analyses are based on Monte-Carlo computer simulations and were carried out within the INTERPHONE Study, an international collaborative case-control study in 13 countries. Recall error scenarios simulated plausible values of random and systematic, non-differential and differential recall errors in amount of mobile phone use reported by study subjects. Plausible values for the recall error were obtained from validation studies. Selection bias scenarios assumed varying selection probabilities for cases and controls, mobile phone users, and non-users. Where possible these selection probabilities were based on existing information from non-respondents in INTERPHONE. Simulations used exposure distributions based on existing INTERPHONE data and assumed varying levels of the true risk of brain cancer related to mobile phone use. Results suggest that random recall errors of plausible levels can lead to a large underestimation in the risk of brain cancer associated with mobile phone use. Random errors were found to have larger impact than plausible systematic errors. Differential errors in recall had very little additional impact in the presence of large random errors. Selection bias resulting from underselection of unexposed controls led to J-shaped exposure-response patterns, with risk apparently decreasing at low to moderate exposure levels. The present results, in conjunction with those of the validation studies conducted within the INTERPHONE study, will play an important role in the interpretation of existing and future case-control studies of mobile phone use and cancer risk, including the INTERPHONE study.

Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

PubMed

Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

2013-09-01

The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.

On the Importance of Cycle Minimum in Sunspot Cycle Prediction

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.; Reichmann, Edwin J.

1996-01-01

The characteristics of the minima between sunspot cycles are found to provide important information for predicting the amplitude and timing of the following cycle. For example, the time of the occurrence of sunspot minimum sets the length of the previous cycle, which is correlated by the amplitude-period effect to the amplitude of the next cycle, with cycles of shorter (longer) than average length usually being followed by cycles of larger (smaller) than average size (true for 16 of 21 sunspot cycles). Likewise, the size of the minimum at cycle onset is correlated with the size of the cycle's maximum amplitude, with cycles of larger (smaller) than average size minima usually being associated with larger (smaller) than average size maxima (true for 16 of 22 sunspot cycles). Also, it was found that the size of the previous cycle's minimum and maximum relates to the size of the following cycle's minimum and maximum with an even-odd cycle number dependency. The latter effect suggests that cycle 23 will have a minimum and maximum amplitude probably larger than average in size (in particular, minimum smoothed sunspot number Rm = 12.3 +/- 7.5 and maximum smoothed sunspot number RM = 198.8 +/- 36.5, at the 95-percent level of confidence), further suggesting (by the Waldmeier effect) that it will have a faster than average rise to maximum (fast-rising cycles have ascent durations of about 41 +/- 7 months). Thus, if, as expected, onset for cycle 23 will be December 1996 +/- 3 months, based on smoothed sunspot number, then the length of cycle 22 will be about 123 +/- 3 months, inferring that it is a short-period cycle and that cycle 23 maximum amplitude probably will be larger than average in size (from the amplitude-period effect), having an RM of about 133 +/- 39 (based on the usual +/- 30 percent spread that has been seen between observed and predicted values), with maximum amplitude occurrence likely sometime between July 1999 and October 2000.

Optimization of traffic data collection for specific pavement design applications.

DOT National Transportation Integrated Search

2006-05-01

The objective of this study is to establish the minimum traffic data collection effort required for pavement design applications satisfying a maximum acceptable error under a prescribed confidence level. The approach consists of simulating the traffi...

Probability of Detection of Genotyping Errors and Mutations as Inheritance Inconsistencies in Nuclear-Family Data

PubMed Central

Douglas, Julie A.; Skol, Andrew D.; Boehnke, Michael

2002-01-01

Gene-mapping studies routinely rely on checking for Mendelian transmission of marker alleles in a pedigree, as a means of screening for genotyping errors and mutations, with the implicit assumption that, if a pedigree is consistent with Mendel’s laws of inheritance, then there are no genotyping errors. However, the occurrence of inheritance inconsistencies alone is an inadequate measure of the number of genotyping errors, since the rate of occurrence depends on the number and relationships of genotyped pedigree members, the type of errors, and the distribution of marker-allele frequencies. In this article, we calculate the expected probability of detection of a genotyping error or mutation as an inheritance inconsistency in nuclear-family data, as a function of both the number of genotyped parents and offspring and the marker-allele frequency distribution. Through computer simulation, we explore the sensitivity of our analytic calculations to the underlying error model. Under a random-allele–error model, we find that detection rates are 51%–77% for multiallelic markers and 13%–75% for biallelic markers; detection rates are generally lower when the error occurs in a parent than in an offspring, unless a large number of offspring are genotyped. Errors are especially difficult to detect for biallelic markers with equally frequent alleles, even when both parents are genotyped; in this case, the maximum detection rate is 34% for four-person nuclear families. Error detection in families in which parents are not genotyped is limited, even with multiallelic markers. Given these results, we recommend that additional error checking (e.g., on the basis of multipoint analysis) be performed, beyond routine checking for Mendelian consistency. Furthermore, our results permit assessment of the plausibility of an observed number of inheritance inconsistencies for a family, allowing the detection of likely pedigree—rather than genotyping—errors in the early stages of a genome scan. Such early assessments are valuable in either the targeting of families for resampling or discontinued genotyping. PMID:11791214

Error Discounting in Probabilistic Category Learning

PubMed Central

Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.

2011-01-01

Some current theories of probabilistic categorization assume that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report two probabilistic-categorization experiments that investigated error discounting by shifting feedback probabilities to new values after different amounts of training. In both experiments, responding gradually became less responsive to errors, and learning was slowed for some time after the feedback shift. Both results are indicative of error discounting. Quantitative modeling of the data revealed that adding a mechanism for error discounting significantly improved the fits of an exemplar-based and a rule-based associative learning model, as well as of a recency-based model of categorization. We conclude that error discounting is an important component of probabilistic learning. PMID:21355666

Modeling of a bubble-memory organization with self-checking translators to achieve high reliability.

NASA Technical Reports Server (NTRS)

Bouricius, W. G.; Carter, W. C.; Hsieh, E. P.; Wadia, A. B.; Jessep, D. C., Jr.

1973-01-01

Study of the design and modeling of a highly reliable bubble-memory system that has the capabilities of: (1) correcting a single 16-adjacent bit-group error resulting from failures in a single basic storage module (BSM), and (2) detecting with a probability greater than 0.99 any double errors resulting from failures in BSM's. The results of the study justify the design philosophy adopted of employing memory data encoding and a translator to correct single group errors and detect double group errors to enhance the overall system reliability.

Experimental investigation of false positive errors in auditory species occurrence surveys

USGS Publications Warehouse

Miller, David A.W.; Weir, Linda A.; McClintock, Brett T.; Grant, Evan H. Campbell; Bailey, Larissa L.; Simons, Theodore R.

2012-01-01

False positive errors are a significant component of many ecological data sets, which in combination with false negative errors, can lead to severe biases in conclusions about ecological systems. We present results of a field experiment where observers recorded observations for known combinations of electronically broadcast calling anurans under conditions mimicking field surveys to determine species occurrence. Our objectives were to characterize false positive error probabilities for auditory methods based on a large number of observers, to determine if targeted instruction could be used to reduce false positive error rates, and to establish useful predictors of among-observer and among-species differences in error rates. We recruited 31 observers, ranging in abilities from novice to expert, that recorded detections for 12 species during 180 calling trials (66,960 total observations). All observers made multiple false positive errors and on average 8.1% of recorded detections in the experiment were false positive errors. Additional instruction had only minor effects on error rates. After instruction, false positive error probabilities decreased by 16% for treatment individuals compared to controls with broad confidence interval overlap of 0 (95% CI: -46 to 30%). This coincided with an increase in false negative errors due to the treatment (26%; -3 to 61%). Differences among observers in false positive and in false negative error rates were best predicted by scores from an online test and a self-assessment of observer ability completed prior to the field experiment. In contrast, years of experience conducting call surveys was a weak predictor of error rates. False positive errors were also more common for species that were played more frequently, but were not related to the dominant spectral frequency of the call. Our results corroborate other work that demonstrates false positives are a significant component of species occurrence data collected by auditory methods. Instructing observers to only report detections they are completely certain are correct is not sufficient to eliminate errors. As a result, analytical methods that account for false positive errors will be needed, and independent testing of observer ability is a useful predictor for among-observer variation in observation error rates.

Measurement-device-independent quantum key distribution with source state errors and statistical fluctuation

NASA Astrophysics Data System (ADS)

Jiang, Cong; Yu, Zong-Wen; Wang, Xiang-Bin

2017-03-01

We show how to calculate the secure final key rate in the four-intensity decoy-state measurement-device-independent quantum key distribution protocol with both source errors and statistical fluctuations with a certain failure probability. Our results rely only on the range of only a few parameters in the source state. All imperfections in this protocol have been taken into consideration without assuming any specific error patterns of the source.

Minimum probe length for unique identification of all open reading frames in a microbial genome

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

Sokhansanj, B A; Ng, J; Fitch, J P

2000-03-05

In this paper, we determine the minimum hybridization probe length to uniquely identify at least 95% of the open reading frame (ORF) in an organism. We analyze the whole genome sequences of 17 species, 11 bacteria, 4 archaea, and 2 eukaryotes. We also present a mathematical model for minimum probe length based on assuming that all ORFs are random, of constant length, and contain an equal distribution of bases. The model accurately predicts the minimum probe length for all species, but it incorrectly predicts that all ORFs may be uniquely identified. However, a probe length of just 9 bases ismore » adequate to identify over 95% of the ORFs for all 15 prokaryotic species we studied. Using a minimum probe length, while accepting that some ORFs may not be identified and that data will be lost due to hybridization error, may result in significant savings in microarray and oligonucleotide probe design.« less

A cascaded coding scheme for error control and its performance analysis

NASA Technical Reports Server (NTRS)

Lin, Shu; Kasami, Tadao; Fujiwara, Tohru; Takata, Toyoo

1986-01-01

A coding scheme is investigated for error control in data communication systems. The scheme is obtained by cascading two error correcting codes, called the inner and outer codes. The error performance of the scheme is analyzed for a binary symmetric channel with bit error rate epsilon <1/2. It is shown that if the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit error rate. Various specific example schemes with inner codes ranging form high rates to very low rates and Reed-Solomon codes as inner codes are considered, and their error probabilities are evaluated. They all provide extremely high reliability even for very high bit error rates. Several example schemes are being considered by NASA for satellite and spacecraft down link error control.

Asymmetries in Predictive and Diagnostic Reasoning

ERIC Educational Resources Information Center

Fernbach, Philip M.; Darlow, Adam; Sloman, Steven A.

2011-01-01

In this article, we address the apparent discrepancy between causal Bayes net theories of cognition, which posit that judgments of uncertainty are generated from causal beliefs in a way that respects the norms of probability, and evidence that probability judgments based on causal beliefs are systematically in error. One purported source of bias…

Anytime synthetic projection: Maximizing the probability of goal satisfaction

NASA Technical Reports Server (NTRS)

Drummond, Mark; Bresina, John L.

1990-01-01

A projection algorithm is presented for incremental control rule synthesis. The algorithm synthesizes an initial set of goal achieving control rules using a combination of situation probability and estimated remaining work as a search heuristic. This set of control rules has a certain probability of satisfying the given goal. The probability is incrementally increased by synthesizing additional control rules to handle 'error' situations the execution system is likely to encounter when following the initial control rules. By using situation probabilities, the algorithm achieves a computationally effective balance between the limited robustness of triangle tables and the absolute robustness of universal plans.

Bounds on Block Error Probability for Multilevel Concatenated Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Moorthy, Hari T.; Stojanovic, Diana

1996-01-01

Maximum likelihood decoding of long block codes is not feasable due to large complexity. Some classes of codes are shown to be decomposable into multilevel concatenated codes (MLCC). For these codes, multistage decoding provides good trade-off between performance and complexity. In this paper, we derive an upper bound on the probability of block error for MLCC. We use this bound to evaluate difference in performance for different decompositions of some codes. Examples given show that a significant reduction in complexity can be achieved when increasing number of stages of decoding. Resulting performance degradation varies for different decompositions. A guideline is given for finding good m-level decompositions.

Performance of DPSK with convolutional encoding on time-varying fading channels

NASA Technical Reports Server (NTRS)

Mui, S. Y.; Modestino, J. W.

1977-01-01

The bit error probability performance of a differentially-coherent phase-shift keyed (DPSK) modem with convolutional encoding and Viterbi decoding on time-varying fading channels is examined. Both the Rician and the lognormal channels are considered. Bit error probability upper bounds on fully-interleaved (zero-memory) fading channels are derived and substantiated by computer simulation. It is shown that the resulting coded system performance is a relatively insensitive function of the choice of channel model provided that the channel parameters are related according to the correspondence developed as part of this paper. Finally, a comparison of DPSK with a number of other modulation strategies is provided.

Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks

PubMed Central

Nasir, Hina; Javaid, Nadeem; Sher, Muhammad; Qasim, Umar; Khan, Zahoor Ali; Alrajeh, Nabil; Niaz, Iftikhar Azim

2016-01-01

This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs); performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE) efficient depth based routing and Enhanced-ACE (E-ACE) are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ). E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment. PMID:27420061

Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions.

PubMed

Potter, Gail E; Smieszek, Timo; Sailer, Kerstin

2015-09-01

Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0-5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models.

Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions

PubMed Central

Potter, Gail E.; Smieszek, Timo; Sailer, Kerstin

2015-01-01

Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models. PMID:26634122

Extended target recognition in cognitive radar networks.

PubMed

Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

2010-01-01

We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches.

A Rational Approach to Determine Minimum Strength Thresholds in Novel Structural Materials

NASA Technical Reports Server (NTRS)

Schur, Willi W.; Bilen, Canan; Sterling, Jerry

2003-01-01

Design of safe and survivable structures requires the availability of guaranteed minimum strength thresholds for structural materials to enable a meaningful comparison of strength requirement and available strength. This paper develops a procedure for determining such a threshold with a desired degree of confidence, for structural materials with none or minimal industrial experience. The problem arose in attempting to use a new, highly weight-efficient structural load tendon material to achieve a lightweight super-pressure balloon. The developed procedure applies to lineal (one dimensional) structural elements. One important aspect of the formulation is that it extrapolates to expected probability distributions for long length specimen samples from some hypothesized probability distribution that has been obtained from a shorter length specimen sample. The use of the developed procedure is illustrated using both real and simulated data.

Environmental Assessment, Repair of the Dam at Non-Potable Reservoir #1, United States Air Force Academy, Colorado

DTIC Science & Technology

2015-08-01

crimping alone is insufficient. Hydro-mulch shall be applied using a color dye and the manufacturer’s recommended rate of an organic tackifier. D...drainage areas where erosion is probable. All erosion control blanket shall be 100% biodegradable , net- free, wood fiber (excelsior) or coconut...Manufactured biodegradable stakes (6-inch minimum) or wooden stakes (8-inch minimum) shall be used to anchor any erosion materials; metal staples

On higher order discrete phase-locked loops.

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

A high speed sequential decoder

NASA Technical Reports Server (NTRS)

Lum, H., Jr.

1972-01-01

The performance and theory of operation for the High Speed Hard Decision Sequential Decoder are delineated. The decoder is a forward error correction system which is capable of accepting data from binary-phase-shift-keyed and quadriphase-shift-keyed modems at input data rates up to 30 megabits per second. Test results show that the decoder is capable of maintaining a composite error rate of 0.00001 at an input E sub b/N sub o of 5.6 db. This performance has been obtained with minimum circuit complexity.

Asymmetric soft-error resistant memory

NASA Technical Reports Server (NTRS)

Buehler, Martin G. (Inventor); Perlman, Marvin (Inventor)

1991-01-01

A memory system is provided, of the type that includes an error-correcting circuit that detects and corrects, that more efficiently utilizes the capacity of a memory formed of groups of binary cells whose states can be inadvertently switched by ionizing radiation. Each memory cell has an asymmetric geometry, so that ionizing radiation causes a significantly greater probability of errors in one state than in the opposite state (e.g., an erroneous switch from '1' to '0' is far more likely than a switch from '0' to'1'. An asymmetric error correcting coding circuit can be used with the asymmetric memory cells, which requires fewer bits than an efficient symmetric error correcting code.

Discrimination of binary coherent states using a homodyne detector and a photon number resolving detector

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

Wittmann, Christoffer; Sych, Denis; Leuchs, Gerd

2010-06-15

We investigate quantum measurement strategies capable of discriminating two coherent states probabilistically with significantly smaller error probabilities than can be obtained using nonprobabilistic state discrimination. We apply a postselection strategy to the measurement data of a homodyne detector as well as a photon number resolving detector in order to lower the error probability. We compare the two different receivers with an optimal intermediate measurement scheme where the error rate is minimized for a fixed rate of inconclusive results. The photon number resolving (PNR) receiver is experimentally demonstrated and compared to an experimental realization of a homodyne receiver with postselection. Inmore » the comparison, it becomes clear that the performance of the PNR receiver surpasses the performance of the homodyne receiver, which we prove to be optimal within any Gaussian operations and conditional dynamics.« less

The genomic structure: proof of the role of non-coding DNA.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2006-01-01

We prove that the introns play the role of a decoy in absorbing mutations in the same way hollow uninhabited structures are used by the military to protect important installations. Our approach is based on a probability of error analysis, where errors are mutations which occur in the exon sequences. We derive the optimal exon length distribution, which minimizes the probability of error in the genome. Furthermore, to understand how can Nature generate the optimal distribution, we propose a diffusive random walk model for exon generation throughout evolution. This model results in an alpha stable exon length distribution, which is asymptotically equivalent to the optimal distribution. Experimental results show that both distributions accurately fit the real data. Given that introns also drive biological evolution by increasing the rate of unequal crossover between genes, we conclude that the role of introns is to maintain a genius balance between stability and adaptability in eukaryotic genomes.

Peelle's pertinent puzzle using the Monte Carlo technique

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

Kawano, Toshihiko; Talou, Patrick; Burr, Thomas

2009-01-01

We try to understand the long-standing problem of the Peelle's Pertinent Puzzle (PPP) using the Monte Carlo technique. We allow the probability density functions to be any kind of form to assume the impact of distribution, and obtain the least-squares solution directly from numerical simulations. We found that the standard least squares method gives the correct answer if a weighting function is properly provided. Results from numerical simulations show that the correct answer of PPP is 1.1 {+-} 0.25 if the common error is multiplicative. The thought-provoking answer of 0.88 is also correct, if the common error is additive, andmore » if the error is proportional to the measured values. The least squares method correctly gives us the most probable case, where the additive component has a negative value. Finally, the standard method fails for PPP due to a distorted (non Gaussian) joint distribution.« less

Driver landmark and traffic sign identification in early Alzheimer's disease.

PubMed

Uc, E Y; Rizzo, M; Anderson, S W; Shi, Q; Dawson, J D

2005-06-01

To assess visual search and recognition of roadside targets and safety errors during a landmark and traffic sign identification task in drivers with Alzheimer's disease. 33 drivers with probable Alzheimer's disease of mild severity and 137 neurologically normal older adults underwent a battery of visual and cognitive tests and were asked to report detection of specific landmarks and traffic signs along a segment of an experimental drive. The drivers with mild Alzheimer's disease identified significantly fewer landmarks and traffic signs and made more at-fault safety errors during the task than control subjects. Roadside target identification performance and safety errors were predicted by scores on standardised tests of visual and cognitive function. Drivers with Alzheimer's disease are impaired in a task of visual search and recognition of roadside targets; the demands of these targets on visual perception, attention, executive functions, and memory probably increase the cognitive load, worsening driving safety.

Resolving Mixed Algal Species in Hyperspectral Images

PubMed Central

Mehrubeoglu, Mehrube; Teng, Ming Y.; Zimba, Paul V.

2014-01-01

We investigated a lab-based hyperspectral imaging system's response from pure (single) and mixed (two) algal cultures containing known algae types and volumetric combinations to characterize the system's performance. The spectral response to volumetric changes in single and combinations of algal mixtures with known ratios were tested. Constrained linear spectral unmixing was applied to extract the algal content of the mixtures based on abundances that produced the lowest root mean square error. Percent prediction error was computed as the difference between actual percent volumetric content and abundances at minimum RMS error. Best prediction errors were computed as 0.4%, 0.4% and 6.3% for the mixed spectra from three independent experiments. The worst prediction errors were found as 5.6%, 5.4% and 13.4% for the same order of experiments. Additionally, Beer-Lambert's law was utilized to relate transmittance to different volumes of pure algal suspensions demonstrating linear logarithmic trends for optical property measurements. PMID:24451451

29 CFR 18.103 - Rulings on evidence.

Code of Federal Regulations, 2010 CFR

2010-07-01

... is more probably true than not true that the error did not materially contribute to the decision or... if explicitly not relied upon by the judge in support of the decision or order. (b) Record of offer... making of an offer in question and answer form. (c) Plain error. Nothing in this rule precludes taking...

Student Distractor Choices on the Mathematics Virginia Standards of Learning Middle School Assessments

ERIC Educational Resources Information Center

Lewis, Virginia Vimpeny

2011-01-01

Number Concepts; Measurement; Geometry; Probability; Statistics; and Patterns, Functions and Algebra. Procedural Errors were further categorized into the following content categories: Computation; Measurement; Statistics; and Patterns, Functions, and Algebra. The results of the analysis showed the main sources of error for 6th, 7th, and 8th…

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

Rewriting Evolution—“Been There, Done That”

PubMed Central

Penny, David

2013-01-01

A recent paper by a science journalist in Nature shows major errors in understanding phylogenies, in this case of placental mammals. The underlying unrooted tree is probably correct, but the placement of the root just reflects a well-known error from the acceleration in the rate of evolution among some myomorph rodents. PMID:23558594

Dosimetric effects of patient rotational setup errors on prostate IMRT treatments

NASA Astrophysics Data System (ADS)

Fu, Weihua; Yang, Yong; Li, Xiang; Heron, Dwight E.; Saiful Huq, M.; Yue, Ning J.

2006-10-01

The purpose of this work is to determine dose delivery errors that could result from systematic rotational setup errors (ΔΦ) for prostate cancer patients treated with three-phase sequential boost IMRT. In order to implement this, different rotational setup errors around three Cartesian axes were simulated for five prostate patients and dosimetric indices, such as dose-volume histogram (DVH), tumour control probability (TCP), normal tissue complication probability (NTCP) and equivalent uniform dose (EUD), were employed to evaluate the corresponding dosimetric influences. Rotational setup errors were simulated by adjusting the gantry, collimator and horizontal couch angles of treatment beams and the dosimetric effects were evaluated by recomputing the dose distributions in the treatment planning system. Our results indicated that, for prostate cancer treatment with the three-phase sequential boost IMRT technique, the rotational setup errors do not have significant dosimetric impacts on the cumulative plan. Even in the worst-case scenario with ΔΦ = 3°, the prostate EUD varied within 1.5% and TCP decreased about 1%. For seminal vesicle, slightly larger influences were observed. However, EUD and TCP changes were still within 2%. The influence on sensitive structures, such as rectum and bladder, is also negligible. This study demonstrates that the rotational setup error degrades the dosimetric coverage of target volume in prostate cancer treatment to a certain degree. However, the degradation was not significant for the three-phase sequential boost prostate IMRT technique and for the margin sizes used in our institution.

An MEG signature corresponding to an axiomatic model of reward prediction error.

PubMed

Talmi, Deborah; Fuentemilla, Lluis; Litvak, Vladimir; Duzel, Emrah; Dolan, Raymond J

2012-01-02

Optimal decision-making is guided by evaluating the outcomes of previous decisions. Prediction errors are theoretical teaching signals which integrate two features of an outcome: its inherent value and prior expectation of its occurrence. To uncover the magnetic signature of prediction errors in the human brain we acquired magnetoencephalographic (MEG) data while participants performed a gambling task. Our primary objective was to use formal criteria, based upon an axiomatic model (Caplin and Dean, 2008a), to determine the presence and timing profile of MEG signals that express prediction errors. We report analyses at the sensor level, implemented in SPM8, time locked to outcome onset. We identified, for the first time, a MEG signature of prediction error, which emerged approximately 320 ms after an outcome and expressed as an interaction between outcome valence and probability. This signal followed earlier, separate signals for outcome valence and probability, which emerged approximately 200 ms after an outcome. Strikingly, the time course of the prediction error signal, as well as the early valence signal, resembled the Feedback-Related Negativity (FRN). In simultaneously acquired EEG data we obtained a robust FRN, but the win and loss signals that comprised this difference wave did not comply with the axiomatic model. Our findings motivate an explicit examination of the critical issue of timing embodied in computational models of prediction errors as seen in human electrophysiological data. Copyright © 2011 Elsevier Inc. All rights reserved.

Testing boundary conditions for the conjunction fallacy: effects of response mode, conceptual focus, and problem type.

PubMed

Wedell, Douglas H; Moro, Rodrigo

2008-04-01

Two experiments used within-subject designs to examine how conjunction errors depend on the use of (1) choice versus estimation tasks, (2) probability versus frequency language, and (3) conjunctions of two likely events versus conjunctions of likely and unlikely events. All problems included a three-option format verified to minimize misinterpretation of the base event. In both experiments, conjunction errors were reduced when likely events were conjoined. Conjunction errors were also reduced for estimations compared with choices, with this reduction greater for likely conjuncts, an interaction effect. Shifting conceptual focus from probabilities to frequencies did not affect conjunction error rates. Analyses of numerical estimates for a subset of the problems provided support for the use of three general models by participants for generating estimates. Strikingly, the order in which the two tasks were carried out did not affect the pattern of results, supporting the idea that the mode of responding strongly determines the mode of thinking about conjunctions and hence the occurrence of the conjunction fallacy. These findings were evaluated in terms of implications for rationality of human judgment and reasoning.

Avoiding the ensemble decorrelation problem using member-by-member post-processing

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2014-05-01

Forecast calibration or post-processing has become a standard tool in atmospheric and climatological science due to the presence of systematic initial condition and model errors. For ensemble forecasts the most competitive methods derive from the assumption of a fixed ensemble distribution. However, when independently applying such 'statistical' methods at different locations, lead times or for multiple variables the correlation structure for individual ensemble members is destroyed. Instead of reastablishing the correlation structure as in Schefzik et al. (2013) we instead propose a calibration method that avoids such problem by correcting each ensemble member individually. Moreover, we analyse the fundamental mechanisms by which the probabilistic ensemble skill can be enhanced. In terms of continuous ranked probability score, our member-by-member approach amounts to skill gain that extends for lead times far beyond the error doubling time and which is as good as the one of the most competitive statistical approach, non-homogeneous Gaussian regression (Gneiting et al. 2005). Besides the conservation of correlation structure, additional benefits arise including the fact that higher-order ensemble moments like kurtosis and skewness are inherited from the uncorrected forecasts. Our detailed analysis is performed in the context of the Kuramoto-Sivashinsky equation and different simple models but the results extent succesfully to the ensemble forecast of the European Centre for Medium-Range Weather Forecasts (Van Schaeybroeck and Vannitsem, 2013, 2014) . References [1] Gneiting, T., Raftery, A. E., Westveld, A., Goldman, T., 2005: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Mon. Weather Rev. 133, 1098-1118. [2] Schefzik, R., T.L. Thorarinsdottir, and T. Gneiting, 2013: Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling. To appear in Statistical Science 28. [3] Van Schaeybroeck, B., and S. Vannitsem, 2013: Reliable probabilities through statistical post-processing of ensemble forecasts. Proceedings of the European Conference on Complex Systems 2012, Springer proceedings on complexity, XVI, p. 347-352. [4] Van Schaeybroeck, B., and S. Vannitsem, 2014: Ensemble post-processing using member-by-member approaches: theoretical aspects, under review.

Variance in age-specific sex composition of Pacific halibut catches, and comparison of statistical and genetic methods for reconstructing sex ratios

NASA Astrophysics Data System (ADS)

Loher, Timothy; Woods, Monica A.; Jimenez-Hidalgo, Isadora; Hauser, Lorenz

2016-01-01

Declines in size at age of Pacific halibut Hippoglossus stenolepis, in concert with sexually-dimorphic growth and a constant minimum commercial size limit, have led to the expectation that the sex composition of commercial catches should be increasingly female-biased. Sensitivity analyses suggest that variance in sex composition of landings may be the most influential source of uncertainty affecting current understanding of spawning stock biomass. However, there is no reliable way to determine sex at landing because all halibut are eviscerated at sea. In 2014, a statistical method based on survey data was developed to estimate the probability that fish of any given length at age (LAA) would be female, derived from the fundamental observation that large, young fish are likely female whereas small, old fish have a high probability of being male. Here, we examine variability in age-specific sex composition using at-sea commercial and closed-season survey catches, and compare the accuracy of the survey-based LAA technique to genetic markers for reconstructing the sex composition of catches. Sexing by LAA performed best for summer-collected samples, consistent with the hypothesis that the ability to characterize catches can be influenced by seasonal demographic shifts. Additionally, differences between survey and commercial selectivity that allow fishers to harvest larger fish within cohorts may generate important mismatch between survey and commercial datasets. Length-at-age-based estimates ranged from 4.7% underestimation of female proportion to 12.0% overestimation, with mean error of 5.8 ± 1.5%. Ratios determined by genetics were closer to true sample proportions and displayed less variability; estimation to within < 1% of true ratios was limited to genetics. Genetic estimation of female proportions ranged from 4.9% underestimation to 2.5% overestimation, with a mean absolute error of 1.2 ± 1.2%. Males were generally more difficult to assign than females: 6.7% of males and 3.4% of females were incorrectly assigned. Although nuclear microsatellites proved more consistent at partitioning catches by sex, we recommend that SNP assays be developed to allow for rapid, cost-effective, and accurate sex identification.

A Probabilistic, Facility-Centric Approach to Lightning Strike Location

NASA Technical Reports Server (NTRS)

Huddleston, Lisa L.; Roeder, William p.; Merceret, Francis J.

2012-01-01

A new probabilistic facility-centric approach to lightning strike location has been developed. This process uses the bivariate Gaussian distribution of probability density provided by the current lightning location error ellipse for the most likely location of a lightning stroke and integrates it to determine the probability that the stroke is inside any specified radius of any location, even if that location is not centered on or even with the location error ellipse. This technique is adapted from a method of calculating the probability of debris collisionith spacecraft. Such a technique is important in spaceport processing activities because it allows engineers to quantify the risk of induced current damage to critical electronics due to nearby lightning strokes. This technique was tested extensively and is now in use by space launch organizations at Kennedy Space Center and Cape Canaveral Air Force Station. Future applications could include forensic meteorology.

Maximum likelihood estimation of label imperfections and its use in the identification of mislabeled patterns

NASA Technical Reports Server (NTRS)

Chittineni, C. B.

1979-01-01

The problem of estimating label imperfections and the use of the estimation in identifying mislabeled patterns is presented. Expressions for the maximum likelihood estimates of classification errors and a priori probabilities are derived from the classification of a set of labeled patterns. Expressions also are given for the asymptotic variances of probability of correct classification and proportions. Simple models are developed for imperfections in the labels and for classification errors and are used in the formulation of a maximum likelihood estimation scheme. Schemes are presented for the identification of mislabeled patterns in terms of threshold on the discriminant functions for both two-class and multiclass cases. Expressions are derived for the probability that the imperfect label identification scheme will result in a wrong decision and are used in computing thresholds. The results of practical applications of these techniques in the processing of remotely sensed multispectral data are presented.

Qualitative fusion technique based on information poor system and its application to factor analysis for vibration of rolling bearings

NASA Astrophysics Data System (ADS)

Xia, Xintao; Wang, Zhongyu

2008-10-01

For some methods of stability analysis of a system using statistics, it is difficult to resolve the problems of unknown probability distribution and small sample. Therefore, a novel method is proposed in this paper to resolve these problems. This method is independent of probability distribution, and is useful for small sample systems. After rearrangement of the original data series, the order difference and two polynomial membership functions are introduced to estimate the true value, the lower bound and the supper bound of the system using fuzzy-set theory. Then empirical distribution function is investigated to ensure confidence level above 95%, and the degree of similarity is presented to evaluate stability of the system. Cases of computer simulation investigate stable systems with various probability distribution, unstable systems with linear systematic errors and periodic systematic errors and some mixed systems. The method of analysis for systematic stability is approved.

Clinical implementation and failure mode and effects analysis of HDR skin brachytherapy using Valencia and Leipzig surface applicators.

PubMed

Sayler, Elaine; Eldredge-Hindy, Harriet; Dinome, Jessie; Lockamy, Virginia; Harrison, Amy S

2015-01-01

The planning procedure for Valencia and Leipzig surface applicators (VLSAs) (Nucletron, Veenendaal, The Netherlands) differs substantially from CT-based planning; the unfamiliarity could lead to significant errors. This study applies failure modes and effects analysis (FMEA) to high-dose-rate (HDR) skin brachytherapy using VLSAs to ensure safety and quality. A multidisciplinary team created a protocol for HDR VLSA skin treatments and applied FMEA. Failure modes were identified and scored by severity, occurrence, and detectability. The clinical procedure was then revised to address high-scoring process nodes. Several key components were added to the protocol to minimize risk probability numbers. (1) Diagnosis, prescription, applicator selection, and setup are reviewed at weekly quality assurance rounds. Peer review reduces the likelihood of an inappropriate treatment regime. (2) A template for HDR skin treatments was established in the clinic's electronic medical record system to standardize treatment instructions. This reduces the chances of miscommunication between the physician and planner as well as increases the detectability of an error. (3) A screen check was implemented during the second check to increase detectability of an error. (4) To reduce error probability, the treatment plan worksheet was designed to display plan parameters in a format visually similar to the treatment console display, facilitating data entry and verification. (5) VLSAs are color coded and labeled to match the electronic medical record prescriptions, simplifying in-room selection and verification. Multidisciplinary planning and FMEA increased detectability and reduced error probability during VLSA HDR brachytherapy. This clinical model may be useful to institutions implementing similar procedures. Copyright © 2015 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

Resampling-Based Empirical Bayes Multiple Testing Procedures for Controlling Generalized Tail Probability and Expected Value Error Rates: Focus on the False Discovery Rate and Simulation Study

PubMed Central

Dudoit, Sandrine; Gilbert, Houston N.; van der Laan, Mark J.

2014-01-01

Summary This article proposes resampling-based empirical Bayes multiple testing procedures for controlling a broad class of Type I error rates, defined as generalized tail probability (gTP) error rates, gTP(q, g) = Pr(g(Vn, Sn) > q), and generalized expected value (gEV) error rates, gEV(g) = E[g(Vn, Sn)], for arbitrary functions g(Vn, Sn) of the numbers of false positives Vn and true positives Sn. Of particular interest are error rates based on the proportion g(Vn, Sn) = Vn/(Vn + Sn) of Type I errors among the rejected hypotheses, such as the false discovery rate (FDR), FDR = E[Vn/(Vn + Sn)]. The proposed procedures offer several advantages over existing methods. They provide Type I error control for general data generating distributions, with arbitrary dependence structures among variables. Gains in power are achieved by deriving rejection regions based on guessed sets of true null hypotheses and null test statistics randomly sampled from joint distributions that account for the dependence structure of the data. The Type I error and power properties of an FDR-controlling version of the resampling-based empirical Bayes approach are investigated and compared to those of widely-used FDR-controlling linear step-up procedures in a simulation study. The Type I error and power trade-off achieved by the empirical Bayes procedures under a variety of testing scenarios allows this approach to be competitive with or outperform the Storey and Tibshirani (2003) linear step-up procedure, as an alternative to the classical Benjamini and Hochberg (1995) procedure. PMID:18932138

VizieR Online Data Catalog: V and R CCD photometry of visual binaries (Abad+, 2004)

NASA Astrophysics Data System (ADS)

Abad, C.; Docobo, J. A.; Lanchares, V.; Lahulla, J. F.; Abelleira, P.; Blanco, J.; Alvarez, C.

2003-11-01

Table 1 gives relevant data for the visual binaries observed. Observations were carried out over a short period of time, therefore we assign the mean epoch (1998.58) for the totality of data. Data of individual stars are presented as average data with errors, by parameter, when various observations have been calculated, as well as the number of observations involved. Errors corresponding to astrometric relative positions between components are always present. For single observations, parameter fitting errors, specially for dx and dy parameters, have been calculated analysing the chi2 test around the minimum. Following the rules for error propagation, theta and rho errors can be estimated. Then, Table 1 shows single observation errors with an additional significant digit. When a star does not have known references, we include it in Table 2, where J2000 position and magnitudes are from the USNO-A2.0 catalogue (Monet et al., 1998, Cat. ). (2 data files).