A Strategy to Use Soft Data Effectively in Randomized Controlled Clinical Trials.

ERIC Educational Resources Information Center

Kraemer, Helena Chmura; Thiemann, Sue

1989-01-01

Sees soft data, measures having substantial intrasubject variability due to errors of measurement or response inconsistency, as important measures of response in randomized clinical trials. Shows that using intensive design and slope of response on time as outcome measure maximizes sample retention and decreases within-group variability, thus…

Elimination of Emergency Department Medication Errors Due To Estimated Weights.

PubMed

Greenwalt, Mary; Griffen, David; Wilkerson, Jim

2017-01-01

From 7/2014 through 6/2015, 10 emergency department (ED) medication dosing errors were reported through the electronic incident reporting system of an urban academic medical center. Analysis of these medication errors identified inaccurate estimated weight on patients as the root cause. The goal of this project was to reduce weight-based dosing medication errors due to inaccurate estimated weights on patients presenting to the ED. Chart review revealed that 13.8% of estimated weights documented on admitted ED patients varied more than 10% from subsequent actual admission weights recorded. A random sample of 100 charts containing estimated weights revealed 2 previously unreported significant medication dosage errors (.02 significant error rate). Key improvements included removing barriers to weighing ED patients, storytelling to engage staff and change culture, and removal of the estimated weight documentation field from the ED electronic health record (EHR) forms. With these improvements estimated weights on ED patients, and the resulting medication errors, were eliminated.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Quantifying Adventitious Error in a Covariance Structure as a Random Effect

PubMed Central

Wu, Hao; Browne, Michael W.

2017-01-01

We present an approach to quantifying errors in covariance structures in which adventitious error, identified as the process underlying the discrepancy between the population and the structured model, is explicitly modeled as a random effect with a distribution, and the dispersion parameter of this distribution to be estimated gives a measure of misspecification. Analytical properties of the resultant procedure are investigated and the measure of misspecification is found to be related to the RMSEA. An algorithm is developed for numerical implementation of the procedure. The consistency and asymptotic sampling distributions of the estimators are established under a new asymptotic paradigm and an assumption weaker than the standard Pitman drift assumption. Simulations validate the asymptotic sampling distributions and demonstrate the importance of accounting for the variations in the parameter estimates due to adventitious error. Two examples are also given as illustrations. PMID:25813463

Random Weighting, Strong Tracking, and Unscented Kalman Filter for Soft Tissue Characterization.

PubMed

Shin, Jaehyun; Zhong, Yongmin; Oetomo, Denny; Gu, Chengfan

2018-05-21

This paper presents a new nonlinear filtering method based on the Hunt-Crossley model for online nonlinear soft tissue characterization. This method overcomes the problem of performance degradation in the unscented Kalman filter due to contact model error. It adopts the concept of Mahalanobis distance to identify contact model error, and further incorporates a scaling factor in predicted state covariance to compensate identified model error. This scaling factor is determined according to the principle of innovation orthogonality to avoid the cumbersome computation of Jacobian matrix, where the random weighting concept is adopted to improve the estimation accuracy of innovation covariance. A master-slave robotic indentation system is developed to validate the performance of the proposed method. Simulation and experimental results as well as comparison analyses demonstrate that the efficacy of the proposed method for online characterization of soft tissue parameters in the presence of contact model error.

Influence of ultraviolet irradiation on data retention characteristics in resistive random access memory

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

Kimura, K.; Ohmi, K.; Tottori University Electronic Display Research Center, 101 Minami4-chome, Koyama-cho, Tottori-shi, Tottori 680-8551

With increasing density of memory devices, the issue of generating soft errors by cosmic rays is becoming more and more serious. Therefore, the irradiation resistance of resistance random access memory (ReRAM) to cosmic radiation has to be elucidated for practical use. In this paper, we investigated the data retention characteristics of ReRAM against ultraviolet irradiation with a Pt/NiO/ITO structure. Soft errors were confirmed to be caused by ultraviolet irradiation in both low- and high-resistance states. An analysis of the wavelength dependence of light irradiation on data retention characteristics suggested that electronic excitation from the valence to the conduction band andmore » to the energy level generated due to the introduction of oxygen vacancies caused the errors. Based on a statistically estimated soft error rates, the errors were suggested to be caused by the cohesion and dispersion of oxygen vacancies owing to the generation of electron-hole pairs and valence changes by the ultraviolet irradiation.« less

[Exploration of the concept of genetic drift in genetics teaching of undergraduates].

PubMed

Wang, Chun-ming

2016-01-01

Genetic drift is one of the difficulties in teaching genetics due to its randomness and probability which could easily cause conceptual misunderstanding. The “sampling error" in its definition is often misunderstood because of the research method of “sampling", which disturbs the results and causes the random changes in allele frequency. I analyzed and compared the definitions of genetic drift in domestic and international genetic textbooks, and found that the definitions containing “sampling error" are widely adopted but are interpreted correctly in only a few textbooks. Here, the history of research on genetic drift, i.e., the contributions of Wright, Fisher and Kimura, is introduced. Moreover, I particularly describe two representative articles recently published about genetic drift teaching of undergraduates, which point out that misconceptions are inevitable for undergraduates during the studying process and also provide a preliminary solution. Combined with my own teaching practice, I suggest that the definition of genetic drift containing “sampling error" can be adopted with further interpretation, i.e., “sampling error" is random sampling among gametes when generating the next generation of alleles which is equivalent to a random sampling of all gametes participating in mating in gamete pool and has no relationship with artificial sampling in general genetics studies. This article may provide some help in genetics teaching.

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.

The Number of Patients and Events Required to Limit the Risk of Overestimation of Intervention Effects in Meta-Analysis—A Simulation Study

PubMed Central

Thorlund, Kristian; Imberger, Georgina; Walsh, Michael; Chu, Rong; Gluud, Christian; Wetterslev, Jørn; Guyatt, Gordon; Devereaux, Philip J.; Thabane, Lehana

2011-01-01

Background Meta-analyses including a limited number of patients and events are prone to yield overestimated intervention effect estimates. While many assume bias is the cause of overestimation, theoretical considerations suggest that random error may be an equal or more frequent cause. The independent impact of random error on meta-analyzed intervention effects has not previously been explored. It has been suggested that surpassing the optimal information size (i.e., the required meta-analysis sample size) provides sufficient protection against overestimation due to random error, but this claim has not yet been validated. Methods We simulated a comprehensive array of meta-analysis scenarios where no intervention effect existed (i.e., relative risk reduction (RRR) = 0%) or where a small but possibly unimportant effect existed (RRR = 10%). We constructed different scenarios by varying the control group risk, the degree of heterogeneity, and the distribution of trial sample sizes. For each scenario, we calculated the probability of observing overestimates of RRR>20% and RRR>30% for each cumulative 500 patients and 50 events. We calculated the cumulative number of patients and events required to reduce the probability of overestimation of intervention effect to 10%, 5%, and 1%. We calculated the optimal information size for each of the simulated scenarios and explored whether meta-analyses that surpassed their optimal information size had sufficient protection against overestimation of intervention effects due to random error. Results The risk of overestimation of intervention effects was usually high when the number of patients and events was small and this risk decreased exponentially over time as the number of patients and events increased. The number of patients and events required to limit the risk of overestimation depended considerably on the underlying simulation settings. Surpassing the optimal information size generally provided sufficient protection against overestimation. Conclusions Random errors are a frequent cause of overestimation of intervention effects in meta-analyses. Surpassing the optimal information size will provide sufficient protection against overestimation. PMID:22028777

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.

2004-01-01

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Enhancement of cooperation in the spatial prisoner's dilemma with a coherence-resonance effect through annealed randomness at a cooperator-defector boundary; comparison of two variant models

NASA Astrophysics Data System (ADS)

Tanimoto, Jun

2016-11-01

Inspired by the commonly observed real-world fact that people tend to behave in a somewhat random manner after facing interim equilibrium to break a stalemate situation whilst seeking a higher output, we established two models of the spatial prisoner's dilemma. One presumes that an agent commits action errors, while the other assumes that an agent refers to a payoff matrix with an added random noise instead of an original payoff matrix. A numerical simulation revealed that mechanisms based on the annealing of randomness due to either the action error or the payoff noise could significantly enhance the cooperation fraction. In this study, we explain the detailed enhancement mechanism behind the two models by referring to the concepts that we previously presented with respect to evolutionary dynamic processes under the names of enduring and expanding periods.

Light Scattered from Polished Optical Surfaces: Wings of the Point Spread Function

NASA Technical Reports Server (NTRS)

Kenknight, C. E.

1984-01-01

Random figure errors from the polishing process plus particles on the main mirrors in a telescope cause an extended point spread function (PSF) declining approximately as the inverse square of the sine of the angle from a star from about 100 micro-rad to a right angle. The decline in at least one case, and probably in general, proceeds as the inverse cube at smaller angles where the usual focal plane aperture radius is chosen. The photometric error due to misalignment by one Airy ring spacing with an aperture of n rings depends on the net variance in the figure. It is approximately 60/(n+1)(3) when using the data of Kormendy (1973). A typical value is 6 x 10 to the -5th power per ring of misalignment with n = 100 rings. The encircled power may be modulated on a time scale of hours by parts per thousand in a wavelength dependent manner due to relative humidity effects on mirror dust. The scattering according to an inverse power law is due to a random walk in aberration height caused by a multitude of facets and slope errors left by the polishing process. A deviation from such a law at grazing emergence may permit monitoring the dust effects.

[Errors in Peruvian medical journals references].

PubMed

Huamaní, Charles; Pacheco-Romero, José

2009-01-01

References are fundamental in our studies; an adequate selection is asimportant as an adequate description. To determine the number of errors in a sample of references found in Peruvian medical journals. We reviewed 515 scientific papers references selected by systematic randomized sampling and corroborated reference information with the original document or its citation in Pubmed, LILACS or SciELO-Peru. We found errors in 47,6% (245) of the references, identifying 372 types of errors; the most frequent were errors in presentation style (120), authorship (100) and title (100), mainly due to spelling mistakes (91). References error percentage was high, varied and multiple. We suggest systematic revision of references in the editorial process as well as to extend the discussion on this theme. references, periodicals, research, bibliometrics.

Component Analysis of Errors on PERSIANN Precipitation Estimates over Urmia Lake Basin, IRAN

NASA Astrophysics Data System (ADS)

Ghajarnia, N.; Daneshkar Arasteh, P.; Liaghat, A. M.; Araghinejad, S.

2016-12-01

In this study, PERSIANN daily dataset is evaluated from 2000 to 2011 in 69 pixels over Urmia Lake basin in northwest of Iran. Different analytical approaches and indexes are used to examine PERSIANN precision in detection and estimation of rainfall rate. The residuals are decomposed into Hit, Miss and FA estimation biases while continues decomposition of systematic and random error components are also analyzed seasonally and categorically. New interpretation of estimation accuracy named "reliability on PERSIANN estimations" is introduced while the changing manners of existing categorical/statistical measures and error components are also seasonally analyzed over different rainfall rate categories. This study yields new insights into the nature of PERSIANN errors over Urmia lake basin as a semi-arid region in the middle-east, including the followings: - The analyzed contingency table indexes indicate better detection precision during spring and fall. - A relatively constant level of error is generally observed among different categories. The range of precipitation estimates at different rainfall rate categories is nearly invariant as a sign for the existence of systematic error. - Low level of reliability is observed on PERSIANN estimations at different categories which are mostly associated with high level of FA error. However, it is observed that as the rate of precipitation increase, the ability and precision of PERSIANN in rainfall detection also increases. - The systematic and random error decomposition in this area shows that PERSIANN has more difficulty in modeling the system and pattern of rainfall rather than to have bias due to rainfall uncertainties. The level of systematic error also considerably increases in heavier rainfalls. It is also important to note that PERSIANN error characteristics at each season varies due to the condition and rainfall patterns of that season which shows the necessity of seasonally different approach for the calibration of this product. Overall, we believe that different error component's analysis performed in this study, can substantially help any further local studies for post-calibration and bias reduction of PERSIANN estimations.

Reducing Errors in Satellite Simulated Views of Clouds with an Improved Parameterization of Unresolved Scales

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Marchand, R.; Ackerman, T. P.

2016-12-01

Satellite instrument simulators have emerged as a means to reduce errors in model evaluation by producing simulated or psuedo-retrievals from model fields, which account for limitations in the satellite retrieval process. Because of the mismatch in resolved scales between satellite retrievals and large-scale models, model cloud fields must first be downscaled to scales consistent with satellite retrievals. This downscaling is analogous to that required for model radiative transfer calculations. The assumption is often made in both model radiative transfer codes and satellite simulators that the unresolved clouds follow maximum-random overlap with horizontally homogeneous cloud condensate amounts. We examine errors in simulated MISR and CloudSat retrievals that arise due to these assumptions by applying the MISR and CloudSat simulators to cloud resolving model (CRM) output generated by the Super-parameterized Community Atmosphere Model (SP-CAM). Errors are quantified by comparing simulated retrievals performed directly on the CRM fields with those simulated by first averaging the CRM fields to approximately 2-degree resolution, applying a "subcolumn generator" to regenerate psuedo-resolved cloud and precipitation condensate fields, and then applying the MISR and CloudSat simulators on the regenerated condensate fields. We show that errors due to both assumptions of maximum-random overlap and homogeneous condensate are significant (relative to uncertainties in the observations and other simulator limitations). The treatment of precipitation is particularly problematic for CloudSat-simulated radar reflectivity. We introduce an improved subcolumn generator for use with the simulators, and show that these errors can be greatly reduced by replacing the maximum-random overlap assumption with the more realistic generalized overlap and incorporating a simple parameterization of subgrid-scale cloud and precipitation condensate heterogeneity. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. SAND2016-7485 A

Multi-muscle FES force control of the human arm for arbitrary goals.

PubMed

Schearer, Eric M; Liao, Yu-Wei; Perreault, Eric J; Tresch, Matthew C; Memberg, William D; Kirsch, Robert F; Lynch, Kevin M

2014-05-01

We present a method for controlling a neuroprosthesis for a paralyzed human arm using functional electrical stimulation (FES) and characterize the errors of the controller. The subject has surgically implanted electrodes for stimulating muscles in her shoulder and arm. Using input/output data, a model mapping muscle stimulations to isometric endpoint forces measured at the subject's hand was identified. We inverted the model of this redundant and coupled multiple-input multiple-output system by minimizing muscle activations and used this inverse for feedforward control. The magnitude of the total root mean square error over a grid in the volume of achievable isometric endpoint force targets was 11% of the total range of achievable forces. Major sources of error were random error due to trial-to-trial variability and model bias due to nonstationary system properties. Because the muscles working collectively are the actuators of the skeletal system, the quantification of errors in force control guides designs of motion controllers for multi-joint, multi-muscle FES systems that can achieve arbitrary goals.

Robust quantum logic in neutral atoms via adiabatic Rydberg dressing

DOE PAGES

Keating, Tyler; Cook, Robert L.; Hankin, Aaron M.; ...

2015-01-28

We study a scheme for implementing a controlled-Z (CZ) gate between two neutral-atom qubits based on the Rydberg blockade mechanism in a manner that is robust to errors caused by atomic motion. By employing adiabatic dressing of the ground electronic state, we can protect the gate from decoherence due to random phase errors that typically arise because of atomic thermal motion. In addition, the adiabatic protocol allows for a Doppler-free configuration that involves counterpropagating lasers in a σ +/σ - orthogonal polarization geometry that further reduces motional errors due to Doppler shifts. The residual motional error is dominated by dipole-dipolemore » forces acting on doubly-excited Rydberg atoms when the blockade is imperfect. As a result, for reasonable parameters, with qubits encoded into the clock states of 133Cs, we predict that our protocol could produce a CZ gate in < 10 μs with error probability on the order of 10 -3.« less

The statistical pitfalls of the partially randomized preference design in non-blinded trials of psychological interventions.

PubMed

Gemmell, Isla; Dunn, Graham

2011-03-01

In a partially randomized preference trial (PRPT) patients with no treatment preference are allocated to groups at random, but those who express a preference receive the treatment of their choice. It has been suggested that the design can improve the external and internal validity of trials. We used computer simulation to illustrate the impact that an unmeasured confounder could have on the results and conclusions drawn from a PRPT. We generated 4000 observations ("patients") that reflected the distribution of the Beck Depression Index (DBI) in trials of depression. Half were randomly assigned to a randomized controlled trial (RCT) design and half were assigned to a PRPT design. In the RCT, "patients" were evenly split between treatment and control groups; whereas in the preference arm, to reflect patient choice, 87.5% of patients were allocated to the experimental treatment and 12.5% to the control. Unadjusted analyses of the PRPT data consistently overestimated the treatment effect and its standard error. This lead to Type I errors when the true treatment effect was small and Type II errors when the confounder effect was large. The PRPT design is not recommended as a method of establishing an unbiased estimate of treatment effect due to the potential influence of unmeasured confounders. Copyright © 2011 John Wiley & Sons, Ltd.

Multiscale measurement error models for aggregated small area health data.

PubMed

Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin

2016-08-01

Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. © The Author(s) 2016.

Model studies of the beam-filling error for rain-rate retrieval with microwave radiometers

NASA Technical Reports Server (NTRS)

Ha, Eunho; North, Gerald R.

1995-01-01

Low-frequency (less than 20 GHz) single-channel microwave retrievals of rain rate encounter the problem of beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of the rain field. This means that one may not simply insert the area average of the brightness temperature into the formula for rain rate without incurring both bias and random error. The statistical heterogeneity of the rain-rate field in the footprint of the instrument is key to determining the nature of these errors. This paper makes use of a series of random rain-rate fields to study the size of the bias and random error associated with beam filling. A number of examples are analyzed in detail: the binomially distributed field, the gamma, the Gaussian, the mixed gamma, the lognormal, and the mixed lognormal ('mixed' here means there is a finite probability of no rain rate at a point of space-time). Of particular interest are the applicability of a simple error formula due to Chiu and collaborators and a formula that might hold in the large field of view limit. It is found that the simple formula holds for Gaussian rain-rate fields but begins to fail for highly skewed fields such as the mixed lognormal. While not conclusively demonstrated here, it is suggested that the notionof climatologically adjusting the retrievals to remove the beam-filling bias is a reasonable proposition.

Procedures for dealing with certain types of noise and systematic errors common to many Hadamard transform optical systems

NASA Technical Reports Server (NTRS)

Harwit, M.

1977-01-01

Sources of noise and error correcting procedures characteristic of Hadamard transform optical systems were investigated. Reduction of spectral noise due to noise spikes in the data, the effect of random errors, the relative performance of Fourier and Hadamard transform spectrometers operated under identical detector-noise-limited conditions, and systematic means for dealing with mask defects are among the topics discussed. The distortion in Hadamard transform optical instruments caused by moving Masks, incorrect mask alignment, missing measurements, and diffraction is analyzed and techniques for reducing or eliminating this distortion are described.

A general method for the definition of margin recipes depending on the treatment technique applied in helical tomotherapy prostate plans.

PubMed

Sevillano, David; Mínguez, Cristina; Sánchez, Alicia; Sánchez-Reyes, Alberto

2016-01-01

To obtain specific margin recipes that take into account the dosimetric characteristics of the treatment plans used in a single institution. We obtained dose-population histograms (DPHs) of 20 helical tomotherapy treatment plans for prostate cancer by simulating the effects of different systematic errors (Σ) and random errors (σ) on these plans. We obtained dosimetric margins and margin reductions due to random errors (random margins) by fitting the theoretical results of coverages for Gaussian distributions with coverages of the planned D99% obtained from the DPHs. The dosimetric margins obtained for helical tomotherapy prostate treatments were 3.3 mm, 3 mm, and 1 mm in the lateral (Lat), anterior-posterior (AP), and superior-inferior (SI) directions. Random margins showed parabolic dependencies, yielding expressions of 0.16σ(2), 0.13σ(2), and 0.15σ(2) for the Lat, AP, and SI directions, respectively. When focusing on values up to σ = 5 mm, random margins could be fitted considering Gaussian penumbras with standard deviations (σp) equal to 4.5 mm Lat, 6 mm AP, and 5.5 mm SI. Despite complex dose distributions in helical tomotherapy treatment plans, we were able to simplify the behaviour of our plans against treatment errors to single values of dosimetric and random margins for each direction. These margins allowed us to develop specific margin recipes for the respective treatment technique. The method is general and could be used for any treatment technique provided that DPHs can be obtained. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Using integrated models to minimize environmentally induced wavefront error in optomechanical design and analysis

NASA Astrophysics Data System (ADS)

Genberg, Victor L.; Michels, Gregory J.

2017-08-01

The ultimate design goal of an optical system subjected to dynamic loads is to minimize system level wavefront error (WFE). In random response analysis, system WFE is difficult to predict from finite element results due to the loss of phase information. In the past, the use of ystem WFE was limited by the difficulty of obtaining a linear optics model. In this paper, an automated method for determining system level WFE using a linear optics model is presented. An error estimate is included in the analysis output based on fitting errors of mode shapes. The technique is demonstrated by example with SigFit, a commercially available tool integrating mechanical analysis with optical analysis.

Effects of Heterogeneity and Uncertainties in Sources and Initial and Boundary Conditions on Spatiotemporal Variations of Groundwater Levels

NASA Astrophysics Data System (ADS)

Zhang, Y. K.; Liang, X.

2014-12-01

Effects of aquifer heterogeneity and uncertainties in source/sink, and initial and boundary conditions in a groundwater flow model on the spatiotemporal variations of groundwater level, h(x,t), were investigated. Analytical solutions for the variance and covariance of h(x, t) in an unconfined aquifer described by a linearized Boussinesq equation with a white noise source/sink and a random transmissivity field were derived. It was found that in a typical aquifer the error in h(x,t) in early time is mainly caused by the random initial condition and the error reduces as time goes to reach a constant error in later time. The duration during which the effect of the random initial condition is significant may last a few hundred days in most aquifers. The constant error in groundwater in later time is due to the combined effects of the uncertain source/sink and flux boundary: the closer to the flux boundary, the larger the error. The error caused by the uncertain head boundary is limited in a narrow zone near the boundary but it remains more or less constant over time. The effect of the heterogeneity is to increase the variation of groundwater level and the maximum effect occurs close to the constant head boundary because of the linear mean hydraulic gradient. The correlation of groundwater level decreases with temporal interval and spatial distance. In addition, the heterogeneity enhances the correlation of groundwater level, especially at larger time intervals and small spatial distances.

REMOVED: Mindfulness meditation with incarcerated youth: A randomized controlled trial informed by neuropsychosocial theories of adolescence.

PubMed

Evans-Chase, Michelle

2015-12-01

This article has been removed: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal) This meeting abstract has been removed by the Publisher. Due to an administrative error, abstracts that were not presented at the ISDN 2014 meeting were inadvertently published in the meeting's abstract supplement. The Publisher apologizes to the authors and readers for this error. Copyright © 2015. Published by Elsevier Ltd.

Bias, Confounding, and Interaction: Lions and Tigers, and Bears, Oh My!

PubMed

Vetter, Thomas R; Mascha, Edward J

2017-09-01

Epidemiologists seek to make a valid inference about the causal effect between an exposure and a disease in a specific population, using representative sample data from a specific population. Clinical researchers likewise seek to make a valid inference about the association between an intervention and outcome(s) in a specific population, based upon their randomly collected, representative sample data. Both do so by using the available data about the sample variable to make a valid estimate about its corresponding or underlying, but unknown population parameter. Random error in an experiment can be due to the natural, periodic fluctuation or variation in the accuracy or precision of virtually any data sampling technique or health measurement tool or scale. In a clinical research study, random error can be due to not only innate human variability but also purely chance. Systematic error in an experiment arises from an innate flaw in the data sampling technique or measurement instrument. In the clinical research setting, systematic error is more commonly referred to as systematic bias. The most commonly encountered types of bias in anesthesia, perioperative, critical care, and pain medicine research include recall bias, observational bias (Hawthorne effect), attrition bias, misclassification or informational bias, and selection bias. A confounding variable is a factor associated with both the exposure of interest and the outcome of interest. A confounding variable (confounding factor or confounder) is a variable that correlates (positively or negatively) with both the exposure and outcome. Confounding is typically not an issue in a randomized trial because the randomized groups are sufficiently balanced on all potential confounding variables, both observed and nonobserved. However, confounding can be a major problem with any observational (nonrandomized) study. Ignoring confounding in an observational study will often result in a "distorted" or incorrect estimate of the association or treatment effect. Interaction among variables, also known as effect modification, exists when the effect of 1 explanatory variable on the outcome depends on the particular level or value of another explanatory variable. Bias and confounding are common potential explanations for statistically significant associations between exposure and outcome when the true relationship is noncausal. Understanding interactions is vital to proper interpretation of treatment effects. These complex concepts should be consistently and appropriately considered whenever one is not only designing but also analyzing and interpreting data from a randomized trial or observational study.

Comparison of direct and heterodyne detection optical intersatellite communication links

NASA Technical Reports Server (NTRS)

Chen, C. C.; Gardner, C. S.

1987-01-01

The performance of direct and heterodyne detection optical intersatellite communication links are evaluated and compared. It is shown that the performance of optical links is very sensitive to the pointing and tracking errors at the transmitter and receiver. In the presence of random pointing and tracking errors, optimal antenna gains exist that will minimize the required transmitter power. In addition to limiting the antenna gains, random pointing and tracking errors also impose a power penalty in the link budget. This power penalty is between 1.6 to 3 dB for a direct detection QPPM link, and 3 to 5 dB for a heterodyne QFSK system. For the heterodyne systems, the carrier phase noise presents another major factor of performance degradation that must be considered. In contrast, the loss due to synchronization error is small. The link budgets for direct and heterodyne detection systems are evaluated. It is shown that, for systems with large pointing and tracking errors, the link budget is dominated by the spatial tracking error, and the direct detection system shows a superior performance because it is less sensitive to the spatial tracking error. On the other hand, for systems with small pointing and tracking jitters, the antenna gains are in general limited by the launch cost, and suboptimal antenna gains are often used in practice. In which case, the heterodyne system has a slightly higher power margin because of higher receiver sensitivity.

Beyond alpha: an empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual differences constructs.

PubMed

Schmidt, Frank L; Le, Huy; Ilies, Remus

2003-06-01

On the basis of an empirical study of measures of constructs from the cognitive domain, the personality domain, and the domain of affective traits, the authors of this study examine the implications of transient measurement error for the measurement of frequently studied individual differences variables. The authors clarify relevant reliability concepts as they relate to transient error and present a procedure for estimating the coefficient of equivalence and stability (L. J. Cronbach, 1947), the only classical reliability coefficient that assesses all 3 major sources of measurement error (random response, transient, and specific factor errors). The authors conclude that transient error exists in all 3 trait domains and is especially large in the domain of affective traits. Their findings indicate that the nearly universal use of the coefficient of equivalence (Cronbach's alpha; L. J. Cronbach, 1951), which fails to assess transient error, leads to overestimates of reliability and undercorrections for biases due to measurement error.

Impact of random pointing and tracking errors on the design of coherent and incoherent optical intersatellite communication links

NASA Technical Reports Server (NTRS)

Chen, Chien-Chung; Gardner, Chester S.

1989-01-01

Given the rms transmitter pointing error and the desired probability of bit error (PBE), it can be shown that an optimal transmitter antenna gain exists which minimizes the required transmitter power. Given the rms local oscillator tracking error, an optimum receiver antenna gain can be found which optimizes the receiver performance. The impact of pointing and tracking errors on the design of direct-detection pulse-position modulation (PPM) and heterodyne noncoherent frequency-shift keying (NCFSK) systems are then analyzed in terms of constraints on the antenna size and the power penalty incurred. It is shown that in the limit of large spatial tracking errors, the advantage in receiver sensitivity for the heterodyne system is quickly offset by the smaller antenna gain and the higher power penalty due to tracking errors. In contrast, for systems with small spatial tracking errors, the heterodyne system is superior because of the higher receiver sensitivity.

An investigation of error characteristics and coding performance

NASA Technical Reports Server (NTRS)

Ebel, William J.; Ingels, Frank M.

1992-01-01

The performance of forward error correcting coding schemes on errors anticipated for the Earth Observation System (EOS) Ku-band downlink are studied. The EOS transmits picture frame data to the ground via the Telemetry Data Relay Satellite System (TDRSS) to a ground-based receiver at White Sands. Due to unintentional RF interference from other systems operating in the Ku band, the noise at the receiver is non-Gaussian which may result in non-random errors output by the demodulator. That is, the downlink channel cannot be modeled by a simple memoryless Gaussian-noise channel. From previous experience, it is believed that those errors are bursty. The research proceeded by developing a computer based simulation, called Communication Link Error ANalysis (CLEAN), to model the downlink errors, forward error correcting schemes, and interleavers used with TDRSS. To date, the bulk of CLEAN was written, documented, debugged, and verified. The procedures for utilizing CLEAN to investigate code performance were established and are discussed.

Effect of patient setup errors on simultaneously integrated boost head and neck IMRT treatment plans

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

Siebers, Jeffrey V.; Keall, Paul J.; Wu Qiuwen

2005-10-01

Purpose: The purpose of this study is to determine dose delivery errors that could result from random and systematic setup errors for head-and-neck patients treated using the simultaneous integrated boost (SIB)-intensity-modulated radiation therapy (IMRT) technique. Methods and Materials: Twenty-four patients who participated in an intramural Phase I/II parotid-sparing IMRT dose-escalation protocol using the SIB treatment technique had their dose distributions reevaluated to assess the impact of random and systematic setup errors. The dosimetric effect of random setup error was simulated by convolving the two-dimensional fluence distribution of each beam with the random setup error probability density distribution. Random setup errorsmore » of {sigma} = 1, 3, and 5 mm were simulated. Systematic setup errors were simulated by randomly shifting the patient isocenter along each of the three Cartesian axes, with each shift selected from a normal distribution. Systematic setup error distributions with {sigma} = 1.5 and 3.0 mm along each axis were simulated. Combined systematic and random setup errors were simulated for {sigma} = {sigma} = 1.5 and 3.0 mm along each axis. For each dose calculation, the gross tumor volume (GTV) received by 98% of the volume (D{sub 98}), clinical target volume (CTV) D{sub 90}, nodes D{sub 90}, cord D{sub 2}, and parotid D{sub 50} and parotid mean dose were evaluated with respect to the plan used for treatment for the structure dose and for an effective planning target volume (PTV) with a 3-mm margin. Results: Simultaneous integrated boost-IMRT head-and-neck treatment plans were found to be less sensitive to random setup errors than to systematic setup errors. For random-only errors, errors exceeded 3% only when the random setup error {sigma} exceeded 3 mm. Simulated systematic setup errors with {sigma} = 1.5 mm resulted in approximately 10% of plan having more than a 3% dose error, whereas a {sigma} = 3.0 mm resulted in half of the plans having more than a 3% dose error and 28% with a 5% dose error. Combined random and systematic dose errors with {sigma} = {sigma} = 3.0 mm resulted in more than 50% of plans having at least a 3% dose error and 38% of the plans having at least a 5% dose error. Evaluation with respect to a 3-mm expanded PTV reduced the observed dose deviations greater than 5% for the {sigma} = {sigma} = 3.0 mm simulations to 5.4% of the plans simulated. Conclusions: Head-and-neck SIB-IMRT dosimetric accuracy would benefit from methods to reduce patient systematic setup errors. When GTV, CTV, or nodal volumes are used for dose evaluation, plans simulated including the effects of random and systematic errors deviate substantially from the nominal plan. The use of PTVs for dose evaluation in the nominal plan improves agreement with evaluated GTV, CTV, and nodal dose values under simulated setup errors. PTV concepts should be used for SIB-IMRT head-and-neck squamous cell carcinoma patients, although the size of the margins may be less than those used with three-dimensional conformal radiation therapy.« less

The distribution of probability values in medical abstracts: an observational study.

PubMed

Ginsel, Bastiaan; Aggarwal, Abhinav; Xuan, Wei; Harris, Ian

2015-11-26

A relatively high incidence of p values immediately below 0.05 (such as 0.047 or 0.04) compared to p values immediately above 0.05 (such as 0.051 or 0.06) has been noticed anecdotally in published medical abstracts. If p values immediately below 0.05 are over-represented, such a distribution may reflect the true underlying distribution of p values or may be due to error (a false distribution). If due to error, a consistent over-representation of p values immediately below 0.05 would be a systematic error due either to publication bias or (overt or inadvertent) bias within studies. We searched the Medline 2012 database to identify abstracts containing a p value. Two thousand abstracts out of 80,649 abstracts were randomly selected. Two independent researchers extracted all p values. The p values were plotted and compared to a predicted curve. Chi square test was used to test assumptions and significance was set at 0.05. 2798 p value ranges and 3236 exact p values were reported. 4973 of these (82%) were significant (<0.05). There was an over-representation of p values immediately below 0.05 (between 0.01 and 0.049) compared to those immediately above 0.05 (between 0.05 and 0.1) (p = 0.001). The distribution of p values in reported medical abstracts provides evidence for systematic error in the reporting of p values. This may be due to publication bias, methodological errors (underpowering, selective reporting and selective analyses) or fraud.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

A note on variance estimation in random effects meta-regression.

PubMed

Sidik, Kurex; Jonkman, Jeffrey N

2005-01-01

For random effects meta-regression inference, variance estimation for the parameter estimates is discussed. Because estimated weights are used for meta-regression analysis in practice, the assumed or estimated covariance matrix used in meta-regression is not strictly correct, due to possible errors in estimating the weights. Therefore, this note investigates the use of a robust variance estimation approach for obtaining variances of the parameter estimates in random effects meta-regression inference. This method treats the assumed covariance matrix of the effect measure variables as a working covariance matrix. Using an example of meta-analysis data from clinical trials of a vaccine, the robust variance estimation approach is illustrated in comparison with two other methods of variance estimation. A simulation study is presented, comparing the three methods of variance estimation in terms of bias and coverage probability. We find that, despite the seeming suitability of the robust estimator for random effects meta-regression, the improved variance estimator of Knapp and Hartung (2003) yields the best performance among the three estimators, and thus may provide the best protection against errors in the estimated weights.

Autoregressive Modeling of Drift and Random Error to Characterize a Continuous Intravascular Glucose Monitoring Sensor.

PubMed

Zhou, Tony; Dickson, Jennifer L; Geoffrey Chase, J

2018-01-01

Continuous glucose monitoring (CGM) devices have been effective in managing diabetes and offer potential benefits for use in the intensive care unit (ICU). Use of CGM devices in the ICU has been limited, primarily due to the higher point accuracy errors over currently used traditional intermittent blood glucose (BG) measures. General models of CGM errors, including drift and random errors, are lacking, but would enable better design of protocols to utilize these devices. This article presents an autoregressive (AR) based modeling method that separately characterizes the drift and random noise of the GlySure CGM sensor (GlySure Limited, Oxfordshire, UK). Clinical sensor data (n = 33) and reference measurements were used to generate 2 AR models to describe sensor drift and noise. These models were used to generate 100 Monte Carlo simulations based on reference blood glucose measurements. These were then compared to the original CGM clinical data using mean absolute relative difference (MARD) and a Trend Compass. The point accuracy MARD was very similar between simulated and clinical data (9.6% vs 9.9%). A Trend Compass was used to assess trend accuracy, and found simulated and clinical sensor profiles were similar (simulated trend index 11.4° vs clinical trend index 10.9°). The model and method accurately represents cohort sensor behavior over patients, providing a general modeling approach to any such sensor by separately characterizing each type of error that can arise in the data. Overall, it enables better protocol design based on accurate expected CGM sensor behavior, as well as enabling the analysis of what level of each type of sensor error would be necessary to obtain desired glycemic control safety and performance with a given protocol.

Single molecule counting and assessment of random molecular tagging errors with transposable giga-scale error-correcting barcodes.

PubMed

Lau, Billy T; Ji, Hanlee P

2017-09-21

RNA-Seq measures gene expression by counting sequence reads belonging to unique cDNA fragments. Molecular barcodes commonly in the form of random nucleotides were recently introduced to improve gene expression measures by detecting amplification duplicates, but are susceptible to errors generated during PCR and sequencing. This results in false positive counts, leading to inaccurate transcriptome quantification especially at low input and single-cell RNA amounts where the total number of molecules present is minuscule. To address this issue, we demonstrated the systematic identification of molecular species using transposable error-correcting barcodes that are exponentially expanded to tens of billions of unique labels. We experimentally showed random-mer molecular barcodes suffer from substantial and persistent errors that are difficult to resolve. To assess our method's performance, we applied it to the analysis of known reference RNA standards. By including an inline random-mer molecular barcode, we systematically characterized the presence of sequence errors in random-mer molecular barcodes. We observed that such errors are extensive and become more dominant at low input amounts. We described the first study to use transposable molecular barcodes and its use for studying random-mer molecular barcode errors. Extensive errors found in random-mer molecular barcodes may warrant the use of error correcting barcodes for transcriptome analysis as input amounts decrease.

Technical Note: Introduction of variance component analysis to setup error analysis in radiotherapy

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

Matsuo, Yukinori, E-mail: ymatsuo@kuhp.kyoto-u.ac.

Purpose: The purpose of this technical note is to introduce variance component analysis to the estimation of systematic and random components in setup error of radiotherapy. Methods: Balanced data according to the one-factor random effect model were assumed. Results: Analysis-of-variance (ANOVA)-based computation was applied to estimate the values and their confidence intervals (CIs) for systematic and random errors and the population mean of setup errors. The conventional method overestimates systematic error, especially in hypofractionated settings. The CI for systematic error becomes much wider than that for random error. The ANOVA-based estimation can be extended to a multifactor model considering multiplemore » causes of setup errors (e.g., interpatient, interfraction, and intrafraction). Conclusions: Variance component analysis may lead to novel applications to setup error analysis in radiotherapy.« less

Prevalence of refractive errors among school children in gondar town, northwest ethiopia.

PubMed

Yared, Assefa Wolde; Belaynew, Wasie Taye; Destaye, Shiferaw; Ayanaw, Tsegaw; Zelalem, Eshete

2012-10-01

Many children with poor vision due to refractive error remain undiagnosed and perform poorly in school. The situation is worse in the Sub-Saharan Africa, including Ethiopia, and current information is lacking. The objective of this study is to determine the prevalence of refractive error among children enrolled in elementary schools in Gondar town, Ethiopia. This was a cross-sectional study of 1852 students in 8 elementary schools. Subjects were selected by multistage random sampling. The study parameters were visual acuity (VA) evaluation and ocular examination. VA was measured by staff optometrists with the Snellen E-chart while students with subnormal vision were examined using pinhole, retinoscopy evaluation and subjective refraction by ophthalmologists. The study cohort was comprised of 45.8% males and 54.2% females from 8 randomly selected elementary schools with a response rate of 93%. Refractive errors in either eye were present in 174 (9.4%) children. Of these, myopia was diagnosed in 55 (31.6%) children in the right and left eyes followed by hyperopia in 46 (26.4%) and 39 (22.4%) in the right and left eyes respectively. Low myopia was the most common refractive error in 61 (49.2%) and 68 (50%) children for the right and left eyes respectively. Refractive error among children is a common problem in Gondar town and needs to be assessed at every health evaluation of school children for timely treatment.

Combined influence of CT random noise and HU-RSP calibration curve nonlinearities on proton range systematic errors

NASA Astrophysics Data System (ADS)

Brousmiche, S.; Souris, K.; Orban de Xivry, J.; Lee, J. A.; Macq, B.; Seco, J.

2017-11-01

Proton range random and systematic uncertainties are the major factors undermining the advantages of proton therapy, namely, a sharp dose falloff and a better dose conformality for lower doses in normal tissues. The influence of CT artifacts such as beam hardening or scatter can easily be understood and estimated due to their large-scale effects on the CT image, like cupping and streaks. In comparison, the effects of weakly-correlated stochastic noise are more insidious and less attention is drawn on them partly due to the common belief that they only contribute to proton range uncertainties and not to systematic errors thanks to some averaging effects. A new source of systematic errors on the range and relative stopping powers (RSP) has been highlighted and proved not to be negligible compared to the 3.5% uncertainty reference value used for safety margin design. Hence, we demonstrate that the angular points in the HU-to-RSP calibration curve are an intrinsic source of proton range systematic error for typical levels of zero-mean stochastic CT noise. Systematic errors on RSP of up to 1% have been computed for these levels. We also show that the range uncertainty does not generally vary linearly with the noise standard deviation. We define a noise-dependent effective calibration curve that better describes, for a given material, the RSP value that is actually used. The statistics of the RSP and the range continuous slowing down approximation (CSDA) have been analytically derived for the general case of a calibration curve obtained by the stoichiometric calibration procedure. These models have been validated against actual CSDA simulations for homogeneous and heterogeneous synthetical objects as well as on actual patient CTs for prostate and head-and-neck treatment planning situations.

Development of an errorable car-following driver model

NASA Astrophysics Data System (ADS)

Yang, H.-H.; Peng, H.

2010-06-01

An errorable car-following driver model is presented in this paper. An errorable driver model is one that emulates human driver's functions and can generate both nominal (error-free), as well as devious (with error) behaviours. This model was developed for evaluation and design of active safety systems. The car-following data used for developing and validating the model were obtained from a large-scale naturalistic driving database. The stochastic car-following behaviour was first analysed and modelled as a random process. Three error-inducing behaviours were then introduced. First, human perceptual limitation was studied and implemented. Distraction due to non-driving tasks was then identified based on the statistical analysis of the driving data. Finally, time delay of human drivers was estimated through a recursive least-square identification process. By including these three error-inducing behaviours, rear-end collisions with the lead vehicle could occur. The simulated crash rate was found to be similar but somewhat higher than that reported in traffic statistics.

Claims, errors, and compensation payments in medical malpractice litigation.

PubMed

Studdert, David M; Mello, Michelle M; Gawande, Atul A; Gandhi, Tejal K; Kachalia, Allen; Yoon, Catherine; Puopolo, Ann Louise; Brennan, Troyen A

2006-05-11

In the current debate over tort reform, critics of the medical malpractice system charge that frivolous litigation--claims that lack evidence of injury, substandard care, or both--is common and costly. Trained physicians reviewed a random sample of 1452 closed malpractice claims from five liability insurers to determine whether a medical injury had occurred and, if so, whether it was due to medical error. We analyzed the prevalence, characteristics, litigation outcomes, and costs of claims that lacked evidence of error. For 3 percent of the claims, there were no verifiable medical injuries, and 37 percent did not involve errors. Most of the claims that were not associated with errors (370 of 515 [72 percent]) or injuries (31 of 37 [84 percent]) did not result in compensation; most that involved injuries due to error did (653 of 889 [73 percent]). Payment of claims not involving errors occurred less frequently than did the converse form of inaccuracy--nonpayment of claims associated with errors. When claims not involving errors were compensated, payments were significantly lower on average than were payments for claims involving errors (313,205 dollars vs. 521,560 dollars, P=0.004). Overall, claims not involving errors accounted for 13 to 16 percent of the system's total monetary costs. For every dollar spent on compensation, 54 cents went to administrative expenses (including those involving lawyers, experts, and courts). Claims involving errors accounted for 78 percent of total administrative costs. Claims that lack evidence of error are not uncommon, but most are denied compensation. The vast majority of expenditures go toward litigation over errors and payment of them. The overhead costs of malpractice litigation are exorbitant. Copyright 2006 Massachusetts Medical Society.

Short-term Variability of Extinction by Broadband Stellar Photometry

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

Musat, I.C.; Ellingson, R.G.

2005-03-18

Aerosol optical depth variation over short-term time intervals is determined from broadband observations of stars with a whole sky imager. The main difficulty in such measurements consists of accurately separating the star flux value from the non-stellar diffuse skylight. Using correction method to overcome this difficulty, the monochromatic extinction at the ground due to aerosols is extracted from heterochromatic measurements. A form of closure is achieved by comparison with simultaneous or temporally close measurements with other instruments, and the total error of the method, as a combination of random error of measurements and systematic error of calibration and model, ismore » assessed as being between 2.6 and 3% rms.« less

Anthropometric data error detecting and correction with a computer

NASA Technical Reports Server (NTRS)

Chesak, D. D.

1981-01-01

Data obtained with automated anthropometric data aquisition equipment was examined for short term errors. The least squares curve fitting technique was used to ascertain which data values were erroneous and to replace them, if possible, with corrected values. Errors were due to random reflections of light, masking of the light rays, and other types of optical and electrical interference. It was found that the signals were impossible to eliminate from the initial data produced by the television cameras, and that this was primarily a software problem requiring a digital computer to refine the data off line. The specific data of interest was related to the arm reach envelope of a human being.

Error sensitivity analysis in 10-30-day extended range forecasting by using a nonlinear cross-prediction error model

NASA Astrophysics Data System (ADS)

Xia, Zhiye; Xu, Lisheng; Chen, Hongbin; Wang, Yongqian; Liu, Jinbao; Feng, Wenlan

2017-06-01

Extended range forecasting of 10-30 days, which lies between medium-term and climate prediction in terms of timescale, plays a significant role in decision-making processes for the prevention and mitigation of disastrous meteorological events. The sensitivity of initial error, model parameter error, and random error in a nonlinear crossprediction error (NCPE) model, and their stability in the prediction validity period in 10-30-day extended range forecasting, are analyzed quantitatively. The associated sensitivity of precipitable water, temperature, and geopotential height during cases of heavy rain and hurricane is also discussed. The results are summarized as follows. First, the initial error and random error interact. When the ratio of random error to initial error is small (10-6-10-2), minor variation in random error cannot significantly change the dynamic features of a chaotic system, and therefore random error has minimal effect on the prediction. When the ratio is in the range of 10-1-2 (i.e., random error dominates), attention should be paid to the random error instead of only the initial error. When the ratio is around 10-2-10-1, both influences must be considered. Their mutual effects may bring considerable uncertainty to extended range forecasting, and de-noising is therefore necessary. Second, in terms of model parameter error, the embedding dimension m should be determined by the factual nonlinear time series. The dynamic features of a chaotic system cannot be depicted because of the incomplete structure of the attractor when m is small. When m is large, prediction indicators can vanish because of the scarcity of phase points in phase space. A method for overcoming the cut-off effect ( m > 4) is proposed. Third, for heavy rains, precipitable water is more sensitive to the prediction validity period than temperature or geopotential height; however, for hurricanes, geopotential height is most sensitive, followed by precipitable water.

Analysis on pseudo excitation of random vibration for structure of time flight counter

NASA Astrophysics Data System (ADS)

Wu, Qiong; Li, Dapeng

2015-03-01

Traditional computing method is inefficient for getting key dynamical parameters of complicated structure. Pseudo Excitation Method(PEM) is an effective method for calculation of random vibration. Due to complicated and coupling random vibration in rocket or shuttle launching, the new staging white noise mathematical model is deduced according to the practical launch environment. This deduced model is applied for PEM to calculate the specific structure of Time of Flight Counter(ToFC). The responses of power spectral density and the relevant dynamic characteristic parameters of ToFC are obtained in terms of the flight acceptance test level. Considering stiffness of fixture structure, the random vibration experiments are conducted in three directions to compare with the revised PEM. The experimental results show the structure can bear the random vibration caused by launch without any damage and key dynamical parameters of ToFC are obtained. The revised PEM is similar with random vibration experiment in dynamical parameters and responses are proved by comparative results. The maximum error is within 9%. The reasons of errors are analyzed to improve reliability of calculation. This research provides an effective method for solutions of computing dynamical characteristic parameters of complicated structure in the process of rocket or shuttle launching.

The intention to disclose medical errors among doctors in a referral hospital in North Malaysia.

PubMed

Hs, Arvinder-Singh; Rashid, Abdul

2017-01-23

In this study, medical errors are defined as unintentional patient harm caused by a doctor's mistake. This topic, due to limited research, is poorly understood in Malaysia. The objective of this study was to determine the proportion of doctors intending to disclose medical errors, and their attitudes/perception pertaining to medical errors. This cross-sectional study was conducted at a tertiary public hospital from July- December 2015 among 276 randomly selected doctors. Data was collected using a standardized and validated self-administered questionnaire intending to measure disclosure and attitudes/perceptions. The scale had four vignettes in total two medical and two surgical. Each vignette consisted of five questions and each question measured the disclosure. Disclosure was categorised as "No Disclosure", "Partial Disclosure" or "Full Disclosure". Data was keyed in and analysed using STATA v 13.0. Only 10.1% (n = 28) intended to disclose medical errors. Most respondents felt that they possessed an attitude/perception of adequately disclosing errors to patients. There was a statistically significant difference (p < 0.001) when comparing the intention of disclosure with perceived disclosures. Most respondents were in common agreement that disclosing an error would make them less likely to get sued, that minor errors should be reported and that they experienced relief from disclosing errors. Most doctors in this study would not disclose medical errors although they perceived that the errors were serious and felt responsible for it. Poor disclosure could be due the fear of litigations and improper mechanisms/procedures available for disclosure.

Dealing with systematic laser scanner errors due to misalignment at area-based deformation analyses

NASA Astrophysics Data System (ADS)

Holst, Christoph; Medić, Tomislav; Kuhlmann, Heiner

2018-04-01

The ability to acquire rapid, dense and high quality 3D data has made terrestrial laser scanners (TLS) a desirable instrument for tasks demanding a high geometrical accuracy, such as geodetic deformation analyses. However, TLS measurements are influenced by systematic errors due to internal misalignments of the instrument. The resulting errors in the point cloud might exceed the magnitude of random errors. Hence, it is important to assure that the deformation analysis is not biased by these influences. In this study, we propose and evaluate several strategies for reducing the effect of TLS misalignments on deformation analyses. The strategies are based on the bundled in-situ self-calibration and on the exploitation of two-face measurements. The strategies are verified analyzing the deformation of the Onsala Space Observatory's radio telescope's main reflector. It is demonstrated that either two-face measurements as well as the in-situ calibration of the laser scanner in a bundle adjustment improve the results of deformation analysis. The best solution is gained by a combination of both strategies.

Numerical Error Estimation with UQ

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Korn, Peter; Marotzke, Jochem

2014-05-01

Ocean models are still in need of means to quantify model errors, which are inevitably made when running numerical experiments. The total model error can formally be decomposed into two parts, the formulation error and the discretization error. The formulation error arises from the continuous formulation of the model not fully describing the studied physical process. The discretization error arises from having to solve a discretized model instead of the continuously formulated model. Our work on error estimation is concerned with the discretization error. Given a solution of a discretized model, our general problem statement is to find a way to quantify the uncertainties due to discretization in physical quantities of interest (diagnostics), which are frequently used in Geophysical Fluid Dynamics. The approach we use to tackle this problem is called the "Goal Error Ensemble method". The basic idea of the Goal Error Ensemble method is that errors in diagnostics can be translated into a weighted sum of local model errors, which makes it conceptually based on the Dual Weighted Residual method from Computational Fluid Dynamics. In contrast to the Dual Weighted Residual method these local model errors are not considered deterministically but interpreted as local model uncertainty and described stochastically by a random process. The parameters for the random process are tuned with high-resolution near-initial model information. However, the original Goal Error Ensemble method, introduced in [1], was successfully evaluated only in the case of inviscid flows without lateral boundaries in a shallow-water framework and is hence only of limited use in a numerical ocean model. Our work consists in extending the method to bounded, viscous flows in a shallow-water framework. As our numerical model, we use the ICON-Shallow-Water model. In viscous flows our high-resolution information is dependent on the viscosity parameter, making our uncertainty measures viscosity-dependent. We will show that we can choose a sensible parameter by using the Reynolds-number as a criteria. Another topic, we will discuss is the choice of the underlying distribution of the random process. This is especially of importance in the scope of lateral boundaries. We will present resulting error estimates for different height- and velocity-based diagnostics applied to the Munk gyre experiment. References [1] F. RAUSER: Error Estimation in Geophysical Fluid Dynamics through Learning; PhD Thesis, IMPRS-ESM, Hamburg, 2010 [2] F. RAUSER, J. MAROTZKE, P. KORN: Ensemble-type numerical uncertainty quantification from single model integrations; SIAM/ASA Journal on Uncertainty Quantification, submitted

Predicting Coastal Flood Severity using Random Forest Algorithm

NASA Astrophysics Data System (ADS)

Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2017-12-01

Coastal floods have become more common recently and are predicted to further increase in frequency and severity due to sea level rise. Predicting floods in coastal cities can be difficult due to the number of environmental and geographic factors which can influence flooding events. Built stormwater infrastructure and irregular urban landscapes add further complexity. This paper demonstrates the use of machine learning algorithms in predicting street flood occurrence in an urban coastal setting. The model is trained and evaluated using data from Norfolk, Virginia USA from September 2010 - October 2016. Rainfall, tide levels, water table levels, and wind conditions are used as input variables. Street flooding reports made by city workers after named and unnamed storm events, ranging from 1-159 reports per event, are the model output. Results show that Random Forest provides predictive power in estimating the number of flood occurrences given a set of environmental conditions with an out-of-bag root mean squared error of 4.3 flood reports and a mean absolute error of 0.82 flood reports. The Random Forest algorithm performed much better than Poisson regression. From the Random Forest model, total daily rainfall was by far the most important factor in flood occurrence prediction, followed by daily low tide and daily higher high tide. The model demonstrated here could be used to predict flood severity based on forecast rainfall and tide conditions and could be further enhanced using more complete street flooding data for model training.

Statistical Field Estimation and Scale Estimation for Complex Coastal Regions and Archipelagos

DTIC Science & Technology

2009-05-01

instruments applied to mode-73. Deep-Sea Research, 23:559–582. Brown , R. G. and Hwang , P. Y. C. (1997). Introduction to Random Signals and Applied Kalman ...the covariance matrix becomes neg- ative due to numerical issues ( Brown and Hwang , 1997). Some useful techniques to counter these divergence problems...equations ( Brown and Hwang , 1997). If the number of observations is large, divergence problems can arise under certain con- ditions due to truncation errors

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

Ellefson, S; Department of Human Oncology, University of Wisconsin, Madison, WI; Culberson, W

Purpose: Discrepancies in absolute dose values have been detected between the ViewRay treatment planning system and ArcCHECK readings when performing delivery quality assurance on the ViewRay system with the ArcCHECK-MR diode array (SunNuclear Corporation). In this work, we investigate whether these discrepancies are due to errors in the ViewRay planning and/or delivery system or due to errors in the ArcCHECK’s readings. Methods: Gamma analysis was performed on 19 ViewRay patient plans using the ArcCHECK. Frequency analysis on the dose differences was performed. To investigate whether discrepancies were due to measurement or delivery error, 10 diodes in low-gradient dose regions weremore » chosen to compare with ion chamber measurements in a PMMA phantom with the same size and shape as the ArcCHECK, provided by SunNuclear. The diodes chosen all had significant discrepancies in absolute dose values compared to the ViewRay TPS. Absolute doses to PMMA were compared between the ViewRay TPS calculations, ArcCHECK measurements, and measurements in the PMMA phantom. Results: Three of the 19 patient plans had 3%/3mm gamma passing rates less than 95%, and ten of the 19 plans had 2%/2mm passing rates less than 95%. Frequency analysis implied a non-random error process. Out of the 10 diode locations measured, ion chamber measurements were all within 2.2% error relative to the TPS and had a mean error of 1.2%. ArcCHECK measurements ranged from 4.5% to over 15% error relative to the TPS and had a mean error of 8.0%. Conclusion: The ArcCHECK performs well for quality assurance on the ViewRay under most circumstances. However, under certain conditions the absolute dose readings are significantly higher compared to the planned doses. As the ion chamber measurements consistently agree with the TPS, it can be concluded that the discrepancies are due to ArcCHECK measurement error and not TPS or delivery system error. This work was funded by the Bhudatt Paliwal Professorship and the University of Wisconsin Medical Radiation Research Center.« less

Errors in causal inference: an organizational schema for systematic error and random error.

PubMed

Suzuki, Etsuji; Tsuda, Toshihide; Mitsuhashi, Toshiharu; Mansournia, Mohammad Ali; Yamamoto, Eiji

2016-11-01

To provide an organizational schema for systematic error and random error in estimating causal measures, aimed at clarifying the concept of errors from the perspective of causal inference. We propose to divide systematic error into structural error and analytic error. With regard to random error, our schema shows its four major sources: nondeterministic counterfactuals, sampling variability, a mechanism that generates exposure events and measurement variability. Structural error is defined from the perspective of counterfactual reasoning and divided into nonexchangeability bias (which comprises confounding bias and selection bias) and measurement bias. Directed acyclic graphs are useful to illustrate this kind of error. Nonexchangeability bias implies a lack of "exchangeability" between the selected exposed and unexposed groups. A lack of exchangeability is not a primary concern of measurement bias, justifying its separation from confounding bias and selection bias. Many forms of analytic errors result from the small-sample properties of the estimator used and vanish asymptotically. Analytic error also results from wrong (misspecified) statistical models and inappropriate statistical methods. Our organizational schema is helpful for understanding the relationship between systematic error and random error from a previously less investigated aspect, enabling us to better understand the relationship between accuracy, validity, and precision. Copyright © 2016 Elsevier Inc. All rights reserved.

Prevalence of visual impairment due to uncorrected refractive error: Results from Delhi-Rapid Assessment of Visual Impairment Study.

PubMed

Senjam, Suraj Singh; Vashist, Praveen; Gupta, Noopur; Malhotra, Sumit; Misra, Vasundhara; Bhardwaj, Amit; Gupta, Vivek

2016-05-01

To estimate the prevalence of visual impairment (VI) due to uncorrected refractive error (URE) and to assess the barriers to utilization of services in the adult urban population of Delhi. A population-based rapid assessment of VI was conducted among people aged 40 years and above in 24 randomly selected clusters of East Delhi district. Presenting visual acuity (PVA) was assessed in each eye using Snellen's "E" chart. Pinhole examination was done if PVA was <20/60 in either eye and ocular examination to ascertain the cause of VI. Barriers to utilization of services for refractive error were recorded with questionnaires. Of 2421 individuals enumerated, 2331 (96%) individuals were examined. Females were 50.7% among them. The mean age of all examined subjects was 51.32 ± 10.5 years (standard deviation). VI in either eye due to URE was present in 275 individuals (11.8%, 95% confidence interval [CI]: 10.5-13.1). URE was identified as the most common cause (53.4%) of VI. The overall prevalence of VI due to URE in the study population was 6.1% (95% CI: 5.1-7.0). The elder population as well as females were more likely to have VI due to URE (odds ratio [OR] = 12.3; P < 0.001 and OR = 1.5; P < 0.02). Lack of felt need was the most common reported barrier (31.5%). The prevalence of VI due to URE among the urban adult population of Delhi is still high despite the availability of abundant eye care facilities. The majority of reported barriers are related to human behavior and attitude toward the refractive error. Understanding these aspects will help in planning appropriate strategies to eliminate VI due to URE.

Uncertainty in eddy covariance measurements and its application to physiological models

Treesearch

D.Y. Hollinger; A.D. Richardson; A.D. Richardson

2005-01-01

Flux data are noisy, and this uncertainty is largely due to random measurement error. Knowledge of uncertainty is essential for the statistical evaluation of modeled andmeasured fluxes, for comparison of parameters derived by fitting models to measured fluxes and in formal data-assimilation efforts. We used the difference between simultaneous measurements from two...

Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

ERIC Educational Resources Information Center

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…

An Old Problem with a New Solution, Raising Classical Questions: A Commentary on Humphry

ERIC Educational Resources Information Center

Heene, Moritz

2011-01-01

Humphry (this issue) deserves credit for drawing attention to the long-neglected fact that differences in item discrimination parameters are often due to empirical factors and not the product of random error components. In doing so, Humphry offers a psychometrically elegant, coherent, and practically important new model that is more flexible while…

Prevalence of Refractive Errors Among School Children in Gondar Town, Northwest Ethiopia

PubMed Central

Yared, Assefa Wolde; Belaynew, Wasie Taye; Destaye, Shiferaw; Ayanaw, Tsegaw; Zelalem, Eshete

2012-01-01

Purpose: Many children with poor vision due to refractive error remain undiagnosed and perform poorly in school. The situation is worse in the Sub-Saharan Africa, including Ethiopia, and current information is lacking. The objective of this study is to determine the prevalence of refractive error among children enrolled in elementary schools in Gondar town, Ethiopia. Materials and Methods: This was a cross-sectional study of 1852 students in 8 elementary schools. Subjects were selected by multistage random sampling. The study parameters were visual acuity (VA) evaluation and ocular examination. VA was measured by staff optometrists with the Snellen E-chart while students with subnormal vision were examined using pinhole, retinoscopy evaluation and subjective refraction by ophthalmologists. Results: The study cohort was comprised of 45.8% males and 54.2% females from 8 randomly selected elementary schools with a response rate of 93%. Refractive errors in either eye were present in 174 (9.4%) children. Of these, myopia was diagnosed in 55 (31.6%) children in the right and left eyes followed by hyperopia in 46 (26.4%) and 39 (22.4%) in the right and left eyes respectively. Low myopia was the most common refractive error in 61 (49.2%) and 68 (50%) children for the right and left eyes respectively. Conclusions: Refractive error among children is a common problem in Gondar town and needs to be assessed at every health evaluation of school children for timely treatment. PMID:23248538

Multi-kW coherent combining of fiber lasers seeded with pseudo random phase modulated light

NASA Astrophysics Data System (ADS)

Flores, Angel; Ehrehreich, Thomas; Holten, Roger; Anderson, Brian; Dajani, Iyad

2016-03-01

We report efficient coherent beam combining of five kilowatt-class fiber amplifiers with a diffractive optical element (DOE). Based on a master oscillator power amplifier (MOPA) configuration, the amplifiers were seeded with pseudo random phase modulated light. Each non-polarization maintaining fiber amplifier was optically path length matched and provides approximately 1.2 kW of near diffraction-limited output power (measured M2<1.1). Consequently, a low power sample of each laser was utilized for active linear polarization control. A low power sample of the combined beam after the DOE provided an error signal for active phase locking which was performed via Locking of Optical Coherence by Single-Detector Electronic-Frequency Tagging (LOCSET). After phase stabilization, the beams were coherently combined via the 1x5 DOE. A total combined output power of 4.9 kW was achieved with 82% combining efficiency and excellent beam quality (M2<1.1). The intrinsic DOE splitter loss was 5%. Similarly, losses due in part to non-ideal polarization, ASE content, uncorrelated wavefront errors, and misalignment errors contributed to the efficiency reduction.

Soft-error tolerance and energy consumption evaluation of embedded computer with magnetic random access memory in practical systems using computer simulations

NASA Astrophysics Data System (ADS)

Nebashi, Ryusuke; Sakimura, Noboru; Sugibayashi, Tadahiko

2017-08-01

We evaluated the soft-error tolerance and energy consumption of an embedded computer with magnetic random access memory (MRAM) using two computer simulators. One is a central processing unit (CPU) simulator of a typical embedded computer system. We simulated the radiation-induced single-event-upset (SEU) probability in a spin-transfer-torque MRAM cell and also the failure rate of a typical embedded computer due to its main memory SEU error. The other is a delay tolerant network (DTN) system simulator. It simulates the power dissipation of wireless sensor network nodes of the system using a revised CPU simulator and a network simulator. We demonstrated that the SEU effect on the embedded computer with 1 Gbit MRAM-based working memory is less than 1 failure in time (FIT). We also demonstrated that the energy consumption of the DTN sensor node with MRAM-based working memory can be reduced to 1/11. These results indicate that MRAM-based working memory enhances the disaster tolerance of embedded computers.

Distance error correction for time-of-flight cameras

NASA Astrophysics Data System (ADS)

Fuersattel, Peter; Schaller, Christian; Maier, Andreas; Riess, Christian

2017-06-01

The measurement accuracy of time-of-flight cameras is limited due to properties of the scene and systematic errors. These errors can accumulate to multiple centimeters which may limit the applicability of these range sensors. In the past, different approaches have been proposed for improving the accuracy of these cameras. In this work, we propose a new method that improves two important aspects of the range calibration. First, we propose a new checkerboard which is augmented by a gray-level gradient. With this addition it becomes possible to capture the calibration features for intrinsic and distance calibration at the same time. The gradient strip allows to acquire a large amount of distance measurements for different surface reflectivities, which results in more meaningful training data. Second, we present multiple new features which are used as input to a random forest regressor. By using random regression forests, we circumvent the problem of finding an accurate model for the measurement error. During application, a correction value for each individual pixel is estimated with the trained forest based on a specifically tailored feature vector. With our approach the measurement error can be reduced by more than 40% for the Mesa SR4000 and by more than 30% for the Microsoft Kinect V2. In our evaluation we also investigate the impact of the individual forest parameters and illustrate the importance of the individual features.

Peak-locking centroid bias in Shack-Hartmann wavefront sensing

NASA Astrophysics Data System (ADS)

Anugu, Narsireddy; Garcia, Paulo J. V.; Correia, Carlos M.

2018-05-01

Shack-Hartmann wavefront sensing relies on accurate spot centre measurement. Several algorithms were developed with this aim, mostly focused on precision, i.e. minimizing random errors. In the solar and extended scene community, the importance of the accuracy (bias error due to peak-locking, quantization, or sampling) of the centroid determination was identified and solutions proposed. But these solutions only allow partial bias corrections. To date, no systematic study of the bias error was conducted. This article bridges the gap by quantifying the bias error for different correlation peak-finding algorithms and types of sub-aperture images and by proposing a practical solution to minimize its effects. Four classes of sub-aperture images (point source, elongated laser guide star, crowded field, and solar extended scene) together with five types of peak-finding algorithms (1D parabola, the centre of gravity, Gaussian, 2D quadratic polynomial, and pyramid) are considered, in a variety of signal-to-noise conditions. The best performing peak-finding algorithm depends on the sub-aperture image type, but none is satisfactory to both bias and random errors. A practical solution is proposed that relies on the antisymmetric response of the bias to the sub-pixel position of the true centre. The solution decreases the bias by a factor of ˜7 to values of ≲ 0.02 pix. The computational cost is typically twice of current cross-correlation algorithms.

Some practical problems in implementing randomization.

PubMed

Downs, Matt; Tucker, Kathryn; Christ-Schmidt, Heidi; Wittes, Janet

2010-06-01

While often theoretically simple, implementing randomization to treatment in a masked, but confirmable, fashion can prove difficult in practice. At least three categories of problems occur in randomization: (1) bad judgment in the choice of method, (2) design and programming errors in implementing the method, and (3) human error during the conduct of the trial. This article focuses on these latter two types of errors, dealing operationally with what can go wrong after trial designers have selected the allocation method. We offer several case studies and corresponding recommendations for lessening the frequency of problems in allocating treatment or for mitigating the consequences of errors. Recommendations include: (1) reviewing the randomization schedule before starting a trial, (2) being especially cautious of systems that use on-demand random number generators, (3) drafting unambiguous randomization specifications, (4) performing thorough testing before entering a randomization system into production, (5) maintaining a dataset that captures the values investigators used to randomize participants, thereby allowing the process of treatment allocation to be reproduced and verified, (6) resisting the urge to correct errors that occur in individual treatment assignments, (7) preventing inadvertent unmasking to treatment assignments in kit allocations, and (8) checking a sample of study drug kits to allow detection of errors in drug packaging and labeling. Although we performed a literature search of documented randomization errors, the examples that we provide and the resultant recommendations are based largely on our own experience in industry-sponsored clinical trials. We do not know how representative our experience is or how common errors of the type we have seen occur. Our experience underscores the importance of verifying the integrity of the treatment allocation process before and during a trial. Clinical Trials 2010; 7: 235-245. http://ctj.sagepub.com.

The utility of point count surveys to predict wildlife interactions with wind energy facilities: An example focused on golden eagles

USGS Publications Warehouse

Sur, Maitreyi; Belthoff, James R.; Bjerre, Emily R.; Millsap, Brian A.; Katzner, Todd

2018-01-01

Wind energy development is rapidly expanding in North America, often accompanied by requirements to survey potential facility locations for existing wildlife. Within the USA, golden eagles (Aquila chrysaetos) are among the most high-profile species of birds that are at risk from wind turbines. To minimize golden eagle fatalities in areas proposed for wind development, modified point count surveys are usually conducted to estimate use by these birds. However, it is not always clear what drives variation in the relationship between on-site point count data and actual use by eagles of a wind energy project footprint. We used existing GPS-GSM telemetry data, collected at 15 min intervals from 13 golden eagles in 2012 and 2013, to explore the relationship between point count data and eagle use of an entire project footprint. To do this, we overlaid the telemetry data on hypothetical project footprints and simulated a variety of point count sampling strategies for those footprints. We compared the time an eagle was found in the sample plots with the time it was found in the project footprint using a metric we called “error due to sampling”. Error due to sampling for individual eagles appeared to be influenced by interactions between the size of the project footprint (20, 40, 90 or 180 km2) and the sampling type (random, systematic or stratified) and was greatest on 90 km2 plots. However, use of random sampling resulted in lowest error due to sampling within intermediate sized plots. In addition sampling intensity and sampling frequency both influenced the effectiveness of point count sampling. Although our work focuses on individual eagles (not the eagle populations typically surveyed in the field), our analysis shows both the utility of simulations to identify specific influences on error and also potential improvements to sampling that consider the context-specific manner that point counts are laid out on the landscape.

Sun compass error model

NASA Technical Reports Server (NTRS)

Blucker, T. J.; Ferry, W. W.

1971-01-01

An error model is described for the Apollo 15 sun compass, a contingency navigational device. Field test data are presented along with significant results of the test. The errors reported include a random error resulting from tilt in leveling the sun compass, a random error because of observer sighting inaccuracies, a bias error because of mean tilt in compass leveling, a bias error in the sun compass itself, and a bias error because the device is leveled to the local terrain slope.

Dynamically corrected gates for singlet-triplet spin qubits with control-dependent errors

NASA Astrophysics Data System (ADS)

Jacobson, N. Tobias; Witzel, Wayne M.; Nielsen, Erik; Carroll, Malcolm S.

2013-03-01

Magnetic field inhomogeneity due to random polarization of quasi-static local magnetic impurities is a major source of environmentally induced error for singlet-triplet double quantum dot (DQD) spin qubits. Moreover, for singlet-triplet qubits this error may depend on the applied controls. This effect is significant when a static magnetic field gradient is applied to enable full qubit control. Through a configuration interaction analysis, we observe that the dependence of the field inhomogeneity-induced error on the DQD bias voltage can vary systematically as a function of the controls for certain experimentally relevant operating regimes. To account for this effect, we have developed a straightforward prescription for adapting dynamically corrected gate sequences that assume control-independent errors into sequences that compensate for systematic control-dependent errors. We show that accounting for such errors may lead to a substantial increase in gate fidelities. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. DOE's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Ensemble-type numerical uncertainty information from single model integrations

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

Rauser, Florian, E-mail: florian.rauser@mpimet.mpg.de; Marotzke, Jochem; Korn, Peter

2015-07-01

We suggest an algorithm that quantifies the discretization error of time-dependent physical quantities of interest (goals) for numerical models of geophysical fluid dynamics. The goal discretization error is estimated using a sum of weighted local discretization errors. The key feature of our algorithm is that these local discretization errors are interpreted as realizations of a random process. The random process is determined by the model and the flow state. From a class of local error random processes we select a suitable specific random process by integrating the model over a short time interval at different resolutions. The weights of themore » influences of the local discretization errors on the goal are modeled as goal sensitivities, which are calculated via automatic differentiation. The integration of the weighted realizations of local error random processes yields a posterior ensemble of goal approximations from a single run of the numerical model. From the posterior ensemble we derive the uncertainty information of the goal discretization error. This algorithm bypasses the requirement of detailed knowledge about the models discretization to generate numerical error estimates. The algorithm is evaluated for the spherical shallow-water equations. For two standard test cases we successfully estimate the error of regional potential energy, track its evolution, and compare it to standard ensemble techniques. The posterior ensemble shares linear-error-growth properties with ensembles of multiple model integrations when comparably perturbed. The posterior ensemble numerical error estimates are of comparable size as those of a stochastic physics ensemble.« less

Random errors in interferometry with the least-squares method

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

Wang Qi

2011-01-20

This investigation analyzes random errors in interferometric surface profilers using the least-squares method when random noises are present. Two types of random noise are considered here: intensity noise and position noise. Two formulas have been derived for estimating the standard deviations of the surface height measurements: one is for estimating the standard deviation when only intensity noise is present, and the other is for estimating the standard deviation when only position noise is present. Measurements on simulated noisy interferometric data have been performed, and standard deviations of the simulated measurements have been compared with those theoretically derived. The relationships havemore » also been discussed between random error and the wavelength of the light source and between random error and the amplitude of the interference fringe.« less

Systematic instruction for individuals with acquired brain injury: Results of a randomized controlled trial

PubMed Central

Powell, Laurie Ehlhardt; Glang, Ann; Ettel, Deborah; Todis, Bonnie; Sohlberg, McKay; Albin, Richard

2012-01-01

The goal of this study was to experimentally evaluate systematic instruction compared with trial-and-error learning (conventional instruction) applied to assistive technology for cognition (ATC), in a double blind, pretest-posttest, randomized controlled trial. Twenty-nine persons with moderate-severe cognitive impairments due to acquired brain injury (15 in systematic instruction group; 14 in conventional instruction) completed the study. Both groups received 12, 45-minute individual training sessions targeting selected skills on the Palm Tungsten E2 personal digital assistant (PDA). A criterion-based assessment of PDA skills was used to evaluate accuracy, fluency/efficiency, maintenance, and generalization of skills. There were no significant differences between groups at immediate posttest with regard to accuracy and fluency. However, significant differences emerged at 30-day follow-up in favor of systematic instruction. Furthermore, systematic instruction participants performed significantly better at immediate posttest generalizing trained PDA skills when interacting with people other than the instructor. These results demonstrate that systematic instruction applied to ATC results in better skill maintenance and generalization than trial-and-error learning for individuals with moderate-severe cognitive impairments due to acquired brain injury. Implications, study limitations, and directions for future research are discussed. PMID:22264146

Extension of sonic anemometry to high subsonic Mach number flows

NASA Astrophysics Data System (ADS)

Otero, R.; Lowe, K. T.; Ng, W. F.

2017-03-01

In the literature, the application of sonic anemometry has been limited to low subsonic Mach number, near-incompressible flow conditions. To the best of the authors’ knowledge, this paper represents the first time a sonic anemometry approach has been used to characterize flow velocity beyond Mach 0.3. Using a high speed jet, flow velocity was measured using a modified sonic anemometry technique in flow conditions up to Mach 0.83. A numerical study was conducted to identify the effects of microphone placement on the accuracy of the measured velocity. Based on estimated error strictly due to uncertainty in time-of-acoustic flight, a random error of +/- 4 m s-1 was identified for the configuration used in this experiment. Comparison with measurements from a Pitot probe indicated a velocity RMS error of +/- 9 m s-1. The discrepancy in error is attributed to a systematic error which may be calibrated out in future work. Overall, the experimental results from this preliminary study support the use of acoustics for high subsonic flow characterization.

Comparison of Oral Reading Errors between Contextual Sentences and Random Words among Schoolchildren

ERIC Educational Resources Information Center

Khalid, Nursyairah Mohd; Buari, Noor Halilah; Chen, Ai-Hong

2017-01-01

This paper compares the oral reading errors between the contextual sentences and random words among schoolchildren. Two sets of reading materials were developed to test the oral reading errors in 30 schoolchildren (10.00±1.44 years). Set A was comprised contextual sentences while Set B encompassed random words. The schoolchildren were asked to…

Random measurement error: Why worry? An example of cardiovascular risk factors.

PubMed

Brakenhoff, Timo B; van Smeden, Maarten; Visseren, Frank L J; Groenwold, Rolf H H

2018-01-01

With the increased use of data not originally recorded for research, such as routine care data (or 'big data'), measurement error is bound to become an increasingly relevant problem in medical research. A common view among medical researchers on the influence of random measurement error (i.e. classical measurement error) is that its presence leads to some degree of systematic underestimation of studied exposure-outcome relations (i.e. attenuation of the effect estimate). For the common situation where the analysis involves at least one exposure and one confounder, we demonstrate that the direction of effect of random measurement error on the estimated exposure-outcome relations can be difficult to anticipate. Using three example studies on cardiovascular risk factors, we illustrate that random measurement error in the exposure and/or confounder can lead to underestimation as well as overestimation of exposure-outcome relations. We therefore advise medical researchers to refrain from making claims about the direction of effect of measurement error in their manuscripts, unless the appropriate inferential tools are used to study or alleviate the impact of measurement error from the analysis.

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

NASA Technical Reports Server (NTRS)

Deloach, Richard; Obara, Clifford J.; Goodman, Wesley L.

2012-01-01

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Evaluation of Classifier Performance for Multiclass Phenotype Discrimination in Untargeted Metabolomics.

PubMed

Trainor, Patrick J; DeFilippis, Andrew P; Rai, Shesh N

2017-06-21

Statistical classification is a critical component of utilizing metabolomics data for examining the molecular determinants of phenotypes. Despite this, a comprehensive and rigorous evaluation of the accuracy of classification techniques for phenotype discrimination given metabolomics data has not been conducted. We conducted such an evaluation using both simulated and real metabolomics datasets, comparing Partial Least Squares-Discriminant Analysis (PLS-DA), Sparse PLS-DA, Random Forests, Support Vector Machines (SVM), Artificial Neural Network, k -Nearest Neighbors ( k -NN), and Naïve Bayes classification techniques for discrimination. We evaluated the techniques on simulated data generated to mimic global untargeted metabolomics data by incorporating realistic block-wise correlation and partial correlation structures for mimicking the correlations and metabolite clustering generated by biological processes. Over the simulation studies, covariance structures, means, and effect sizes were stochastically varied to provide consistent estimates of classifier performance over a wide range of possible scenarios. The effects of the presence of non-normal error distributions, the introduction of biological and technical outliers, unbalanced phenotype allocation, missing values due to abundances below a limit of detection, and the effect of prior-significance filtering (dimension reduction) were evaluated via simulation. In each simulation, classifier parameters, such as the number of hidden nodes in a Neural Network, were optimized by cross-validation to minimize the probability of detecting spurious results due to poorly tuned classifiers. Classifier performance was then evaluated using real metabolomics datasets of varying sample medium, sample size, and experimental design. We report that in the most realistic simulation studies that incorporated non-normal error distributions, unbalanced phenotype allocation, outliers, missing values, and dimension reduction, classifier performance (least to greatest error) was ranked as follows: SVM, Random Forest, Naïve Bayes, sPLS-DA, Neural Networks, PLS-DA and k -NN classifiers. When non-normal error distributions were introduced, the performance of PLS-DA and k -NN classifiers deteriorated further relative to the remaining techniques. Over the real datasets, a trend of better performance of SVM and Random Forest classifier performance was observed.

Predicting membrane protein types using various decision tree classifiers based on various modes of general PseAAC for imbalanced datasets.

PubMed

Sankari, E Siva; Manimegalai, D

2017-12-21

Predicting membrane protein types is an important and challenging research area in bioinformatics and proteomics. Traditional biophysical methods are used to classify membrane protein types. Due to large exploration of uncharacterized protein sequences in databases, traditional methods are very time consuming, expensive and susceptible to errors. Hence, it is highly desirable to develop a robust, reliable, and efficient method to predict membrane protein types. Imbalanced datasets and large datasets are often handled well by decision tree classifiers. Since imbalanced datasets are taken, the performance of various decision tree classifiers such as Decision Tree (DT), Classification And Regression Tree (CART), C4.5, Random tree, REP (Reduced Error Pruning) tree, ensemble methods such as Adaboost, RUS (Random Under Sampling) boost, Rotation forest and Random forest are analysed. Among the various decision tree classifiers Random forest performs well in less time with good accuracy of 96.35%. Another inference is RUS boost decision tree classifier is able to classify one or two samples in the class with very less samples while the other classifiers such as DT, Adaboost, Rotation forest and Random forest are not sensitive for the classes with fewer samples. Also the performance of decision tree classifiers is compared with SVM (Support Vector Machine) and Naive Bayes classifier. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Effect of Random Error on Diagnostic Accuracy Illustrated with the Anthropometric Diagnosis of Malnutrition

PubMed Central

2016-01-01

Background It is often thought that random measurement error has a minor effect upon the results of an epidemiological survey. Theoretically, errors of measurement should always increase the spread of a distribution. Defining an illness by having a measurement outside an established healthy range will lead to an inflated prevalence of that condition if there are measurement errors. Methods and results A Monte Carlo simulation was conducted of anthropometric assessment of children with malnutrition. Random errors of increasing magnitude were imposed upon the populations and showed that there was an increase in the standard deviation with each of the errors that became exponentially greater with the magnitude of the error. The potential magnitude of the resulting error of reported prevalence of malnutrition were compared with published international data and found to be of sufficient magnitude to make a number of surveys and the numerous reports and analyses that used these data unreliable. Conclusions The effect of random error in public health surveys and the data upon which diagnostic cut-off points are derived to define “health” has been underestimated. Even quite modest random errors can more than double the reported prevalence of conditions such as malnutrition. Increasing sample size does not address this problem, and may even result in less accurate estimates. More attention needs to be paid to the selection, calibration and maintenance of instruments, measurer selection, training & supervision, routine estimation of the likely magnitude of errors using standardization tests, use of statistical likelihood of error to exclude data from analysis and full reporting of these procedures in order to judge the reliability of survey reports. PMID:28030627

Single event upset in avionics

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

Taber, A.; Normand, E.

1993-04-01

Data from military/experimental flights and laboratory testing indicate that typical non radiation-hardened 64K and 256K static random access memories (SRAMs) can experience a significant soft upset rate at aircraft altitudes due to energetic neutrons created by cosmic ray interactions in the atmosphere. It is suggested that error detection and correction (EDAC) circuitry be considered for all avionics designs containing large amounts of semi-conductor memory.

A case study of the effects of random errors in rawinsonde data on computations of ageostrophic winds

NASA Technical Reports Server (NTRS)

Moore, J. T.

1985-01-01

Data input for the AVE-SESAME I experiment are utilized to describe the effects of random errors in rawinsonde data on the computation of ageostrophic winds. Computer-generated random errors for wind direction and speed and temperature are introduced into the station soundings at 25 mb intervals from which isentropic data sets are created. Except for the isallobaric and the local wind tendency, all winds are computed for Apr. 10, 1979 at 2000 GMT. Divergence fields reveal that the isallobaric and inertial-geostrophic-advective divergences are less affected by rawinsonde random errors than the divergence of the local wind tendency or inertial-advective winds.

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

Sampling Errors of SSM/I and TRMM Rainfall Averages: Comparison with Error Estimates from Surface Data and a Sample Model

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Kummerow, Christian D.; Einaudi, Franco (Technical Monitor)

2000-01-01

Quantitative use of satellite-derived maps of monthly rainfall requires some measure of the accuracy of the satellite estimates. The rainfall estimate for a given map grid box is subject to both remote-sensing error and, in the case of low-orbiting satellites, sampling error due to the limited number of observations of the grid box provided by the satellite. A simple model of rain behavior predicts that Root-mean-square (RMS) random error in grid-box averages should depend in a simple way on the local average rain rate, and the predicted behavior has been seen in simulations using surface rain-gauge and radar data. This relationship was examined using satellite SSM/I data obtained over the western equatorial Pacific during TOGA COARE. RMS error inferred directly from SSM/I rainfall estimates was found to be larger than predicted from surface data, and to depend less on local rain rate than was predicted. Preliminary examination of TRMM microwave estimates shows better agreement with surface data. A simple method of estimating rms error in satellite rainfall estimates is suggested, based on quantities that can be directly computed from the satellite data.

On the predictivity of pore-scale simulations: Estimating uncertainties with multilevel Monte Carlo

NASA Astrophysics Data System (ADS)

Icardi, Matteo; Boccardo, Gianluca; Tempone, Raúl

2016-09-01

A fast method with tunable accuracy is proposed to estimate errors and uncertainties in pore-scale and Digital Rock Physics (DRP) problems. The overall predictivity of these studies can be, in fact, hindered by many factors including sample heterogeneity, computational and imaging limitations, model inadequacy and not perfectly known physical parameters. The typical objective of pore-scale studies is the estimation of macroscopic effective parameters such as permeability, effective diffusivity and hydrodynamic dispersion. However, these are often non-deterministic quantities (i.e., results obtained for specific pore-scale sample and setup are not totally reproducible by another ;equivalent; sample and setup). The stochastic nature can arise due to the multi-scale heterogeneity, the computational and experimental limitations in considering large samples, and the complexity of the physical models. These approximations, in fact, introduce an error that, being dependent on a large number of complex factors, can be modeled as random. We propose a general simulation tool, based on multilevel Monte Carlo, that can reduce drastically the computational cost needed for computing accurate statistics of effective parameters and other quantities of interest, under any of these random errors. This is, to our knowledge, the first attempt to include Uncertainty Quantification (UQ) in pore-scale physics and simulation. The method can also provide estimates of the discretization error and it is tested on three-dimensional transport problems in heterogeneous materials, where the sampling procedure is done by generation algorithms able to reproduce realistic consolidated and unconsolidated random sphere and ellipsoid packings and arrangements. A totally automatic workflow is developed in an open-source code [1], that include rigid body physics and random packing algorithms, unstructured mesh discretization, finite volume solvers, extrapolation and post-processing techniques. The proposed method can be efficiently used in many porous media applications for problems such as stochastic homogenization/upscaling, propagation of uncertainty from microscopic fluid and rock properties to macro-scale parameters, robust estimation of Representative Elementary Volume size for arbitrary physics.

Incorporating a prediction of postgrazing herbage mass into a whole-farm model for pasture-based dairy systems.

PubMed

Gregorini, P; Galli, J; Romera, A J; Levy, G; Macdonald, K A; Fernandez, H H; Beukes, P C

2014-07-01

The DairyNZ whole-farm model (WFM; DairyNZ, Hamilton, New Zealand) consists of a framework that links component models for animal, pastures, crops, and soils. The model was developed to assist with analysis and design of pasture-based farm systems. New (this work) and revised (e.g., cow, pasture, crops) component models can be added to the WFM, keeping the model flexible and up to date. Nevertheless, the WFM does not account for plant-animal relationships determining herbage-depletion dynamics. The user has to preset the maximum allowable level of herbage depletion [i.e., postgrazing herbage mass (residuals)] throughout the year. Because residuals have a direct effect on herbage regrowth, the WFM in its current form does not dynamically simulate the effect of grazing pressure on herbage depletion and consequent effect on herbage regrowth. The management of grazing pressure is a key component of pasture-based dairy systems. Thus, the main objective of the present work was to develop a new version of the WFM able to predict residuals, and thereby simulate related effects of grazing pressure dynamically at the farm scale. This objective was accomplished by incorporating a new component model into the WFM. This model represents plant-animal relationships, for example sward structure and herbage intake rate, and resulting level of herbage depletion. The sensitivity of the new version of the WFM was evaluated and then the new WFM was tested against an experimental data set previously used to evaluate the WFM and to illustrate the adequacy and improvement of the model development. Key outputs variables of the new version pertinent to this work (milk production, herbage dry matter intake, intake rate, harvesting efficiency, and residuals) responded acceptably to a range of input variables. The relative prediction errors for monthly and mean annual residual predictions were 20 and 5%, respectively. Monthly predictions of residuals had a line bias (1.5%), with a proportion of square root of mean square prediction error (RMSPE) due to random error of 97.5%. Predicted monthly herbage growth rates had a line bias of 2%, a proportion of RMSPE due to random error of 96%, and a concordance correlation coefficient of 0.87. Annual herbage production was predicted with an RMSPE of 531 (kg of herbage dry matter/ha per year), a line bias of 11%, a proportion of RMSPE due to random error of 80%, and relative prediction errors of 2%. Annual herbage dry matter intake per cow and hectare, both per year, were predicted with RMSPE, relative prediction error, and concordance correlation coefficient of 169 and 692kg of dry matter, 3 and 4%, and 0.91 and 0.87, respectively. These results indicate that predictions of the new WFM are relatively accurate and precise, with a conclusion that incorporating a plant-animal relationship model into the WFM allows for dynamic predictions of residuals and more realistic simulations of the effect of grazing pressure on herbage production and intake at the farm level without the intervention from the user. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

Reference-free error estimation for multiple measurement methods.

PubMed

Madan, Hennadii; Pernuš, Franjo; Špiclin, Žiga

2018-01-01

We present a computational framework to select the most accurate and precise method of measurement of a certain quantity, when there is no access to the true value of the measurand. A typical use case is when several image analysis methods are applied to measure the value of a particular quantitative imaging biomarker from the same images. The accuracy of each measurement method is characterized by systematic error (bias), which is modeled as a polynomial in true values of measurand, and the precision as random error modeled with a Gaussian random variable. In contrast to previous works, the random errors are modeled jointly across all methods, thereby enabling the framework to analyze measurement methods based on similar principles, which may have correlated random errors. Furthermore, the posterior distribution of the error model parameters is estimated from samples obtained by Markov chain Monte-Carlo and analyzed to estimate the parameter values and the unknown true values of the measurand. The framework was validated on six synthetic and one clinical dataset containing measurements of total lesion load, a biomarker of neurodegenerative diseases, which was obtained with four automatic methods by analyzing brain magnetic resonance images. The estimates of bias and random error were in a good agreement with the corresponding least squares regression estimates against a reference.

Diagnostic grade wireless ECG monitoring.

PubMed

Garudadri, Harinath; Chi, Yuejie; Baker, Steve; Majumdar, Somdeb; Baheti, Pawan K; Ballard, Dan

2011-01-01

In remote monitoring of Electrocardiogram (ECG), it is very important to ensure that the diagnostic integrity of signals is not compromised by sensing artifacts and channel errors. It is also important for the sensors to be extremely power efficient to enable wearable form factors and long battery life. We present an application of Compressive Sensing (CS) as an error mitigation scheme at the application layer for wearable, wireless sensors in diagnostic grade remote monitoring of ECG. In our previous work, we described an approach to mitigate errors due to packet losses by projecting ECG data to a random space and recovering a faithful representation using sparse reconstruction methods. Our contributions in this work are twofold. First, we present an efficient hardware implementation of random projection at the sensor. Second, we validate the diagnostic integrity of the reconstructed ECG after packet loss mitigation. We validate our approach on MIT and AHA databases comprising more than 250,000 normal and abnormal beats using EC57 protocols adopted by the Food and Drug Administration (FDA). We show that sensitivity and positive predictivity of a state-of-the-art ECG arrhythmia classifier is essentially invariant under CS based packet loss mitigation for both normal and abnormal beats even at high packet loss rates. In contrast, the performance degrades significantly in the absence of any error mitigation scheme, particularly for abnormal beats such as Ventricular Ectopic Beats (VEB).

Errors in radial velocity variance from Doppler wind lidar

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

Wang, H.; Barthelmie, R. J.; Doubrawa, P.

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

Errors in radial velocity variance from Doppler wind lidar

DOE PAGES

Wang, H.; Barthelmie, R. J.; Doubrawa, P.; ...

2016-08-29

A high-fidelity lidar turbulence measurement technique relies on accurate estimates of radial velocity variance that are subject to both systematic and random errors determined by the autocorrelation function of radial velocity, the sampling rate, and the sampling duration. Our paper quantifies the effect of the volumetric averaging in lidar radial velocity measurements on the autocorrelation function and the dependence of the systematic and random errors on the sampling duration, using both statistically simulated and observed data. For current-generation scanning lidars and sampling durations of about 30 min and longer, during which the stationarity assumption is valid for atmospheric flows, themore » systematic error is negligible but the random error exceeds about 10%.« less

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.

NASA's New Orbital Debris Engineering Model, ORDEM2010

NASA Technical Reports Server (NTRS)

Krisko, Paula H.

2010-01-01

This paper describes the functionality and use of ORDEM2010, which replaces ORDEM2000, as the NASA Orbital Debris Program Office (ODPO) debris engineering model. Like its predecessor, ORDEM2010 serves the ODPO mission of providing spacecraft designers/operators and debris observers with a publicly available model to calculate orbital debris flux by current-state-of-knowledge methods. The key advance in ORDEM2010 is the input file structure of the yearly debris populations from 1995-2035 of sizes 10 micron - 1 m. These files include debris from low-Earth orbits (LEO) through geosynchronous orbits (GEO). Stable orbital elements (i.e., those that do not randomize on a sub-year timescale) are included in the files as are debris size, debris number, material density, random error and population error. Material density is implemented from ground-test data into the NASA breakup model and assigned to debris fragments accordingly. The random and population errors are due to machine error and uncertainties in debris sizes. These high-fidelity population files call for a much higher-level model analysis than what was possible with the populations of ORDEM2000. Population analysis in the ORDEM2010 model consists of mapping matrices that convert the debris population elements to debris fluxes. One output mode results in a spacecraft encompassing 3-D igloo of debris flux, compartmentalized by debris size, velocity, pitch, and yaw with respect to spacecraft ram direction. The second output mode provides debris flux through an Earth-based telescope/radar beam from LEO through GEO. This paper compares the new ORDEM2010 with ORDEM2000 in terms of processes and results with examples of specific orbits.

A radio-aware routing algorithm for reliable directed diffusion in lossy wireless sensor networks.

PubMed

Kim, Yong-Pyo; Jung, Euihyun; Park, Yong-Jin

2009-01-01

In Wireless Sensor Networks (WSNs), transmission errors occur frequently due to node failure, battery discharge, contention or interference by objects. Although Directed Diffusion has been considered as a prominent data-centric routing algorithm, it has some weaknesses due to unexpected network errors. In order to address these problems, we proposed a radio-aware routing algorithm to improve the reliability of Directed Diffusion in lossy WSNs. The proposed algorithm is aware of the network status based on the radio information from MAC and PHY layers using a cross-layer design. The cross-layer design can be used to get detailed information about current status of wireless network such as a link quality or transmission errors of communication links. The radio information indicating variant network conditions and link quality was used to determine an alternative route that provides reliable data transmission under lossy WSNs. According to the simulation result, the radio-aware reliable routing algorithm showed better performance in both grid and random topologies with various error rates. The proposed solution suggested the possibility of providing a reliable transmission method for QoS requests in lossy WSNs based on the radio-awareness. The energy and mobility issues will be addressed in the future work.

[Prospective assessment of medication errors in critically ill patients in a university hospital].

PubMed

Salazar L, Nicole; Jirón A, Marcela; Escobar O, Leslie; Tobar, Eduardo; Romero, Carlos

2011-11-01

Critically ill patients are especially vulnerable to medication errors (ME) due to their severe clinical situation and the complexities of their management. To determine the frequency and characteristics of ME and identify shortcomings in the processes of medication management in an Intensive Care Unit. During a 3 months period, an observational prospective and randomized study was carried out in the ICU of a university hospital. Every step of patient's medication management (prescription, transcription, dispensation, preparation and administration) was evaluated by an external trained professional. Steps with higher frequency of ME and their therapeutic groups involved were identified. Medications errors were classified according to the National Coordinating Council for Medication Error Reporting and Prevention. In 52 of 124 patients evaluated, 66 ME were found in 194 drugs prescribed. In 34% of prescribed drugs, there was at least 1 ME during its use. Half of ME occurred during medication administration, mainly due to problems in infusion rates and schedule times. Antibacterial drugs had the highest rate of ME. We found a 34% rate of ME per drug prescribed, which is in concordance with international reports. The identification of those steps more prone to ME in the ICU, will allow the implementation of an intervention program to improve the quality and security of medication management.

Simulation of wave propagation in three-dimensional random media

NASA Astrophysics Data System (ADS)

Coles, Wm. A.; Filice, J. P.; Frehlich, R. G.; Yadlowsky, M.

1995-04-01

Quantitative error analyses for the simulation of wave propagation in three-dimensional random media, when narrow angular scattering is assumed, are presented for plane-wave and spherical-wave geometry. This includes the errors that result from finite grid size, finite simulation dimensions, and the separation of the two-dimensional screens along the propagation direction. Simple error scalings are determined for power-law spectra of the random refractive indices of the media. The effects of a finite inner scale are also considered. The spatial spectra of the intensity errors are calculated and compared with the spatial spectra of

Scattering from binary optics

NASA Technical Reports Server (NTRS)

Ricks, Douglas W.

1993-01-01

There are a number of sources of scattering in binary optics: etch depth errors, line edge errors, quantization errors, roughness, and the binary approximation to the ideal surface. These sources of scattering can be systematic (deterministic) or random. In this paper, scattering formulas for both systematic and random errors are derived using Fourier optics. These formulas can be used to explain the results of scattering measurements and computer simulations.

Image guidance in prostate cancer - can offline corrections be an effective substitute for daily online imaging?

PubMed

Prasad, Devleena; Das, Pinaki; Saha, Niladri S; Chatterjee, Sanjoy; Achari, Rimpa; Mallick, Indranil

2014-01-01

This aim of this study was to determine if a less resource-intensive and established offline correction protocol - the No Action Level (NAL) protocol was as effective as daily online corrections of setup deviations in curative high-dose radiotherapy of prostate cancer. A total of 683 daily megavoltage CT (MVCT) or kilovoltage CT (kvCBCT) images of 30 patients with localized prostate cancer treated with intensity modulated radiotherapy were evaluated. Daily image-guidance was performed and setup errors in three translational axes recorded. The NAL protocol was simulated by using the mean shift calculated from the first five fractions and implemented on all subsequent treatments. Using the imaging data from the remaining fractions, the daily residual error (RE) was determined. The proportion of fractions where the RE was greater than 3,5 and 7 mm was calculated, and also the actual PTV margin that would be required if the offline protocol was followed. Using the NAL protocol reduced the systematic but not the random errors. Corrections made using the NAL protocol resulted in small and acceptable RE in the mediolateral (ML) and superoinferior (SI) directions with 46/533 (8.1%) and 48/533 (5%) residual shifts above 5 mm. However; residual errors greater than 5mm in the anteroposterior (AP) direction remained in 181/533 (34%) of fractions. The PTV margins calculated based on residual errors were 5mm, 5mm and 13 mm in the ML, SI and AP directions respectively. Offline correction using the NAL protocol resulted in unacceptably high residual errors in the AP direction, due to random uncertainties of rectal and bladder filling. Daily online imaging and corrections remain the standard image guidance policy for highly conformal radiotherapy of prostate cancer.

Error monitoring issues for common channel signaling

NASA Astrophysics Data System (ADS)

Hou, Victor T.; Kant, Krishna; Ramaswami, V.; Wang, Jonathan L.

1994-04-01

Motivated by field data which showed a large number of link changeovers and incidences of link oscillations between in-service and out-of-service states in common channel signaling (CCS) networks, a number of analyses of the link error monitoring procedures in the SS7 protocol were performed by the authors. This paper summarizes the results obtained thus far and include the following: (1) results of an exact analysis of the performance of the error monitoring procedures under both random and bursty errors; (2) a demonstration that there exists a range of error rates within which the error monitoring procedures of SS7 may induce frequent changeovers and changebacks; (3) an analysis of the performance ofthe SS7 level-2 transmission protocol to determine the tolerable error rates within which the delay requirements can be met; (4) a demonstration that the tolerable error rate depends strongly on various link and traffic characteristics, thereby implying that a single set of error monitor parameters will not work well in all situations; (5) some recommendations on a customizable/adaptable scheme of error monitoring with a discussion on their implementability. These issues may be particularly relevant in the presence of anticipated increases in SS7 traffic due to widespread deployment of Advanced Intelligent Network (AIN) and Personal Communications Service (PCS) as well as for developing procedures for high-speed SS7 links currently under consideration by standards bodies.

Analysis of the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery☆

PubMed Central

Arba-Mosquera, Samuel; Aslanides, Ioannis M.

2012-01-01

Purpose To analyze the effects of Eye-Tracker performance on the pulse positioning errors during refractive surgery. Methods A comprehensive model, which directly considers eye movements, including saccades, vestibular, optokinetic, vergence, and miniature, as well as, eye-tracker acquisition rate, eye-tracker latency time, scanner positioning time, laser firing rate, and laser trigger delay have been developed. Results Eye-tracker acquisition rates below 100 Hz correspond to pulse positioning errors above 1.5 mm. Eye-tracker latency times to about 15 ms correspond to pulse positioning errors of up to 3.5 mm. Scanner positioning times to about 9 ms correspond to pulse positioning errors of up to 2 mm. Laser firing rates faster than eye-tracker acquisition rates basically duplicate pulse-positioning errors. Laser trigger delays to about 300 μs have minor to no impact on pulse-positioning errors. Conclusions The proposed model can be used for comparison of laser systems used for ablation processes. Due to the pseudo-random nature of eye movements, positioning errors of single pulses are much larger than observed decentrations in the clinical settings. There is no single parameter that ‘alone’ minimizes the positioning error. It is the optimal combination of the several parameters that minimizes the error. The results of this analysis are important to understand the limitations of correcting very irregular ablation patterns.

SU-F-J-65: Prediction of Patient Setup Errors and Errors in the Calibration Curve from Prompt Gamma Proton Range Measurements

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

Albert, J; Labarbe, R; Sterpin, E

2016-06-15

Purpose: To understand the extent to which the prompt gamma camera measurements can be used to predict the residual proton range due to setup errors and errors in the calibration curve. Methods: We generated ten variations on a default calibration curve (CC) and ten corresponding range maps (RM). Starting with the default RM, we chose a square array of N beamlets, which were then rotated by a random angle θ and shifted by a random vector s. We added a 5% distal Gaussian noise to each beamlet in order to introduce discrepancies that exist between the ranges predicted from themore » prompt gamma measurements and those simulated with Monte Carlo algorithms. For each RM, s, θ, along with an offset u in the CC, were optimized using a simple Euclidian distance between the default ranges and the ranges produced by the given RM. Results: The application of our method lead to the maximal overrange of 2.0mm and underrange of 0.6mm on average. Compared to the situations where s, θ, and u were ignored, these values were larger: 2.1mm and 4.3mm. In order to quantify the need for setup error corrections, we also performed computations in which u was corrected for, but s and θ were not. This yielded: 3.2mm and 3.2mm. The average computation time for 170 beamlets was 65 seconds. Conclusion: These results emphasize the necessity to correct for setup errors and the errors in the calibration curve. The simplicity and speed of our method makes it a good candidate for being implemented as a tool for in-room adaptive therapy. This work also demonstrates that the Prompt gamma range measurements can indeed be useful in the effort to reduce range errors. Given these results, and barring further refinements, this approach is a promising step towards an adaptive proton radiotherapy.« less

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.

Spatial serial order processing in schizophrenia.

PubMed

Fraser, David; Park, Sohee; Clark, Gina; Yohanna, Daniel; Houk, James C

2004-10-01

The aim of this study was to examine serial order processing deficits in 21 schizophrenia patients and 16 age- and education-matched healthy controls. In a spatial serial order working memory task, one to four spatial targets were presented in a randomized sequence. Subjects were required to remember the locations and the order in which the targets were presented. Patients showed a marked deficit in ability to remember the sequences compared with controls. Increasing the number of targets within a sequence resulted in poorer memory performance for both control and schizophrenia subjects, but the effect was much more pronounced in the patients. Targets presented at the end of a long sequence were more vulnerable to memory error in schizophrenia patients. Performance deficits were not attributable to motor errors, but to errors in target choice. The results support the idea that the memory errors seen in schizophrenia patients may be due to saturating the working memory network at relatively low levels of memory load.

Sonority contours in word recognition

NASA Astrophysics Data System (ADS)

McLennan, Sean

2003-04-01

Contrary to the Generativist distinction between competence and performance which asserts that speech or perception errors are due to random, nonlinguistic factors, it seems likely that errors are principled and possibly governed by some of the same constraints as language. A preliminary investigation of errors modeled after the child's ``Chain Whisper'' game (a degraded stimulus task) suggests that a significant number of recognition errors can be characterized as an improvement in syllable sonority contour towards the linguistically least-marked, voiceless-stop-plus-vowel syllable. An independent study of sonority contours showed that approximately half of the English lexicon can be uniquely identified by their contour alone. Additionally, ``sororities'' (groups of words that share a single sonority contour), surprisingly, show no correlation to familiarity or frequency in either size or membership. Together these results imply that sonority contours may be an important factor in word recognition and in defining word ``neighborhoods.'' Moreover, they suggest that linguistic markedness constraints may be more prevalent in performance-related phenomena than previously accepted.

Systematic evaluation of NASA precipitation radar estimates using NOAA/NSSL National Mosaic QPE products

NASA Astrophysics Data System (ADS)

Kirstetter, P.; Hong, Y.; Gourley, J. J.; Chen, S.; Flamig, Z.; Zhang, J.; Howard, K.; Petersen, W. A.

2011-12-01

Proper characterization of the error structure of TRMM Precipitation Radar (PR) quantitative precipitation estimation (QPE) is needed for their use in TRMM combined products, water budget studies and hydrological modeling applications. Due to the variety of sources of error in spaceborne radar QPE (attenuation of the radar signal, influence of land surface, impact of off-nadir viewing angle, etc.) and the impact of correction algorithms, the problem is addressed by comparison of PR QPEs with reference values derived from ground-based measurements (GV) using NOAA/NSSL's National Mosaic QPE (NMQ) system. An investigation of this subject has been carried out at the PR estimation scale (instantaneous and 5 km) on the basis of a 3-month-long data sample. A significant effort has been carried out to derive a bias-corrected, robust reference rainfall source from NMQ. The GV processing details will be presented along with preliminary results of PR's error characteristics using contingency table statistics, probability distribution comparisons, scatter plots, semi-variograms, and systematic biases and random errors.

Silicon microring resonators

NASA Astrophysics Data System (ADS)

Tan, Ying; Dai, Daoxin

2018-05-01

Silicon microring resonators (MRRs) are very popular for many applications because of the advantages of footprint compactness, easy scalability, and functional versatility. Ultra-compact silicon MRRs with box-like spectral responses are realized with a very large free-spectral range (FSR) by introducing bent directional couplers. The measured box-like spectral response has an FSR of >30 nm. The permanent wavelength-alignment techniques for MRRs are also presented, including the laser-induced local-oxidation technique as well as the local-etching technique. With these techniques, one can control finely the permanent wavelength shift, which is also large enough to compensate the random wavelength variation due to the random fabrication errors.

A Novel Approach of Understanding and Incorporating Error of Chemical Transport Models into a Geostatistical Framework

NASA Astrophysics Data System (ADS)

Reyes, J.; Vizuete, W.; Serre, M. L.; Xu, Y.

2015-12-01

The EPA employs a vast monitoring network to measure ambient PM2.5 concentrations across the United States with one of its goals being to quantify exposure within the population. However, there are several areas of the country with sparse monitoring spatially and temporally. One means to fill in these monitoring gaps is to use PM2.5 modeled estimates from Chemical Transport Models (CTMs) specifically the Community Multi-scale Air Quality (CMAQ) model. CMAQ is able to provide complete spatial coverage but is subject to systematic and random error due to model uncertainty. Due to the deterministic nature of CMAQ, often these uncertainties are not quantified. Much effort is employed to quantify the efficacy of these models through different metrics of model performance. Currently evaluation is specific to only locations with observed data. Multiyear studies across the United States are challenging because the error and model performance of CMAQ are not uniform over such large space/time domains. Error changes regionally and temporally. Because of the complex mix of species that constitute PM2.5, CMAQ error is also a function of increasing PM2.5 concentration. To address this issue we introduce a model performance evaluation for PM2.5 CMAQ that is regionalized and non-linear. This model performance evaluation leads to error quantification for each CMAQ grid. Areas and time periods of error being better qualified. The regionalized error correction approach is non-linear and is therefore more flexible at characterizing model performance than approaches that rely on linearity assumptions and assume homoscedasticity of CMAQ predictions errors. Corrected CMAQ data are then incorporated into the modern geostatistical framework of Bayesian Maximum Entropy (BME). Through cross validation it is shown that incorporating error-corrected CMAQ data leads to more accurate estimates than just using observed data by themselves.

Carbon monoxide measurement in the global atmospheric sampling program

NASA Technical Reports Server (NTRS)

Dudzinski, T. J.

1979-01-01

The carbon monoxide measurement system used in the NASA Global Atmospheric Sampling Program (GASP) is described. The system used a modified version of a commercially available infrared absorption analyzer. The modifications increased the sensitivity of the analyzer to 1 ppmv full scale, with a limit of detectability of 0.02 ppmv. Packaging was modified for automatic, unattended operation in an aircraft environment. The GASP system is described along with analyzer operation, calibration procedures, and measurement errors. Uncertainty of the CO measurement over a 2-year period ranged from + or - 3 to + or - 13 percent of reading, plus an error due to random fluctuation of the output signal + or - 3 to + or - 15 ppbv.

Free space optical ultra-wideband communications over atmospheric turbulence channels.

PubMed

Davaslioğlu, Kemal; Cağiral, Erman; Koca, Mutlu

2010-08-02

A hybrid impulse radio ultra-wideband (IR-UWB) communication system in which UWB pulses are transmitted over long distances through free space optical (FSO) links is proposed. FSO channels are characterized by random fluctuations in the received light intensity mainly due to the atmospheric turbulence. For this reason, theoretical detection error probability analysis is presented for the proposed system for a time-hopping pulse-position modulated (TH-PPM) UWB signal model under weak, moderate and strong turbulence conditions. For the optical system output distributed over radio frequency UWB channels, composite error analysis is also presented. The theoretical derivations are verified via simulation results, which indicate a computationally and spectrally efficient UWB-over-FSO system.

Simultaneous Laser Ranging and Communication from an Earth-Based Satellite Laser Ranging Station to the Lunar Reconnaissance Orbiter in Lunar Orbit

NASA Technical Reports Server (NTRS)

Sun, Xiaoli; Skillman, David R.; Hoffman, Evan D.; Mao, Dandan; McGarry, Jan F.; Neumann, Gregory A.; McIntire, Leva; Zellar, Ronald S.; Davidson, Frederic M.; Fong, Wai H.;

Efficient Z gates for quantum computing

NASA Astrophysics Data System (ADS)

McKay, David C.; Wood, Christopher J.; Sheldon, Sarah; Chow, Jerry M.; Gambetta, Jay M.

2017-08-01

For superconducting qubits, microwave pulses drive rotations around the Bloch sphere. The phase of these drives can be used to generate zero-duration arbitrary virtual Z gates, which, combined with two Xπ /2 gates, can generate any SU(2) gate. Here we show how to best utilize these virtual Z gates to both improve algorithms and correct pulse errors. We perform randomized benchmarking using a Clifford set of Hadamard and Z gates and show that the error per Clifford is reduced versus a set consisting of standard finite-duration X and Y gates. Z gates can correct unitary rotation errors for weakly anharmonic qubits as an alternative to pulse-shaping techniques such as derivative removal by adiabatic gate (DRAG). We investigate leakage and show that a combination of DRAG pulse shaping to minimize leakage and Z gates to correct rotation errors realizes a 13.3 ns Xπ /2 gate characterized by low error [1.95 (3 ) ×10-4] and low leakage [3.1 (6 ) ×10-6] . Ultimately leakage is limited by the finite temperature of the qubit, but this limit is two orders of magnitude smaller than pulse errors due to decoherence.

Horizon sensors attitude errors simulation for the Brazilian Remote Sensing Satellite

NASA Astrophysics Data System (ADS)

Vicente de Brum, Antonio Gil; Ricci, Mario Cesar

Remote sensing, meteorological and other types of satellites require an increasingly better Earth related positioning. From the past experience it is well known that the thermal horizon in the 15 micrometer band provides conditions of determining the local vertical at any time. This detection is done by horizon sensors which are accurate instruments for Earth referred attitude sensing and control whose performance is limited by systematic and random errors amounting about 0.5 deg. Using the computer programs OBLATE, SEASON, ELECTRO and MISALIGN, developed at INPE to simulate four distinct facets of conical scanning horizon sensors, attitude errors are obtained for the Brazilian Remote Sensing Satellite (the first one, SSR-1, is scheduled to fly in 1996). These errors are due to the oblate shape of the Earth, seasonal and latitudinal variations of the 15 micrometer infrared radiation, electronic processing time delay and misalignment of sensor axis. The sensor related attitude errors are thus properly quantified in this work and will, together with other systematic errors (for instance, ambient temperature variation) take part in the pre-launch analysis of the Brazilian Remote Sensing Satellite, with respect to the horizon sensor performance.

Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model

NASA Astrophysics Data System (ADS)

Zou, Guang'an; Wang, Qiang; Mu, Mu

2016-09-01

Sensitive areas for prediction of the Kuroshio large meander using a 1.5-layer, shallow-water ocean model were investigated using the conditional nonlinear optimal perturbation (CNOP) and first singular vector (FSV) methods. A series of sensitivity experiments were designed to test the sensitivity of sensitive areas within the numerical model. The following results were obtained: (1) the eff ect of initial CNOP and FSV patterns in their sensitive areas is greater than that of the same patterns in randomly selected areas, with the eff ect of the initial CNOP patterns in CNOP sensitive areas being the greatest; (2) both CNOP- and FSV-type initial errors grow more quickly than random errors; (3) the eff ect of random errors superimposed on the sensitive areas is greater than that of random errors introduced into randomly selected areas, and initial errors in the CNOP sensitive areas have greater eff ects on final forecasts. These results reveal that the sensitive areas determined using the CNOP are more sensitive than those of FSV and other randomly selected areas. In addition, ideal hindcasting experiments were conducted to examine the validity of the sensitive areas. The results indicate that reduction (or elimination) of CNOP-type errors in CNOP sensitive areas at the initial time has a greater forecast benefit than the reduction (or elimination) of FSV-type errors in FSV sensitive areas. These results suggest that the CNOP method is suitable for determining sensitive areas in the prediction of the Kuroshio large-meander path.

Portable and Error-Free DNA-Based Data Storage.

PubMed

Yazdi, S M Hossein Tabatabaei; Gabrys, Ryan; Milenkovic, Olgica

2017-07-10

DNA-based data storage is an emerging nonvolatile memory technology of potentially unprecedented density, durability, and replication efficiency. The basic system implementation steps include synthesizing DNA strings that contain user information and subsequently retrieving them via high-throughput sequencing technologies. Existing architectures enable reading and writing but do not offer random-access and error-free data recovery from low-cost, portable devices, which is crucial for making the storage technology competitive with classical recorders. Here we show for the first time that a portable, random-access platform may be implemented in practice using nanopore sequencers. The novelty of our approach is to design an integrated processing pipeline that encodes data to avoid costly synthesis and sequencing errors, enables random access through addressing, and leverages efficient portable sequencing via new iterative alignment and deletion error-correcting codes. Our work represents the only known random access DNA-based data storage system that uses error-prone nanopore sequencers, while still producing error-free readouts with the highest reported information rate/density. As such, it represents a crucial step towards practical employment of DNA molecules as storage media.

Simulation of the Effects of Random Measurement Errors

ERIC Educational Resources Information Center

Kinsella, I. A.; Hannaidh, P. B. O.

1978-01-01

Describes a simulation method for measurement of errors that requires calculators and tables of random digits. Each student simulates the random behaviour of the component variables in the function and by combining the results of all students, the outline of the sampling distribution of the function can be obtained. (GA)

The impact of 3D volume of interest definition on accuracy and precision of activity estimation in quantitative SPECT and planar processing methods

NASA Astrophysics Data System (ADS)

He, Bin; Frey, Eric C.

2010-06-01

Accurate and precise estimation of organ activities is essential for treatment planning in targeted radionuclide therapy. We have previously evaluated the impact of processing methodology, statistical noise and variability in activity distribution and anatomy on the accuracy and precision of organ activity estimates obtained with quantitative SPECT (QSPECT) and planar (QPlanar) processing. Another important factor impacting the accuracy and precision of organ activity estimates is accuracy of and variability in the definition of organ regions of interest (ROI) or volumes of interest (VOI). The goal of this work was thus to systematically study the effects of VOI definition on the reliability of activity estimates. To this end, we performed Monte Carlo simulation studies using randomly perturbed and shifted VOIs to assess the impact on organ activity estimates. The 3D NCAT phantom was used with activities that modeled clinically observed 111In ibritumomab tiuxetan distributions. In order to study the errors resulting from misdefinitions due to manual segmentation errors, VOIs of the liver and left kidney were first manually defined. Each control point was then randomly perturbed to one of the nearest or next-nearest voxels in three ways: with no, inward or outward directional bias, resulting in random perturbation, erosion or dilation, respectively, of the VOIs. In order to study the errors resulting from the misregistration of VOIs, as would happen, e.g. in the case where the VOIs were defined using a misregistered anatomical image, the reconstructed SPECT images or projections were shifted by amounts ranging from -1 to 1 voxels in increments of with 0.1 voxels in both the transaxial and axial directions. The activity estimates from the shifted reconstructions or projections were compared to those from the originals, and average errors were computed for the QSPECT and QPlanar methods, respectively. For misregistration, errors in organ activity estimations were linear in the shift for both the QSPECT and QPlanar methods. QPlanar was less sensitive to object definition perturbations than QSPECT, especially for dilation and erosion cases. Up to 1 voxel misregistration or misdefinition resulted in up to 8% error in organ activity estimates, with the largest errors for small or low uptake organs. Both types of VOI definition errors produced larger errors in activity estimates for a small and low uptake organs (i.e. -7.5% to 5.3% for the left kidney) than for a large and high uptake organ (i.e. -2.9% to 2.1% for the liver). We observed that misregistration generally had larger effects than misdefinition, with errors ranging from -7.2% to 8.4%. The different imaging methods evaluated responded differently to the errors from misregistration and misdefinition. We found that QSPECT was more sensitive to misdefinition errors, but less sensitive to misregistration errors, as compared to the QPlanar method. Thus, sensitivity to VOI definition errors should be an important criterion in evaluating quantitative imaging methods.

On the robustness of bucket brigade quantum RAM

NASA Astrophysics Data System (ADS)

Arunachalam, Srinivasan; Gheorghiu, Vlad; Jochym-O'Connor, Tomas; Mosca, Michele; Varshinee Srinivasan, Priyaa

2015-12-01

We study the robustness of the bucket brigade quantum random access memory model introduced by Giovannetti et al (2008 Phys. Rev. Lett.100 160501). Due to a result of Regev and Schiff (ICALP ’08 733), we show that for a class of error models the error rate per gate in the bucket brigade quantum memory has to be of order o({2}-n/2) (where N={2}n is the size of the memory) whenever the memory is used as an oracle for the quantum searching problem. We conjecture that this is the case for any realistic error model that will be encountered in practice, and that for algorithms with super-polynomially many oracle queries the error rate must be super-polynomially small, which further motivates the need for quantum error correction. By contrast, for algorithms such as matrix inversion Harrow et al (2009 Phys. Rev. Lett.103 150502) or quantum machine learning Rebentrost et al (2014 Phys. Rev. Lett.113 130503) that only require a polynomial number of queries, the error rate only needs to be polynomially small and quantum error correction may not be required. We introduce a circuit model for the quantum bucket brigade architecture and argue that quantum error correction for the circuit causes the quantum bucket brigade architecture to lose its primary advantage of a small number of ‘active’ gates, since all components have to be actively error corrected.

A preliminary taxonomy of medical errors in family practice

PubMed Central

Dovey, S; Meyers, D; Phillips, R; Green, L; Fryer, G; Galliher, J; Kappus, J; Grob, P

2002-01-01

Objective: To develop a preliminary taxonomy of primary care medical errors. Design: Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. Setting: The National Network for Family Practice and Primary Care Research. Participants: Family physicians. Main outcome measures: Medical error category, context, and consequence. Results: Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failures (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. Conclusions: This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors. PMID:12486987

A preliminary taxonomy of medical errors in family practice.

PubMed

Dovey, S M; Meyers, D S; Phillips, R L; Green, L A; Fryer, G E; Galliher, J M; Kappus, J; Grob, P

2002-09-01

To develop a preliminary taxonomy of primary care medical errors. Qualitative analysis to identify categories of error reported during a randomized controlled trial of computer and paper reporting methods. The National Network for Family Practice and Primary Care Research. Family physicians. Medical error category, context, and consequence. Forty two physicians made 344 reports: 284 (82.6%) arose from healthcare systems dysfunction; 46 (13.4%) were errors due to gaps in knowledge or skills; and 14 (4.1%) were reports of adverse events, not errors. The main subcategories were: administrative failure (102; 30.9% of errors), investigation failures (82; 24.8%), treatment delivery lapses (76; 23.0%), miscommunication (19; 5.8%), payment systems problems (4; 1.2%), error in the execution of a clinical task (19; 5.8%), wrong treatment decision (14; 4.2%), and wrong diagnosis (13; 3.9%). Most reports were of errors that were recognized and occurred in reporters' practices. Affected patients ranged in age from 8 months to 100 years, were of both sexes, and represented all major US ethnic groups. Almost half the reports were of events which had adverse consequences. Ten errors resulted in patients being admitted to hospital and one patient died. This medical error taxonomy, developed from self-reports of errors observed by family physicians during their routine clinical practice, emphasizes problems in healthcare processes and acknowledges medical errors arising from shortfalls in clinical knowledge and skills. Patient safety strategies with most effect in primary care settings need to be broader than the current focus on medication errors.

Development of multiple-eye PIV using mirror array

NASA Astrophysics Data System (ADS)

Maekawa, Akiyoshi; Sakakibara, Jun

2018-06-01

In order to reduce particle image velocimetry measurement error, we manufactured an ellipsoidal polyhedral mirror and placed it between a camera and flow target to capture n images of identical particles from n (=80 maximum) different directions. The 3D particle positions were determined from the ensemble average of n C2 intersecting points of a pair of line-of-sight back-projected points from a particle found in any combination of two images in the n images. The method was then applied to a rigid-body rotating flow and a turbulent pipe flow. In the former measurement, bias error and random error fell in a range of  ±0.02 pixels and 0.02–0.05 pixels, respectively; additionally, random error decreased in proportion to . In the latter measurement, in which the measured value was compared to direct numerical simulation, bias error was reduced and random error also decreased in proportion to .

Error Estimation of Pathfinder Version 5.3 SST Level 3C Using Three-way Error Analysis

NASA Astrophysics Data System (ADS)

Saha, K.; Dash, P.; Zhao, X.; Zhang, H. M.

2017-12-01

One of the essential climate variables for monitoring as well as detecting and attributing climate change, is Sea Surface Temperature (SST). A long-term record of global SSTs are available with observations obtained from ships in the early days to the more modern observation based on in-situ as well as space-based sensors (satellite/aircraft). There are inaccuracies associated with satellite derived SSTs which can be attributed to the errors associated with spacecraft navigation, sensor calibrations, sensor noise, retrieval algorithms, and leakages due to residual clouds. Thus it is important to estimate accurate errors in satellite derived SST products to have desired results in its applications.Generally for validation purposes satellite derived SST products are compared against the in-situ SSTs which have inaccuracies due to spatio/temporal inhomogeneity between in-situ and satellite measurements. A standard deviation in their difference fields usually have contributions from both satellite as well as the in-situ measurements. A real validation of any geophysical variable must require the knowledge of the "true" value of the said variable. Therefore a one-to-one comparison of satellite based SST with in-situ data does not truly provide us the real error in the satellite SST and there will be ambiguity due to errors in the in-situ measurements and their collocation differences. A Triple collocation (TC) or three-way error analysis using 3 mutually independent error-prone measurements, can be used to estimate root-mean square error (RMSE) associated with each of the measurements with high level of accuracy without treating any one system a perfectly-observed "truth". In this study we are estimating the absolute random errors associated with Pathfinder Version 5.3 Level-3C SST product Climate Data record. Along with the in-situ SST data, the third source of dataset used for this analysis is the AATSR reprocessing of climate (ARC) dataset for the corresponding period. All three SST observations are collocated, and statistics of difference between each pair is estimated. Instead of using a traditional TC analysis we have implemented the Extended Triple Collocation (ETC) approach to estimate the correlation coefficient of each measurement system w.r.t. the unknown target variable along with their RMSE.

DNA Barcoding through Quaternary LDPC Codes

PubMed Central

Tapia, Elizabeth; Spetale, Flavio; Krsticevic, Flavia; Angelone, Laura; Bulacio, Pilar

2015-01-01

For many parallel applications of Next-Generation Sequencing (NGS) technologies short barcodes able to accurately multiplex a large number of samples are demanded. To address these competitive requirements, the use of error-correcting codes is advised. Current barcoding systems are mostly built from short random error-correcting codes, a feature that strongly limits their multiplexing accuracy and experimental scalability. To overcome these problems on sequencing systems impaired by mismatch errors, the alternative use of binary BCH and pseudo-quaternary Hamming codes has been proposed. However, these codes either fail to provide a fine-scale with regard to size of barcodes (BCH) or have intrinsic poor error correcting abilities (Hamming). Here, the design of barcodes from shortened binary BCH codes and quaternary Low Density Parity Check (LDPC) codes is introduced. Simulation results show that although accurate barcoding systems of high multiplexing capacity can be obtained with any of these codes, using quaternary LDPC codes may be particularly advantageous due to the lower rates of read losses and undetected sample misidentification errors. Even at mismatch error rates of 10−2 per base, 24-nt LDPC barcodes can be used to multiplex roughly 2000 samples with a sample misidentification error rate in the order of 10−9 at the expense of a rate of read losses just in the order of 10−6. PMID:26492348

DNA Barcoding through Quaternary LDPC Codes.

PubMed

Tapia, Elizabeth; Spetale, Flavio; Krsticevic, Flavia; Angelone, Laura; Bulacio, Pilar

2015-01-01

For many parallel applications of Next-Generation Sequencing (NGS) technologies short barcodes able to accurately multiplex a large number of samples are demanded. To address these competitive requirements, the use of error-correcting codes is advised. Current barcoding systems are mostly built from short random error-correcting codes, a feature that strongly limits their multiplexing accuracy and experimental scalability. To overcome these problems on sequencing systems impaired by mismatch errors, the alternative use of binary BCH and pseudo-quaternary Hamming codes has been proposed. However, these codes either fail to provide a fine-scale with regard to size of barcodes (BCH) or have intrinsic poor error correcting abilities (Hamming). Here, the design of barcodes from shortened binary BCH codes and quaternary Low Density Parity Check (LDPC) codes is introduced. Simulation results show that although accurate barcoding systems of high multiplexing capacity can be obtained with any of these codes, using quaternary LDPC codes may be particularly advantageous due to the lower rates of read losses and undetected sample misidentification errors. Even at mismatch error rates of 10(-2) per base, 24-nt LDPC barcodes can be used to multiplex roughly 2000 samples with a sample misidentification error rate in the order of 10(-9) at the expense of a rate of read losses just in the order of 10(-6).

An Enhanced MEMS Error Modeling Approach Based on Nu-Support Vector Regression

PubMed Central

Bhatt, Deepak; Aggarwal, Priyanka; Bhattacharya, Prabir; Devabhaktuni, Vijay

2012-01-01

Micro Electro Mechanical System (MEMS)-based inertial sensors have made possible the development of a civilian land vehicle navigation system by offering a low-cost solution. However, the accurate modeling of the MEMS sensor errors is one of the most challenging tasks in the design of low-cost navigation systems. These sensors exhibit significant errors like biases, drift, noises; which are negligible for higher grade units. Different conventional techniques utilizing the Gauss Markov model and neural network method have been previously utilized to model the errors. However, Gauss Markov model works unsatisfactorily in the case of MEMS units due to the presence of high inherent sensor errors. On the other hand, modeling the random drift utilizing Neural Network (NN) is time consuming, thereby affecting its real-time implementation. We overcome these existing drawbacks by developing an enhanced Support Vector Machine (SVM) based error model. Unlike NN, SVMs do not suffer from local minimisation or over-fitting problems and delivers a reliable global solution. Experimental results proved that the proposed SVM approach reduced the noise standard deviation by 10–35% for gyroscopes and 61–76% for accelerometers. Further, positional error drifts under static conditions improved by 41% and 80% in comparison to NN and GM approaches. PMID:23012552

Analysis of filter tuning techniques for sequential orbit determination

NASA Technical Reports Server (NTRS)

Lee, T.; Yee, C.; Oza, D.

1995-01-01

This paper examines filter tuning techniques for a sequential orbit determination (OD) covariance analysis. Recently, there has been a renewed interest in sequential OD, primarily due to the successful flight qualification of the Tracking and Data Relay Satellite System (TDRSS) Onboard Navigation System (TONS) using Doppler data extracted onboard the Extreme Ultraviolet Explorer (EUVE) spacecraft. TONS computes highly accurate orbit solutions onboard the spacecraft in realtime using a sequential filter. As the result of the successful TONS-EUVE flight qualification experiment, the Earth Observing System (EOS) AM-1 Project has selected TONS as the prime navigation system. In addition, sequential OD methods can be used successfully for ground OD. Whether data are processed onboard or on the ground, a sequential OD procedure is generally favored over a batch technique when a realtime automated OD system is desired. Recently, OD covariance analyses were performed for the TONS-EUVE and TONS-EOS missions using the sequential processing options of the Orbit Determination Error Analysis System (ODEAS). ODEAS is the primary covariance analysis system used by the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). The results of these analyses revealed a high sensitivity of the OD solutions to the state process noise filter tuning parameters. The covariance analysis results show that the state estimate error contributions from measurement-related error sources, especially those due to the random noise and satellite-to-satellite ionospheric refraction correction errors, increase rapidly as the state process noise increases. These results prompted an in-depth investigation of the role of the filter tuning parameters in sequential OD covariance analysis. This paper analyzes how the spacecraft state estimate errors due to dynamic and measurement-related error sources are affected by the process noise level used. This information is then used to establish guidelines for determining optimal filter tuning parameters in a given sequential OD scenario for both covariance analysis and actual OD. Comparisons are also made with corresponding definitive OD results available from the TONS-EUVE analysis.

Effects of Random Circuit Fabrication Errors on Small Signal Gain and on Output Phase In a Traveling Wave Tube

NASA Astrophysics Data System (ADS)

Rittersdorf, I. M.; Antonsen, T. M., Jr.; Chernin, D.; Lau, Y. Y.

2011-10-01

Random fabrication errors may have detrimental effects on the performance of traveling-wave tubes (TWTs) of all types. A new scaling law for the modification in the average small signal gain and in the output phase is derived from the third order ordinary differential equation that governs the forward wave interaction in a TWT in the presence of random error that is distributed along the axis of the tube. Analytical results compare favorably with numerical results, in both gain and phase modifications as a result of random error in the phase velocity of the slow wave circuit. Results on the effect of the reverse-propagating circuit mode will be reported. This work supported by AFOSR, ONR, L-3 Communications Electron Devices, and Northrop Grumman Corporation.

At least some errors are randomly generated (Freud was wrong)

NASA Technical Reports Server (NTRS)

Sellen, A. J.; Senders, J. W.

1986-01-01

An experiment was carried out to expose something about human error generating mechanisms. In the context of the experiment, an error was made when a subject pressed the wrong key on a computer keyboard or pressed no key at all in the time allotted. These might be considered, respectively, errors of substitution and errors of omission. Each of seven subjects saw a sequence of three digital numbers, made an easily learned binary judgement about each, and was to press the appropriate one of two keys. Each session consisted of 1,000 presentations of randomly permuted, fixed numbers broken into 10 blocks of 100. One of two keys should have been pressed within one second of the onset of each stimulus. These data were subjected to statistical analyses in order to probe the nature of the error generating mechanisms. Goodness of fit tests for a Poisson distribution for the number of errors per 50 trial interval and for an exponential distribution of the length of the intervals between errors were carried out. There is evidence for an endogenous mechanism that may best be described as a random error generator. Furthermore, an item analysis of the number of errors produced per stimulus suggests the existence of a second mechanism operating on task driven factors producing exogenous errors. Some errors, at least, are the result of constant probability generating mechanisms with error rate idiosyncratically determined for each subject.

On the Calculation of Uncertainty Statistics with Error Bounds for CFD Calculations Containing Random Parameters and Fields

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2016-01-01

This chapter discusses the ongoing development of combined uncertainty and error bound estimates for computational fluid dynamics (CFD) calculations subject to imposed random parameters and random fields. An objective of this work is the construction of computable error bound formulas for output uncertainty statistics that guide CFD practitioners in systematically determining how accurately CFD realizations should be approximated and how accurately uncertainty statistics should be approximated for output quantities of interest. Formal error bounds formulas for moment statistics that properly account for the presence of numerical errors in CFD calculations and numerical quadrature errors in the calculation of moment statistics have been previously presented in [8]. In this past work, hierarchical node-nested dense and sparse tensor product quadratures are used to calculate moment statistics integrals. In the present work, a framework has been developed that exploits the hierarchical structure of these quadratures in order to simplify the calculation of an estimate of the quadrature error needed in error bound formulas. When signed estimates of realization error are available, this signed error may also be used to estimate output quantity of interest probability densities as a means to assess the impact of realization error on these density estimates. Numerical results are presented for CFD problems with uncertainty to demonstrate the capabilities of this framework.

Systematic and random variations in digital Thematic Mapper data

NASA Technical Reports Server (NTRS)

Duggin, M. J. (Principal Investigator); Sakhavat, H.

1985-01-01

Radiance recorded by any remote sensing instrument will contain noise which will consist of both systematic and random variations. Systematic variations may be due to sun-target-sensor geometry, atmospheric conditions, and the interaction of the spectral characteristics of the sensor with those of upwelling radiance. Random variations in the data may be caused by variations in the nature and in the heterogeneity of the ground cover, by variations in atmospheric transmission, and by the interaction of these variations with the sensing device. It is important to be aware of the extent of random and systematic errors in recorded radiance data across ostensibly uniform ground areas in order to assess the impact on quantative image analysis procedures for both the single date and the multidate cases. It is the intention here to examine the systematic and the random variations in digital radiance data recorded in each band by the thematic mapper over crop areas which are ostensibly uniform and which are free from visible cloud.

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

Lee, Y; Fullerton, G; Goins, B

Purpose: In our previous study a preclinical multi-modality quality assurance (QA) phantom that contains five tumor-simulating test objects with 2, 4, 7, 10 and 14 mm diameters was developed for accurate tumor size measurement by researchers during cancer drug development and testing. This study analyzed the errors during tumor volume measurement from preclinical magnetic resonance (MR), micro-computed tomography (micro- CT) and ultrasound (US) images acquired in a rodent tumor model using the preclinical multi-modality QA phantom. Methods: Using preclinical 7-Tesla MR, US and micro-CT scanners, images were acquired of subcutaneous SCC4 tumor xenografts in nude rats (3–4 rats per group;more » 5 groups) along with the QA phantom using the same imaging protocols. After tumors were excised, in-air micro-CT imaging was performed to determine reference tumor volume. Volumes measured for the rat tumors and phantom test objects were calculated using formula V = (π/6)*a*b*c where a, b and c are the maximum diameters in three perpendicular dimensions determined by the three imaging modalities. Then linear regression analysis was performed to compare image-based tumor volumes with the reference tumor volume and known test object volume for the rats and the phantom respectively. Results: The slopes of regression lines for in-vivo tumor volumes measured by three imaging modalities were 1.021, 1.101 and 0.862 for MRI, micro-CT and US respectively. For phantom, the slopes were 0.9485, 0.9971 and 0.9734 for MRI, micro-CT and US respectively. Conclusion: For both animal and phantom studies, random and systematic errors were observed. Random errors were observer-dependent and systematic errors were mainly due to selected imaging protocols and/or measurement method. In the animal study, there were additional systematic errors attributed to ellipsoidal assumption for tumor shape. The systematic errors measured using the QA phantom need to be taken into account to reduce measurement errors during the animal study.« less

Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling

NASA Astrophysics Data System (ADS)

Chen, Huili; Liang, Qiuhua; Liu, Yong; Xie, Shuguang

2018-04-01

Digital Elevation Model (DEM) is one of the most important controlling factors determining the simulation accuracy of hydraulic models. However, the currently available global topographic data is confronted with limitations for application in 2-D hydraulic modeling, mainly due to the existence of vegetation bias, random errors and insufficient spatial resolution. A hydraulic correction method (HCM) for the SRTM DEM is proposed in this study to improve modeling accuracy. Firstly, we employ the global vegetation corrected DEM (i.e. Bare-Earth DEM), developed from the SRTM DEM to include both vegetation height and SRTM vegetation signal. Then, a newly released DEM, removing both vegetation bias and random errors (i.e. Multi-Error Removed DEM), is employed to overcome the limitation of height errors. Last, an approach to correct the Multi-Error Removed DEM is presented to account for the insufficiency of spatial resolution, ensuring flow connectivity of the river networks. The approach involves: (a) extracting river networks from the Multi-Error Removed DEM using an automated algorithm in ArcGIS; (b) correcting the location and layout of extracted streams with the aid of Google Earth platform and Remote Sensing imagery; and (c) removing the positive biases of the raised segment in the river networks based on bed slope to generate the hydraulically corrected DEM. The proposed HCM utilizes easily available data and tools to improve the flow connectivity of river networks without manual adjustment. To demonstrate the advantages of HCM, an extreme flood event in Huifa River Basin (China) is simulated on the original DEM, Bare-Earth DEM, Multi-Error removed DEM, and hydraulically corrected DEM using an integrated hydrologic-hydraulic model. A comparative analysis is subsequently performed to assess the simulation accuracy and performance of four different DEMs and favorable results have been obtained on the corrected DEM.

Patterns of technical error among surgical malpractice claims: an analysis of strategies to prevent injury to surgical patients.

PubMed

Regenbogen, Scott E; Greenberg, Caprice C; Studdert, David M; Lipsitz, Stuart R; Zinner, Michael J; Gawande, Atul A

2007-11-01

To identify the most prevalent patterns of technical errors in surgery, and evaluate commonly recommended interventions in light of these patterns. The majority of surgical adverse events involve technical errors, but little is known about the nature and causes of these events. We examined characteristics of technical errors and common contributing factors among closed surgical malpractice claims. Surgeon reviewers analyzed 444 randomly sampled surgical malpractice claims from four liability insurers. Among 258 claims in which injuries due to error were detected, 52% (n = 133) involved technical errors. These technical errors were further analyzed with a structured review instrument designed by qualitative content analysis. Forty-nine percent of the technical errors caused permanent disability; an additional 16% resulted in death. Two-thirds (65%) of the technical errors were linked to manual error, 9% to errors in judgment, and 26% to both manual and judgment error. A minority of technical errors involved advanced procedures requiring special training ("index operations"; 16%), surgeons inexperienced with the task (14%), or poorly supervised residents (9%). The majority involved experienced surgeons (73%), and occurred in routine, rather than index, operations (84%). Patient-related complexities-including emergencies, difficult or unexpected anatomy, and previous surgery-contributed to 61% of technical errors, and technology or systems failures contributed to 21%. Most technical errors occur in routine operations with experienced surgeons, under conditions of increased patient complexity or systems failure. Commonly recommended interventions, including restricting high-complexity operations to experienced surgeons, additional training for inexperienced surgeons, and stricter supervision of trainees, are likely to address only a minority of technical errors. Surgical safety research should instead focus on improving decision-making and performance in routine operations for complex patients and circumstances.

Using Audit Information to Adjust Parameter Estimates for Data Errors in Clinical Trials

PubMed Central

Shepherd, Bryan E.; Shaw, Pamela A.; Dodd, Lori E.

2013-01-01

Background Audits are often performed to assess the quality of clinical trial data, but beyond detecting fraud or sloppiness, the audit data is generally ignored. In earlier work using data from a non-randomized study, Shepherd and Yu (2011) developed statistical methods to incorporate audit results into study estimates, and demonstrated that audit data could be used to eliminate bias. Purpose In this manuscript we examine the usefulness of audit-based error-correction methods in clinical trial settings where a continuous outcome is of primary interest. Methods We demonstrate the bias of multiple linear regression estimates in general settings with an outcome that may have errors and a set of covariates for which some may have errors and others, including treatment assignment, are recorded correctly for all subjects. We study this bias under different assumptions including independence between treatment assignment, covariates, and data errors (conceivable in a double-blinded randomized trial) and independence between treatment assignment and covariates but not data errors (possible in an unblinded randomized trial). We review moment-based estimators to incorporate the audit data and propose new multiple imputation estimators. The performance of estimators is studied in simulations. Results When treatment is randomized and unrelated to data errors, estimates of the treatment effect using the original error-prone data (i.e., ignoring the audit results) are unbiased. In this setting, both moment and multiple imputation estimators incorporating audit data are more variable than standard analyses using the original data. In contrast, in settings where treatment is randomized but correlated with data errors and in settings where treatment is not randomized, standard treatment effect estimates will be biased. And in all settings, parameter estimates for the original, error-prone covariates will be biased. Treatment and covariate effect estimates can be corrected by incorporating audit data using either the multiple imputation or moment-based approaches. Bias, precision, and coverage of confidence intervals improve as the audit size increases. Limitations The extent of bias and the performance of methods depend on the extent and nature of the error as well as the size of the audit. This work only considers methods for the linear model. Settings much different than those considered here need further study. Conclusions In randomized trials with continuous outcomes and treatment assignment independent of data errors, standard analyses of treatment effects will be unbiased and are recommended. However, if treatment assignment is correlated with data errors or other covariates, naive analyses may be biased. In these settings, and when covariate effects are of interest, approaches for incorporating audit results should be considered. PMID:22848072

HyDEn: A Hybrid Steganocryptographic Approach for Data Encryption Using Randomized Error-Correcting DNA Codes

PubMed Central

Regoui, Chaouki; Durand, Guillaume; Belliveau, Luc; Léger, Serge

2013-01-01

This paper presents a novel hybrid DNA encryption (HyDEn) approach that uses randomized assignments of unique error-correcting DNA Hamming code words for single characters in the extended ASCII set. HyDEn relies on custom-built quaternary codes and a private key used in the randomized assignment of code words and the cyclic permutations applied on the encoded message. Along with its ability to detect and correct errors, HyDEn equals or outperforms existing cryptographic methods and represents a promising in silico DNA steganographic approach. PMID:23984392

Estimation of Rice Crop Yields Using Random Forests in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. F.; Lin, H. S.; Nguyen, S. T.; Chen, C. R.

2017-12-01

Rice is globally one of the most important food crops, directly feeding more people than any other crops. Rice is not only the most important commodity, but also plays a critical role in the economy of Taiwan because it provides employment and income for large rural populations. The rice harvested area and production are thus monitored yearly due to the government's initiatives. Agronomic planners need such information for more precise assessment of food production to tackle issues of national food security and policymaking. This study aimed to develop a machine-learning approach using physical parameters to estimate rice crop yields in Taiwan. We processed the data for 2014 cropping seasons, following three main steps: (1) data pre-processing to construct input layers, including soil types and weather parameters (e.g., maxima and minima air temperature, precipitation, and solar radiation) obtained from meteorological stations across the country; (2) crop yield estimation using the random forests owing to its merits as it can process thousands of variables, estimate missing data, maintain the accuracy level when a large proportion of the data is missing, overcome most of over-fitting problems, and run fast and efficiently when handling large datasets; and (3) error verification. To execute the model, we separated the datasets into two groups of pixels: group-1 (70% of pixels) for training the model and group-2 (30% of pixels) for testing the model. Once the model is trained to produce small and stable out-of-bag error (i.e., the mean squared error between predicted and actual values), it can be used for estimating rice yields of cropping seasons. The results obtained from the random forests-based regression were compared with the actual yield statistics indicated the values of root mean square error (RMSE) and mean absolute error (MAE) achieved for the first rice crop were respectively 6.2% and 2.7%, while those for the second rice crop were 5.3% and 2.9%, respectively. Although there are several uncertainties attributed to the data quality of input layers, our study demonstrates the promising application of random forests for estimating rice crop yields at the national level in Taiwan. This approach could be transferable to other regions of the world for improving large-scale estimation of rice crop yields.

Systematic bias in genomic classification due to contaminating non-neoplastic tissue in breast tumor samples.

PubMed

Elloumi, Fathi; Hu, Zhiyuan; Li, Yan; Parker, Joel S; Gulley, Margaret L; Amos, Keith D; Troester, Melissa A

2011-06-30

Genomic tests are available to predict breast cancer recurrence and to guide clinical decision making. These predictors provide recurrence risk scores along with a measure of uncertainty, usually a confidence interval. The confidence interval conveys random error and not systematic bias. Standard tumor sampling methods make this problematic, as it is common to have a substantial proportion (typically 30-50%) of a tumor sample comprised of histologically benign tissue. This "normal" tissue could represent a source of non-random error or systematic bias in genomic classification. To assess the performance characteristics of genomic classification to systematic error from normal contamination, we collected 55 tumor samples and paired tumor-adjacent normal tissue. Using genomic signatures from the tumor and paired normal, we evaluated how increasing normal contamination altered recurrence risk scores for various genomic predictors. Simulations of normal tissue contamination caused misclassification of tumors in all predictors evaluated, but different breast cancer predictors showed different types of vulnerability to normal tissue bias. While two predictors had unpredictable direction of bias (either higher or lower risk of relapse resulted from normal contamination), one signature showed predictable direction of normal tissue effects. Due to this predictable direction of effect, this signature (the PAM50) was adjusted for normal tissue contamination and these corrections improved sensitivity and negative predictive value. For all three assays quality control standards and/or appropriate bias adjustment strategies can be used to improve assay reliability. Normal tissue sampled concurrently with tumor is an important source of bias in breast genomic predictors. All genomic predictors show some sensitivity to normal tissue contamination and ideal strategies for mitigating this bias vary depending upon the particular genes and computational methods used in the predictor.

Random Error in Judgment: The Contribution of Encoding and Retrieval Processes

ERIC Educational Resources Information Center

Pleskac, Timothy J.; Dougherty, Michael R.; Rivadeneira, A. Walkyria; Wallsten, Thomas S.

2009-01-01

Theories of confidence judgments have embraced the role random error plays in influencing responses. An important next step is to identify the source(s) of these random effects. To do so, we used the stochastic judgment model (SJM) to distinguish the contribution of encoding and retrieval processes. In particular, we investigated whether dividing…

Evaluation of domain randomness in periodically poled lithium niobate by diffraction noise measurement.

PubMed

Dwivedi, Prashant Povel; Choi, Hee Joo; Kim, Byoung Joo; Cha, Myoungsik

2013-12-16

Random duty-cycle errors (RDE) in ferroelectric quasi-phase-matching (QPM) devices not only affect the frequency conversion efficiency, but also generate non-phase-matched parasitic noise that can be detrimental to some applications. We demonstrate an accurate but simple method for measuring the RDE in periodically poled lithium niobate. Due to the equivalence between the undepleted harmonic generation spectrum and the diffraction pattern from the QPM grating, we employed linear diffraction measurement which is much simpler than tunable harmonic generation experiments [J. S. Pelc, et al., Opt. Lett.36, 864-866 (2011)]. As a result, we could relate the RDE for the QPM device to the relative noise intensity between the diffraction orders.

Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Andres, R.; Houghton, R.; Stocker, B. D.; Wanninkhof, R.; Anderegg, W.; Cooper, L. A.; DeGrandpre, M.; Tans, P. P.; Miller, J. B.; Alden, C.; White, J. W. C.

2015-04-01

Over the last 5 decades monitoring systems have been developed to detect changes in the accumulation of carbon (C) in the atmosphere and ocean; however, our ability to detect changes in the behavior of the global C cycle is still hindered by measurement and estimate errors. Here we present a rigorous and flexible framework for assessing the temporal and spatial components of estimate errors and their impact on uncertainty in net C uptake by the biosphere. We present a novel approach for incorporating temporally correlated random error into the error structure of emission estimates. Based on this approach, we conclude that the 2σ uncertainties of the atmospheric growth rate have decreased from 1.2 Pg C yr-1 in the 1960s to 0.3 Pg C yr-1 in the 2000s due to an expansion of the atmospheric observation network. The 2σ uncertainties in fossil fuel emissions have increased from 0.3 Pg C yr-1 in the 1960s to almost 1.0 Pg C yr-1 during the 2000s due to differences in national reporting errors and differences in energy inventories. Lastly, while land use emissions have remained fairly constant, their errors still remain high and thus their global C uptake uncertainty is not trivial. Currently, the absolute errors in fossil fuel emissions rival the total emissions from land use, highlighting the extent to which fossil fuels dominate the global C budget. Because errors in the atmospheric growth rate have decreased faster than errors in total emissions have increased, a ~20% reduction in the overall uncertainty of net C global uptake has occurred. Given all the major sources of error in the global C budget that we could identify, we are 93% confident that terrestrial C uptake has increased and 97% confident that ocean C uptake has increased over the last 5 decades. Thus, it is clear that arguably one of the most vital ecosystem services currently provided by the biosphere is the continued removal of approximately half of atmospheric CO2 emissions from the atmosphere, although there are certain environmental costs associated with this service, such as the acidification of ocean waters.

Automatic liver segmentation on Computed Tomography using random walkers for treatment planning

PubMed Central

Moghbel, Mehrdad; Mashohor, Syamsiah; Mahmud, Rozi; Saripan, M. Iqbal Bin

2016-01-01

Segmentation of the liver from Computed Tomography (CT) volumes plays an important role during the choice of treatment strategies for liver diseases. Despite lots of attention, liver segmentation remains a challenging task due to the lack of visible edges on most boundaries of the liver coupled with high variability of both intensity patterns and anatomical appearances with all these difficulties becoming more prominent in pathological livers. To achieve a more accurate segmentation, a random walker based framework is proposed that can segment contrast-enhanced livers CT images with great accuracy and speed. Based on the location of the right lung lobe, the liver dome is automatically detected thus eliminating the need for manual initialization. The computational requirements are further minimized utilizing rib-caged area segmentation, the liver is then extracted by utilizing random walker method. The proposed method was able to achieve one of the highest accuracies reported in the literature against a mixed healthy and pathological liver dataset compared to other segmentation methods with an overlap error of 4.47 % and dice similarity coefficient of 0.94 while it showed exceptional accuracy on segmenting the pathological livers with an overlap error of 5.95 % and dice similarity coefficient of 0.91. PMID:28096782

Errors of five-day mean surface wind and temperature conditions due to inadequate sampling

NASA Technical Reports Server (NTRS)

Legler, David M.

1991-01-01

Surface meteorological reports of wind components, wind speed, air temperature, and sea-surface temperature from buoys located in equatorial and midlatitude regions are used in a simulation of random sampling to determine errors of the calculated means due to inadequate sampling. Subsampling the data with several different sample sizes leads to estimates of the accuracy of the subsampled means. The number N of random observations needed to compute mean winds with chosen accuracies of 0.5 (N sub 0.5) and 1.0 (N sub 1,0) m/s and mean air and sea surface temperatures with chosen accuracies of 0.1 (N sub 0.1) and 0.2 (N sub 0.2) C were calculated for each 5-day and 30-day period in the buoy datasets. Mean values of N for the various accuracies and datasets are given. A second-order polynomial relation is established between N and the variability of the data record. This relationship demonstrates that for the same accuracy, N increases as the variability of the data record increases. The relationship is also independent of the data source. Volunteer-observing ship data do not satisfy the recommended minimum number of observations for obtaining 0.5 m/s and 0.2 C accuracy for most locations. The effect of having remotely sensed data is discussed.

Calculating radiotherapy margins based on Bayesian modelling of patient specific random errors

NASA Astrophysics Data System (ADS)

Herschtal, A.; te Marvelde, L.; Mengersen, K.; Hosseinifard, Z.; Foroudi, F.; Devereux, T.; Pham, D.; Ball, D.; Greer, P. B.; Pichler, P.; Eade, T.; Kneebone, A.; Bell, L.; Caine, H.; Hindson, B.; Kron, T.

2015-02-01

Collected real-life clinical target volume (CTV) displacement data show that some patients undergoing external beam radiotherapy (EBRT) demonstrate significantly more fraction-to-fraction variability in their displacement (‘random error’) than others. This contrasts with the common assumption made by historical recipes for margin estimation for EBRT, that the random error is constant across patients. In this work we present statistical models of CTV displacements in which random errors are characterised by an inverse gamma (IG) distribution in order to assess the impact of random error variability on CTV-to-PTV margin widths, for eight real world patient cohorts from four institutions, and for different sites of malignancy. We considered a variety of clinical treatment requirements and penumbral widths. The eight cohorts consisted of a total of 874 patients and 27 391 treatment sessions. Compared to a traditional margin recipe that assumes constant random errors across patients, for a typical 4 mm penumbral width, the IG based margin model mandates that in order to satisfy the common clinical requirement that 90% of patients receive at least 95% of prescribed RT dose to the entire CTV, margins be increased by a median of 10% (range over the eight cohorts -19% to +35%). This substantially reduces the proportion of patients for whom margins are too small to satisfy clinical requirements.

[Monitoring medication errors in personalised dispensing using the Sentinel Surveillance System method].

PubMed

Pérez-Cebrián, M; Font-Noguera, I; Doménech-Moral, L; Bosó-Ribelles, V; Romero-Boyero, P; Poveda-Andrés, J L

2011-01-01

To assess the efficacy of a new quality control strategy based on daily randomised sampling and monitoring a Sentinel Surveillance System (SSS) medication cart, in order to identify medication errors and their origin at different levels of the process. Prospective quality control study with one year follow-up. A SSS medication cart was randomly selected once a week and double-checked before dispensing medication. Medication errors were recorded before it was taken to the relevant hospital ward. Information concerning complaints after receiving medication and 24-hour monitoring were also noted. Type and origin error data were assessed by a Unit Dose Quality Control Group, which proposed relevant improvement measures. Thirty-four SSS carts were assessed, including 5130 medication lines and 9952 dispensed doses, corresponding to 753 patients. Ninety erroneous lines (1.8%) and 142 mistaken doses (1.4%) were identified at the Pharmacy Department. The most frequent error was dose duplication (38%) and its main cause inappropriate management and forgetfulness (69%). Fifty medication complaints (6.6% of patients) were mainly due to new treatment at admission (52%), and 41 (0.8% of all medication lines), did not completely match the prescription (0.6% lines) as recorded by the Pharmacy Department. Thirty-seven (4.9% of patients) medication complaints due to changes at admission and 32 matching errors (0.6% medication lines) were recorded. The main cause also was inappropriate management and forgetfulness (24%). The simultaneous recording of incidences due to complaints and new medication coincided in 33.3%. In addition, 433 (4.3%) of dispensed doses were returned to the Pharmacy Department. After the Unit Dose Quality Control Group conducted their feedback analysis, 64 improvement measures for Pharmacy Department nurses, 37 for pharmacists, and 24 for the hospital ward were introduced. The SSS programme has proven to be useful as a quality control strategy to identify Unit Dose Distribution System errors at initial, intermediate and final stages of the process, improving the involvement of the Pharmacy Department and ward nurses. Copyright © 2009 SEFH. Published by Elsevier Espana. All rights reserved.

Particle Tracking on the BNL Relativistic Heavy Ion Collider

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

Dell, G. F.

1986-08-07

Tracking studies including the effects of random multipole errors as well as the effects of random and systematic multipole errors have been made for RHIC. Initial results for operating at an off diagonal working point are discussed.

An approach to develop an algorithm to detect the climbing height in radial-axial ring rolling

NASA Astrophysics Data System (ADS)

Husmann, Simon; Hohmann, Magnus; Kuhlenkötter, Bernd

2017-10-01

Radial-axial ring rolling is the mainly used forming process to produce seamless rings, which are applied in miscellaneous industries like the energy sector, the aerospace technology or in the automotive industry. Due to the simultaneously forming in two opposite rolling gaps and the fact that ring rolling is a mass forming process, different errors could occur during the rolling process. Ring climbing is one of the most occurring process errors leading to a distortion of the ring's cross section and a deformation of the rings geometry. The conventional sensors of a radial-axial rolling machine could not detect this error. Therefore, it is a common strategy to roll a slightly bigger ring, so that random occurring process errors could be reduce afterwards by removing the additional material. The LPS installed an image processing system to the radial rolling gap of their ring rolling machine to enable the recognition and measurement of climbing rings and by this, to reduce the additional material. This paper presents the algorithm which enables the image processing system to detect the error of a climbing ring and ensures comparable reliable results for the measurement of the climbing height of the rings.

Discovery of error-tolerant biclusters from noisy gene expression data.

PubMed

Gupta, Rohit; Rao, Navneet; Kumar, Vipin

2011-11-24

An important analysis performed on microarray gene-expression data is to discover biclusters, which denote groups of genes that are coherently expressed for a subset of conditions. Various biclustering algorithms have been proposed to find different types of biclusters from these real-valued gene-expression data sets. However, these algorithms suffer from several limitations such as inability to explicitly handle errors/noise in the data; difficulty in discovering small bicliusters due to their top-down approach; inability of some of the approaches to find overlapping biclusters, which is crucial as many genes participate in multiple biological processes. Association pattern mining also produce biclusters as their result and can naturally address some of these limitations. However, traditional association mining only finds exact biclusters, which limits its applicability in real-life data sets where the biclusters may be fragmented due to random noise/errors. Moreover, as they only work with binary or boolean attributes, their application on gene-expression data require transforming real-valued attributes to binary attributes, which often results in loss of information. Many past approaches have tried to address the issue of noise and handling real-valued attributes independently but there is no systematic approach that addresses both of these issues together. In this paper, we first propose a novel error-tolerant biclustering model, 'ET-bicluster', and then propose a bottom-up heuristic-based mining algorithm to sequentially discover error-tolerant biclusters directly from real-valued gene-expression data. The efficacy of our proposed approach is illustrated by comparing it with a recent approach RAP in the context of two biological problems: discovery of functional modules and discovery of biomarkers. For the first problem, two real-valued S.Cerevisiae microarray gene-expression data sets are used to demonstrate that the biclusters obtained from ET-bicluster approach not only recover larger set of genes as compared to those obtained from RAP approach but also have higher functional coherence as evaluated using the GO-based functional enrichment analysis. The statistical significance of the discovered error-tolerant biclusters as estimated by using two randomization tests, reveal that they are indeed biologically meaningful and statistically significant. For the second problem of biomarker discovery, we used four real-valued Breast Cancer microarray gene-expression data sets and evaluate the biomarkers obtained using MSigDB gene sets. The results obtained for both the problems: functional module discovery and biomarkers discovery, clearly signifies the usefulness of the proposed ET-bicluster approach and illustrate the importance of explicitly incorporating noise/errors in discovering coherent groups of genes from gene-expression data.

Simulation of wave propagation in three-dimensional random media

NASA Technical Reports Server (NTRS)

Coles, William A.; Filice, J. P.; Frehlich, R. G.; Yadlowsky, M.

1993-01-01

Quantitative error analysis for simulation of wave propagation in three dimensional random media assuming narrow angular scattering are presented for the plane wave and spherical wave geometry. This includes the errors resulting from finite grid size, finite simulation dimensions, and the separation of the two-dimensional screens along the propagation direction. Simple error scalings are determined for power-law spectra of the random refractive index of the media. The effects of a finite inner scale are also considered. The spatial spectra of the intensity errors are calculated and compared to the spatial spectra of intensity. The numerical requirements for a simulation of given accuracy are determined for realizations of the field. The numerical requirements for accurate estimation of higher moments of the field are less stringent.

Effects of Cloud on Goddard Lidar Observatory for Wind (GLOW) Performance and Analysis of Associated Errors

NASA Astrophysics Data System (ADS)

Bacha, Tulu

The Goddard Lidar Observatory for Wind (GLOW), a mobile direct detection Doppler LIDAR based on molecular backscattering for measurement of wind in the troposphere and lower stratosphere region of atmosphere is operated and its errors characterized. It was operated at Howard University Beltsville Center for Climate Observation System (BCCOS) side by side with other operating instruments: the NASA/Langely Research Center Validation Lidar (VALIDAR), Leosphere WLS70, and other standard wind sensing instruments. The performance of Goddard Lidar Observatory for Wind (GLOW) is presented for various optical thicknesses of cloud conditions. It was also compared to VALIDAR under various conditions. These conditions include clear and cloudy sky regions. The performance degradation due to the presence of cirrus clouds is quantified by comparing the wind speed error to cloud thickness. The cloud thickness is quantified in terms of aerosol backscatter ratio (ASR) and cloud optical depth (COD). ASR and COD are determined from Howard University Raman Lidar (HURL) operating at the same station as GLOW. The wind speed error of GLOW was correlated with COD and aerosol backscatter ratio (ASR) which are determined from HURL data. The correlation related in a weak linear relationship. Finally, the wind speed measurements of GLOW were corrected using the quantitative relation from the correlation relations. Using ASR reduced the GLOW wind error from 19% to 8% in a thin cirrus cloud and from 58% to 28% in a relatively thick cloud. After correcting for cloud induced error, the remaining error is due to shot noise and atmospheric variability. Shot-noise error is the statistical random error of backscattered photons detected by photon multiplier tube (PMT) can only be minimized by averaging large number of data recorded. The atmospheric backscatter measured by GLOW along its line-of-sight direction is also used to analyze error due to atmospheric variability within the volume of measurement. GLOW scans in five different directions (vertical and at elevation angles of 45° in north, south, east, and west) to generate wind profiles. The non-uniformity of the atmosphere in all scanning directions is a factor contributing to the measurement error of GLOW. The atmospheric variability in the scanning region leads to difference in the intensity of backscattered signals for scanning directions. Taking the ratio of the north (east) to south (west) and comparing the statistical differences lead to a weak linear relation between atmospheric variability and line-of-sights wind speed differences. This relation was used to make correction which reduced by about 50%.

Regionalized PM2.5 Community Multiscale Air Quality model performance evaluation across a continuous spatiotemporal domain.

PubMed

Reyes, Jeanette M; Xu, Yadong; Vizuete, William; Serre, Marc L

2017-01-01

The regulatory Community Multiscale Air Quality (CMAQ) model is a means to understanding the sources, concentrations and regulatory attainment of air pollutants within a model's domain. Substantial resources are allocated to the evaluation of model performance. The Regionalized Air quality Model Performance (RAMP) method introduced here explores novel ways of visualizing and evaluating CMAQ model performance and errors for daily Particulate Matter ≤ 2.5 micrometers (PM2.5) concentrations across the continental United States. The RAMP method performs a non-homogenous, non-linear, non-homoscedastic model performance evaluation at each CMAQ grid. This work demonstrates that CMAQ model performance, for a well-documented 2001 regulatory episode, is non-homogeneous across space/time. The RAMP correction of systematic errors outperforms other model evaluation methods as demonstrated by a 22.1% reduction in Mean Square Error compared to a constant domain wide correction. The RAMP method is able to accurately reproduce simulated performance with a correlation of r = 76.1%. Most of the error coming from CMAQ is random error with only a minority of error being systematic. Areas of high systematic error are collocated with areas of high random error, implying both error types originate from similar sources. Therefore, addressing underlying causes of systematic error will have the added benefit of also addressing underlying causes of random error.

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

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

Chowdhary, Kenny; Najm, Habib N.

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Bayesian estimation of Karhunen–Loève expansions; A random subspace approach

DOE PAGES

Chowdhary, Kenny; Najm, Habib N.

2016-04-13

One of the most widely-used statistical procedures for dimensionality reduction of high dimensional random fields is Principal Component Analysis (PCA), which is based on the Karhunen-Lo eve expansion (KLE) of a stochastic process with finite variance. The KLE is analogous to a Fourier series expansion for a random process, where the goal is to find an orthogonal transformation for the data such that the projection of the data onto this orthogonal subspace is optimal in the L 2 sense, i.e, which minimizes the mean square error. In practice, this orthogonal transformation is determined by performing an SVD (Singular Value Decomposition)more » on the sample covariance matrix or on the data matrix itself. Sampling error is typically ignored when quantifying the principal components, or, equivalently, basis functions of the KLE. Furthermore, it is exacerbated when the sample size is much smaller than the dimension of the random field. In this paper, we introduce a Bayesian KLE procedure, allowing one to obtain a probabilistic model on the principal components, which can account for inaccuracies due to limited sample size. The probabilistic model is built via Bayesian inference, from which the posterior becomes the matrix Bingham density over the space of orthonormal matrices. We use a modified Gibbs sampling procedure to sample on this space and then build a probabilistic Karhunen-Lo eve expansions over random subspaces to obtain a set of low-dimensional surrogates of the stochastic process. We illustrate this probabilistic procedure with a finite dimensional stochastic process inspired by Brownian motion.« less

Incidence of speech recognition errors in the emergency department.

PubMed

Goss, Foster R; Zhou, Li; Weiner, Scott G

2016-09-01

Physician use of computerized speech recognition (SR) technology has risen in recent years due to its ease of use and efficiency at the point of care. However, error rates between 10 and 23% have been observed, raising concern about the number of errors being entered into the permanent medical record, their impact on quality of care and medical liability that may arise. Our aim was to determine the incidence and types of SR errors introduced by this technology in the emergency department (ED). Level 1 emergency department with 42,000 visits/year in a tertiary academic teaching hospital. A random sample of 100 notes dictated by attending emergency physicians (EPs) using SR software was collected from the ED electronic health record between January and June 2012. Two board-certified EPs annotated the notes and conducted error analysis independently. An existing classification schema was adopted to classify errors into eight errors types. Critical errors deemed to potentially impact patient care were identified. There were 128 errors in total or 1.3 errors per note, and 14.8% (n=19) errors were judged to be critical. 71% of notes contained errors, and 15% contained one or more critical errors. Annunciation errors were the highest at 53.9% (n=69), followed by deletions at 18.0% (n=23) and added words at 11.7% (n=15). Nonsense errors, homonyms and spelling errors were present in 10.9% (n=14), 4.7% (n=6), and 0.8% (n=1) of notes, respectively. There were no suffix or dictionary errors. Inter-annotator agreement was 97.8%. This is the first estimate at classifying speech recognition errors in dictated emergency department notes. Speech recognition errors occur commonly with annunciation errors being the most frequent. Error rates were comparable if not lower than previous studies. 15% of errors were deemed critical, potentially leading to miscommunication that could affect patient care. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

New GRACE-Derived Storage Change Estimates Using Empirical Mode Extraction

NASA Astrophysics Data System (ADS)

Aierken, A.; Lee, H.; Yu, H.; Ate, P.; Hossain, F.; Basnayake, S. B.; Jayasinghe, S.; Saah, D. S.; Shum, C. K.

2017-12-01

Estimated mass change from GRACE spherical harmonic solutions have north/south stripes and east/west banded errors due to random noise and modeling errors. Low pass filters like decorrelation and Gaussian smoothing are typically applied to reduce noise and errors. However, these filters introduce leakage errors that need to be addressed. GRACE mascon estimates (JPL and CSR mascon solutions) do not need decorrelation or Gaussian smoothing and offer larger signal magnitudes compared to the GRACE spherical harmonics (SH) filtered results. However, a recent study [Chen et al., JGR, 2017] demonstrated that both JPL and CSR mascon solutions also have leakage errors. We developed a new postprocessing method based on empirical mode decomposition to estimate mass change from GRACE SH solutions without decorrelation and Gaussian smoothing, the two main sources of leakage errors. We found that, without any post processing, the noise and errors in spherical harmonic solutions introduced very clear high frequency components in the spatial domain. By removing these high frequency components and reserve the overall pattern of the signal, we obtained better mass estimates with minimum leakage errors. The new global mass change estimates captured all the signals observed by GRACE without the stripe errors. Results were compared with traditional methods over the Tonle Sap Basin in Cambodia, Northwestern India, Central Valley in California, and the Caspian Sea. Our results provide larger signal magnitudes which are in good agreement with the leakage corrected (forward modeled) SH results.

Error Distribution Evaluation of the Third Vanishing Point Based on Random Statistical Simulation

NASA Astrophysics Data System (ADS)

Li, C.

2012-07-01

POS, integrated by GPS / INS (Inertial Navigation Systems), has allowed rapid and accurate determination of position and attitude of remote sensing equipment for MMS (Mobile Mapping Systems). However, not only does INS have system error, but also it is very expensive. Therefore, in this paper error distributions of vanishing points are studied and tested in order to substitute INS for MMS in some special land-based scene, such as ground façade where usually only two vanishing points can be detected. Thus, the traditional calibration approach based on three orthogonal vanishing points is being challenged. In this article, firstly, the line clusters, which parallel to each others in object space and correspond to the vanishing points, are detected based on RANSAC (Random Sample Consensus) and parallelism geometric constraint. Secondly, condition adjustment with parameters is utilized to estimate nonlinear error equations of two vanishing points (VX, VY). How to set initial weights for the adjustment solution of single image vanishing points is presented. Solving vanishing points and estimating their error distributions base on iteration method with variable weights, co-factor matrix and error ellipse theory. Thirdly, under the condition of known error ellipses of two vanishing points (VX, VY) and on the basis of the triangle geometric relationship of three vanishing points, the error distribution of the third vanishing point (VZ) is calculated and evaluated by random statistical simulation with ignoring camera distortion. Moreover, Monte Carlo methods utilized for random statistical estimation are presented. Finally, experimental results of vanishing points coordinate and their error distributions are shown and analyzed.

Error free physically unclonable function with programmed resistive random access memory using reliable resistance states by specific identification-generation method

NASA Astrophysics Data System (ADS)

Tseng, Po-Hao; Hsu, Kai-Chieh; Lin, Yu-Yu; Lee, Feng-Min; Lee, Ming-Hsiu; Lung, Hsiang-Lan; Hsieh, Kuang-Yeu; Chung Wang, Keh; Lu, Chih-Yuan

2018-04-01

A high performance physically unclonable function (PUF) implemented with WO3 resistive random access memory (ReRAM) is presented in this paper. This robust ReRAM-PUF can eliminated bit flipping problem at very high temperature (up to 250 °C) due to plentiful read margin by using initial resistance state and set resistance state. It is also promised 10 years retention at the temperature range of 210 °C. These two stable resistance states enable stable operation at automotive environments from -40 to 125 °C without need of temperature compensation circuit. The high uniqueness of PUF can be achieved by implementing a proposed identification (ID)-generation method. Optimized forming condition can move 50% of the cells to low resistance state and the remaining 50% remain at initial high resistance state. The inter- and intra-PUF evaluations with unlimited separation of hamming distance (HD) are successfully demonstrated even under the corner condition. The number of reproduction was measured to exceed 107 times with 0% bit error rate (BER) at read voltage from 0.4 to 0.7 V.

Accuracy of Robotic Radiosurgical Liver Treatment Throughout the Respiratory Cycle

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

Winter, Jeff D.; Wong, Raimond; Swaminath, Anand

Purpose: To quantify random uncertainties in robotic radiosurgical treatment of liver lesions with real-time respiratory motion management. Methods and Materials: We conducted a retrospective analysis of 27 liver cancer patients treated with robotic radiosurgery over 118 fractions. The robotic radiosurgical system uses orthogonal x-ray images to determine internal target position and correlates this position with an external surrogate to provide robotic corrections of linear accelerator positioning. Verification and update of this internal–external correlation model was achieved using periodic x-ray images collected throughout treatment. To quantify random uncertainties in targeting, we analyzed logged tracking information and isolated x-ray images collected immediately beforemore » beam delivery. For translational correlation errors, we quantified the difference between correlation model–estimated target position and actual position determined by periodic x-ray imaging. To quantify prediction errors, we computed the mean absolute difference between the predicted coordinates and actual modeled position calculated 115 milliseconds later. We estimated overall random uncertainty by quadratically summing correlation, prediction, and end-to-end targeting errors. We also investigated relationships between tracking errors and motion amplitude using linear regression. Results: The 95th percentile absolute correlation errors in each direction were 2.1 mm left–right, 1.8 mm anterior–posterior, 3.3 mm cranio–caudal, and 3.9 mm 3-dimensional radial, whereas 95th percentile absolute radial prediction errors were 0.5 mm. Overall 95th percentile random uncertainty was 4 mm in the radial direction. Prediction errors were strongly correlated with modeled target amplitude (r=0.53-0.66, P<.001), whereas only weak correlations existed for correlation errors. Conclusions: Study results demonstrate that model correlation errors are the primary random source of uncertainty in Cyberknife liver treatment and, unlike prediction errors, are not strongly correlated with target motion amplitude. Aggregate 3-dimensional radial position errors presented here suggest the target will be within 4 mm of the target volume for 95% of the beam delivery.« less

Gossip and Distributed Kalman Filtering: Weak Consensus Under Weak Detectability

NASA Astrophysics Data System (ADS)

Kar, Soummya; Moura, José M. F.

2011-04-01

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where inter-sensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1. the GIKF error process remains stochastically bounded, irrespective of the instability properties of the random process dynamics; and 2. the network achieves \\emph{weak consensus}, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semi-definite matrices (independent of the initial state.) To prove these results, we interpret the filtered states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a non-stationary Markov chain on the network graph.

What errors do peer reviewers detect, and does training improve their ability to detect them?

PubMed

Schroter, Sara; Black, Nick; Evans, Stephen; Godlee, Fiona; Osorio, Lyda; Smith, Richard

2008-10-01

To analyse data from a trial and report the frequencies with which major and minor errors are detected at a general medical journal, the types of errors missed and the impact of training on error detection. 607 peer reviewers at the BMJ were randomized to two intervention groups receiving different types of training (face-to-face training or a self-taught package) and a control group. Each reviewer was sent the same three test papers over the study period, each of which had nine major and five minor methodological errors inserted. BMJ peer reviewers. The quality of review, assessed using a validated instrument, and the number and type of errors detected before and after training. The number of major errors detected varied over the three papers. The interventions had small effects. At baseline (Paper 1) reviewers found an average of 2.58 of the nine major errors, with no notable difference between the groups. The mean number of errors reported was similar for the second and third papers, 2.71 and 3.0, respectively. Biased randomization was the error detected most frequently in all three papers, with over 60% of reviewers rejecting the papers identifying this error. Reviewers who did not reject the papers found fewer errors and the proportion finding biased randomization was less than 40% for each paper. Editors should not assume that reviewers will detect most major errors, particularly those concerned with the context of study. Short training packages have only a slight impact on improving error detection.

Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

NASA Astrophysics Data System (ADS)

Baum, Bryan A.; Wielicki, Bruce A.

1994-01-01

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

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

NASA Technical Reports Server (NTRS)

Fell, P. J.

1981-01-01

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

Recovery of chemical Estimates by Field Inhomogeneity Neighborhood Error Detection (REFINED): Fat/Water Separation at 7T

PubMed Central

Narayan, Sreenath; Kalhan, Satish C.; Wilson, David L.

2012-01-01

I.Abstract Purpose To reduce swaps in fat-water separation methods, a particular issue on 7T small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Materials and Methods Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Results Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Conclusion Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. PMID:23023815

Recovery of chemical estimates by field inhomogeneity neighborhood error detection (REFINED): fat/water separation at 7 tesla.

PubMed

Narayan, Sreenath; Kalhan, Satish C; Wilson, David L

2013-05-01

To reduce swaps in fat-water separation methods, a particular issue on 7 Tesla (T) small animal scanners due to field inhomogeneity, using image postprocessing innovations that detect and correct errors in the B0 field map. Fat-water decompositions and B0 field maps were computed for images of mice acquired on a 7T Bruker BioSpec scanner, using a computationally efficient method for solving the Markov Random Field formulation of the multi-point Dixon model. The B0 field maps were processed with a novel hole-filling method, based on edge strength between regions, and a novel k-means method, based on field-map intensities, which were iteratively applied to automatically detect and reinitialize error regions in the B0 field maps. Errors were manually assessed in the B0 field maps and chemical parameter maps both before and after error correction. Partial swaps were found in 6% of images when processed with FLAWLESS. After REFINED correction, only 0.7% of images contained partial swaps, resulting in an 88% decrease in error rate. Complete swaps were not problematic. Ex post facto error correction is a viable supplement to a priori techniques for producing globally smooth B0 field maps, without partial swaps. With our processing pipeline, it is possible to process image volumes rapidly, robustly, and almost automatically. Copyright © 2012 Wiley Periodicals, Inc.

Frequency and types of the medication errors in an academic emergency department in Iran: The emergent need for clinical pharmacy services in emergency departments.

PubMed

Zeraatchi, Alireza; Talebian, Mohammad-Taghi; Nejati, Amir; Dashti-Khavidaki, Simin

2013-07-01

Emergency departments (EDs) are characterized by simultaneous care of multiple patients with various medical conditions. Due to a large number of patients with complex diseases, speed and complexity of medication use, working in under-staffing and crowded environment, medication errors are commonly perpetrated by emergency care providers. This study was designed to evaluate the incidence of medication errors among patients attending to an ED in a teaching hospital in Iran. In this cross-sectional study, a total of 500 patients attending to ED were randomly assessed for incidence and types of medication errors. Some factors related to medication errors such as working shift, weekdays and schedule of the educational program of trainee were also evaluated. Nearly, 22% of patients experienced at least one medication error. The rate of medication errors were 0.41 errors per patient and 0.16 errors per ordered medication. The frequency of medication errors was higher in men, middle age patients, first weekdays, night-time work schedules and the first semester of educational year of new junior emergency medicine residents. More than 60% of errors were prescription errors by physicians and the remaining were transcription or administration errors by nurses. More than 35% of the prescribing errors happened during the selection of drug dose and frequency. The most common medication errors by nurses during the administration were omission error (16.2%) followed by unauthorized drug (6.4%). Most of the medication errors happened for anticoagulants and thrombolytics (41.2%) followed by antimicrobial agents (37.7%) and insulin (7.4%). In this study, at least one-fifth of the patients attending to ED experienced medication errors resulting from multiple factors. More common prescription errors happened during ordering drug dose and frequency. More common administration errors included dug omission or unauthorized drug.

A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1

NASA Technical Reports Server (NTRS)

Ingels, F. M.; Mo, C. D.

1978-01-01

An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error.

Error threshold for color codes and random three-body Ising models.

PubMed

Katzgraber, Helmut G; Bombin, H; Martin-Delgado, M A

2009-08-28

We study the error threshold of color codes, a class of topological quantum codes that allow a direct implementation of quantum Clifford gates suitable for entanglement distillation, teleportation, and fault-tolerant quantum computation. We map the error-correction process onto a statistical mechanical random three-body Ising model and study its phase diagram via Monte Carlo simulations. The obtained error threshold of p(c) = 0.109(2) is very close to that of Kitaev's toric code, showing that enhanced computational capabilities do not necessarily imply lower resistance to noise.

Effect of random errors in planar PIV data on pressure estimation in vortex dominated flows

NASA Astrophysics Data System (ADS)

McClure, Jeffrey; Yarusevych, Serhiy

2015-11-01

The sensitivity of pressure estimation techniques from Particle Image Velocimetry (PIV) measurements to random errors in measured velocity data is investigated using the flow over a circular cylinder as a test case. Direct numerical simulations are performed for ReD = 100, 300 and 1575, spanning laminar, transitional, and turbulent wake regimes, respectively. A range of random errors typical for PIV measurements is applied to synthetic PIV data extracted from numerical results. A parametric study is then performed using a number of common pressure estimation techniques. Optimal temporal and spatial resolutions are derived based on the sensitivity of the estimated pressure fields to the simulated random error in velocity measurements, and the results are compared to an optimization model derived from error propagation theory. It is shown that the reductions in spatial and temporal scales at higher Reynolds numbers leads to notable changes in the optimal pressure evaluation parameters. The effect of smaller scale wake structures is also quantified. The errors in the estimated pressure fields are shown to depend significantly on the pressure estimation technique employed. The results are used to provide recommendations for the use of pressure and force estimation techniques from experimental PIV measurements in vortex dominated laminar and turbulent wake flows.

Refractive error and visual impairment in private school children in Ghana.

PubMed

Kumah, Ben D; Ebri, Anne; Abdul-Kabir, Mohammed; Ahmed, Abdul-Sadik; Koomson, Nana Ya; Aikins, Samual; Aikins, Amos; Amedo, Angela; Lartey, Seth; Naidoo, Kovin

2013-12-01

To assess the prevalence of refractive error and visual impairment in private school children in Ghana. A random selection of geographically defined classes in clusters was used to identify a sample of school children aged 12 to 15 years in the Ashanti Region. Children in 60 clusters were enumerated and examined in classrooms. The examination included visual acuity, retinoscopy, autorefraction under cycloplegia, and examination of anterior segment, media, and fundus. For quality assurance, a random sample of children with reduced and normal vision were selected and re-examined independently. A total of 2454 children attending 53 private schools were enumerated, and of these, 2435 (99.2%) were examined. Prevalence of uncorrected, presenting, and best visual acuity of 20/40 or worse in the better eye was 3.7, 3.5, and 0.4%, respectively. Refractive error was the cause of reduced vision in 71.7% of 152 eyes, amblyopia in 9.9%, retinal disorders in 5.9%, and corneal opacity in 4.6%. Exterior and anterior segment abnormalities occurred in 43 (1.8%) children. Myopia (at least -0.50 D) in one or both eyes was present in 3.2% of children when measured with retinoscopy and in 3.4% measured with autorefraction. Myopia was not significantly associated with gender (P = 0.82). Hyperopia (+2.00 D or more) in at least one eye was present in 0.3% of children with retinoscopy and autorefraction. The prevalence of reduced vision in Ghanaian private school children due to uncorrected refractive error was low. However, the prevalence of amblyopia, retinal disorders, and corneal opacities indicate the need for early interventions.

Modeling Errors in Daily Precipitation Measurements: Additive or Multiplicative?

NASA Technical Reports Server (NTRS)

Tian, Yudong; Huffman, George J.; Adler, Robert F.; Tang, Ling; Sapiano, Matthew; Maggioni, Viviana; Wu, Huan

2013-01-01

The definition and quantification of uncertainty depend on the error model used. For uncertainties in precipitation measurements, two types of error models have been widely adopted: the additive error model and the multiplicative error model. This leads to incompatible specifications of uncertainties and impedes intercomparison and application.In this letter, we assess the suitability of both models for satellite-based daily precipitation measurements in an effort to clarify the uncertainty representation. Three criteria were employed to evaluate the applicability of either model: (1) better separation of the systematic and random errors; (2) applicability to the large range of variability in daily precipitation; and (3) better predictive skills. It is found that the multiplicative error model is a much better choice under all three criteria. It extracted the systematic errors more cleanly, was more consistent with the large variability of precipitation measurements, and produced superior predictions of the error characteristics. The additive error model had several weaknesses, such as non constant variance resulting from systematic errors leaking into random errors, and the lack of prediction capability. Therefore, the multiplicative error model is a better choice.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine.

PubMed

Howard, Jeremy T; Ashwell, Melissa S; Baynes, Ronald E; Brooks, James D; Yeatts, James L; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs ( n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study.

Genetic Parameter Estimates for Metabolizing Two Common Pharmaceuticals in Swine

PubMed Central

Howard, Jeremy T.; Ashwell, Melissa S.; Baynes, Ronald E.; Brooks, James D.; Yeatts, James L.; Maltecca, Christian

2018-01-01

In livestock, the regulation of drugs used to treat livestock has received increased attention and it is currently unknown how much of the phenotypic variation in drug metabolism is due to the genetics of an animal. Therefore, the objective of the study was to determine the amount of phenotypic variation in fenbendazole and flunixin meglumine drug metabolism due to genetics. The population consisted of crossbred female and castrated male nursery pigs (n = 198) that were sired by boars represented by four breeds. The animals were spread across nine batches. Drugs were administered intravenously and blood collected a minimum of 10 times over a 48 h period. Genetic parameters for the parent drug and metabolite concentration within each drug were estimated based on pharmacokinetics (PK) parameters or concentrations across time utilizing a random regression model. The PK parameters were estimated using a non-compartmental analysis. The PK model included fixed effects of sex and breed of sire along with random sire and batch effects. The random regression model utilized Legendre polynomials and included a fixed population concentration curve, sex, and breed of sire effects along with a random sire deviation from the population curve and batch effect. The sire effect included the intercept for all models except for the fenbendazole metabolite (i.e., intercept and slope). The mean heritability across PK parameters for the fenbendazole and flunixin meglumine parent drug (metabolite) was 0.15 (0.18) and 0.31 (0.40), respectively. For the parent drug (metabolite), the mean heritability across time was 0.27 (0.60) and 0.14 (0.44) for fenbendazole and flunixin meglumine, respectively. The errors surrounding the heritability estimates for the random regression model were smaller compared to estimates obtained from PK parameters. Across both the PK and plasma drug concentration across model, a moderate heritability was estimated. The model that utilized the plasma drug concentration across time resulted in estimates with a smaller standard error compared to models that utilized PK parameters. The current study found a low to moderate proportion of the phenotypic variation in metabolizing fenbendazole and flunixin meglumine that was explained by genetics in the current study. PMID:29487615

One-step random mutagenesis by error-prone rolling circle amplification

PubMed Central

Fujii, Ryota; Kitaoka, Motomitsu; Hayashi, Kiyoshi

2004-01-01

In vitro random mutagenesis is a powerful tool for altering properties of enzymes. We describe here a novel random mutagenesis method using rolling circle amplification, named error-prone RCA. This method consists of only one DNA amplification step followed by transformation of the host strain, without treatment with any restriction enzymes or DNA ligases, and results in a randomly mutated plasmid library with 3–4 mutations per kilobase. Specific primers or special equipment, such as a thermal-cycler, are not required. This method permits rapid preparation of randomly mutated plasmid libraries, enabling random mutagenesis to become a more commonly used technique. PMID:15507684

[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.

[Statistical Process Control (SPC) can help prevent treatment errors without increasing costs in radiotherapy].

PubMed

Govindarajan, R; Llueguera, E; Melero, A; Molero, J; Soler, N; Rueda, C; Paradinas, C

2010-01-01

Statistical Process Control (SPC) was applied to monitor patient set-up in radiotherapy and, when the measured set-up error values indicated a loss of process stability, its root cause was identified and eliminated to prevent set-up errors. Set up errors were measured for medial-lateral (ml), cranial-caudal (cc) and anterior-posterior (ap) dimensions and then the upper control limits were calculated. Once the control limits were known and the range variability was acceptable, treatment set-up errors were monitored using sub-groups of 3 patients, three times each shift. These values were plotted on a control chart in real time. Control limit values showed that the existing variation was acceptable. Set-up errors, measured and plotted on a X chart, helped monitor the set-up process stability and, if and when the stability was lost, treatment was interrupted, the particular cause responsible for the non-random pattern was identified and corrective action was taken before proceeding with the treatment. SPC protocol focuses on controlling the variability due to assignable cause instead of focusing on patient-to-patient variability which normally does not exist. Compared to weekly sampling of set-up error in each and every patient, which may only ensure that just those sampled sessions were set-up correctly, the SPC method enables set-up error prevention in all treatment sessions for all patients and, at the same time, reduces the control costs. Copyright © 2009 SECA. Published by Elsevier Espana. All rights reserved.

Stochastic goal-oriented error estimation with memory

NASA Astrophysics Data System (ADS)

Ackmann, Jan; Marotzke, Jochem; Korn, Peter

2017-11-01

We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality.

PubMed

Bishara, Anthony J; Hittner, James B

2015-10-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box-Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples ( n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated.

Reducing Bias and Error in the Correlation Coefficient Due to Nonnormality

PubMed Central

Hittner, James B.

2014-01-01

It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared with its major alternatives, including the Spearman rank-order correlation, the bootstrap estimate, the Box–Cox transformation family, and a general normalizing transformation (i.e., rankit), as well as to various bias adjustments. Nonnormality caused the correlation coefficient to be inflated by up to +.14, particularly when the nonnormality involved heavy-tailed distributions. Traditional bias adjustments worsened this problem, further inflating the estimate. The Spearman and rankit correlations eliminated this inflation and provided conservative estimates. Rankit also minimized random error for most sample sizes, except for the smallest samples (n = 10), where bootstrapping was more effective. Overall, results justify the use of carefully chosen alternatives to the Pearson correlation when normality is violated. PMID:29795841

Random Versus Nonrandom Peer Review: A Case for More Meaningful Peer Review.

PubMed

Itri, Jason N; Donithan, Adam; Patel, Sohil H

2018-05-10

Random peer review programs are not optimized to discover cases with diagnostic error and thus have inherent limitations with respect to educational and quality improvement value. Nonrandom peer review offers an alternative approach in which diagnostic error cases are targeted for collection during routine clinical practice. The objective of this study was to compare error cases identified through random and nonrandom peer review approaches at an academic center. During the 1-year study period, the number of discrepancy cases and score of discrepancy were determined from each approach. The nonrandom peer review process collected 190 cases, of which 60 were scored as 2 (minor discrepancy), 94 as 3 (significant discrepancy), and 36 as 4 (major discrepancy). In the random peer review process, 1,690 cases were reviewed, of which 1,646 were scored as 1 (no discrepancy), 44 were scored as 2 (minor discrepancy), and none were scored as 3 or 4. Several teaching lessons and quality improvement measures were developed as a result of analysis of error cases collected through the nonrandom peer review process. Our experience supports the implementation of nonrandom peer review as a replacement to random peer review, with nonrandom peer review serving as a more effective method for collecting diagnostic error cases with educational and quality improvement value. Copyright © 2018 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Improved estimates of partial volume coefficients from noisy brain MRI using spatial context.

PubMed

Manjón, José V; Tohka, Jussi; Robles, Montserrat

2010-11-01

This paper addresses the problem of accurate voxel-level estimation of tissue proportions in the human brain magnetic resonance imaging (MRI). Due to the finite resolution of acquisition systems, MRI voxels can contain contributions from more than a single tissue type. The voxel-level estimation of this fractional content is known as partial volume coefficient estimation. In the present work, two new methods to calculate the partial volume coefficients under noisy conditions are introduced and compared with current similar methods. Concretely, a novel Markov Random Field model allowing sharp transitions between partial volume coefficients of neighbouring voxels and an advanced non-local means filtering technique are proposed to reduce the errors due to random noise in the partial volume coefficient estimation. In addition, a comparison was made to find out how the different methodologies affect the measurement of the brain tissue type volumes. Based on the obtained results, the main conclusions are that (1) both Markov Random Field modelling and non-local means filtering improved the partial volume coefficient estimation results, and (2) non-local means filtering was the better of the two strategies for partial volume coefficient estimation. Copyright 2010 Elsevier Inc. All rights reserved.

Efficient Measurement of Quantum Gate Error by Interleaved Randomized Benchmarking

NASA Astrophysics Data System (ADS)

Magesan, Easwar; Gambetta, Jay M.; Johnson, B. R.; Ryan, Colm A.; Chow, Jerry M.; Merkel, Seth T.; da Silva, Marcus P.; Keefe, George A.; Rothwell, Mary B.; Ohki, Thomas A.; Ketchen, Mark B.; Steffen, M.

2012-08-01

We describe a scalable experimental protocol for estimating the average error of individual quantum computational gates. This protocol consists of interleaving random Clifford gates between the gate of interest and provides an estimate as well as theoretical bounds for the average error of the gate under test, so long as the average noise variation over all Clifford gates is small. This technique takes into account both state preparation and measurement errors and is scalable in the number of qubits. We apply this protocol to a superconducting qubit system and find a bounded average error of 0.003 [0,0.016] for the single-qubit gates Xπ/2 and Yπ/2. These bounded values provide better estimates of the average error than those extracted via quantum process tomography.

Efficacy of Visual-Acoustic Biofeedback Intervention for Residual Rhotic Errors: A Single-Subject Randomization Study

ERIC Educational Resources Information Center

Byun, Tara McAllister

2017-01-01

Purpose: This study documented the efficacy of visual-acoustic biofeedback intervention for residual rhotic errors, relative to a comparison condition involving traditional articulatory treatment. All participants received both treatments in a single-subject experimental design featuring alternating treatments with blocked randomization of…

Statistical Analysis Experiment for Freshman Chemistry Lab.

ERIC Educational Resources Information Center

Salzsieder, John C.

1995-01-01

Describes a laboratory experiment dissolving zinc from galvanized nails in which data can be gathered very quickly for statistical analysis. The data have sufficient significant figures and the experiment yields a nice distribution of random errors. Freshman students can gain an appreciation of the relationships between random error, number of…

Evaluation of seasonal and spatial variations of lumped water balance model sensitivity to precipitation data errors

NASA Astrophysics Data System (ADS)

Xu, Chong-yu; Tunemar, Liselotte; Chen, Yongqin David; Singh, V. P.

2006-06-01

Sensitivity of hydrological models to input data errors have been reported in the literature for particular models on a single or a few catchments. A more important issue, i.e. how model's response to input data error changes as the catchment conditions change has not been addressed previously. This study investigates the seasonal and spatial effects of precipitation data errors on the performance of conceptual hydrological models. For this study, a monthly conceptual water balance model, NOPEX-6, was applied to 26 catchments in the Mälaren basin in Central Sweden. Both systematic and random errors were considered. For the systematic errors, 5-15% of mean monthly precipitation values were added to the original precipitation to form the corrupted input scenarios. Random values were generated by Monte Carlo simulation and were assumed to be (1) independent between months, and (2) distributed according to a Gaussian law of zero mean and constant standard deviation that were taken as 5, 10, 15, 20, and 25% of the mean monthly standard deviation of precipitation. The results show that the response of the model parameters and model performance depends, among others, on the type of the error, the magnitude of the error, physical characteristics of the catchment, and the season of the year. In particular, the model appears less sensitive to the random error than to the systematic error. The catchments with smaller values of runoff coefficients were more influenced by input data errors than were the catchments with higher values. Dry months were more sensitive to precipitation errors than were wet months. Recalibration of the model with erroneous data compensated in part for the data errors by altering the model parameters.

Effect of magnesium added to local anesthetics for caudal anesthesia on postoperative pain in pediatric surgical patients: A systematic review and meta-analysis with Trial Sequential Analysis.

PubMed

Kawakami, Hiromasa; Mihara, Takahiro; Nakamura, Nobuhito; Ka, Koui; Goto, Takahisa

2018-01-01

Magnesium has been investigated as an adjuvant for neuraxial anesthesia, but the effect of caudal magnesium on postoperative pain is inconsistent. The aim of this systematic review and meta-analysis was to evaluate the analgesic effect of caudal magnesium. We searched six databases, including trial registration sites. Randomized clinical trials reporting the effect of caudal magnesium on postoperative pain after general anesthesia were eligible. The risk ratio for use of rescue analgesics after surgery was combined using a random-effects model. We also assessed adverse events. The I2 statistic was used to assess heterogeneity. We assessed risk of bias with Cochrane domains. We controlled type I and II errors due to sparse data and repetitive testing with Trial Sequential Analysis. We assessed the quality of evidence with GRADE. Four randomized controlled trials (247 patients) evaluated the need for rescue analgesics. In all four trials, 50 mg of magnesium was administered with caudal ropivacaine. The results suggested that the need for rescue analgesia was reduced significantly by caudal magnesium administration (risk ratio 0.45; 95% confidence interval 0.24-0.86). There was considerable heterogeneity as indicated by an I2 value of 62.5%. The Trial Sequential Analysis-adjusted confidence interval was 0.04-5.55, indicating that further trials are required. The quality of evidence was very low. The rate of adverse events was comparable between treatment groups. Caudal magnesium may reduce the need for rescue analgesia after surgery, but further randomized clinical trials with a low risk of bias and a low risk of random errors are necessary to assess the effect of caudal magnesium on postoperative pain and adverse events. University Hospital Medical Information Network Clinical Trials Registry UMIN000025344.

Determination of the precision error of the pulmonary artery thermodilution catheter using an in vitro continuous flow test rig.

PubMed

Yang, Xiao-Xing; Critchley, Lester A; Joynt, Gavin M

2011-01-01

Thermodilution cardiac output using a pulmonary artery catheter is the reference method against which all new methods of cardiac output measurement are judged. However, thermodilution lacks precision and has a quoted precision error of ± 20%. There is uncertainty about its true precision and this causes difficulty when validating new cardiac output technology. Our aim in this investigation was to determine the current precision error of thermodilution measurements. A test rig through which water circulated at different constant rates with ports to insert catheters into a flow chamber was assembled. Flow rate was measured by an externally placed transonic flowprobe and meter. The meter was calibrated by timed filling of a cylinder. Arrow and Edwards 7Fr thermodilution catheters, connected to a Siemens SC9000 cardiac output monitor, were tested. Thermodilution readings were made by injecting 5 mL of ice-cold water. Precision error was divided into random and systematic components, which were determined separately. Between-readings (random) variability was determined for each catheter by taking sets of 10 readings at different flow rates. Coefficient of variation (CV) was calculated for each set and averaged. Between-catheter systems (systematic) variability was derived by plotting calibration lines for sets of catheters. Slopes were used to estimate the systematic component. Performances of 3 cardiac output monitors were compared: Siemens SC9000, Siemens Sirecust 1261, and Philips MP50. Five Arrow and 5 Edwards catheters were tested using the Siemens SC9000 monitor. Flow rates between 0.7 and 7.0 L/min were studied. The CV (random error) for Arrow was 5.4% and for Edwards was 4.8%. The random precision error was ± 10.0% (95% confidence limits). CV (systematic error) was 5.8% and 6.0%, respectively. The systematic precision error was ± 11.6%. The total precision error of a single thermodilution reading was ± 15.3% and ± 13.0% for triplicate readings. Precision error increased by 45% when using the Sirecust monitor and 100% when using the Philips monitor. In vitro testing of pulmonary artery catheters enabled us to measure both the random and systematic error components of thermodilution cardiac output measurement, and thus calculate the precision error. Using the Siemens monitor, we established a precision error of ± 15.3% for single and ± 13.0% for triplicate reading, which was similar to the previous estimate of ± 20%. However, this precision error was significantly worsened by using the Sirecust and Philips monitors. Clinicians should recognize that the precision error of thermodilution cardiac output is dependent on the selection of catheter and monitor model.

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

NASA Technical Reports Server (NTRS)

Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

2011-01-01

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

The relative importance of random error and observation frequency in detecting trends in upper tropospheric water vapor

NASA Astrophysics Data System (ADS)

Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

2011-11-01

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Comment on Sub-15 nm Hard X-Ray Focusing with a New Total-Reflection Zone Plate

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

Specht, Eliot D

2011-01-01

Takano et al. report the focusing of 10-keV X-rays to a size of 14.4 nm using a total-reflection zone plate (TRZP). This focal size is at the diffraction limit for the optic's aperture. This would be a noteworthy result, since the TRZP was fabricated using conventional lithography techniques. Alternative nanofocusing optics require more demanding fabrication methods. However, as I will discuss in this Comment, the intensity distribution presented by Takano et al. (Fig. 4 of ref. 1) is more consistent with the random speckle pattern produced by the scattering of a coherent incident beam by a distorted optic than withmore » a diffraction-limited focus. When interpreted in this manner, the true focal spot size is {approx}70 nm: 5 times the diffraction limit. When a coherent photon beam illuminates an optic containing randomly distributed regions which introduce different phase shifts, the scattered diffraction pattern consists of a speckle pattern. Each speckle will be diffraction-limited: the peak width of a single speckle depends entirely on the source coherence and gives no information about the optic. The envelope of the speckle distribution corresponds to the focal spot which would be observed using incoherent illumination. The width of this envelope is due to the finite size of the coherently-diffracting domains produced by slope and position errors in the optic. The focal intensity distribution in Fig. 4 of ref. 1 indeed contains a diffraction-limited peak, but this peak contains only a fraction of the power in the focused, and forms part of a distribution of sharp peaks with an envelope {approx}70 nm in width, just as expected for a speckle pattern. At the 4mm focal distance, the 70 nm width corresponds to a slope error of 18 {micro}rad. To reach the 14 nm diffraction limit, the slope error must be reduced to 3 {micro}rad. Takano et al. have identified a likely source of this error: warping due to stress as a result of zone deposition. It will be interesting to see whether the use of a more rigid substrate gives improved results.« less

Individual pore and interconnection size analysis of macroporous ceramic scaffolds using high-resolution X-ray tomography

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

Jerban, Saeed, E-mail: saeed.jerban@usherbrooke.ca

2016-08-15

The pore interconnection size of β-tricalcium phosphate scaffolds plays an essential role in the bone repair process. Although, the μCT technique is widely used in the biomaterial community, it is rarely used to measure the interconnection size because of the lack of algorithms. In addition, discrete nature of the μCT introduces large systematic errors due to the convex geometry of interconnections. We proposed, verified and validated a novel pore-level algorithm to accurately characterize the individual pores and interconnections. Specifically, pores and interconnections were isolated, labeled, and individually analyzed with high accuracy. The technique was verified thoroughly by visually inspecting andmore » verifying over 3474 properties of randomly selected pores. This extensive verification process has passed a one-percent accuracy criterion. Scanning errors inherent in the discretization, which lead to both dummy and significantly overestimated interconnections, have been examined using computer-based simulations and additional high-resolution scanning. Then accurate correction charts were developed and used to reduce the scanning errors. Only after the corrections, both the μCT and SEM-based results converged, and the novel algorithm was validated. Material scientists with access to all geometrical properties of individual pores and interconnections, using the novel algorithm, will have a more-detailed and accurate description of the substitute architecture and a potentially deeper understanding of the link between the geometric and biological interaction. - Highlights: •An algorithm is developed to analyze individually all pores and interconnections. •After pore isolating, the discretization errors in interconnections were corrected. •Dummy interconnections and overestimated sizes were due to thin material walls. •The isolating algorithm was verified through visual inspection (99% accurate). •After correcting for the systematic errors, algorithm was validated successfully.« less

Bias and heteroscedastic memory error in self-reported health behavior: an investigation using covariance structure analysis

PubMed Central

Kupek, Emil

2002-01-01

Background Frequent use of self-reports for investigating recent and past behavior in medical research requires statistical techniques capable of analyzing complex sources of bias associated with this methodology. In particular, although decreasing accuracy of recalling more distant past events is commonplace, the bias due to differential in memory errors resulting from it has rarely been modeled statistically. Methods Covariance structure analysis was used to estimate the recall error of self-reported number of sexual partners for past periods of varying duration and its implication for the bias. Results Results indicated increasing levels of inaccuracy for reports about more distant past. Considerable positive bias was found for a small fraction of respondents who reported ten or more partners in the last year, last two years and last five years. This is consistent with the effect of heteroscedastic random error where the majority of partners had been acquired in the more distant past and therefore were recalled less accurately than the partners acquired more recently to the time of interviewing. Conclusions Memory errors of this type depend on the salience of the events recalled and are likely to be present in many areas of health research based on self-reported behavior. PMID:12435276

Image enhancement by spectral-error correction for dual-energy computed tomography.

PubMed

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Error suppression and correction for quantum annealing

NASA Astrophysics Data System (ADS)

Lidar, Daniel

While adiabatic quantum computing and quantum annealing enjoy a certain degree of inherent robustness against excitations and control errors, there is no escaping the need for error correction or suppression. In this talk I will give an overview of our work on the development of such error correction and suppression methods. We have experimentally tested one such method combining encoding, energy penalties and decoding, on a D-Wave Two processor, with encouraging results. Mean field theory shows that this can be explained in terms of a softening of the closing of the gap due to the energy penalty, resulting in protection against excitations that occur near the quantum critical point. Decoding recovers population from excited states and enhances the success probability of quantum annealing. Moreover, we have demonstrated that using repetition codes with increasing code distance can lower the effective temperature of the annealer. References: K.L. Pudenz, T. Albash, D.A. Lidar, ``Error corrected quantum annealing with hundreds of qubits'', Nature Commun. 5, 3243 (2014). K.L. Pudenz, T. Albash, D.A. Lidar, ``Quantum annealing correction for random Ising problems'', Phys. Rev. A. 91, 042302 (2015). S. Matsuura, H. Nishimori, T. Albash, D.A. Lidar, ``Mean Field Analysis of Quantum Annealing Correction''. arXiv:1510.07709. W. Vinci et al., in preparation.

Irregular analytical errors in diagnostic testing - a novel concept.

PubMed

Vogeser, Michael; Seger, Christoph

2018-02-23

In laboratory medicine, routine periodic analyses for internal and external quality control measurements interpreted by statistical methods are mandatory for batch clearance. Data analysis of these process-oriented measurements allows for insight into random analytical variation and systematic calibration bias over time. However, in such a setting, any individual sample is not under individual quality control. The quality control measurements act only at the batch level. Quantitative or qualitative data derived for many effects and interferences associated with an individual diagnostic sample can compromise any analyte. It is obvious that a process for a quality-control-sample-based approach of quality assurance is not sensitive to such errors. To address the potential causes and nature of such analytical interference in individual samples more systematically, we suggest the introduction of a new term called the irregular (individual) analytical error. Practically, this term can be applied in any analytical assay that is traceable to a reference measurement system. For an individual sample an irregular analytical error is defined as an inaccuracy (which is the deviation from a reference measurement procedure result) of a test result that is so high it cannot be explained by measurement uncertainty of the utilized routine assay operating within the accepted limitations of the associated process quality control measurements. The deviation can be defined as the linear combination of the process measurement uncertainty and the method bias for the reference measurement system. Such errors should be coined irregular analytical errors of the individual sample. The measurement result is compromised either by an irregular effect associated with the individual composition (matrix) of the sample or an individual single sample associated processing error in the analytical process. Currently, the availability of reference measurement procedures is still highly limited, but LC-isotope-dilution mass spectrometry methods are increasingly used for pre-market validation of routine diagnostic assays (these tests also involve substantial sets of clinical validation samples). Based on this definition/terminology, we list recognized causes of irregular analytical error as a risk catalog for clinical chemistry in this article. These issues include reproducible individual analytical errors (e.g. caused by anti-reagent antibodies) and non-reproducible, sporadic errors (e.g. errors due to incorrect pipetting volume due to air bubbles in a sample), which can both lead to inaccurate results and risks for patients.

Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty

DOE PAGES

Ballantyne, A. P.; Andres, R.; Houghton, R.; ...

2015-04-30

Over the last 5 decades monitoring systems have been developed to detect changes in the accumulation of carbon (C) in the atmosphere and ocean; however, our ability to detect changes in the behavior of the global C cycle is still hindered by measurement and estimate errors. Here we present a rigorous and flexible framework for assessing the temporal and spatial components of estimate errors and their impact on uncertainty in net C uptake by the biosphere. We present a novel approach for incorporating temporally correlated random error into the error structure of emission estimates. Based on this approach, we concludemore » that the 2σ uncertainties of the atmospheric growth rate have decreased from 1.2 Pg C yr ₋1 in the 1960s to 0.3 Pg C yr ₋1 in the 2000s due to an expansion of the atmospheric observation network. The 2σ uncertainties in fossil fuel emissions have increased from 0.3 Pg C yr ₋1 in the 1960s to almost 1.0 Pg C yr ₋1 during the 2000s due to differences in national reporting errors and differences in energy inventories. Lastly, while land use emissions have remained fairly constant, their errors still remain high and thus their global C uptake uncertainty is not trivial. Currently, the absolute errors in fossil fuel emissions rival the total emissions from land use, highlighting the extent to which fossil fuels dominate the global C budget. Because errors in the atmospheric growth rate have decreased faster than errors in total emissions have increased, a ~20% reduction in the overall uncertainty of net C global uptake has occurred. Given all the major sources of error in the global C budget that we could identify, we are 93% confident that terrestrial C uptake has increased and 97% confident that ocean C uptake has increased over the last 5 decades. Thus, it is clear that arguably one of the most vital ecosystem services currently provided by the biosphere is the continued removal of approximately half of atmospheric CO 2 emissions from the atmosphere, although there are certain environmental costs associated with this service, such as the acidification of ocean waters.« less

On Time/Space Aggregation of Fine-Scale Error Estimates (Invited)

NASA Astrophysics Data System (ADS)

Huffman, G. J.

2013-12-01

Estimating errors inherent in fine time/space-scale satellite precipitation data sets is still an on-going problem and a key area of active research. Complicating features of these data sets include the intrinsic intermittency of the precipitation in space and time and the resulting highly skewed distribution of precipitation rates. Additional issues arise from the subsampling errors that satellites introduce, the errors due to retrieval algorithms, and the correlated error that retrieval and merger algorithms sometimes introduce. Several interesting approaches have been developed recently that appear to make progress on these long-standing issues. At the same time, the monthly averages over 2.5°x2.5° grid boxes in the Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) precipitation data set follow a very simple sampling-based error model (Huffman 1997) with coefficients that are set using coincident surface and GPCP SG data. This presentation outlines the unsolved problem of how to aggregate the fine-scale errors (discussed above) to an arbitrary time/space averaging volume for practical use in applications, reducing in the limit to simple Gaussian expressions at the monthly 2.5°x2.5° scale. Scatter diagrams with different time/space averaging show that the relationship between the satellite and validation data improves due to the reduction in random error. One of the key, and highly non-linear, issues is that fine-scale estimates tend to have large numbers of cases with points near the axes on the scatter diagram (one of the values is exactly or nearly zero, while the other value is higher). Averaging 'pulls' the points away from the axes and towards the 1:1 line, which usually happens for higher precipitation rates before lower rates. Given this qualitative observation of how aggregation affects error, we observe that existing aggregation rules, such as the Steiner et al. (2003) power law, only depend on the aggregated precipitation rate. Is this sufficient, or is it necessary to aggregate the precipitation error estimates across the time/space data cube used for averaging? At least for small time/space data cubes it would seem that the detailed variables that affect each precipitation error estimate in the aggregation, such as sensor type, land/ocean surface type, convective/stratiform type, and so on, drive variations that must be accounted for explicitly.

On-board error correction improves IR earth sensor accuracy

NASA Astrophysics Data System (ADS)

Alex, T. K.; Kasturirangan, K.; Shrivastava, S. K.

1989-10-01

Infra-red earth sensors are used in satellites for attitude sensing. Their accuracy is limited by systematic and random errors. The sources of errors in a scanning infra-red earth sensor are analyzed in this paper. The systematic errors arising from seasonal variation of infra-red radiation, oblate shape of the earth, ambient temperature of sensor, changes in scan/spin rates have been analyzed. Simple relations are derived using least square curve fitting for on-board correction of these errors. Random errors arising out of noise from detector and amplifiers, instability of alignment and localized radiance anomalies are analyzed and possible correction methods are suggested. Sun and Moon interference on earth sensor performance has seriously affected a number of missions. The on-board processor detects Sun/Moon interference and corrects the errors on-board. It is possible to obtain eight times improvement in sensing accuracy, which will be comparable with ground based post facto attitude refinement.

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part 1; Improved Method and Uncertainties

NASA Technical Reports Server (NTRS)

Olson, William S.; Kummerow, Christian D.; Yang, Song; Petty, Grant W.; Tao, Wei-Kuo; Bell, Thomas L.; Braun, Scott A.; Wang, Yansen; Lang, Stephen E.; Johnson, Daniel E.;

The Effect of Ionospheric Models on Electromagnetic Pulse Locations

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

Fenimore, Edward E.; Triplett, Laurie A.

2014-07-01

Locations of electromagnetic pulses (EMPs) determined by time-of-arrival (TOA) often have outliers with significantly larger errors than expected. In the past, these errors were thought to arise from high order terms in the Appleton-Hartree equation. We simulated 1000 events randomly spread around the Earth into a constellation of 22 GPS satellites. We used four different ionospheres: “simple” where the time delay goes as the inverse of the frequency-squared, “full Appleton-Hartree”, the “BobRD integrals” and a full raytracing code. The simple and full Appleton-Hartree ionospheres do not show outliers whereas the BobRD and raytracing do. This strongly suggests that the causemore » of the outliers is not additional terms in the Appleton-Hartree equation, but rather is due to the additional path length due to refraction. A method to fix the outliers is suggested based on fitting a time to the delays calculated at the 5 GPS frequencies with BobRD and simple ionospheres. The difference in time is used as a correction to the TOAs.« less

A comparison of the stochastic and machine learning approaches in hydrologic time series forecasting

NASA Astrophysics Data System (ADS)

Kim, T.; Joo, K.; Seo, J.; Heo, J. H.

2016-12-01

Hydrologic time series forecasting is an essential task in water resources management and it becomes more difficult due to the complexity of runoff process. Traditional stochastic models such as ARIMA family has been used as a standard approach in time series modeling and forecasting of hydrological variables. Due to the nonlinearity in hydrologic time series data, machine learning approaches has been studied with the advantage of discovering relevant features in a nonlinear relation among variables. This study aims to compare the predictability between the traditional stochastic model and the machine learning approach. Seasonal ARIMA model was used as the traditional time series model, and Random Forest model which consists of decision tree and ensemble method using multiple predictor approach was applied as the machine learning approach. In the application, monthly inflow data from 1986 to 2015 of Chungju dam in South Korea were used for modeling and forecasting. In order to evaluate the performances of the used models, one step ahead and multi-step ahead forecasting was applied. Root mean squared error and mean absolute error of two models were compared.

Kinetic energy budget during strong jet stream activity over the eastern United States

NASA Technical Reports Server (NTRS)

Fuelberg, H. E.; Scoggins, J. R.

1980-01-01

Kinetic energy budgets are computed during a cold air outbreak in association with strong jet stream activity over the eastern United States. The period is characterized by large generation of kinetic energy due to cross-contour flow. Horizontal export and dissipation of energy to subgrid scales of motion constitute the important energy sinks. Rawinsonde data at 3 and 6 h intervals during a 36 h period are used in the analysis and reveal that energy fluctuations on a time scale of less than 12 h are generally small even though the overall energy balance does change considerably during the period in conjunction with an upper level trough which moves through the region. An error analysis of the energy budget terms suggests that this major change in the budget is not due to random errors in the input data but is caused by the changing synoptic situation. The study illustrates the need to consider the time and space scales of associated weather phenomena in interpreting energy budgets obtained through use of higher frequency data.

What Randomized Benchmarking Actually Measures

DOE PAGES

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin; ...

2017-09-28

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

Quantifying errors without random sampling.

PubMed

Phillips, Carl V; LaPole, Luwanna M

2003-06-12

All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified. When a quantification does not involve sampling, error is almost never quantified and results are often reported in ways that dramatically overstate their precision. We argue that the precision implicit in typical reporting is problematic and sketch methods for quantifying the various sources of error, building up from simple examples that can be solved analytically to more complex cases. There are straightforward ways to partially quantify the uncertainty surrounding a parameter that is not characterized by random sampling, such as limiting reported significant figures. We present simple methods for doing such quantifications, and for incorporating them into calculations. More complicated methods become necessary when multiple sources of uncertainty must be combined. We demonstrate that Monte Carlo simulation, using available software, can estimate the uncertainty resulting from complicated calculations with many sources of uncertainty. We apply the method to the current estimate of the annual incidence of foodborne illness in the United States. Quantifying uncertainty from systematic errors is practical. Reporting this uncertainty would more honestly represent study results, help show the probability that estimated values fall within some critical range, and facilitate better targeting of further research.

Random errors of oceanic monthly rainfall derived from SSM/I using probability distribution functions

NASA Technical Reports Server (NTRS)

Chang, Alfred T. C.; Chiu, Long S.; Wilheit, Thomas T.

1993-01-01

Global averages and random errors associated with the monthly oceanic rain rates derived from the Special Sensor Microwave/Imager (SSM/I) data using the technique developed by Wilheit et al. (1991) are computed. Accounting for the beam-filling bias, a global annual average rain rate of 1.26 m is computed. The error estimation scheme is based on the existence of independent (morning and afternoon) estimates of the monthly mean. Calculations show overall random errors of about 50-60 percent for each 5 deg x 5 deg box. The results are insensitive to different sampling strategy (odd and even days of the month). Comparison of the SSM/I estimates with raingage data collected at the Pacific atoll stations showed a low bias of about 8 percent, a correlation of 0.7, and an rms difference of 55 percent.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies

PubMed Central

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-01-01

Abstract Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. PMID:29106476

Flux control coefficients determined by inhibitor titration: the design and analysis of experiments to minimize errors.

PubMed Central

Small, J R

1993-01-01

This paper is a study into the effects of experimental error on the estimated values of flux control coefficients obtained using specific inhibitors. Two possible techniques for analysing the experimental data are compared: a simple extrapolation method (the so-called graph method) and a non-linear function fitting method. For these techniques, the sources of systematic errors are identified and the effects of systematic and random errors are quantified, using both statistical analysis and numerical computation. It is shown that the graph method is very sensitive to random errors and, under all conditions studied, that the fitting method, even under conditions where the assumptions underlying the fitted function do not hold, outperformed the graph method. Possible ways of designing experiments to minimize the effects of experimental errors are analysed and discussed. PMID:8257434

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

NASA Astrophysics Data System (ADS)

Lychak, Oleh V.; Holyns'kiy, Ivan S.

2016-03-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.

Biometrics based key management of double random phase encoding scheme using error control codes

NASA Astrophysics Data System (ADS)

Saini, Nirmala; Sinha, Aloka

2013-08-01

In this paper, an optical security system has been proposed in which key of the double random phase encoding technique is linked to the biometrics of the user to make it user specific. The error in recognition due to the biometric variation is corrected by encoding the key using the BCH code. A user specific shuffling key is used to increase the separation between genuine and impostor Hamming distance distribution. This shuffling key is then further secured using the RSA public key encryption to enhance the security of the system. XOR operation is performed between the encoded key and the feature vector obtained from the biometrics. The RSA encoded shuffling key and the data obtained from the XOR operation are stored into a token. The main advantage of the present technique is that the key retrieval is possible only in the simultaneous presence of the token and the biometrics of the user which not only authenticates the presence of the original input but also secures the key of the system. Computational experiments showed the effectiveness of the proposed technique for key retrieval in the decryption process by using the live biometrics of the user.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Influence of Blurred Ways on Pattern Recognition of a Scale-Free Hopfield Neural Network

NASA Astrophysics Data System (ADS)

Chang, Wen-Li

2010-01-01

We investigate the influence of blurred ways on pattern recognition of a Barabási-Albert scale-free Hopfield neural network (SFHN) with a small amount of errors. Pattern recognition is an important function of information processing in brain. Due to heterogeneous degree of scale-free network, different blurred ways have different influences on pattern recognition with same errors. Simulation shows that among partial recognition, the larger loading ratio (the number of patterns to average degree P/langlekrangle) is, the smaller the overlap of SFHN is. The influence of directed (large) way is largest and the directed (small) way is smallest while random way is intermediate between them. Under the ratio of the numbers of stored patterns to the size of the network P/N is less than 0. 1 conditions, there are three families curves of the overlap corresponding to directed (small), random and directed (large) blurred ways of patterns and these curves are not associated with the size of network and the number of patterns. This phenomenon only occurs in the SFHN. These conclusions are benefit for understanding the relation between neural network structure and brain function.

Large Uncertainty in Estimating pCO2 From Carbonate Equilibria in Lakes

NASA Astrophysics Data System (ADS)

Golub, Malgorzata; Desai, Ankur R.; McKinley, Galen A.; Remucal, Christina K.; Stanley, Emily H.

2017-11-01

Most estimates of carbon dioxide (CO2) evasion from freshwaters rely on calculating partial pressure of aquatic CO2 (pCO2) from two out of three CO2-related parameters using carbonate equilibria. However, the pCO2 uncertainty has not been systematically evaluated across multiple lake types and equilibria. We quantified random errors in pH, dissolved inorganic carbon, alkalinity, and temperature from the North Temperate Lakes Long-Term Ecological Research site in four lake groups across a broad gradient of chemical composition. These errors were propagated onto pCO2 calculated from three carbonate equilibria, and for overlapping observations, compared against uncertainties in directly measured pCO2. The empirical random errors in CO2-related parameters were mostly below 2% of their median values. Resulting random pCO2 errors ranged from ±3.7% to ±31.5% of the median depending on alkalinity group and choice of input parameter pairs. Temperature uncertainty had a negligible effect on pCO2. When compared with direct pCO2 measurements, all parameter combinations produced biased pCO2 estimates with less than one third of total uncertainty explained by random pCO2 errors, indicating that systematic uncertainty dominates over random error. Multidecadal trend of pCO2 was difficult to reconstruct from uncertain historical observations of CO2-related parameters. Given poor precision and accuracy of pCO2 estimates derived from virtually any combination of two CO2-related parameters, we recommend direct pCO2 measurements where possible. To achieve consistently robust estimates of CO2 emissions from freshwater components of terrestrial carbon balances, future efforts should focus on improving accuracy and precision of CO2-related parameters (including direct pCO2) measurements and associated pCO2 calculations.

Assessing representation errors of IAGOS CO2, CO and CH4 profile observations: the impact of spatial variations in near-field emissions

NASA Astrophysics Data System (ADS)

Boschetti, Fabio; Thouret, Valerie; Nedelec, Philippe; Chen, Huilin; Gerbig, Christoph

2015-04-01

Airborne platforms have their main strength in the ability of collecting mixing ratio and meteorological data at different heights across a vertical profile, allowing an insight in the internal structure of the atmosphere. However, rental airborne platforms are usually expensive, limiting the number of flights that can be afforded and hence on the amount of data that can be collected. To avoid this disadvantage, the MOZAIC/IAGOS (Measurements of Ozone and water vapor by Airbus In-service airCraft/In-service Aircraft for a Global Observing System) program makes use of commercial airliners, providing data on a regular basis. It is therefore considered an important tool in atmospheric investigations. However, due to the nature of said platforms, MOZAIC/IAGOS's profiles are located near international airports, which are usually significant emission sources, and are in most cases close to major urban settlements, characterized by higher anthropogenic emissions compared to rural areas. When running transport models at finite resolution, these local emissions can heavily affect measurements resulting in biases in model/observation mismatch. Model/observation mismatch can include different aspects in both horizontal and vertical direction, for example spatial and temporal resolution of the modeled fluxes, or poorly represented convective transport or turbulent mixing in the boundary layer. In the framework of the IGAS (IAGOS for GMES Atmospheric Service) project, whose aim is to improve connections between data collected by MOZAIC/IAGOS and Copernicus Atmospheric Service, the present study is focused on the effect of the spatial resolution of emission fluxes, referred to here as representation error. To investigate this, the Lagrangian transport model STILT (Stochastic Time Inverted Lagrangian Transport) was coupled with EDGAR (Emission Database for Global Atmospheric Research) version-4.3 emission inventory at European regional scale. EDGAR's simulated fluxes for CO, CO2 and CH4 with a spatial resolution of 10x10 km for the time frame 2006-2011 was be aggregated into coarser and coarser grid cells in order to evaluate the representation error at different spatial scales. The dependence of representation error from wind direction and month of the year was evaluated for different location in the European domain, for both random and bias component. The representation error was then validated against the model-data mismatch derived from the comparison of MACC (Monitoring Atmospheric Composition and Climate) reanalysis with IAGOS observations for CO to investigate its suitability for modeling applications. We found that the random and bias components of the representation error show a similar pattern dependent on wind direction. In addition, we found a clear linear relationship between the representation error and the model-data mismatch for both (random and bias) components, indicating that about 50% of the model-data mismatch is related to the representation error. This suggests that the representation error derived using STILT provides useful information for better understanding causes for model-data mismatch.

Development of Na Adaptive Filter to Estimate the Percentage of Body Fat Based on Anthropometric Measures

NASA Astrophysics Data System (ADS)

do Lago, Naydson Emmerson S. P.; Kardec Barros, Allan; Sousa, Nilviane Pires S.; Junior, Carlos Magno S.; Oliveira, Guilherme; Guimares Polisel, Camila; Eder Carvalho Santana, Ewaldo

2018-01-01

This study aims to develop an algorithm of an adaptive filter to determine the percentage of body fat based on the use of anthropometric indicators in adolescents. Measurements such as body mass, height and waist circumference were collected for a better analysis. The development of this filter was based on the Wiener filter, used to produce an estimate of a random process. The Wiener filter minimizes the mean square error between the estimated random process and the desired process. The LMS algorithm was also studied for the development of the filter because it is important due to its simplicity and facility of computation. Excellent results were obtained with the filter developed, being these results analyzed and compared with the data collected.

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

Yu, Juan; Beltran, Chris J., E-mail: beltran.chris@mayo.edu; Herman, Michael G.

Purpose: To quantitatively and systematically assess dosimetric effects induced by spot positioning error as a function of spot spacing (SS) on intensity-modulated proton therapy (IMPT) plan quality and to facilitate evaluation of safety tolerance limits on spot position. Methods: Spot position errors (PE) ranging from 1 to 2 mm were simulated. Simple plans were created on a water phantom, and IMPT plans were calculated on two pediatric patients with a brain tumor of 28 and 3 cc, respectively, using a commercial planning system. For the phantom, a uniform dose was delivered to targets located at different depths from 10 tomore » 20 cm with various field sizes from 2{sup 2} to 15{sup 2} cm{sup 2}. Two nominal spot sizes, 4.0 and 6.6 mm of 1 σ in water at isocenter, were used for treatment planning. The SS ranged from 0.5 σ to 1.5 σ, which is 2–6 mm for the small spot size and 3.3–9.9 mm for the large spot size. Various perturbation scenarios of a single spot error and systematic and random multiple spot errors were studied. To quantify the dosimetric effects, percent dose error (PDE) depth profiles and the value of percent dose error at the maximum dose difference (PDE [ΔDmax]) were used for evaluation. Results: A pair of hot and cold spots was created per spot shift. PDE[ΔDmax] is found to be a complex function of PE, SS, spot size, depth, and global spot distribution that can be well defined in simple models. For volumetric targets, the PDE [ΔDmax] is not noticeably affected by the change of field size or target volume within the studied ranges. In general, reducing SS decreased the dose error. For the facility studied, given a single spot error with a PE of 1.2 mm and for both spot sizes, a SS of 1σ resulted in a 2% maximum dose error; a SS larger than 1.25 σ substantially increased the dose error and its sensitivity to PE. A similar trend was observed in multiple spot errors (both systematic and random errors). Systematic PE can lead to noticeable hot spots along the field edges, which may be near critical structures. However, random PE showed minimal dose error. Conclusions: Dose error dependence for PE was quantitatively and systematically characterized and an analytic tool was built to simulate systematic and random errors for patient-specific IMPT. This information facilitates the determination of facility specific spot position error thresholds.« less

Thermodynamic Basis for the Emergence of Genomes during Prebiotic Evolution

PubMed Central

Woo, Hyung-June; Vijaya Satya, Ravi; Reifman, Jaques

2012-01-01

The RNA world hypothesis views modern organisms as descendants of RNA molecules. The earliest RNA molecules must have been random sequences, from which the first genomes that coded for polymerase ribozymes emerged. The quasispecies theory by Eigen predicts the existence of an error threshold limiting genomic stability during such transitions, but does not address the spontaneity of changes. Following a recent theoretical approach, we applied the quasispecies theory combined with kinetic/thermodynamic descriptions of RNA replication to analyze the collective behavior of RNA replicators based on known experimental kinetics data. We find that, with increasing fidelity (relative rate of base-extension for Watson-Crick versus mismatched base pairs), replications without enzymes, with ribozymes, and with protein-based polymerases are above, near, and below a critical point, respectively. The prebiotic evolution therefore must have crossed this critical region. Over large regions of the phase diagram, fitness increases with increasing fidelity, biasing random drifts in sequence space toward ‘crystallization.’ This region encloses the experimental nonenzymatic fidelity value, favoring evolutions toward polymerase sequences with ever higher fidelity, despite error rates above the error catastrophe threshold. Our work shows that experimentally characterized kinetics and thermodynamics of RNA replication allow us to determine the physicochemical conditions required for the spontaneous crystallization of biological information. Our findings also suggest that among many potential oligomers capable of templated replication, RNAs may have evolved to form prebiotic genomes due to the value of their nonenzymatic fidelity. PMID:22693440

Testing the Recognition and Perception of Errors in Context

ERIC Educational Resources Information Center

Brandenburg, Laura C.

2015-01-01

This study tests the recognition of errors in context and whether the presence of errors affects the reader's perception of the writer's ethos. In an experimental, posttest only design, participants were randomly assigned a memo to read in an online survey: one version with errors and one version without. Of the six intentional errors in version…

Exploring Measurement Error with Cookies: A Real and Virtual Approach via Interactive Excel

ERIC Educational Resources Information Center

Sinex, Scott A; Gage, Barbara A.; Beck, Peggy J.

2007-01-01

A simple, guided-inquiry investigation using stacked sandwich cookies is employed to develop a simple linear mathematical model and to explore measurement error by incorporating errors as part of the investigation. Both random and systematic errors are presented. The model and errors are then investigated further by engaging with an interactive…

Estimation of population mean in the presence of measurement error and non response under stratified random sampling

PubMed Central

Shabbir, Javid

2018-01-01

In the present paper we propose an improved class of estimators in the presence of measurement error and non-response under stratified random sampling for estimating the finite population mean. The theoretical and numerical studies reveal that the proposed class of estimators performs better than other existing estimators. PMID:29401519

Perceptions of Randomness: Why Three Heads Are Better than Four

ERIC Educational Resources Information Center

Hahn, Ulrike; Warren, Paul A.

2009-01-01

A long tradition of psychological research has lamented the systematic errors and biases in people's perception of the characteristics of sequences generated by a random mechanism such as a coin toss. It is proposed that once the likely nature of people's actual experience of such processes is taken into account, these "errors" and "biases"…

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

Elliott, C.J.; McVey, B.; Quimby, D.C.

The level of field errors in an FEL is an important determinant of its performance. We have computed 3D performance of a large laser subsystem subjected to field errors of various types. These calculations have been guided by simple models such as SWOOP. The technique of choice is utilization of the FELEX free electron laser code that now possesses extensive engineering capabilities. Modeling includes the ability to establish tolerances of various types: fast and slow scale field bowing, field error level, beam position monitor error level, gap errors, defocusing errors, energy slew, displacement and pointing errors. Many effects of thesemore » errors on relative gain and relative power extraction are displayed and are the essential elements of determining an error budget. The random errors also depend on the particular random number seed used in the calculation. The simultaneous display of the performance versus error level of cases with multiple seeds illustrates the variations attributable to stochasticity of this model. All these errors are evaluated numerically for comprehensive engineering of the system. In particular, gap errors are found to place requirements beyond mechanical tolerances of {plus minus}25{mu}m, and amelioration of these may occur by a procedure utilizing direct measurement of the magnetic fields at assembly time. 4 refs., 12 figs.« less

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do.

PubMed

Zhao, Linlin; Wang, Wenyi; Sedykh, Alexander; Zhu, Hao

2017-06-30

Numerous chemical data sets have become available for quantitative structure-activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting.

Experimental Errors in QSAR Modeling Sets: What We Can Do and What We Cannot Do

PubMed Central

2017-01-01

Numerous chemical data sets have become available for quantitative structure–activity relationship (QSAR) modeling studies. However, the quality of different data sources may be different based on the nature of experimental protocols. Therefore, potential experimental errors in the modeling sets may lead to the development of poor QSAR models and further affect the predictions of new compounds. In this study, we explored the relationship between the ratio of questionable data in the modeling sets, which was obtained by simulating experimental errors, and the QSAR modeling performance. To this end, we used eight data sets (four continuous endpoints and four categorical endpoints) that have been extensively curated both in-house and by our collaborators to create over 1800 various QSAR models. Each data set was duplicated to create several new modeling sets with different ratios of simulated experimental errors (i.e., randomizing the activities of part of the compounds) in the modeling process. A fivefold cross-validation process was used to evaluate the modeling performance, which deteriorates when the ratio of experimental errors increases. All of the resulting models were also used to predict external sets of new compounds, which were excluded at the beginning of the modeling process. The modeling results showed that the compounds with relatively large prediction errors in cross-validation processes are likely to be those with simulated experimental errors. However, after removing a certain number of compounds with large prediction errors in the cross-validation process, the external predictions of new compounds did not show improvement. Our conclusion is that the QSAR predictions, especially consensus predictions, can identify compounds with potential experimental errors. But removing those compounds by the cross-validation procedure is not a reasonable means to improve model predictivity due to overfitting. PMID:28691113

Statistical model for speckle pattern optimization.

PubMed

Su, Yong; Zhang, Qingchuan; Gao, Zeren

2017-11-27

Image registration is the key technique of optical metrologies such as digital image correlation (DIC), particle image velocimetry (PIV), and speckle metrology. Its performance depends critically on the quality of image pattern, and thus pattern optimization attracts extensive attention. In this article, a statistical model is built to optimize speckle patterns that are composed of randomly positioned speckles. It is found that the process of speckle pattern generation is essentially a filtered Poisson process. The dependence of measurement errors (including systematic errors, random errors, and overall errors) upon speckle pattern generation parameters is characterized analytically. By minimizing the errors, formulas of the optimal speckle radius are presented. Although the primary motivation is from the field of DIC, we believed that scholars in other optical measurement communities, such as PIV and speckle metrology, will benefit from these discussions.

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.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

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

Wang, Yueqi; Lava, Pascal; Reu, Phillip

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE PAGES

Wang, Yueqi; Lava, Pascal; Reu, Phillip; ...

2015-12-23

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Variation of mutational burden in healthy human tissues suggests non-random strand segregation and allows measuring somatic mutation rates.

PubMed

Werner, Benjamin; Sottoriva, Andrea

2018-06-01

The immortal strand hypothesis poses that stem cells could produce differentiated progeny while conserving the original template strand, thus avoiding accumulating somatic mutations. However, quantitating the extent of non-random DNA strand segregation in human stem cells remains difficult in vivo. Here we show that the change of the mean and variance of the mutational burden with age in healthy human tissues allows estimating strand segregation probabilities and somatic mutation rates. We analysed deep sequencing data from healthy human colon, small intestine, liver, skin and brain. We found highly effective non-random DNA strand segregation in all adult tissues (mean strand segregation probability: 0.98, standard error bounds (0.97,0.99)). In contrast, non-random strand segregation efficiency is reduced to 0.87 (0.78,0.88) in neural tissue during early development, suggesting stem cell pool expansions due to symmetric self-renewal. Healthy somatic mutation rates differed across tissue types, ranging from 3.5 × 10-9/bp/division in small intestine to 1.6 × 10-7/bp/division in skin.

An uncertainty model of acoustic metamaterials with random parameters

NASA Astrophysics Data System (ADS)

He, Z. C.; Hu, J. Y.; Li, Eric

2018-01-01

Acoustic metamaterials (AMs) are man-made composite materials. However, the random uncertainties are unavoidable in the application of AMs due to manufacturing and material errors which lead to the variance of the physical responses of AMs. In this paper, an uncertainty model based on the change of variable perturbation stochastic finite element method (CVPS-FEM) is formulated to predict the probability density functions of physical responses of AMs with random parameters. Three types of physical responses including the band structure, mode shapes and frequency response function of AMs are studied in the uncertainty model, which is of great interest in the design of AMs. In this computation, the physical responses of stochastic AMs are expressed as linear functions of the pre-defined random parameters by using the first-order Taylor series expansion and perturbation technique. Then, based on the linear function relationships of parameters and responses, the probability density functions of the responses can be calculated by the change-of-variable technique. Three numerical examples are employed to demonstrate the effectiveness of the CVPS-FEM for stochastic AMs, and the results are validated by Monte Carlo method successfully.

Error Analysis of Indirect Broadband Monitoring of Multilayer Optical Coatings using Computer Simulations

NASA Astrophysics Data System (ADS)

Semenov, Z. V.; Labusov, V. A.

2017-11-01

Results of studying the errors of indirect monitoring by means of computer simulations are reported. The monitoring method is based on measuring spectra of reflection from additional monitoring substrates in a wide spectral range. Special software (Deposition Control Simulator) is developed, which allows one to estimate the influence of the monitoring system parameters (noise of the photodetector array, operating spectral range of the spectrometer and errors of its calibration in terms of wavelengths, drift of the radiation source intensity, and errors in the refractive index of deposited materials) on the random and systematic errors of deposited layer thickness measurements. The direct and inverse problems of multilayer coatings are solved using the OptiReOpt library. Curves of the random and systematic errors of measurements of the deposited layer thickness as functions of the layer thickness are presented for various values of the system parameters. Recommendations are given on using the indirect monitoring method for the purpose of reducing the layer thickness measurement error.

Error analysis and algorithm implementation for an improved optical-electric tracking device based on MEMS

NASA Astrophysics Data System (ADS)

Sun, Hong; Wu, Qian-zhong

2013-09-01

In order to improve the precision of optical-electric tracking device, proposing a kind of improved optical-electric tracking device based on MEMS, in allusion to the tracking error of gyroscope senor and the random drift, According to the principles of time series analysis of random sequence, establish AR model of gyro random error based on Kalman filter algorithm, then the output signals of gyro are multiple filtered with Kalman filter. And use ARM as micro controller servo motor is controlled by fuzzy PID full closed loop control algorithm, and add advanced correction and feed-forward links to improve response lag of angle input, Free-forward can make output perfectly follow input. The function of lead compensation link is to shorten the response of input signals, so as to reduce errors. Use the wireless video monitor module and remote monitoring software (Visual Basic 6.0) to monitor servo motor state in real time, the video monitor module gathers video signals, and the wireless video module will sent these signals to upper computer, so that show the motor running state in the window of Visual Basic 6.0. At the same time, take a detailed analysis to the main error source. Through the quantitative analysis of the errors from bandwidth and gyro sensor, it makes the proportion of each error in the whole error more intuitive, consequently, decrease the error of the system. Through the simulation and experiment results shows the system has good following characteristic, and it is very valuable for engineering application.

Error Sources in Asteroid Astrometry

NASA Technical Reports Server (NTRS)

Owen, William M., Jr.

2000-01-01

Asteroid astrometry, like any other scientific measurement process, is subject to both random and systematic errors, not all of which are under the observer's control. To design an astrometric observing program or to improve an existing one requires knowledge of the various sources of error, how different errors affect one's results, and how various errors may be minimized by careful observation or data reduction techniques.

Correcting the Standard Errors of 2-Stage Residual Inclusion Estimators for Mendelian Randomization Studies.

PubMed

Palmer, Tom M; Holmes, Michael V; Keating, Brendan J; Sheehan, Nuala A

2017-11-01

Mendelian randomization studies use genotypes as instrumental variables to test for and estimate the causal effects of modifiable risk factors on outcomes. Two-stage residual inclusion (TSRI) estimators have been used when researchers are willing to make parametric assumptions. However, researchers are currently reporting uncorrected or heteroscedasticity-robust standard errors for these estimates. We compared several different forms of the standard error for linear and logistic TSRI estimates in simulations and in real-data examples. Among others, we consider standard errors modified from the approach of Newey (1987), Terza (2016), and bootstrapping. In our simulations Newey, Terza, bootstrap, and corrected 2-stage least squares (in the linear case) standard errors gave the best results in terms of coverage and type I error. In the real-data examples, the Newey standard errors were 0.5% and 2% larger than the unadjusted standard errors for the linear and logistic TSRI estimators, respectively. We show that TSRI estimators with modified standard errors have correct type I error under the null. Researchers should report TSRI estimates with modified standard errors instead of reporting unadjusted or heteroscedasticity-robust standard errors. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health.

Recovering area-to-mass ratio of resident space objects through data mining

NASA Astrophysics Data System (ADS)

Peng, Hao; Bai, Xiaoli

2018-01-01

The area-to-mass ratio (AMR) of a resident space object (RSO) is an important parameter for improved space situation awareness capability due to its effect on the non-conservative forces including the atmosphere drag force and the solar radiation pressure force. However, information about AMR is often not provided in most space catalogs. The present paper investigates recovering the AMR information from the consistency error, which refers to the difference between the orbit predicted from an earlier estimate and the orbit estimated at the current epoch. A data mining technique, particularly the random forest (RF) method, is used to discover the relationship between the consistency error and the AMR. Using a simulation-based space catalog environment as the testbed, this paper demonstrates that the classification RF model can determine the RSO's category AMR and the regression RF model can generate continuous AMR values, both with good accuracies. Furthermore, the paper reveals that by recording additional information besides the consistency error, the RF model can estimate the AMR with even higher accuracy.

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks

PubMed Central

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X.; Li, Huailiang; Shi, Rui

2017-01-01

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring. PMID:28471418

Multiple Two-Way Time Message Exchange (TTME) Time Synchronization for Bridge Monitoring Wireless Sensor Networks.

PubMed

Shi, Fanrong; Tuo, Xianguo; Yang, Simon X; Li, Huailiang; Shi, Rui

2017-05-04

Wireless sensor networks (WSNs) have been widely used to collect valuable information in Structural Health Monitoring (SHM) of bridges, using various sensors, such as temperature, vibration and strain sensors. Since multiple sensors are distributed on the bridge, accurate time synchronization is very important for multi-sensor data fusion and information processing. Based on shape of the bridge, a spanning tree is employed to build linear topology WSNs and achieve time synchronization in this paper. Two-way time message exchange (TTME) and maximum likelihood estimation (MLE) are employed for clock offset estimation. Multiple TTMEs are proposed to obtain a subset of TTME observations. The time out restriction and retry mechanism are employed to avoid the estimation errors that are caused by continuous clock offset and software latencies. The simulation results show that the proposed algorithm could avoid the estimation errors caused by clock drift and minimize the estimation error due to the large random variable delay jitter. The proposed algorithm is an accurate and low complexity time synchronization algorithm for bridge health monitoring.

Global Surface Temperature Change and Uncertainties Since 1861

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M. (Technical Monitor)

2002-01-01

The objective of this talk is to analyze the warming trend and its uncertainties of the global and hemi-spheric surface temperatures. By the method of statistical optimal averaging scheme, the land surface air temperature and sea surface temperature observational data are used to compute the spatial average annual mean surface air temperature. The optimal averaging method is derived from the minimization of the mean square error between the true and estimated averages and uses the empirical orthogonal functions. The method can accurately estimate the errors of the spatial average due to observational gaps and random measurement errors. In addition, quantified are three independent uncertainty factors: urbanization, change of the in situ observational practices and sea surface temperature data corrections. Based on these uncertainties, the best linear fit to annual global surface temperature gives an increase of 0.61 +/- 0.16 C between 1861 and 2000. This lecture will also touch the topics on the impact of global change on nature and environment. as well as the latest assessment methods for the attributions of global change.

Health plan auditing: 100-percent-of-claims vs. random-sample audits.

PubMed

Sillup, George P; Klimberg, Ronald K

2011-01-01

The objective of this study was to examine the relative efficacy of two different methodologies for auditing self-funded medical claim expenses: 100-percent-of-claims auditing versus random-sampling auditing. Multiple data sets of claim errors or 'exceptions' from two Fortune-100 corporations were analysed and compared to 100 simulated audits of 300- and 400-claim random samples. Random-sample simulations failed to identify a significant number and amount of the errors that ranged from $200,000 to $750,000. These results suggest that health plan expenses of corporations could be significantly reduced if they audited 100% of claims and embraced a zero-defect approach.

Error baseline rates of five sample preparation methods used to characterize RNA virus populations.

PubMed

Kugelman, Jeffrey R; Wiley, Michael R; Nagle, Elyse R; Reyes, Daniel; Pfeffer, Brad P; Kuhn, Jens H; Sanchez-Lockhart, Mariano; Palacios, Gustavo F

2017-01-01

Individual RNA viruses typically occur as populations of genomes that differ slightly from each other due to mutations introduced by the error-prone viral polymerase. Understanding the variability of RNA virus genome populations is critical for understanding virus evolution because individual mutant genomes may gain evolutionary selective advantages and give rise to dominant subpopulations, possibly even leading to the emergence of viruses resistant to medical countermeasures. Reverse transcription of virus genome populations followed by next-generation sequencing is the only available method to characterize variation for RNA viruses. However, both steps may lead to the introduction of artificial mutations, thereby skewing the data. To better understand how such errors are introduced during sample preparation, we determined and compared error baseline rates of five different sample preparation methods by analyzing in vitro transcribed Ebola virus RNA from an artificial plasmid-based system. These methods included: shotgun sequencing from plasmid DNA or in vitro transcribed RNA as a basic "no amplification" method, amplicon sequencing from the plasmid DNA or in vitro transcribed RNA as a "targeted" amplification method, sequence-independent single-primer amplification (SISPA) as a "random" amplification method, rolling circle reverse transcription sequencing (CirSeq) as an advanced "no amplification" method, and Illumina TruSeq RNA Access as a "targeted" enrichment method. The measured error frequencies indicate that RNA Access offers the best tradeoff between sensitivity and sample preparation error (1.4-5) of all compared methods.

Subnanosecond GPS-based clock synchronization and precision deep-space tracking

NASA Technical Reports Server (NTRS)

Dunn, C. E.; Lichten, S. M.; Jefferson, D. C.; Border, J. S.

1992-01-01

Interferometric spacecraft tracking is accomplished by the Deep Space Network (DSN) by comparing the arrival time of electromagnetic spacecraft signals at ground antennas separated by baselines on the order of 8000 km. Clock synchronization errors within and between DSN stations directly impact the attainable tracking accuracy, with a 0.3-nsec error in clock synchronization resulting in an 11-nrad angular position error. This level of synchronization is currently achieved by observing a quasar which is angularly close to the spacecraft just after the spacecraft observations. By determining the differential arrival times of the random quasar signal at the stations, clock offsets and propagation delays within the atmosphere and within the DSN stations are calibrated. Recent developments in time transfer techniques may allow medium accuracy (50-100 nrad) spacecraft tracking without near-simultaneous quasar-based calibrations. Solutions are presented for a worldwide network of Global Positioning System (GPS) receivers in which the formal errors for DSN clock offset parameters are less than 0.5 nsec. Comparisons of clock rate offsets derived from GPS measurements and from very long baseline interferometry (VLBI), as well as the examination of clock closure, suggest that these formal errors are a realistic measure of GPS-based clock offset precision and accuracy. Incorporating GPS-based clock synchronization measurements into a spacecraft differential ranging system would allow tracking without near-simultaneous quasar observations. The impact on individual spacecraft navigation-error sources due to elimination of quasar-based calibrations is presented. System implementation, including calibration of station electronic delays, is discussed.

Sub-nanosecond clock synchronization and precision deep space tracking

NASA Technical Reports Server (NTRS)

Dunn, Charles; Lichten, Stephen; Jefferson, David; Border, James S.

1992-01-01

Interferometric spacecraft tracking is accomplished at the NASA Deep Space Network (DSN) by comparing the arrival time of electromagnetic spacecraft signals to ground antennas separated by baselines on the order of 8000 km. Clock synchronization errors within and between DSN stations directly impact the attainable tracking accuracy, with a 0.3 ns error in clock synchronization resulting in an 11 nrad angular position error. This level of synchronization is currently achieved by observing a quasar which is angularly close to the spacecraft just after the spacecraft observations. By determining the differential arrival times of the random quasar signal at the stations, clock synchronization and propagation delays within the atmosphere and within the DSN stations are calibrated. Recent developments in time transfer techniques may allow medium accuracy (50-100 nrad) spacecraft observations without near-simultaneous quasar-based calibrations. Solutions are presented for a global network of GPS receivers in which the formal errors in clock offset parameters are less than 0.5 ns. Comparisons of clock rate offsets derived from GPS measurements and from very long baseline interferometry and the examination of clock closure suggest that these formal errors are a realistic measure of GPS-based clock offset precision and accuracy. Incorporating GPS-based clock synchronization measurements into a spacecraft differential ranging system would allow tracking without near-simultaneous quasar observations. The impact on individual spacecraft navigation error sources due to elimination of quasar-based calibrations is presented. System implementation, including calibration of station electronic delays, is discussed.

Error reduction study employing a pseudo-random binary sequence for use in acoustic pyrometry of gases

NASA Astrophysics Data System (ADS)

Ewan, B. C. R.; Ireland, S. N.

2000-12-01

Acoustic pyrometry uses the temperature dependence of sound speed in materials to measure temperature. This is normally achieved by measuring the transit time for a sound signal over a known path length and applying the material relation between temperature and velocity to extract an "average" temperature. Sources of error associated with the measurement of mean transit time are discussed in implementing the technique in gases, one of the principal causes being background noise in typical industrial environments. A number of transmitted signal and processing strategies which can be used in the area are examined and the expected error in mean transit time associated with each technique is quantified. Transmitted signals included pulses, pure frequencies, chirps, and pseudorandom binary sequences (prbs), while processing involves edge detection and correlation. Errors arise through the misinterpretation of the positions of edge arrival or correlation peaks due to instantaneous deviations associated with background noise and these become more severe as signal to noise amplitude ratios decrease. Population errors in the mean transit time are estimated for the different measurement strategies and it is concluded that PRBS combined with correlation can provide the lowest errors when operating in high noise environments. The operation of an instrument based on PRBS transmitted signals is described and test results under controlled noise conditions are presented. These confirm the value of the strategy and demonstrate that measurements can be made with signal to noise amplitude ratios down to 0.5.

Enhanced orbit determination filter sensitivity analysis: Error budget development

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Burkhart, P. D.

1994-01-01

An error budget analysis is presented which quantifies the effects of different error sources in the orbit determination process when the enhanced orbit determination filter, recently developed, is used to reduce radio metric data. The enhanced filter strategy differs from more traditional filtering methods in that nearly all of the principal ground system calibration errors affecting the data are represented as filter parameters. Error budget computations were performed for a Mars Observer interplanetary cruise scenario for cases in which only X-band (8.4-GHz) Doppler data were used to determine the spacecraft's orbit, X-band ranging data were used exclusively, and a combined set in which the ranging data were used in addition to the Doppler data. In all three cases, the filter model was assumed to be a correct representation of the physical world. Random nongravitational accelerations were found to be the largest source of error contributing to the individual error budgets. Other significant contributors, depending on the data strategy used, were solar-radiation pressure coefficient uncertainty, random earth-orientation calibration errors, and Deep Space Network (DSN) station location uncertainty.

Cognitive fatigue effects on physical performance: A systematic review and meta-analysis.

PubMed

McMorris, Terry; Barwood, Martin; Hale, Beverley J; Dicks, Matt; Corbett, Jo

2018-05-01

Recent research has examined the effect that undertaking a cognitively fatiguing task for ≤90 min has on subsequent physical performance. Cognitive fatigue is claimed to affect subsequent physical performance by inducing energy depletion in the brain, depletion of brain catecholamine neurotransmitters or changes in motivation. Observation of the psychophysiology and neurochemistry literature questions the ability of 90 min' cognitive activity to deplete energy or catecholamine resources. The purpose of this study, therefore, was to examine the evidence for cognitive fatigue having an effect on subsequent physical performance. A systematic, meta-analytic review was undertaken. We found a small but significant pooled effect size based on comparison between physical performance post-cognitive fatigue compared to post-control (g = -0.27, SE = -0.12, 95% CI -0.49 to -0.04, Z(10) = -2.283, p < 0.05). However, the results were not heterogenous (Q(10) = 2.789, p > 0.10, Τ 2  < 0.001), suggesting that the pooled effect size does not amount to a real effect and differences are due to random error. No publication bias was evident (Kendall's τ = -0.07, p > 0.05). Thus, the results are somewhat contradictory. The pooled effect size shows a small but significant negative effect of cognitive fatigue, however tests of heterogeneity show that the results are due to random error. Future research should use neuroscientific tests to ensure that cognitive fatigue has been achieved. Copyright © 2018 Elsevier Inc. All rights reserved.

Analytical evaluation of the combined influence of polarization mode dispersion and group velocity dispersion on the bit error rate performance of optical homodyne quadrature phase-shift keying systems

NASA Astrophysics Data System (ADS)

Taher, Kazi Abu; Majumder, Satya Prasad

2017-12-01

A theoretical approach is presented to evaluate the bit error rate (BER) performance of an optical fiber transmission system with quadrature phase-shift keying (QPSK) modulation under the combined influence of polarization mode dispersion (PMD) and group velocity dispersion (GVD) in a single-mode fiber (SMF). The analysis is carried out without and with polarization division multiplexed (PDM) transmission considering a coherent homodyne receiver. The probability density function (pdf) of the random phase fluctuations due to PMD and GVD at the output of the receiver is determined analytically, considering the pdf of differential group delay (DGD) to be Maxwellian distribution and that of GVD to be Gaussian approximation. The exact pdf of the phase fluctuation due to PMD and GVD is also evaluated from its moments using a Monte Carlo simulation technique. Average BER is evaluated by averaging the conditional BER over the pdf of the random phase fluctuation. The BER performance results are evaluated for different system parameters. It is found that PDM-QPSK coherent homodyne system suffers more power penalty than the homodyne QPSK system without PDM. A PDM-QPSK system suffers a penalty of 4.3 dB whereas power penalty of QPSK system is 3.0 dB at a BER of 10-9 for DGD of 0.8 Tb and GVD of 1700 ps/nm. Analytical results are compared with the experimental results reported earlier and found to have good conformity.

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros

2004-01-01

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

Does Mckuer's Law Hold for Heart Rate Control via Biofeedback Display?

NASA Technical Reports Server (NTRS)

Courter, B. J.; Jex, H. R.

1984-01-01

Some persons can control their pulse rate with the aid of a biofeedback display. If the biofeedback display is modified to show the error between a command pulse-rate and the measured rate, a compensatory (error correcting) heart rate tracking control loop can be created. The dynamic response characteristics of this control loop when subjected to step and quasi-random disturbances were measured. The control loop includes a beat-to-beat cardiotachmeter differenced with a forcing function from a quasi-random input generator; the resulting error pulse-rate is displayed as feedback. The subject acts to null the displayed pulse-rate error, thereby closing a compensatory control loop. McRuer's Law should hold for this case. A few subjects already skilled in voluntary pulse-rate control were tested for heart-rate control response. Control-law properties are derived, such as: crossover frequency, stability margins, and closed-loop bandwidth. These are evaluated for a range of forcing functions and for step as well as random disturbances.

Synthesis of hover autopilots for rotary-wing VTOL aircraft

NASA Technical Reports Server (NTRS)

Hall, W. E.; Bryson, A. E., Jr.

1972-01-01

The practical situation is considered where imperfect information on only a few rotor and fuselage state variables is available. Filters are designed to estimate all the state variables from noisy measurements of fuselage pitch/roll angles and from noisy measurements of both fuselage and rotor pitch/roll angles. The mean square response of the vehicle to a very gusty, random wind is computed using various filter/controllers and is found to be quite satisfactory although, of course, not so good as when one has perfect information (idealized case). The second part of the report considers precision hover over a point on the ground. A vehicle model without rotor dynamics is used and feedback signals in position and integral of position error are added. The mean square response of the vehicle to a very gusty, random wind is computed, assuming perfect information feedback, and is found to be excellent. The integral error feedback gives zero position error for a steady wind, and smaller position error for a random wind.

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2009-01-01

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Meta-analysis in evidence-based healthcare: a paradigm shift away from random effects is overdue.

PubMed

Doi, Suhail A R; Furuya-Kanamori, Luis; Thalib, Lukman; Barendregt, Jan J

2017-12-01

Each year up to 20 000 systematic reviews and meta-analyses are published whose results influence healthcare decisions, thus making the robustness and reliability of meta-analytic methods one of the world's top clinical and public health priorities. The evidence synthesis makes use of either fixed-effect or random-effects statistical methods. The fixed-effect method has largely been replaced by the random-effects method as heterogeneity of study effects led to poor error estimation. However, despite the widespread use and acceptance of the random-effects method to correct this, it too remains unsatisfactory and continues to suffer from defective error estimation, posing a serious threat to decision-making in evidence-based clinical and public health practice. We discuss here the problem with the random-effects approach and demonstrate that there exist better estimators under the fixed-effect model framework that can achieve optimal error estimation. We argue for an urgent return to the earlier framework with updates that address these problems and conclude that doing so can markedly improve the reliability of meta-analytical findings and thus decision-making in healthcare.

Quantifying the morphodynamics of river restoration schemes using Unmanned Aerial Vehicles (UAVs)

NASA Astrophysics Data System (ADS)

Williams, Richard; Byrne, Patrick; Gilles, Eric; Hart, John; Hoey, Trevor; Maniatis, George; Moir, Hamish; Reid, Helen; Ves, Nikolas

2017-04-01

River restoration schemes are particularly sensitive to morphological adjustment during the first set of high-flow events that they are subjected to. Quantifying elevation change associated with morphological adjustment can contribute to improved adaptive decision making to ensure river restoration scheme objectives are achieved. To date the relatively high cost, technical demands and challenging logistics associated with acquiring repeat, high-resolution topographic surveys has resulted in a significant barrier to monitoring the three-dimensional morphodynamics of river restoration schemes. The availability of low-cost, consumer grade Unmanned Aerial Vehicles that are capable of acquiring imagery for processing using Structure-from-Motion Multi-View Stereo (SfM MVS) photogrammetry has the potential to transform the survey the morphodynamics of river restoration schemes. Application guidance does, however, need to be developed to fully exploit the advances of UAV technology and SfM MVS processing techniques. In particular, there is a need to quantify the effect of the number and spatial distribution of ground targets on vertical error. This is particularly significant because vertical errors propagate when mapping morphological change, and thus determine the evidence that is available for decision making. This presentation presents results from a study that investigated how the number and spatial distribution of targets influenced vertical error, and then used the findings to determine survey protocols for a monitoring campaign that has quantified morphological change across a number of restoration schemes. At the Swindale river restoration scheme, Cumbria, England, 31 targets were distributed across a 700 m long reach and the centre of each target was surveyed using RTK-GPS. Using the targets as General Control Points (GCPs) or checkpoints, they were divided into three different spatial patterns (centre, edge and random) and used for processing images acquired from a SenseFly Swinglet CAM UAV with a Canon IXUS 240 HS camera. Results indicate that if targets were distributed centrally then vertical distortions would be most notable in outer region of the processing domain; if an edge pattern was used then vertical errors were greatest in the central region of the processing domain; if targets were distributed randomly then errors were more evenly distributed. For this optimal random layout, vertical errors were lowest when 15 to 23 targets were used as GCPs. The best solution achieved planimetric (XY) errors of 0.006 m and vertical (Z) errors of 0.05 m. This result was used to determine target density and distribution for repeat surveys on two other restoration schemes, Whit Beck (Cumbria, England) and Allt Lorgy (Highlands, Scotland). These repeat surveys have been processed to produce DEMs of Difference (DoDs). The DoDs have been used to quantify the spatial distribution of erosion and deposition of these schemes due to high-flow events. Broader interpretation enables insight into patterns of morphological sensitivity that are related to scheme design.

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Validation of a general practice audit and data extraction tool.

PubMed

Peiris, David; Agaliotis, Maria; Patel, Bindu; Patel, Anushka

2013-11-01

We assessed how accurately a common general practitioner (GP) audit tool extracts data from two software systems. First, pathology test codes were audited at 33 practices covering nine companies. Second, a manual audit of chronic disease data from 200 random patient records at two practices was compared with audit tool data. Pathology review: all companies assigned correct codes for cholesterol, creatinine and glycated haemoglobin; four companies assigned incorrect codes for albuminuria tests, precluding accurate detection with the audit tool. Case record review: there was strong agreement between the manual audit and the tool for all variables except chronic kidney disease diagnoses, which was due to a tool-related programming error. The audit tool accurately detected most chronic disease data in two GP record systems. The one exception, however, highlights the importance of surveillance systems to promptly identify errors. This will maximise potential for audit tools to improve healthcare quality.

A path planning method used in fluid jet polishing eliminating lightweight mirror imprinting effect

NASA Astrophysics Data System (ADS)

Li, Wenzong; Fan, Bin; Shi, Chunyan; Wang, Jia; Zhuo, Bin

2014-08-01

With the development of space technology, the design of optical system tends to large aperture lightweight mirror with high dimension-thickness ratio. However, when the lightweight mirror PV value is less than λ/10 , the surface will show wavy imprinting effect obviously. Imprinting effect introduced by head-tool pressure has become a technological barrier in high-precision lightweight mirror manufacturing. Fluid jet polishing can exclude outside pressure. Presently, machining tracks often used are grating type path, screw type path and pseudo-random path. On the edge of imprinting error, the speed of adjacent path points changes too fast, which causes the machine hard to reflect quickly, brings about new path error, and increases the polishing time due to superfluous path. This paper presents a new planning path method to eliminate imprinting effect. Simulation results show that the path of the improved grating path can better eliminate imprinting effect compared to the general path.

Data-driven gradient algorithm for high-precision quantum control

NASA Astrophysics Data System (ADS)

Wu, Re-Bing; Chu, Bing; Owens, David H.; Rabitz, Herschel

2018-04-01

In the quest to achieve scalable quantum information processing technologies, gradient-based optimal control algorithms (e.g., grape) are broadly used for implementing high-precision quantum gates, but their performance is often hindered by deterministic or random errors in the system model and the control electronics. In this paper, we show that grape can be taught to be more effective by jointly learning from the design model and the experimental data obtained from process tomography. The resulting data-driven gradient optimization algorithm (d-grape) can in principle correct all deterministic gate errors, with a mild efficiency loss. The d-grape algorithm may become more powerful with broadband controls that involve a large number of control parameters, while other algorithms usually slow down due to the increased size of the search space. These advantages are demonstrated by simulating the implementation of a two-qubit controlled-not gate.

Spatiotemporal dynamics of random stimuli account for trial-to-trial variability in perceptual decision making

PubMed Central

Park, Hame; Lueckmann, Jan-Matthis; von Kriegstein, Katharina; Bitzer, Sebastian; Kiebel, Stefan J.

2016-01-01

Decisions in everyday life are prone to error. Standard models typically assume that errors during perceptual decisions are due to noise. However, it is unclear how noise in the sensory input affects the decision. Here we show that there are experimental tasks for which one can analyse the exact spatio-temporal details of a dynamic sensory noise and better understand variability in human perceptual decisions. Using a new experimental visual tracking task and a novel Bayesian decision making model, we found that the spatio-temporal noise fluctuations in the input of single trials explain a significant part of the observed responses. Our results show that modelling the precise internal representations of human participants helps predict when perceptual decisions go wrong. Furthermore, by modelling precisely the stimuli at the single-trial level, we were able to identify the underlying mechanism of perceptual decision making in more detail than standard models. PMID:26752272

VLBI height corrections due to gravitational deformation of antenna structures

NASA Astrophysics Data System (ADS)

Sarti, P.; Negusini, M.; Abbondanza, C.; Petrov, L.

2009-12-01

From an analysis of regional European VLBI data we evaluate the impact of a VLBI signal path correction model developed to account for gravitational deformations of the antenna structures. The model was derived from a combination of terrestrial surveying methods applied to telescopes at Medicina and Noto in Italy. We find that the model corrections shift the derived height components of these VLBI telescopes' reference points downward by 14.5 and 12.2 mm, respectively. No other parameter estimates nor other station positions are affected. Such systematic height errors are much larger than the formal VLBI random errors and imply the possibility of significant VLBI frame scale distortions, of major concern for the International Terrestrial Reference Frame (ITRF) and its applications. This demonstrates the urgent need to investigate gravitational deformations in other VLBI telescopes and eventually correct them in routine data analysis.

ON NONSTATIONARY STOCHASTIC MODELS FOR EARTHQUAKES.

USGS Publications Warehouse

Safak, Erdal; Boore, David M.

1986-01-01

A seismological stochastic model for earthquake ground-motion description is presented. Seismological models are based on the physical properties of the source and the medium and have significant advantages over the widely used empirical models. The model discussed here provides a convenient form for estimating structural response by using random vibration theory. A commonly used random process for ground acceleration, filtered white-noise multiplied by an envelope function, introduces some errors in response calculations for structures whose periods are longer than the faulting duration. An alternate random process, filtered shot-noise process, eliminates these errors.

In the Aftermath: Attitudes of Anesthesiologists to Supportive Strategies After an Unexpected Intraoperative Patient Death.

PubMed

Heard, Gaylene C; Thomas, Rowan D; Sanderson, Penelope M

2016-05-01

Although most anesthesiologists will have 1 catastrophic perioperative event or more during their careers, there has been little research on their attitudes to assistive strategies after the event. There are wide-ranging emotional consequences for anesthesiologists involved in an unexpected intraoperative patient death, particularly if the anesthesiologist made an error. We used a between-groups survey study design to ask whether there are different attitudes to assistive strategies when a hypothetical patient death is caused by a drug error versus not caused by an error. First, we explored attitudes to generalized supportive strategies. Second, we examined our hypothesis that the presence of an error causing the hypothetical patient death would increase the perceived social stigma and self-stigma of help-seeking. Finally, we examined the strategies to assist help-seeking. An anonymous, mailed, self-administered survey was conducted with 1600 consultant anesthesiologists in Australia on the mailing list of the Australian and New Zealand College of Anaesthetists. The participants were randomized into "error" versus "no-error" groups for the hypothetical scenario of patient death due to anaphylaxis. Nonparametric, descriptive, parametric, and inferential tests were used for data analysis. P' is used where P values were corrected for multiple comparisons. There was a usable response rate of 48.9%. When an error had caused the hypothetical patient death, participants were more likely to agree with 4 of the 5 statements about support, including need for time off (P' = 0.003), counseling (P' < 0.001), a formal strategy for assistance (P' < 0.001), and the anesthesiologist not performing further cases that day (P' = 0.047). There were no differences between groups in perceived self-stigma (P = 0.98) or social stigma (P = 0.15) of seeking counseling, whether or not an error had caused the hypothetical patient death. Finally, when an error had caused the patient death, participants were more likely to agree with 2 of the 5 statements about help-seeking, including the need for a formal, hospital-based process that provides information on where to obtain professional counseling (P' = 0.006) and the availability of after-hours counseling services (P' = 0.035). Our participants were more likely to agree with assistive strategies such as not performing further work that day, time off, counseling, formal support strategies, and availability of after-hours counseling services, when the hypothetical patient death from anaphylaxis was due to an error. The perceived stigma toward attending counseling was not affected by the presence or absence of an error as the cause of the patient death, disproving our hypothesis.

Systematic reviews of randomised clinical trials examining the effects of psychotherapeutic interventions versus "no intervention" for acute major depressive disorder and a randomised trial examining the effects of "third wave" cognitive therapy versus mentalization-based treatment for acute major depressive disorder.

PubMed

Jakobsen, Janus Christian

2014-10-01

Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy and psychodynamic therapy may be effective treatment options for major depressive disorder, but the effects have only had limited assessment in systematic reviews. The two modern forms of psychotherapy, "third wave" cognitive therapy and mentalization-based treatment, have both gained some ground as treatments of psychiatric disorders. No randomised trial has compared the effects of these two interventions for major depressive disorder. We performed two systematic reviews with meta-analyses and trial sequential analyses using The Cochrane Collaboration methodology examining the effects of cognitive therapy and psycho-dynamic therapy for major depressive disorder. We developed a thorough treatment protocol for a randomised trial with low risks of bias (systematic error) and low risks of random errors ("play of chance") examining the effects of third wave' cognitive therapy versus mentalization-based treatment for major depressive disorder. We conducted a randomised trial according to good clinical practice examining the effects of "third wave" cognitive therapy versus mentalisation-based treatment for major depressive disorder. The first systematic review included five randomised trials examining the effects of psychodynamic therapy versus "no intervention' for major depressive disorder. Altogether the five trials randomised 365 participants who in each trial received similar antidepressants as co-interventions. All trials had high risk of bias. Four trials assessed "interpersonal psychotherapy" and one trial "short psychodynamic supportive psychotherapy". Both of these interventions are different forms of psychodynamic therapy. Meta-analysis showed that psychodynamic therapy significantly reduced depressive symptoms on the Hamilton Depression Rating Scale (HDRS) compared with "no intervention" (mean difference -3.01 (95% confidence interval -3.98 to -2.03; p = 0.00001), no significant heterogeneity between trials). Trial sequential analysis confirmed this result. The second systematic review included 12 randomised trials examining the effects of cognitive therapy versus "no intervention" for major depressive disorder. Altogether a total of 669 participants were randomised. All trials had high risk of bias. Meta-analysis showed that cognitive therapy significantly reduced depressive symptoms on the HDRS compared with "no intervention" (four trials; mean difference -3.05 (95% confidence interval, -5.23 to -0.87; p = 0.006)). Trial sequential analysis could not confirm this result. The trial protocol showed that it seemed feasible to conduct a randomised trial with low risks of bias and low risks of random errors examining the effects of "third wave" cognitive therapy versus mentalization-based therapy in a setting in the Danish healthcare system. It turned out to be much more difficult to recruit participants in the randomised trial than expected. We only included about half of the planned participants. The results from the randomised trial showed that participants randomised to "third wave" therapy compared with participants randomised to mentalization-based treatment had borderline significantly lower HDRS scores at 18 weeks in an unadjusted analysis (mean difference -4.14 score; 95% CI -8.30 to 0.03; p = 0.051). In the adjusted analysis, the difference was significant (p = 0.039). Five (22.7%) of the participants randomised to "third wave" cognitive therapy had remission at 18 weeks versus none of the participants randomised to mentalization-based treatment (p = 0.049). Sequential analysis showed that these findings could be due to random errors. No significant differences between the two groups was found regarding Beck's Depression Inventory (BDI II), Symptom Checklist 90 Revised (SCL 90-R), and The World Health Organization-Five Well-being Index 1999 (WHO 5). We concluded that cognitive therapy and psychodynamic therapy might be effective interventions for depression measured on HDRS and BDI, but the review results might be erroneous due to risks of bias and random errors. Furthermore, the effects seem relatively small. The trial protocol showed that it was possible to develop a protocol for a randomised trial examining the effects of "third wave" cognitive therapy versus mentalization-based treatment with low risks of bias and low risks of random errors. Our trial results showed that "third wave" cognitive therapy might be a more effective intervention for depressive symptoms measured on the HDRS compared with mentalization-based treatment. The two interventions did not seem to differ significantly regarding BDI II, SCL 90-R, and WHO 5. More randomised trials with low risks of bias and low risks of random errors are needed to assess the effects of cognitive therapy, psychodynamic therapy, "third wave" cognitive therapy, and mentalization-based treatment.

Classification of echolocation clicks from odontocetes in the Southern California Bight.

PubMed

Roch, Marie A; Klinck, Holger; Baumann-Pickering, Simone; Mellinger, David K; Qui, Simon; Soldevilla, Melissa S; Hildebrand, John A

2011-01-01

This study presents a system for classifying echolocation clicks of six species of odontocetes in the Southern California Bight: Visually confirmed bottlenose dolphins, short- and long-beaked common dolphins, Pacific white-sided dolphins, Risso's dolphins, and presumed Cuvier's beaked whales. Echolocation clicks are represented by cepstral feature vectors that are classified by Gaussian mixture models. A randomized cross-validation experiment is designed to provide conditions similar to those found in a field-deployed system. To prevent matched conditions from inappropriately lowering the error rate, echolocation clicks associated with a single sighting are never split across the training and test data. Sightings are randomly permuted before assignment to folds in the experiment. This allows different combinations of the training and test data to be used while keeping data from each sighting entirely in the training or test set. The system achieves a mean error rate of 22% across 100 randomized three-fold cross-validation experiments. Four of the six species had mean error rates lower than the overall mean, with the presumed Cuvier's beaked whale clicks showing the best performance (<2% error rate). Long-beaked common and bottlenose dolphins proved the most difficult to classify, with mean error rates of 53% and 68%, respectively.

Effects of random tooth profile errors on the dynamic behaviors of planetary gears

NASA Astrophysics Data System (ADS)

Xun, Chao; Long, Xinhua; Hua, Hongxing

2018-02-01

In this paper, a nonlinear random model is built to describe the dynamics of planetary gear trains (PGTs), in which the time-varying mesh stiffness, tooth profile modification (TPM), tooth contact loss, and random tooth profile error are considered. A stochastic method based on the method of multiple scales (MMS) is extended to analyze the statistical property of the dynamic performance of PGTs. By the proposed multiple-scales based stochastic method, the distributions of the dynamic transmission errors (DTEs) are investigated, and the lower and upper bounds are determined based on the 3σ principle. Monte Carlo method is employed to verify the proposed method. Results indicate that the proposed method can be used to determine the distribution of the DTE of PGTs high efficiently and allow a link between the manufacturing precision and the dynamical response. In addition, the effects of tooth profile modification on the distributions of vibration amplitudes and the probability of tooth contact loss with different manufacturing tooth profile errors are studied. The results show that the manufacturing precision affects the distribution of dynamic transmission errors dramatically and appropriate TPMs are helpful to decrease the nominal value and the deviation of the vibration amplitudes.

A multi-site analysis of random error in tower-based measurements of carbon and energy fluxes

Treesearch

Andrew D. Richardson; David Y. Hollinger; George G. Burba; Kenneth J. Davis; Lawrence B. Flanagan; Gabriel G. Katul; J. William Munger; Daniel M. Ricciuto; Paul C. Stoy; Andrew E. Suyker; Shashi B. Verma; Steven C. Wofsy; Steven C. Wofsy

2006-01-01

Measured surface-atmosphere fluxes of energy (sensible heat, H, and latent heat, LE) and CO2 (FCO2) represent the ``true?? flux plus or minus potential random and systematic measurement errors. Here, we use data from seven sites in the AmeriFlux network, including five forested sites (two of which include ``tall tower?? instrumentation), one grassland site, and one...

Statistical error model for a solar electric propulsion thrust subsystem

NASA Technical Reports Server (NTRS)

Bantell, M. H.

1973-01-01

The solar electric propulsion thrust subsystem statistical error model was developed as a tool for investigating the effects of thrust subsystem parameter uncertainties on navigation accuracy. The model is currently being used to evaluate the impact of electric engine parameter uncertainties on navigation system performance for a baseline mission to Encke's Comet in the 1980s. The data given represent the next generation in statistical error modeling for low-thrust applications. Principal improvements include the representation of thrust uncertainties and random process modeling in terms of random parametric variations in the thrust vector process for a multi-engine configuration.

Asteroid thermal modeling in the presence of reflected sunlight

NASA Astrophysics Data System (ADS)

Myhrvold, Nathan

2018-03-01

A new derivation of simple asteroid thermal models is presented, investigating the need to account correctly for Kirchhoff's law of thermal radiation when IR observations contain substantial reflected sunlight. The framework applies to both the NEATM and related thermal models. A new parameterization of these models eliminates the dependence of thermal modeling on visible absolute magnitude H, which is not always available. Monte Carlo simulations are used to assess the potential impact of violating Kirchhoff's law on estimates of physical parameters such as diameter and IR albedo, with an emphasis on NEOWISE results. The NEOWISE papers use ten different models, applied to 12 different combinations of WISE data bands, in 47 different combinations. The most prevalent combinations are simulated and the accuracy of diameter estimates is found to be depend critically on the model and data band combination. In the best case of full thermal modeling of all four band the errors in an idealized model the 1σ (68.27%) confidence interval is -5% to +6%, but this combination is just 1.9% of NEOWISE results. Other combinations representing 42% of the NEOWISE results have about twice the CI at -10% to +12%, before accounting for errors due to irregular shape or other real world effects that are not simulated. The model and data band combinations found for the majority of NEOWISE results have much larger systematic and random errors. Kirchhoff's law violation by NEOWISE models leads to errors in estimation accuracy that are strongest for asteroids with W1, W2 band emissivity ɛ12 in both the lowest (0.605 ≤ɛ12 ≤ 0 . 780), and highest decile (0.969 ≤ɛ12 ≤ 0 . 988), corresponding to the highest and lowest deciles of near-IR albedo pIR. Systematic accuracy error between deciles ranges from a low of 5% to as much as 45%, and there are also differences in the random errors. Kirchhoff's law effects also produce large errors in NEOWISE estimates of pIR, particularly for high values. IR observations of asteroids in bands that have substantial reflected sunlight can largely avoid these problems by adopting the Kirchhoff law compliant modeling framework presented here, which is conceptually straightforward and comes without computational cost.

An Analysis of Computational Errors in the Use of Division Algorithms by Fourth-Grade Students.

ERIC Educational Resources Information Center

Stefanich, Greg P.; Rokusek, Teri

1992-01-01

Presents a study that analyzed errors made by randomly chosen fourth grade students (25 of 57) while using the division algorithm and investigated the effect of remediation on identified systematic errors. Results affirm that error pattern diagnosis and directed remediation lead to new learning and long-term retention. (MDH)

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Correcting for deformation in skin-based marker systems.

PubMed

Alexander, E J; Andriacchi, T P

2001-03-01

A new technique is described that reduces error due to skin movement artifact in the opto-electronic measurement of in vivo skeletal motion. This work builds on a previously described point cluster technique marker set and estimation algorithm by extending the transformation equations to the general deformation case using a set of activity-dependent deformation models. Skin deformation during activities of daily living are modeled as consisting of a functional form defined over the observation interval (the deformation model) plus additive noise (modeling error). The method is described as an interval deformation technique. The method was tested using simulation trials with systematic and random components of deformation error introduced into marker position vectors. The technique was found to substantially outperform methods that require rigid-body assumptions. The method was tested in vivo on a patient fitted with an external fixation device (Ilizarov). Simultaneous measurements from markers placed on the Ilizarov device (fixed to bone) were compared to measurements derived from skin-based markers. The interval deformation technique reduced the errors in limb segment pose estimate by 33 and 25% compared to the classic rigid-body technique for position and orientation, respectively. This newly developed method has demonstrated that by accounting for the changing shape of the limb segment, a substantial improvement in the estimates of in vivo skeletal movement can be achieved.

Understanding native Russian listeners' errors on an English word recognition test: model-based analysis of phoneme confusion.

PubMed

Shi, Lu-Feng; Morozova, Natalia

2012-08-01

Word recognition is a basic component in a comprehensive hearing evaluation, but data are lacking for listeners speaking two languages. This study obtained such data for Russian natives in the US and analysed the data using the perceptual assimilation model (PAM) and speech learning model (SLM). Listeners were randomly presented 200 NU-6 words in quiet. Listeners responded verbally and in writing. Performance was scored on words and phonemes (word-initial consonants, vowels, and word-final consonants). Seven normal-hearing, adult monolingual English natives (NM), 16 English-dominant (ED), and 15 Russian-dominant (RD) Russian natives participated. ED and RD listeners differed significantly in their language background. Consistent with the SLM, NM outperformed ED listeners and ED outperformed RD listeners, whether responses were scored on words or phonemes. NM and ED listeners shared similar phoneme error patterns, whereas RD listeners' errors had unique patterns that could be largely understood via the PAM. RD listeners had particular difficulty differentiating vowel contrasts /i-I/, /æ-ε/, and /ɑ-Λ/, word-initial consonant contrasts /p-h/ and /b-f/, and word-final contrasts /f-v/. Both first-language phonology and second-language learning history affect word and phoneme recognition. Current findings may help clinicians differentiate word recognition errors due to language background from hearing pathologies.

Physical layer one-time-pad data encryption through synchronized semiconductor laser networks

NASA Astrophysics Data System (ADS)

Argyris, Apostolos; Pikasis, Evangelos; Syvridis, Dimitris

2016-02-01

Semiconductor lasers (SL) have been proven to be a key device in the generation of ultrafast true random bit streams. Their potential to emit chaotic signals under conditions with desirable statistics, establish them as a low cost solution to cover various needs, from large volume key generation to real-time encrypted communications. Usually, only undemanding post-processing is needed to convert the acquired analog timeseries to digital sequences that pass all established tests of randomness. A novel architecture that can generate and exploit these true random sequences is through a fiber network in which the nodes are semiconductor lasers that are coupled and synchronized to central hub laser. In this work we show experimentally that laser nodes in such a star network topology can synchronize with each other through complex broadband signals that are the seed to true random bit sequences (TRBS) generated at several Gb/s. The potential for each node to access real-time generated and synchronized with the rest of the nodes random bit streams, through the fiber optic network, allows to implement an one-time-pad encryption protocol that mixes the synchronized true random bit sequence with real data at Gb/s rates. Forward-error correction methods are used to reduce the errors in the TRBS and the final error rate at the data decoding level. An appropriate selection in the sampling methodology and properties, as well as in the physical properties of the chaotic seed signal through which network locks in synchronization, allows an error free performance.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

NASA Astrophysics Data System (ADS)

Brokamp, Cole; Jandarov, Roman; Rao, M. B.; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches.

PubMed

Brokamp, Cole; Jandarov, Roman; Rao, M B; LeMasters, Grace; Ryan, Patrick

2017-02-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment.

Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches

PubMed Central

Brokamp, Cole; Jandarov, Roman; Rao, M.B.; LeMasters, Grace; Ryan, Patrick

2017-01-01

Exposure assessment for elemental components of particulate matter (PM) using land use modeling is a complex problem due to the high spatial and temporal variations in pollutant concentrations at the local scale. Land use regression (LUR) models may fail to capture complex interactions and non-linear relationships between pollutant concentrations and land use variables. The increasing availability of big spatial data and machine learning methods present an opportunity for improvement in PM exposure assessment models. In this manuscript, our objective was to develop a novel land use random forest (LURF) model and compare its accuracy and precision to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio. PM smaller than 2.5 μm (PM2.5) and eleven elemental components were measured at 24 sampling stations from the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS). Over 50 different predictors associated with transportation, physical features, community socioeconomic characteristics, greenspace, land cover, and emission point sources were used to construct LUR and LURF models. Cross validation was used to quantify and compare model performance. LURF and LUR models were created for aluminum (Al), copper (Cu), iron (Fe), potassium (K), manganese (Mn), nickel (Ni), lead (Pb), sulfur (S), silicon (Si), vanadium (V), zinc (Zn), and total PM2.5 in the CCAAPS study area. LURF utilized a more diverse and greater number of predictors than LUR and LURF models for Al, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all showed a decrease in fractional predictive error of at least 5% compared to their LUR models. LURF models for Al, Cu, Fe, K, Mn, Pb, Si, Zn, TRAP, and PM2.5 all had a cross validated fractional predictive error less than 30%. Furthermore, LUR models showed a differential exposure assessment bias and had a higher prediction error variance. Random forest and other machine learning methods may provide more accurate exposure assessment. PMID:28959135

A predictability study of Lorenz's 28-variable model as a dynamical system

NASA Technical Reports Server (NTRS)

Krishnamurthy, V.

1993-01-01

The dynamics of error growth in a two-layer nonlinear quasi-geostrophic model has been studied to gain an understanding of the mathematical theory of atmospheric predictability. The growth of random errors of varying initial magnitudes has been studied, and the relation between this classical approach and the concepts of the nonlinear dynamical systems theory has been explored. The local and global growths of random errors have been expressed partly in terms of the properties of an error ellipsoid and the Liapunov exponents determined by linear error dynamics. The local growth of small errors is initially governed by several modes of the evolving error ellipsoid but soon becomes dominated by the longest axis. The average global growth of small errors is exponential with a growth rate consistent with the largest Liapunov exponent. The duration of the exponential growth phase depends on the initial magnitude of the errors. The subsequent large errors undergo a nonlinear growth with a steadily decreasing growth rate and attain saturation that defines the limit of predictability. The degree of chaos and the largest Liapunov exponent show considerable variation with change in the forcing, which implies that the time variation in the external forcing can introduce variable character to the predictability.

Adjustment of Measurements with Multiplicative Errors: Error Analysis, Estimates of the Variance of Unit Weight, and Effect on Volume Estimation from LiDAR-Type Digital Elevation Models

PubMed Central

Shi, Yun; Xu, Peiliang; Peng, Junhuan; Shi, Chuang; Liu, Jingnan

2014-01-01

Modern observation technology has verified that measurement errors can be proportional to the true values of measurements such as GPS, VLBI baselines and LiDAR. Observational models of this type are called multiplicative error models. This paper is to extend the work of Xu and Shimada published in 2000 on multiplicative error models to analytical error analysis of quantities of practical interest and estimates of the variance of unit weight. We analytically derive the variance-covariance matrices of the three least squares (LS) adjustments, the adjusted measurements and the corrections of measurements in multiplicative error models. For quality evaluation, we construct five estimators for the variance of unit weight in association of the three LS adjustment methods. Although LiDAR measurements are contaminated with multiplicative random errors, LiDAR-based digital elevation models (DEM) have been constructed as if they were of additive random errors. We will simulate a model landslide, which is assumed to be surveyed with LiDAR, and investigate the effect of LiDAR-type multiplicative error measurements on DEM construction and its effect on the estimate of landslide mass volume from the constructed DEM. PMID:24434880

Liquid Medication Dosing Errors by Hispanic Parents: Role of Health Literacy and English Proficiency

PubMed Central

Harris, Leslie M.; Dreyer, Benard; Mendelsohn, Alan; Bailey, Stacy C.; Sanders, Lee M.; Wolf, Michael S.; Parker, Ruth M.; Patel, Deesha A.; Kim, Kwang Youn A.; Jimenez, Jessica J.; Jacobson, Kara; Smith, Michelle; Yin, H. Shonna

2016-01-01

Objective Hispanic parents in the US are disproportionately affected by low health literacy and limited English proficiency (LEP). We examined associations between health literacy, LEP, and liquid medication dosing errors in Hispanic parents. Methods Cross-sectional analysis of data from a multisite randomized controlled experiment to identify best practices for the labeling/dosing of pediatric liquid medications (SAFE Rx for Kids study); 3 urban pediatric clinics. Analyses were limited to Hispanic parents of children <8 years, with health literacy and LEP data (n=1126). Parents were randomized to 5 groups that varied by pairing of units of measurement on the label/dosing tool. Each parent measured 9 doses [3 amounts (2.5,5,7.5 mL) using 3 tools (2 syringes (0.2,0.5 mL increment), 1 cup)] in random order. Dependent variable: Dosing error=>20% dose deviation. Predictor variables: health literacy (Newest Vital Sign) [limited=0–3; adequate=4–6], LEP (speaks English less than “very well”). Results 83.1% made dosing errors (mean(SD) errors/parent=2.2(1.9)). Parents with limited health literacy and LEP had the greatest odds of making a dosing error compared to parents with adequate health literacy who were English proficient (% trials with errors/parent=28.8 vs. 12.9%; AOR=2.2[1.7–2.8]). Parents with limited health literacy who were English proficient were also more likely to make errors (% trials with errors/parent=18.8%; AOR=1.4[1.1–1.9]). Conclusion Dosing errors are common among Hispanic parents; those with both LEP and limited health literacy are at particular risk. Further study is needed to examine how the redesign of medication labels and dosing tools could reduce literacy and language-associated disparities in dosing errors. PMID:28477800

Combinatorial neural codes from a mathematical coding theory perspective.

PubMed

Curto, Carina; Itskov, Vladimir; Morrison, Katherine; Roth, Zachary; Walker, Judy L

2013-07-01

Shannon's seminal 1948 work gave rise to two distinct areas of research: information theory and mathematical coding theory. While information theory has had a strong influence on theoretical neuroscience, ideas from mathematical coding theory have received considerably less attention. Here we take a new look at combinatorial neural codes from a mathematical coding theory perspective, examining the error correction capabilities of familiar receptive field codes (RF codes). We find, perhaps surprisingly, that the high levels of redundancy present in these codes do not support accurate error correction, although the error-correcting performance of receptive field codes catches up to that of random comparison codes when a small tolerance to error is introduced. However, receptive field codes are good at reflecting distances between represented stimuli, while the random comparison codes are not. We suggest that a compromise in error-correcting capability may be a necessary price to pay for a neural code whose structure serves not only error correction, but must also reflect relationships between stimuli.

Effects of learning climate and registered nurse staffing on medication errors.

PubMed

Chang, Yunkyung; Mark, Barbara

2011-01-01

Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.

Supersonic Retropropulsion Experimental Results from the NASA Langley Unitary Plan Wind Tunnel

NASA Technical Reports Server (NTRS)

Berry, Scott A.; Rhode, Matthew N.; Edquist, Karl T.; Player, Charles J.

2011-01-01

A new supersonic retropropulsion experimental effort, intended to provide code validation data, was recently completed in the Langley Research Center Unitary Plan Wind Tunnel Test Section 2 over the Mach number range from 2.4 to 4.6. The experimental model was designed using insights gained from pre-test computations, which were instrumental for sizing and refining the model to minimize tunnel wall interference and internal flow separation concerns. A 5-in diameter 70-deg sphere-cone forebody with a roughly 10-in long cylindrical aftbody was the baseline configuration selected for this study. The forebody was designed to accommodate up to four 4:1 area ratio supersonic nozzles. Primary measurements for this model were a large number of surface pressures on the forebody and aftbody. Supplemental data included high-speed Schlieren video and internal pressures and temperatures. The run matrix was developed to allow for the quantification of various sources of experimental uncertainty, such as random errors due to run-to-run variations and bias errors due to flow field or model misalignments. Preliminary results and observations from the test are presented, while detailed data and uncertainty analyses are ongoing.

Student understanding of the direction of the magnetic force on a charged particle

NASA Astrophysics Data System (ADS)

Scaife, Thomas M.; Heckler, Andrew F.

2010-08-01

We study student understanding of the direction of the magnetic force experienced by a charged particle moving through a homogeneous magnetic field in both the magnetic pole and field line representations of the magnetic field. In five studies, we administer a series of simple questions in either written or interview format. Our results indicate that although students begin at the same low level of performance in both representations, they answer correctly more often in the field line representation than in the pole representation after instruction. This difference is due in part to more students believing that charges are attracted to magnetic poles than believing that charges are pushed along magnetic field lines. Although traditional instruction is fairly effective in teaching students to answer correctly up to a few weeks following instruction, especially for the field line representation, some students revert to their initial misconceptions several months after instruction. The responses reveal persistent and largely random sign errors in the direction of the force. The sign errors are largely nonsystematic and due to confusion about the direction of the magnetic field and the execution and choice of the right-hand rule and lack of recognition of the noncommutativity of the cross product.

Parameter identification of JONSWAP spectrum acquired by airborne LIDAR

NASA Astrophysics Data System (ADS)

Yu, Yang; Pei, Hailong; Xu, Chengzhong

2017-12-01

In this study, we developed the first linear Joint North Sea Wave Project (JONSWAP) spectrum (JS), which involves a transformation from the JS solution to the natural logarithmic scale. This transformation is convenient for defining the least squares function in terms of the scale and shape parameters. We identified these two wind-dependent parameters to better understand the wind effect on surface waves. Due to its efficiency and high-resolution, we employed the airborne Light Detection and Ranging (LIDAR) system for our measurements. Due to the lack of actual data, we simulated ocean waves in the MATLAB environment, which can be easily translated into industrial programming language. We utilized the Longuet-Higgin (LH) random-phase method to generate the time series of wave records and used the fast Fourier transform (FFT) technique to compute the power spectra density. After validating these procedures, we identified the JS parameters by minimizing the mean-square error of the target spectrum to that of the estimated spectrum obtained by FFT. We determined that the estimation error is relative to the amount of available wave record data. Finally, we found the inverse computation of wind factors (wind speed and wind fetch length) to be robust and sufficiently precise for wave forecasting.

Sodium Absorption from the Exoplanetary Atmosphere of HD 189733b Detected in the Optical Transmission Spectrum

NASA Astrophysics Data System (ADS)

Redfield, Seth; Endl, Michael; Cochran, William D.; Koesterke, Lars

2008-01-01

We present the first ground-based detection of sodium absorption in the transmission spectrum of an extrasolar planet. Absorption due to the atmosphere of the extrasolar planet HD 189733b is detected in both lines of the Na I doublet. High spectral resolution observations were taken of 11 transits with the High Resolution Spectrograph (HRS) on the 9.2 m Hobby-Eberly Telescope (HET). The Na I absorption in the transmission spectrum due to HD 189733b is (- 67.2 +/- 20.7) × 10-5 deeper in the "narrow" spectral band that encompasses both lines relative to adjacent bands. The 1 σ error includes both random and systematic errors, and the detection is >3 σ. This amount of relative absorption in Na I for HD 189733b is ~3 times larger than that detected for HD 209458b by Charbonneau et al. (2002) and indicates that these two hot Jupiters may have significantly different atmospheric properties. Based on observations obtained with the Hobby-Eberly Telescope, which is a joint project of the University of Texas at Austin, the Pennsylvania State University, Stanford University, Ludwig-Maximilians-Universität München, and Georg-August-Universität Göttingen.

The (mis)reporting of statistical results in psychology journals.

PubMed

Bakker, Marjan; Wicherts, Jelte M

2011-09-01

In order to study the prevalence, nature (direction), and causes of reporting errors in psychology, we checked the consistency of reported test statistics, degrees of freedom, and p values in a random sample of high- and low-impact psychology journals. In a second study, we established the generality of reporting errors in a random sample of recent psychological articles. Our results, on the basis of 281 articles, indicate that around 18% of statistical results in the psychological literature are incorrectly reported. Inconsistencies were more common in low-impact journals than in high-impact journals. Moreover, around 15% of the articles contained at least one statistical conclusion that proved, upon recalculation, to be incorrect; that is, recalculation rendered the previously significant result insignificant, or vice versa. These errors were often in line with researchers' expectations. We classified the most common errors and contacted authors to shed light on the origins of the errors.

Random synaptic feedback weights support error backpropagation for deep learning

NASA Astrophysics Data System (ADS)

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-11-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning.

Random synaptic feedback weights support error backpropagation for deep learning

PubMed Central

Lillicrap, Timothy P.; Cownden, Daniel; Tweed, Douglas B.; Akerman, Colin J.

2016-01-01

The brain processes information through multiple layers of neurons. This deep architecture is representationally powerful, but complicates learning because it is difficult to identify the responsible neurons when a mistake is made. In machine learning, the backpropagation algorithm assigns blame by multiplying error signals with all the synaptic weights on each neuron's axon and further downstream. However, this involves a precise, symmetric backward connectivity pattern, which is thought to be impossible in the brain. Here we demonstrate that this strong architectural constraint is not required for effective error propagation. We present a surprisingly simple mechanism that assigns blame by multiplying errors by even random synaptic weights. This mechanism can transmit teaching signals across multiple layers of neurons and performs as effectively as backpropagation on a variety of tasks. Our results help reopen questions about how the brain could use error signals and dispel long-held assumptions about algorithmic constraints on learning. PMID:27824044

Construction of the Second Quito Astrolabe Catalogue

NASA Astrophysics Data System (ADS)

Kolesnik, Y. B.

1994-03-01

A method for astrolabe catalogue construction is presented. It is based on classical concepts, but the model of conditional equations for the group reduction is modified, additional parameters being introduced in the step- wise regressions. The chain adjustment is neglected, and the advantages of this approach are discussed. The method has been applied to the data obtained with the astrolabe of the Quito Astronomical Observatory from 1964 to 1983. Various characteristics of the catalogue produced with this method are compared with those due to the rigorous classical method. Some improvement both in systematic and random errors is outlined.

Stereographic cloud heights from the imagery of two scan-synchronized geostationary satellites

NASA Technical Reports Server (NTRS)

Minzner, R. A.; Teagle, R. D.; Steranka, J.; Shenk, W. E.

1979-01-01

Scan synchronization of the sensors of two SMS-GOES satellites yields imagery from which cloud heights can be derived stereographically with a theoretical two-sigma random uncertainty of + or - 0.25 km for pairs of satellites separated by 60 degrees of longitude. Systematic height errors due to cloud motion can be kept below 100 m for all clouds with east-west components of speed below hurricane speed, provided the scan synchronization is within 40 seconds at the mid-point latitude, and the spin axis of each satellite is parallel to that of the earth.

How to measure a-few-nanometer-small LER occurring in EUV lithography processed feature

NASA Astrophysics Data System (ADS)

Kawada, Hiroki; Kawasaki, Takahiro; Kakuta, Junichi; Ikota, Masami; Kondo, Tsuyoshi

2018-03-01

For EUV lithography features we want to decrease the dose and/or energy of CD-SEM's probe beam because LER decreases with severe resist-material's shrink. Under such conditions, however, measured LER increases from true LER, due to LER bias that is fake LER caused by random noise in SEM image. A gap error occurs between the right and the left LERs. In this work we propose new procedures to obtain true LER by excluding the LER bias from the measured LER. To verify it we propose a LER's reference-metrology using TEM.

Electronic laboratory system reduces errors in National Tuberculosis Program: a cluster randomized controlled trial.

PubMed

Blaya, J A; Shin, S S; Yale, G; Suarez, C; Asencios, L; Contreras, C; Rodriguez, P; Kim, J; Cegielski, P; Fraser, H S F

2010-08-01

To evaluate the impact of the e-Chasqui laboratory information system in reducing reporting errors compared to the current paper system. Cluster randomized controlled trial in 76 health centers (HCs) between 2004 and 2008. Baseline data were collected every 4 months for 12 months. HCs were then randomly assigned to intervention (e-Chasqui) or control (paper). Further data were collected for the same months the following year. Comparisons were made between intervention and control HCs, and before and after the intervention. Intervention HCs had respectively 82% and 87% fewer errors in reporting results for drug susceptibility tests (2.1% vs. 11.9%, P = 0.001, OR 0.17, 95%CI 0.09-0.31) and cultures (2.0% vs. 15.1%, P < 0.001, OR 0.13, 95%CI 0.07-0.24), than control HCs. Preventing missing results through online viewing accounted for at least 72% of all errors. e-Chasqui users sent on average three electronic error reports per week to the laboratories. e-Chasqui reduced the number of missing laboratory results at point-of-care health centers. Clinical users confirmed viewing electronic results not available on paper. Reporting errors to the laboratory using e-Chasqui promoted continuous quality improvement. The e-Chasqui laboratory information system is an important part of laboratory infrastructure improvements to support multidrug-resistant tuberculosis care in Peru.

Effect of magnesium added to local anesthetics for caudal anesthesia on postoperative pain in pediatric surgical patients: A systematic review and meta-analysis with Trial Sequential Analysis

PubMed Central

Mihara, Takahiro; Nakamura, Nobuhito; Ka, Koui; Goto, Takahisa

2018-01-01

Background Magnesium has been investigated as an adjuvant for neuraxial anesthesia, but the effect of caudal magnesium on postoperative pain is inconsistent. The aim of this systematic review and meta-analysis was to evaluate the analgesic effect of caudal magnesium. Methods We searched six databases, including trial registration sites. Randomized clinical trials reporting the effect of caudal magnesium on postoperative pain after general anesthesia were eligible. The risk ratio for use of rescue analgesics after surgery was combined using a random-effects model. We also assessed adverse events. The I2 statistic was used to assess heterogeneity. We assessed risk of bias with Cochrane domains. We controlled type I and II errors due to sparse data and repetitive testing with Trial Sequential Analysis. We assessed the quality of evidence with GRADE. Results Four randomized controlled trials (247 patients) evaluated the need for rescue analgesics. In all four trials, 50 mg of magnesium was administered with caudal ropivacaine. The results suggested that the need for rescue analgesia was reduced significantly by caudal magnesium administration (risk ratio 0.45; 95% confidence interval 0.24–0.86). There was considerable heterogeneity as indicated by an I2 value of 62.5%. The Trial Sequential Analysis-adjusted confidence interval was 0.04–5.55, indicating that further trials are required. The quality of evidence was very low. The rate of adverse events was comparable between treatment groups. Conclusion Caudal magnesium may reduce the need for rescue analgesia after surgery, but further randomized clinical trials with a low risk of bias and a low risk of random errors are necessary to assess the effect of caudal magnesium on postoperative pain and adverse events. Trial registration University Hospital Medical Information Network Clinical Trials Registry UMIN000025344. PMID:29293586

Effect of MLC leaf position, collimator rotation angle, and gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma

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

Bai, Sen; Li, Guangjun; Wang, Maojie

The purpose of this study was to investigate the effect of multileaf collimator (MLC) leaf position, collimator rotation angle, and accelerator gantry rotation angle errors on intensity-modulated radiotherapy plans for nasopharyngeal carcinoma. To compare dosimetric differences between the simulating plans and the clinical plans with evaluation parameters, 6 patients with nasopharyngeal carcinoma were selected for simulation of systematic and random MLC leaf position errors, collimator rotation angle errors, and accelerator gantry rotation angle errors. There was a high sensitivity to dose distribution for systematic MLC leaf position errors in response to field size. When the systematic MLC position errors weremore » 0.5, 1, and 2 mm, respectively, the maximum values of the mean dose deviation, observed in parotid glands, were 4.63%, 8.69%, and 18.32%, respectively. The dosimetric effect was comparatively small for systematic MLC shift errors. For random MLC errors up to 2 mm and collimator and gantry rotation angle errors up to 0.5°, the dosimetric effect was negligible. We suggest that quality control be regularly conducted for MLC leaves, so as to ensure that systematic MLC leaf position errors are within 0.5 mm. Because the dosimetric effect of 0.5° collimator and gantry rotation angle errors is negligible, it can be concluded that setting a proper threshold for allowed errors of collimator and gantry rotation angle may increase treatment efficacy and reduce treatment time.« less

Combined Uncertainty and A-Posteriori Error Bound Estimates for General CFD Calculations: Theory and Software Implementation

NASA Technical Reports Server (NTRS)

Barth, Timothy J.

2014-01-01

This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.

Evaluation of Bayesian Sequential Proportion Estimation Using Analyst Labels

NASA Technical Reports Server (NTRS)

Lennington, R. K.; Abotteen, K. M. (Principal Investigator)

1980-01-01

The author has identified the following significant results. A total of ten Large Area Crop Inventory Experiment Phase 3 blind sites and analyst-interpreter labels were used in a study to compare proportional estimates obtained by the Bayes sequential procedure with estimates obtained from simple random sampling and from Procedure 1. The analyst error rate using the Bayes technique was shown to be no greater than that for the simple random sampling. Also, the segment proportion estimates produced using this technique had smaller bias and mean squared errors than the estimates produced using either simple random sampling or Procedure 1.

Center of mass perception and inertial frames of reference.

PubMed

Bingham, G P; Muchisky, M M

1993-11-01

Center of mass perception was investigated by varying the shape, size, and orientation of planar objects. Shape was manipulated to investigate symmetries as information. The number of reflective symmetry axes, the amount of rotational symmetry, and the presence of radial symmetry were varied. Orientation affected systematic errors. Judgments tended to undershoot the center of mass. Random errors increased with size and decreased with symmetry. Size had no effect on random errors for maximally symmetric objects, although orientation did. The spatial distributions of judgments were elliptical. Distribution axes were found to align with the principle moments of inertia. Major axes tended to align with gravity in maximally symmetric objects. A functional and physical account was given in terms of the repercussions of error. Overall, judgments were very accurate.

Gene-targeted Random Mutagenesis to Select Heterochromatin-destabilizing Proteasome Mutants in Fission Yeast.

PubMed

Seo, Hogyu David; Lee, Daeyoup

2018-05-15

Random mutagenesis of a target gene is commonly used to identify mutations that yield the desired phenotype. Of the methods that may be used to achieve random mutagenesis, error-prone PCR is a convenient and efficient strategy for generating a diverse pool of mutants (i.e., a mutant library). Error-prone PCR is the method of choice when a researcher seeks to mutate a pre-defined region, such as the coding region of a gene while leaving other genomic regions unaffected. After the mutant library is amplified by error-prone PCR, it must be cloned into a suitable plasmid. The size of the library generated by error-prone PCR is constrained by the efficiency of the cloning step. However, in the fission yeast, Schizosaccharomyces pombe, the cloning step can be replaced by the use of a highly efficient one-step fusion PCR to generate constructs for transformation. Mutants of desired phenotypes may then be selected using appropriate reporters. Here, we describe this strategy in detail, taking as an example, a reporter inserted at centromeric heterochromatin.

Smooth empirical Bayes estimation of observation error variances in linear systems

NASA Technical Reports Server (NTRS)

Martz, H. F., Jr.; Lian, M. W.

1972-01-01

A smooth empirical Bayes estimator was developed for estimating the unknown random scale component of each of a set of observation error variances. It is shown that the estimator possesses a smaller average squared error loss than other estimators for a discrete time linear system.

Early star catalogues of the southern sky. De Houtman, Kepler (second and third classes), and Halley

NASA Astrophysics Data System (ADS)

Verbunt, F.; van Gent, R. H.

2011-06-01

De Houtman in 1603, Kepler in 1627 and Halley in 1679 published the earliest modern catalogues of the southern sky. We provide machine-readable versions of these catalogues, make some comparisons between them, and briefly discuss their accuracy on the basis of comparison with data from the modern Hipparcos Catalogue. We also compare our results for De Houtman with those by Knobel in 1917 finding good overall agreement. About half of the ~ 200 new stars (with respect to Ptolemaios) added by De Houtman are in twelve new constellations, half in old constellations like Centaurus, Lupus and Argo. The right ascensions and declinations given by De Houtman have error distributions with widths of about 40', the longitudes and latitudes given by Kepler have error distributions with widths of about 45'. Halley improves on this by more than an order of magnitude to widths of about 3', and all entries in his catalogue can be identified. The measurement errors of Halley are due to a systematic deviation of his sextant (increasing with angle to 2' at 60°) and random errors of 0.7 arcmin. The position errors in the catalogue of Halley are dominated by the position errors in the reference stars, which he took from Brahe. The full Tables Houtman, Classis, Aliter and Halley (see Tables 6, 7, 8) are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/530/A93

Prevalence of refractive error in Europe: the European Eye Epidemiology (E(3)) Consortium.

PubMed

Williams, Katie M; Verhoeven, Virginie J M; Cumberland, Phillippa; Bertelsen, Geir; Wolfram, Christian; Buitendijk, Gabriëlle H S; Hofman, Albert; van Duijn, Cornelia M; Vingerling, Johannes R; Kuijpers, Robert W A M; Höhn, René; Mirshahi, Alireza; Khawaja, Anthony P; Luben, Robert N; Erke, Maja Gran; von Hanno, Therese; Mahroo, Omar; Hogg, Ruth; Gieger, Christian; Cougnard-Grégoire, Audrey; Anastasopoulos, Eleftherios; Bron, Alain; Dartigues, Jean-François; Korobelnik, Jean-François; Creuzot-Garcher, Catherine; Topouzis, Fotis; Delcourt, Cécile; Rahi, Jugnoo; Meitinger, Thomas; Fletcher, Astrid; Foster, Paul J; Pfeiffer, Norbert; Klaver, Caroline C W; Hammond, Christopher J

2015-04-01

To estimate the prevalence of refractive error in adults across Europe. Refractive data (mean spherical equivalent) collected between 1990 and 2013 from fifteen population-based cohort and cross-sectional studies of the European Eye Epidemiology (E(3)) Consortium were combined in a random effects meta-analysis stratified by 5-year age intervals and gender. Participants were excluded if they were identified as having had cataract surgery, retinal detachment, refractive surgery or other factors that might influence refraction. Estimates of refractive error prevalence were obtained including the following classifications: myopia ≤-0.75 diopters (D), high myopia ≤-6D, hyperopia ≥1D and astigmatism ≥1D. Meta-analysis of refractive error was performed for 61,946 individuals from fifteen studies with median age ranging from 44 to 81 and minimal ethnic variation (98 % European ancestry). The age-standardised prevalences (using the 2010 European Standard Population, limited to those ≥25 and <90 years old) were: myopia 30.6 % [95 % confidence interval (CI) 30.4-30.9], high myopia 2.7 % (95 % CI 2.69-2.73), hyperopia 25.2 % (95 % CI 25.0-25.4) and astigmatism 23.9 % (95 % CI 23.7-24.1). Age-specific estimates revealed a high prevalence of myopia in younger participants [47.2 % (CI 41.8-52.5) in 25-29 years-olds]. Refractive error affects just over a half of European adults. The greatest burden of refractive error is due to myopia, with high prevalence rates in young adults. Using the 2010 European population estimates, we estimate there are 227.2 million people with myopia across Europe.

Within-Tunnel Variations in Pressure Data for Three Transonic Wind Tunnels

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2014-01-01

This paper compares the results of pressure measurements made on the same test article with the same test matrix in three transonic wind tunnels. A comparison is presented of the unexplained variance associated with polar replicates acquired in each tunnel. The impact of a significance component of systematic (not random) unexplained variance is reviewed, and the results of analyses of variance are presented to assess the degree of significant systematic error in these representative wind tunnel tests. Total uncertainty estimates are reported for 140 samples of pressure data, quantifying the effects of within-polar random errors and between-polar systematic bias errors.

The accuracy of the measurements in Ulugh Beg's star catalogue

NASA Astrophysics Data System (ADS)

Krisciunas, K.

1992-12-01

The star catalogue compiled by Ulugh Beg and his collaborators in Samarkand (ca. 1437) is the only catalogue primarily based on original observations between the times of Ptolemy and Tycho Brahe. Evans (1987) has given convincing evidence that Ulugh Beg's star catalogue was based on measurements made with a zodiacal armillary sphere graduated to 15(') , with interpolation to 0.2 units. He and Shevchenko (1990) were primarily interested in the systematic errors in ecliptic longitude. Shevchenko's analysis of the random errors was limited to the twelve zodiacal constellations. We have analyzed all 843 ecliptic longitudes and latitudes attributed to Ulugh Beg by Knobel (1917). This required multiplying all the longitude errors by the respective values of the cosine of the celestial latitudes. We find a random error of +/- 17minp 7 for ecliptic longitude and +/- 16minp 5 for ecliptic latitude. On the whole, the random errors are largest near the ecliptic, decreasing towards the ecliptic poles. For all of Ulugh Beg's measurements (excluding outliers) the mean systematic error is -10minp 8 +/- 0minp 8 for ecliptic longitude and 7minp 5 +/- 0minp 7 for ecliptic latitude, with the errors in the sense ``computed minus Ulugh Beg''. For the brighter stars (those designated alpha , beta , and gamma in the respective constellations), the mean systematic errors are -11minp 3 +/- 1minp 9 for ecliptic longitude and 9minp 4 +/- 1minp 5 for ecliptic latitude. Within the errors this matches the systematic error in both coordinates for alpha Vir. With greater confidence we may conclude that alpha Vir was the principal reference star in the catalogues of Ulugh Beg and Ptolemy. Evans, J. 1987, J. Hist. Astr. 18, 155. Knobel, E. B. 1917, Ulugh Beg's Catalogue of Stars, Washington, D. C.: Carnegie Institution. Shevchenko, M. 1990, J. Hist. Astr. 21, 187.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

PubMed

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

On the Estimation of Errors in Sparse Bathymetric Geophysical Data Sets

NASA Astrophysics Data System (ADS)

Jakobsson, M.; Calder, B.; Mayer, L.; Armstrong, A.

2001-05-01

There is a growing demand in the geophysical community for better regional representations of the world ocean's bathymetry. However, given the vastness of the oceans and the relative limited coverage of even the most modern mapping systems, it is likely that many of the older data sets will remain part of our cumulative database for several more decades. Therefore, regional bathymetrical compilations that are based on a mixture of historic and contemporary data sets will have to remain the standard. This raises the problem of assembling bathymetric compilations and utilizing data sets not only with a heterogeneous cover but also with a wide range of accuracies. In combining these data to regularly spaced grids of bathymetric values, which the majority of numerical procedures in earth sciences require, we are often forced to use a complex interpolation scheme due to the sparseness and irregularity of the input data points. Consequently, we are faced with the difficult task of assessing the confidence that we can assign to the final grid product, a task that is not usually addressed in most bathymetric compilations. We approach the problem of assessing the confidence via a direct-simulation Monte Carlo method. We start with a small subset of data from the International Bathymetric Chart of the Arctic Ocean (IBCAO) grid model [Jakobsson et al., 2000]. This grid is compiled from a mixture of data sources ranging from single beam soundings with available metadata to spot soundings with no available metadata, to digitized contours; the test dataset shows examples of all of these types. From this database, we assign a priori error variances based on available meta-data, and when this is not available, based on a worst-case scenario in an essentially heuristic manner. We then generate a number of synthetic datasets by randomly perturbing the base data using normally distributed random variates, scaled according to the predicted error model. These datasets are then re-gridded using the same methodology as the original product, generating a set of plausible grid models of the regional bathymetry that we can use for standard error estimates. Finally, we repeat the entire random estimation process and analyze each run's standard error grids in order to examine sampling bias and variance in the predictions. The final products of the estimation are a collection of standard error grids, which we combine with the source data density in order to create a grid that contains information about the bathymetry model's reliability. Jakobsson, M., Cherkis, N., Woodward, J., Coakley, B., and Macnab, R., 2000, A new grid of Arctic bathymetry: A significant resource for scientists and mapmakers, EOS Transactions, American Geophysical Union, v. 81, no. 9, p. 89, 93, 96.

Phonological and Motor Errors in Individuals with Acquired Sound Production Impairment

ERIC Educational Resources Information Center

Buchwald, Adam; Miozzo, Michele

2012-01-01

Purpose: This study aimed to compare sound production errors arising due to phonological processing impairment with errors arising due to motor speech impairment. Method: Two speakers with similar clinical profiles who produced similar consonant cluster simplification errors were examined using a repetition task. We compared both overall accuracy…

Fitness landscapes, heuristics and technological paradigms: A critique on random search models in evolutionary economics

NASA Astrophysics Data System (ADS)

Frenken, Koen

2001-06-01

The biological evolution of complex organisms, in which the functioning of genes is interdependent, has been analyzed as "hill-climbing" on NK fitness landscapes through random mutation and natural selection. In evolutionary economics, NK fitness landscapes have been used to simulate the evolution of complex technological systems containing elements that are interdependent in their functioning. In these models, economic agents randomly search for new technological design by trial-and-error and run the risk of ending up in sub-optimal solutions due to interdependencies between the elements in a complex system. These models of random search are legitimate for reasons of modeling simplicity, but remain limited as these models ignore the fact that agents can apply heuristics. A specific heuristic is one that sequentially optimises functions according to their ranking by users of the system. To model this heuristic, a generalized NK-model is developed. In this model, core elements that influence many functions can be distinguished from peripheral elements that affect few functions. The concept of paradigmatic search can then be analytically defined as search that leaves core elements in tact while concentrating on improving functions by mutation of peripheral elements.

Hand pose estimation in depth image using CNN and random forest

NASA Astrophysics Data System (ADS)

Chen, Xi; Cao, Zhiguo; Xiao, Yang; Fang, Zhiwen

2018-03-01

Thanks to the availability of low cost depth cameras, like Microsoft Kinect, 3D hand pose estimation attracted special research attention in these years. Due to the large variations in hand`s viewpoint and the high dimension of hand motion, 3D hand pose estimation is still challenging. In this paper we propose a two-stage framework which joint with CNN and Random Forest to boost the performance of hand pose estimation. First, we use a standard Convolutional Neural Network (CNN) to regress the hand joints` locations. Second, using a Random Forest to refine the joints from the first stage. In the second stage, we propose a pyramid feature which merges the information flow of the CNN. Specifically, we get the rough joints` location from first stage, then rotate the convolutional feature maps (and image). After this, for each joint, we map its location to each feature map (and image) firstly, then crop features at each feature map (and image) around its location, put extracted features to Random Forest to refine at last. Experimentally, we evaluate our proposed method on ICVL dataset and get the mean error about 11mm, our method is also real-time on a desktop.

Random access to mobile networks with advanced error correction

NASA Technical Reports Server (NTRS)

Dippold, Michael

1990-01-01

A random access scheme for unreliable data channels is investigated in conjunction with an adaptive Hybrid-II Automatic Repeat Request (ARQ) scheme using Rate Compatible Punctured Codes (RCPC) Forward Error Correction (FEC). A simple scheme with fixed frame length and equal slot sizes is chosen and reservation is implicit by the first packet transmitted randomly in a free slot, similar to Reservation Aloha. This allows the further transmission of redundancy if the last decoding attempt failed. Results show that a high channel utilization and superior throughput can be achieved with this scheme that shows a quite low implementation complexity. For the example of an interleaved Rayleigh channel and soft decision utilization and mean delay are calculated. A utilization of 40 percent may be achieved for a frame with the number of slots being equal to half the station number under high traffic load. The effects of feedback channel errors and some countermeasures are discussed.

Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Zhang, Li-jie

2017-10-01

Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian, Yudong

2011-01-01

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Sloppy-slotted ALOHA

NASA Technical Reports Server (NTRS)

Crozier, Stewart N.

1990-01-01

Random access signaling, which allows slotted packets to spill over into adjacent slots, is investigated. It is shown that sloppy-slotted ALOHA can always provide higher throughput than conventional slotted ALOHA. The degree of improvement depends on the timing error distribution. Throughput performance is presented for Gaussian timing error distributions, modified to include timing error corrections. A general channel capacity lower bound, independent of the specific timing error distribution, is also presented.

Technical Note: Millimeter precision in ultrasound based patient positioning: Experimental quantification of inherent technical limitations

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

Ballhausen, Hendrik, E-mail: hendrik.ballhausen@med.uni-muenchen.de; Hieber, Sheila; Li, Minglun

2014-08-15

Purpose: To identify the relevant technical sources of error of a system based on three-dimensional ultrasound (3D US) for patient positioning in external beam radiotherapy. To quantify these sources of error in a controlled laboratory setting. To estimate the resulting end-to-end geometric precision of the intramodality protocol. Methods: Two identical free-hand 3D US systems at both the planning-CT and the treatment room were calibrated to the laboratory frame of reference. Every step of the calibration chain was repeated multiple times to estimate its contribution to overall systematic and random error. Optimal margins were computed given the identified and quantified systematicmore » and random errors. Results: In descending order of magnitude, the identified and quantified sources of error were: alignment of calibration phantom to laser marks 0.78 mm, alignment of lasers in treatment vs planning room 0.51 mm, calibration and tracking of 3D US probe 0.49 mm, alignment of stereoscopic infrared camera to calibration phantom 0.03 mm. Under ideal laboratory conditions, these errors are expected to limit ultrasound-based positioning to an accuracy of 1.05 mm radially. Conclusions: The investigated 3D ultrasound system achieves an intramodal accuracy of about 1 mm radially in a controlled laboratory setting. The identified systematic and random errors require an optimal clinical tumor volume to planning target volume margin of about 3 mm. These inherent technical limitations do not prevent clinical use, including hypofractionation or stereotactic body radiation therapy.« less

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.

Effect of Random Circuit Fabrication Errors on Small Signal Gain and Phase in Helix Traveling Wave Tubes

NASA Astrophysics Data System (ADS)

Pengvanich, P.; Chernin, D. P.; Lau, Y. Y.; Luginsland, J. W.; Gilgenbach, R. M.

2007-11-01

Motivated by the current interest in mm-wave and THz sources, which use miniature, difficult-to-fabricate circuit components, we evaluate the statistical effects of random fabrication errors on a helix traveling wave tube amplifier's small signal characteristics. The small signal theory is treated in a continuum model in which the electron beam is assumed to be monoenergetic, and axially symmetric about the helix axis. Perturbations that vary randomly along the beam axis are introduced in the dimensionless Pierce parameters b, the beam-wave velocity mismatch, C, the gain parameter, and d, the cold tube circuit loss. Our study shows, as expected, that perturbation in b dominates the other two. The extensive numerical data have been confirmed by our analytic theory. They show in particular that the standard deviation of the output phase is linearly proportional to standard deviation of the individual perturbations in b, C, and d. Simple formulas have been derived which yield the output phase variations in terms of the statistical random manufacturing errors. This work was supported by AFOSR and by ONR.

Accuracy of indirect estimation of power output from uphill performance in cycling.

PubMed

Millet, Grégoire P; Tronche, Cyrille; Grappe, Frédéric

2014-09-01

To use measurement by cycling power meters (Pmes) to evaluate the accuracy of commonly used models for estimating uphill cycling power (Pest). Experiments were designed to explore the influence of wind speed and steepness of climb on accuracy of Pest. The authors hypothesized that the random error in Pest would be largely influenced by the windy conditions, the bias would be diminished in steeper climbs, and windy conditions would induce larger bias in Pest. Sixteen well-trained cyclists performed 15 uphill-cycling trials (range: length 1.3-6.3 km, slope 4.4-10.7%) in a random order. Trials included different riding position in a group (lead or follow) and different wind speeds. Pmes was quantified using a power meter, and Pest was calculated with a methodology used by journalists reporting on the Tour de France. Overall, the difference between Pmes and Pest was -0.95% (95%CI: -10.4%, +8.5%) for all trials and 0.24% (-6.1%, +6.6%) in conditions without wind (<2 m/s). The relationship between percent slope and the error between Pest and Pmes were considered trivial. Aerodynamic drag (affected by wind velocity and orientation, frontal area, drafting, and speed) is the most confounding factor. The mean estimated values are close to the power-output values measured by power meters, but the random error is between ±6% and ±10%. Moreover, at the power outputs (>400 W) produced by professional riders, this error is likely to be higher. This observation calls into question the validity of releasing individual values without reporting the range of random errors.

Behavioural and neural basis of anomalous motor learning in children with autism.

PubMed

Marko, Mollie K; Crocetti, Deana; Hulst, Thomas; Donchin, Opher; Shadmehr, Reza; Mostofsky, Stewart H

2015-03-01

Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8-12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in the cerebellum. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Stochastic Forcing for High-Resolution Regional and Global Ocean and Atmosphere-Ocean Coupled Ensemble Forecast System

NASA Astrophysics Data System (ADS)

Rowley, C. D.; Hogan, P. J.; Martin, P.; Thoppil, P.; Wei, M.

2017-12-01

An extended range ensemble forecast system is being developed in the US Navy Earth System Prediction Capability (ESPC), and a global ocean ensemble generation capability to represent uncertainty in the ocean initial conditions has been developed. At extended forecast times, the uncertainty due to the model error overtakes the initial condition as the primary source of forecast uncertainty. Recently, stochastic parameterization or stochastic forcing techniques have been applied to represent the model error in research and operational atmospheric, ocean, and coupled ensemble forecasts. A simple stochastic forcing technique has been developed for application to US Navy high resolution regional and global ocean models, for use in ocean-only and coupled atmosphere-ocean-ice-wave ensemble forecast systems. Perturbation forcing is added to the tendency equations for state variables, with the forcing defined by random 3- or 4-dimensional fields with horizontal, vertical, and temporal correlations specified to characterize different possible kinds of error. Here, we demonstrate the stochastic forcing in regional and global ensemble forecasts with varying perturbation amplitudes and length and time scales, and assess the change in ensemble skill measured by a range of deterministic and probabilistic metrics.

Towards System Calibration of Panoramic Laser Scanners from a Single Station

PubMed Central

Medić, Tomislav; Holst, Christoph; Kuhlmann, Heiner

2017-01-01

Terrestrial laser scanner measurements suffer from systematic errors due to internal misalignments. The magnitude of the resulting errors in the point cloud in many cases exceeds the magnitude of random errors. Hence, the task of calibrating a laser scanner is important for applications with high accuracy demands. This paper primarily addresses the case of panoramic terrestrial laser scanners. Herein, it is proven that most of the calibration parameters can be estimated from a single scanner station without a need for any reference information. This hypothesis is confirmed through an empirical experiment, which was conducted in a large machine hall using a Leica Scan Station P20 panoramic laser scanner. The calibration approach is based on the widely used target-based self-calibration approach, with small modifications. A new angular parameterization is used in order to implicitly introduce measurements in two faces of the instrument and for the implementation of calibration parameters describing genuine mechanical misalignments. Additionally, a computationally preferable calibration algorithm based on the two-face measurements is introduced. In the end, the calibration results are discussed, highlighting all necessary prerequisites for the scanner calibration from a single scanner station. PMID:28513548

Evaluation of voice codecs for the Australian mobile satellite system

NASA Technical Reports Server (NTRS)

Bundrock, Tony; Wilkinson, Mal

1990-01-01

The evaluation procedure to choose a low bit rate voice coding algorithm is described for the Australian land mobile satellite system. The procedure is designed to assess both the inherent quality of the codec under 'normal' conditions and its robustness under 'severe' conditions. For the assessment, normal conditions were chosen to be random bit error rate with added background acoustic noise and the severe condition is designed to represent burst error conditions when mobile satellite channel suffers from signal fading due to roadside vegetation. The assessment is divided into two phases. First, a reduced set of conditions is used to determine a short list of candidate codecs for more extensive testing in the second phase. The first phase conditions include quality and robustness and codecs are ranked with a 60:40 weighting on the two. Second, the short listed codecs are assessed over a range of input voice levels, BERs, background noise conditions, and burst error distributions. Assessment is by subjective rating on a five level opinion scale and all results are then used to derive a weighted Mean Opinion Score using appropriate weights for each of the test conditions.

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.

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

Proctor, Timothy; Rudinger, Kenneth; Young, Kevin

Randomized benchmarking (RB) is widely used to measure an error rate of a set of quantum gates, by performing random circuits that would do nothing if the gates were perfect. In the limit of no finite-sampling error, the exponential decay rate of the observable survival probabilities, versus circuit length, yields a single error metric r. For Clifford gates with arbitrary small errors described by process matrices, r was believed to reliably correspond to the mean, over all Clifford gates, of the average gate infidelity between the imperfect gates and their ideal counterparts. We show that this quantity is not amore » well-defined property of a physical gate set. It depends on the representations used for the imperfect and ideal gates, and the variant typically computed in the literature can differ from r by orders of magnitude. We present new theories of the RB decay that are accurate for all small errors describable by process matrices, and show that the RB decay curve is a simple exponential for all such errors. Here, these theories allow explicit computation of the error rate that RB measures (r), but as far as we can tell it does not correspond to the infidelity of a physically allowed (completely positive) representation of the imperfect gates.« less

The detection of problem analytes in a single proficiency test challenge in the absence of the Health Care Financing Administration rule violations.

PubMed

Cembrowski, G S; Hackney, J R; Carey, N

1993-04-01

The Clinical Laboratory Improvement Act of 1988 (CLIA 88) has dramatically changed proficiency testing (PT) practices having mandated (1) satisfactory PT for certain analytes as a condition of laboratory operation, (2) fixed PT limits for many of these "regulated" analytes, and (3) an increased number of PT specimens (n = 5) for each testing cycle. For many of these analytes, the fixed limits are much broader than the previously employed Standard Deviation Index (SDI) criteria. Paradoxically, there may be less incentive to identify and evaluate analytically significant outliers to improve the analytical process. Previously described "control rules" to evaluate these PT results are unworkable as they consider only two or three results. We used Monte Carlo simulations of Kodak Ektachem analyzers participating in PT to determine optimal control rules for the identification of PT results that are inconsistent with those from other laboratories using the same methods. The analysis of three representative analytes, potassium, creatine kinase, and iron was simulated with varying intrainstrument and interinstrument standard deviations (si and sg, respectively) obtained from the College of American Pathologists (Northfield, Ill) Quality Assurance Services data and Proficiency Test data, respectively. Analytical errors were simulated in each of the analytes and evaluated in terms of multiples of the interlaboratory SDI. Simple control rules for detecting systematic and random error were evaluated with power function graphs, graphs of probability of error detected vs magnitude of error. Based on the simulation results, we recommend screening all analytes for the occurrence of two or more observations exceeding the same +/- 1 SDI limit. For any analyte satisfying this condition, the mean of the observations should be calculated. For analytes with sg/si ratios between 1.0 and 1.5, a significant systematic error is signaled by the mean exceeding 1.0 SDI. Significant random error is signaled by one observation exceeding the +/- 3-SDI limit or the range of the observations exceeding 4 SDIs. For analytes with higher sg/si, significant systematic or random error is signaled by violation of the screening rule (having at least two observations exceeding the same +/- 1 SDI limit). Random error can also be signaled by one observation exceeding the +/- 1.5-SDI limit or the range of the observations exceeding 3 SDIs. We present a practical approach to the workup of apparent PT errors.

An efficient algorithm for generating random number pairs drawn from a bivariate normal distribution

NASA Technical Reports Server (NTRS)

Campbell, C. W.

1983-01-01

An efficient algorithm for generating random number pairs from a bivariate normal distribution was developed. Any desired value of the two means, two standard deviations, and correlation coefficient can be selected. Theoretically the technique is exact and in practice its accuracy is limited only by the quality of the uniform distribution random number generator, inaccuracies in computer function evaluation, and arithmetic. A FORTRAN routine was written to check the algorithm and good accuracy was obtained. Some small errors in the correlation coefficient were observed to vary in a surprisingly regular manner. A simple model was developed which explained the qualities aspects of the errors.

Overlay improvement by exposure map based mask registration optimization

NASA Astrophysics Data System (ADS)

Shi, Irene; Guo, Eric; Chen, Ming; Lu, Max; Li, Gordon; Li, Rivan; Tian, Eric

2015-03-01

Along with the increased miniaturization of semiconductor electronic devices, the design rules of advanced semiconductor devices shrink dramatically. [1] One of the main challenges of lithography step is the layer-to-layer overlay control. Furthermore, DPT (Double Patterning Technology) has been adapted for the advanced technology node like 28nm and 14nm, corresponding overlay budget becomes even tighter. [2][3] After the in-die mask registration (pattern placement) measurement is introduced, with the model analysis of a KLA SOV (sources of variation) tool, it's observed that registration difference between masks is a significant error source of wafer layer-to-layer overlay at 28nm process. [4][5] Mask registration optimization would highly improve wafer overlay performance accordingly. It was reported that a laser based registration control (RegC) process could be applied after the pattern generation or after pellicle mounting and allowed fine tuning of the mask registration. [6] In this paper we propose a novel method of mask registration correction, which can be applied before mask writing based on mask exposure map, considering the factors of mask chip layout, writing sequence, and pattern density distribution. Our experiment data show if pattern density on the mask keeps at a low level, in-die mask registration residue error in 3sigma could be always under 5nm whatever blank type and related writer POSCOR (position correction) file was applied; it proves random error induced by material or equipment would occupy relatively fixed error budget as an error source of mask registration. On the real production, comparing the mask registration difference through critical production layers, it could be revealed that registration residue error of line space layers with higher pattern density is always much larger than the one of contact hole layers with lower pattern density. Additionally, the mask registration difference between layers with similar pattern density could also achieve under 5nm performance. We assume mask registration excluding random error is mostly induced by charge accumulation during mask writing, which may be calculated from surrounding exposed pattern density. Multi-loading test mask registration result shows that with x direction writing sequence, mask registration behavior in x direction is mainly related to sequence direction, but mask registration in y direction would be highly impacted by pattern density distribution map. It proves part of mask registration error is due to charge issue from nearby environment. If exposure sequence is chip by chip for normal multi chip layout case, mask registration of both x and y direction would be impacted analogously, which has also been proved by real data. Therefore, we try to set up a simple model to predict the mask registration error based on mask exposure map, and correct it with the given POSCOR (position correction) file for advanced mask writing if needed.

The Applicability of Standard Error of Measurement and Minimal Detectable Change to Motor Learning Research-A Behavioral Study.

PubMed

Furlan, Leonardo; Sterr, Annette

2018-01-01

Motor learning studies face the challenge of differentiating between real changes in performance and random measurement error. While the traditional p -value-based analyses of difference (e.g., t -tests, ANOVAs) provide information on the statistical significance of a reported change in performance scores, they do not inform as to the likely cause or origin of that change, that is, the contribution of both real modifications in performance and random measurement error to the reported change. One way of differentiating between real change and random measurement error is through the utilization of the statistics of standard error of measurement (SEM) and minimal detectable change (MDC). SEM is estimated from the standard deviation of a sample of scores at baseline and a test-retest reliability index of the measurement instrument or test employed. MDC, in turn, is estimated from SEM and a degree of confidence, usually 95%. The MDC value might be regarded as the minimum amount of change that needs to be observed for it to be considered a real change, or a change to which the contribution of real modifications in performance is likely to be greater than that of random measurement error. A computer-based motor task was designed to illustrate the applicability of SEM and MDC to motor learning research. Two studies were conducted with healthy participants. Study 1 assessed the test-retest reliability of the task and Study 2 consisted in a typical motor learning study, where participants practiced the task for five consecutive days. In Study 2, the data were analyzed with a traditional p -value-based analysis of difference (ANOVA) and also with SEM and MDC. The findings showed good test-retest reliability for the task and that the p -value-based analysis alone identified statistically significant improvements in performance over time even when the observed changes could in fact have been smaller than the MDC and thereby caused mostly by random measurement error, as opposed to by learning. We suggest therefore that motor learning studies could complement their p -value-based analyses of difference with statistics such as SEM and MDC in order to inform as to the likely cause or origin of any reported changes in performance.

Assessing the quality of humidity measurements from global operational radiosonde sensors

NASA Astrophysics Data System (ADS)

Moradi, Isaac; Soden, Brian; Ferraro, Ralph; Arkin, Phillip; Vömel, Holger

2013-07-01

The quality of humidity measurements from global operational radiosonde sensors in upper, middle, and lower troposphere for the period 2000-2011 were investigated using satellite observations from three microwave water vapor channels operating at 183.31±1, 183.31±3, and 183.31±7 GHz. The radiosonde data were partitioned based on sensor type into 19 classes. The satellite brightness temperatures (Tb) were simulated using radiosonde profiles and a radiative transfer model, then the radiosonde simulated Tb's were compared with the observed Tb's from the satellites. The surface affected Tb's were excluded from the comparison due to the lack of reliable surface emissivity data at the microwave frequencies. Daytime and nighttime data were examined separately to see the possible effect of daytime radiation bias on the sonde data. The error characteristics among different radiosondes vary significantly, which largely reflects the differences in sensor type. These differences are more evident in the mid-upper troposphere than in the lower troposphere, mainly because some of the sensors stop responding to tropospheric humidity somewhere in the upper or even in the middle troposphere. In the upper troposphere, most sensors have a dry bias but Russian sensors and a few other sensors including GZZ2, VZB2, and RS80H have a wet bias. In middle troposphere, Russian sensors still have a wet bias but all other sensors have a dry bias. All sensors, including Russian sensors, have a dry bias in lower troposphere. The systematic and random errors generally decrease from upper to lower troposphere. Sensors from China, India, Russia, and the U.S. have a large random error in upper troposphere, which indicates that these sensors are not suitable for upper tropospheric studies as they fail to respond to humidity changes in the upper and even middle troposphere. Overall, Vaisala sensors perform better than other sensors throughout the troposphere exhibiting the smallest systematic and random errors. Because of the large differences between different radiosonde humidity sensors, it is important for long-term trend studies to only use data measured using a single type of sensor at any given station. If multiple sensor types are used then it is necessary to consider the bias between sensor types and its possible dependence on humidity and temperature.

Error characterization and quantum control benchmarking in liquid state NMR using quantum information processing techniques

NASA Astrophysics Data System (ADS)

Laforest, Martin

Quantum information processing has been the subject of countless discoveries since the early 1990's. It is believed to be the way of the future for computation: using quantum systems permits one to perform computation exponentially faster than on a regular classical computer. Unfortunately, quantum systems that not isolated do not behave well. They tend to lose their quantum nature due to the presence of the environment. If key information is known about the noise present in the system, methods such as quantum error correction have been developed in order to reduce the errors introduced by the environment during a given quantum computation. In order to harness the quantum world and implement the theoretical ideas of quantum information processing and quantum error correction, it is imperative to understand and quantify the noise present in the quantum processor and benchmark the quality of the control over the qubits. Usual techniques to estimate the noise or the control are based on quantum process tomography (QPT), which, unfortunately, demands an exponential amount of resources. This thesis presents work towards the characterization of noisy processes in an efficient manner. The protocols are developed from a purely abstract setting with no system-dependent variables. To circumvent the exponential nature of quantum process tomography, three different efficient protocols are proposed and experimentally verified. The first protocol uses the idea of quantum error correction to extract relevant parameters about a given noise model, namely the correlation between the dephasing of two qubits. Following that is a protocol using randomization and symmetrization to extract the probability that a given number of qubits are simultaneously corrupted in a quantum memory, regardless of the specifics of the error and which qubits are affected. Finally, a last protocol, still using randomization ideas, is developed to estimate the average fidelity per computational gates for single and multi qubit systems. Even though liquid state NMR is argued to be unsuitable for scalable quantum information processing, it remains the best test-bed system to experimentally implement, verify and develop protocols aimed at increasing the control over general quantum information processors. For this reason, all the protocols described in this thesis have been implemented in liquid state NMR, which then led to further development of control and analysis techniques.

Positivity, discontinuity, finite resources, and nonzero error for arbitrarily varying quantum channels

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

Boche, H., E-mail: boche@tum.de, E-mail: janis.noetzel@tum.de; Nötzel, J., E-mail: boche@tum.de, E-mail: janis.noetzel@tum.de

2014-12-15

This work is motivated by a quite general question: Under which circumstances are the capacities of information transmission systems continuous? The research is explicitly carried out on finite arbitrarily varying quantum channels (AVQCs). We give an explicit example that answers the recent question whether the transmission of messages over AVQCs can benefit from assistance by distribution of randomness between the legitimate sender and receiver in the affirmative. The specific class of channels introduced in that example is then extended to show that the unassisted capacity does have discontinuity points, while it is known that the randomness-assisted capacity is always continuousmore » in the channel. We characterize the discontinuity points and prove that the unassisted capacity is always continuous around its positivity points. After having established shared randomness as an important resource, we quantify the interplay between the distribution of finite amounts of randomness between the legitimate sender and receiver, the (nonzero) probability of a decoding error with respect to the average error criterion and the number of messages that can be sent over a finite number of channel uses. We relate our results to the entanglement transmission capacities of finite AVQCs, where the role of shared randomness is not yet well understood, and give a new sufficient criterion for the entanglement transmission capacity with randomness assistance to vanish.« less

Noise in two-color electronic distance meter measurements revisited

USGS Publications Warehouse

Langbein, J.

2004-01-01

Frequent, high-precision geodetic data have temporally correlated errors. Temporal correlations directly affect both the estimate of rate and its standard error; the rate of deformation is a key product from geodetic measurements made in tectonically active areas. Various models of temporally correlated errors are developed and these provide relations between the power spectral density and the data covariance matrix. These relations are applied to two-color electronic distance meter (EDM) measurements made frequently in California over the past 15-20 years. Previous analysis indicated that these data have significant random walk error. Analysis using the noise models developed here indicates that the random walk model is valid for about 30% of the data. A second 30% of the data can be better modeled with power law noise with a spectral index between 1 and 2, while another 30% of the data can be modeled with a combination of band-pass-filtered plus random walk noise. The remaining 10% of the data can be best modeled as a combination of band-pass-filtered plus power law noise. This band-pass-filtered noise is a product of an annual cycle that leaks into adjacent frequency bands. For time spans of more than 1 year these more complex noise models indicate that the precision in rate estimates is better than that inferred by just the simpler, random walk model of noise.

Helical tomotherapy setup variations in canine nasal tumor patients immobilized with a bite block.

PubMed

Kubicek, Lyndsay N; Seo, Songwon; Chappell, Richard J; Jeraj, Robert; Forrest, Lisa J

2012-01-01

The purpose of our study was to compare setup variation in four degrees of freedom (vertical, longitudinal, lateral, and roll) between canine nasal tumor patients immobilized with a mattress and bite block, versus a mattress alone. Our secondary aim was to define a clinical target volume (CTV) to planning target volume (PTV) expansion margin based on our mean systematic error values associated with nasal tumor patients immobilized by a mattress and bite block. We evaluated six parameters for setup corrections: systematic error, random error, patient-patient variation in systematic errors, the magnitude of patient-specific random errors (root mean square [RMS]), distance error, and the variation of setup corrections from zero shift. The variations in all parameters were statistically smaller in the group immobilized by a mattress and bite block. The mean setup corrections in the mattress and bite block group ranged from 0.91 mm to 1.59 mm for the translational errors and 0.5°. Although most veterinary radiation facilities do not have access to Image-guided radiotherapy (IGRT), we identified a need for more rigid fixation, established the value of adding IGRT to veterinary radiation therapy, and define the CTV-PTV setup error margin for canine nasal tumor patients immobilized in a mattress and bite block. © 2012 Veterinary Radiology & Ultrasound.

Propagation of stage measurement uncertainties to streamflow time series

NASA Astrophysics Data System (ADS)

Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary

2016-04-01

Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.

[Epidemiology of refractive errors].

PubMed

Wolfram, C

2017-07-01

Refractive errors are very common and can lead to severe pathological changes in the eye. This article analyzes the epidemiology of refractive errors in the general population in Germany and worldwide and describes common definitions for refractive errors and clinical characteristics for pathologicaal changes. Refractive errors differ between age groups due to refractive changes during the life time and also due to generation-specific factors. Current research about the etiology of refractive errors has strengthened the influence of environmental factors, which led to new strategies for the prevention of refractive pathologies.

Unforced errors and error reduction in tennis

PubMed Central

Brody, H

2006-01-01

Only at the highest level of tennis is the number of winners comparable to the number of unforced errors. As the average player loses many more points due to unforced errors than due to winners by an opponent, if the rate of unforced errors can be reduced, it should lead to an increase in points won. This article shows how players can improve their game by understanding and applying the laws of physics to reduce the number of unforced errors. PMID:16632568

Secure Minutiae-Based Fingerprint Templates Using Random Triangle Hashing

NASA Astrophysics Data System (ADS)

Jin, Zhe; Jin Teoh, Andrew Beng; Ong, Thian Song; Tee, Connie

Due to privacy concern on the widespread use of biometric authentication systems, biometric template protection has gained great attention in the biometric research recently. It is a challenging task to design a biometric template protection scheme which is anonymous, revocable and noninvertible while maintaining acceptable performance. Many methods have been proposed to resolve this problem, and cancelable biometrics is one of them. In this paper, we propose a scheme coined as Random Triangle Hashing which follows the concept of cancelable biometrics in the fingerprint domain. In this method, re-alignment of fingerprints is not required as all the minutiae are translated into a pre-defined 2 dimensional space based on a reference minutia. After that, the proposed Random Triangle hashing method is used to enforce the one-way property (non-invertibility) of the biometric template. The proposed method is resistant to minor translation error and rotation distortion. Finally, the hash vectors are converted into bit-strings to be stored in the database. The proposed method is evaluated using the public database FVC2004 DB1. An EER of less than 1% is achieved by using the proposed method.

Bit Error Probability for Maximum Likelihood Decoding of Linear Block Codes

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc P. C.; Rhee, Dojun

1996-01-01

In this paper, the bit error probability P(sub b) for maximum likelihood decoding of binary linear codes is investigated. The contribution of each information bit to P(sub b) is considered. For randomly generated codes, it is shown that the conventional approximation at high SNR P(sub b) is approximately equal to (d(sub H)/N)P(sub s), where P(sub s) represents the block error probability, holds for systematic encoding only. Also systematic encoding provides the minimum P(sub b) when the inverse mapping corresponding to the generator matrix of the code is used to retrieve the information sequence. The bit error performances corresponding to other generator matrix forms are also evaluated. Although derived for codes with a generator matrix randomly generated, these results are shown to provide good approximations for codes used in practice. Finally, for decoding methods which require a generator matrix with a particular structure such as trellis decoding or algebraic-based soft decision decoding, equivalent schemes that reduce the bit error probability are discussed.

Effect of phase errors in stepped-frequency radar systems

NASA Astrophysics Data System (ADS)

Vanbrundt, H. E.

1988-04-01

Stepped-frequency waveforms are being considered for inverse synthetic aperture radar (ISAR) imaging from ship and airborne platforms and for detailed radar cross section (RCS) measurements of ships and aircraft. These waveforms make it possible to achieve resolutions of 1.0 foot by using existing radar designs and processing technology. One problem not yet fully resolved in using stepped-frequency waveform for ISAR imaging is the deterioration in signal level caused by random frequency error. Random frequency error of the stepped-frequency source results in reduced peak responses and increased null responses. The resulting reduced signal-to-noise ratio is range dependent. Two of the major concerns addressed in this report are radar range limitations for ISAR and the error in calibration for RCS measurements caused by differences in range between a passive reflector used for an RCS reference and the target to be measured. In addressing these concerns, NOSC developed an analysis to assess the tolerable frequency error in terms of resulting power loss in signal power and signal-to-phase noise.

Value stream mapping of the Pap test processing procedure: a lean approach to improve quality and efficiency.

PubMed

Michael, Claire W; Naik, Kalyani; McVicker, Michael

2013-05-01

We developed a value stream map (VSM) of the Papanicolaou test procedure to identify opportunities to reduce waste and errors, created a new VSM, and implemented a new process emphasizing Lean tools. Preimplementation data revealed the following: (1) processing time (PT) for 1,140 samples averaged 54 hours; (2) 27 accessioning errors were detected on review of 357 random requisitions (7.6%); (3) 5 of the 20,060 tests had labeling errors that had gone undetected in the processing stage. Four were detected later during specimen processing but 1 reached the reporting stage. Postimplementation data were as follows: (1) PT for 1,355 samples averaged 31 hours; (2) 17 accessioning errors were detected on review of 385 random requisitions (4.4%); and (3) no labeling errors were undetected. Our results demonstrate that implementation of Lean methods, such as first-in first-out processes and minimizing batch size by staff actively participating in the improvement process, allows for higher quality, greater patient safety, and improved efficiency.

[A proposal for a new definition of excess mortality associated with influenza-epidemics and its estimation].

PubMed

Takahashi, M; Tango, T

2001-05-01

As methods for estimating excess mortality associated with influenza-epidemic, the Serfling's cyclical regression model and the Kawai and Fukutomi model with seasonal indices have been proposed. Excess mortality under the old definition (i.e., the number of deaths actually recorded in excess of the number expected on the basis of past seasonal experience) covers the random error for that portion of variation regarded as due to chance. In addition, it disregards the range of random variation of mortality with the season. In this paper, we propose a new definition of excess mortality associated with influenza-epidemics and a new estimation method, considering these questions with the Kawai and Fukutomi method. The new definition of excess mortality and a novel method for its estimation were generated as follows. Factors bringing about variation in mortality in months with influenza-epidemics may be divided into two groups: 1. Influenza itself, 2. others (practically random variation). The range of variation of mortality due to the latter (normal range) can be estimated from the range for months in the absence of influenza-epidemics. Excess mortality is defined as death over the normal range. A new definition of excess mortality associated with influenza-epidemics and an estimation method are proposed. The new method considers variation in mortality in months in the absence of influenza-epidemics. Consequently, it provides reasonable estimates of excess mortality by separating the portion of random variation. Further, it is a characteristic that the proposed estimate can be used as a criterion of statistical significance test.

Why the null matters: statistical tests, random walks and evolution.

PubMed

Sheets, H D; Mitchell, C E

2001-01-01

A number of statistical tests have been developed to determine what type of dynamics underlie observed changes in morphology in evolutionary time series, based on the pattern of change within the time series. The theory of the 'scaled maximum', the 'log-rate-interval' (LRI) method, and the Hurst exponent all operate on the same principle of comparing the maximum change, or rate of change, in the observed dataset to the maximum change expected of a random walk. Less change in a dataset than expected of a random walk has been interpreted as indicating stabilizing selection, while more change implies directional selection. The 'runs test' in contrast, operates on the sequencing of steps, rather than on excursion. Applications of these tests to computer generated, simulated time series of known dynamical form and various levels of additive noise indicate that there is a fundamental asymmetry in the rate of type II errors of the tests based on excursion: they are all highly sensitive to noise in models of directional selection that result in a linear trend within a time series, but are largely noise immune in the case of a simple model of stabilizing selection. Additionally, the LRI method has a lower sensitivity than originally claimed, due to the large range of LRI rates produced by random walks. Examination of the published results of these tests show that they have seldom produced a conclusion that an observed evolutionary time series was due to directional selection, a result which needs closer examination in light of the asymmetric response of these tests.

Estimation of daily interfractional larynx residual setup error after isocentric alignment for head and neck radiotherapy: Quality-assurance implications for target volume and organ-at-risk margination using daily CT-on-rails imaging

PubMed Central

Baron, Charles A.; Awan, Musaddiq J.; Mohamed, Abdallah S. R.; Akel, Imad; Rosenthal, David I.; Gunn, G. Brandon; Garden, Adam S.; Dyer, Brandon A.; Court, Laurence; Sevak, Parag R; Kocak-Uzel, Esengul; Fuller, Clifton D.

2016-01-01

Larynx may alternatively serve as a target or organ-at-risk (OAR) in head and neck cancer (HNC) image-guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population–based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT-on-rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other 6 points were calculated post-isocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all 6 points for all scans over the course of treatment were calculated. Residual systematic and random error, and the necessary compensatory CTV-to-PTV and OAR-to-PRV margins were calculated, using both observational cohort data and a bootstrap-resampled population estimator. The grand mean displacements for all anatomical points was 5.07mm, with mean systematic error of 1.1mm and mean random setup error of 2.63mm, while bootstrapped POIs grand mean displacement was 5.09mm, with mean systematic error of 1.23mm and mean random setup error of 2.61mm. Required margin for CTV-PTV expansion was 4.6mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9mm. The calculated OAR-to-PRV expansion for the observed residual set-up error was 2.7mm, and bootstrap estimated expansion of 2.9mm. We conclude that the interfractional larynx setup error is a significant source of RT set-up/delivery error in HNC both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5mm to compensate for set up error if the larynx is a target or 3mm if the larynx is an OAR when using a non-laryngeal bony isocenter. PMID:25679151

Estimation of daily interfractional larynx residual setup error after isocentric alignment for head and neck radiotherapy: quality assurance implications for target volume and organs‐at‐risk margination using daily CT on‐rails imaging

PubMed Central

Baron, Charles A.; Awan, Musaddiq J.; Mohamed, Abdallah S.R.; Akel, Imad; Rosenthal, David I.; Gunn, G. Brandon; Garden, Adam S.; Dyer, Brandon A.; Court, Laurence; Sevak, Parag R.; Kocak‐Uzel, Esengul

2014-01-01

Larynx may alternatively serve as a target or organs at risk (OAR) in head and neck cancer (HNC) image‐guided radiotherapy (IGRT). The objective of this study was to estimate IGRT parameters required for larynx positional error independent of isocentric alignment and suggest population‐based compensatory margins. Ten HNC patients receiving radiotherapy (RT) with daily CT on‐rails imaging were assessed. Seven landmark points were placed on each daily scan. Taking the most superior‐anterior point of the C5 vertebra as a reference isocenter for each scan, residual displacement vectors to the other six points were calculated postisocentric alignment. Subsequently, using the first scan as a reference, the magnitude of vector differences for all six points for all scans over the course of treatment was calculated. Residual systematic and random error and the necessary compensatory CTV‐to‐PTV and OAR‐to‐PRV margins were calculated, using both observational cohort data and a bootstrap‐resampled population estimator. The grand mean displacements for all anatomical points was 5.07 mm, with mean systematic error of 1.1 mm and mean random setup error of 2.63 mm, while bootstrapped POIs grand mean displacement was 5.09 mm, with mean systematic error of 1.23 mm and mean random setup error of 2.61 mm. Required margin for CTV‐PTV expansion was 4.6 mm for all cohort points, while the bootstrap estimator of the equivalent margin was 4.9 mm. The calculated OAR‐to‐PRV expansion for the observed residual setup error was 2.7 mm and bootstrap estimated expansion of 2.9 mm. We conclude that the interfractional larynx setup error is a significant source of RT setup/delivery error in HNC, both when the larynx is considered as a CTV or OAR. We estimate the need for a uniform expansion of 5 mm to compensate for setup error if the larynx is a target, or 3 mm if the larynx is an OAR, when using a nonlaryngeal bony isocenter. PACS numbers: 87.55.D‐, 87.55.Qr

Modeling methodology for MLS range navigation system errors using flight test data

NASA Technical Reports Server (NTRS)

Karmali, M. S.; Phatak, A. V.

1982-01-01

Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.

[Population-based breast cancer screening: certainties, controversies, and future perspectives].

PubMed

Apesteguía Ciriza, Luis; Pina Insausti, Luis Javier

2014-01-01

Population-based breast cancer screening programs based on mammography must maintain a high level of quality, so the results must be constantly monitored. Although most authors consider that these programs have decreased the mortality due to breast cancer by about 30%, others claim that the mortality has decreased by only about 12% due to errors in the randomization of patients, because the rate of advanced tumors has hardly decreased and because adjuvant treatment also improves survival. Other criticisms focus on overdiagnosis and overtreatment. We believe that despite the unquestionable value of mammographic screening, we should be open to certain changes such as the stratification of patients by their level of risk and the introduction of complementary techniques like tomosynthesis, ultrasonography, and magnetic resonance imaging in selected cases. Copyright © 2012 SERAM. Published by Elsevier Espana. All rights reserved.

Improving data sharing in research with context-free encoded missing data.

PubMed

Hoevenaar-Blom, Marieke P; Guillemont, Juliette; Ngandu, Tiia; Beishuizen, Cathrien R L; Coley, Nicola; Moll van Charante, Eric P; Andrieu, Sandrine; Kivipelto, Miia; Soininen, Hilkka; Brayne, Carol; Meiller, Yannick; Richard, Edo

2017-01-01

Lack of attention to missing data in research may result in biased results, loss of power and reduced generalizability. Registering reasons for missing values at the time of data collection, or-in the case of sharing existing data-before making data available to other teams, can save time and efforts, improve scientific value and help to prevent erroneous assumptions and biased results. To ensure that encoding of missing data is sufficient to understand the reason why data are missing, it should ideally be context-free. Therefore, 11 context-free codes of missing data were carefully designed based on three completed randomized controlled clinical trials and tested in a new randomized controlled clinical trial by an international team consisting of clinical researchers and epidemiologists with extended experience in designing and conducting trials and an Information System expert. These codes can be divided into missing due to participant and/or participation characteristics (n = 6), missing by design (n = 4), and due to a procedural error (n = 1). Broad implementation of context-free missing data encoding may enhance the possibilities of data sharing and pooling, thus allowing more powerful analyses using existing data.

Probabilistic global maps of the CO2 column at daily and monthly scales from sparse satellite measurements

NASA Astrophysics Data System (ADS)

Chevallier, Frédéric; Broquet, Grégoire; Pierangelo, Clémence; Crisp, David

2017-07-01

The column-average dry air-mole fraction of carbon dioxide in the atmosphere (XCO2) is measured by scattered satellite measurements like those from the Orbiting Carbon Observatory (OCO-2). We show that global continuous maps of XCO2 (corresponding to level 3 of the satellite data) at daily or coarser temporal resolution can be inferred from these data with a Kalman filter built on a model of persistence. Our application of this approach on 2 years of OCO-2 retrievals indicates that the filter provides better information than a climatology of XCO2 at both daily and monthly scales. Provided that the assigned observation uncertainty statistics are tuned in each grid cell of the XCO2 maps from an objective method (based on consistency diagnostics), the errors predicted by the filter at daily and monthly scales represent the true error statistics reasonably well, except for a bias in the high latitudes of the winter hemisphere and a lack of resolution (i.e., a too small discrimination skill) of the predicted error standard deviations. Due to the sparse satellite sampling, the broad-scale patterns of XCO2 described by the filter seem to lag behind the real signals by a few weeks. Finally, the filter offers interesting insights into the quality of the retrievals, both in terms of random and systematic errors.

[Failure mode and effects analysis on computerized drug prescriptions].

PubMed

Paredes-Atenciano, J A; Roldán-Aviña, J P; González-García, Mercedes; Blanco-Sánchez, M C; Pinto-Melero, M A; Pérez-Ramírez, C; Calvo Rubio-Burgos, Miguel; Osuna-Navarro, F J; Jurado-Carmona, A M

2015-01-01

To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

Excitation of transverse dipole and quadrupole modes in a pure ion plasma in a linear Paul trap to study collective processes in intense beams

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

Gilson, Erik P.; Davidson, Ronald C.; Efthimion, Philip C.

Transverse dipole and quadrupole modes have been excited in a one-component cesium ion plasma trapped in the Paul Trap Simulator Experiment (PTSX) in order to characterize their properties and understand the effect of their excitation on equivalent long-distance beam propagation. The PTSX device is a compact laboratory Paul trap that simulates the transverse dynamics of a long, intense charge bunch propagating through an alternating-gradient transport system by putting the physicist in the beam's frame of reference. A pair of arbitrary function generators was used to apply trapping voltage waveform perturbations with a range of frequencies and, by changing which electrodesmore » were driven with the perturbation, with either a dipole or quadrupole spatial structure. The results presented in this paper explore the dependence of the perturbation voltage's effect on the perturbation duration and amplitude. Perturbations were also applied that simulate the effect of random lattice errors that exist in an accelerator with quadrupole magnets that are misaligned or have variance in their field strength. The experimental results quantify the growth in the equivalent transverse beam emittance that occurs due to the applied noise and demonstrate that the random lattice errors interact with the trapped plasma through the plasma's internal collective modes. Coherent periodic perturbations were applied to simulate the effects of magnet errors in circular machines such as storage rings. The trapped one component plasma is strongly affected when the perturbation frequency is commensurate with a plasma mode frequency. The experimental results, which help to understand the physics of quiescent intense beam propagation over large distances, are compared with analytic models.« less

Limitations of the planning organ at risk volume (PRV) concept.

PubMed

Stroom, Joep C; Heijmen, Ben J M

2006-09-01

Previously, we determined a planning target volume (PTV) margin recipe for geometrical errors in radiotherapy equal to M(T) = 2 Sigma + 0.7 sigma, with Sigma and sigma standard deviations describing systematic and random errors, respectively. In this paper, we investigated margins for organs at risk (OAR), yielding the so-called planning organ at risk volume (PRV). For critical organs with a maximum dose (D(max)) constraint, we calculated margins such that D(max) in the PRV is equal to the motion averaged D(max) in the (moving) clinical target volume (CTV). We studied margins for the spinal cord in 10 head-and-neck cases and 10 lung cases, each with two different clinical plans. For critical organs with a dose-volume constraint, we also investigated whether a margin recipe was feasible. For the 20 spinal cords considered, the average margin recipe found was: M(R) = 1.6 Sigma + 0.2 sigma with variations for systematic and random errors of 1.2 Sigma to 1.8 Sigma and -0.2 sigma to 0.6 sigma, respectively. The variations were due to differences in shape and position of the dose distributions with respect to the cords. The recipe also depended significantly on the volume definition of D(max). For critical organs with a dose-volume constraint, the PRV concept appears even less useful because a margin around, e.g., the rectum changes the volume in such a manner that dose-volume constraints stop making sense. The concept of PRV for planning of radiotherapy is of limited use. Therefore, alternative ways should be developed to include geometric uncertainties of OARs in radiotherapy planning.

Do Old Errors Always Lead to New Truths? A Randomized Controlled Trial of Errorless Goal Management Training in Brain-Injured Patients.

PubMed

Bertens, Dirk; Kessels, Roy P C; Fiorenzato, Eleonora; Boelen, Danielle H E; Fasotti, Luciano

2015-09-01

Both errorless learning (EL) and Goal Management Training (GMT) have been shown effective cognitive rehabilitation methods aimed at optimizing the performance on everyday skills after brain injury. We examine whether a combination of EL and GMT is superior to traditional GMT for training complex daily tasks in brain-injured patients with executive dysfunction. This was an assessor-blinded randomized controlled trial conducted in 67 patients with executive impairments due to brain injury of non-progressive nature (minimal post-onset time: 3 months), referred for outpatient rehabilitation. Individually selected everyday tasks were trained using 8 sessions of an experimental combination of EL and GMT or via conventional GMT, which follows a trial-and-error approach. Primary outcome measure was everyday task performance assessed after treatment compared to baseline. Goal attainment scaling, rated by both trainers and patients, was used as secondary outcome measure. EL-GMT improved everyday task performance significantly more than conventional GMT (adjusted difference 15.43, 95% confidence interval [CI] [4.52, 26.35]; Cohen's d=0.74). Goal attainment, as scored by the trainers, was significantly higher after EL-GMT compared to conventional GMT (mean difference 7.34, 95% CI [2.99, 11.68]; Cohen's d=0.87). The patients' goal attainment scores did not differ between the two treatment arms (mean difference 3.51, 95% CI [-1.41, 8.44]). Our study is the first to show that preventing the occurrence of errors during executive strategy training enhances the acquisition of everyday activities. A combined EL-GMT intervention is a valuable contribution to cognitive rehabilitation in clinical practice.

Pointing control for LDR

NASA Technical Reports Server (NTRS)

Yam, Y.; Briggs, C.

1988-01-01

One important aspect of the LDR control problem is the possible excitations of structural modes due to random disturbances, mirror chopping, and slewing maneuvers. An analysis was performed to yield a first order estimate of the effects of such dynamic excitations. The analysis involved a study of slewing jitters, chopping jitters, disturbance responses, and pointing errors, making use of a simplified planar LDR model which describes the LDR dynamics on a plane perpendicular to the primary reflector. Briefly, the results indicate that the command slewing profile plays an important role in minimizing the resultant jitter, even to a level acceptable without any control action. An optimal profile should therefore be studied.

Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors

PubMed Central

Shah, Priya; Wyatt, Jeremy C; Makubate, Boikanyo; Cross, Frank W

2011-01-01

Objective Expert authorities recommend clinical decision support systems to reduce prescribing error rates, yet large numbers of insignificant on-screen alerts presented in modal dialog boxes persistently interrupt clinicians, limiting the effectiveness of these systems. This study compared the impact of modal and non-modal electronic (e-) prescribing alerts on prescribing error rates, to help inform the design of clinical decision support systems. Design A randomized study of 24 junior doctors each performing 30 simulated prescribing tasks in random order with a prototype e-prescribing system. Using a within-participant design, doctors were randomized to be shown one of three types of e-prescribing alert (modal, non-modal, no alert) during each prescribing task. Measurements The main outcome measure was prescribing error rate. Structured interviews were performed to elicit participants' preferences for the prescribing alerts and their views on clinical decision support systems. Results Participants exposed to modal alerts were 11.6 times less likely to make a prescribing error than those not shown an alert (OR 11.56, 95% CI 6.00 to 22.26). Those shown a non-modal alert were 3.2 times less likely to make a prescribing error (OR 3.18, 95% CI 1.91 to 5.30) than those not shown an alert. The error rate with non-modal alerts was 3.6 times higher than with modal alerts (95% CI 1.88 to 7.04). Conclusions Both kinds of e-prescribing alerts significantly reduced prescribing error rates, but modal alerts were over three times more effective than non-modal alerts. This study provides new evidence about the relative effects of modal and non-modal alerts on prescribing outcomes. PMID:21836158

Statistics of the epoch of reionization 21-cm signal - I. Power spectrum error-covariance

NASA Astrophysics Data System (ADS)

Mondal, Rajesh; Bharadwaj, Somnath; Majumdar, Suman

2016-02-01

The non-Gaussian nature of the epoch of reionization (EoR) 21-cm signal has a significant impact on the error variance of its power spectrum P(k). We have used a large ensemble of seminumerical simulations and an analytical model to estimate the effect of this non-Gaussianity on the entire error-covariance matrix {C}ij. Our analytical model shows that {C}ij has contributions from two sources. One is the usual variance for a Gaussian random field which scales inversely of the number of modes that goes into the estimation of P(k). The other is the trispectrum of the signal. Using the simulated 21-cm Signal Ensemble, an ensemble of the Randomized Signal and Ensembles of Gaussian Random Ensembles we have quantified the effect of the trispectrum on the error variance {C}II. We find that its relative contribution is comparable to or larger than that of the Gaussian term for the k range 0.3 ≤ k ≤ 1.0 Mpc-1, and can be even ˜200 times larger at k ˜ 5 Mpc-1. We also establish that the off-diagonal terms of {C}ij have statistically significant non-zero values which arise purely from the trispectrum. This further signifies that the error in different k modes are not independent. We find a strong correlation between the errors at large k values (≥0.5 Mpc-1), and a weak correlation between the smallest and largest k values. There is also a small anticorrelation between the errors in the smallest and intermediate k values. These results are relevant for the k range that will be probed by the current and upcoming EoR 21-cm experiments.

Evaluation and optimization of sampling errors for the Monte Carlo Independent Column Approximation

NASA Astrophysics Data System (ADS)

Räisänen, Petri; Barker, W. Howard

2004-07-01

The Monte Carlo Independent Column Approximation (McICA) method for computing domain-average broadband radiative fluxes is unbiased with respect to the full ICA, but its flux estimates contain conditional random noise. McICA's sampling errors are evaluated here using a global climate model (GCM) dataset and a correlated-k distribution (CKD) radiation scheme. Two approaches to reduce McICA's sampling variance are discussed. The first is to simply restrict all of McICA's samples to cloudy regions. This avoids wasting precious few samples on essentially homogeneous clear skies. Clear-sky fluxes need to be computed separately for this approach, but this is usually done in GCMs for diagnostic purposes anyway. Second, accuracy can be improved by repeated sampling, and averaging those CKD terms with large cloud radiative effects. Although this naturally increases computational costs over the standard CKD model, random errors for fluxes and heating rates are reduced by typically 50% to 60%, for the present radiation code, when the total number of samples is increased by 50%. When both variance reduction techniques are applied simultaneously, globally averaged flux and heating rate random errors are reduced by a factor of #3.

An efficient computational method for characterizing the effects of random surface errors on the average power pattern of reflectors

NASA Technical Reports Server (NTRS)

Rahmat-Samii, Y.

1983-01-01

Based on the works of Ruze (1966) and Vu (1969), a novel mathematical model has been developed to determine efficiently the average power pattern degradations caused by random surface errors. In this model, both nonuniform root mean square (rms) surface errors and nonuniform illumination functions are employed. In addition, the model incorporates the dependence on F/D in the construction of the solution. The mathematical foundation of the model rests on the assumption that in each prescribed annular region of the antenna, the geometrical rms surface value is known. It is shown that closed-form expressions can then be derived, which result in a very efficient computational method for the average power pattern. Detailed parametric studies are performed with these expressions to determine the effects of different random errors and illumination tapers on parameters such as gain loss and sidelobe levels. The results clearly demonstrate that as sidelobe levels decrease, their dependence on the surface rms/wavelength becomes much stronger and, for a specified tolerance level, a considerably smaller rms/wavelength is required to maintain the low sidelobes within the required bounds.

Screening actuator locations for static shape control

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

1990-01-01

Correction of shape distortion due to zero-mean normally distributed errors in structural sizes which are random variables is examined. A bound on the maximum improvement in the expected value of the root-mean-square shape error is obtained. The shape correction associated with the optimal actuators is also characterized. An actuator effectiveness index is developed and shown to be helpful in screening actuator locations in the structure. The results are specialized to a simple form for truss structures composed of nominally identical members. The bound and effectiveness index are tested on a 55-m radiometer antenna truss structure. It is found that previously obtained results for optimum actuators had a performance close to the bound obtained here. Furthermore, the actuators associated with the optimum design are shown to have high effectiveness indices. Since only a small fraction of truss elements tend to have high effectiveness indices, the proposed screening procedure can greatly reduce the number of truss members that need to be considered as actuator sites.

Efficient Sparse Signal Transmission over a Lossy Link Using Compressive Sensing

PubMed Central

Wu, Liantao; Yu, Kai; Cao, Dongyu; Hu, Yuhen; Wang, Zhi

2015-01-01

Reliable data transmission over lossy communication link is expensive due to overheads for error protection. For signals that have inherent sparse structures, compressive sensing (CS) is applied to facilitate efficient sparse signal transmissions over lossy communication links without data compression or error protection. The natural packet loss in the lossy link is modeled as a random sampling process of the transmitted data, and the original signal will be reconstructed from the lossy transmission results using the CS-based reconstruction method at the receiving end. The impacts of packet lengths on transmission efficiency under different channel conditions have been discussed, and interleaving is incorporated to mitigate the impact of burst data loss. Extensive simulations and experiments have been conducted and compared to the traditional automatic repeat request (ARQ) interpolation technique, and very favorable results have been observed in terms of both accuracy of the reconstructed signals and the transmission energy consumption. Furthermore, the packet length effect provides useful insights for using compressed sensing for efficient sparse signal transmission via lossy links. PMID:26287195

Narrowband (LPC-10) Vocoder Performance under Combined Effects of Random Bit Errors and Jet Aircraft Cabin Noise.

DTIC Science & Technology

1983-12-01

rAD-141 333 NRRROWRAND (LPC-iB) VOCODER PERFORMANCE UNDER COMBINED i/ EFFECTS OF RRNDOM.(U) ROME AIR DEVELOPMENT CENTER GRIFFISS RFB NY C P SMITH DEC...LPC-10) VOCODER In House. PERFORMANCE UNDER COMBINED EFFECTS June 82 - Sept. 83 OF RANDOM BIT ERRORS AND JET AIRCRAFT Z PERFORMING ORG REPO- NUMSEF...PAGE(Wh.n Does Eneerd) 20. (contd) Compartment, and NCA Compartment were alike in their effects on overall vocoder performance . Composite performance

Insight into organic reactions from the direct random phase approximation and its corrections

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

Ruzsinszky, Adrienn; Zhang, Igor Ying; Scheffler, Matthias

2015-10-14

The performance of the random phase approximation (RPA) and beyond-RPA approximations for the treatment of electron correlation is benchmarked on three different molecular test sets. The test sets are chosen to represent three typical sources of error which can contribute to the failure of most density functional approximations in chemical reactions. The first test set (atomization and n-homodesmotic reactions) offers a gradually increasing balance of error from the chemical environment. The second test set (Diels-Alder reaction cycloaddition = DARC) reflects more the effect of weak dispersion interactions in chemical reactions. Finally, the third test set (self-interaction error 11 = SIE11)more » represents reactions which are exposed to noticeable self-interaction errors. This work seeks to answer whether any one of the many-body approximations considered here successfully addresses all these challenges.« less

Nano-metrology: The art of measuring X-ray mirrors with slope errors <100 nrad

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

Alcock, Simon G., E-mail: simon.alcock@diamond.ac.uk; Nistea, Ioana; Sawhney, Kawal

2016-05-15

We present a comprehensive investigation of the systematic and random errors of the nano-metrology instruments used to characterize synchrotron X-ray optics at Diamond Light Source. With experimental skill and careful analysis, we show that these instruments used in combination are capable of measuring state-of-the-art X-ray mirrors. Examples are provided of how Diamond metrology data have helped to achieve slope errors of <100 nrad for optical systems installed on synchrotron beamlines, including: iterative correction of substrates using ion beam figuring and optimal clamping of monochromator grating blanks in their holders. Simulations demonstrate how random noise from the Diamond-NOM’s autocollimator adds intomore » the overall measured value of the mirror’s slope error, and thus predict how many averaged scans are required to accurately characterize different grades of mirror.« less

The Gnomon Experiment

NASA Astrophysics Data System (ADS)

Krisciunas, Kevin

2007-12-01

A gnomon, or vertical pointed stick, can be used to determine the north-south direction at a site, as well as one's latitude. If one has accurate time and knows one's time zone, it is also possible to determine one's longitude. From observations on the first day of winter and the first day of summer one can determine the obliquity of the ecliptic. Since we can obtain accurate geographical coordinates from Google Earth or a GPS device, analysis of set of shadow length measurements can be used by students to learn about astronomical coordinate systems, time systems, systematic errors, and random errors. Systematic latitude errors of student datasets are typically 30 nautical miles (0.5 degree) or more, but with care one can achieve systematic and random errors less than 8 nautical miles. One of the advantages of this experiment is that it can be carried out during the day. Also, it is possible to determine if a student has made up his data.

Biometrics encryption combining palmprint with two-layer error correction codes

NASA Astrophysics Data System (ADS)

Li, Hengjian; Qiu, Jian; Dong, Jiwen; Feng, Guang

2017-07-01

To bridge the gap between the fuzziness of biometrics and the exactitude of cryptography, based on combining palmprint with two-layer error correction codes, a novel biometrics encryption method is proposed. Firstly, the randomly generated original keys are encoded by convolutional and cyclic two-layer coding. The first layer uses a convolution code to correct burst errors. The second layer uses cyclic code to correct random errors. Then, the palmprint features are extracted from the palmprint images. Next, they are fused together by XORing operation. The information is stored in a smart card. Finally, the original keys extraction process is the information in the smart card XOR the user's palmprint features and then decoded with convolutional and cyclic two-layer code. The experimental results and security analysis show that it can recover the original keys completely. The proposed method is more secure than a single password factor, and has higher accuracy than a single biometric factor.

Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

NASA Technical Reports Server (NTRS)

Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

2016-01-01

Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

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.

Reflective properties of randomly rough surfaces under large incidence angles.

PubMed

Qiu, J; Zhang, W J; Liu, L H; Hsu, P-f; Liu, L J

2014-06-01

The reflective properties of randomly rough surfaces at large incidence angles have been reported due to their potential applications in some of the radiative heat transfer research areas. The main purpose of this work is to investigate the formation mechanism of the specular reflection peak of rough surfaces at large incidence angles. The bidirectional reflectance distribution function (BRDF) of rough aluminum surfaces with different roughnesses at different incident angles is measured by a three-axis automated scatterometer. This study used a validated and accurate computational model, the rigorous coupled-wave analysis (RCWA) method, to compare and analyze the measurement BRDF results. It is found that the RCWA results show the same trend of specular peak as the measurement. This paper mainly focuses on the relative roughness at the range of 0.16<σ/λ<5.35. As the relative roughness decreases, the specular peak enhancement dramatically increases and the scattering region significantly reduces, especially under large incidence angles. The RCWA and the Rayleigh criterion results have been compared, showing that the relative error of the total integrated scatter increases as the roughness of the surface increases at large incidence angles. In addition, the zero-order diffractive power calculated by RCWA and the reflectance calculated by Fresnel equations are compared. The comparison shows that the relative error declines sharply when the incident angle is large and the roughness is small.

[Efficacy of motivational interviewing for reducing medication errors in chronic patients over 65 years with polypharmacy: Results of a cluster randomized trial].

PubMed

Pérula de Torres, Luis Angel; Pulido Ortega, Laura; Pérula de Torres, Carlos; González Lama, Jesús; Olaya Caro, Inmaculada; Ruiz Moral, Roger

2014-10-21

To evaluate the effectiveness of an intervention based on motivational interviewing to reduce medication errors in chronic patients over 65 with polypharmacy. Cluster randomized trial that included doctors and nurses of 16 Primary Care centers and chronic patients with polypharmacy over 65 years. The professionals were assigned to the experimental or the control group using stratified randomization. Interventions consisted of training of professionals and revision of patient treatments, application of motivational interviewing in the experimental group and also the usual approach in the control group. The primary endpoint (medication error) was analyzed at individual level, and was estimated with the absolute risk reduction (ARR), relative risk reduction (RRR), number of subjects to treat (NNT) and by multiple logistic regression analysis. Thirty-two professionals were randomized (19 doctors and 13 nurses), 27 of them recruited 154 patients consecutively (13 professionals in the experimental group recruited 70 patients and 14 professionals recruited 84 patients in the control group) and completed 6 months of follow-up. The mean age of patients was 76 years (68.8% women). A decrease in the average of medication errors was observed along the period. The reduction was greater in the experimental than in the control group (F=5.109, P=.035). RRA 29% (95% confidence interval [95% CI] 15.0-43.0%), RRR 0.59 (95% CI:0.31-0.76), and NNT 3.5 (95% CI 2.3-6.8). Motivational interviewing is more efficient than the usual approach to reduce medication errors in patients over 65 with polypharmacy. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

DOE PAGES

Ye, Xin; Garikapati, Venu M.; You, Daehyun; ...

2017-11-08

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

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

Ye, Xin; Garikapati, Venu M.; You, Daehyun

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less

Estimation of attitude sensor timetag biases

NASA Technical Reports Server (NTRS)

Sedlak, J.

1995-01-01

This paper presents an extended Kalman filter for estimating attitude sensor timing errors. Spacecraft attitude is determined by finding the mean rotation from a set of reference vectors in inertial space to the corresponding observed vectors in the body frame. Any timing errors in the observations can lead to attitude errors if either the spacecraft is rotating or the reference vectors themselves vary with time. The state vector here consists of the attitude quaternion, timetag biases, and, optionally, gyro drift rate biases. The filter models the timetags as random walk processes: their expectation values propagate as constants and white noise contributes to their covariance. Thus, this filter is applicable to cases where the true timing errors are constant or slowly varying. The observability of the state vector is studied first through an examination of the algebraic observability condition and then through several examples with simulated star tracker timing errors. The examples use both simulated and actual flight data from the Extreme Ultraviolet Explorer (EUVE). The flight data come from times when EUVE had a constant rotation rate, while the simulated data feature large angle attitude maneuvers. The tests include cases with timetag errors on one or two sensors, both constant and time-varying, and with and without gyro bias errors. Due to EUVE's sensor geometry, the observability of the state vector is severely limited when the spacecraft rotation rate is constant. In the absence of attitude maneuvers, the state elements are highly correlated, and the state estimate is unreliable. The estimates are particularly sensitive to filter mistuning in this case. The EUVE geometry, though, is a degenerate case having coplanar sensors and rotation vector. Observability is much improved and the filter performs well when the rate is either varying or noncoplanar with the sensors, as during a slew. Even with bad geometry and constant rates, if gyro biases are independently known, the timetag error for a single sensor can be accurately estimated as long as its boresight is not too close to the spacecraft rotation axis.

Regional Carbon Dioxide and Water Vapor Exchange Over Heterogeneous Terrain

NASA Technical Reports Server (NTRS)

Mahrt, Larry J.

2005-01-01

In spite of setbacks due to forest fires, eviction after a change of landowners and unanticipated need to upgrade and replace much of the instrumentation, substantial progress has been made during the past three years, resulting in major new findings. Although most of the results are in manuscript form, three papers have been published and a fourth was recently submitted. The data has been subjected to extensive quality control. Extra attention has been devoted to the influence of tilt rotation and flux-calculation method, particularly with respect to nocturnal fluxes. Previous/standard methods for calculating nocturnal fluxes with moderate and strong stability are inadequate and lead to large random fluxes errors for individual records, due partly to inadvertent inclusion of mesoscale motions that strongly contaminant the estimation of fluxes by weak turbulence. Such large errors are serious for process studies requiring carbon dioxide fluxes for individual records, but are substantially reduced when averaging fluxes over longer periods as in calculation of annual NEE budgets. We have employed a superior method for estimating fluxes in stable conditions with a variable averaging width . Mesoscale fluxes are generally unimportant except for events and are generally not systematic or predictable. Mesoscale or regional models of our region are not able to reproduce important aspects of the diurnally varying wind field

Supersonic Retro-Propulsion Experimental Design for Computational Fluid Dynamics Model Validation

NASA Technical Reports Server (NTRS)

Berry, Scott A.; Laws, Christopher T.; Kleb, W. L.; Rhode, Matthew N.; Spells, Courtney; McCrea, Andrew C.; Truble, Kerry A.; Schauerhamer, Daniel G.; Oberkampf, William L.

2011-01-01

The development of supersonic retro-propulsion, an enabling technology for heavy payload exploration missions to Mars, is the primary focus for the present paper. A new experimental model, intended to provide computational fluid dynamics model validation data, was recently designed for the Langley Research Center Unitary Plan Wind Tunnel Test Section 2. Pre-test computations were instrumental for sizing and refining the model, over the Mach number range of 2.4 to 4.6, such that tunnel blockage and internal flow separation issues would be minimized. A 5-in diameter 70-deg sphere-cone forebody, which accommodates up to four 4:1 area ratio nozzles, followed by a 10-in long cylindrical aftbody was developed for this study based on the computational results. The model was designed to allow for a large number of surface pressure measurements on the forebody and aftbody. Supplemental data included high-speed Schlieren video and internal pressures and temperatures. The run matrix was developed to allow for the quantification of various sources of experimental uncertainty, such as random errors due to run-to-run variations and bias errors due to flow field or model misalignments. Some preliminary results and observations from the test are presented, although detailed analyses of the data and uncertainties are still on going.

[Comparative volumetry of human testes using special types of testicular sonography, Prader's orchidometer, Schirren's circle and sliding caliber].

PubMed

Dörnberger, V; Dörnberger, G

1987-01-01

On 99 testes of corpses (death had occurred between 26 und 86 years) comparative volumetry was done. In the left surrounding capsules (without scrotal skin and tunica dartos) the testes were measured via real time sonography in a waterbath (7.5 MHz linear-scan), afterwards length, breadth and height were measured by a sliding calibre, the largest diameter (the length) of the testis was determined by Schirren's circle and finally the size of the testis was measured via Prader's orchidometer. After all the testes were surgically exposed, their volume (by litres) was determined according to Archimedes' principle. As for the Archimedes' principle a random mean error of 7% must be accepted, sonographic determination of the volume showed a random mean error of 15%. Whereas the accuracy of measurement increases with increasing volumes, both methods should be used with caution if the volumes are below 4 ml, since the possibilities of error are rather great. According to Prader's orchidometer the measured volumes on average were higher (+ 27%) with a random mean error of 19.5%. With Schirren's circle the obtained mean value was even higher (+ 52%) in comparison to the "real" volume by Archimedes' principle with a random mean error of 19%. The measurements of the testes in the left capsules by sliding calibre can be optimized, if one applies a correcting factor f (sliding calibre) = 0.39 for calculation of the testis volume corresponding to an ellipsoid. Here you will get the same mean value as in Archimedes' principle with a standard mean error of only 9%. If one applies the correction factor of real time sonography of testis f (sono) = 0.65 the mean value of sliding calibre measurements would be 68.8% too high with a standard mean error of 20.3%. For measurements via sliding calibre the calculation of the testis volume corresponding to an ellipsoid one should apply the smaller factor f (sliding calibre) = 0.39, because in this way the left capsules of testis and the epididymis are considered.

Variability And Uncertainty Analysis Of Contaminant Transport Model Using Fuzzy Latin Hypercube Sampling Technique

NASA Astrophysics Data System (ADS)

Kumar, V.; Nayagum, D.; Thornton, S.; Banwart, S.; Schuhmacher2, M.; Lerner, D.

2006-12-01

Characterization of uncertainty associated with groundwater quality models is often of critical importance, as for example in cases where environmental models are employed in risk assessment. Insufficient data, inherent variability and estimation errors of environmental model parameters introduce uncertainty into model predictions. However, uncertainty analysis using conventional methods such as standard Monte Carlo sampling (MCS) may not be efficient, or even suitable, for complex, computationally demanding models and involving different nature of parametric variability and uncertainty. General MCS or variant of MCS such as Latin Hypercube Sampling (LHS) assumes variability and uncertainty as a single random entity and the generated samples are treated as crisp assuming vagueness as randomness. Also when the models are used as purely predictive tools, uncertainty and variability lead to the need for assessment of the plausible range of model outputs. An improved systematic variability and uncertainty analysis can provide insight into the level of confidence in model estimates, and can aid in assessing how various possible model estimates should be weighed. The present study aims to introduce, Fuzzy Latin Hypercube Sampling (FLHS), a hybrid approach of incorporating cognitive and noncognitive uncertainties. The noncognitive uncertainty such as physical randomness, statistical uncertainty due to limited information, etc can be described by its own probability density function (PDF); whereas the cognitive uncertainty such estimation error etc can be described by the membership function for its fuzziness and confidence interval by ?-cuts. An important property of this theory is its ability to merge inexact generated data of LHS approach to increase the quality of information. The FLHS technique ensures that the entire range of each variable is sampled with proper incorporation of uncertainty and variability. A fuzzified statistical summary of the model results will produce indices of sensitivity and uncertainty that relate the effects of heterogeneity and uncertainty of input variables to model predictions. The feasibility of the method is validated to assess uncertainty propagation of parameter values for estimation of the contamination level of a drinking water supply well due to transport of dissolved phenolics from a contaminated site in the UK.

Setup deviations for whole-breast radiotherapy with TomoDirect: A comparison of weekly and biweekly image-guided protocols

NASA Astrophysics Data System (ADS)

Jung, Jae Hong; Jung, Joo-Young; Bae, Sun Hyun; Moon, Seong Kwon; Cho, Kwang Hwan

2016-10-01

The purpose of this study was to compare patient setup deviations for different image-guided protocols (weekly vs. biweekly) that are used in TomoDirect three-dimensional conformal radiotherapy (TD-3DCRT) for whole-breast radiation therapy (WBRT). A total of 138 defined megavoltage computed tomography (MVCT) image sets from 46 breast cancer cases were divided into two groups based on the imaging acquisition times: weekly or biweekly. The mean error, three-dimensional setup displacement error (3D-error), systematic error (Σ), and random error (σ) were calculated for each group. The 3D-errors were 4.29 ± 1.11 mm and 5.02 ± 1.85 mm for the weekly and biweekly groups, respectively; the biweekly error was 14.6% higher than the weekly error. The systematic errors in the roll angle and the x, y, and z directions were 0.48°, 1.72 mm, 2.18 mm, and 1.85 mm for the weekly protocol and 0.21°, 1.24 mm, 1.39 mm, and 1.85 mm for the biweekly protocol. Random errors in the roll angle and the x, y, and z directions were 25.7%, 40.6%, 40.0%, and 40.8% higher in the biweekly group than in the weekly group. For the x, y, and z directions, the distributions of the treatment frequency at less than 5 mm were 98.6%, 91.3%, and 94.2% in the weekly group and 94.2%, 89.9%, and 82.6% in the biweekly group. Moreover, the roll angles with 0 - 1° were 79.7% and 89.9% in the weekly and the biweekly groups, respectively. Overall, the evaluation of setup deviations for the two protocols revealed no significant differences (p > 0.05). Reducing the frequency of MVCT imaging could have promising effects on imaging doses and machine times during treatment. However, the biweekly protocol was associated with increased random setup deviations in the treatment. We have demonstrated a biweekly protocol of TD-3DCRT for WBRT, and we anticipate that our method may provide an alternative approach for considering the uncertainties in the patient setup.

Documentation of study medication dispensing in a prospective large randomized clinical trial: experiences from the ARISTOTLE Trial.

PubMed

Alexander, John H; Levy, Elliott; Lawrence, Jack; Hanna, Michael; Waclawski, Anthony P; Wang, Junyuan; Califf, Robert M; Wallentin, Lars; Granger, Christopher B

2013-09-01

In ARISTOTLE, apixaban resulted in a 21% reduction in stroke, a 31% reduction in major bleeding, and an 11% reduction in death. However, approval of apixaban was delayed to investigate a statement in the clinical study report that "7.3% of subjects in the apixaban group and 1.2% of subjects in the warfarin group received, at some point during the study, a container of the wrong type." Rates of study medication dispensing error were characterized through reviews of study medication container tear-off labels in 6,520 participants from randomly selected study sites. The potential effect of dispensing errors on study outcomes was statistically simulated in sensitivity analyses in the overall population. The rate of medication dispensing error resulting in treatment error was 0.04%. Rates of participants receiving at least 1 incorrect container were 1.04% (34/3,273) in the apixaban group and 0.77% (25/3,247) in the warfarin group. Most of the originally reported errors were data entry errors in which the correct medication container was dispensed but the wrong container number was entered into the case report form. Sensitivity simulations in the overall trial population showed no meaningful effect of medication dispensing error on the main efficacy and safety outcomes. Rates of medication dispensing error were low and balanced between treatment groups. The initially reported dispensing error rate was the result of data recording and data management errors and not true medication dispensing errors. These analyses confirm the previously reported results of ARISTOTLE. © 2013.

Combined application of airborne and terrestrial laserscanning for quantifying sediment relocation by a large debris flow event

NASA Astrophysics Data System (ADS)

Bremer, Magnus; Sass, Oliver; Vetter, Michael; Geilhausen, Martin

2010-05-01

Country-wide ALS datasets of high resolution become more and more available and can provide a solid basis for geomorphological research. On the other hand, terrain changes after geomorphological extreme events can be quickly and flexibly documented by TLS and be compared to the pre-existing ALS datasets. For quantifying net-erosion, net-sedimentation and transport rates of events like rock falls, landslides and debris flows, comparing TLS surveys after the event to ALS data before the event is likely to become a widespread and powerful tool. However, the accuracy and possible errors of fitting ALS and TLS data have to be carefully assessed. We tried to quantify sediment movement and terrain changes caused by a major debris-flow-event in the Halltal in the Karwendel Mountains (Tyrol, Austria). Wide areas of limestone debris were dissected and relocated in the course of an exceptional rainstorm event on 29th June 2008. The event occurred 64 years after wildfire-driven deforestation. In the area, dense dwarf pine (pinus mugo) shrub cover is widespread, causing specific problems in generating terrain models. We compared a pre-event ALS-dataset, provided by the federal-state of Tyrol, and a post-event TLS survey. The two scanner systems have differing system characteristics (scan angles, resolutions, application of dGPS, etc.), causing different systematic and random errors. Combining TLS and ALS point data was achieved using an algorithm of the RISCAN_PRO software (Multi Station Adjustment), enabling a least square fitting between the two surfaces. Adjustment and registration accuracies as well as the quality of applied vegetation filters, mainly eliminating non-groundpoints from the raw data, are crucial for the generation of high-quality terrain models and a reliable comparison of the two data sets. Readily available filter algorithms provide good performance for gently sloped terrain and high forest vegetation. However, the low krummholz vegetation on steep terrain proved difficult to be filtered. This is due to a small height difference between terrain and canopy, a very strong height variation of the terrain points compared to the height variation of the canopy points and a very high density of the vegetation. The letter leads to very low percentages of groundpoints (1 - 5%). A combined filtering approach using a surface-based filter and a morphological filter, adapted to the characteristics of the krummholz vegetation were applied to overcome these problems. In the next step, the datasets were compared, erosion- and sedimentation areas were detected and quantified (cut-and-fill) in view of the accuracy achieved. The position of the relocated surface areas were compared to the morphological structures of the initial surface (inclination, curvature, flowpaths, hydrological catchments). Considerable deviations between the datasets were caused, besides the geomorphic terrain changes, by systematic and random errors. Due to the scanner perspective, parts of the steep slopes are depicted inaccurately by ALS. Rugged terrain surfaces cause random errors of ALS/TLS adjustment when the ratio of point density to surface variability is low. Due to multiple returns and alteration of pulse shape, terrain altitude is frequently overestimated when dense shrub cover is present. This effect becomes stronger with larger footprints. Despite these problems, erosional and depositional areas of debris flows could be clearly identified and match the results of field surveys. Strongest erosion occurred along the flowpaths with the greatest runoff concentration, mainly at the bedrock-debris interface.

A steep peripheral ring in irregular cornea topography, real or an instrument error?

PubMed

Galindo-Ferreiro, Alicia; Galvez-Ruiz, Alberto; Schellini, Silvana A; Galindo-Alonso, Julio

2016-01-01

To demonstrate that the steep peripheral ring (red zone) on corneal topography after myopic laser in situ keratomileusis (LASIK) could possibly due to instrument error and not always to a real increase in corneal curvature. A spherical model for the corneal surface and modifying topography software was used to analyze the cause of an error due to instrument design. This study involved modification of the software of a commercially available topographer. A small modification of the topography image results in a red zone on the corneal topography color map. Corneal modeling indicates that the red zone could be an artifact due to an instrument-induced error. The steep curvature changes after LASIK, signified by the red zone, could be also an error due to the plotting algorithms of the corneal topographer, besides a steep curvature change.

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

Test-retest reliability of jump execution variables using mechanography: a comparison of jump protocols.

PubMed

Fitzgerald, John S; Johnson, LuAnn; Tomkinson, Grant; Stein, Jesse; Roemmich, James N

2018-05-01

Mechanography during the vertical jump may enhance screening and determining mechanistic causes underlying physical performance changes. Utility of jump mechanography for evaluation is limited by scant test-retest reliability data on force-time variables. This study examined the test-retest reliability of eight jump execution variables assessed from mechanography. Thirty-two women (mean±SD: age 20.8 ± 1.3 yr) and 16 men (age 22.1 ± 1.9 yr) attended a familiarization session and two testing sessions, all one week apart. Participants performed two variations of the squat jump with squat depth self-selected and controlled using a goniometer to 80º knee flexion. Test-retest reliability was quantified as the systematic error (using effect size between jumps), random error (using coefficients of variation), and test-retest correlations (using intra-class correlation coefficients). Overall, jump execution variables demonstrated acceptable reliability, evidenced by small systematic errors (mean±95%CI: 0.2 ± 0.07), moderate random errors (mean±95%CI: 17.8 ± 3.7%), and very strong test-retest correlations (range: 0.73-0.97). Differences in random errors between controlled and self-selected protocols were negligible (mean±95%CI: 1.3 ± 2.3%). Jump execution variables demonstrated acceptable reliability, with no meaningful differences between the controlled and self-selected jump protocols. To simplify testing, a self-selected jump protocol can be used to assess force-time variables with negligible impact on measurement error.

Model Error Estimation for the CPTEC Eta Model

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; daSilva, Arlindo

1999-01-01

Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.

A general model for attitude determination error analysis

NASA Technical Reports Server (NTRS)

Markley, F. Landis; Seidewitz, ED; Nicholson, Mark

1988-01-01

An overview is given of a comprehensive approach to filter and dynamics modeling for attitude determination error analysis. The models presented include both batch least-squares and sequential attitude estimation processes for both spin-stabilized and three-axis stabilized spacecraft. The discussion includes a brief description of a dynamics model of strapdown gyros, but it does not cover other sensor models. Model parameters can be chosen to be solve-for parameters, which are assumed to be estimated as part of the determination process, or consider parameters, which are assumed to have errors but not to be estimated. The only restriction on this choice is that the time evolution of the consider parameters must not depend on any of the solve-for parameters. The result of an error analysis is an indication of the contributions of the various error sources to the uncertainties in the determination of the spacecraft solve-for parameters. The model presented gives the uncertainty due to errors in the a priori estimates of the solve-for parameters, the uncertainty due to measurement noise, the uncertainty due to dynamic noise (also known as process noise or measurement noise), the uncertainty due to the consider parameters, and the overall uncertainty due to all these sources of error.

The Hurst Phenomenon in Error Estimates Related to Atmospheric Turbulence

NASA Astrophysics Data System (ADS)

Dias, Nelson Luís; Crivellaro, Bianca Luhm; Chamecki, Marcelo

2018-05-01

The Hurst phenomenon is a well-known feature of long-range persistence first observed in hydrological and geophysical time series by E. Hurst in the 1950s. It has also been found in several cases in turbulence time series measured in the wind tunnel, the atmosphere, and in rivers. Here, we conduct a systematic investigation of the value of the Hurst coefficient H in atmospheric surface-layer data, and its impact on the estimation of random errors. We show that usually H > 0.5 , which implies the non-existence (in the statistical sense) of the integral time scale. Since the integral time scale is present in the Lumley-Panofsky equation for the estimation of random errors, this has important practical consequences. We estimated H in two principal ways: (1) with an extension of the recently proposed filtering method to estimate the random error (H_p ), and (2) with the classical rescaled range introduced by Hurst (H_R ). Other estimators were tried but were found less able to capture the statistical behaviour of the large scales of turbulence. Using data from three micrometeorological campaigns we found that both first- and second-order turbulence statistics display the Hurst phenomenon. Usually, H_R is larger than H_p for the same dataset, raising the question that one, or even both, of these estimators, may be biased. For the relative error, we found that the errors estimated with the approach adopted by us, that we call the relaxed filtering method, and that takes into account the occurrence of the Hurst phenomenon, are larger than both the filtering method and the classical Lumley-Panofsky estimates. Finally, we found that there is no apparent relationship between H and the Obukhov stability parameter. The relative errors, however, do show stability dependence, particularly in the case of the error of the kinematic momentum flux in unstable conditions, and that of the kinematic sensible heat flux in stable conditions.

A multiobserver study of the effects of including point-of-care patient photographs with portable radiography: a means to detect wrong-patient errors.

PubMed

Tridandapani, Srini; Ramamurthy, Senthil; Provenzale, James; Obuchowski, Nancy A; Evanoff, Michael G; Bhatti, Pamela

2014-08-01

To evaluate whether the presence of facial photographs obtained at the point-of-care of portable radiography leads to increased detection of wrong-patient errors. In this institutional review board-approved study, 166 radiograph-photograph combinations were obtained from 30 patients. Consecutive radiographs from the same patients resulted in 83 unique pairs (ie, a new radiograph and prior, comparison radiograph) for interpretation. To simulate wrong-patient errors, mismatched pairs were generated by pairing radiographs from different patients chosen randomly from the sample. Ninety radiologists each interpreted a unique randomly chosen set of 10 radiographic pairs, containing up to 10% mismatches (ie, error pairs). Radiologists were randomly assigned to interpret radiographs with or without photographs. The number of mismatches was identified, and interpretation times were recorded. Ninety radiologists with 21 ± 10 (mean ± standard deviation) years of experience were recruited to participate in this observer study. With the introduction of photographs, the proportion of errors detected increased from 31% (9 of 29) to 77% (23 of 30; P = .006). The odds ratio for detection of error with photographs to detection without photographs was 7.3 (95% confidence interval: 2.29-23.18). Observer qualifications, training, or practice in cardiothoracic radiology did not influence sensitivity for error detection. There is no significant difference in interpretation time for studies without photographs and those with photographs (60 ± 22 vs. 61 ± 25 seconds; P = .77). In this observer study, facial photographs obtained simultaneously with portable chest radiographs increased the identification of any wrong-patient errors, without substantial increase in interpretation time. This technique offers a potential means to increase patient safety through correct patient identification. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

A spatial error model with continuous random effects and an application to growth convergence

NASA Astrophysics Data System (ADS)

Laurini, Márcio Poletti

2017-10-01

We propose a spatial error model with continuous random effects based on Matérn covariance functions and apply this model for the analysis of income convergence processes (β -convergence). The use of a model with continuous random effects permits a clearer visualization and interpretation of the spatial dependency patterns, avoids the problems of defining neighborhoods in spatial econometrics models, and allows projecting the spatial effects for every possible location in the continuous space, circumventing the existing aggregations in discrete lattice representations. We apply this model approach to analyze the economic growth of Brazilian municipalities between 1991 and 2010 using unconditional and conditional formulations and a spatiotemporal model of convergence. The results indicate that the estimated spatial random effects are consistent with the existence of income convergence clubs for Brazilian municipalities in this period.

Reducing Modeling Error of Graphical Methods for Estimating Volume of Distribution Measurements in PIB-PET study

PubMed Central

Guo, Hongbin; Renaut, Rosemary A; Chen, Kewei; Reiman, Eric M

2010-01-01

Graphical analysis methods are widely used in positron emission tomography quantification because of their simplicity and model independence. But they may, particularly for reversible kinetics, lead to bias in the estimated parameters. The source of the bias is commonly attributed to noise in the data. Assuming a two-tissue compartmental model, we investigate the bias that originates from modeling error. This bias is an intrinsic property of the simplified linear models used for limited scan durations, and it is exaggerated by random noise and numerical quadrature error. Conditions are derived under which Logan's graphical method either over- or under-estimates the distribution volume in the noise-free case. The bias caused by modeling error is quantified analytically. The presented analysis shows that the bias of graphical methods is inversely proportional to the dissociation rate. Furthermore, visual examination of the linearity of the Logan plot is not sufficient for guaranteeing that equilibrium has been reached. A new model which retains the elegant properties of graphical analysis methods is presented, along with a numerical algorithm for its solution. We perform simulations with the fibrillar amyloid β radioligand [11C] benzothiazole-aniline using published data from the University of Pittsburgh and Rotterdam groups. The results show that the proposed method significantly reduces the bias due to modeling error. Moreover, the results for data acquired over a 70 minutes scan duration are at least as good as those obtained using existing methods for data acquired over a 90 minutes scan duration. PMID:20493196

Visual disability, visual function, and myopia among rural chinese secondary school children: the Xichang Pediatric Refractive Error Study (X-PRES)--report 1.

PubMed

Congdon, Nathan; Wang, Yunfei; Song, Yue; Choi, Kai; Zhang, Mingzhi; Zhou, Zhongxia; Xie, Zhenling; Li, Liping; Liu, Xueyu; Sharma, Abhishek; Wu, Bin; Lam, Dennis S C

2008-07-01

To evaluate visual acuity, visual function, and prevalence of refractive error among Chinese secondary-school children in a cross-sectional school-based study. Uncorrected, presenting, and best corrected visual acuity, cycloplegic autorefraction with refinement, and self-reported visual function were assessed in a random, cluster sample of rural secondary school students in Xichang, China. Among the 1892 subjects (97.3% of the consenting children, 84.7% of the total sample), mean age was 14.7 +/- 0.8 years, 51.2% were female, and 26.4% were wearing glasses. The proportion of children with uncorrected, presenting, and corrected visual disability (< or = 6/12 in the better eye) was 41.2%, 19.3%, and 0.5%, respectively. Myopia < -0.5, < -2.0, and < -6.0 D in both eyes was present in 62.3%, 31.1%, and 1.9% of the subjects, respectively. Among the children with visual disability when tested without correction, 98.7% was due to refractive error, while only 53.8% (414/770) of these children had appropriate correction. The girls had significantly (P < 0.001) more presenting visual disability and myopia < -2.0 D than did the boys. More myopic refractive error was associated with worse self-reported visual function (ANOVA trend test, P < 0.001). Visual disability in this population was common, highly correctable, and frequently uncorrected. The impact of refractive error on self-reported visual function was significant. Strategies and studies to understand and remove barriers to spectacle wear are needed.

The Propagation of Errors in Experimental Data Analysis: A Comparison of Pre-and Post-Test Designs

ERIC Educational Resources Information Center

Gorard, Stephen

2013-01-01

Experimental designs involving the randomization of cases to treatment and control groups are powerful and under-used in many areas of social science and social policy. This paper reminds readers of the pre-and post-test, and the post-test only, designs, before explaining briefly how measurement errors propagate according to error theory. The…

Analysis of Errors Committed by Physics Students in Secondary Schools in Ilorin Metropolis, Nigeria

ERIC Educational Resources Information Center

Omosewo, Esther Ore; Akanbi, Abdulrasaq Oladimeji

2013-01-01

The study attempt to find out the types of error committed and influence of gender on the type of error committed by senior secondary school physics students in metropolis. Six (6) schools were purposively chosen for the study. One hundred and fifty five students' scripts were randomly sampled for the study. Joint Mock physics essay questions…

Statistical models for estimating daily streamflow in Michigan

USGS Publications Warehouse

Holtschlag, D.J.; Salehi, Habib

1992-01-01

Statistical models for estimating daily streamflow were analyzed for 25 pairs of streamflow-gaging stations in Michigan. Stations were paired by randomly choosing a station operated in 1989 at which 10 or more years of continuous flow data had been collected and at which flow is virtually unregulated; a nearby station was chosen where flow characteristics are similar. Streamflow data from the 25 randomly selected stations were used as the response variables; streamflow data at the nearby stations were used to generate a set of explanatory variables. Ordinary-least squares regression (OLSR) equations, autoregressive integrated moving-average (ARIMA) equations, and transfer function-noise (TFN) equations were developed to estimate the log transform of flow for the 25 randomly selected stations. The precision of each type of equation was evaluated on the basis of the standard deviation of the estimation errors. OLSR equations produce one set of estimation errors; ARIMA and TFN models each produce l sets of estimation errors corresponding to the forecast lead. The lead-l forecast is the estimate of flow l days ahead of the most recent streamflow used as a response variable in the estimation. In this analysis, the standard deviation of lead l ARIMA and TFN forecast errors were generally lower than the standard deviation of OLSR errors for l < 2 days and l < 9 days, respectively. Composite estimates were computed as a weighted average of forecasts based on TFN equations and backcasts (forecasts of the reverse-ordered series) based on ARIMA equations. The standard deviation of composite errors varied throughout the length of the estimation interval and generally was at maximum near the center of the interval. For comparison with OLSR errors, the mean standard deviation of composite errors were computed for intervals of length 1 to 40 days. The mean standard deviation of length-l composite errors were generally less than the standard deviation of the OLSR errors for l < 32 days. In addition, the composite estimates ensure a gradual transition between periods of estimated and measured flows. Model performance among stations of differing model error magnitudes were compared by computing ratios of the mean standard deviation of the length l composite errors to the standard deviation of OLSR errors. The mean error ratio for the set of 25 selected stations was less than 1 for intervals l < 32 days. Considering the frequency characteristics of the length of intervals of estimated record in Michigan, the effective mean error ratio for intervals < 30 days was 0.52. Thus, for intervals of estimation of 1 month or less, the error of the composite estimate is substantially lower than error of the OLSR estimate.

Error coding simulations in C

NASA Technical Reports Server (NTRS)

Noble, Viveca K.

1994-01-01

When data is transmitted through a noisy channel, errors are produced within the data rendering it indecipherable. Through the use of error control coding techniques, the bit error rate can be reduced to any desired level without sacrificing the transmission data rate. The Astrionics Laboratory at Marshall Space Flight Center has decided to use a modular, end-to-end telemetry data simulator to simulate the transmission of data from flight to ground and various methods of error control. The simulator includes modules for random data generation, data compression, Consultative Committee for Space Data Systems (CCSDS) transfer frame formation, error correction/detection, error generation and error statistics. The simulator utilizes a concatenated coding scheme which includes CCSDS standard (255,223) Reed-Solomon (RS) code over GF(2(exp 8)) with interleave depth of 5 as the outermost code, (7, 1/2) convolutional code as an inner code and CCSDS recommended (n, n-16) cyclic redundancy check (CRC) code as the innermost code, where n is the number of information bits plus 16 parity bits. The received signal-to-noise for a desired bit error rate is greatly reduced through the use of forward error correction techniques. Even greater coding gain is provided through the use of a concatenated coding scheme. Interleaving/deinterleaving is necessary to randomize burst errors which may appear at the input of the RS decoder. The burst correction capability length is increased in proportion to the interleave depth. The modular nature of the simulator allows for inclusion or exclusion of modules as needed. This paper describes the development and operation of the simulator, the verification of a C-language Reed-Solomon code, and the possibility of using Comdisco SPW(tm) as a tool for determining optimal error control schemes.

Validation of prostate-specific antigen laboratory values recorded in Surveillance, Epidemiology, and End Results registries.

PubMed

Adamo, Margaret Peggy; Boten, Jessica A; Coyle, Linda M; Cronin, Kathleen A; Lam, Clara J K; Negoita, Serban; Penberthy, Lynne; Stevens, Jennifer L; Ward, Kevin C

2017-02-15

Researchers have used prostate-specific antigen (PSA) values collected by central cancer registries to evaluate tumors for potential aggressive clinical disease. An independent study collecting PSA values suggested a high error rate (18%) related to implied decimal points. To evaluate the error rate in the Surveillance, Epidemiology, and End Results (SEER) program, a comprehensive review of PSA values recorded across all SEER registries was performed. Consolidated PSA values for eligible prostate cancer cases in SEER registries were reviewed and compared with text documentation from abstracted records. Four types of classification errors were identified: implied decimal point errors, abstraction or coding implementation errors, nonsignificant errors, and changes related to "unknown" values. A total of 50,277 prostate cancer cases diagnosed in 2012 were reviewed. Approximately 94.15% of cases did not have meaningful changes (85.85% correct, 5.58% with a nonsignificant change of <1 ng/mL, and 2.80% with no clinical change). Approximately 5.70% of cases had meaningful changes (1.93% due to implied decimal point errors, 1.54% due to abstract or coding errors, and 2.23% due to errors related to unknown categories). Only 419 of the original 50,277 cases (0.83%) resulted in a change in disease stage due to a corrected PSA value. The implied decimal error rate was only 1.93% of all cases in the current validation study, with a meaningful error rate of 5.81%. The reasons for the lower error rate in SEER are likely due to ongoing and rigorous quality control and visual editing processes by the central registries. The SEER program currently is reviewing and correcting PSA values back to 2004 and will re-release these data in the public use research file. Cancer 2017;123:697-703. © 2016 American Cancer Society. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

Query construction, entropy, and generalization in neural-network models

NASA Astrophysics Data System (ADS)

Sollich, Peter

1994-05-01

We study query construction algorithms, which aim at improving the generalization ability of systems that learn from examples by choosing optimal, nonredundant training sets. We set up a general probabilistic framework for deriving such algorithms from the requirement of optimizing a suitable objective function; specifically, we consider the objective functions entropy (or information gain) and generalization error. For two learning scenarios, the high-low game and the linear perceptron, we evaluate the generalization performance obtained by applying the corresponding query construction algorithms and compare it to training on random examples. We find qualitative differences between the two scenarios due to the different structure of the underlying rules (nonlinear and ``noninvertible'' versus linear); in particular, for the linear perceptron, random examples lead to the same generalization ability as a sequence of queries in the limit of an infinite number of examples. We also investigate learning algorithms which are ill matched to the learning environment and find that, in this case, minimum entropy queries can in fact yield a lower generalization ability than random examples. Finally, we study the efficiency of single queries and its dependence on the learning history, i.e., on whether the previous training examples were generated randomly or by querying, and the difference between globally and locally optimal query construction.

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.

Stochastic characterization of phase detection algorithms in phase-shifting interferometry

DOE PAGES

Munteanu, Florin

2016-11-01

Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here,more » we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.« less

Study on the Rationality and Validity of Probit Models of Domino Effect to Chemical Process Equipment caused by Overpressure

NASA Astrophysics Data System (ADS)

Sun, Dongliang; Huang, Guangtuan; Jiang, Juncheng; Zhang, Mingguang; Wang, Zhirong

2013-04-01

Overpressure is one important cause of domino effect in accidents of chemical process equipments. Some models considering propagation probability and threshold values of the domino effect caused by overpressure have been proposed in previous study. In order to prove the rationality and validity of the models reported in the reference, two boundary values of three damage degrees reported were considered as random variables respectively in the interval [0, 100%]. Based on the overpressure data for damage to the equipment and the damage state, and the calculation method reported in the references, the mean square errors of the four categories of damage probability models of overpressure were calculated with random boundary values, and then a relationship of mean square error vs. the two boundary value was obtained, the minimum of mean square error was obtained, compared with the result of the present work, mean square error decreases by about 3%. Therefore, the error was in the acceptable range of engineering applications, the models reported can be considered reasonable and valid.

Vitamin D supplementation for prevention of cancer in adults.

PubMed

Bjelakovic, Goran; Gluud, Lise Lotte; Nikolova, Dimitrinka; Whitfield, Kate; Krstic, Goran; Wetterslev, Jørn; Gluud, Christian

2014-06-23

The evidence on whether vitamin D supplementation is effective in decreasing cancers is contradictory. To assess the beneficial and harmful effects of vitamin D supplementation for prevention of cancer in adults. We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, LILACS, Science Citation Index Expanded, and the Conference Proceedings Citation Index-Science to February 2014. We scanned bibliographies of relevant publications and asked experts and pharmaceutical companies for additional trials. We included randomised trials that compared vitamin D at any dose, duration, and route of administration versus placebo or no intervention in adults who were healthy or were recruited among the general population, or diagnosed with a specific disease. Vitamin D could have been administered as supplemental vitamin D (vitamin D₃ (cholecalciferol) or vitamin D₂ (ergocalciferol)), or an active form of vitamin D (1α-hydroxyvitamin D (alfacalcidol), or 1,25-dihydroxyvitamin D (calcitriol)). Two review authors extracted data independently. We conducted random-effects and fixed-effect model meta-analyses. For dichotomous outcomes, we calculated the risk ratios (RRs). We considered risk of bias in order to assess the risk of systematic errors. We conducted trial sequential analyses to assess the risk of random errors. Eighteen randomised trials with 50,623 participants provided data for the analyses. All trials came from high-income countries. Most of the trials had a high risk of bias, mainly for-profit bias. Most trials included elderly community-dwelling women (aged 47 to 97 years). Vitamin D was administered for a weighted mean of six years. Fourteen trials tested vitamin D₃, one trial tested vitamin D₂, and three trials tested calcitriol supplementation. Cancer occurrence was observed in 1927/25,275 (7.6%) recipients of vitamin D versus 1943/25,348 (7.7%) recipients of control interventions (RR 1.00 (95% confidence interval (CI) 0.94 to 1.06); P = 0.88; I² = 0%; 18 trials; 50,623 participants; moderate quality evidence according to the GRADE instrument). Trial sequential analysis (TSA) of the 18 vitamin D trials shows that the futility area is reached after the 10th trial, allowing us to conclude that a possible intervention effect, if any, is lower than a 5% relative risk reduction. We did not observe substantial differences in the effect of vitamin D on cancer in subgroup analyses of trials at low risk of bias compared to trials at high risk of bias; of trials with no risk of for-profit bias compared to trials with risk of for-profit bias; of trials assessing primary prevention compared to trials assessing secondary prevention; of trials including participants with vitamin D levels below 20 ng/mL at entry compared to trials including participants with vitamin D levels of 20 ng/mL or more at entry; or of trials using concomitant calcium supplementation compared to trials without calcium. Vitamin D decreased all-cause mortality (1854/24,846 (7.5%) versus 2007/25,020 (8.0%); RR 0.93 (95% CI 0.88 to 0.98); P = 0.009; I² = 0%; 15 trials; 49,866 participants; moderate quality evidence), but TSA indicates that this finding could be due to random errors. Cancer occurrence was observed in 1918/24,908 (7.7%) recipients of vitamin D₃ versus 1933/24,983 (7.7%) in recipients of control interventions (RR 1.00 (95% CI 0.94 to 1.06); P = 0.88; I² = 0%; 14 trials; 49,891 participants; moderate quality evidence). TSA of the vitamin D₃ trials shows that the futility area is reached after the 10th trial, allowing us to conclude that a possible intervention effect, if any, is lower than a 5% relative risk reduction. Vitamin D₃ decreased cancer mortality (558/22,286 (2.5%) versus 634/22,206 (2.8%); RR 0.88 (95% CI 0.78 to 0.98); P = 0.02; I² = 0%; 4 trials; 44,492 participants; low quality evidence), but TSA indicates that this finding could be due to random errors. Vitamin D₃ combined with calcium increased nephrolithiasis (RR 1.17 (95% CI 1.03 to 1.34); P = 0.02; I² = 0%; 3 trials; 42,753 participants; moderate quality evidence). TSA, however, indicates that this finding could be due to random errors. We did not find any data on health-related quality of life or health economics in the randomised trials included in this review. There is currently no firm evidence that vitamin D supplementation decreases or increases cancer occurrence in predominantly elderly community-dwelling women. Vitamin D₃ supplementation decreased cancer mortality and vitamin D supplementation decreased all-cause mortality, but these estimates are at risk of type I errors due to the fact that too few participants were examined, and to risks of attrition bias originating from substantial dropout of participants. Combined vitamin D₃ and calcium supplements increased nephrolithiasis, whereas it remains unclear from the included trials whether vitamin D₃, calcium, or both were responsible for this effect. We need more trials on vitamin D supplementation, assessing the benefits and harms among younger participants, men, and people with low vitamin D status, and assessing longer duration of treatments as well as higher dosages of vitamin D. Follow-up of all participants is necessary to reduce attrition bias.

Disclosure of Medical Errors: What Factors Influence How Patients Respond?

PubMed Central

Mazor, Kathleen M; Reed, George W; Yood, Robert A; Fischer, Melissa A; Baril, Joann; Gurwitz, Jerry H

2006-01-01

BACKGROUND Disclosure of medical errors is encouraged, but research on how patients respond to specific practices is limited. OBJECTIVE This study sought to determine whether full disclosure, an existing positive physician-patient relationship, an offer to waive associated costs, and the severity of the clinical outcome influenced patients' responses to medical errors. PARTICIPANTS Four hundred and seven health plan members participated in a randomized experiment in which they viewed video depictions of medical error and disclosure. DESIGN Subjects were randomly assigned to experimental condition. Conditions varied in type of medication error, level of disclosure, reference to a prior positive physician-patient relationship, an offer to waive costs, and clinical outcome. MEASURES Self-reported likelihood of changing physicians and of seeking legal advice; satisfaction, trust, and emotional response. RESULTS Nondisclosure increased the likelihood of changing physicians, and reduced satisfaction and trust in both error conditions. Nondisclosure increased the likelihood of seeking legal advice and was associated with a more negative emotional response in the missed allergy error condition, but did not have a statistically significant impact on seeking legal advice or emotional response in the monitoring error condition. Neither the existence of a positive relationship nor an offer to waive costs had a statistically significant impact. CONCLUSIONS This study provides evidence that full disclosure is likely to have a positive effect or no effect on how patients respond to medical errors. The clinical outcome also influences patients' responses. The impact of an existing positive physician-patient relationship, or of waiving costs associated with the error remains uncertain. PMID:16808770

Considerations for analysis of time-to-event outcomes measured with error: Bias and correction with SIMEX.

PubMed

Oh, Eric J; Shepherd, Bryan E; Lumley, Thomas; Shaw, Pamela A

2018-04-15

For time-to-event outcomes, a rich literature exists on the bias introduced by covariate measurement error in regression models, such as the Cox model, and methods of analysis to address this bias. By comparison, less attention has been given to understanding the impact or addressing errors in the failure time outcome. For many diseases, the timing of an event of interest (such as progression-free survival or time to AIDS progression) can be difficult to assess or reliant on self-report and therefore prone to measurement error. For linear models, it is well known that random errors in the outcome variable do not bias regression estimates. With nonlinear models, however, even random error or misclassification can introduce bias into estimated parameters. We compare the performance of 2 common regression models, the Cox and Weibull models, in the setting of measurement error in the failure time outcome. We introduce an extension of the SIMEX method to correct for bias in hazard ratio estimates from the Cox model and discuss other analysis options to address measurement error in the response. A formula to estimate the bias induced into the hazard ratio by classical measurement error in the event time for a log-linear survival model is presented. Detailed numerical studies are presented to examine the performance of the proposed SIMEX method under varying levels and parametric forms of the error in the outcome. We further illustrate the method with observational data on HIV outcomes from the Vanderbilt Comprehensive Care Clinic. Copyright © 2017 John Wiley & Sons, Ltd.

Magnetic field errors tolerances of Nuclotron booster

NASA Astrophysics Data System (ADS)

Butenko, Andrey; Kazinova, Olha; Kostromin, Sergey; Mikhaylov, Vladimir; Tuzikov, Alexey; Khodzhibagiyan, Hamlet

2018-04-01

Generation of magnetic field in units of booster synchrotron for the NICA project is one of the most important conditions for getting the required parameters and qualitative accelerator operation. Research of linear and nonlinear dynamics of ion beam 197Au31+ in the booster have carried out with MADX program. Analytical estimation of magnetic field errors tolerance and numerical computation of dynamic aperture of booster DFO-magnetic lattice are presented. Closed orbit distortion with random errors of magnetic fields and errors in layout of booster units was evaluated.

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.

Convergence study of global meshing on enamel-cement-bracket finite element model

NASA Astrophysics Data System (ADS)

Samshuri, S. F.; Daud, R.; Rojan, M. A.; Basaruddin, K. S.; Abdullah, A. B.; Ariffin, A. K.

2017-09-01

This paper presents on meshing convergence analysis of finite element (FE) model to simulate enamel-cement-bracket fracture. Three different materials used in this study involving interface fracture are concerned. Complex behavior ofinterface fracture due to stress concentration is the reason to have a well-constructed meshing strategy. In FE analysis, meshing size is a critical factor that influenced the accuracy and computational time of analysis. The convergence study meshing scheme involving critical area (CA) and non-critical area (NCA) to ensure an optimum meshing sizes are acquired for this FE model. For NCA meshing, the area of interest are at the back of enamel, bracket ligature groove and bracket wing. For CA meshing, area of interest are enamel area close to cement layer, the cement layer and bracket base. The value of constant NCA meshing tested are meshing size 1 and 0.4. The value constant CA meshing tested are 0.4 and 0.1. Manipulative variables are randomly selected and must abide the rule of NCA must be higher than CA. This study employed first principle stresses due to brittle failure nature of the materials used. Best meshing size are selected according to convergence error analysis. Results show that, constant CA are more stable compare to constant NCA meshing. Then, 0.05 constant CA meshing are tested to test the accuracy of smaller meshing. However, unpromising result obtained as the errors are increasing. Thus, constant CA 0.1 with NCA mesh of 0.15 until 0.3 are the most stable meshing as the error in this region are lowest. Convergence test was conducted on three selected coarse, medium and fine meshes at the range of NCA mesh of 0.15 until 3 and CA mesh area stay constant at 0.1. The result shows that, at coarse mesh 0.3, the error are 0.0003% compare to 3% acceptable error. Hence, the global meshing are converge as the meshing size at CA 0.1 and NCA 0.15 for this model.

Calibration of visually guided reaching is driven by error-corrective learning and internal dynamics.

PubMed

Cheng, Sen; Sabes, Philip N

2007-04-01

The sensorimotor calibration of visually guided reaching changes on a trial-to-trial basis in response to random shifts in the visual feedback of the hand. We show that a simple linear dynamical system is sufficient to model the dynamics of this adaptive process. In this model, an internal variable represents the current state of sensorimotor calibration. Changes in this state are driven by error feedback signals, which consist of the visually perceived reach error, the artificial shift in visual feedback, or both. Subjects correct for > or =20% of the error observed on each movement, despite being unaware of the visual shift. The state of adaptation is also driven by internal dynamics, consisting of a decay back to a baseline state and a "state noise" process. State noise includes any source of variability that directly affects the state of adaptation, such as variability in sensory feedback processing, the computations that drive learning, or the maintenance of the state. This noise is accumulated in the state across trials, creating temporal correlations in the sequence of reach errors. These correlations allow us to distinguish state noise from sensorimotor performance noise, which arises independently on each trial from random fluctuations in the sensorimotor pathway. We show that these two noise sources contribute comparably to the overall magnitude of movement variability. Finally, the dynamics of adaptation measured with random feedback shifts generalizes to the case of constant feedback shifts, allowing for a direct comparison of our results with more traditional blocked-exposure experiments.

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…

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

PubMed Central

Marchal-Crespo, Laura; Michels, Lars; Jaeger, Lukas; López-Olóriz, Jorge; Riener, Robert

2017-01-01

Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS) in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL), i.e., precuneus, and temporal cortex. These neuroimaging findings indicate that gait-like motor learning depends on interplay between subcortical, cerebellar, and fronto-parietal brain regions. An interesting observation was the low activation observed in the brain's reward system after training with error amplification compared to training without perturbations. Our results suggest that to enhance learning of a locomotor task, errors should be augmented based on subjects' skill level. The impacts of these strategies on motor learning, brain activation, and motivation in neurological patients need further investigation. PMID:29021739

Nonconvergence of the Wang-Landau algorithms with multiple random walkers.

PubMed

Belardinelli, R E; Pereyra, V D

2016-05-01

This paper discusses some convergence properties in the entropic sampling Monte Carlo methods with multiple random walkers, particularly in the Wang-Landau (WL) and 1/t algorithms. The classical algorithms are modified by the use of m-independent random walkers in the energy landscape to calculate the density of states (DOS). The Ising model is used to show the convergence properties in the calculation of the DOS, as well as the critical temperature, while the calculation of the number π by multiple dimensional integration is used in the continuum approximation. In each case, the error is obtained separately for each walker at a fixed time, t; then, the average over m walkers is performed. It is observed that the error goes as 1/sqrt[m]. However, if the number of walkers increases above a certain critical value m>m_{x}, the error reaches a constant value (i.e., it saturates). This occurs for both algorithms; however, it is shown that for a given system, the 1/t algorithm is more efficient and accurate than the similar version of the WL algorithm. It follows that it makes no sense to increase the number of walkers above a critical value m_{x}, since it does not reduce the error in the calculation. Therefore, the number of walkers does not guarantee convergence.

Accounting for Sampling Error in Genetic Eigenvalues Using Random Matrix Theory.

PubMed

Sztepanacz, Jacqueline L; Blows, Mark W

2017-07-01

The distribution of genetic variance in multivariate phenotypes is characterized by the empirical spectral distribution of the eigenvalues of the genetic covariance matrix. Empirical estimates of genetic eigenvalues from random effects linear models are known to be overdispersed by sampling error, where large eigenvalues are biased upward, and small eigenvalues are biased downward. The overdispersion of the leading eigenvalues of sample covariance matrices have been demonstrated to conform to the Tracy-Widom (TW) distribution. Here we show that genetic eigenvalues estimated using restricted maximum likelihood (REML) in a multivariate random effects model with an unconstrained genetic covariance structure will also conform to the TW distribution after empirical scaling and centering. However, where estimation procedures using either REML or MCMC impose boundary constraints, the resulting genetic eigenvalues tend not be TW distributed. We show how using confidence intervals from sampling distributions of genetic eigenvalues without reference to the TW distribution is insufficient protection against mistaking sampling error as genetic variance, particularly when eigenvalues are small. By scaling such sampling distributions to the appropriate TW distribution, the critical value of the TW statistic can be used to determine if the magnitude of a genetic eigenvalue exceeds the sampling error for each eigenvalue in the spectral distribution of a given genetic covariance matrix. Copyright © 2017 by the Genetics Society of America.

CONTEXTUAL INTERFERENCE AND INTROVERSION/EXTRAVERSION IN MOTOR LEARNING.

PubMed

Meira, Cassio M; Fairbrother, Jeffrey T; Perez, Carlos R

2015-10-01

The Introversion/Extraversion dimension may interact with contextual interference, as random and blocked practice schedules imply distinct levels of variation. This study investigated the effect of different practice schedules in the acquisition of a motor skill in extraverts and introverts. Forty male undergraduate students (M = 24.3 yr., SD = 5.6) were classified as extraverts (n = 20) and introverts (n = 20) by the Eysenck Personality Questionnaire and allocated in one of two practice schedules with different levels of contextual interference: blocked (low contextual interference) and random (high contextual interference). Half of each group was assigned to a blocked practice schedule, and the other half was assigned to a random practice schedule. The design had two phases: acquisition and transfer (5 min. and 24 hr.). The participants learned variations of a sequential timing keypressing task. Each variation required the same sequence but different timing; three variations were used in acquisition, and one variation of intermediate length was used in transfer. Results for absolute error and overall timing error (root mean square error) indicated that the contextual interference effect was more pronounced for introverts. In addition, introverts who practiced according to the blocked schedule committed more errors during the 24-hr. transfer, suggesting that introverts did not appear to be challenged by a low contextual interference practice schedule.

Estimating the Standard Error of the Impact Estimator in Individually Randomized Trials with Clustering

ERIC Educational Resources Information Center

Weiss, Michael J.; Lockwood, J. R.; McCaffrey, Daniel F.

2016-01-01

In the "individually randomized group treatment" (IRGT) experimental design, individuals are first randomly assigned to a treatment arm or a control arm, but then within each arm, are grouped together (e.g., within classrooms/schools, through shared case managers, in group therapy sessions, through shared doctors, etc.) to receive…

Audit of the global carbon budget: estimate errors and their impact on uptake uncertainty

NASA Astrophysics Data System (ADS)

Ballantyne, A. P.; Andres, R.; Houghton, R.; Stocker, B. D.; Wanninkhof, R.; Anderegg, W.; Cooper, L. A.; DeGrandpre, M.; Tans, P. P.; Miller, J. C.; Alden, C.; White, J. W. C.

2014-10-01

Over the last 5 decades monitoring systems have been developed to detect changes in the accumulation of C in the atmosphere, ocean, and land; however, our ability to detect changes in the behavior of the global C cycle is still hindered by measurement and estimate errors. Here we present a rigorous and flexible framework for assessing the temporal and spatial components of estimate error and their impact on uncertainty in net C uptake by the biosphere. We present a novel approach for incorporating temporally correlated random error into the error structure of emission estimates. Based on this approach, we conclude that the 2 σ error of the atmospheric growth rate has decreased from 1.2 Pg C yr-1 in the 1960s to 0.3 Pg C yr-1 in the 2000s, leading to a ~20% reduction in the over-all uncertainty of net global C uptake by the biosphere. While fossil fuel emissions have increased by a factor of 4 over the last 5 decades, 2 σ errors in fossil fuel emissions due to national reporting errors and differences in energy reporting practices have increased from 0.3 Pg C yr-1 in the 1960s to almost 1.0 Pg C yr-1 during the 2000s. At the same time land use emissions have declined slightly over the last 5 decades, but their relative errors remain high. Notably, errors associated with fossil fuel emissions have come to dominate uncertainty in the global C budget and are now comparable to the total emissions from land use, thus efforts to reduce errors in fossil fuel emissions are necessary. Given all the major sources of error in the global C budget that we could identify, we are 93% confident that C uptake has increased and 97% confident that C uptake by the terrestrial biosphere has increased over the last 5 decades. Although the persistence of future C sinks remains unknown and some ecosystem services may be compromised by this continued C uptake (e.g. ocean acidification), it is clear that arguably the greatest ecosystem service currently provided by the biosphere is the continued removal of approximately half of atmospheric CO2 emissions from the atmosphere.

High-resolution moisture profiles from full-waveform probabilistic inversion of TDR signals

NASA Astrophysics Data System (ADS)

Laloy, Eric; Huisman, Johan Alexander; Jacques, Diederik

2014-11-01

This study presents an novel Bayesian inversion scheme for high-dimensional undetermined TDR waveform inversion. The methodology quantifies uncertainty in the moisture content distribution, using a Gaussian Markov random field (GMRF) prior as regularization operator. A spatial resolution of 1 cm along a 70-cm long TDR probe is considered for the inferred moisture content. Numerical testing shows that the proposed inversion approach works very well in case of a perfect model and Gaussian measurement errors. Real-world application results are generally satisfying. For a series of TDR measurements made during imbibition and evaporation from a laboratory soil column, the average root-mean-square error (RMSE) between maximum a posteriori (MAP) moisture distribution and reference TDR measurements is 0.04 cm3 cm-3. This RMSE value reduces to less than 0.02 cm3 cm-3 for a field application in a podzol soil. The observed model-data discrepancies are primarily due to model inadequacy, such as our simplified modeling of the bulk soil electrical conductivity profile. Among the important issues that should be addressed in future work are the explicit inference of the soil electrical conductivity profile along with the other sampled variables, the modeling of the temperature-dependence of the coaxial cable properties and the definition of an appropriate statistical model of the residual errors.

Random-access algorithms for multiuser computer communication networks. Doctoral thesis, 1 September 1986-31 August 1988

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

Papantoni-Kazakos, P.; Paterakis, M.

1988-07-01

For many communication applications with time constraints (e.g., transmission of packetized voice messages), a critical performance measure is the percentage of messages transmitted within a given amount of time after their generation at the transmitting station. This report presents a random-access algorithm (RAA) suitable for time-constrained applications. Performance analysis demonstrates that significant message-delay improvement is attained at the expense of minimal traffic loss. Also considered is the case of noisy channels. The noise effect appears at erroneously observed channel feedback. Error sensitivity analysis shows that the proposed random-access algorithm is insensitive to feedback channel errors. Window Random-Access Algorithms (RAAs) aremore » considered next. These algorithms constitute an important subclass of Multiple-Access Algorithms (MAAs); they are distributive, and they attain high throughput and low delays by controlling the number of simultaneously transmitting users.« less

Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

NASA Technical Reports Server (NTRS)

Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)

2001-01-01

A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.

Comparison of error-based and errorless learning for people with severe traumatic brain injury: study protocol for a randomized control trial.

PubMed

Ownsworth, Tamara; Fleming, Jennifer; Tate, Robyn; Shum, David H K; Griffin, Janelle; Schmidt, Julia; Lane-Brown, Amanda; Kendall, Melissa; Chevignard, Mathilde

2013-11-05

Poor skills generalization poses a major barrier to successful outcomes of rehabilitation after traumatic brain injury (TBI). Error-based learning (EBL) is a relatively new intervention approach that aims to promote skills generalization by teaching people internal self-regulation skills, or how to anticipate, monitor and correct their own errors. This paper describes the protocol of a study that aims to compare the efficacy of EBL and errorless learning (ELL) for improving error self-regulation, behavioral competency, awareness of deficits and long-term outcomes after TBI. This randomized, controlled trial (RCT) has two arms (EBL and ELL); each arm entails 8 × 2 h training sessions conducted within the participants' homes. The first four sessions involve a meal preparation activity, and the final four sessions incorporate a multitasking errand activity. Based on a sample size estimate, 135 participants with severe TBI will be randomized into either the EBL or ELL condition. The primary outcome measure assesses error self-regulation skills on a task related to but distinct from training. Secondary outcomes include measures of self-monitoring and self-regulation, behavioral competency, awareness of deficits, role participation and supportive care needs. Assessments will be conducted at pre-intervention, post-intervention, and at 6-months post-intervention. This study seeks to determine the efficacy and long-term impact of EBL for training internal self-regulation strategies following severe TBI. In doing so, the study will advance theoretical understanding of the role of errors in task learning and skills generalization. EBL has the potential to reduce the length and costs of rehabilitation and lifestyle support because the techniques could enhance generalization success and lifelong application of strategies after TBI. ACTRN12613000585729.

Robust Tomography using Randomized Benchmarking

NASA Astrophysics Data System (ADS)

Silva, Marcus; Kimmel, Shelby; Johnson, Blake; Ryan, Colm; Ohki, Thomas

2013-03-01

Conventional randomized benchmarking (RB) can be used to estimate the fidelity of Clifford operations in a manner that is robust against preparation and measurement errors -- thus allowing for a more accurate and relevant characterization of the average error in Clifford gates compared to standard tomography protocols. Interleaved RB (IRB) extends this result to the extraction of error rates for individual Clifford gates. In this talk we will show how to combine multiple IRB experiments to extract all information about the unital part of any trace preserving quantum process. Consequently, one can compute the average fidelity to any unitary, not just the Clifford group, with tighter bounds than IRB. Moreover, the additional information can be used to design improvements in control. MS, BJ, CR and TO acknowledge support from IARPA under contract W911NF-10-1-0324.

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Feedback-tuned, noise resilient gates for encoded spin qubits

NASA Astrophysics Data System (ADS)

Bluhm, Hendrik

Spin 1/2 particles form native two level systems and thus lend themselves as a natural qubit implementation. However, encoding a single qubit in several spins entails benefits, such as reducing the resources necessary for qubit control and protection from certain decoherence channels. While several varieties of such encoded spin qubits have been implemented, accurate control remains challenging, and leakage out of the subspace of valid qubit states is a potential issue. Optimal performance typically requires large pulse amplitudes for fast control, which is prone to systematic errors and prohibits standard control approaches based on Rabi flopping. Furthermore, the exchange interaction typically used to electrically manipulate encoded spin qubits is inherently sensitive to charge noise. I will discuss all-electrical, high-fidelity single qubit operations for a spin qubit encoded in two electrons in a GaAs double quantum dot. Starting from a set of numerically optimized control pulses, we employ an iterative tuning procedure based on measured error syndromes to remove systematic errors.Randomized benchmarking yields an average gate fidelity exceeding 98 % and a leakage rate into invalid states of 0.2 %. These gates exhibit a certain degree of resilience to both slow charge and nuclear spin fluctuations due to dynamical correction analogous to a spin echo. Furthermore, the numerical optimization minimizes the impact of fast charge noise. Both types of noise make relevant contributions to gate errors. The general approach is also adaptable to other qubit encodings and exchange based two-qubit gates.

An accurate nonlinear stochastic model for MEMS-based inertial sensor error with wavelet networks

NASA Astrophysics Data System (ADS)

El-Diasty, Mohammed; El-Rabbany, Ahmed; Pagiatakis, Spiros

2007-12-01

The integration of Global Positioning System (GPS) with Inertial Navigation System (INS) has been widely used in many applications for positioning and orientation purposes. Traditionally, random walk (RW), Gauss-Markov (GM), and autoregressive (AR) processes have been used to develop the stochastic model in classical Kalman filters. The main disadvantage of classical Kalman filter is the potentially unstable linearization of the nonlinear dynamic system. Consequently, a nonlinear stochastic model is not optimal in derivative-based filters due to the expected linearization error. With a derivativeless-based filter such as the unscented Kalman filter or the divided difference filter, the filtering process of a complicated highly nonlinear dynamic system is possible without linearization error. This paper develops a novel nonlinear stochastic model for inertial sensor error using a wavelet network (WN). A wavelet network is a highly nonlinear model, which has recently been introduced as a powerful tool for modelling and prediction. Static and kinematic data sets are collected using a MEMS-based IMU (DQI-100) to develop the stochastic model in the static mode and then implement it in the kinematic mode. The derivativeless-based filtering method using GM, AR, and the proposed WN-based processes are used to validate the new model. It is shown that the first-order WN-based nonlinear stochastic model gives superior positioning results to the first-order GM and AR models with an overall improvement of 30% when 30 and 60 seconds GPS outages are introduced.

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.

Risk behaviours for organism transmission in health care delivery-A two month unstructured observational study.

PubMed

Lindberg, Maria; Lindberg, Magnus; Skytt, Bernice

2017-05-01

Errors in infection control practices risk patient safety. The probability for errors can increase when care practices become more multifaceted. It is therefore fundamental to track risk behaviours and potential errors in various care situations. The aim of this study was to describe care situations involving risk behaviours for organism transmission that could lead to subsequent healthcare-associated infections. Unstructured nonparticipant observations were performed at three medical wards. Healthcare personnel (n=27) were shadowed, in total 39h, on randomly selected weekdays between 7:30 am and 12 noon. Content analysis was used to inductively categorize activities into tasks and based on the character into groups. Risk behaviours for organism transmission were deductively classified into types of errors. Multiple response crosstabs procedure was used to visualize the number and proportion of errors in tasks. One-Way ANOVA with Bonferroni post Hoc test was used to determine differences among the three groups of activities. The qualitative findings gives an understanding of that risk behaviours for organism transmission goes beyond the five moments of hand hygiene and also includes the handling and placement of materials and equipment. The tasks with the highest percentage of errors were; 'personal hygiene', 'elimination' and 'dressing/wound care'. The most common types of errors in all identified tasks were; 'hand disinfection', 'glove usage', and 'placement of materials'. Significantly more errors (p<0.0001) were observed the more multifaceted (single, combined or interrupted) the activity was. The numbers and types of errors as well as the character of activities performed in care situations described in this study confirm the need to improve current infection control practices. It is fundamental that healthcare personnel practice good hand hygiene however effective preventive hygiene is complex in healthcare activities due to the multifaceted care situations, especially when activities are interrupted. A deeper understanding of infection control practices that goes beyond the sense of security by means of hand disinfection and use of gloves is needed as materials and surfaces in the care environment might be contaminated and thus pose a risk for organism transmission. Copyright © 2017 Elsevier Ltd. All rights reserved.

Syzygies, Pluricanonical Maps, and the Birational Geometry of Varieties of Maximal Albanese Dimension

NASA Astrophysics Data System (ADS)

Tesfagiorgis, Kibrewossen B.

Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products in mountainous regions. The present work develops an approach to seamlessly blend satellite, available radar, climatological and gauge precipitation products to fill gaps in ground-based radar precipitation field. To mix different precipitation products, the error of any of the products relative to each other should be removed. For bias correction, the study uses a new ensemble-based method which aims to estimate spatially varying multiplicative biases in SPEs using a radar-gauge precipitation product. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. In addition to biases, sometimes there is also spatial error between the radar and satellite precipitation estimates; one of them has to be geometrically corrected with reference to the other. A set of corresponding raining points between SPE and radar products are selected to apply linear registration using a regularized least square technique to minimize the dislocation error in SPEs with respect to available radar products. A weighted Successive Correction Method (SCM) is used to make the merging between error corrected satellite and radar precipitation estimates. In addition to SCM, we use a combination of SCM and Bayesian spatial method for merging the rain gauges and climatological precipitation sources with radar and SPEs. We demonstrated the method using two satellite-based, CPC Morphing (CMORPH) and Hydro-Estimator (HE), two radar-gauge based, Stage-II and ST-IV, a climatological product PRISM and rain gauge dataset for several rain events from 2006 to 2008 over different geographical locations of the United States. Results show that: (a) the method of ensembles helped reduce biases in SPEs significantly; (b) the SCM method in combination with the Bayesian spatial model produced a precipitation product in good agreement with independent measurements .The study implies that using the available radar pixels surrounding the gap area, rain gauge, PRISM and satellite products, a radar like product is achievable over radar gap areas that benefits the operational meteorology and hydrology community.

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)

PubMed Central

Xu, Chonggang; Gertner, George

2013-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements. PMID:24143037

Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST).

PubMed

Xu, Chonggang; Gertner, George

2011-01-01

Fourier Amplitude Sensitivity Test (FAST) is one of the most popular uncertainty and sensitivity analysis techniques. It uses a periodic sampling approach and a Fourier transformation to decompose the variance of a model output into partial variances contributed by different model parameters. Until now, the FAST analysis is mainly confined to the estimation of partial variances contributed by the main effects of model parameters, but does not allow for those contributed by specific interactions among parameters. In this paper, we theoretically show that FAST analysis can be used to estimate partial variances contributed by both main effects and interaction effects of model parameters using different sampling approaches (i.e., traditional search-curve based sampling, simple random sampling and random balance design sampling). We also analytically calculate the potential errors and biases in the estimation of partial variances. Hypothesis tests are constructed to reduce the effect of sampling errors on the estimation of partial variances. Our results show that compared to simple random sampling and random balance design sampling, sensitivity indices (ratios of partial variances to variance of a specific model output) estimated by search-curve based sampling generally have higher precision but larger underestimations. Compared to simple random sampling, random balance design sampling generally provides higher estimation precision for partial variances contributed by the main effects of parameters. The theoretical derivation of partial variances contributed by higher-order interactions and the calculation of their corresponding estimation errors in different sampling schemes can help us better understand the FAST method and provide a fundamental basis for FAST applications and further improvements.

Comparing errors in ED computer-assisted vs conventional pediatric drug dosing and administration.

PubMed

Yamamoto, Loren; Kanemori, Joan

2010-06-01

Compared to fixed-dose single-vial drug administration in adults, pediatric drug dosing and administration requires a series of calculations, all of which are potentially error prone. The purpose of this study is to compare error rates and task completion times for common pediatric medication scenarios using computer program assistance vs conventional methods. Two versions of a 4-part paper-based test were developed. Each part consisted of a set of medication administration and/or dosing tasks. Emergency department and pediatric intensive care unit nurse volunteers completed these tasks using both methods (sequence assigned to start with a conventional or a computer-assisted approach). Completion times, errors, and the reason for the error were recorded. Thirty-eight nurses completed the study. Summing the completion of all 4 parts, the mean conventional total time was 1243 seconds vs the mean computer program total time of 879 seconds (P < .001). The conventional manual method had a mean of 1.8 errors vs the computer program with a mean of 0.7 errors (P < .001). Of the 97 total errors, 36 were due to misreading the drug concentration on the label, 34 were due to calculation errors, and 8 were due to misplaced decimals. Of the 36 label interpretation errors, 18 (50%) occurred with digoxin or insulin. Computerized assistance reduced errors and the time required for drug administration calculations. A pattern of errors emerged, noting that reading/interpreting certain drug labels were more error prone. Optimizing the layout of drug labels could reduce the error rate for error-prone labels. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Dynamic modelling and estimation of the error due to asynchronism in a redundant asynchronous multiprocessor system

NASA Technical Reports Server (NTRS)

Huynh, Loc C.; Duval, R. W.

1986-01-01

The use of Redundant Asynchronous Multiprocessor System to achieve ultrareliable Fault Tolerant Control Systems shows great promise. The development has been hampered by the inability to determine whether differences in the outputs of redundant CPU's are due to failures or to accrued error built up by slight differences in CPU clock intervals. This study derives an analytical dynamic model of the difference between redundant CPU's due to differences in their clock intervals and uses this model with on-line parameter identification to idenitify the differences in the clock intervals. The ability of this methodology to accurately track errors due to asynchronisity generate an error signal with the effect of asynchronisity removed and this signal may be used to detect and isolate actual system failures.

Improved L-BFGS diagonal preconditioners for a large-scale 4D-Var inversion system: application to CO2 flux constraints and analysis error calculation

NASA Astrophysics Data System (ADS)

Bousserez, Nicolas; Henze, Daven; Bowman, Kevin; Liu, Junjie; Jones, Dylan; Keller, Martin; Deng, Feng

2013-04-01

This work presents improved analysis error estimates for 4D-Var systems. From operational NWP models to top-down constraints on trace gas emissions, many of today's data assimilation and inversion systems in atmospheric science rely on variational approaches. This success is due to both the mathematical clarity of these formulations and the availability of computationally efficient minimization algorithms. However, unlike Kalman Filter-based algorithms, these methods do not provide an estimate of the analysis or forecast error covariance matrices, these error statistics being propagated only implicitly by the system. From both a practical (cycling assimilation) and scientific perspective, assessing uncertainties in the solution of the variational problem is critical. For large-scale linear systems, deterministic or randomization approaches can be considered based on the equivalence between the inverse Hessian of the cost function and the covariance matrix of analysis error. For perfectly quadratic systems, like incremental 4D-Var, Lanczos/Conjugate-Gradient algorithms have proven to be most efficient in generating low-rank approximations of the Hessian matrix during the minimization. For weakly non-linear systems though, the Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS), a quasi-Newton descent algorithm, is usually considered the best method for the minimization. Suitable for large-scale optimization, this method allows one to generate an approximation to the inverse Hessian using the latest m vector/gradient pairs generated during the minimization, m depending upon the available core memory. At each iteration, an initial low-rank approximation to the inverse Hessian has to be provided, which is called preconditioning. The ability of the preconditioner to retain useful information from previous iterations largely determines the efficiency of the algorithm. Here we assess the performance of different preconditioners to estimate the inverse Hessian of a large-scale 4D-Var system. The impact of using the diagonal preconditioners proposed by Gilbert and Le Maréchal (1989) instead of the usual Oren-Spedicato scalar will be first presented. We will also introduce new hybrid methods that combine randomization estimates of the analysis error variance with L-BFGS diagonal updates to improve the inverse Hessian approximation. Results from these new algorithms will be evaluated against standard large ensemble Monte-Carlo simulations. The methods explored here are applied to the problem of inferring global atmospheric CO2 fluxes using remote sensing observations, and are intended to be integrated with the future NASA Carbon Monitoring System.

A proposed method to investigate reliability throughout a questionnaire.

PubMed

Wentzel-Larsen, Tore; Norekvål, Tone M; Ulvik, Bjørg; Nygård, Ottar; Pripp, Are H

2011-10-05

Questionnaires are used extensively in medical and health care research and depend on validity and reliability. However, participants may differ in interest and awareness throughout long questionnaires, which can affect reliability of their answers. A method is proposed for "screening" of systematic change in random error, which could assess changed reliability of answers. A simulation study was conducted to explore whether systematic change in reliability, expressed as changed random error, could be assessed using unsupervised classification of subjects by cluster analysis (CA) and estimation of intraclass correlation coefficient (ICC). The method was also applied on a clinical dataset from 753 cardiac patients using the Jalowiec Coping Scale. The simulation study showed a relationship between the systematic change in random error throughout a questionnaire and the slope between the estimated ICC for subjects classified by CA and successive items in a questionnaire. This slope was proposed as an awareness measure--to assessing if respondents provide only a random answer or one based on a substantial cognitive effort. Scales from different factor structures of Jalowiec Coping Scale had different effect on this awareness measure. Even though assumptions in the simulation study might be limited compared to real datasets, the approach is promising for assessing systematic change in reliability throughout long questionnaires. Results from a clinical dataset indicated that the awareness measure differed between scales.

An evaluation of satellite-derived humidity and its relationship to convective development

NASA Technical Reports Server (NTRS)

Fuelberg, Henry E.

1993-01-01

An aircraft prototype of the High-Resolution Interferometer Sounder (HIS) was flown over Tennessee and northern Alabama during summer 1986. The HIS temperature and dewpoint soundings were examined on two flight days to determine their error characteristics and utility in mesoscale analyses. Random errors were calculated from structure functions while total errors were obtained by pairing the HIS soundings with radiosonde-derived profiles. Random temperature errors were found to be less than 1 C at most levels, but random dewpoint errors ranged from 1 to 5 C. Total errors of both parameters were considerably greater, with dewpoint errors especially large on the day having a pronounced subsidence inversion. Cumulus cloud cover on 15 June limited HIS mesoscale analyses on that day. Previously undetected clouds were found in many HIS fields of view, and these probably produced the low-level horizontal temperature and dewpoint variations observed in the retrievals. HIS dewpoints at 300 mb indicated a strong moisture gradient that was confirmed by GOES 6.7-micron imagery. HIS mesoscale analyses on 19 June revealed a tongue of humid air stretching across the study area. The moist region was confirmed by radiosonde data and imagery from the Multispectral Atmospheric Mapping Sensor (MAMS). Convective temperatures derived from HIS retrievals helped explain the cloud formation that occurred after the HIS overflights. Crude estimates of Bowen ratio were obtained from HIS data using a mixing-line approach. Values indicated that areas of large sensible heat flux were the areas of first cloud development. These locations were also suggested by GOES visible and infrared imagery. The HIS retrievals indicated that areas of thunderstorm formation were regions of greatest instability. Local landscape variability and atmospheric temperature and humidity fluctuations were found to be important factors in producing the cumulus clouds on 19 June. HIS soundings were capable of detecting some of this variability. The authors were impressed by HIS's performance on the two study days.

High Dimensional Classification Using Features Annealed Independence Rules.

PubMed

Fan, Jianqing; Fan, Yingying

2008-01-01

Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

Fast decoding techniques for extended single-and-double-error-correcting Reed Solomon codes

NASA Technical Reports Server (NTRS)

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

1984-01-01

A problem in designing semiconductor memories is to provide some measure of error control without requiring excessive coding overhead or decoding time. For example, some 256K-bit dynamic random access memories are organized as 32K x 8 bit-bytes. Byte-oriented codes such as Reed Solomon (RS) codes provide efficient low overhead error control for such memories. However, the standard iterative algorithm for decoding RS codes is too slow for these applications. Some special high speed decoding techniques for extended single and double error correcting RS codes. These techniques are designed to find the error locations and the error values directly from the syndrome without having to form the error locator polynomial and solve for its roots.

Stable estimate of primary OC/EC ratios in the EC tracer method

NASA Astrophysics Data System (ADS)

Chu, Shao-Hang

In fine particulate matter studies, the primary OC/EC ratio plays an important role in estimating the secondary organic aerosol contribution to PM2.5 concentrations using the EC tracer method. In this study, numerical experiments are carried out to test and compare various statistical techniques in the estimation of primary OC/EC ratios. The influence of random measurement errors in both primary OC and EC measurements on the estimation of the expected primary OC/EC ratios is examined. It is found that random measurement errors in EC generally create an underestimation of the slope and an overestimation of the intercept of the ordinary least-squares regression line. The Deming regression analysis performs much better than the ordinary regression, but it tends to overcorrect the problem by slightly overestimating the slope and underestimating the intercept. Averaging the ratios directly is usually undesirable because the average is strongly influenced by unrealistically high values of OC/EC ratios resulting from random measurement errors at low EC concentrations. The errors generally result in a skewed distribution of the OC/EC ratios even if the parent distributions of OC and EC are close to normal. When measured OC contains a significant amount of non-combustion OC Deming regression is a much better tool and should be used to estimate both the primary OC/EC ratio and the non-combustion OC. However, if the non-combustion OC is negligibly small the best and most robust estimator of the OC/EC ratio turns out to be the simple ratio of the OC and EC averages. It not only reduces random errors by averaging individual variables separately but also acts as a weighted average of ratios to minimize the influence of unrealistically high OC/EC ratios created by measurement errors at low EC concentrations. The median of OC/EC ratios ranks a close second, and the geometric mean of ratios ranks third. This is because their estimations are insensitive to questionable extreme values. A real world example is given using the ambient data collected from an Atlanta STN site during the winter of 2001-2002.

Advanced Water Vapor Lidar Detection System

NASA Technical Reports Server (NTRS)

Elsayed-Ali, Hani

1998-01-01

In the present water vapor lidar system, the detected signal is sent over long cables to a waveform digitizer in a CAMAC crate. This has the disadvantage of transmitting analog signals for a relatively long distance, which is subjected to pickup noise, leading to a decrease in the signal to noise ratio. Generally, errors in the measurement of water vapor with the DIAL method arise from both random and systematic sources. Systematic errors in DIAL measurements are caused by both atmospheric and instrumentation effects. The selection of the on-line alexandrite laser with a narrow linewidth, suitable intensity and high spectral purity, and its operation at the center of the water vapor lines, ensures minimum influence in the DIAL measurement that are caused by the laser spectral distribution and avoid system overloads. Random errors are caused by noise in the detected signal. Variability of the photon statistics in the lidar return signal, noise resulting from detector dark current, and noise in the background signal are the main sources of random error. This type of error can be minimized by maximizing the signal to noise ratio. The increase in the signal to noise ratio can be achieved by several ways. One way is to increase the laser pulse energy, by increasing its amplitude or the pulse repetition rate. Another way, is to use a detector system with higher quantum efficiency and lower noise, on the other hand, the selection of a narrow band optical filter that rejects most of the day background light and retains high optical efficiency is an important issue. Following acquisition of the lidar data, we minimize random errors in the DIAL measurement by averaging the data, but this will result in the reduction of the vertical and horizontal resolutions. Thus, a trade off is necessary to achieve a balance between the spatial resolution and the measurement precision. Therefore, the main goal of this research effort is to increase the signal to noise ratio by a factor of 10 over the current system, using a newly evaluated, very low noise avalanche photo diode detector and constructing a 10 MHz waveform digitizer which will replace the current CAMAC system.

Decorrelation of the true and estimated classifier errors in high-dimensional settings.

PubMed

Hanczar, Blaise; Hua, Jianping; Dougherty, Edward R

2007-01-01

The aim of many microarray experiments is to build discriminatory diagnosis and prognosis models. Given the huge number of features and the small number of examples, model validity which refers to the precision of error estimation is a critical issue. Previous studies have addressed this issue via the deviation distribution (estimated error minus true error), in particular, the deterioration of cross-validation precision in high-dimensional settings where feature selection is used to mitigate the peaking phenomenon (overfitting). Because classifier design is based upon random samples, both the true and estimated errors are sample-dependent random variables, and one would expect a loss of precision if the estimated and true errors are not well correlated, so that natural questions arise as to the degree of correlation and the manner in which lack of correlation impacts error estimation. We demonstrate the effect of correlation on error precision via a decomposition of the variance of the deviation distribution, observe that the correlation is often severely decreased in high-dimensional settings, and show that the effect of high dimensionality on error estimation tends to result more from its decorrelating effects than from its impact on the variance of the estimated error. We consider the correlation between the true and estimated errors under different experimental conditions using both synthetic and real data, several feature-selection methods, different classification rules, and three error estimators commonly used (leave-one-out cross-validation, k-fold cross-validation, and .632 bootstrap). Moreover, three scenarios are considered: (1) feature selection, (2) known-feature set, and (3) all features. Only the first is of practical interest; however, the other two are needed for comparison purposes. We will observe that the true and estimated errors tend to be much more correlated in the case of a known feature set than with either feature selection or using all features, with the better correlation between the latter two showing no general trend, but differing for different models.

Why Are People Bad at Detecting Randomness? A Statistical Argument

ERIC Educational Resources Information Center

Williams, Joseph J.; Griffiths, Thomas L.

2013-01-01

Errors in detecting randomness are often explained in terms of biases and misconceptions. We propose and provide evidence for an account that characterizes the contribution of the inherent statistical difficulty of the task. Our account is based on a Bayesian statistical analysis, focusing on the fact that a random process is a special case of…

77 FR 41699 - Transportation of Household Goods in Interstate Commerce; Consumer Protection Regulations...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-07-16

... due Revision due to agency Collection Old burden to error error (old-- error) IC1: ``Ready to Move... Revisions of Estimates of Annual Costs to Respondents Total cost Collection New cost Old cost reduction (new--old) IC1: ``Ready to Move?'' $288,000 $720,000 -$432,000 ``Rights & Responsibilities'' 3,264,000 8,160...

Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

2007-12-01

The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed and applied a methodology that statistically separates the two error sources. Using TRMM monthly estimates and high-resolution radar and gauge data, this method has been used to estimate sampling and retrieval error budgets over GV sites. More recently, a multi- year data set of instantaneous rain rates from the TRMM microwave imager (TMI), the precipitation radar (PR), and the combined algorithm was spatio-temporally matched and inter-compared to GV radar rain rates collected during satellite overpasses of select GV sites at the scale of the TMI footprint. The analysis provided a more direct probe of the satellite rain algorithms using ground data as an empirical reference. TSVO has also made significant advances in radar quality control through the development of the Relative Calibration Adjustment (RCA) technique. The RCA is currently being used to provide a long-term record of radar calibration for the radar at Kwajalein, a strategically important GV site in the tropical Pacific. The RCA technique has revealed previously undetected alterations in the radar sensitivity due to engineering changes (e.g., system modifications, antenna offsets, alterations of the receiver, or the data processor), making possible the correction of the radar rainfall measurements and ensuring the integrity of nearly a decade of TRMM GV observations and resources.

Medication errors in anesthesia: unacceptable or unavoidable?

PubMed

Dhawan, Ira; Tewari, Anurag; Sehgal, Sankalp; Sinha, Ashish Chandra

Medication errors are the common causes of patient morbidity and mortality. It adds financial burden to the institution as well. Though the impact varies from no harm to serious adverse effects including death, it needs attention on priority basis since medication errors' are preventable. In today's world where people are aware and medical claims are on the hike, it is of utmost priority that we curb this issue. Individual effort to decrease medication error alone might not be successful until a change in the existing protocols and system is incorporated. Often drug errors that occur cannot be reversed. The best way to 'treat' drug errors is to prevent them. Wrong medication (due to syringe swap), overdose (due to misunderstanding or preconception of the dose, pump misuse and dilution error), incorrect administration route, under dosing and omission are common causes of medication error that occur perioperatively. Drug omission and calculation mistakes occur commonly in ICU. Medication errors can occur perioperatively either during preparation, administration or record keeping. Numerous human and system errors can be blamed for occurrence of medication errors. The need of the hour is to stop the blame - game, accept mistakes and develop a safe and 'just' culture in order to prevent medication errors. The newly devised systems like VEINROM, a fluid delivery system is a novel approach in preventing drug errors due to most commonly used medications in anesthesia. Similar developments along with vigilant doctors, safe workplace culture and organizational support all together can help prevent these errors. Copyright © 2016. Published by Elsevier Editora Ltda.

The Stability of Perceived Pubertal Timing across Adolescence

PubMed Central

Cance, Jessica Duncan; Ennett, Susan T.; Morgan-Lopez, Antonio A.; Foshee, Vangie A.

2011-01-01

It is unknown whether perceived pubertal timing changes as puberty progresses or whether it is an important component of adolescent identity formation that is fixed early in pubertal development. The purpose of this study is to examine the stability of perceived pubertal timing among a school-based sample of rural adolescents aged 11 to 17 (N=6,425; 50% female; 53% White). Two measures of pubertal timing were used, stage-normative, based on the Pubertal Development Scale, a self-report scale of secondary sexual characteristics, and peer-normative, a one-item measure of perceived pubertal timing. Two longitudinal methods were used: one-way random effects ANOVA models and latent class analysis. When calculating intraclass correlation coefficients using the one-way random effects ANOVA models, which is based on the average reliability from one time point to the next, both measures had similar, but poor, stability. In contrast, latent class analysis, which looks at the longitudinal response pattern of each individual and treats deviation from that pattern as measurement error, showed three stable and distinct response patterns for both measures: always early, always on-time, and always late. Study results suggest instability in perceived pubertal timing from one age to the next, but this instability is likely due to measurement error. Thus, it may be necessary to take into account the longitudinal pattern of perceived pubertal timing across adolescence rather than measuring perceived pubertal timing at one point in time. PMID:21983873

Local ensemble transform Kalman filter for ionospheric data assimilation: Observation influence analysis during a geomagnetic storm event

NASA Astrophysics Data System (ADS)

Durazo, Juan A.; Kostelich, Eric J.; Mahalov, Alex

2017-09-01

We propose a targeted observation strategy, based on the influence matrix diagnostic, that optimally selects where additional observations may be placed to improve ionospheric forecasts. This strategy is applied in data assimilation observing system experiments, where synthetic electron density vertical profiles, which represent those of Constellation Observing System for Meteorology, Ionosphere, and Climate/Formosa satellite 3, are assimilated into the Thermosphere-Ionosphere-Electrodynamics General Circulation Model using the local ensemble transform Kalman filter during the 26 September 2011 geomagnetic storm. During each analysis step, the observation vector is augmented with five synthetic vertical profiles optimally placed to target electron density errors, using our targeted observation strategy. Forecast improvement due to assimilation of augmented vertical profiles is measured with the root-mean-square error (RMSE) of analyzed electron density, averaged over 600 km regions centered around the augmented vertical profile locations. Assimilating vertical profiles with targeted locations yields about 60%-80% reduction in electron density RMSE, compared to a 15% average reduction when assimilating randomly placed vertical profiles. Assimilating vertical profiles whose locations target the zonal component of neutral winds (Un) yields on average a 25% RMSE reduction in Un estimates, compared to a 2% average improvement obtained with randomly placed vertical profiles. These results demonstrate that our targeted strategy can improve data assimilation efforts during extreme events by detecting regions where additional observations would provide the largest benefit to the forecast.

Antioxidant supplements and mortality.

PubMed

Bjelakovic, Goran; Nikolova, Dimitrinka; Gluud, Christian

2014-01-01

Oxidative damage to cells and tissues is considered involved in the aging process and in the development of chronic diseases in humans, including cancer and cardiovascular diseases, the leading causes of death in high-income countries. This has stimulated interest in the preventive potential of antioxidant supplements. Today, more than one half of adults in high-income countries ingest antioxidant supplements hoping to improve their health, oppose unhealthy behaviors, and counteract the ravages of aging. Older observational studies and some randomized clinical trials with high risks of systematic errors ('bias') have suggested that antioxidant supplements may improve health and prolong life. A number of randomized clinical trials with adequate methodologies observed neutral or negative results of antioxidant supplements. Recently completed large randomized clinical trials with low risks of bias and systematic reviews of randomized clinical trials taking systematic errors ('bias') and risks of random errors ('play of chance') into account have shown that antioxidant supplements do not seem to prevent cancer, cardiovascular diseases, or death. Even more, beta-carotene, vitamin A, and vitamin E may increase mortality. Some recent large observational studies now support these findings. According to recent dietary guidelines, there is no evidence to support the use of antioxidant supplements in the primary prevention of chronic diseases or mortality. Antioxidant supplements do not possess preventive effects and may be harmful with unwanted consequences to our health, especially in well-nourished populations. The optimal source of antioxidants seems to come from our diet, not from antioxidant supplements in pills or tablets.

POLICY IMPLICATIONS OF ADJUSTING RANDOMIZED TRIAL DATA FOR ECONOMIC EVALUATIONS: A DEMONSTRATION FROM THE ASCUS-LSIL TRIAGE STUDY

PubMed Central

Campos, Nicole G.; Castle, Philip E.; Schiffman, Mark; Kim, Jane J.

2013-01-01

Background Although the randomized controlled trial (RCT) is widely considered the most reliable method for evaluation of health care interventions, challenges to both internal and external validity exist. Thus, the efficacy of an intervention in a trial setting does not necessarily represent the real-world performance that decision makers seek to inform comparative effectiveness studies and economic evaluations. Methods Using data from the ASCUS-LSIL Triage Study (ALTS), we performed a simplified economic evaluation of age-based management strategies to detect cervical intraepithelial neoplasia grade 3 (CIN3) among women who were referred to the study with low-grade squamous intraepithelial lesions (LSIL). We used data from the trial itself to adjust for 1) potential lead time bias and random error that led to variation in the observed prevalence of CIN3 by study arm, and 2) potential ascertainment bias among providers in the most aggressive management arm. Results We found that using unadjusted RCT data may result in counterintuitive cost-effectiveness results when random error and/or bias are present. Following adjustment, the rank order of management strategies changed for two of the three age groups we considered. Conclusion Decision analysts need to examine study design, available trial data and cost-effectiveness results closely in order to detect evidence of potential bias. Adjustment for random error and bias in RCTs may yield different policy conclusions relative to unadjusted trial data. PMID:22147881

Development and Prospective Federal State-Wide Evaluation of a Device for Height-Based Dose Recommendations in Prehospital Pediatric Emergencies: A Simple Tool to Prevent Most Severe Drug Errors.

PubMed

Kaufmann, Jost; Roth, Bernhard; Engelhardt, Thomas; Lechleuthner, Alex; Laschat, Michael; Hadamitzky, Christoph; Wappler, Frank; Hellmich, Martin

2018-01-01

Drug dosing errors pose a particular threat to children in prehospital emergency care. With the Pediatric emergency ruler (PaedER), we developed a simple height-based dose recommendation system and evaluated its effectiveness in a pre-post interventional trial as the Ethics Committee disapproved randomization due to the expected positive effect of the PaedER on outcome. Pre-interventional data were retrospectively retrieved from the electronic records and medical protocols of the Cologne Emergency Medical Service over a two-year period prior to the introduction of the PaedER. Post-interventional data were collected prospectively over a six-year period in a federal state-wide open trial. The administered doses of either intravenous or intraosseous fentanyl, midazolam, ketamine or epinephrine were recorded. Primary outcome measure was the number and severity of drug dose deviation from recommended dose (DRD) based on the patient's weight. Fifty-nine pre-interventional and 91 post-interventional prehospital drug administrations in children were analyzed. The rate of DRD > 300% overall medications were 22.0% in the pre- and 2.2% in the post-interventional group (p < 0.001). All administrations of epinephrine occurred excessive (DRD > 300%) in pre-interventional and none in post-interventional patients (p < 0.001). The use of the PaedER resulted in a 90% reduction of medication errors (95% CI: 57% to 98%; p < 0.001) and prevented all potentially life-threatening errors associated with epinephrine administration. There is an urgent need to increase the safety of emergency drug dosing in children during emergencies. A simple height-based system can support health care providers and helps to avoid life-threatening medication errors.

Prevalence of Amblyopia and Refractive Errors Among Primary School Children

PubMed Central

Rajavi, Zhale; Sabbaghi, Hamideh; Baghini, Ahmad Shojaei; Yaseri, Mehdi; Moein, Hamidreza; Akbarian, Shadi; Behradfar, Narges; Hosseini, Simin; Rabei, Hossein Mohammad; Sheibani, Kourosh

2015-01-01

Purpose: To determine the prevalence of amblyopia and refractive errors among 7 to 12-year-old primary school children in Tehran, Iran. Methods: This population-based cross-sectional study included 2,410 randomly selected students. Visual acuity was tested using an E-chart on Yang vision tester. Refractive errors were measured by photorefractometry and cycloautorefraction. Strabismus was checked using cover test. Direct ophthalmoscopy was used to assess the anterior segment, lens opacities, red reflex and fundus. Functional amblyopia was defined as best corrected visual acuity ≤20/40 in one or both eyes with no anatomical problems. Results: Amblyopia was present in 2.3% (95% CI: 1.8% to 2.9%) of participants with no difference between the genders. Amblyopic subjects were significantly younger than non-amblyopic children (P=0.004). Overall, 15.9% of hyperopic and 5.9% of myopic cases had amblyopia. The prevalence of hyperopia ≥+2.00D, myopia ≤-0.50D, astigmatism ≥0.75D, and anisometropia (≥1.00D) was 3.5%, 4.9%, 22.6%, and 3.9%, respectively. With increasing age, the prevalence of myopia increased (P<0.001), that of hyperopia decreased (P=0.007), but astigmatism showed no change. Strabismus was found in 2.3% of cases. Strabismus (OR=17.9) and refractive errors, especially anisometropia (OR=12.87) and hyperopia (OR=11.87), were important amblyogenic risk factors. Conclusion: The high prevalence of amblyopia in our subjects in comparison to developed countries reveals the necessity of timely and sensitive screening methods. Due to the high prevalence of amblyopia among children with refractive errors, particularly high hyperopia and anisometropia, provision of glasses should be specifically attended by parents and supported by the Ministry of Health and insurance organizations. PMID:27051485

Electron Beam Propagation Through a Magnetic Wiggler with Random Field Errors

DTIC Science & Technology

1989-08-21

Another quantity of interest is the vector potential 6.A,.(:) associated with the field error 6B,,,(:). Defining the normalized vector potentials ba = ebA...then follows that the correlation of the normalized vector potential errors is given by 1 . 12 (-a.(zj)a.,(z2)) = a,k,, dz’ , dz" (bBE(z’)bB , (z")) a2...Throughout the following, terms of order O(z:/z) will be neglected. Similarly, for the y-component of the normalized vector potential errors, one

Remediating Common Math Errors.

ERIC Educational Resources Information Center

Wagner, Rudolph F.

1981-01-01

Explanations and remediation suggestions for five types of mathematics errors due either to perceptual or cognitive difficulties are given. Error types include directionality problems, mirror writing, visually misperceived signs, diagnosed directionality problems, and mixed process errors. (CL)

Intimate Partner Violence, 1993-2010

MedlinePlus

... appendix table 2 for standard errors. *Due to methodological changes, use caution when comparing 2006 NCVS criminal ... appendix table 2 for standard errors. *Due to methodological changes, use caution when comparing 2006 NCVS criminal ...

A retrospective study on the incidences of adverse drug events and analysis of the contributing trigger factors

PubMed Central

Sam, Aaseer Thamby; Lian Jessica, Looi Li; Parasuraman, Subramani

2015-01-01

Objectives: To retrospectively determine the extent and types of adverse drug events (ADEs) from the patient cases sheets and identify the contributing factors of medication errors. To assess causality and severity using the World Health Organization (WHO) probability scale and Hartwig's scale, respectively. Methods: Hundred patient case sheets were randomly selected, modified version of the Institute for Healthcare Improvement (IHI) Global Trigger Tool was utilized to identify the ADEs; causality and severity were calculated utilizing the WHO probability scale and Hartwig's severity assessment scale, respectively. Results: In total, 153 adverse events (AEs) were identified using the IHI Global Trigger Tool. Majority of the AEs are due to medication errors (46.41%) followed by 60 adverse drug reactions (ADRs), 15 therapeutic failure incidents, and 7 over-dose cases. Out of the 153 AEs, 60 are due to ADRs such as rashes, nausea, and vomiting. Therapeutic failure contributes 9.80% of the AEs, while overdose contributes to 4.58% of the total 153 AEs. Using the trigger tools, we were able to detect 45 positive triggers in 36 patient records. Among it, 19 AEs were identified in 15 patient records. The percentage of AE/100 patients is 17%. The average ADEs/1000 doses is 2.03% (calculated). Conclusion: The IHI Global Trigger Tool is an effective method to aid provisionally-registered pharmacists to identify ADEs quicker. PMID:25767366

Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions

NASA Astrophysics Data System (ADS)

Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej

2014-05-01

The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a factor of 2 or 3. The assumption of white plus flicker plus random-walk noise (which is considered to be the effect of badly monumented stations) resulted in the random-walk amplitudes at the level of single millimetres for some of the stations, while for the majority of them no random-walk was detected, due to the fact that flicker noise prevails in GPS time series. The removal of CME caused the decrease in flicker noise amplitudes leading at the same time to greater random-walk amplitudes. The assumed combination of white plus power-law noise showed that the spectral indices for the best fitted noise model are unevenly distributed around -1 what also indicates the flicker noise existence in EPN weekly time series. The poster will present all of the assumed noise model combinations with the comparison of noise amplitudes before and after spatial filtering. Additionally, we will discuss over the latitude and longitude noise dependencies for the area of Europe to indicate any similarities between noise amplitudes and the location of stations. Finally, we will focus on the velocities with their uncertainties that were determined from EPN weekly solutions and show how the wrong assumption of noise model changes both of them.

Phenotypic Graphs and Evolution Unfold the Standard Genetic Code as the Optimal

NASA Astrophysics Data System (ADS)

Zamudio, Gabriel S.; José, Marco V.

2018-03-01

In this work, we explicitly consider the evolution of the Standard Genetic Code (SGC) by assuming two evolutionary stages, to wit, the primeval RNY code and two intermediate codes in between. We used network theory and graph theory to measure the connectivity of each phenotypic graph. The connectivity values are compared to the values of the codes under different randomization scenarios. An error-correcting optimal code is one in which the algebraic connectivity is minimized. We show that the SGC is optimal in regard to its robustness and error-tolerance when compared to all random codes under different assumptions.

Entropy-Based TOA Estimation and SVM-Based Ranging Error Mitigation in UWB Ranging Systems

PubMed Central

Yin, Zhendong; Cui, Kai; Wu, Zhilu; Yin, Liang

2015-01-01

The major challenges for Ultra-wide Band (UWB) indoor ranging systems are the dense multipath and non-line-of-sight (NLOS) problems of the indoor environment. To precisely estimate the time of arrival (TOA) of the first path (FP) in such a poor environment, a novel approach of entropy-based TOA estimation and support vector machine (SVM) regression-based ranging error mitigation is proposed in this paper. The proposed method can estimate the TOA precisely by measuring the randomness of the received signals and mitigate the ranging error without the recognition of the channel conditions. The entropy is used to measure the randomness of the received signals and the FP can be determined by the decision of the sample which is followed by a great entropy decrease. The SVM regression is employed to perform the ranging-error mitigation by the modeling of the regressor between the characteristics of received signals and the ranging error. The presented numerical simulation results show that the proposed approach achieves significant performance improvements in the CM1 to CM4 channels of the IEEE 802.15.4a standard, as compared to conventional approaches. PMID:26007726

Debiasing affective forecasting errors with targeted, but not representative, experience narratives.

PubMed

Shaffer, Victoria A; Focella, Elizabeth S; Scherer, Laura D; Zikmund-Fisher, Brian J

2016-10-01

To determine whether representative experience narratives (describing a range of possible experiences) or targeted experience narratives (targeting the direction of forecasting bias) can reduce affective forecasting errors, or errors in predictions of experiences. In Study 1, participants (N=366) were surveyed about their experiences with 10 common medical events. Those who had never experienced the event provided ratings of predicted discomfort and those who had experienced the event provided ratings of actual discomfort. Participants making predictions were randomly assigned to either the representative experience narrative condition or the control condition in which they made predictions without reading narratives. In Study 2, participants (N=196) were again surveyed about their experiences with these 10 medical events, but participants making predictions were randomly assigned to either the targeted experience narrative condition or the control condition. Affective forecasting errors were observed in both studies. These forecasting errors were reduced with the use of targeted experience narratives (Study 2) but not representative experience narratives (Study 1). Targeted, but not representative, narratives improved the accuracy of predicted discomfort. Public collections of patient experiences should favor stories that target affective forecasting biases over stories representing the range of possible experiences. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Maximum type I error rate inflation from sample size reassessment when investigators are blind to treatment labels.

PubMed

Żebrowska, Magdalena; Posch, Martin; Magirr, Dominic

2016-05-30

Consider a parallel group trial for the comparison of an experimental treatment to a control, where the second-stage sample size may depend on the blinded primary endpoint data as well as on additional blinded data from a secondary endpoint. For the setting of normally distributed endpoints, we demonstrate that this may lead to an inflation of the type I error rate if the null hypothesis holds for the primary but not the secondary endpoint. We derive upper bounds for the inflation of the type I error rate, both for trials that employ random allocation and for those that use block randomization. We illustrate the worst-case sample size reassessment rule in a case study. For both randomization strategies, the maximum type I error rate increases with the effect size in the secondary endpoint and the correlation between endpoints. The maximum inflation increases with smaller block sizes if information on the block size is used in the reassessment rule. Based on our findings, we do not question the well-established use of blinded sample size reassessment methods with nuisance parameter estimates computed from the blinded interim data of the primary endpoint. However, we demonstrate that the type I error rate control of these methods relies on the application of specific, binding, pre-planned and fully algorithmic sample size reassessment rules and does not extend to general or unplanned sample size adjustments based on blinded data. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Improved uncertainty quantification in nondestructive assay for nonproliferation

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

Burr, Tom; Croft, Stephen; Jarman, Ken

2016-12-01

This paper illustrates methods to improve uncertainty quantification (UQ) for non-destructive assay (NDA) measurements used in nuclear nonproliferation. First, it is shown that current bottom-up UQ applied to calibration data is not always adequate, for three main reasons: (1) Because there are errors in both the predictors and the response, calibration involves a ratio of random quantities, and calibration data sets in NDA usually consist of only a modest number of samples (3–10); therefore, asymptotic approximations involving quantities needed for UQ such as means and variances are often not sufficiently accurate; (2) Common practice overlooks that calibration implies a partitioningmore » of total error into random and systematic error, and (3) In many NDA applications, test items exhibit non-negligible departures in physical properties from calibration items, so model-based adjustments are used, but item-specific bias remains in some data. Therefore, improved bottom-up UQ using calibration data should predict the typical magnitude of item-specific bias, and the suggestion is to do so by including sources of item-specific bias in synthetic calibration data that is generated using a combination of modeling and real calibration data. Second, for measurements of the same nuclear material item by both the facility operator and international inspectors, current empirical (top-down) UQ is described for estimating operator and inspector systematic and random error variance components. A Bayesian alternative is introduced that easily accommodates constraints on variance components, and is more robust than current top-down methods to the underlying measurement error distributions.« less

Intrusion errors in visuospatial working memory performance.

PubMed

Cornoldi, Cesare; Mammarella, Nicola

2006-02-01

This study tested the hypothesis that failure in active visuospatial working memory tasks involves a difficulty in avoiding intrusions due to information that is already activated. Two experiments are described, in which participants were required to process several series of locations on a 4 x 4 matrix and then to produce only the final location of each series. Results revealed a higher number of errors due to already activated locations (intrusions) compared with errors due to new locations (inventions). Moreover, when participants were required to pay extra attention to some irrelevant (non-final) locations by tapping on the table, intrusion errors increased. Results are discussed in terms of current models of working memory functioning.

MERLIN: a Franco-German LIDAR space mission for atmospheric methane

NASA Astrophysics Data System (ADS)

Bousquet, P.; Ehret, G.; Pierangelo, C.; Marshall, J.; Bacour, C.; Chevallier, F.; Gibert, F.; Armante, R.; Crevoisier, C. D.; Edouart, D.; Esteve, F.; Julien, E.; Kiemle, C.; Alpers, M.; Millet, B.

2017-12-01

The Methane Remote Sensing Lidar Mission (MERLIN), currently in phase C, is a joint cooperation between France and Germany on the development, launch and operation of a space LIDAR dedicated to the retrieval of total weighted methane (CH4) atmospheric columns. Atmospheric methane is the second most potent anthropogenic greenhouse gas, contributing 20% to climate radiative forcing but also plying an important role in atmospheric chemistry as a precursor of tropospheric ozone and low-stratosphere water vapour. Its short lifetime ( 9 years) and the nature and variety of its anthropogenic sources also offer interesting mitigation options in regards to the 2° objective of the Paris agreement. For the first time, measurements of atmospheric composition will be performed from space thanks to an IPDA (Integrated Path Differential Absorption) LIDAR (Light Detecting And Ranging), with a precision (target ±27 ppb for a 50km aggregation along the trace) and accuracy (target <3.7 ppb at 68%) sufficient to significantly reduce the uncertainties on methane emissions. The very low targeted systematic error target is particularly ambitious compared to current passive methane space mission. It is achievable because of the differential active measurements of MERLIN, which guarantees almost no contamination by aerosols or water vapour cross-sensitivity. As an active mission, MERLIN will deliver global methane weighted columns (XCH4) for all seasons and all latitudes, day and night Here, we recall the MERLIN objectives and mission characteristics. We also propose an end-to-end error analysis, from the causes of random and systematic errors of the instrument, of the platform and of the data treatment, to the error on methane emissions. To do so, we propose an OSSE analysis (observing system simulation experiment) to estimate the uncertainty reduction on methane emissions brought by MERLIN XCH4. The originality of our inversion system is to transfer both random and systematic errors from the observation space to the flux space, thus providing more realistic error reductions than usually provided in OSSE only using the random part of errors. Uncertainty reductions are presented using two different atmospheric transport models, TM3 and LMDZ, and compared with error reduction achieved with the GOSAT passive mission.

Effect of citizen engagement levels in flood forecasting by assimilating crowdsourced observations in hydrological models

NASA Astrophysics Data System (ADS)

Mazzoleni, Maurizio; Cortes Arevalo, Juliette; Alfonso, Leonardo; Wehn, Uta; Norbiato, Daniele; Monego, Martina; Ferri, Michele; Solomatine, Dimitri

2017-04-01

In the past years, a number of methods have been proposed to reduce uncertainty in flood prediction by means of model updating techniques. Traditional physical observations are usually integrated into hydrological and hydraulic models to improve model performances and consequent flood predictions. Nowadays, low-cost sensors can be used for crowdsourced observations. Different type of social sensors can measure, in a more distributed way, physical variables such as precipitation and water level. However, these crowdsourced observations are not integrated into a real-time fashion into water-system models due to their varying accuracy and random spatial-temporal coverage. We assess the effect in model performance due to the assimilation of crowdsourced observations of water level. Our method consists in (1) implementing a Kalman filter into a cascade of hydrological and hydraulic models. (2) defining observation errors depending on the type of sensor either physical or social. Randomly distributed errors are based on accuracy ranges that slightly improve according to the citizens' expertise level. (3) Using a simplified social model to realistically represent citizen engagement levels based on population density and citizens' motivation scenarios. To test our method, we synthetically derive crowdsourced observations for different citizen engagement levels from a distributed network of physical and social sensors. The observations are assimilated during a particular flood event occurred in the Bacchiglione catchment, Italy. The results of this study demonstrate that sharing crowdsourced water level observations (often motivated by a feeling of belonging to a community of friends) can help in improving flood prediction. On the other hand, a growing participation of individual citizens or weather enthusiasts sharing hydrological observations in cities can help to improve model performance. This study is a first step to assess the effects of crowdsourced observations in flood model predictions. Effective communication and feedback about the quality of observations from water authorities to engaged citizens are further required to minimize their intrinsic low-variable accuracy.

Goldmann tonometer error correcting prism: clinical evaluation.

PubMed

McCafferty, Sean; Lim, Garrett; Duncan, William; Enikov, Eniko T; Schwiegerling, Jim; Levine, Jason; Kew, Corin

2017-01-01

Clinically evaluate a modified applanating surface Goldmann tonometer prism designed to substantially negate errors due to patient variability in biomechanics. A modified Goldmann prism with a correcting applanation tonometry surface (CATS) was mathematically optimized to minimize the intraocular pressure (IOP) measurement error due to patient variability in corneal thickness, stiffness, curvature, and tear film adhesion force. A comparative clinical study of 109 eyes measured IOP with CATS and Goldmann prisms. The IOP measurement differences between the CATS and Goldmann prisms were correlated to corneal thickness, hysteresis, and curvature. The CATS tonometer prism in correcting for Goldmann central corneal thickness (CCT) error demonstrated a reduction to <±2 mmHg in 97% of a standard CCT population. This compares to only 54% with CCT error <±2 mmHg using the Goldmann prism. Equal reductions of ~50% in errors due to corneal rigidity and curvature were also demonstrated. The results validate the CATS prism's improved accuracy and expected reduced sensitivity to Goldmann errors without IOP bias as predicted by mathematical modeling. The CATS replacement for the Goldmann prism does not change Goldmann measurement technique or interpretation.

Research of laser echo signal simulator

NASA Astrophysics Data System (ADS)

Xu, Rui; Shi, Rui; Wang, Xin; Li, Zhou

2015-11-01

Laser echo signal simulator is one of the most significant components of hardware-in-the-loop (HWIL) simulation systems for LADAR. System model and time series model of laser echo signal simulator are established. Some influential factors which could induce fixed error and random error on the simulated return signals are analyzed, and then these system insertion errors are analyzed quantitatively. Using this theoretical model, the simulation system is investigated experimentally. The results corrected by subtracting fixed error indicate that the range error of the simulated laser return signal is less than 0.25m, and the distance range that the system can simulate is from 50m to 20km.

Natural Selection as an Emergent Process: Instructional Implications

ERIC Educational Resources Information Center

Cooper, Robert A.

2017-01-01

Student reasoning about cases of natural selection is often plagued by errors that stem from miscategorising selection as a direct, causal process, misunderstanding the role of randomness, and from the intuitive ideas of intentionality, teleology and essentialism. The common thread throughout many of these reasoning errors is a failure to apply…

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2010 CFR

2010-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2014 CFR

2014-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2012 CFR

2012-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2013 CFR

2013-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

26 CFR 301.6621-3 - Higher interest rate payable on large corporate underpayments.

Code of Federal Regulations, 2011 CFR

2011-04-01

... resulting from a math error on Y's return. Y did not request an abatement of the assessment pursuant to...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...,000 amount shown as due on the math error assessment notice (plus interest) on or before January 31...

Data entry errors and design for model-based tight glycemic control in critical care.

PubMed

Ward, Logan; Steel, James; Le Compte, Aaron; Evans, Alicia; Tan, Chia-Siong; Penning, Sophie; Shaw, Geoffrey M; Desaive, Thomas; Chase, J Geoffrey

2012-01-01

Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human data entry, particularly of blood glucose (BG) values, which can be significantly prone to error. This study presents the design and optimization of data entry methods to minimize error for a computerized and model-based TGC method prior to pilot clinical trials. To minimize data entry error, two tests were carried out to optimize a method with errors less than the 5%-plus reported in other studies. Four initial methods were tested on 40 subjects in random order, and the best two were tested more rigorously on 34 subjects. The tests measured entry speed and accuracy. Errors were reported as corrected and uncorrected errors, with the sum comprising a total error rate. The first set of tests used randomly selected values, while the second set used the same values for all subjects to allow comparisons across users and direct assessment of the magnitude of errors. These research tests were approved by the University of Canterbury Ethics Committee. The final data entry method tested reduced errors to less than 1-2%, a 60-80% reduction from reported values. The magnitude of errors was clinically significant and was typically by 10.0 mmol/liter or an order of magnitude but only for extreme values of BG < 2.0 mmol/liter or BG > 15.0-20.0 mmol/liter, both of which could be easily corrected with automated checking of extreme values for safety. The data entry method selected significantly reduced data entry errors in the limited design tests presented, and is in use on a clinical pilot TGC study. The overall approach and testing methods are easily performed and generalizable to other applications and protocols. © 2012 Diabetes Technology Society.

An Economical Analytical Equation for the Integrated Vertical Overlap of Cumulus and Stratus

NASA Astrophysics Data System (ADS)

Park, Sungsu

2018-03-01

By extending the previously proposed heuristic parameterization, the author derived an analytical equation computing the overlap areas between the precipitation (or radiation) areas and the cloud areas in a cloud system consisting of cumulus and stratus. The new analytical equation is accurate and much more efficient than the previous heuristic equation, which suffers from the truncation error in association with the digitalization of the overlap areas. Global test simulations with the new analytical formula in an offline mode showed that the maximum cumulus overlap simulates more surface precipitation flux than the random cumulus overlap. On the other hand, the maximum stratus overlap simulates less surface precipitation flux than random stratus overlap, which is due to the increase in the evaporation rate of convective precipitation from the random to maximum stratus overlap. The independent precipitation approximation (IPA) marginally decreases the surface precipitation flux, implying that IPA works well with other parameterizations. In contrast to the net production rate of precipitation and surface precipitation flux that increase when the cumulus and stratus are maximally and randomly overlapped, respectively, the global mean net radiative cooling and longwave cloud radiative forcing (LWCF) increase when the cumulus and stratus are randomly overlapped. On the global average, the vertical cloud overlap exerts larger impacts on the precipitation flux than on the radiation flux. The radiation scheme taking the subgrid variability of water vapor between the cloud and clear portions into account substantially increases the global mean LWCF in tropical deep convection and midlatitude storm track regions.

Localization Methods for a Mobile Robot in Urban Environments

DTIC Science & Technology

2004-10-04

Columbia University, Department of Computer Science, 2001. [30] R. Brown and P. Hwang , Introduction to random signals and applied Kalman filtering, 3rd...sensor. An extended Kalman filter integrates the sensor data and keeps track of the uncertainty associated with it. The second method is based on...errors+ compass/GPS errors corrected odometry pose odometry error estimates zk zk h(x)~ h(x)~ Kalman Filter zk Fig. 4. A diagram of the extended

Wavefront reconstruction algorithm based on Legendre polynomials for radial shearing interferometry over a square area and error analysis.

PubMed

Kewei, E; Zhang, Chen; Li, Mengyang; Xiong, Zhao; Li, Dahai

2015-08-10

Based on the Legendre polynomials expressions and its properties, this article proposes a new approach to reconstruct the distorted wavefront under test of a laser beam over square area from the phase difference data obtained by a RSI system. And the result of simulation and experimental results verifies the reliability of the method proposed in this paper. The formula of the error propagation coefficients is deduced when the phase difference data of overlapping area contain noise randomly. The matrix T which can be used to evaluate the impact of high-orders Legendre polynomial terms on the outcomes of the low-order terms due to mode aliasing is proposed, and the magnitude of impact can be estimated by calculating the F norm of the T. In addition, the relationship between ratio shear, sampling points, terms of polynomials and noise propagation coefficients, and the relationship between ratio shear, sampling points and norms of the T matrix are both analyzed, respectively. Those research results can provide an optimization design way for radial shearing interferometry system with the theoretical reference and instruction.

Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials

PubMed Central

Gilbert, Peter B.; Janes, Holly E.; Huang, Yunda

2016-01-01

In a randomized controlled clinical trial that assesses treatment efficacy, a common objective is to assess the association of a measured biomarker response endpoint with the primary study endpoint in the active treatment group, using a case-cohort, case-control, or two-phase sampling design. Methods for power and sample size calculations for such biomarker association analyses typically do not account for the level of treatment efficacy, precluding interpretation of the biomarker association results in terms of biomarker effect modification of treatment efficacy, with detriment that the power calculations may tacitly and inadvertently assume that the treatment harms some study participants. We develop power and sample size methods accounting for this issue, and the methods also account for inter-individual variability of the biomarker that is not biologically relevant (e.g., due to technical measurement error). We focus on a binary study endpoint and on a biomarker subject to measurement error that is normally distributed or categorical with two or three levels. We illustrate the methods with preventive HIV vaccine efficacy trials, and include an R package implementing the methods. PMID:27037797

A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms

PubMed Central

Yang, Changju; Kim, Hyongsuk; Adhikari, Shyam Prasad; Chua, Leon O.

2016-01-01

A hybrid learning method of a software-based backpropagation learning and a hardware-based RWC learning is proposed for the development of circuit-based neural networks. The backpropagation is known as one of the most efficient learning algorithms. A weak point is that its hardware implementation is extremely difficult. The RWC algorithm, which is very easy to implement with respect to its hardware circuits, takes too many iterations for learning. The proposed learning algorithm is a hybrid one of these two. The main learning is performed with a software version of the BP algorithm, firstly, and then, learned weights are transplanted on a hardware version of a neural circuit. At the time of the weight transplantation, a significant amount of output error would occur due to the characteristic difference between the software and the hardware. In the proposed method, such error is reduced via a complementary learning of the RWC algorithm, which is implemented in a simple hardware. The usefulness of the proposed hybrid learning system is verified via simulations upon several classical learning problems. PMID:28025566

Detecting and preventing error propagation via competitive learning.

PubMed

Silva, Thiago Christiano; Zhao, Liang

2013-05-01

Semisupervised learning is a machine learning approach which is able to employ both labeled and unlabeled samples in the training process. It is an important mechanism for autonomous systems due to the ability of exploiting the already acquired information and for exploring the new knowledge in the learning space at the same time. In these cases, the reliability of the labels is a crucial factor, because mislabeled samples may propagate wrong labels to a portion of or even the entire data set. This paper has the objective of addressing the error propagation problem originated by these mislabeled samples by presenting a mechanism embedded in a network-based (graph-based) semisupervised learning method. Such a procedure is based on a combined random-preferential walk of particles in a network constructed from the input data set. The particles of the same class cooperate among them, while the particles of different classes compete with each other to propagate class labels to the whole network. Computer simulations conducted on synthetic and real-world data sets reveal the effectiveness of the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

PubMed

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Modified Bat Algorithm for Feature Selection with the Wisconsin Diagnosis Breast Cancer (WDBC) Dataset

PubMed

Jeyasingh, Suganthi; Veluchamy, Malathi

2017-05-01

Early diagnosis of breast cancer is essential to save lives of patients. Usually, medical datasets include a large variety of data that can lead to confusion during diagnosis. The Knowledge Discovery on Database (KDD) process helps to improve efficiency. It requires elimination of inappropriate and repeated data from the dataset before final diagnosis. This can be done using any of the feature selection algorithms available in data mining. Feature selection is considered as a vital step to increase the classification accuracy. This paper proposes a Modified Bat Algorithm (MBA) for feature selection to eliminate irrelevant features from an original dataset. The Bat algorithm was modified using simple random sampling to select the random instances from the dataset. Ranking was with the global best features to recognize the predominant features available in the dataset. The selected features are used to train a Random Forest (RF) classification algorithm. The MBA feature selection algorithm enhanced the classification accuracy of RF in identifying the occurrence of breast cancer. The Wisconsin Diagnosis Breast Cancer Dataset (WDBC) was used for estimating the performance analysis of the proposed MBA feature selection algorithm. The proposed algorithm achieved better performance in terms of Kappa statistic, Mathew’s Correlation Coefficient, Precision, F-measure, Recall, Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Relative Absolute Error (RAE) and Root Relative Squared Error (RRSE). Creative Commons Attribution License

Effects of tropospheric and ionospheric refraction errors in the utilization of GEOS-C altimeter data

NASA Technical Reports Server (NTRS)

Goad, C. C.

1977-01-01

The effects of tropospheric and ionospheric refraction errors are analyzed for the GEOS-C altimeter project in terms of their resultant effects on C-band orbits and the altimeter measurement itself. Operational procedures using surface meteorological measurements at ground stations and monthly means for ocean surface conditions are assumed, with no corrections made for ionospheric effects. Effects on the orbit height due to tropospheric errors are approximately 15 cm for single pass short arcs (such as for calibration) and 10 cm for global orbits of one revolution. Orbit height errors due to neglect of the ionosphere have an amplitude of approximately 40 cm when the orbits are determined from C-band range data with predominantly daylight tracking. Altimeter measurement errors are approximately 10 cm due to residual tropospheric refraction correction errors. Ionospheric effects on the altimeter range measurement are also on the order of 10 cm during the GEOS-C launch and early operation period.

Geographically correlated orbit error

NASA Technical Reports Server (NTRS)

Rosborough, G. W.

1989-01-01

The dominant error source in estimating the orbital position of a satellite from ground based tracking data is the modeling of the Earth's gravity field. The resulting orbit error due to gravity field model errors are predominantly long wavelength in nature. This results in an orbit error signature that is strongly correlated over distances on the size of ocean basins. Anderle and Hoskin (1977) have shown that the orbit error along a given ground track also is correlated to some degree with the orbit error along adjacent ground tracks. This cross track correlation is verified here and is found to be significant out to nearly 1000 kilometers in the case of TOPEX/POSEIDON when using the GEM-T1 gravity model. Finally, it was determined that even the orbit error at points where ascending and descending ground traces cross is somewhat correlated. The implication of these various correlations is that the orbit error due to gravity error is geographically correlated. Such correlations have direct implications when using altimetry to recover oceanographic signals.

Iterative random vs. Kennard-Stone sampling for IR spectrum-based classification task using PLS2-DA

NASA Astrophysics Data System (ADS)

Lee, Loong Chuen; Liong, Choong-Yeun; Jemain, Abdul Aziz

2018-04-01

External testing (ET) is preferred over auto-prediction (AP) or k-fold-cross-validation in estimating more realistic predictive ability of a statistical model. With IR spectra, Kennard-stone (KS) sampling algorithm is often used to split the data into training and test sets, i.e. respectively for model construction and for model testing. On the other hand, iterative random sampling (IRS) has not been the favored choice though it is theoretically more likely to produce reliable estimation. The aim of this preliminary work is to compare performances of KS and IRS in sampling a representative training set from an attenuated total reflectance - Fourier transform infrared spectral dataset (of four varieties of blue gel pen inks) for PLS2-DA modeling. The `best' performance achievable from the dataset is estimated with AP on the full dataset (APF, error). Both IRS (n = 200) and KS were used to split the dataset in the ratio of 7:3. The classic decision rule (i.e. maximum value-based) is employed for new sample prediction via partial least squares - discriminant analysis (PLS2-DA). Error rate of each model was estimated repeatedly via: (a) AP on full data (APF, error); (b) AP on training set (APS, error); and (c) ET on the respective test set (ETS, error). A good PLS2-DA model is expected to produce APS, error and EVS, error that is similar to the APF, error. Bearing that in mind, the similarities between (a) APS, error vs. APF, error; (b) ETS, error vs. APF, error and; (c) APS, error vs. ETS, error were evaluated using correlation tests (i.e. Pearson and Spearman's rank test), using series of PLS2-DA models computed from KS-set and IRS-set, respectively. Overall, models constructed from IRS-set exhibits more similarities between the internal and external error rates than the respective KS-set, i.e. less risk of overfitting. In conclusion, IRS is more reliable than KS in sampling representative training set.

Transperineal prostate biopsy under magnetic resonance image guidance: a needle placement accuracy study.

PubMed

Blumenfeld, Philip; Hata, Nobuhiko; DiMaio, Simon; Zou, Kelly; Haker, Steven; Fichtinger, Gabor; Tempany, Clare M C

2007-09-01

To quantify needle placement accuracy of magnetic resonance image (MRI)-guided core needle biopsy of the prostate. A total of 10 biopsies were performed with 18-gauge (G) core biopsy needle via a percutaneous transperineal approach. Needle placement error was assessed by comparing the coordinates of preplanned targets with the needle tip measured from the intraprocedural coherent gradient echo images. The source of these errors was subsequently investigated by measuring displacement caused by needle deflection and needle susceptibility artifact shift in controlled phantom studies. Needle placement error due to misalignment of the needle template guide was also evaluated. The mean and standard deviation (SD) of errors in targeted biopsies was 6.5 +/- 3.5 mm. Phantom experiments showed significant placement error due to needle deflection with a needle with an asymmetrically beveled tip (3.2-8.7 mm depending on tissue type) but significantly smaller error with a symmetrical bevel (0.6-1.1 mm). Needle susceptibility artifacts observed a shift of 1.6 +/- 0.4 mm from the true needle axis. Misalignment of the needle template guide contributed an error of 1.5 +/- 0.3 mm. Needle placement error was clinically significant in MRI-guided biopsy for diagnosis of prostate cancer. Needle placement error due to needle deflection was the most significant cause of error, especially for needles with an asymmetrical bevel. (c) 2007 Wiley-Liss, Inc.

Approximating prediction uncertainty for random forest regression models

Treesearch

John W. Coulston; Christine E. Blinn; Valerie A. Thomas; Randolph H. Wynne

2016-01-01

Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as...

A variational regularization of Abel transform for GPS radio occultation

NASA Astrophysics Data System (ADS)

Wee, Tae-Kwon

2018-04-01

In the Global Positioning System (GPS) radio occultation (RO) technique, the inverse Abel transform of measured bending angle (Abel inversion, hereafter AI) is the standard means of deriving the refractivity. While concise and straightforward to apply, the AI accumulates and propagates the measurement error downward. The measurement error propagation is detrimental to the refractivity in lower altitudes. In particular, it builds up negative refractivity bias in the tropical lower troposphere. An alternative to AI is the numerical inversion of the forward Abel transform, which does not incur the integration of error-possessing measurement and thus precludes the error propagation. The variational regularization (VR) proposed in this study approximates the inversion of the forward Abel transform by an optimization problem in which the regularized solution describes the measurement as closely as possible within the measurement's considered accuracy. The optimization problem is then solved iteratively by means of the adjoint technique. VR is formulated with error covariance matrices, which permit a rigorous incorporation of prior information on measurement error characteristics and the solution's desired behavior into the regularization. VR holds the control variable in the measurement space to take advantage of the posterior height determination and to negate the measurement error due to the mismodeling of the refractional radius. The advantages of having the solution and the measurement in the same space are elaborated using a purposely corrupted synthetic sounding with a known true solution. The competency of VR relative to AI is validated with a large number of actual RO soundings. The comparison to nearby radiosonde observations shows that VR attains considerably smaller random and systematic errors compared to AI. A noteworthy finding is that in the heights and areas that the measurement bias is supposedly small, VR follows AI very closely in the mean refractivity deserting the first guess. In the lowest few kilometers that AI produces large negative refractivity bias, VR reduces the refractivity bias substantially with the aid of the background, which in this study is the operational forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF). It is concluded based on the results presented in this study that VR offers a definite advantage over AI in the quality of refractivity.

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

Accurate Magnetometer/Gyroscope Attitudes Using a Filter with Correlated Sensor Noise

NASA Technical Reports Server (NTRS)

Sedlak, J.; Hashmall, J.

1997-01-01

Magnetometers and gyroscopes have been shown to provide very accurate attitudes for a variety of spacecraft. These results have been obtained, however, using a batch-least-squares algorithm and long periods of data. For use in onboard applications, attitudes are best determined using sequential estimators such as the Kalman filter. When a filter is used to determine attitudes using magnetometer and gyroscope data for input, the resulting accuracy is limited by both the sensor accuracies and errors inherent in the Earth magnetic field model. The Kalman filter accounts for the random component by modeling the magnetometer and gyroscope errors as white noise processes. However, even when these tuning parameters are physically realistic, the rate biases (included in the state vector) have been found to show systematic oscillations. These are attributed to the field model errors. If the gyroscope noise is sufficiently small, the tuned filter 'memory' will be long compared to the orbital period. In this case, the variations in the rate bias induced by field model errors are substantially reduced. Mistuning the filter to have a short memory time leads to strongly oscillating rate biases and increased attitude errors. To reduce the effect of the magnetic field model errors, these errors are estimated within the filter and used to correct the reference model. An exponentially-correlated noise model is used to represent the filter estimate of the systematic error. Results from several test cases using in-flight data from the Compton Gamma Ray Observatory are presented. These tests emphasize magnetometer errors, but the method is generally applicable to any sensor subject to a combination of random and systematic noise.

A Simple Exact Error Rate Analysis for DS-CDMA with Arbitrary Pulse Shape in Flat Nakagami Fading

NASA Astrophysics Data System (ADS)

Rahman, Mohammad Azizur; Sasaki, Shigenobu; Kikuchi, Hisakazu; Harada, Hiroshi; Kato, Shuzo

A simple exact error rate analysis is presented for random binary direct sequence code division multiple access (DS-CDMA) considering a general pulse shape and flat Nakagami fading channel. First of all, a simple model is developed for the multiple access interference (MAI). Based on this, a simple exact expression of the characteristic function (CF) of MAI is developed in a straight forward manner. Finally, an exact expression of error rate is obtained following the CF method of error rate analysis. The exact error rate so obtained can be much easily evaluated as compared to the only reliable approximate error rate expression currently available, which is based on the Improved Gaussian Approximation (IGA).

A service evaluation of on-line image-guided radiotherapy to lower extremity sarcoma: Investigating the workload implications of a 3 mm action level for image assessment and correction prior to delivery.

PubMed

Taylor, C; Parker, J; Stratford, J; Warren, M

2018-05-01

Although all systematic and random positional setup errors can be corrected for in entirety during on-line image-guided radiotherapy, the use of a specified action level, below which no correction occurs, is also an option. The following service evaluation aimed to investigate the use of this 3 mm action level for on-line image assessment and correction (online, systematic set-up error and weekly evaluation) for lower extremity sarcoma, and understand the impact on imaging frequency and patient positioning error within one cancer centre. All patients were immobilised using a thermoplastic shell attached to a plastic base and an individual moulded footrest. A retrospective analysis of 30 patients was performed. Patient setup and correctional data derived from cone beam CT analysis was retrieved. The timing, frequency and magnitude of corrections were evaluated. The population systematic and random error was derived. 20% of patients had no systematic corrections over the duration of treatment, and 47% had one. The maximum number of systematic corrections per course of radiotherapy was 4, which occurred for 2 patients. 34% of episodes occurred within the first 5 fractions. All patients had at least one observed translational error during their treatment greater than 0.3 cm, and 80% of patients had at least one observed translational error during their treatment greater than 0.5 cm. The population systematic error was 0.14 cm, 0.10 cm, 0.14 cm and random error was 0.27 cm, 0.22 cm, 0.23 cm in the lateral, caudocranial and anteroposterial directions. The required Planning Target Volume margin for the study population was 0.55 cm, 0.41 cm and 0.50 cm in the lateral, caudocranial and anteroposterial directions. The 3 mm action level for image assessment and correction prior to delivery reduced the imaging burden and focussed intervention on patients that exhibited greater positional variability. This strategy could be an efficient deployment of departmental resources if full daily correction of positional setup error is not possible. Copyright © 2017. Published by Elsevier Ltd.

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

Chengqiang, L; Yin, Y; Chen, L

Purpose: To investigate the impact of MLC position errors on simultaneous integrated boost intensity-modulated radiotherapy (SIB-IMRT) for patients with nasopharyngeal carcinoma. Methods: To compare the dosimetric differences between the simulated plans and the clinical plans, ten patients with locally advanced NPC treated with SIB-IMRT were enrolled in this study. All plans were calculated with an inverse planning system (Pinnacle3, Philips Medical System{sub )}. Random errors −2mm to 2mm{sub )},shift errors{sub (} 2mm,1mm and 0.5mm) and systematic extension/ contraction errors (±2mm, ±1mm and ±0.5mm) of the MLC leaf position were introduced respectively into the original plans to create the simulated plans.more » Dosimetry factors were compared between the original and the simulated plans. Results: The dosimetric impact of the random and system shift errors of MLC position was insignificant within 2mm, the maximum changes in D95% of PGTV,PTV1,PTV2 were-0.92±0.51%,1.00±0.24% and 0.62±0.17%, the maximum changes in the D0.1cc of spinal cord and brainstem were 1.90±2.80% and −1.78±1.42%, the maximum changes in the Dmean of parotids were1.36±1.23% and −2.25±2.04%.However,the impact of MLC extension or contraction errors was found significant. For 2mm leaf extension errors, the average changes in D95% of PGTV,PTV1,PTV2 were 4.31±0.67%,4.29±0.65% and 4.79±0.82%, the averaged value of the D0.1cc to spinal cord and brainstem were increased by 7.39±5.25% and 6.32±2.28%,the averaged value of the mean dose to left and right parotid were increased by 12.75±2.02%,13.39±2.17% respectively. Conclusion: The dosimetric effect was insignificant for random MLC leaf position errors up to 2mm. There was a high sensitivity to dose distribution for MLC extension or contraction errors.We should pay attention to the anatomic changes in target organs and anatomical structures during the course,individual radiotherapy was recommended to ensure adaptive doses.« less

Learning a locomotor task: with or without errors?

PubMed

Marchal-Crespo, Laura; Schneider, Jasmin; Jaeger, Lukas; Riener, Robert

2014-03-04

Robotic haptic guidance is the most commonly used robotic training strategy to reduce performance errors while training. However, research on motor learning has emphasized that errors are a fundamental neural signal that drive motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. However, to date, no study has analyzed with precision which training strategy is the most appropriate to learn an especially simple task. In this study, the impact of robotic training strategies that amplify or reduce errors on muscle activation and motor learning of a simple locomotor task was investigated in twenty two healthy subjects. The experiment was conducted with the MAgnetic Resonance COmpatible Stepper (MARCOS) a special robotic device developed for investigations in the MR scanner. The robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping-like movement. Learning with four different training strategies that reduce or amplify errors was evaluated: (i) Haptic guidance: errors were eliminated by passively moving the limbs, (ii) No guidance: no robot disturbances were presented, (iii) Error amplification: existing errors were amplified with repulsive forces, (iv) Noise disturbance: errors were evoked intentionally with a randomly-varying force disturbance on top of the no guidance strategy. Additionally, the activation of four lower limb muscles was measured by the means of surface electromyography (EMG). Strategies that reduce or do not amplify errors limit muscle activation during training and result in poor learning gains. Adding random disturbing forces during training seems to increase attention, and therefore improve motor learning. Error amplification seems to be the most suitable strategy for initially less skilled subjects, perhaps because subjects could better detect their errors and correct them. Error strategies have a great potential to evoke higher muscle activation and provoke better motor learning of simple tasks. Neuroimaging evaluation of brain regions involved in learning can provide valuable information on observed behavioral outcomes related to learning processes. The impacts of these strategies on neurological patients need further investigations.

A dynamic system matching technique for improving the accuracy of MEMS gyroscopes

NASA Astrophysics Data System (ADS)

Stubberud, Peter A.; Stubberud, Stephen C.; Stubberud, Allen R.

2014-12-01

A classical MEMS gyro transforms angular rates into electrical values through Euler's equations of angular rotation. Production models of a MEMS gyroscope will have manufacturing errors in the coefficients of the differential equations. The output signal of a production gyroscope will be corrupted by noise, with a major component of the noise due to the manufacturing errors. As is the case of the components in an analog electronic circuit, one way of controlling the variability of a subsystem is to impose extremely tight control on the manufacturing process so that the coefficient values are within some specified bounds. This can be expensive and may even be impossible as is the case in certain applications of micro-electromechanical (MEMS) sensors. In a recent paper [2], the authors introduced a method for combining the measurements from several nominally equal MEMS gyroscopes using a technique based on a concept from electronic circuit design called dynamic element matching [1]. Because the method in this paper deals with systems rather than elements, it is called a dynamic system matching technique (DSMT). The DSMT generates a single output by randomly switching the outputs of several, nominally identical, MEMS gyros in and out of the switch output. This has the effect of 'spreading the spectrum' of the noise caused by the coefficient errors generated in the manufacture of the individual gyros. A filter can then be used to eliminate that part of the spread spectrum that is outside the pass band of the gyro. A heuristic analysis in that paper argues that the DSMT can be used to control the effects of the random coefficient variations. In a follow-on paper [4], a simulation of a DSMT indicated that the heuristics were consistent. In this paper, analytic expressions of the DSMT noise are developed which confirm that the earlier conclusions are valid. These expressions include the various DSMT design parameters and, therefore, can be used as design tools for DSMT systems.

Residual Seminal Vesicle Displacement in Marker-Based Image-Guided Radiotherapy for Prostate Cancer and the Impact on Margin Design

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

Smitsmans, Monique H.P.; Bois, Josien de; Sonke, Jan-Jakob

Purpose: The objectives of this study were to quantify residual interfraction displacement of seminal vesicles (SV) and investigate the efficacy of rotation correction on SV displacement in marker-based prostate image-guided radiotherapy (IGRT). We also determined the effect of marker registration on the measured SV displacement and its impact on margin design. Methods and Materials: SV displacement was determined relative to marker registration by using 296 cone beam computed tomography scans of 13 prostate cancer patients with implanted markers. SV were individually registered in the transverse plane, based on gray-value information. The target registration error (TRE) for the SV due tomore » marker registration inaccuracies was estimated. Correlations between prostate gland rotations and SV displacement and between individual SV displacements were determined. Results: The SV registration success rate was 99%. Displacement amounts of both SVs were comparable. Systematic and random residual SV displacements were 1.6 mm and 2.0 mm in the left-right direction, respectively, and 2.8 mm and 3.1 mm in the anteroposterior (AP) direction, respectively. Rotation correction did not reduce residual SV displacement. Prostate gland rotation around the left-right axis correlated with SV AP displacement (R{sup 2} = 42%); a correlation existed between both SVs for AP displacement (R{sup 2} = 62%); considerable correlation existed between random errors of SV displacement and TRE (R{sup 2} = 34%). Conclusions: Considerable residual SV displacement exists in marker-based IGRT. Rotation correction barely reduced SV displacement, rather, a larger SV displacement was shown relative to the prostate gland that was not captured by the marker position. Marker registration error partly explains SV displacement when correcting for rotations. Correcting for rotations, therefore, is not advisable when SV are part of the target volume. Margin design for SVs should take these uncertainties into account.« less

A dynamic system matching technique for improving the accuracy of MEMS gyroscopes

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

Stubberud, Peter A., E-mail: stubber@ee.unlv.edu; Stubberud, Stephen C., E-mail: scstubberud@ieee.org; Stubberud, Allen R., E-mail: stubberud@att.net

A classical MEMS gyro transforms angular rates into electrical values through Euler's equations of angular rotation. Production models of a MEMS gyroscope will have manufacturing errors in the coefficients of the differential equations. The output signal of a production gyroscope will be corrupted by noise, with a major component of the noise due to the manufacturing errors. As is the case of the components in an analog electronic circuit, one way of controlling the variability of a subsystem is to impose extremely tight control on the manufacturing process so that the coefficient values are within some specified bounds. This canmore » be expensive and may even be impossible as is the case in certain applications of micro-electromechanical (MEMS) sensors. In a recent paper [2], the authors introduced a method for combining the measurements from several nominally equal MEMS gyroscopes using a technique based on a concept from electronic circuit design called dynamic element matching [1]. Because the method in this paper deals with systems rather than elements, it is called a dynamic system matching technique (DSMT). The DSMT generates a single output by randomly switching the outputs of several, nominally identical, MEMS gyros in and out of the switch output. This has the effect of 'spreading the spectrum' of the noise caused by the coefficient errors generated in the manufacture of the individual gyros. A filter can then be used to eliminate that part of the spread spectrum that is outside the pass band of the gyro. A heuristic analysis in that paper argues that the DSMT can be used to control the effects of the random coefficient variations. In a follow-on paper [4], a simulation of a DSMT indicated that the heuristics were consistent. In this paper, analytic expressions of the DSMT noise are developed which confirm that the earlier conclusions are valid. These expressions include the various DSMT design parameters and, therefore, can be used as design tools for DSMT systems.« less

Analysis of Prostate Patient Setup and Tracking Data: Potential Intervention Strategies

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

Su Zhong, E-mail: zsu@floridaproton.org; Zhang Lisha; Murphy, Martin

Purpose: To evaluate the setup, interfraction, and intrafraction organ motion error distributions and simulate intrafraction intervention strategies for prostate radiotherapy. Methods and Materials: A total of 17 patients underwent treatment setup and were monitored using the Calypso system during radiotherapy. On average, the prostate tracking measurements were performed for 8 min/fraction for 28 fractions for each patient. For both patient couch shift data and intrafraction organ motion data, the systematic and random errors were obtained from the patient population. The planning target volume margins were calculated using the van Herk formula. Two intervention strategies were simulated using the tracking data:more » the deviation threshold and period. The related planning target volume margins, time costs, and prostate position 'fluctuation' were presented. Results: The required treatment margin for the left-right, superoinferior, and anteroposterior axes was 8.4, 10.8, and 14.7 mm for skin mark-only setup and 1.3, 2.3, and 2.8 mm using the on-line setup correction, respectively. Prostate motion significantly correlated among the superoinferior and anteroposterior directions. Of the 17 patients, 14 had prostate motion within 5 mm of the initial setup position for {>=}91.6% of the total tracking time. The treatment margin decreased to 1.1, 1.8, and 2.3 mm with a 3-mm threshold correction and to 0.5, 1.0, and 1.5 mm with an every-2-min correction in the left-right, superoinferior, and anteroposterior directions, respectively. The periodic corrections significantly increase the treatment time and increased the number of instances when the setup correction was made during transient excursions. Conclusions: The residual systematic and random error due to intrafraction prostate motion is small after on-line setup correction. Threshold-based and time-based intervention strategies both reduced the planning target volume margins. The time-based strategies increased the treatment time and the in-fraction position fluctuation.« less

Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

USGS Publications Warehouse

Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

2015-01-01

Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.