Results for “error indicators” — Page 28

NASA NTRSDate not supplied

Dose Error Correction Using Simulation Extrapolation for Community Noise Dose-Response Modeling

The objective of this work is to provide a framework to account and correct for dose error in dose-response modeling due to measurement uncertainty. Error in noise measurements, especially in the case of limited monitoring locations in a community, can lead to an attenuation or misestimation of parameters in dose-response models. This error can result in overpredicted annoyance at lower doses and underpredicted annoyance at higher doses. Simulated data in the present work are based on previous NASA community studies and incorporate a notional design for future studies with the X-59 aircraft. Several populations of different annoyance response sensitivities are included. Simulation extrapolation (SIMEX, Cook and Stefanski 1994) is used to correct for the dose error in a simple, fully pooled logistic regression. Results indicate the negative impact of attenuation is greatly diminished for all amounts of dose error considered, regardless of a population’s annoyance sensitivity. Therefore, SIMEX can help produce a more accurate dose-response relationship.

SIMEX↗

DOE OSTI2023

Enter Gaussian Mixture Modeling Extensions for Improved False Discovery Rate Estimation in GC-MS Metabolomics

Identifying small molecules (e.g., metabolites) is key towards driving scientific advancement in metabolomics, and gas chromatography–mass spectrometry (GC-MS) is an analytic method that may be applied to facilitate this process. The typical GC-MS identification workflow involves quantifying the similarity of an observed sample spectrum and other features (e.g. retention index) to that of several references, noting the compound of the best-matching reference spectrum as the identified metabolite. While a deluge of similarity metrics exists, none characterize the error rate of generated identifications, thereby presenting an unknown risk of false identification or discovery. To quantify this unknown risk, we propose a model-based framework for estimating the false discovery rate (FDR) among a set of identifications. Extending the traditional mixture modeling framework, our method incorporates both similarity score and experimental information in estimating the FDR. We apply these models to identification lists derived from across 548 samples of varying complexity and sample type (e.g., fungal species, standard mixtures, etc.), comparing their performance to that of the traditional Gaussian mixture model (GMM). Through simulation, we additionally assess the impact of reference library size on the accuracy of FDR estimates. In comparing the best performing model extensions to the GMM, our results indicate relative decreases in median absolute estimation error (MAE) ranging from 12% to 70%, based on comparisons of the median MAEs across all hit-lists. Results indicate that these relative performance improvements generally hold despite library size, however FDR estimation error typically worsens as the set of reference compounds diminishes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2004

Performance of Thermal Mass Flow Meters in a Variable Gravitational Environment

The performance of five thermal mass flow meters, MKS Instruments 179A and 258C, Unit Instruments UFM-8100, Sierra Instruments 830L, and Hastings Instruments HFM-200, were tested on the KC-135 Reduced Gravity Aircraft in orthogonal, coparallel, and counterparallel orientations relative to gravity. Data was taken throughout the parabolic trajectory where the g-level varied from 0.01 to 1.8 times normal gravity. Each meter was calibrated in normal gravity in the orthogonal position prior to flight followed by ground testing at seven different flow conditions to establish a baseline operation. During the tests, the actual flow rate was measured independently using choked-flow orifices. Gravitational acceleration and attitude had a unique effect on the performance of each meter. All meters operated within acceptable limits at all gravity levels in the calibrated orthogonal position. However, when operated in other orientations, the deviations from the reference flow became substantial for several of the flow meters. Data analysis indicated that the greatest source of error was the effect of orientation, followed by the gravity level. This work emphasized that when operating thermal flow meters in a variable gravity environment, it is critical to orient the meter in the same direction relative to gravity in which it was calibrated. Unfortunately, there was no test in normal gravity that could predict the performance of a meter in reduced gravity. When operating in reduced gravity, all meters indicated within 5 percent of the full scale reading at all flow conditions and orientations.

Brooker, John E.↗

NASA NTRS1995

A simple method for verifying the deployment of the TOMS-EP solar arrays

The Total Ozone Mapping Spectrometer-Earth Probe (TOMS-EP) mission relies upon a successful deployment of the spacecraft's solar arrays. Several methods of verification are being employed to ascertain the solar array deployment status, with each requiring differing amounts of data. This paper describes a robust attitude-independent verification method that utilizes telemetry from the coarse Sun sensors (CSS's) and the three-axis magnetometers (TAM's) to determine the solar array deployment status - and it can do so with only a few, not necessarily contiguous, points of data. The method developed assumes that the solar arrays are deployed. Telemetry data from the CSS and TAM are converted to the Sun and magnetic field vectors in spacecraft body coordinates, and the angle between them is calculated. Deployment is indicated if this angle is within a certain error tolerance of the angle between the reference Sun and magnetic field vectors. Although several other methods can indicate a non-deployed state, with this method there is a 70% confidence level in confirming deployment as well as a nearly 100% certainty in confirming a non-deployed state. In addition, the spacecraft attitude (which is not known during the first orbit after launch) is not needed for this algorithm because the angle between the Sun and magnetic field vectors is independent of the spacecraft attitude. This technique can be applied to any spacecraft with a TAM and with CSS's mounted on the solar array(s).

Koppersmith, James R.↗

NASA NTRS1981

Error in Dasibi flight measurements of atmospheric ozone due to instrument wall-loss

Theory suggests that in laminar flow the percent loss of a trace constituent to the walls of a measuring instrument varies as P to the -2/3, where P is the total gas pressure. Preliminary laboratory ozone wall-loss measurements confirm this P to the -2/3 dependence. Accurate assessment of wall-loss is thus of particular importance for those balloon-borne instruments utilizing laminar flow at ambient pressure, since the ambient pressure decreases by a factor of 350 during ascent to 40 km. Measurements and extrapolations made for a Dasibi ozone monitor modified for balloon flight indicate that the wall-loss error at 40 km was between 6 and 30 percent and that the wall-loss error in the derived total ozone column-content for the region from the surface to 40 km altitude was between 2 and 10 percent. At 1000 mb, turbulence caused an order of magnitude increase in the Dasibi wall-loss.

Ainsworth, J. E.↗

NASA NTRS1979

Error in total ozone measurements arising from aerosol attenuation

A generalized least squares method for deducing both total ozone and aerosol extinction spectrum parameters from Dobson spectrophotometer measurements was developed. An error analysis applied to this system indicates that there is little advantage to additional measurements once a sufficient number of line pairs have been employed to solve for the selected detail in the attenuation model. It is shown that when there is a predominance of small particles (less than about 0.35 microns in diameter) the total ozone from the standard AD system is too high by about one percent. When larger particles are present the derived total ozone may be an overestimate or an underestimate but serious errors occur only for narrow polydispersions.

Thomas, R. W. L.↗

NASA NTRS1991

Mars approach navigation using Doppler and range measurements to surface beacons and orbiting spacecraft

Approximate analytical models are developed and used to construct an error covariance analysis for investigating the range of orbit determination accuracies which might be achieved for typical Mars approach trajectories. The sensitivity or orbit determination accuracy to beacon/orbiter position errors and to small spacecraft force modeling errors is also investigated. The results indicate that the orbit determination performance obtained from both Doppler and range data is a strong function of the inclination of the approach trajectory to the Martian equator, for surface beacons, and for orbiters, the inclination relative to the orbital plane. Large variations in performance were also observed for different approach velocity magnitudes; Doppler data in particular were found to perform poorly in determining the downtrack (along the direction of flight) component of spacecraft position. In addition, it was found that small spacecraft acceleration modeling errors can induce large errors in the Doppler-derived downtrack position estimate.

Thurman, Sam W.↗

DOE OSTI2022

Data assimilation for burnup distribution of PWR with three-dimensional variational algorithm and artificial neutral network

In this paper, a data-assimilation method has been proposed and applied for the burnup distribution of PWR. The burnup distribution is significant to the safety and economy of the reactor, as it is essential for the fuel-reloading design and optimization. Due to the burnup distribution cannot be measured directly during the reactor operation, the numerical simulation is widely applied to determine the burnup distribution. However, there is a deviation between the numerical simulation and the actual core due to some unavoidable factors, such as component manufacturing deviation, uneven flow distribution and so on. These differences would induce the errors to the simulation values of power distributions and hence to the burnup distribution. To address this problem, a data-assimilation method for the burnup distribution has been proposed with the application of power-distribution measurements. In our research, the three-dimensional variational (3DVAR) algorithm was applied for burnup-distribution calibration and the artificial neutral network (ANN) was applied to establish the relation between power distribution and corresponding burnup distribution. As engineering verification, the proposed data-assimilation method has been applied to the CNP1000 PWR operated in China. The numerical results indicated that the burnup-distribution errors can be reduced notably, as the maximum value of relative errors for power distribution can be reduced from 5.35% to 3.96%. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1975

Galilean satellite mutual occultation data processing

Results of processing seven mutual occultation lightcurves are presented. The lightcurves were obtained using the 60-in. telescope (152 cm) at Mt. Wilson to observe six J1 occulting J2 events and one J3 occulting J2 event. Using a uniformly illuminated disk model, local satellite Jovicentric longitude corrections of 675 plus or minus 150 km, 275 plus or minus 240 km, and 1175 plus or minus 350 km for J1, J2, and J3, respectively, were determined. These corrections enabled the event midpoint times to be computed to within 5 sec of the observed midpoint times for all seven events. These longitude corrections have been verified by Pioneer 10 and recent (1973 and 1974) conventional Jovian eclipse observations. A relative J1:J2 out-of-plane error of less than a few hundred kilometers has been indicated; however, it appears that the relative J3:J2 out-of-plane error is larger than 600 km. Deficiencies in both the uniformly illuminated disk model and Sampson's theory of the Galilean satellite motions for the reduction of mutual event data are described.

Duxbury, T. C.↗

NASA NTRS1993

On the Effects of a Spacecraft Subcarrier Unbalanced Modulator

This paper presents mathematical models with associated analysis of the deleterious effects which a spacecraft's subcarrier unbalanced modulator has on the performance of a phase-modulated residual carrier communications link. The undesired spectral components produced by the phase and amplitude imbalances in the subcarrier modulator can cause (1) potential interference to the carrier tracking and (2) degradation in the telemetry bit signal-to-noise ratio (SNR). A suitable model for the unbalanced modulator is developed and the threshold levels of undesired components that fall into the carrier tracking loop are determined. The distribution of the carrier phase error caused by the additive White Gaussian noise (AWGN) and undesired component at the residual RF carrier is derived for the limiting cases. Further, this paper analyses the telemetry bit signal-to-noise ratio degradations due to undesirable spectral components as well as the carrier tracking phase error induced by phase and amplitude imbalances. Numerical results which indicate the sensitivity of the carrier tracking loop and the telemetry symbol-error rate (SER) to various parameters of the models are also provided as a tool in the design of the subcarrier balanced modulator.

Nguyen, Tien Manh↗

NASA NTRS1949

The Static-Pressure Error of a Wing Airspeed Installation of the McDonnell XF-88 Airplane in Dives to Transonic Speeds

Measurements were made, in dives to transonic speeds, of the static-pressure position error at a distance of one chord ahead of the McDonnell XF-88 airplane. The airplane incorporates a wing which is swept back 35 deg along the 0.22 chord line and utilizes a 65-series airfoil with a 9-percent-thick section perpendicular to the 0.25-chord line. The section in the stream direction is approximately 8-percent thick. Data up to a Mach number of about 0.97 were obtained within an airplane normal-force-coefficient range from about 0.05 to about 0.68. Data at Mach numbers above about 0.97 were obtained within an airplane normal-force-coefficient range from about 0.05 to about 0.68. Results of the measurements indicate that the static-pressure error, within the accuracy of measurement, is negligible from a Mach number of 0.65 to a Mach number of about 0.97. With a further increase in Mach number, the static-pressure error increases rapidly; at the highest Mach number attained in these tests (about M = 1.038), the error increases to about 8 percent of the impact pressure. Above a Mach number of about 0.975, the recorded Mach number remains substantially constant with increasing true Mach number; the installation is of no value between a Mach number of about 0.975 and at least 1.038, as the true Mach number cannot be obtained from the recorded Mach number in this range. Previously published data have shown that at 0.96 chord ahead of the wing tip of the straight-wing X-l airplanes, a rapid rise of position error started at a Mach number of about 0.8. In the case of the XF-88 airplane, this rise of position error was delayed, presumably by the sweep of the wing, to a Mach number of about 0.97.

Goodman, Harold R.↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRS1991

Experimental study of adaptive pointing and tracking for large flexible space structures

This paper describes an experimental study of adaptive pointing and tracking control for flexible spacecraft conducted on a complex ground experiment facility. The algorithm used in this study is based on a multivariable direct model reference adaptive control law. Several experimental validation studies were performed earlier using this algorithm for vibration damping and robust regulation, with excellent results. The current work extends previous studies by addressing the pointing and tracking problem. As is consistent with an adaptive control framework, the plant is assumed to be poorly known to the extent that only system level knowledge of its dynamics is available. Explicit bounds on the steady-state pointing error are derived as functions of the adaptive controller design parameters. It is shown that good tracking performance can be achieved in an experimental setting by adjusting adaptive controller design weightings according to the guidelines indicated by the analytical expressions for the error.

Boussalis, D.↗

NASA NTRS2020

Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product

The retrieval of optimal aerosol datasets by the synergistic use of hyperspectral ultraviolet(UV)–visible and broadband meteorological imager (MI) techniques was investigated. The Aura Ozone Monitoring Instrument (OMI) Level 1B (L1B) was used as a proxy for hyperspectral UV–visible instrument data to which the Geostationary Environment Monitoring Spectrometer (GEMS) aerosol algorithm was applied. Moderate-Resolution Imaging Spectroradiometer (MODIS) L1B and dark target aerosol Level 2 (L2) data were used with a broadband MI to take advantage of the consistent time gap between the MODIS and the OMI. First, the use of cloud mask information from the MI infrared (IR) channel was tested for synergy. High-spatial-resolution and IR channels of the MI helped mask cirrus and sub-pixel cloud contamination of GEMS aerosol, as clearly seen in aerosol optical depth (AOD) validation with Aerosol Robotic Network (AERONET) data. Second, dust aerosols were distinguished in the GEMS aerosol-type classification algorithm by calculating the total dust confidence index (TDCI) from MODIS L1B IR channels. Statistical analysis indicates that the Probability of Correct Detection (POCD) between the forward and inversion aerosol dust models (DS) was increased from 72% to 94% by use of the TDCI for GEMS aerosol-type classification, and updated aerosol types were then applied to the GEMS algorithm. Use of the TDCI for DS type classification in the GEMS retrieval procedure gave improved single-scattering albedo (SSA) values for absorbing fine pollution particles (BC) and DS aerosols. Aerosol layer height (ALH) retrieved from GEMS was compared with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data, which provides high-resolution vertical aerosol profile information. The CALIOP ALH was calculated from total attenuated backscatter data at 1064 nm, which is identical to the definition of GEMS ALH. Application of the TDCI value reduced the median bias of GEMS ALH data slightly. The GEMS ALH bias approximates zero, especially for GEMS AOD values of>~0.4 and GEMS SSA values of<~0.95.Finally, the AOD products from the GEMS algorithm and MI were used in aerosol merging with the maximum-likelihood estimation method, based on a weighting factor derived from the standard deviation of the original AOD products. With the advantage of the UV–visible channel in retrieving aerosol properties over bright surfaces, the combined AOD products demonstrated better spatial data availability than the original AOD products, with comparable accuracy. Furthermore, pixel-level error analysis of GEMS AOD data indicates improvement through MI synergy.

aerosol↗

NASA NTRS1973

An empirical Bayes approach for the Poisson life distribution.

A smooth empirical Bayes estimator is derived for the intensity parameter (hazard rate) in the Poisson distribution as used in life testing. The reliability function is also estimated either by using the empirical Bayes estimate of the parameter, or by obtaining the expectation of the reliability function. The behavior of the empirical Bayes procedure is studied through Monte Carlo simulation in which estimates of mean-squared errors of the empirical Bayes estimators are compared with those of conventional estimators such as minimum variance unbiased or maximum likelihood. Results indicate a significant reduction in mean-squared error of the empirical Bayes estimators over the conventional variety.

Canavos, G. C.↗

NASA NTRS1991

Software reliability experiments data analysis and investigation

The objectives are to investigate the fundamental reasons which cause independently developed software programs to fail dependently, and to examine fault tolerant software structures which maximize reliability gain in the presence of such dependent failure behavior. The authors used 20 redundant programs from a software reliability experiment to analyze the software errors causing coincident failures, to compare the reliability of N-version and recovery block structures composed of these programs, and to examine the impact of diversity on software reliability using subpopulations of these programs. The results indicate that both conceptually related and unrelated errors can cause coincident failures and that recovery block structures offer more reliability gain than N-version structures if acceptance checks that fail independently from the software components are available. The authors present a theory of general program checkers that have potential application for acceptance tests.

Walker, J. Leslie↗

NASA NTRS1990

Masking of errors in transmission of VAPC-coded speech

A subjective evaluation is provided of the bit error sensitivity of the message elements of a Vector Adaptive Predictive (VAPC) speech coder, along with an indication of the amenability of these elements to a popular error masking strategy (cross frame hold over). As expected, a wide range of bit error sensitivity was observed. The most sensitive message components were the short term spectral information and the most significant bits of the pitch and gain indices. The cross frame hold over strategy was found to be useful for pitch and gain information, but it was not beneficial for the spectral information unless severe corruption had occurred.

Cox, Neil B.↗