Parameter Estimation in Atmospheric Data Sets

NASA Technical Reports Server (NTRS)

Wenig, Mark; Colarco, Peter

2004-01-01

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

District wide water resources investigation and management using LANDSAT data. Phase 1: Lake volume

NASA Technical Reports Server (NTRS)

Shih, S. F. (Principal Investigator)

1982-01-01

A technique for estimating available water storage volume using LANDSAT data was developed and applied to Lake Washington and Lake Harris in central Florida. The technique can be applied two ways. First, where the historical stage records are available, the historical LANDSAT data can be used to establish the relationship between lake volume and lake stage. In the second case, where the historical stage records are not available, the historical LANDSAT data can be used to estimate the historical lake stage after the lake volume and stage information become available in the future.

A Comparison of Two Methods for Estimating Black Hole Spin in Active Galactic Nuclei

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

Capellupo, Daniel M.; Haggard, Daryl; Wafflard-Fernandez, Gaylor, E-mail: danielc@physics.mcgill.ca

Angular momentum, or spin, is a fundamental property of black holes (BHs), yet it is much more difficult to estimate than mass or accretion rate (for actively accreting systems). In recent years, high-quality X-ray observations have allowed for detailed measurements of the Fe K α emission line, where relativistic line broadening allows constraints on the spin parameter (the X-ray reflection method). Another technique uses accretion disk models to fit the AGN continuum emission (the continuum-fitting, or CF, method). Although each technique has model-dependent uncertainties, these are the best empirical tools currently available and should be vetted in systems where bothmore » techniques can be applied. A detailed comparison of the two methods is also useful because neither method can be applied to all AGN. The X-ray reflection technique targets mostly local ( z ≲ 0.1) systems, while the CF method can be applied at higher redshift, up to and beyond the peak of AGN activity and growth. Here, we apply the CF method to two AGN with X-ray reflection measurements. For both the high-mass AGN, H1821+643, and the Seyfert 1, NGC 3783, we find a range in spin parameter consistent with the X-ray reflection measurements. However, the near-maximal spin favored by the reflection method for NGC 3783 is more probable if we add a disk wind to the model. Refinement of these techniques, together with improved X-ray measurements and tighter BH mass constraints, will permit this comparison in a larger sample of AGN and increase our confidence in these spin estimation techniques.« less

Two self-test methods applied to an inertial system problem. [estimating gyroscope and accelerometer bias

NASA Technical Reports Server (NTRS)

Willsky, A. S.; Deyst, J. J.; Crawford, B. S.

1975-01-01

The paper describes two self-test procedures applied to the problem of estimating the biases in accelerometers and gyroscopes on an inertial platform. The first technique is the weighted sum-squared residual (WSSR) test, with which accelerator bias jumps are easily isolated, but gyro bias jumps are difficult to isolate. The WSSR method does not take full advantage of the knowledge of system dynamics. The other technique is a multiple hypothesis method developed by Buxbaum and Haddad (1969). It has the advantage of directly providing jump isolation information, but suffers from computational problems. It might be possible to use the WSSR to detect state jumps and then switch to the BH system for jump isolation and estimate compensation.

Development of the One-Sided Nonlinear Adaptive Doppler Shift Estimation

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.; Singh, Upendra N.; Kavaya, Michael J.; Serror, Judith A.

2009-01-01

The new development of a one-sided nonlinear adaptive shift estimation technique (NADSET) is introduced. The background of the algorithm and a brief overview of NADSET are presented. The new technique is applied to the wind parameter estimates from a 2-micron wavelength coherent Doppler lidar system called VALIDAR located in NASA Langley Research Center in Virginia. The new technique enhances wind parameters such as Doppler shift and power estimates in low Signal-To-Noise-Ratio (SNR) regimes using the estimates in high SNR regimes as the algorithm scans the range bins from low to high altitude. The original NADSET utilizes the statistics in both the lower and the higher range bins to refine the wind parameter estimates in between. The results of the two different approaches of NADSET are compared.

Software for the grouped optimal aggregation technique

NASA Technical Reports Server (NTRS)

Brown, P. M.; Shaw, G. W. (Principal Investigator)

1982-01-01

The grouped optimal aggregation technique produces minimum variance, unbiased estimates of acreage and production for countries, zones (states), or any designated collection of acreage strata. It uses yield predictions, historical acreage information, and direct acreage estimate from satellite data. The acreage strata are grouped in such a way that the ratio model over historical acreage provides a smaller variance than if the model were applied to each individual stratum. An optimal weighting matrix based on historical acreages, provides the link between incomplete direct acreage estimates and the total, current acreage estimate.

Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates

EPA Science Inventory

Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impa...

Comparison of data inversion techniques for remotely sensed wide-angle observations of Earth emitted radiation

NASA Technical Reports Server (NTRS)

Green, R. N.

1981-01-01

The shape factor, parameter estimation, and deconvolution data analysis techniques were applied to the same set of Earth emitted radiation measurements to determine the effects of different techniques on the estimated radiation field. All three techniques are defined and their assumptions, advantages, and disadvantages are discussed. Their results are compared globally, zonally, regionally, and on a spatial spectrum basis. The standard deviations of the regional differences in the derived radiant exitance varied from 7.4 W-m/2 to 13.5 W-m/2.

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Signal-to-noise ratio estimation in digital computer simulation of lowpass and bandpass systems with applications to analog and digital communications, volume 3

NASA Technical Reports Server (NTRS)

Tranter, W. H.; Turner, M. D.

1977-01-01

Techniques are developed to estimate power gain, delay, signal-to-noise ratio, and mean square error in digital computer simulations of lowpass and bandpass systems. The techniques are applied to analog and digital communications. The signal-to-noise ratio estimates are shown to be maximum likelihood estimates in additive white Gaussian noise. The methods are seen to be especially useful for digital communication systems where the mapping from the signal-to-noise ratio to the error probability can be obtained. Simulation results show the techniques developed to be accurate and quite versatile in evaluating the performance of many systems through digital computer simulation.

Optimal Tuner Selection for Kalman Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A linear point design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. This paper derives theoretical Kalman filter estimation error bias and variance values at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the conventional approach of tuner selection. Experimental simulation results are found to be in agreement with theoretical predictions. The new methodology is shown to yield a significant improvement in on-line engine performance estimation accuracy

Evaluation of small area crop estimation techniques using LANDSAT- and ground-derived data. [South Dakota

NASA Technical Reports Server (NTRS)

Amis, M. L.; Martin, M. V.; Mcguire, W. G.; Shen, S. S. (Principal Investigator)

1982-01-01

Studies completed in fiscal year 1981 in support of the clustering/classification and preprocessing activities of the Domestic Crops and Land Cover project. The theme throughout the study was the improvement of subanalysis district (usually county level) crop hectarage estimates, as reflected in the following three objectives: (1) to evaluate the current U.S. Department of Agriculture Statistical Reporting Service regression approach to crop area estimation as applied to the problem of obtaining subanalysis district estimates; (2) to develop and test alternative approaches to subanalysis district estimation; and (3) to develop and test preprocessing techniques for use in improving subanalysis district estimates.

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

NASA Technical Reports Server (NTRS)

Rakoczy, John M.; Herren, Kenneth A.

2008-01-01

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

Space Vehicle Pose Estimation via Optical Correlation and Nonlinear Estimation

NASA Technical Reports Server (NTRS)

Rakoczy, John; Herren, Kenneth

2007-01-01

A technique for 6-degree-of-freedom (6DOF) pose estimation of space vehicles is being developed. This technique draws upon recent developments in implementing optical correlation measurements in a nonlinear estimator, which relates the optical correlation measurements to the pose states (orientation and position). For the optical correlator, the use of both conjugate filters and binary, phase-only filters in the design of synthetic discriminant function (SDF) filters is explored. A static neural network is trained a priori and used as the nonlinear estimator. New commercial animation and image rendering software is exploited to design the SDF filters and to generate a large filter set with which to train the neural network. The technique is applied to pose estimation for rendezvous and docking of free-flying spacecraft and to terrestrial surface mobility systems for NASA's Vision for Space Exploration. Quantitative pose estimation performance will be reported. Advantages and disadvantages of the implementation of this technique are discussed.

How accurately can we estimate energetic costs in a marine top predator, the king penguin?

PubMed

Halsey, Lewis G; Fahlman, Andreas; Handrich, Yves; Schmidt, Alexander; Woakes, Anthony J; Butler, Patrick J

2007-01-01

King penguins (Aptenodytes patagonicus) are one of the greatest consumers of marine resources. However, while their influence on the marine ecosystem is likely to be significant, only an accurate knowledge of their energy demands will indicate their true food requirements. Energy consumption has been estimated for many marine species using the heart rate-rate of oxygen consumption (f(H) - V(O2)) technique, and the technique has been applied successfully to answer eco-physiological questions. However, previous studies on the energetics of king penguins, based on developing or applying this technique, have raised a number of issues about the degree of validity of the technique for this species. These include the predictive validity of the present f(H) - V(O2) equations across different seasons and individuals and during different modes of locomotion. In many cases, these issues also apply to other species for which the f(H) - V(O2) technique has been applied. In the present study, the accuracy of three prediction equations for king penguins was investigated based on validity studies and on estimates of V(O2) from published, field f(H) data. The major conclusions from the present study are: (1) in contrast to that for walking, the f(H) - V(O2) relationship for swimming king penguins is not affected by body mass; (2) prediction equation (1), log(V(O2) = -0.279 + 1.24log(f(H) + 0.0237t - 0.0157log(f(H)t, derived in a previous study, is the most suitable equation presently available for estimating V(O2) in king penguins for all locomotory and nutritional states. A number of possible problems associated with producing an f(H) - V(O2) relationship are discussed in the present study. Finally, a statistical method to include easy-to-measure morphometric characteristics, which may improve the accuracy of f(H) - V(O2) prediction equations, is explained.

Using remote sensing and GIS techniques to estimate discharge and recharge fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Turner, A.K.; ,

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were used to calculate discharge volumes for these area. An empirical method of groundwater recharge estimation was modified to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Phase Retrieval on Undersampled Data from the Thermal Infrared Sensor (TIRS)

NASA Technical Reports Server (NTRS)

Bolcar, Matthew R.; Mentzell, Eric

2011-01-01

Phase retrieval was applied to under-sampled data from a thermal infrared imaging system to estimate defocus across the field of view (FOV). We compare phase retrieval estimated values to those obtained using an independent technique.

An extended stochastic method for seismic hazard estimation

NASA Astrophysics Data System (ADS)

Abd el-aal, A. K.; El-Eraki, M. A.; Mostafa, S. I.

2015-12-01

In this contribution, we developed an extended stochastic technique for seismic hazard assessment purposes. This technique depends on the hypothesis of stochastic technique of Boore (2003) "Simulation of ground motion using the stochastic method. Appl. Geophy. 160:635-676". The essential characteristics of extended stochastic technique are to obtain and simulate ground motion in order to minimize future earthquake consequences. The first step of this technique is defining the seismic sources which mostly affect the study area. Then, the maximum expected magnitude is defined for each of these seismic sources. It is followed by estimating the ground motion using an empirical attenuation relationship. Finally, the site amplification is implemented in calculating the peak ground acceleration (PGA) at each site of interest. We tested and applied this developed technique at Cairo, Suez, Port Said, Ismailia, Zagazig and Damietta cities to predict the ground motion. Also, it is applied at Cairo, Zagazig and Damietta cities to estimate the maximum peak ground acceleration at actual soil conditions. In addition, 0.5, 1, 5, 10 and 20 % damping median response spectra are estimated using the extended stochastic simulation technique. The calculated highest acceleration values at bedrock conditions are found at Suez city with a value of 44 cm s-2. However, these acceleration values decrease towards the north of the study area to reach 14.1 cm s-2 at Damietta city. This comes in agreement with the results of previous studies of seismic hazards in northern Egypt and is found to be comparable. This work can be used for seismic risk mitigation and earthquake engineering purposes.

Classification of wheat: Badhwar profile similarity technique

NASA Technical Reports Server (NTRS)

Austin, W. W.

1980-01-01

The Badwar profile similarity classification technique used successfully for classification of corn was applied to spring wheat classifications. The software programs and the procedures used to generate full-scene classifications are presented, and numerical results of the acreage estimations are given.

A method for nonlinear exponential regression analysis

NASA Technical Reports Server (NTRS)

Junkin, B. G.

1971-01-01

A computer-oriented technique is presented for performing a nonlinear exponential regression analysis on decay-type experimental data. The technique involves the least squares procedure wherein the nonlinear problem is linearized by expansion in a Taylor series. A linear curve fitting procedure for determining the initial nominal estimates for the unknown exponential model parameters is included as an integral part of the technique. A correction matrix was derived and then applied to the nominal estimate to produce an improved set of model parameters. The solution cycle is repeated until some predetermined criterion is satisfied.

Estimation of VOC emissions from produced-water treatment ponds in Uintah Basin oil and gas field using modeling techniques

NASA Astrophysics Data System (ADS)

Tran, H.; Mansfield, M. L.; Lyman, S. N.; O'Neil, T.; Jones, C. P.

2015-12-01

Emissions from produced-water treatment ponds are poorly characterized sources in oil and gas emission inventories that play a critical role in studying elevated winter ozone events in the Uintah Basin, Utah, U.S. Information gaps include un-quantified amounts and compositions of gases emitted from these facilities. The emitted gases are often known as volatile organic compounds (VOCs) which, beside nitrogen oxides (NOX), are major precursors for ozone formation in the near-surface layer. Field measurement campaigns using the flux-chamber technique have been performed to measure VOC emissions from a limited number of produced water ponds in the Uintah Basin of eastern Utah. Although the flux chamber provides accurate measurements at the point of sampling, it covers just a limited area of the ponds and is prone to altering environmental conditions (e.g., temperature, pressure). This fact raises the need to validate flux chamber measurements. In this study, we apply an inverse-dispersion modeling technique with evacuated canister sampling to validate the flux-chamber measurements. This modeling technique applies an initial and arbitrary emission rate to estimate pollutant concentrations at pre-defined receptors, and adjusts the emission rate until the estimated pollutant concentrations approximates measured concentrations at the receptors. The derived emission rates are then compared with flux-chamber measurements and differences are analyzed. Additionally, we investigate the applicability of the WATER9 wastewater emission model for the estimation of VOC emissions from produced-water ponds in the Uintah Basin. WATER9 estimates the emission of each gas based on properties of the gas, its concentration in the waste water, and the characteristics of the influent and treatment units. Results of VOC emission estimations using inverse-dispersion and WATER9 modeling techniques will be reported.

How to apply the optimal estimation method to your lidar measurements for improved retrievals of temperature and composition

NASA Astrophysics Data System (ADS)

Sica, R. J.; Haefele, A.; Jalali, A.; Gamage, S.; Farhani, G.

2018-04-01

The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. The OEM's advantage over traditional techniques includes obtaining a full systematic and random uncertainty budget plus the ability to work with the raw measurements without first applying instrument corrections. In our meeting presentation we will show you how to use the OEM for temperature and composition retrievals for Rayleigh-scatter, Ramanscatter and DIAL lidars.

Techniques for estimating flood hydrographs for ungaged urban watersheds

USGS Publications Warehouse

Stricker, V.A.; Sauer, V.B.

1984-01-01

The Clark Method, modified slightly was used to develop a synthetic, dimensionless hydrograph which can be used to estimate flood hydrographs for ungaged urban watersheds. Application of the technique results in a typical (average) flood hydrograph for a given peak discharge. Input necessary to apply the technique is an estimate of basin lagtime and the recurrence interval peak discharge. Equations for this purpose were obtained from a recent nationwide study on flood frequency in urban watersheds. A regression equation was developed which relates flood volumes to drainage area size, basin lagtime, and peak discharge. This equation is useful where storage of floodwater may be a part of design of flood prevention. (USGS)

Mass balance for on-line alphakLa estimation in activated sludge oxidation ditch.

PubMed

Chatellier, P; Audic, J M

2001-01-01

The capacity of an aeration system to transfer oxygen to a given activated sludge oxidation ditch is characterised by the alphakLa parameter. This parameter is difficult to measure under normal plant working conditions. Usually this measurement involves off-gas techniques or static mass balance. Therefore an on-line technique has been developed and tested in order to evaluate alphakLa. This technique deduces alphakLa from a data analysis of low cost sensor measurement: two flow meters and one oxygen probe. It involves a dynamic mass balance applied to aeration cycles selected according to given criteria. This technique has been applied to a wastewater treatment plant during four years. Significant variations of the alphakLa values have been detected while the number of blowers changes. This technique has been applied to another plant during two months.

Comparisons of Monthly Oceanic Rainfall Derived from TMI and SSM/I

NASA Technical Reports Server (NTRS)

Chang, A. T. C.; Chiu, L. S.; Meng, J.; Wilheit, T. T.; Kummerow, C. D.

1999-01-01

A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to de-emphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.235 GHz brightness temperature histograms. This technique is applied to the SSM/I data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. Six months of rainfall data (January to June 1998) are used in this study. Means and standard deviations are calculated. Paired student t-tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Their differences are discussed in the context of global satellite rainfall estimation.

Optimized tuner selection for engine performance estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

2013-01-01

A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

Estimation of Stratospheric Age Spectrum from Chemical Tracers

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.; Douglass, Anne R.; Polansky, Brian

2005-01-01

We have developed a technique to diagnose the stratospheric age spectrum and estimate the mean age of air using the distributions of at least four constituents with different photochemical lifetimes. We demonstrate that the technique works using a 3D CTM and then apply the technique to UMS CLAES January 1993 observations of CFC11, CFC12, CH4 and N2O. Our results are generally in agreement with mean age of air estimates from the chemical model and from observations of SF6 and CO2; however, the mean age estimates show an intrusion of very young tropical air into the mid-latitude stratosphere. This feature is consistent with mixing of high N20 air out of the tropics during the westerly phase of the QBO.

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

NASA Technical Reports Server (NTRS)

Tilton, J. C.; Swain, P. H. (Principal Investigator); Vardeman, S. B.

1981-01-01

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Comparison on three classification techniques for sex estimation from the bone length of Asian children below 19 years old: an analysis using different group of ages.

PubMed

Darmawan, M F; Yusuf, Suhaila M; Kadir, M R Abdul; Haron, H

2015-02-01

Sex estimation is used in forensic anthropology to assist the identification of individual remains. However, the estimation techniques tend to be unique and applicable only to a certain population. This paper analyzed sex estimation on living individual child below 19 years old using the length of 19 bones of left hand applied for three classification techniques, which were Discriminant Function Analysis (DFA), Support Vector Machine (SVM) and Artificial Neural Network (ANN) multilayer perceptron. These techniques were carried out on X-ray images of the left hand taken from an Asian population data set. All the 19 bones of the left hand were measured using Free Image software, and all the techniques were performed using MATLAB. The group of age "16-19" years old and "7-9" years old were the groups that could be used for sex estimation with as their average of accuracy percentage was above 80%. ANN model was the best classification technique with the highest average of accuracy percentage in the two groups of age compared to other classification techniques. The results show that each classification technique has the best accuracy percentage on each different group of age. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Practical no-gold-standard evaluation framework for quantitative imaging methods: application to lesion segmentation in positron emission tomography

PubMed Central

Jha, Abhinav K.; Mena, Esther; Caffo, Brian; Ashrafinia, Saeed; Rahmim, Arman; Frey, Eric; Subramaniam, Rathan M.

2017-01-01

Abstract. Recently, a class of no-gold-standard (NGS) techniques have been proposed to evaluate quantitative imaging methods using patient data. These techniques provide figures of merit (FoMs) quantifying the precision of the estimated quantitative value without requiring repeated measurements and without requiring a gold standard. However, applying these techniques to patient data presents several practical difficulties including assessing the underlying assumptions, accounting for patient-sampling-related uncertainty, and assessing the reliability of the estimated FoMs. To address these issues, we propose statistical tests that provide confidence in the underlying assumptions and in the reliability of the estimated FoMs. Furthermore, the NGS technique is integrated within a bootstrap-based methodology to account for patient-sampling-related uncertainty. The developed NGS framework was applied to evaluate four methods for segmenting lesions from F-Fluoro-2-deoxyglucose positron emission tomography images of patients with head-and-neck cancer on the task of precisely measuring the metabolic tumor volume. The NGS technique consistently predicted the same segmentation method as the most precise method. The proposed framework provided confidence in these results, even when gold-standard data were not available. The bootstrap-based methodology indicated improved performance of the NGS technique with larger numbers of patient studies, as was expected, and yielded consistent results as long as data from more than 80 lesions were available for the analysis. PMID:28331883

Radar-raingauge data combination techniques: a revision and analysis of their suitability for urban hydrology.

PubMed

Wang, Li-Pen; Ochoa-Rodríguez, Susana; Simões, Nuno Eduardo; Onof, Christian; Maksimović, Cedo

2013-01-01

The applicability of the operational radar and raingauge networks for urban hydrology is insufficient. Radar rainfall estimates provide a good description of the spatiotemporal variability of rainfall; however, their accuracy is in general insufficient. It is therefore necessary to adjust radar measurements using raingauge data, which provide accurate point rainfall information. Several gauge-based radar rainfall adjustment techniques have been developed and mainly applied at coarser spatial and temporal scales; however, their suitability for small-scale urban hydrology is seldom explored. In this paper a review of gauge-based adjustment techniques is first provided. After that, two techniques, respectively based upon the ideas of mean bias reduction and error variance minimisation, were selected and tested using as case study an urban catchment (∼8.65 km(2)) in North-East London. The radar rainfall estimates of four historical events (2010-2012) were adjusted using in situ raingauge estimates and the adjusted rainfall fields were applied to the hydraulic model of the study area. The results show that both techniques can effectively reduce mean bias; however, the technique based upon error variance minimisation can in general better reproduce the spatial and temporal variability of rainfall, which proved to have a significant impact on the subsequent hydraulic outputs. This suggests that error variance minimisation based methods may be more appropriate for urban-scale hydrological applications.

A methodology for treating missing data applied to daily rainfall data in the Candelaro River Basin (Italy).

PubMed

Lo Presti, Rossella; Barca, Emanuele; Passarella, Giuseppe

2010-01-01

Environmental time series are often affected by the "presence" of missing data, but when dealing statistically with data, the need to fill in the gaps estimating the missing values must be considered. At present, a large number of statistical techniques are available to achieve this objective; they range from very simple methods, such as using the sample mean, to very sophisticated ones, such as multiple imputation. A brand new methodology for missing data estimation is proposed, which tries to merge the obvious advantages of the simplest techniques (e.g. their vocation to be easily implemented) with the strength of the newest techniques. The proposed method consists in the application of two consecutive stages: once it has been ascertained that a specific monitoring station is affected by missing data, the "most similar" monitoring stations are identified among neighbouring stations on the basis of a suitable similarity coefficient; in the second stage, a regressive method is applied in order to estimate the missing data. In this paper, four different regressive methods are applied and compared, in order to determine which is the most reliable for filling in the gaps, using rainfall data series measured in the Candelaro River Basin located in South Italy.

Time-reversal imaging for classification of submerged elastic targets via Gibbs sampling and the Relevance Vector Machine.

PubMed

Dasgupta, Nilanjan; Carin, Lawrence

2005-04-01

Time-reversal imaging (TRI) is analogous to matched-field processing, although TRI is typically very wideband and is appropriate for subsequent target classification (in addition to localization). Time-reversal techniques, as applied to acoustic target classification, are highly sensitive to channel mismatch. Hence, it is crucial to estimate the channel parameters before time-reversal imaging is performed. The channel-parameter statistics are estimated here by applying a geoacoustic inversion technique based on Gibbs sampling. The maximum a posteriori (MAP) estimate of the channel parameters are then used to perform time-reversal imaging. Time-reversal implementation requires a fast forward model, implemented here by a normal-mode framework. In addition to imaging, extraction of features from the time-reversed images is explored, with these applied to subsequent target classification. The classification of time-reversed signatures is performed by the relevance vector machine (RVM). The efficacy of the technique is analyzed on simulated in-channel data generated by a free-field finite element method (FEM) code, in conjunction with a channel propagation model, wherein the final classification performance is demonstrated to be relatively insensitive to the associated channel parameters. The underlying theory of Gibbs sampling and TRI are presented along with the feature extraction and target classification via the RVM.

Kalman filter estimation of human pilot-model parameters

NASA Technical Reports Server (NTRS)

Schiess, J. R.; Roland, V. R.

1975-01-01

The parameters of a human pilot-model transfer function are estimated by applying the extended Kalman filter to the corresponding retarded differential-difference equations in the time domain. Use of computer-generated data indicates that most of the parameters, including the implicit time delay, may be reasonably estimated in this way. When applied to two sets of experimental data obtained from a closed-loop tracking task performed by a human, the Kalman filter generated diverging residuals for one of the measurement types, apparently because of model assumption errors. Application of a modified adaptive technique was found to overcome the divergence and to produce reasonable estimates of most of the parameters.

Simple and accurate methods for quantifying deformation, disruption, and development in biological tissues

PubMed Central

Boyle, John J.; Kume, Maiko; Wyczalkowski, Matthew A.; Taber, Larry A.; Pless, Robert B.; Xia, Younan; Genin, Guy M.; Thomopoulos, Stavros

2014-01-01

When mechanical factors underlie growth, development, disease or healing, they often function through local regions of tissue where deformation is highly concentrated. Current optical techniques to estimate deformation can lack precision and accuracy in such regions due to challenges in distinguishing a region of concentrated deformation from an error in displacement tracking. Here, we present a simple and general technique for improving the accuracy and precision of strain estimation and an associated technique for distinguishing a concentrated deformation from a tracking error. The strain estimation technique improves accuracy relative to other state-of-the-art algorithms by directly estimating strain fields without first estimating displacements, resulting in a very simple method and low computational cost. The technique for identifying local elevation of strain enables for the first time the successful identification of the onset and consequences of local strain concentrating features such as cracks and tears in a highly strained tissue. We apply these new techniques to demonstrate a novel hypothesis in prenatal wound healing. More generally, the analytical methods we have developed provide a simple tool for quantifying the appearance and magnitude of localized deformation from a series of digital images across a broad range of disciplines. PMID:25165601

EVALUATION OF ALTERNATIVE GAUSSIAN PLUME DISPERSION MODELING TECHNIQUES IN ESTIMATING SHORT-TERM SULFUR DIOXIDE CONCENTRATIONS

EPA Science Inventory

A routinely applied atmospheric dispersion model was modified to evaluate alternative modeling techniques which allowed for more detailed source data, onsite meteorological data, and several dispersion methodologies. These were evaluated with hourly SO2 concentrations measured at...

Local regression type methods applied to the study of geophysics and high frequency financial data

NASA Astrophysics Data System (ADS)

Mariani, M. C.; Basu, K.

2014-09-01

In this work we applied locally weighted scatterplot smoothing techniques (Lowess/Loess) to Geophysical and high frequency financial data. We first analyze and apply this technique to the California earthquake geological data. A spatial analysis was performed to show that the estimation of the earthquake magnitude at a fixed location is very accurate up to the relative error of 0.01%. We also applied the same method to a high frequency data set arising in the financial sector and obtained similar satisfactory results. The application of this approach to the two different data sets demonstrates that the overall method is accurate and efficient, and the Lowess approach is much more desirable than the Loess method. The previous works studied the time series analysis; in this paper our local regression models perform a spatial analysis for the geophysics data providing different information. For the high frequency data, our models estimate the curve of best fit where data are dependent on time.

Development and application of the maximum entropy method and other spectral estimation techniques

NASA Astrophysics Data System (ADS)

King, W. R.

1980-09-01

This summary report is a collection of four separate progress reports prepared under three contracts, which are all sponsored by the Office of Naval Research in Arlington, Virginia. This report contains the results of investigations into the application of the maximum entropy method (MEM), a high resolution, frequency and wavenumber estimation technique. The report also contains a description of two, new, stable, high resolution spectral estimation techniques that is provided in the final report section. Many examples of wavenumber spectral patterns for all investigated techniques are included throughout the report. The maximum entropy method is also known as the maximum entropy spectral analysis (MESA) technique, and both names are used in the report. Many MEM wavenumber spectral patterns are demonstrated using both simulated and measured radar signal and noise data. Methods for obtaining stable MEM wavenumber spectra are discussed, broadband signal detection using the MEM prediction error transform (PET) is discussed, and Doppler radar narrowband signal detection is demonstrated using the MEM technique. It is also shown that MEM cannot be applied to randomly sampled data. The two new, stable, high resolution, spectral estimation techniques discussed in the final report section, are named the Wiener-King and the Fourier spectral estimation techniques. The two new techniques have a similar derivation based upon the Wiener prediction filter, but the two techniques are otherwise quite different. Further development of the techniques and measurement of the technique spectral characteristics is recommended for subsequent investigation.

Parameter estimation using meta-heuristics in systems biology: a comprehensive review.

PubMed

Sun, Jianyong; Garibaldi, Jonathan M; Hodgman, Charlie

2012-01-01

This paper gives a comprehensive review of the application of meta-heuristics to optimization problems in systems biology, mainly focussing on the parameter estimation problem (also called the inverse problem or model calibration). It is intended for either the system biologist who wishes to learn more about the various optimization techniques available and/or the meta-heuristic optimizer who is interested in applying such techniques to problems in systems biology. First, the parameter estimation problems emerging from different areas of systems biology are described from the point of view of machine learning. Brief descriptions of various meta-heuristics developed for these problems follow, along with outlines of their advantages and disadvantages. Several important issues in applying meta-heuristics to the systems biology modelling problem are addressed, including the reliability and identifiability of model parameters, optimal design of experiments, and so on. Finally, we highlight some possible future research directions in this field.

System Identification Applied to Dynamic CFD Simulation and Wind Tunnel Data

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.; Vicroy, Dan D.

2011-01-01

Demanding aerodynamic modeling requirements for military and civilian aircraft have provided impetus for researchers to improve computational and experimental techniques. Model validation is a key component for these research endeavors so this study is an initial effort to extend conventional time history comparisons by comparing model parameter estimates and their standard errors using system identification methods. An aerodynamic model of an aircraft performing one-degree-of-freedom roll oscillatory motion about its body axes is developed. The model includes linear aerodynamics and deficiency function parameters characterizing an unsteady effect. For estimation of unknown parameters two techniques, harmonic analysis and two-step linear regression, were applied to roll-oscillatory wind tunnel data and to computational fluid dynamics (CFD) simulated data. The model used for this study is a highly swept wing unmanned aerial combat vehicle. Differences in response prediction, parameters estimates, and standard errors are compared and discussed

Direction of Arrival Estimation with a Novel Single-Port Smart Antenna

NASA Astrophysics Data System (ADS)

Sun, Chen; Karmakar, Nemai C.

2004-12-01

A novel direction of arrival (DOA) estimation technique that uses the conventional multiple-signal classification (MUSIC) algorithm with periodic signals is applied to a single-port smart antenna. Results show that the proposed method gives a high-resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only 1 analogue-to-digital converter (ADC) is used in this antenna, which features low power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling among antenna elements. Therefore, it offers an economical way to extensively implement smart antennas into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals such as laptops in wireless networks.

Independent Assessment of ITRF Site Velocities using GPS Imaging

NASA Astrophysics Data System (ADS)

Blewitt, G.; Hammond, W. C.; Kreemer, C.; Altamimi, Z.

2015-12-01

The long-term stability of ITRF is critical to the most challenging scientific applications such as the slow variation of sea level, and of ice sheet loading in Greenland and Antarctica. In 2010, the National Research Council recommended aiming for stability at the level of 1 mm/decade in the ITRF origin and scale. This requires that the ITRF include many globally-distributed sites with motions that are predictable to within a few mm/decade, with a significant number of sites having collocated stations of multiple techniques. Quantifying the stability of ITRF stations can be useful to understand stability of ITRF parameters, and to help the selection and weighting of ITRF stations. Here we apply a new suite of techniques for an independent assessment of ITRF site velocities. Our "GPS Imaging" suite is founded on the principle that, for the case of large numbers of data, the trend can be estimated objectively, automatically, robustly, and accurately by applying non-parametric techniques, which use quantile statistics (e.g., the median). At the foundation of GPS Imaging is the estimator "MIDAS" (Median Interannual Difference Adjusted for Skewness). MIDAS estimates the velocity with a realistic error bar based on sub-sampling the coordinate time series. MIDAS is robust to step discontinuities, outliers, seasonality, and heteroscedasticity. Common-mode noise filters enhance regional- to continental-scale precision in MIDAS estimates, just as they do for standard estimation techniques. Secondly, in regions where there is sufficient spatial sampling, GPS Imaging uses MIDAS velocity estimates to generate a regionally-representative velocity map. For this we apply a median spatial filter to despeckle the maps. We use GPS Imaging to address two questions: (1) How well do the ITRF site velocities derived by parametric estimation agree with non-parametric techniques? (2) Are ITRF site velocities regionally representative? These questions aim to get a handle on (1) the accuracy of ITRF site velocities as a function of characteristics of contributing station data, such as number of step parameters and total time span; and (2) evidence of local processes affecting site velocity, which may impact site stability. Such quantification can be used to rank stations in terms the risk that they may pose to the stability of ITRF.

Ship Speed Retrieval From Single Channel TerraSAR-X Data

NASA Astrophysics Data System (ADS)

Soccorsi, Matteo; Lehner, Susanne

2010-04-01

A method to estimate the speed of a moving ship is presented. The technique, introduced in Kirscht (1998), is extended to marine application and validated on TerraSAR-X High-Resolution (HR) data. The generation of a sequence of single-look SAR images from a single- channel image corresponds to an image time series with reduced resolution. This allows applying change detection techniques on the time series to evaluate the velocity components in range and azimuth of the ship. The evaluation of the displacement vector of a moving target in consecutive images of the sequence allows the estimation of the azimuth velocity component. The range velocity component is estimated by evaluating the variation of the signal amplitude during the sequence. In order to apply the technique on TerraSAR-X Spot Light (SL) data a further processing step is needed. The phase has to be corrected as presented in Eineder et al. (2009) due to the SL acquisition mode; otherwise the image sequence cannot be generated. The analysis, when possible validated by the Automatic Identification System (AIS), was performed in the framework of the ESA project MARISS.

A dynamic mechanical analysis technique for porous media

PubMed Central

Pattison, Adam J; McGarry, Matthew; Weaver, John B; Paulsen, Keith D

2015-01-01

Dynamic mechanical analysis (DMA) is a common way to measure the mechanical properties of materials as functions of frequency. Traditionally, a viscoelastic mechanical model is applied and current DMA techniques fit an analytical approximation to measured dynamic motion data by neglecting inertial forces and adding empirical correction factors to account for transverse boundary displacements. Here, a finite element (FE) approach to processing DMA data was developed to estimate poroelastic material properties. Frequency-dependent inertial forces, which are significant in soft media and often neglected in DMA, were included in the FE model. The technique applies a constitutive relation to the DMA measurements and exploits a non-linear inversion to estimate the material properties in the model that best fit the model response to the DMA data. A viscoelastic version of this approach was developed to validate the approach by comparing complex modulus estimates to the direct DMA results. Both analytical and FE poroelastic models were also developed to explore their behavior in the DMA testing environment. All of the models were applied to tofu as a representative soft poroelastic material that is a common phantom in elastography imaging studies. Five samples of three different stiffnesses were tested from 1 – 14 Hz with rough platens placed on the top and bottom surfaces of the material specimen under test to restrict transverse displacements and promote fluid-solid interaction. The viscoelastic models were identical in the static case, and nearly the same at frequency with inertial forces accounting for some of the discrepancy. The poroelastic analytical method was not sufficient when the relevant physical boundary constraints were applied, whereas the poroelastic FE approach produced high quality estimates of shear modulus and hydraulic conductivity. These results illustrated appropriate shear modulus contrast between tofu samples and yielded a consistent contrast in hydraulic conductivity as well. PMID:25248170

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

Estimation of reliability and dynamic property for polymeric material at high strain rate using SHPB technique and probability theory

NASA Astrophysics Data System (ADS)

Kim, Dong Hyeok; Lee, Ouk Sub; Kim, Hong Min; Choi, Hye Bin

2008-11-01

A modified Split Hopkinson Pressure Bar technique with aluminum pressure bars and a pulse shaper technique to achieve a closer impedance match between the pressure bars and the specimen materials such as hot temperature degraded POM (Poly Oxy Methylene) and PP (Poly Propylene). The more distinguishable experimental signals were obtained to evaluate the more accurate dynamic deformation behavior of materials under a high strain rate loading condition. A pulse shaping technique is introduced to reduce the non-equilibrium on the dynamic material response by modulation of the incident wave during a short period of test. This increases the rise time of the incident pulse in the SHPB experiment. For the dynamic stress strain curve obtained from SHPB experiment, the Johnson-Cook model is applied as a constitutive equation. The applicability of this constitutive equation is verified by using the probabilistic reliability estimation method. Two reliability methodologies such as the FORM and the SORM have been proposed. The limit state function(LSF) includes the Johnson-Cook model and applied stresses. The LSF in this study allows more statistical flexibility on the yield stress than a paper published before. It is found that the failure probability estimated by using the SORM is more reliable than those of the FORM/ It is also noted that the failure probability increases with increase of the applied stress. Moreover, it is also found that the parameters of Johnson-Cook model such as A and n, and the applied stress are found to affect the failure probability more severely than the other random variables according to the sensitivity analysis.

Estimating source parameters from deformation data, with an application to the March 1997 earthquake swarm off the Izu Peninsula, Japan

NASA Astrophysics Data System (ADS)

Cervelli, P.; Murray, M. H.; Segall, P.; Aoki, Y.; Kato, T.

2001-06-01

We have applied two Monte Carlo optimization techniques, simulated annealing and random cost, to the inversion of deformation data for fault and magma chamber geometry. These techniques involve an element of randomness that permits them to escape local minima and ultimately converge to the global minimum of misfit space. We have tested the Monte Carlo algorithms on two synthetic data sets. We have also compared them to one another in terms of their efficiency and reliability. We have applied the bootstrap method to estimate confidence intervals for the source parameters, including the correlations inherent in the data. Additionally, we present methods that use the information from the bootstrapping procedure to visualize the correlations between the different model parameters. We have applied these techniques to GPS, tilt, and leveling data from the March 1997 earthquake swarm off of the Izu Peninsula, Japan. Using the two Monte Carlo algorithms, we have inferred two sources, a dike and a fault, that fit the deformation data and the patterns of seismicity and that are consistent with the regional stress field.

Modeling river total bed material load discharge using artificial intelligence approaches (based on conceptual inputs)

NASA Astrophysics Data System (ADS)

Roushangar, Kiyoumars; Mehrabani, Fatemeh Vojoudi; Shiri, Jalal

2014-06-01

This study presents Artificial Intelligence (AI)-based modeling of total bed material load through developing the accuracy level of the predictions of traditional models. Gene expression programming (GEP) and adaptive neuro-fuzzy inference system (ANFIS)-based models were developed and validated for estimations. Sediment data from Qotur River (Northwestern Iran) were used for developing and validation of the applied techniques. In order to assess the applied techniques in relation to traditional models, stream power-based and shear stress-based physical models were also applied in the studied case. The obtained results reveal that developed AI-based models using minimum number of dominant factors, give more accurate results than the other applied models. Nonetheless, it was revealed that k-fold test is a practical but high-cost technique for complete scanning of applied data and avoiding the over-fitting.

Handwritten document age classification based on handwriting styles

NASA Astrophysics Data System (ADS)

Ramaiah, Chetan; Kumar, Gaurav; Govindaraju, Venu

2012-01-01

Handwriting styles are constantly changing over time. We approach the novel problem of estimating the approximate age of Historical Handwritten Documents using Handwriting styles. This system will have many applications in handwritten document processing engines where specialized processing techniques can be applied based on the estimated age of the document. We propose to learn a distribution over styles across centuries using Topic Models and to apply a classifier over weights learned in order to estimate the approximate age of the documents. We present a comparison of different distance metrics such as Euclidean Distance and Hellinger Distance within this application.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.

2002-01-01

The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR-based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

RESULTS OF COMPUTATIONS MADE FOR DASA-USNRDL FALLOUT SYMPOSIUM

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

Read, R.; Wagner, L.; Moorehead, E.

1962-11-01

The regression techniques introduced by the Civil Defense Research Project for estimating fallout particle deposition coordinates, their standard ellipses, and isointensity contours have been applied to some of the homework problems assigned for the DASA-USNRDL Fallout Symposium. The results are reported and the estimates are contrasted with estimates based on the assumption that winds are invariant with time. (auth).

Using small area estimation and Lidar-derived variables for multivariate prediction of forest attributes

Treesearch

F. Mauro; Vicente Monleon; H. Temesgen

2015-01-01

Small area estimation (SAE) techniques have been successfully applied in forest inventories to provide reliable estimates for domains where the sample size is small (i.e. small areas). Previous studies have explored the use of either Area Level or Unit Level Empirical Best Linear Unbiased Predictors (EBLUPs) in a univariate framework, modeling each variable of interest...

Establishment of a center of excellence for applied mathematical and statistical research

NASA Technical Reports Server (NTRS)

Woodward, W. A.; Gray, H. L.

1983-01-01

The state of the art was assessed with regards to efforts in support of the crop production estimation problem and alternative generic proportion estimation techniques were investigated. Topics covered include modeling the greeness profile (Badhwarmos model), parameter estimation using mixture models such as CLASSY, and minimum distance estimation as an alternative to maximum likelihood estimation. Approaches to the problem of obtaining proportion estimates when the underlying distributions are asymmetric are examined including the properties of Weibull distribution.

Using remote sensing and GIS techniques to estimate discharge and recharge. fluxes for the Death Valley regional groundwater flow system, USA

USGS Publications Warehouse

D'Agnese, F. A.; Faunt, C.C.; Keith, Turner A.

1996-01-01

The recharge and discharge components of the Death Valley regional groundwater flow system were defined by remote sensing and GIS techniques that integrated disparate data types to develop a spatially complex representation of near-surface hydrological processes. Image classification methods were applied to multispectral satellite data to produce a vegetation map. This map provided a basis for subsequent evapotranspiration and infiltration estimations. The vegetation map was combined with ancillary data in a GIS to delineate different types of wetlands, phreatophytes and wet playa areas. Existing evapotranspiration-rate estimates were then used to calculate discharge volumes for these areas. A previously used empirical method of groundwater recharge estimation was modified by GIS methods to incorporate data describing soil-moisture conditions, and a recharge potential map was produced. These discharge and recharge maps were readily converted to data arrays for numerical modelling codes. Inverse parameter estimation techniques also used these data to evaluate the reliability and sensitivity of estimated values.

Estimation of some transducer parameters in a broadband piezoelectric transmitter by using an artificial intelligence technique.

PubMed

Ruíz, A; Ramos, A; San Emeterio, J L

2004-04-01

An estimation procedure to efficiently find approximate values of internal parameters in ultrasonic transducers intended for broadband operation would be a valuable tool to discover internal construction data. This information is necessary in the modelling and simulation of acoustic and electrical behaviour related to ultrasonic systems containing commercial transducers. There is not a general solution for this generic problem of parameter estimation in the case of broadband piezoelectric probes. In this paper, this general problem is briefly analysed for broadband conditions. The viability of application in this field of an artificial intelligence technique supported on the modelling of the transducer internal components is studied. A genetic algorithm (GA) procedure is presented and applied to the estimation of different parameters, related to two transducers which are working as pulsed transmitters. The efficiency of this GA technique is studied, considering the influence of the number and variation range of the estimated parameters. Estimation results are experimentally ratified.

Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area

NASA Astrophysics Data System (ADS)

Arai, Hiroyuki; Miyagawa, Isao; Koike, Hideki; Haseyama, Miki

We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.

Considerations in cross-validation type density smoothing with a look at some data

NASA Technical Reports Server (NTRS)

Schuster, E. F.

1982-01-01

Experience gained in applying nonparametric maximum likelihood techniques of density estimation to judge the comparative quality of various estimators is reported. Two invariate data sets of one hundered samples (one Cauchy, one natural normal) are considered as well as studies in the multivariate case.

Preliminary statistical studies concerning the Campos RJ sugar cane area, using LANDSAT imagery and aerial photographs

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Costa, S. R. X.; Paiao, L. B. F.; Mendonca, F. J.; Shimabukuro, Y. E.; Duarte, V.

1983-01-01

The two phase sampling technique was applied to estimate the area cultivated with sugar cane in an approximately 984 sq km pilot region of Campos. Correlation between existing aerial photography and LANDSAT data was used. The two phase sampling technique corresponded to 99.6% of the results obtained by aerial photography, taken as ground truth. This estimate has a standard deviation of 225 ha, which constitutes a coefficient of variation of 0.6%.

New Flutter Analysis Technique for Time-Domain Computational Aeroelasticity

NASA Technical Reports Server (NTRS)

Pak, Chan-Gi; Lung, Shun-Fat

2017-01-01

A new time-domain approach for computing flutter speed is presented. Based on the time-history result of aeroelastic simulation, the unknown unsteady aerodynamics model is estimated using a system identification technique. The full aeroelastic model is generated via coupling the estimated unsteady aerodynamic model with the known linear structure model. The critical dynamic pressure is computed and used in the subsequent simulation until the convergence of the critical dynamic pressure is achieved. The proposed method is applied to a benchmark cantilevered rectangular wing.

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

NASA Technical Reports Server (NTRS)

Negri, A. J.; Xu, L.; Adler, R. F.; Einaudi, Franco (Technical Monitor)

2000-01-01

The development of a satellite infrared technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall in Amazonia are presented. The Convective-Stratiform. Technique, calibrated by coincident, physically retrieved rain rates from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI), is applied during January to April 1999 over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. Results compare well (a one-hour lag) with the diurnal cycle derived from Tropical Ocean-Global Atmosphere (TOGA) radar-estimated rainfall in Rondonia. The satellite estimates reveal that the convective rain constitutes, in the mean, 24% of the rain area while accounting for 67% of the rain volume. The effects of geography (rivers, lakes, coasts) and topography on the diurnal cycle of convection are examined. In particular, the Amazon River, downstream of Manaus, is shown to both enhance early morning rainfall and inhibit afternoon convection. Monthly estimates from this technique, dubbed CST/TMI, are verified over a dense rain gage network in the state of Ceara, in northeast Brazil. The CST/TMI showed a high bias equal to +33% of the gage mean, indicating that possibly the TMI estimates alone are also high. The root mean square difference (after removal of the bias) equaled 36.6% of the gage mean. The correlation coefficient was 0.77 based on 72 station-months.

Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2011-01-01

An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.

Assessing sequential data assimilation techniques for integrating GRACE data into a hydrological model

NASA Astrophysics Data System (ADS)

Khaki, M.; Hoteit, I.; Kuhn, M.; Awange, J.; Forootan, E.; van Dijk, A. I. J. M.; Schumacher, M.; Pattiaratchi, C.

2017-09-01

The time-variable terrestrial water storage (TWS) products from the Gravity Recovery And Climate Experiment (GRACE) have been increasingly used in recent years to improve the simulation of hydrological models by applying data assimilation techniques. In this study, for the first time, we assess the performance of the most popular data assimilation sequential techniques for integrating GRACE TWS into the World-Wide Water Resources Assessment (W3RA) model. We implement and test stochastic and deterministic ensemble-based Kalman filters (EnKF), as well as Particle filters (PF) using two different resampling approaches of Multinomial Resampling and Systematic Resampling. These choices provide various opportunities for weighting observations and model simulations during the assimilation and also accounting for error distributions. Particularly, the deterministic EnKF is tested to avoid perturbing observations before assimilation (that is the case in an ordinary EnKF). Gaussian-based random updates in the EnKF approaches likely do not fully represent the statistical properties of the model simulations and TWS observations. Therefore, the fully non-Gaussian PF is also applied to estimate more realistic updates. Monthly GRACE TWS are assimilated into W3RA covering the entire Australia. To evaluate the filters performances and analyze their impact on model simulations, their estimates are validated by independent in-situ measurements. Our results indicate that all implemented filters improve the estimation of water storage simulations of W3RA. The best results are obtained using two versions of deterministic EnKF, i.e. the Square Root Analysis (SQRA) scheme and the Ensemble Square Root Filter (EnSRF), respectively, improving the model groundwater estimations errors by 34% and 31% compared to a model run without assimilation. Applying the PF along with Systematic Resampling successfully decreases the model estimation error by 23%.

Improved Pulse Wave Velocity Estimation Using an Arterial Tube-Load Model

PubMed Central

Gao, Mingwu; Zhang, Guanqun; Olivier, N. Bari; Mukkamala, Ramakrishna

2015-01-01

Pulse wave velocity (PWV) is the most important index of arterial stiffness. It is conventionally estimated by non-invasively measuring central and peripheral blood pressure (BP) and/or velocity (BV) waveforms and then detecting the foot-to-foot time delay between the waveforms wherein wave reflection is presumed absent. We developed techniques for improved estimation of PWV from the same waveforms. The techniques effectively estimate PWV from the entire waveforms, rather than just their feet, by mathematically eliminating the reflected wave via an arterial tube-load model. In this way, the techniques may be more robust to artifact while revealing the true PWV in absence of wave reflection. We applied the techniques to estimate aortic PWV from simultaneously and sequentially measured central and peripheral BP waveforms and simultaneously measured central BV and peripheral BP waveforms from 17 anesthetized animals during diverse interventions that perturbed BP widely. Since BP is the major acute determinant of aortic PWV, especially under anesthesia wherein vasomotor tone changes are minimal, we evaluated the techniques in terms of the ability of their PWV estimates to track the acute BP changes in each subject. Overall, the PWV estimates of the techniques tracked the BP changes better than those of the conventional technique (e.g., diastolic BP root-mean-squared-errors of 3.4 vs. 5.2 mmHg for the simultaneous BP waveforms and 7.0 vs. 12.2 mmHg for the BV and BP waveforms (p < 0.02)). With further testing, the arterial tube-load model-based PWV estimation techniques may afford more accurate arterial stiffness monitoring in hypertensive and other patients. PMID:24263016

The Comparison of Matching Methods Using Different Measures of Balance: Benefits and Risks Exemplified within a Study to Evaluate the Effects of German Disease Management Programs on Long-Term Outcomes of Patients with Type 2 Diabetes.

PubMed

Fullerton, Birgit; Pöhlmann, Boris; Krohn, Robert; Adams, John L; Gerlach, Ferdinand M; Erler, Antje

2016-10-01

To present a case study on how to compare various matching methods applying different measures of balance and to point out some pitfalls involved in relying on such measures. Administrative claims data from a German statutory health insurance fund covering the years 2004-2008. We applied three different covariance balance diagnostics to a choice of 12 different matching methods used to evaluate the effectiveness of the German disease management program for type 2 diabetes (DMPDM2). We further compared the effect estimates resulting from applying these different matching techniques in the evaluation of the DMPDM2. The choice of balance measure leads to different results on the performance of the applied matching methods. Exact matching methods performed well across all measures of balance, but resulted in the exclusion of many observations, leading to a change of the baseline characteristics of the study sample and also the effect estimate of the DMPDM2. All PS-based methods showed similar effect estimates. Applying a higher matching ratio and using a larger variable set generally resulted in better balance. Using a generalized boosted instead of a logistic regression model showed slightly better performance for balance diagnostics taking into account imbalances at higher moments. Best practice should include the application of several matching methods and thorough balance diagnostics. Applying matching techniques can provide a useful preprocessing step to reveal areas of the data that lack common support. The use of different balance diagnostics can be helpful for the interpretation of different effect estimates found with different matching methods. © Health Research and Educational Trust.

Coupling Computer-Aided Process Simulation and ...

EPA Pesticide Factsheets

A methodology is described for developing a gate-to-gate life cycle inventory (LCI) of a chemical manufacturing process to support the application of life cycle assessment in the design and regulation of sustainable chemicals. The inventories were derived by first applying process design and simulation of develop a process flow diagram describing the energy and basic material flows of the system. Additional techniques developed by the U.S. Environmental Protection Agency for estimating uncontrolled emissions from chemical processing equipment were then applied to obtain a detailed emission profile for the process. Finally, land use for the process was estimated using a simple sizing model. The methodology was applied to a case study of acetic acid production based on the Cativa tm process. The results reveal improvements in the qualitative LCI for acetic acid production compared to commonly used databases and top-down methodologies. The modeling techniques improve the quantitative LCI results for inputs and uncontrolled emissions. With provisions for applying appropriate emission controls, the proposed method can provide an estimate of the LCI that can be used for subsequent life cycle assessments. As part of its mission, the Agency is tasked with overseeing the use of chemicals in commerce. This can include consideration of a chemical's potential impact on health and safety, resource conservation, clean air and climate change, clean water, and sustainable

Estimating the robustness of contingenet valuation estimates of WTP to survey mode and treatment of protest responses.

Treesearch

John Loomis; Armando Gonzalez-Caban; Joseph Champ

2011-01-01

Over the past four decades teh contingent valuation method (CVM) has become a technique frequently used by economists to estimate willingness-to-pay (WTP) for improvements in environmental quality and prot3tion of natural resources. The CVM was originall applied to estmate recreation use values (Davis, 1963; Hammack and Brown, 1974)and air quality (Brookshire et al....

Nowcasting Cloud Fields for U.S. Air Force Special Operations

DTIC Science & Technology

2017-03-01

application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES

Estimating representative background PM2.5 concentration in heavily polluted areas using baseline separation technique and chemical mass balance model

NASA Astrophysics Data System (ADS)

Gao, Shuang; Yang, Wen; Zhang, Hui; Sun, Yanling; Mao, Jian; Ma, Zhenxing; Cong, Zhiyuan; Zhang, Xian; Tian, Shasha; Azzi, Merched; Chen, Li; Bai, Zhipeng

2018-02-01

The determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 ± 2) μg/m3 for the whole year, (34 ± 4) μg/m3 for the heating period (winter), (21 ± 2) μg/m3 for the non-heating period (summer), and (25 ± 2) μg/m3 for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 ± 3) μg/m3, (40 ± 4) μg/m3, (24 ± 5) μg/m3, and (26 ± 2) μg/m3, respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants.

Signal-to-noise ratio estimation using adaptive tuning on the piecewise cubic Hermite interpolation model for images.

PubMed

Sim, K S; Yeap, Z X; Tso, C P

2016-11-01

An improvement to the existing technique of quantifying signal-to-noise ratio (SNR) of scanning electron microscope (SEM) images using piecewise cubic Hermite interpolation (PCHIP) technique is proposed. The new technique uses an adaptive tuning onto the PCHIP, and is thus named as ATPCHIP. To test its accuracy, 70 images are corrupted with noise and their autocorrelation functions are then plotted. The ATPCHIP technique is applied to estimate the uncorrupted noise-free zero offset point from a corrupted image. Three existing methods, the nearest neighborhood, first order interpolation and original PCHIP, are used to compare with the performance of the proposed ATPCHIP method, with respect to their calculated SNR values. Results show that ATPCHIP is an accurate and reliable method to estimate SNR values from SEM images. SCANNING 38:502-514, 2016. © 2015 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

The area-time-integral technique to estimate convective rain volumes over areas applied to satellite data - A preliminary investigation

NASA Technical Reports Server (NTRS)

Doneaud, Andre A.; Miller, James R., Jr.; Johnson, L. Ronald; Vonder Haar, Thomas H.; Laybe, Patrick

1987-01-01

The use of the area-time-integral (ATI) technique, based only on satellite data, to estimate convective rain volume over a moving target is examined. The technique is based on the correlation between the radar echo area coverage integrated over the lifetime of the storm and the radar estimated rain volume. The processing of the GOES and radar data collected in 1981 is described. The radar and satellite parameters for six convective clusters from storm events occurring on June 12 and July 2, 1981 are analyzed and compared in terms of time steps and cluster lifetimes. Rain volume is calculated by first using the regression analysis to generate the regression equation used to obtain the ATI; the ATI versus rain volume relation is then employed to compute rain volume. The data reveal that the ATI technique using satellite data is applicable to the calculation of rain volume.

Wavelet Analyses of Oil Prices, USD Variations and Impact on Logistics

NASA Astrophysics Data System (ADS)

Melek, M.; Tokgozlu, A.; Aslan, Z.

2009-07-01

This paper is related with temporal variations of historical oil prices and Dollar and Euro in Turkey. Daily data based on OECD and Central Bank of Turkey records beginning from 1946 has been considered. 1D-continuous wavelets and wavelet packets analysis techniques have been applied on data. Wavelet techniques help to detect abrupt changing's, increasing and decreasing trends of data. Estimation of variables has been presented by using linear regression estimation techniques. The results of this study have been compared with the small and large scale effects. Transportation costs of track show a similar variation with fuel prices. The second part of the paper is related with estimation of imports, exports, costs, total number of vehicles and annual variations by considering temporal variation of oil prices and Dollar currency in Turkey. Wavelet techniques offer a user friendly methodology to interpret some local effects on increasing trend of imports and exports data.

Adventures in Uncertainty: An Empirical Investigation of the Use of a Taylor's Series Approximation for the Assessment of Sampling Errors in Educational Research.

ERIC Educational Resources Information Center

Wilson, Mark

This study investigates the accuracy of the Woodruff-Causey technique for estimating sampling errors for complex statistics. The technique may be applied when data are collected by using multistage clustered samples. The technique was chosen for study because of its relevance to the correct use of multivariate analyses in educational survey…

Comparative assessment of bone pose estimation using Point Cluster Technique and OpenSim.

PubMed

Lathrop, Rebecca L; Chaudhari, Ajit M W; Siston, Robert A

2011-11-01

Estimating the position of the bones from optical motion capture data is a challenge associated with human movement analysis. Bone pose estimation techniques such as the Point Cluster Technique (PCT) and simulations of movement through software packages such as OpenSim are used to minimize soft tissue artifact and estimate skeletal position; however, using different methods for analysis may produce differing kinematic results which could lead to differences in clinical interpretation such as a misclassification of normal or pathological gait. This study evaluated the differences present in knee joint kinematics as a result of calculating joint angles using various techniques. We calculated knee joint kinematics from experimental gait data using the standard PCT, the least squares approach in OpenSim applied to experimental marker data, and the least squares approach in OpenSim applied to the results of the PCT algorithm. Maximum and resultant RMS differences in knee angles were calculated between all techniques. We observed differences in flexion/extension, varus/valgus, and internal/external rotation angles between all approaches. The largest differences were between the PCT results and all results calculated using OpenSim. The RMS differences averaged nearly 5° for flexion/extension angles with maximum differences exceeding 15°. Average RMS differences were relatively small (< 1.08°) between results calculated within OpenSim, suggesting that the choice of marker weighting is not critical to the results of the least squares inverse kinematics calculations. The largest difference between techniques appeared to be a constant offset between the PCT and all OpenSim results, which may be due to differences in the definition of anatomical reference frames, scaling of musculoskeletal models, and/or placement of virtual markers within OpenSim. Different methods for data analysis can produce largely different kinematic results, which could lead to the misclassification of normal or pathological gait. Improved techniques to allow non-uniform scaling of generic models to more accurately reflect subject-specific bone geometries and anatomical reference frames may reduce differences between bone pose estimation techniques and allow for comparison across gait analysis platforms.

PETPVC: a toolbox for performing partial volume correction techniques in positron emission tomography

NASA Astrophysics Data System (ADS)

Thomas, Benjamin A.; Cuplov, Vesna; Bousse, Alexandre; Mendes, Adriana; Thielemans, Kris; Hutton, Brian F.; Erlandsson, Kjell

2016-11-01

Positron emission tomography (PET) images are degraded by a phenomenon known as the partial volume effect (PVE). Approaches have been developed to reduce PVEs, typically through the utilisation of structural information provided by other imaging modalities such as MRI or CT. These methods, known as partial volume correction (PVC) techniques, reduce PVEs by compensating for the effects of the scanner resolution, thereby improving the quantitative accuracy. The PETPVC toolbox described in this paper comprises a suite of methods, both classic and more recent approaches, for the purposes of applying PVC to PET data. Eight core PVC techniques are available. These core methods can be combined to create a total of 22 different PVC techniques. Simulated brain PET data are used to demonstrate the utility of toolbox in idealised conditions, the effects of applying PVC with mismatched point-spread function (PSF) estimates and the potential of novel hybrid PVC methods to improve the quantification of lesions. All anatomy-based PVC techniques achieve complete recovery of the PET signal in cortical grey matter (GM) when performed in idealised conditions. Applying deconvolution-based approaches results in incomplete recovery due to premature termination of the iterative process. PVC techniques are sensitive to PSF mismatch, causing a bias of up to 16.7% in GM recovery when over-estimating the PSF by 3 mm. The recovery of both GM and a simulated lesion was improved by combining two PVC techniques together. The PETPVC toolbox has been written in C++, supports Windows, Mac and Linux operating systems, is open-source and publicly available.

Error estimation in multitemporal InSAR deformation time series, with application to Lanzarote, Canary Islands

NASA Astrophysics Data System (ADS)

GonzáLez, Pablo J.; FernáNdez, José

2011-10-01

Interferometric Synthetic Aperture Radar (InSAR) is a reliable technique for measuring crustal deformation. However, despite its long application in geophysical problems, its error estimation has been largely overlooked. Currently, the largest problem with InSAR is still the atmospheric propagation errors, which is why multitemporal interferometric techniques have been successfully developed using a series of interferograms. However, none of the standard multitemporal interferometric techniques, namely PS or SB (Persistent Scatterers and Small Baselines, respectively) provide an estimate of their precision. Here, we present a method to compute reliable estimates of the precision of the deformation time series. We implement it for the SB multitemporal interferometric technique (a favorable technique for natural terrains, the most usual target of geophysical applications). We describe the method that uses a properly weighted scheme that allows us to compute estimates for all interferogram pixels, enhanced by a Montecarlo resampling technique that properly propagates the interferogram errors (variance-covariances) into the unknown parameters (estimated errors for the displacements). We apply the multitemporal error estimation method to Lanzarote Island (Canary Islands), where no active magmatic activity has been reported in the last decades. We detect deformation around Timanfaya volcano (lengthening of line-of-sight ˜ subsidence), where the last eruption in 1730-1736 occurred. Deformation closely follows the surface temperature anomalies indicating that magma crystallization (cooling and contraction) of the 300-year shallow magmatic body under Timanfaya volcano is still ongoing.

Determination of Time Dependent Virus Inactivation Rates

NASA Astrophysics Data System (ADS)

Chrysikopoulos, C. V.; Vogler, E. T.

2003-12-01

A methodology is developed for estimating temporally variable virus inactivation rate coefficients from experimental virus inactivation data. The methodology consists of a technique for slope estimation of normalized virus inactivation data in conjunction with a resampling parameter estimation procedure. The slope estimation technique is based on a relatively flexible geostatistical method known as universal kriging. Drift coefficients are obtained by nonlinear fitting of bootstrap samples and the corresponding confidence intervals are obtained by bootstrap percentiles. The proposed methodology yields more accurate time dependent virus inactivation rate coefficients than those estimated by fitting virus inactivation data to a first-order inactivation model. The methodology is successfully applied to a set of poliovirus batch inactivation data. Furthermore, the importance of accurate inactivation rate coefficient determination on virus transport in water saturated porous media is demonstrated with model simulations.

Application of an Optimal Tuner Selection Approach for On-Board Self-Tuning Engine Models

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Armstrong, Jeffrey B.; Garg, Sanjay

2012-01-01

An enhanced design methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented in this paper. It specific-ally addresses the under-determined estimation problem, in which there are more unknown parameters than available sensor measurements. This work builds upon an existing technique for systematically selecting a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. While the existing technique was optimized for open-loop engine operation at a fixed design point, in this paper an alternative formulation is presented that enables the technique to be optimized for an engine operating under closed-loop control throughout the flight envelope. The theoretical Kalman filter mean squared estimation error at a steady-state closed-loop operating point is derived, and the tuner selection approach applied to minimize this error is discussed. A technique for constructing a globally optimal tuning parameter vector, which enables full-envelope application of the technology, is also presented, along with design steps for adjusting the dynamic response of the Kalman filter state estimates. Results from the application of the technique to linear and nonlinear aircraft engine simulations are presented and compared to the conventional approach of tuner selection. The new methodology is shown to yield a significant improvement in on-line Kalman filter estimation accuracy.

A Technique for Measuring Rotocraft Dynamic Stability in the 40 by 80 Foot Wind Tunnel

NASA Technical Reports Server (NTRS)

Gupta, N. K.; Bohn, J. G.

1977-01-01

An on-line technique is described for the measurement of tilt rotor aircraft dynamic stability in the Ames 40- by 80-Foot Wind Tunnel. The technique is based on advanced system identification methodology and uses the instrumental variables approach. It is particulary applicable to real time estimation problems with limited amounts of noise-contaminated data. Several simulations are used to evaluate the algorithm. Estimated natural frequencies and damping ratios are compared with simulation values. The algorithm is also applied to wind tunnel data in an off-line mode. The results are used to develop preliminary guidelines for effective use of the algorithm.

Quantile Regression in the Study of Developmental Sciences

ERIC Educational Resources Information Center

Petscher, Yaacov; Logan, Jessica A. R.

2014-01-01

Linear regression analysis is one of the most common techniques applied in developmental research, but only allows for an estimate of the average relations between the predictor(s) and the outcome. This study describes quantile regression, which provides estimates of the relations between the predictor(s) and outcome, but across multiple points of…

A non-parametric automatic blending methodology to estimate rainfall fields from rain gauge and radar data

NASA Astrophysics Data System (ADS)

Velasco-Forero, Carlos A.; Sempere-Torres, Daniel; Cassiraga, Eduardo F.; Jaime Gómez-Hernández, J.

2009-07-01

Quantitative estimation of rainfall fields has been a crucial objective from early studies of the hydrological applications of weather radar. Previous studies have suggested that flow estimations are improved when radar and rain gauge data are combined to estimate input rainfall fields. This paper reports new research carried out in this field. Classical approaches for the selection and fitting of a theoretical correlogram (or semivariogram) model (needed to apply geostatistical estimators) are avoided in this study. Instead, a non-parametric technique based on FFT is used to obtain two-dimensional positive-definite correlograms directly from radar observations, dealing with both the natural anisotropy and the temporal variation of the spatial structure of the rainfall in the estimated fields. Because these correlation maps can be automatically obtained at each time step of a given rainfall event, this technique might easily be used in operational (real-time) applications. This paper describes the development of the non-parametric estimator exploiting the advantages of FFT for the automatic computation of correlograms and provides examples of its application on a case study using six rainfall events. This methodology is applied to three different alternatives to incorporate the radar information (as a secondary variable), and a comparison of performances is provided. In particular, their ability to reproduce in estimated rainfall fields (i) the rain gauge observations (in a cross-validation analysis) and (ii) the spatial patterns of radar fields are analyzed. Results seem to indicate that the methodology of kriging with external drift [KED], in combination with the technique of automatically computing 2-D spatial correlograms, provides merged rainfall fields with good agreement with rain gauges and with the most accurate approach to the spatial tendencies observed in the radar rainfall fields, when compared with other alternatives analyzed.

The use of the multiwavelet transform for the estimation of surface wave group and phase velocities and their associated uncertainties

NASA Astrophysics Data System (ADS)

Poppeliers, C.; Preston, L. A.

2017-12-01

Measurements of seismic surface wave dispersion can be used to infer the structure of the Earth's subsurface. Typically, to identify group- and phase-velocity, a series of narrow-band filters are applied to surface wave seismograms. Frequency dependent arrival times of surface waves can then be identified from the resulting suite of narrow band seismograms. The frequency-dependent velocity estimates are then inverted for subsurface velocity structure. However, this technique has no method to estimate the uncertainty of the measured surface wave velocities, and subsequently there is no estimate of uncertainty on, for example, tomographic results. For the work here, we explore using the multiwavelet transform (MWT) as an alternate method to estimate surface wave speeds. The MWT decomposes a signal similarly to the conventional filter bank technique, but with two primary advantages: 1) the time-frequency localization is optimized in regard to the time-frequency tradeoff, and 2) we can use the MWT to estimate the uncertainty of the resulting surface wave group- and phase-velocities. The uncertainties of the surface wave speed measurements can then be propagated into tomographic inversions to provide uncertainties of resolved Earth structure. As proof-of-concept, we apply our technique to four seismic ambient noise correlograms that were collected from the University of Nevada Reno seismic network near the Nevada National Security Site. We invert the estimated group- and phase-velocities, as well the uncertainties, for 1-D Earth structure for each station pair. These preliminary results generally agree with 1-D velocities that are obtained from inverting dispersion curves estimated from a conventional Gaussian filter bank.

Estimation of hysteretic damping of structures by stochastic subspace identification

NASA Astrophysics Data System (ADS)

Bajrić, Anela; Høgsberg, Jan

2018-05-01

Output-only system identification techniques can estimate modal parameters of structures represented by linear time-invariant systems. However, the extension of the techniques to structures exhibiting non-linear behavior has not received much attention. This paper presents an output-only system identification method suitable for random response of dynamic systems with hysteretic damping. The method applies the concept of Stochastic Subspace Identification (SSI) to estimate the model parameters of a dynamic system with hysteretic damping. The restoring force is represented by the Bouc-Wen model, for which an equivalent linear relaxation model is derived. Hysteretic properties can be encountered in engineering structures exposed to severe cyclic environmental loads, as well as in vibration mitigation devices, such as Magneto-Rheological (MR) dampers. The identification technique incorporates the equivalent linear damper model in the estimation procedure. Synthetic data, representing the random vibrations of systems with hysteresis, validate the estimated system parameters by the presented identification method at low and high-levels of excitation amplitudes.

Using Decision Trees for Estimating Mode Choice of Trips in Buca-Izmir

NASA Astrophysics Data System (ADS)

Oral, L. O.; Tecim, V.

2013-05-01

Decision makers develop transportation plans and models for providing sustainable transport systems in urban areas. Mode Choice is one of the stages in transportation modelling. Data mining techniques can discover factors affecting the mode choice. These techniques can be applied with knowledge process approach. In this study a data mining process model is applied to determine the factors affecting the mode choice with decision trees techniques by considering individual trip behaviours from household survey data collected within Izmir Transportation Master Plan. From this perspective transport mode choice problem is solved on a case in district of Buca-Izmir, Turkey with CRISP-DM knowledge process model.

Updated generalized biomass equations for North American tree species

Treesearch

David C. Chojnacky; Linda S. Heath; Jennifer C. Jenkins

2014-01-01

Historically, tree biomass at large scales has been estimated by applying dimensional analysis techniques and field measurements such as diameter at breast height (dbh) in allometric regression equations. Equations often have been developed using differing methods and applied only to certain species or isolated areas. We previously had compiled and combined (in meta-...

Estimating discharge measurement uncertainty using the interpolated variance estimator

USGS Publications Warehouse

Cohn, T.; Kiang, J.; Mason, R.

2012-01-01

Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

Reconstructing the Sky Location of Gravitational-Wave Detected Compact Binary Systems: Methodology for Testing and Comparison

NASA Technical Reports Server (NTRS)

Sidney, T.; Aylott, B.; Christensen, N.; Farr, B.; Farr, W.; Feroz, F.; Gair, J.; Grover, K.; Graff, P.; Hanna, C.;

Reconstructing the sky location of gravitational-wave detected compact binary systems: Methodology for testing and comparison

NASA Astrophysics Data System (ADS)

Sidery, T.; Aylott, B.; Christensen, N.; Farr, B.; Farr, W.; Feroz, F.; Gair, J.; Grover, K.; Graff, P.; Hanna, C.; Kalogera, V.; Mandel, I.; O'Shaughnessy, R.; Pitkin, M.; Price, L.; Raymond, V.; Röver, C.; Singer, L.; van der Sluys, M.; Smith, R. J. E.; Vecchio, A.; Veitch, J.; Vitale, S.

2014-04-01

The problem of reconstructing the sky position of compact binary coalescences detected via gravitational waves is a central one for future observations with the ground-based network of gravitational-wave laser interferometers, such as Advanced LIGO and Advanced Virgo. Different techniques for sky localization have been independently developed. They can be divided in two broad categories: fully coherent Bayesian techniques, which are high latency and aimed at in-depth studies of all the parameters of a source, including sky position, and "triangulation-based" techniques, which exploit the data products from the search stage of the analysis to provide an almost real-time approximation of the posterior probability density function of the sky location of a detection candidate. These techniques have previously been applied to data collected during the last science runs of gravitational-wave detectors operating in the so-called initial configuration. Here, we develop and analyze methods for assessing the self consistency of parameter estimation methods and carrying out fair comparisons between different algorithms, addressing issues of efficiency and optimality. These methods are general, and can be applied to parameter estimation problems other than sky localization. We apply these methods to two existing sky localization techniques representing the two above-mentioned categories, using a set of simulated inspiral-only signals from compact binary systems with a total mass of ≤20M⊙ and nonspinning components. We compare the relative advantages and costs of the two techniques and show that sky location uncertainties are on average a factor ≈20 smaller for fully coherent techniques than for the specific variant of the triangulation-based technique used during the last science runs, at the expense of a factor ≈1000 longer processing time.

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.

A TRMM-Calibrated Infrared Technique for Global Rainfall Estimation

NASA Technical Reports Server (NTRS)

Negri, Andrew J.; Adler, Robert F.; Xu, Li-Ming

2003-01-01

This paper presents the development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during summer 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR- based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and t i f m rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.

Acoustical Direction Finding with Time-Modulated Arrays

PubMed Central

Clark, Ben; Flint, James A.

2016-01-01

Time-Modulated Linear Arrays (TMLAs) offer useful efficiency savings over conventional phased arrays when applied in parameter estimation applications. The present paper considers the application of TMLAs to acoustic systems and proposes an algorithm for efficiently deriving the arrival angle of a signal. The proposed technique is applied in the frequency domain, where the signal and harmonic content is captured. Using a weighted average method on harmonic amplitudes and their respective main beam angles, it is possible to determine an estimate for the signal’s direction of arrival. The method is demonstrated and evaluated using results from both numerical and practical implementations and performance data is provided. The use of Micro-Electromechanical Systems (MEMS) sensors allows time-modulation techniques to be applied at ultrasonic frequencies. Theoretical predictions for an array of five isotropic elements with half-wavelength spacing and 1000 data samples suggest an accuracy of ±1∘ within an angular range of approximately ±50∘. In experiments of a 40 kHz five-element microphone array, a Direction of Arrival (DoA) estimation within ±2.5∘ of the target signal is readily achieved inside a ±45∘ range using a single switched input stage and a simple hardware setup. PMID:27973432

Application of Ground-Penetrating Radar for Detecting Internal Anomalies in Tree Trunks with Irregular Contours.

PubMed

Li, Weilin; Wen, Jian; Xiao, Zhongliang; Xu, Shengxia

2018-02-22

To assess the health conditions of tree trunks, it is necessary to estimate the layers and anomalies of their internal structure. The main objective of this paper is to investigate the internal part of tree trunks considering their irregular contour. In this respect, we used ground penetrating radar (GPR) for non-invasive detection of defects and deteriorations in living trees trunks. The Hilbert transform algorithm and the reflection amplitudes were used to estimate the relative dielectric constant. The point cloud data technique was applied as well to extract the irregular contours of trunks. The feasibility and accuracy of the methods were examined through numerical simulations, laboratory and field measurements. The results demonstrated that the applied methodology allowed for accurate characterizations of the internal inhomogeneity. Furthermore, the point cloud technique resolved the trunk well by providing high-precision coordinate information. This study also demonstrated that cross-section tomography provided images with high resolution and accuracy. These integrated techniques thus proved to be promising for observing tree trunks and other cylindrical objects. The applied approaches offer a great promise for future 3D reconstruction of tomographic images with radar wave.

Optimal pipe size design for looped irrigation water supply system using harmony search: Saemangeum project area.

PubMed

Yoo, Do Guen; Lee, Ho Min; Sadollah, Ali; Kim, Joong Hoon

2015-01-01

Water supply systems are mainly classified into branched and looped network systems. The main difference between these two systems is that, in a branched network system, the flow within each pipe is a known value, whereas in a looped network system, the flow in each pipe is considered an unknown value. Therefore, an analysis of a looped network system is a more complex task. This study aims to develop a technique for estimating the optimal pipe diameter for a looped agricultural irrigation water supply system using a harmony search algorithm, which is an optimization technique. This study mainly serves two purposes. The first is to develop an algorithm and a program for estimating a cost-effective pipe diameter for agricultural irrigation water supply systems using optimization techniques. The second is to validate the developed program by applying the proposed optimized cost-effective pipe diameter to an actual study region (Saemangeum project area, zone 6). The results suggest that the optimal design program, which applies an optimization theory and enhances user convenience, can be effectively applied for the real systems of a looped agricultural irrigation water supply.

Optimal Pipe Size Design for Looped Irrigation Water Supply System Using Harmony Search: Saemangeum Project Area

PubMed Central

Lee, Ho Min; Sadollah, Ali

2015-01-01

Water supply systems are mainly classified into branched and looped network systems. The main difference between these two systems is that, in a branched network system, the flow within each pipe is a known value, whereas in a looped network system, the flow in each pipe is considered an unknown value. Therefore, an analysis of a looped network system is a more complex task. This study aims to develop a technique for estimating the optimal pipe diameter for a looped agricultural irrigation water supply system using a harmony search algorithm, which is an optimization technique. This study mainly serves two purposes. The first is to develop an algorithm and a program for estimating a cost-effective pipe diameter for agricultural irrigation water supply systems using optimization techniques. The second is to validate the developed program by applying the proposed optimized cost-effective pipe diameter to an actual study region (Saemangeum project area, zone 6). The results suggest that the optimal design program, which applies an optimization theory and enhances user convenience, can be effectively applied for the real systems of a looped agricultural irrigation water supply. PMID:25874252

New technique for ensemble dressing combining Multimodel SuperEnsemble and precipitation PDF

NASA Astrophysics Data System (ADS)

Cane, D.; Milelli, M.

2009-09-01

The Multimodel SuperEnsemble technique (Krishnamurti et al., Science 285, 1548-1550, 1999) is a postprocessing method for the estimation of weather forecast parameters reducing direct model output errors. It differs from other ensemble analysis techniques by the use of an adequate weighting of the input forecast models to obtain a combined estimation of meteorological parameters. Weights are calculated by least-square minimization of the difference between the model and the observed field during a so-called training period. Although it can be applied successfully on the continuous parameters like temperature, humidity, wind speed and mean sea level pressure (Cane and Milelli, Meteorologische Zeitschrift, 15, 2, 2006), the Multimodel SuperEnsemble gives good results also when applied on the precipitation, a parameter quite difficult to handle with standard post-processing methods. Here we present our methodology for the Multimodel precipitation forecasts applied on a wide spectrum of results over Piemonte very dense non-GTS weather station network. We will focus particularly on an accurate statistical method for bias correction and on the ensemble dressing in agreement with the observed precipitation forecast-conditioned PDF. Acknowledgement: this work is supported by the Italian Civil Defence Department.

Navigation in Difficult Environments: Multi-Sensor Fusion Techniques

DTIC Science & Technology

2010-03-01

Hwang , Introduction to Random Signals and Applied Kalman Filtering, 3rd ed., John Wiley & Sons, Inc., New York, 1997. [17] J. L. Farrell, “GPS/INS...nav solution Navigation outputs Estimation of inertial errors ( Kalman filter) Error estimates Core sensor Incoming signal INS Estimates of signal...the INS drift terms is performed using the mechanism of a complementary Kalman filter. The idea is that a signal parameter can be generally

Weight estimation techniques for composite airplanes in general aviation industry

NASA Technical Reports Server (NTRS)

Paramasivam, T.; Horn, W. J.; Ritter, J.

1986-01-01

Currently available weight estimation methods for general aviation airplanes were investigated. New equations with explicit material properties were developed for the weight estimation of aircraft components such as wing, fuselage and empennage. Regression analysis was applied to the basic equations for a data base of twelve airplanes to determine the coefficients. The resulting equations can be used to predict the component weights of either metallic or composite airplanes.

Robust regression on noisy data for fusion scaling laws

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

Verdoolaege, Geert, E-mail: geert.verdoolaege@ugent.be; Laboratoire de Physique des Plasmas de l'ERM - Laboratorium voor Plasmafysica van de KMS

2014-11-15

We introduce the method of geodesic least squares (GLS) regression for estimating fusion scaling laws. Based on straightforward principles, the method is easily implemented, yet it clearly outperforms established regression techniques, particularly in cases of significant uncertainty on both the response and predictor variables. We apply GLS for estimating the scaling of the L-H power threshold, resulting in estimates for ITER that are somewhat higher than predicted earlier.

Online Detection of Broken Rotor Bar Fault in Induction Motors by Combining Estimation of Signal Parameters via Min-norm Algorithm and Least Square Method

NASA Astrophysics Data System (ADS)

Wang, Pan-Pan; Yu, Qiang; Hu, Yong-Jun; Miao, Chang-Xin

2017-11-01

Current research in broken rotor bar (BRB) fault detection in induction motors is primarily focused on a high-frequency resolution analysis of the stator current. Compared with a discrete Fourier transformation, the parametric spectrum estimation technique has a higher frequency accuracy and resolution. However, the existing detection methods based on parametric spectrum estimation cannot realize online detection, owing to the large computational cost. To improve the efficiency of BRB fault detection, a new detection method based on the min-norm algorithm and least square estimation is proposed in this paper. First, the stator current is filtered using a band-pass filter and divided into short overlapped data windows. The min-norm algorithm is then applied to determine the frequencies of the fundamental and fault characteristic components with each overlapped data window. Next, based on the frequency values obtained, a model of the fault current signal is constructed. Subsequently, a linear least squares problem solved through singular value decomposition is designed to estimate the amplitudes and phases of the related components. Finally, the proposed method is applied to a simulated current and an actual motor, the results of which indicate that, not only parametric spectrum estimation technique.

Empirical evaluation of the market price of risk using the CIR model

NASA Astrophysics Data System (ADS)

Bernaschi, M.; Torosantucci, L.; Uboldi, A.

2007-03-01

We describe a simple but effective method for the estimation of the market price of risk. The basic idea is to compare the results obtained by following two different approaches in the application of the Cox-Ingersoll-Ross (CIR) model. In the first case, we apply the non-linear least squares method to cross sectional data (i.e., all rates of a single day). In the second case, we consider the short rate obtained by means of the first procedure as a proxy of the real market short rate. Starting from this new proxy, we evaluate the parameters of the CIR model by means of martingale estimation techniques. The estimate of the market price of risk is provided by comparing results obtained with these two techniques, since this approach makes possible to isolate the market price of risk and evaluate, under the Local Expectations Hypothesis, the risk premium given by the market for different maturities. As a test case, we apply the method to data of the European Fixed Income Market.

Evaluation of Airborne l- Band Multi-Baseline Pol-Insar for dem Extraction Beneath Forest Canopy

NASA Astrophysics Data System (ADS)

Li, W. M.; Chen, E. X.; Li, Z. Y.; Jiang, C.; Jia, Y.

2018-04-01

DEM beneath forest canopy is difficult to extract with optical stereo pairs, InSAR and Pol-InSAR techniques. Tomographic SAR (TomoSAR) based on different penetration and view angles could reflect vertical structure and ground structure. This paper aims at evaluating the possibility of TomoSAR for underlying DEM extraction. Airborne L-band repeat-pass Pol-InSAR collected in BioSAR 2008 campaign was applied to reconstruct the 3D structure of forest. And sum of kronecker product and algebraic synthesis algorithm were used to extract ground structure, and phase linking algorithm was applied to estimate ground phase. Then Goldstein cut-branch approach was used to unwrap the phases and then estimated underlying DEM. The average difference between the extracted underlying DEM and Lidar DEM is about 3.39 m in our test site. And the result indicates that it is possible for underlying DEM estimation with airborne L-band repeat-pass TomoSAR technique.

Spectral analysis of GEOS-3 altimeter data and frequency domain collocation. [to estimate gravity anomalies

NASA Technical Reports Server (NTRS)

Eren, K.

1980-01-01

The mathematical background in spectral analysis as applied to geodetic applications is summarized. The resolution (cut-off frequency) of the GEOS 3 altimeter data is examined by determining the shortest wavelength (corresponding to the cut-off frequency) recoverable. The data from some 18 profiles are used. The total power (variance) in the sea surface topography with respect to the reference ellipsoid as well as with respect to the GEM-9 surface is computed. A fast inversion algorithm for matrices of simple and block Toeplitz matrices and its application to least squares collocation is explained. This algorithm yields a considerable gain in computer time and storage in comparison with conventional least squares collocation. Frequency domain least squares collocation techniques are also introduced and applied to estimating gravity anomalies from GEOS 3 altimeter data. These techniques substantially reduce the computer time and requirements in storage associated with the conventional least squares collocation. Numerical examples given demonstrate the efficiency and speed of these techniques.

A volumetric technique for fossil body mass estimation applied to Australopithecus afarensis.

PubMed

Brassey, Charlotte A; O'Mahoney, Thomas G; Chamberlain, Andrew T; Sellers, William I

2018-02-01

Fossil body mass estimation is a well established practice within the field of physical anthropology. Previous studies have relied upon traditional allometric approaches, in which the relationship between one/several skeletal dimensions and body mass in a range of modern taxa is used in a predictive capacity. The lack of relatively complete skeletons has thus far limited the potential application of alternative mass estimation techniques, such as volumetric reconstruction, to fossil hominins. Yet across vertebrate paleontology more broadly, novel volumetric approaches are resulting in predicted values for fossil body mass very different to those estimated by traditional allometry. Here we present a new digital reconstruction of Australopithecus afarensis (A.L. 288-1; 'Lucy') and a convex hull-based volumetric estimate of body mass. The technique relies upon identifying a predictable relationship between the 'shrink-wrapped' volume of the skeleton and known body mass in a range of modern taxa, and subsequent application to an articulated model of the fossil taxa of interest. Our calibration dataset comprises whole body computed tomography (CT) scans of 15 species of modern primate. The resulting predictive model is characterized by a high correlation coefficient (r 2  = 0.988) and a percentage standard error of 20%, and performs well when applied to modern individuals of known body mass. Application of the convex hull technique to A. afarensis results in a relatively low body mass estimate of 20.4 kg (95% prediction interval 13.5-30.9 kg). A sensitivity analysis on the articulation of the chest region highlights the sensitivity of our approach to the reconstruction of the trunk, and the incomplete nature of the preserved ribcage may explain the low values for predicted body mass here. We suggest that the heaviest of previous estimates would require the thorax to be expanded to an unlikely extent, yet this can only be properly tested when more complete fossils are available. Copyright © 2017 Elsevier Ltd. All rights reserved.

Quantitative estimation of climatic parameters from vegetation data in North America by the mutual climatic range technique

USGS Publications Warehouse

Anderson, Katherine H.; Bartlein, Patrick J.; Strickland, Laura E.; Pelltier, Richard T.; Thompson, Robert S.; Shafer, Sarah L.

2012-01-01

The mutual climatic range (MCR) technique is perhaps the most widely used method for estimating past climatic parameters from fossil assemblages, largely because it can be conducted on a simple list of the taxa present in an assemblage. When applied to plant macrofossil data, this unweighted approach (MCRun) will frequently identify a large range for a given climatic parameter where the species in an assemblage can theoretically live together. To narrow this range, we devised a new weighted approach (MCRwt) that employs information from the modern relations between climatic parameters and plant distributions to lessen the influence of the "tails" of the distributions of the climatic data associated with the taxa in an assemblage. To assess the performance of the MCR approaches, we applied them to a set of modern climatic data and plant distributions on a 25-km grid for North America, and compared observed and estimated climatic values for each grid point. In general, MCRwt was superior to MCRun in providing smaller anomalies, less bias, and better correlations between observed and estimated values. However, by the same measures, the results of Modern Analog Technique (MAT) approaches were superior to MCRwt. Although this might be reason to favor MAT approaches, they are based on assumptions that may not be valid for paleoclimatic reconstructions, including that: 1) the absence of a taxon from a fossil sample is meaningful, 2) plant associations were largely unaffected by past changes in either levels of atmospheric carbon dioxide or in the seasonal distributions of solar radiation, and 3) plant associations of the past are adequately represented on the modern landscape. To illustrate the application of these MCR and MAT approaches to paleoclimatic reconstructions, we applied them to a Pleistocene paleobotanical assemblage from the western United States. From our examinations of the estimates of modern and past climates from vegetation assemblages, we conclude that the MCRun technique provides reliable and unbiased estimates of the ranges of possible climatic conditions that can reasonably be associated with these assemblages. The application of MCRwt and MAT approaches can further constrain these estimates and may provide a systematic way to assess uncertainty. The data sets required for MCR analyses in North America are provided in a parallel publication.

A New Approach to Estimate Forest Parameters Using Dual-Baseline Pol-InSAR Data

NASA Astrophysics Data System (ADS)

Bai, L.; Hong, W.; Cao, F.; Zhou, Y.

2009-04-01

In POL-InSAR applications using ESPRIT technique, it is assumed that there exist stable scattering centres in the forest. However, the observations in forest severely suffer from volume and temporal decorrelation. The forest scatters are not stable as assumed. The obtained interferometric information is not accurate as expected. Besides, ESPRIT techniques could not identify the interferometric phases corresponding to the ground and the canopy. It provides multiple estimations for the height between two scattering centers due to phase unwrapping. Therefore, estimation errors are introduced to the forest height results. To suppress the two types of errors, we use the dual-baseline POL-InSAR data to estimate forest height. Dual-baseline coherence optimization is applied to obtain interferometric information of stable scattering centers in the forest. From the interferometric phases for different baselines, estimation errors caused by phase unwrapping is solved. Other estimation errors can be suppressed, too. Experiments are done to the ESAR L band POL-InSAR data. Experimental results show the proposed methods provide more accurate forest height than ESPRIT technique.

Global parameter estimation for thermodynamic models of transcriptional regulation.

PubMed

Suleimenov, Yerzhan; Ay, Ahmet; Samee, Md Abul Hassan; Dresch, Jacqueline M; Sinha, Saurabh; Arnosti, David N

2013-07-15

Deciphering the mechanisms involved in gene regulation holds the key to understanding the control of central biological processes, including human disease, population variation, and the evolution of morphological innovations. New experimental techniques including whole genome sequencing and transcriptome analysis have enabled comprehensive modeling approaches to study gene regulation. In many cases, it is useful to be able to assign biological significance to the inferred model parameters, but such interpretation should take into account features that affect these parameters, including model construction and sensitivity, the type of fitness calculation, and the effectiveness of parameter estimation. This last point is often neglected, as estimation methods are often selected for historical reasons or for computational ease. Here, we compare the performance of two parameter estimation techniques broadly representative of local and global approaches, namely, a quasi-Newton/Nelder-Mead simplex (QN/NMS) method and a covariance matrix adaptation-evolutionary strategy (CMA-ES) method. The estimation methods were applied to a set of thermodynamic models of gene transcription applied to regulatory elements active in the Drosophila embryo. Measuring overall fit, the global CMA-ES method performed significantly better than the local QN/NMS method on high quality data sets, but this difference was negligible on lower quality data sets with increased noise or on data sets simplified by stringent thresholding. Our results suggest that the choice of parameter estimation technique for evaluation of gene expression models depends both on quality of data, the nature of the models [again, remains to be established] and the aims of the modeling effort. Copyright © 2013 Elsevier Inc. All rights reserved.

ENVIRONMENTAL CHEMISTRY

EPA Science Inventory

Environmental chemistry is applied to estimating the exposure of ecosystems and humans to various chemical environmental stressors. Among the stressors of concern are mercury, pesticides, and arsenic. Advanced analytical chemistry techniques are used to measure these stressors ...

Time Domain Estimation of Arterial Parameters using the Windkessel Model and the Monte Carlo Method

NASA Astrophysics Data System (ADS)

Gostuski, Vladimir; Pastore, Ignacio; Rodriguez Palacios, Gaspar; Vaca Diez, Gustavo; Moscoso-Vasquez, H. Marcela; Risk, Marcelo

2016-04-01

Numerous parameter estimation techniques exist for characterizing the arterial system using electrical circuit analogs. However, they are often limited by their requirements and usually high computational burdain. Therefore, a new method for estimating arterial parameters based on Monte Carlo simulation is proposed. A three element Windkessel model was used to represent the arterial system. The approach was to reduce the error between the calculated and physiological aortic pressure by randomly generating arterial parameter values, while keeping constant the arterial resistance. This last value was obtained for each subject using the arterial flow, and was a necessary consideration in order to obtain a unique set of values for the arterial compliance and peripheral resistance. The estimation technique was applied to in vivo data containing steady beats in mongrel dogs, and it reliably estimated Windkessel arterial parameters. Further, this method appears to be computationally efficient for on-line time-domain estimation of these parameters.

Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination

PubMed Central

Berg, Eric; Roncali, Emilie; Hutchcroft, Will; Qi, Jinyi; Cherry, Simon R.

2016-01-01

In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator’s temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (~11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector’s single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal. PMID:27295658

Improving Depth, Energy and Timing Estimation in PET Detectors with Deconvolution and Maximum Likelihood Pulse Shape Discrimination.

PubMed

Berg, Eric; Roncali, Emilie; Hutchcroft, Will; Qi, Jinyi; Cherry, Simon R

2016-11-01

In a scintillation detector, the light generated in the scintillator by a gamma interaction is converted to photoelectrons by a photodetector and produces a time-dependent waveform, the shape of which depends on the scintillator properties and the photodetector response. Several depth-of-interaction (DOI) encoding strategies have been developed that manipulate the scintillator's temporal response along the crystal length and therefore require pulse shape discrimination techniques to differentiate waveform shapes. In this work, we demonstrate how maximum likelihood (ML) estimation methods can be applied to pulse shape discrimination to better estimate deposited energy, DOI and interaction time (for time-of-flight (TOF) PET) of a gamma ray in a scintillation detector. We developed likelihood models based on either the estimated detection times of individual photoelectrons or the number of photoelectrons in discrete time bins, and applied to two phosphor-coated crystals (LFS and LYSO) used in a previously developed TOF-DOI detector concept. Compared with conventional analytical methods, ML pulse shape discrimination improved DOI encoding by 27% for both crystals. Using the ML DOI estimate, we were able to counter depth-dependent changes in light collection inherent to long scintillator crystals and recover the energy resolution measured with fixed depth irradiation (~11.5% for both crystals). Lastly, we demonstrated how the Richardson-Lucy algorithm, an iterative, ML-based deconvolution technique, can be applied to the digitized waveforms to deconvolve the photodetector's single photoelectron response and produce waveforms with a faster rising edge. After deconvolution and applying DOI and time-walk corrections, we demonstrated a 13% improvement in coincidence timing resolution (from 290 to 254 ps) with the LFS crystal and an 8% improvement (323 to 297 ps) with the LYSO crystal.

Using Deep Learning for Tropical Cyclone Intensity Estimation

NASA Astrophysics Data System (ADS)

Miller, J.; Maskey, M.; Berendes, T.

2017-12-01

Satellite-based techniques are the primary approach to estimating tropical cyclone (TC) intensity. Tropical cyclone warning centers worldwide still apply variants of the Dvorak technique for such estimations that include visual inspection of the satellite images. The National Hurricane Center (NHC) estimates about 10-20% uncertainty in its post analyses when only satellite-based estimates are available. The success of the Dvorak technique proves that spatial patterns in infrared (IR) imagery strongly relate to TC intensity. With the ever-increasing quality and quantity of satellite observations of TCs, deep learning techniques designed to excel at pattern recognition have become more relevant in this area of study. In our current study, we aim to provide a fully objective approach to TC intensity estimation by utilizing deep learning in the form of a convolutional neural network trained to predict TC intensity (maximum sustained wind speed) using IR satellite imagery. Large amounts of training data are needed to train a convolutional neural network, so we use GOES IR images from historical tropical storms from the Atlantic and Pacific basins spanning years 2000 to 2015. Images are labeled using a special subset of the HURDAT2 dataset restricted to time periods with airborne reconnaissance data available in order to improve the quality of the HURDAT2 data. Results and the advantages of this technique are to be discussed.

Acoustic Source Bearing Estimation (ASBE) computer program development

NASA Technical Reports Server (NTRS)

Wiese, Michael R.

1987-01-01

A new bearing estimation algorithm (Acoustic Source Analysis Technique - ASAT) and an acoustic analysis computer program (Acoustic Source Bearing Estimation - ASBE) are described, which were developed by Computer Sciences Corporation for NASA Langley Research Center. The ASBE program is used by the Acoustics Division/Applied Acoustics Branch and the Instrument Research Division/Electro-Mechanical Instrumentation Branch to analyze acoustic data and estimate the azimuths from which the source signals radiated. Included are the input and output from a benchmark test case.

Super Resolution and Interference Suppression Technique applied to SHARAD Radar Data

NASA Astrophysics Data System (ADS)

Raguso, M. C.; Mastrogiuseppe, M.; Seu, R.; Piazzo, L.

2017-12-01

We will present a super resolution and interference suppression technique applied to the data acquired by the SHAllow RADar (SHARAD) on board the NASA's 2005 Mars Reconnaissance Orbiter (MRO) mission, currently operating around Mars [1]. The algorithms allow to improve the range resolution roughly by a factor of 3 and the Signal to Noise Ratio (SNR) by a several decibels. Range compression algorithms usually adopt conventional Fourier transform techniques, which are limited in the resolution by the transmitted signal bandwidth, analogous to the Rayleigh's criterion in optics. In this work, we investigate a super resolution method based on autoregressive models and linear prediction techniques [2]. Starting from the estimation of the linear prediction coefficients from the spectral data, the algorithm performs the radar bandwidth extrapolation (BWE), thereby improving the range resolution of the pulse-compressed coherent radar data. Moreover, the EMIs (ElectroMagnetic Interferences) are detected and the spectra is interpolated in order to reconstruct an interference free spectrum, thereby improving the SNR. The algorithm can be applied to the single complex look image after synthetic aperture processing (SAR). We apply the proposed algorithm to simulated as well as to real radar data. We will demonstrate the effective enhancement on vertical resolution with respect to the classical spectral estimator. We will show that the imaging of the subsurface layered structures observed in radargrams is improved, allowing additional insights for the scientific community in the interpretation of the SHARAD radar data, which will help to further our understanding of the formation and evolution of known geological features on Mars. References: [1] Seu et al. 2007, Science, 2007, 317, 1715-1718 [2] K.M. Cuomo, "A Bandwidth Extrapolation Technique for Improved Range Resolution of Coherent Radar Data", Project Report CJP-60, Revision 1, MIT Lincoln Laboratory (4 Dec. 1992).

Alternative Models for Small Samples in Psychological Research: Applying Linear Mixed Effects Models and Generalized Estimating Equations to Repeated Measures Data

ERIC Educational Resources Information Center

Muth, Chelsea; Bales, Karen L.; Hinde, Katie; Maninger, Nicole; Mendoza, Sally P.; Ferrer, Emilio

2016-01-01

Unavoidable sample size issues beset psychological research that involves scarce populations or costly laboratory procedures. When incorporating longitudinal designs these samples are further reduced by traditional modeling techniques, which perform listwise deletion for any instance of missing data. Moreover, these techniques are limited in their…

A Procedure for Estimating a Criterion-Referenced Standard to Identify Educationally Deprived Children for Title I Services. Final Report.

ERIC Educational Resources Information Center

Ziomek, Robert L.; Wright, Benjamin D.

Techniques such as the norm-referenced and average score techniques, commonly used in the identification of educationally disadvantaged students, are critiqued. This study applied latent trait theory, specifically the Rasch Model, along with teacher judgments relative to the mastery of instructional/test decisions, to derive a standard setting…

A Universal Tare Load Prediction Algorithm for Strain-Gage Balance Calibration Data Analysis

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2011-01-01

An algorithm is discussed that may be used to estimate tare loads of wind tunnel strain-gage balance calibration data. The algorithm was originally developed by R. Galway of IAR/NRC Canada and has been described in the literature for the iterative analysis technique. Basic ideas of Galway's algorithm, however, are universally applicable and work for both the iterative and the non-iterative analysis technique. A recent modification of Galway's algorithm is presented that improves the convergence behavior of the tare load prediction process if it is used in combination with the non-iterative analysis technique. The modified algorithm allows an analyst to use an alternate method for the calculation of intermediate non-linear tare load estimates whenever Galway's original approach does not lead to a convergence of the tare load iterations. It is also shown in detail how Galway's algorithm may be applied to the non-iterative analysis technique. Hand load data from the calibration of a six-component force balance is used to illustrate the application of the original and modified tare load prediction method. During the analysis of the data both the iterative and the non-iterative analysis technique were applied. Overall, predicted tare loads for combinations of the two tare load prediction methods and the two balance data analysis techniques showed excellent agreement as long as the tare load iterations converged. The modified algorithm, however, appears to have an advantage over the original algorithm when absolute voltage measurements of gage outputs are processed using the non-iterative analysis technique. In these situations only the modified algorithm converged because it uses an exact solution of the intermediate non-linear tare load estimate for the tare load iteration.

A new slit lamp-based technique for anterior chamber angle estimation.

PubMed

Gispets, Joan; Cardona, Genís; Tomàs, Núria; Fusté, Cèlia; Binns, Alison; Fortes, Miguel A

2014-06-01

To design and test a new noninvasive method for anterior chamber angle (ACA) estimation based on the slit lamp that is accessible to all eye-care professionals. A new technique (slit lamp anterior chamber estimation [SLACE]) that aims to overcome some of the limitations of the van Herick procedure was designed. The technique, which only requires a slit lamp, was applied to estimate the ACA of 50 participants (100 eyes) using two different slit lamp models, and results were compared with gonioscopy as the clinical standard. The Spearman nonparametric correlation between ACA values as determined by gonioscopy and SLACE were 0.81 (p < 0.001) and 0.79 (p < 0.001) for each slit lamp. Sensitivity values of 100 and 87.5% and specificity values of 75 and 81.2%, depending on the slit lamp used, were obtained for the SLACE technique as compared with gonioscopy (Spaeth classification). The SLACE technique, when compared with gonioscopy, displayed good accuracy in the detection of narrow angles, and it may be useful for eye-care clinicians without access to expensive alternative equipment or those who cannot perform gonioscopy because of legal constraints regarding the use of diagnostic drugs.

Estimation of Pulse Transit Time as a Function of Blood Pressure Using a Nonlinear Arterial Tube-Load Model.

PubMed

Gao, Mingwu; Cheng, Hao-Min; Sung, Shih-Hsien; Chen, Chen-Huan; Olivier, Nicholas Bari; Mukkamala, Ramakrishna

2017-07-01

pulse transit time (PTT) varies with blood pressure (BP) throughout the cardiac cycle, yet, because of wave reflection, only one PTT value at the diastolic BP level is conventionally estimated from proximal and distal BP waveforms. The objective was to establish a technique to estimate multiple PTT values at different BP levels in the cardiac cycle. a technique was developed for estimating PTT as a function of BP (to indicate the PTT value for every BP level) from proximal and distal BP waveforms. First, a mathematical transformation from one waveform to the other is defined in terms of the parameters of a nonlinear arterial tube-load model accounting for BP-dependent arterial compliance and wave reflection. Then, the parameters are estimated by optimally fitting the waveforms to each other via the model-based transformation. Finally, PTT as a function of BP is specified by the parameters. The technique was assessed in animals and patients in several ways including the ability of its estimated PTT-BP function to serve as a subject-specific curve for calibrating PTT to BP. the calibration curve derived by the technique during a baseline period yielded bias and precision errors in mean BP of 5.1 ± 0.9 and 6.6 ± 1.0 mmHg, respectively, during hemodynamic interventions that varied mean BP widely. the new technique may permit, for the first time, estimation of PTT values throughout the cardiac cycle from proximal and distal waveforms. the technique could potentially be applied to improve arterial stiffness monitoring and help realize cuff-less BP monitoring.

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

PubMed

Su, Liyun; Zhao, Yanyong; Yan, Tianshun; Li, Fenglan

2012-01-01

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.

Estimation of under-reporting in epidemics using approximations.

PubMed

Gamado, Kokouvi; Streftaris, George; Zachary, Stan

2017-06-01

Under-reporting in epidemics, when it is ignored, leads to under-estimation of the infection rate and therefore of the reproduction number. In the case of stochastic models with temporal data, a usual approach for dealing with such issues is to apply data augmentation techniques through Bayesian methodology. Departing from earlier literature approaches implemented using reversible jump Markov chain Monte Carlo (RJMCMC) techniques, we make use of approximations to obtain faster estimation with simple MCMC. Comparisons among the methods developed here, and with the RJMCMC approach, are carried out and highlight that approximation-based methodology offers useful alternative inference tools for large epidemics, with a good trade-off between time cost and accuracy.

An advanced shape-fitting algorithm applied to quadrupedal mammals: improving volumetric mass estimates

PubMed Central

Brassey, Charlotte A.; Gardiner, James D.

2015-01-01

Body mass is a fundamental physical property of an individual and has enormous bearing upon ecology and physiology. Generating reliable estimates for body mass is therefore a necessary step in many palaeontological studies. Whilst early reconstructions of mass in extinct species relied upon isolated skeletal elements, volumetric techniques are increasingly applied to fossils when skeletal completeness allows. We apply a new ‘alpha shapes’ (α-shapes) algorithm to volumetric mass estimation in quadrupedal mammals. α-shapes are defined by: (i) the underlying skeletal structure to which they are fitted; and (ii) the value α, determining the refinement of fit. For a given skeleton, a range of α-shapes may be fitted around the individual, spanning from very coarse to very fine. We fit α-shapes to three-dimensional models of extant mammals and calculate volumes, which are regressed against mass to generate predictive equations. Our optimal model is characterized by a high correlation coefficient and mean square error (r2=0.975, m.s.e.=0.025). When applied to the woolly mammoth (Mammuthus primigenius) and giant ground sloth (Megatherium americanum), we reconstruct masses of 3635 and 3706 kg, respectively. We consider α-shapes an improvement upon previous techniques as resulting volumes are less sensitive to uncertainties in skeletal reconstructions, and do not require manual separation of body segments from skeletons. PMID:26361559

Neural Network Technique for Global Ocean Color (Chl-a) Estimates Bridging Multiple Satellite Missions

NASA Astrophysics Data System (ADS)

Garraffo, Z. D.; Nadiga, S.; Krasnopolsky, V.; Mehra, A.; Bayler, E. J.; Kim, H. C.; Behringer, D.

2016-02-01

A Neural Network (NN) technique is used to produce consistent global ocean color estimates, bridging multiple satellite ocean color missions by linking ocean color variability - primarily driven by biological processes - with the physical processes of the upper ocean. Satellite-derived surface variables - sea-surface temperature (SST) and sea-surface height (SSH) fields - are used as signatures of upper-ocean dynamics. The NN technique employs adaptive weights that are tuned by applying statistical learning (training) algorithms to past data sets, providing robustness with respect to random noise, accuracy, fast emulations, and fault-tolerance. This study employs Sea-viewing Wide Field-of-View Sensor (SeaWiFS) chlorophyll-a data for 1998-2010 in conjunction with satellite SSH and SST fields. After interpolating all data sets to the same two-degree latitude-longitude grid, the annual mean was removed and monthly anomalies extracted . The NN technique wass trained for even years of that period and tested for errors and bias for the odd years. The NN output are assessed for: (i) bias, (ii) variability, (iii) root-mean-square error (RMSE), and (iv) cross-correlation. A Jacobian is evaluated to estimate the impact of each input (SSH, SST) on the NN chlorophyll-a estimates. The differences between an ensemble of NNs vs a single NN are examined. After the NN is trained for the SeaWiFS period, the NN is then applied and validated for 2005-2015, a period covered by other satellite missions — the Moderate Resolution Imaging Spectroradiometer (MODIS AQUA) and the Visible Imaging Infrared Radiometer Suite (VIIRS).

A forester's look at the application of image manipulation techniques to multitemporal Landsat data

NASA Technical Reports Server (NTRS)

Williams, D. L.; Stauffer, M. L.; Leung, K. C.

1979-01-01

Registered, multitemporal Landsat data of a study area in central Pennsylvania were analyzed to detect and assess changes in the forest canopy resulting from insect defoliation. Images taken July 19, 1976, and June 27, 1977, were chosen specifically to represent forest canopy conditions before and after defoliation, respectively. Several image manipulation and data transformation techniques, developed primarily for estimating agricultural and rangeland standing green biomass, were applied to these data. The applicability of each technique for estimating the severity of forest canopy defoliation was then evaluated. All techniques tested had highly correlated results. In all cases, heavy defoliation was discriminated from healthy forest. Areas of moderate defoliation were confused with healthy forest on northwest (NW) aspects, but were distinct from healthy forest conditions on southeast (SE)-facing slopes.

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Comparison of diffusion length measurements from the Flying Spot Technique and the photocarrier grating method in amorphous thin films

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

Vieira, M.; Fantoni, A.; Martins, R.

1994-12-31

Using the Flying Spot Technique (FST) the authors have studied minority carrier transport parallel and perpendicular to the surface of amorphous silicon films (a-Si:H). To reduce slow transients due to charge redistribution in low resistivity regions during the measurement they have applied a strong homogeneously absorbed bias light. The defect density was estimated from Constant Photocurrent Method (CPM) measurements. The steady-state photocarrier grating technique (SSPG) is a 1-dimensional approach. However, the modulation depth of the carrier profile is also dependent on film surface properties, like surface recombination velocity. Both methods yield comparable diffusion lengths when applied to a-Si:H.

Simultaneous narrowband ultrasonic strain-flow imaging

NASA Astrophysics Data System (ADS)

Tsou, Jean K.; Mai, Jerome J.; Lupotti, Fermin A.; Insana, Michael F.

2004-04-01

We are summarizing new research aimed at forming spatially and temporally registered combinations of strain and color-flow images using echo data recorded from a commercial ultrasound system. Applications include diagnosis of vascular diseases and tumor malignancies. The challenge is to meet the diverse needs of each measurement. The approach is to first apply eigenfilters that separate echo components from moving tissues and blood flow, and then estimate blood velocity and tissue displacement from the filtered-IQ-signal phase modulations. At the cost of a lower acquisition frame rate, we find the autocorrelation strain estimator yields higher resolution strain estimate than the cross-correlator since estimates are made from ensembles at a single point in space. The technique is applied to in vivo carotid imaging, to demonstrate the sensitivity for strain-flow vascular imaging.

A Technical Assessment of Seismic Yield Estimation. Appendix. Part 1

DTIC Science & Technology

1981-01-01

Heamberger, California Institute of Technology, Pasadena "Near Source Effects on P-Waves" 14. John G. Trulio, Applied Theory, Inc.., Los Angeles...to be reported - hence users may apply their own techniques. We expect the NEIS to report several additional magnitudes, where applicable, in the...and there is still uncertainty concerning the effectiveness of such corrections if applied to various aseismic regions. (I don’t know if anyone has even

Ar+ and CuBr laser-assisted chemical bleaching of teeth: estimation of whiteness degree

NASA Astrophysics Data System (ADS)

Dimitrov, S.; Todorovska, Roumyana; Gizbrecht, Alexander I.; Raychev, L.; Petrov, Lyubomir P.

2003-11-01

In this work the results of adaptation of impartial methods for color determination aimed at developing of techniques for estimation of human teeth whiteness degree, sufficiently handy for common use in clinical practice are presented. For approbation and by the way of illustration of the techniques, standards of teeth colors were used as well as model and naturally discolored human teeth treated by two bleaching chemical compositions activated by three light sources each: Ar+ and CuBr lasers, and a standard halogen photopolymerization lamp. Typical reflection and fluorescence spectra of some samples are presented; the samples colors were estimated by a standard computer processing in RGB and B coordinates. The results of the applied spectral and colorimetric techniques are in a good agreement with those of the standard computer processing of the corresponding digital photographs and complies with the visually estimated degree of the teeth whiteness judged according to the standard reference scale commonly used in the aesthetic dentistry.

Applications of physiological bases of ageing to forensic sciences. Estimation of age-at-death.

PubMed

C Zapico, Sara; Ubelaker, Douglas H

2013-03-01

Age-at-death estimation is one of the main challenges in forensic sciences since it contributes to the identification of individuals. There are many anthropological techniques to estimate the age at death in children and adults. However, in adults this methodology is less accurate and requires population specific references. For that reason, new methodologies have been developed. Biochemical methods are based on the natural process of ageing, which induces different biochemical changes that lead to alterations in cells and tissues. In this review, we describe different attempts to estimate the age in adults based on these changes. Chemical approaches imply modifications in molecules or accumulation of some products. Molecular biology approaches analyze the modifications in DNA and chromosomes. Although the most accurate technique appears to be aspartic acid racemization, it is important to take into account the other techniques because the forensic context and the human remains available will determine the possibility to apply one or another methodology. Copyright © 2013 Elsevier B.V. All rights reserved.

Enhanced data reduction of the velocity data on CETA flight experiment. [Crew and Equipment Translation Aid

NASA Technical Reports Server (NTRS)

Finley, Tom D.; Wong, Douglas T.; Tripp, John S.

1993-01-01

A newly developed technique for enhanced data reduction provides an improved procedure that allows least squares minimization to become possible between data sets with an unequal number of data points. This technique was applied in the Crew and Equipment Translation Aid (CETA) experiment on the STS-37 Shuttle flight in April 1991 to obtain the velocity profile from the acceleration data. The new technique uses a least-squares method to estimate the initial conditions and calibration constants. These initial conditions are estimated by least-squares fitting the displacements indicated by the Hall-effect sensor data to the corresponding displacements obtained from integrating the acceleration data. The velocity and displacement profiles can then be recalculated from the corresponding acceleration data using the estimated parameters. This technique, which enables instantaneous velocities to be obtained from the test data instead of only average velocities at varying discrete times, offers more detailed velocity information, particularly during periods of large acceleration or deceleration.

A novel fast and flexible technique of radical kinetic behaviour investigation based on pallet for plasma evaluation structure and numerical analysis

NASA Astrophysics Data System (ADS)

Malinowski, Arkadiusz; Takeuchi, Takuya; Chen, Shang; Suzuki, Toshiya; Ishikawa, Kenji; Sekine, Makoto; Hori, Masaru; Lukasiak, Lidia; Jakubowski, Andrzej

2013-07-01

This paper describes a new, fast, and case-independent technique for sticking coefficient (SC) estimation based on pallet for plasma evaluation (PAPE) structure and numerical analysis. Our approach does not require complicated structure, apparatus, or time-consuming measurements but offers high reliability of data and high flexibility. Thermal analysis is also possible. This technique has been successfully applied to estimation of very low value of SC of hydrogen radicals on chemically amplified ArF 193 nm photoresist (the main goal of this study). Upper bound of our technique has been determined by investigation of SC of fluorine radical on polysilicon (in elevated temperature). Sources of estimation error and ways of its reduction have been also discussed. Results of this study give an insight into the process kinetics, and not only they are helpful in better process understanding but additionally they may serve as parameters in a phenomenological model development for predictive modelling of etching for ultimate CMOS topography simulation.

Technique for simulating peak-flow hydrographs in Maryland

USGS Publications Warehouse

Dillow, Jonathan J.A.

1998-01-01

The efficient design and management of many bridges, culverts, embankments, and flood-protection structures may require the estimation of time-of-inundation and (or) storage of floodwater relating to such structures. These estimates can be made on the basis of information derived from the peak-flow hydrograph. Average peak-flow hydrographs corresponding to a peak discharge of specific recurrence interval can be simulated for drainage basins having drainage areas less than 500 square miles in Maryland, using a direct technique of known accuracy. The technique uses dimensionless hydrographs in conjunction with estimates of basin lagtime and instantaneous peak flow. Ordinary least-squares regression analysis was used to develop an equation for estimating basin lagtime in Maryland. Drainage area, main channel slope, forest cover, and impervious area were determined to be the significant explanatory variables necessary to estimate average basin lagtime at the 95-percent confidence interval. Qualitative variables included in the equation adequately correct for geographic bias across the State. The average standard error of prediction associated with the equation is approximated as plus or minus (+/-) 37.6 percent. Volume correction factors may be applied to the basin lagtime on the basis of a comparison between actual and estimated hydrograph volumes prior to hydrograph simulation. Three dimensionless hydrographs were developed and tested using data collected during 278 significant rainfall-runoff events at 81 stream-gaging stations distributed throughout Maryland and Delaware. The data represent a range of drainage area sizes and basin conditions. The technique was verified by applying it to the simulation of 20 peak-flow events and comparing actual and simulated hydrograph widths at 50 and 75 percent of the observed peak-flow levels. The events chosen are considered extreme in that the average recurrence interval of the selected peak flows is 130 years. The average standard errors of prediction were +/- 61 and +/- 56 percent at the 50 and 75 percent of peak-flow hydrograph widths, respectively.

Estimating Uncertainties of Ship Course and Speed in Early Navigations using ICOADS3.0

NASA Astrophysics Data System (ADS)

Chan, D.; Huybers, P. J.

2017-12-01

Information on ship position and its uncertainty is potentially important for mapping out climatologists and changes in SSTs. Using the 2-hourly ship reports from the International Comprehensive Ocean Atmosphere Dataset 3.0 (ICOADS 3.0), we estimate the uncertainties of ship course, ship speed, and latitude/longitude corrections during 1870-1900. After reviewing the techniques used in early navigations, we build forward navigation model that uses dead reckoning technique, celestial latitude corrections, and chronometer longitude corrections. The modeled ship tracks exhibit jumps in longitude and latitude, when a position correction is applied. These jumps are also seen in ICOADS3.0 observations. In this model, position error at the end of each day increases following a 2D random walk; the latitudinal/longitude errors are reset when a latitude/longitude correction is applied.We fit the variance of the magnitude of latitude/longitude corrections in the observation against model outputs, and estimate that the standard deviation of uncertainty is 5.5 degree for ship course, 32% for ship speed, 22km for latitude correction, and 27km for longitude correction. The estimates here are informative priors for Bayesian methods that quantify position errors of individual tracks.

Estimation of vibration frequency of loudspeaker diaphragm by parallel phase-shifting digital holography

NASA Astrophysics Data System (ADS)

Kakue, T.; Endo, Y.; Shimobaba, T.; Ito, T.

2014-11-01

We report frequency estimation of loudspeaker diaphragm vibrating at high speed by parallel phase-shifting digital holography which is a technique of single-shot phase-shifting interferometry. This technique records multiple phaseshifted holograms required for phase-shifting interferometry by using space-division multiplexing. We constructed a parallel phase-shifting digital holography system consisting of a high-speed polarization-imaging camera. This camera has a micro-polarizer array which selects four linear polarization axes for 2 × 2 pixels. We set a loudspeaker as an object, and recorded vibration of diaphragm of the loudspeaker by the constructed system. By the constructed system, we demonstrated observation of vibration displacement of loudspeaker diaphragm. In this paper, we aim to estimate vibration frequency of the loudspeaker diaphragm by applying the experimental results to frequency analysis. Holograms consisting of 128 × 128 pixels were recorded at a frame rate of 262,500 frames per second by the camera. A sinusoidal wave was input to the loudspeaker via a phone connector. We observed displacement of the loudspeaker diaphragm vibrating by the system. We also succeeded in estimating vibration frequency of the loudspeaker diaphragm by applying frequency analysis to the experimental results.

Results and Error Estimates from GRACE Forward Modeling over Greenland, Canada, and Alaska

NASA Astrophysics Data System (ADS)

Bonin, J. A.; Chambers, D. P.

2012-12-01

Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Greenland and Antarctica. However, the accuracy of the forward model technique has not been determined, nor is it known how the distribution of the local basins affects the results. We use a "truth" model composed of hydrology and ice-melt slopes as an example case, to estimate the uncertainties of this forward modeling method and expose those design parameters which may result in an incorrect high-resolution mass distribution. We then apply these optimal parameters in a forward model estimate created from RL05 GRACE data. We compare the resulting mass slopes with the expected systematic errors from the simulation, as well as GIA and basic trend-fitting uncertainties. We also consider whether specific regions (such as Ellesmere Island and Baffin Island) can be estimated reliably using our optimal basin layout.

Earth Observation System Flight Dynamics System Covariance Realism

NASA Technical Reports Server (NTRS)

Zaidi, Waqar H.; Tracewell, David

2016-01-01

This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.

Mapping ecological risks with a portfolio-based technique: incorporating uncertainty and decision-making preferences

Treesearch

Denys Yemshanov; Frank H. Koch; Mark Ducey; Klaus Koehler

2013-01-01

Geographic mapping of risks is a useful analytical step in ecological risk assessments and in particular, in analyses aimed to estimate risks associated with introductions of invasive organisms. In this paper, we approach invasive species risk mapping as a portfolio allocation problem and apply techniques from decision theory to build an invasion risk map that combines...

A Novel Technique Applying Spectral Estimation to Johnson Noise Thermometry

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

Ezell, N. Dianne Bull; Britton, Chuck; Ericson, Nance

Johnson noise thermometry is one of many important measurement techniques used to monitor the safety levels and stability in a nuclear reactor. However, this measurement is very dependent on the minimal electromagnetic environment. Properly removing unwanted electromagnetic interference (EMI) is critical for accurate drift-free temperature measurements. The two techniques developed by Oak Ridge National Laboratory (ORNL) to remove transient and periodic EMI are briefly discussed here. Spectral estimation is a key component in the signal processing algorithm used for EMI removal and temperature calculation. The cross-power spectral density is a key component in the Johnson noise temperature computation. Applying eithermore » technique requires the simple addition of electronics and signal processing to existing resistive thermometers. With minimal installation changes, the system discussed here can be installed on existing nuclear power plants. The Johnson noise system developed is tested at three locations: ORNL, Sandia National Laboratory, and the Tennessee Valley Authority’s Kingston Fossil Plant. Each of these locations enabled improvement on the EMI removal algorithm. Finally, the conclusions made from the results at each of these locations is discussed, as well as possible future work.« less

A Novel Technique Applying Spectral Estimation to Johnson Noise Thermometry

DOE PAGES

Ezell, N. Dianne Bull; Britton, Chuck; Ericson, Nance; ...

2018-03-30

Johnson noise thermometry is one of many important measurement techniques used to monitor the safety levels and stability in a nuclear reactor. However, this measurement is very dependent on the minimal electromagnetic environment. Properly removing unwanted electromagnetic interference (EMI) is critical for accurate drift-free temperature measurements. The two techniques developed by Oak Ridge National Laboratory (ORNL) to remove transient and periodic EMI are briefly discussed here. Spectral estimation is a key component in the signal processing algorithm used for EMI removal and temperature calculation. The cross-power spectral density is a key component in the Johnson noise temperature computation. Applying eithermore » technique requires the simple addition of electronics and signal processing to existing resistive thermometers. With minimal installation changes, the system discussed here can be installed on existing nuclear power plants. The Johnson noise system developed is tested at three locations: ORNL, Sandia National Laboratory, and the Tennessee Valley Authority’s Kingston Fossil Plant. Each of these locations enabled improvement on the EMI removal algorithm. Finally, the conclusions made from the results at each of these locations is discussed, as well as possible future work.« less

Kinematic Measurement of Knee Prosthesis from Single-Plane Projection Images

NASA Astrophysics Data System (ADS)

Hirokawa, Shunji; Ariyoshi, Shogo; Takahashi, Kenji; Maruyama, Koichi

In this paper, the measurement of 3D motion from 2D perspective projections of knee prosthesis is described. The technique reported by Banks and Hodge was further developed in this study. The estimation was performed in two steps. The first-step estimation was performed on the assumption of orthogonal projection. Then, the second-step estimation was subsequently carried out based upon the perspective projection to accomplish more accurate estimation. The simulation results have demonstrated that the technique archived sufficient accuracies of position/orientation estimation for prosthetic kinematics. Then we applied our algorithm to the CCD images, thereby examining the influences of various artifacts, possibly incorporated through an imaging process, on the estimation accuracies. We found that accuracies in the experiment were influenced mainly by the geometric discrepancies between the prosthesis component and computer generated model and by the spacial inconsistencies between the coordinate axes of the positioner and that of the computer model. However, we verified that our algorithm could achieve proper and consistent estimation even for the CCD images.

Energy and maximum norm estimates for nonlinear conservation laws

NASA Technical Reports Server (NTRS)

Olsson, Pelle; Oliger, Joseph

1994-01-01

We have devised a technique that makes it possible to obtain energy estimates for initial-boundary value problems for nonlinear conservation laws. The two major tools to achieve the energy estimates are a certain splitting of the flux vector derivative f(u)(sub x), and a structural hypothesis, referred to as a cone condition, on the flux vector f(u). These hypotheses are fulfilled for many equations that occur in practice, such as the Euler equations of gas dynamics. It should be noted that the energy estimates are obtained without any assumptions on the gradient of the solution u. The results extend to weak solutions that are obtained as point wise limits of vanishing viscosity solutions. As a byproduct we obtain explicit expressions for the entropy function and the entropy flux of symmetrizable systems of conservation laws. Under certain circumstances the proposed technique can be applied repeatedly so as to yield estimates in the maximum norm.

Simultaneous multiple non-crossing quantile regression estimation using kernel constraints

PubMed Central

Liu, Yufeng; Wu, Yichao

2011-01-01

Quantile regression (QR) is a very useful statistical tool for learning the relationship between the response variable and covariates. For many applications, one often needs to estimate multiple conditional quantile functions of the response variable given covariates. Although one can estimate multiple quantiles separately, it is of great interest to estimate them simultaneously. One advantage of simultaneous estimation is that multiple quantiles can share strength among them to gain better estimation accuracy than individually estimated quantile functions. Another important advantage of joint estimation is the feasibility of incorporating simultaneous non-crossing constraints of QR functions. In this paper, we propose a new kernel-based multiple QR estimation technique, namely simultaneous non-crossing quantile regression (SNQR). We use kernel representations for QR functions and apply constraints on the kernel coefficients to avoid crossing. Both unregularised and regularised SNQR techniques are considered. Asymptotic properties such as asymptotic normality of linear SNQR and oracle properties of the sparse linear SNQR are developed. Our numerical results demonstrate the competitive performance of our SNQR over the original individual QR estimation. PMID:22190842

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

PubMed

Sim, K S; Kiani, M A; Nia, M E; Tso, C P

2014-01-01

A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Kernel and divergence techniques in high energy physics separations

NASA Astrophysics Data System (ADS)

Bouř, Petr; Kůs, Václav; Franc, Jiří

2017-10-01

Binary decision trees under the Bayesian decision technique are used for supervised classification of high-dimensional data. We present a great potential of adaptive kernel density estimation as the nested separation method of the supervised binary divergence decision tree. Also, we provide a proof of alternative computing approach for kernel estimates utilizing Fourier transform. Further, we apply our method to Monte Carlo data set from the particle accelerator Tevatron at DØ experiment in Fermilab and provide final top-antitop signal separation results. We have achieved up to 82 % AUC while using the restricted feature selection entering the signal separation procedure.

Conducting Meta-Analyses Based on p Values

PubMed Central

van Aert, Robbie C. M.; Wicherts, Jelte M.; van Assen, Marcel A. L. M.

2016-01-01

Because of overwhelming evidence of publication bias in psychology, techniques to correct meta-analytic estimates for such bias are greatly needed. The methodology on which the p-uniform and p-curve methods are based has great promise for providing accurate meta-analytic estimates in the presence of publication bias. However, in this article, we show that in some situations, p-curve behaves erratically, whereas p-uniform may yield implausible estimates of negative effect size. Moreover, we show that (and explain why) p-curve and p-uniform result in overestimation of effect size under moderate-to-large heterogeneity and may yield unpredictable bias when researchers employ p-hacking. We offer hands-on recommendations on applying and interpreting results of meta-analyses in general and p-uniform and p-curve in particular. Both methods as well as traditional methods are applied to a meta-analysis on the effect of weight on judgments of importance. We offer guidance for applying p-uniform or p-curve using R and a user-friendly web application for applying p-uniform. PMID:27694466

A new data assimilation engine for physics-based thermospheric density models

NASA Astrophysics Data System (ADS)

Sutton, E. K.; Henney, C. J.; Hock-Mysliwiec, R.

2017-12-01

The successful assimilation of data into physics-based coupled Ionosphere-Thermosphere models requires rethinking the filtering techniques currently employed in fields such as tropospheric weather modeling. In the realm of Ionospheric-Thermospheric modeling, the estimation of system drivers is a critical component of any reliable data assimilation technique. How to best estimate and apply these drivers, however, remains an open question and active area of research. The recently developed method of Iterative Re-Initialization, Driver Estimation and Assimilation (IRIDEA) accounts for the driver/response time-delay characteristics of the Ionosphere-Thermosphere system relative to satellite accelerometer observations. Results from two near year-long simulations are shown: (1) from a period of elevated solar and geomagnetic activity during 2003, and (2) from a solar minimum period during 2007. This talk will highlight the challenges and successes of implementing a technique suited for both solar min and max, as well as expectations for improving neutral density forecasts.

Variational Bayesian Parameter Estimation Techniques for the General Linear Model

PubMed Central

Starke, Ludger; Ostwald, Dirk

2017-01-01

Variational Bayes (VB), variational maximum likelihood (VML), restricted maximum likelihood (ReML), and maximum likelihood (ML) are cornerstone parametric statistical estimation techniques in the analysis of functional neuroimaging data. However, the theoretical underpinnings of these model parameter estimation techniques are rarely covered in introductory statistical texts. Because of the widespread practical use of VB, VML, ReML, and ML in the neuroimaging community, we reasoned that a theoretical treatment of their relationships and their application in a basic modeling scenario may be helpful for both neuroimaging novices and practitioners alike. In this technical study, we thus revisit the conceptual and formal underpinnings of VB, VML, ReML, and ML and provide a detailed account of their mathematical relationships and implementational details. We further apply VB, VML, ReML, and ML to the general linear model (GLM) with non-spherical error covariance as commonly encountered in the first-level analysis of fMRI data. To this end, we explicitly derive the corresponding free energy objective functions and ensuing iterative algorithms. Finally, in the applied part of our study, we evaluate the parameter and model recovery properties of VB, VML, ReML, and ML, first in an exemplary setting and then in the analysis of experimental fMRI data acquired from a single participant under visual stimulation. PMID:28966572

Real-Time Airborne Gamma-Ray Background Estimation Using NASVD with MLE and Radiation Transport for Calibration

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

Kulisek, Jonathan A.; Schweppe, John E.; Stave, Sean C.

2015-06-01

Helicopter-mounted gamma-ray detectors can provide law enforcement officials the means to quickly and accurately detect, identify, and locate radiological threats over a wide geographical area. The ability to accurately distinguish radiological threat-generated gamma-ray signatures from background gamma radiation in real time is essential in order to realize this potential. This problem is non-trivial, especially in urban environments for which the background may change very rapidly during flight. This exacerbates the challenge of estimating background due to the poor counting statistics inherent in real-time airborne gamma-ray spectroscopy measurements. To address this, we have developed a new technique for real-time estimation ofmore » background gamma radiation from aerial measurements. This method is built upon on the noise-adjusted singular value decomposition (NASVD) technique that was previously developed for estimating the potassium (K), uranium (U), and thorium (T) concentrations in soil post-flight. The method can be calibrated using K, U, and T spectra determined from radiation transport simulations along with basis functions, which may be determined empirically by applying maximum likelihood estimation (MLE) to previously measured airborne gamma-ray spectra. The method was applied to both measured and simulated airborne gamma-ray spectra, with and without man-made radiological source injections. Compared to schemes based on simple averaging, this technique was less sensitive to background contamination from the injected man-made sources and may be particularly useful when the gamma-ray background frequently changes during the course of the flight.« less

Center of Excellence for Applied Mathematical and Statistical Research in support of development of multicrop production monitoring capability

NASA Technical Reports Server (NTRS)

Woodward, W. A.; Gray, H. L.

1983-01-01

Efforts in support of the development of multicrop production monitoring capability are reported. In particular, segment level proportion estimation techniques based upon a mixture model were investigated. Efforts have dealt primarily with evaluation of current techniques and development of alternative ones. A comparison of techniques is provided on both simulated and LANDSAT data along with an analysis of the quality of profile variables obtained from LANDSAT data.

Rigorous Approach in Investigation of Seismic Structure and Source Characteristicsin Northeast Asia: Hierarchical and Trans-dimensional Bayesian Inversion

NASA Astrophysics Data System (ADS)

Mustac, M.; Kim, S.; Tkalcic, H.; Rhie, J.; Chen, Y.; Ford, S. R.; Sebastian, N.

2015-12-01

Conventional approaches to inverse problems suffer from non-linearity and non-uniqueness in estimations of seismic structures and source properties. Estimated results and associated uncertainties are often biased by applied regularizations and additional constraints, which are commonly introduced to solve such problems. Bayesian methods, however, provide statistically meaningful estimations of models and their uncertainties constrained by data information. In addition, hierarchical and trans-dimensional (trans-D) techniques are inherently implemented in the Bayesian framework to account for involved error statistics and model parameterizations, and, in turn, allow more rigorous estimations of the same. Here, we apply Bayesian methods throughout the entire inference process to estimate seismic structures and source properties in Northeast Asia including east China, the Korean peninsula, and the Japanese islands. Ambient noise analysis is first performed to obtain a base three-dimensional (3-D) heterogeneity model using continuous broadband waveforms from more than 300 stations. As for the tomography of surface wave group and phase velocities in the 5-70 s band, we adopt a hierarchical and trans-D Bayesian inversion method using Voronoi partition. The 3-D heterogeneity model is further improved by joint inversions of teleseismic receiver functions and dispersion data using a newly developed high-efficiency Bayesian technique. The obtained model is subsequently used to prepare 3-D structural Green's functions for the source characterization. A hierarchical Bayesian method for point source inversion using regional complete waveform data is applied to selected events from the region. The seismic structure and source characteristics with rigorously estimated uncertainties from the novel Bayesian methods provide enhanced monitoring and discrimination of seismic events in northeast Asia.

ECO-ITS : Intelligent Transportation System Applications to Improve Environmental Performance

DOT National Transportation Integrated Search

2012-05-01

This report describes recent research supported by the US DOTs AERIS program, building upon existing work through developing and improving data collection methods, developing new data fusion techniques to improve estimates, and applying appropriat...

POSTPROCESSING MIXED FINITE ELEMENT METHODS FOR SOLVING CAHN-HILLIARD EQUATION: METHODS AND ERROR ANALYSIS

PubMed Central

Wang, Wansheng; Chen, Long; Zhou, Jie

2015-01-01

A postprocessing technique for mixed finite element methods for the Cahn-Hilliard equation is developed and analyzed. Once the mixed finite element approximations have been computed at a fixed time on the coarser mesh, the approximations are postprocessed by solving two decoupled Poisson equations in an enriched finite element space (either on a finer grid or a higher-order space) for which many fast Poisson solvers can be applied. The nonlinear iteration is only applied to a much smaller size problem and the computational cost using Newton and direct solvers is negligible compared with the cost of the linear problem. The analysis presented here shows that this technique remains the optimal rate of convergence for both the concentration and the chemical potential approximations. The corresponding error estimate obtained in our paper, especially the negative norm error estimates, are non-trivial and different with the existing results in the literatures. PMID:27110063

Estimation of minimum miscibility pressure (MMP) of CO2 and liquid n-alkane systems using an improved MRI technique.

PubMed

Liu, Yu; Jiang, Lanlan; Song, Yongchen; Zhao, Yuechao; Zhang, Yi; Wang, Dayong

2016-02-01

Minimum miscible pressure (MMP) of gas and oil system is a key parameter for the injection system design of CO2 miscible flooding. Some industrial standard approaches such as the experiment using a rising bubble apparatus (RBA), the slim tube tests (STT), the pressure-density diagram (PDD), etc. have been applied for decades to determine the MMP of gas and oil. Some theoretical or experiential calculations of the MMP were also applied to the gas-oil miscible system. In the present work, an improved technique based on our previous research for the estimation of the MMP by using magnetic resonance imaging (MRI) was proposed. This technique was then applied to the CO2 and n-alkane binary and ternary systems to observe the mixing procedure and to study the miscibility. MRI signal intensities, which represent the proton concentration of n-alkane in both the hydrocarbon rich phase and the CO2 rich phase, were plotted as a reference for determining the MMP. The accuracy of the MMP obtained by using this improved technique was enhanced comparing with the data obtained from our previous works. The results also show good agreement with other established techniques (such as the STT) in previous published works. It demonstrates increases of MMPs as the temperature rise from 20 °C to 37.8 °C. The MMPs of CO2 and n-alkane systems are also found to be proportional to the carbon number in the range of C10 to C14. Copyright © 2015 Elsevier Inc. All rights reserved.

Practical aspects of a maximum likelihood estimation method to extract stability and control derivatives from flight data

NASA Technical Reports Server (NTRS)

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

1976-01-01

A maximum likelihood estimation method was applied to flight data and procedures to facilitate the routine analysis of a large amount of flight data were described. Techniques that can be used to obtain stability and control derivatives from aircraft maneuvers that are less than ideal for this purpose are described. The techniques involve detecting and correcting the effects of dependent or nearly dependent variables, structural vibration, data drift, inadequate instrumentation, and difficulties with the data acquisition system and the mathematical model. The use of uncertainty levels and multiple maneuver analysis also proved to be useful in improving the quality of the estimated coefficients. The procedures used for editing the data and for overall analysis are also discussed.

Mass estimating techniques for earth-to-orbit transports with various configuration factors and technologies applied

NASA Technical Reports Server (NTRS)

Klich, P. J.; Macconochie, I. O.

1979-01-01

A study of an array of advanced earth-to-orbit space transportation systems with a focus on mass properties and technology requirements is presented. Methods of estimating weights of these vehicles differ from those used for commercial and military aircraft; the new techniques emphasizing winged horizontal and vertical takeoff advanced systems are described utilizing the space shuttle subsystem data base for the weight estimating equations. The weight equations require information on mission profile, the structural materials, the thermal protection system, and the ascent propulsion system, allowing for the type of construction and various propellant tank shapes. The overall system weights are calculated using this information and incorporated into the Systems Engineering Mass Properties Computer Program.

Estimating the size of an open population using sparse capture-recapture data.

PubMed

Huggins, Richard; Stoklosa, Jakub; Roach, Cameron; Yip, Paul

2018-03-01

Sparse capture-recapture data from open populations are difficult to analyze using currently available frequentist statistical methods. However, in closed capture-recapture experiments, the Chao sparse estimator (Chao, 1989, Biometrics 45, 427-438) may be used to estimate population sizes when there are few recaptures. Here, we extend the Chao (1989) closed population size estimator to the open population setting by using linear regression and extrapolation techniques. We conduct a small simulation study and apply the models to several sparse capture-recapture data sets. © 2017, The International Biometric Society.

Speckle noise reduction in quantitative optical metrology techniques by application of the discrete wavelet transformation

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

2002-06-01

Effective suppression of speckle noise content in interferometric data images can help in improving accuracy and resolution of the results obtained with interferometric optical metrology techniques. In this paper, novel speckle noise reduction algorithms based on the discrete wavelet transformation are presented. The algorithms proceed by: (a) estimating the noise level contained in the interferograms of interest, (b) selecting wavelet families, (c) applying the wavelet transformation using the selected families, (d) wavelet thresholding, and (e) applying the inverse wavelet transformation, producing denoised interferograms. The algorithms are applied to the different stages of the processing procedures utilized for generation of quantitative speckle correlation interferometry data of fiber-optic based opto-electronic holography (FOBOEH) techniques, allowing identification of optimal processing conditions. It is shown that wavelet algorithms are effective for speckle noise reduction while preserving image features otherwise faded with other algorithms.

Large-scale precipitation estimation using Kalpana-1 IR measurements and its validation using GPCP and GPCC data

NASA Astrophysics Data System (ADS)

Prakash, Satya; Mahesh, C.; Gairola, Rakesh M.

2011-12-01

Large-scale precipitation estimation is very important for climate science because precipitation is a major component of the earth's water and energy cycles. In the present study, the GOES precipitation index technique has been applied to the Kalpana-1 satellite infrared (IR) images of every three-hourly, i.e., of 0000, 0300, 0600,…., 2100 hours UTC, for rainfall estimation as a preparatory to the INSAT-3D. After the temperatures of all the pixels in a grid are known, they are distributed to generate a three-hourly 24-class histogram of brightness temperatures of IR (10.5-12.5 μm) images for a 1.0° × 1.0° latitude/longitude box. The daily, monthly, and seasonal rainfall have been estimated using these three-hourly rain estimates for the entire south-west monsoon period of 2009 in the present study. To investigate the potential of these rainfall estimates, the validation of monthly and seasonal rainfall estimates has been carried out using the Global Precipitation Climatology Project and Global Precipitation Climatology Centre data. The validation results show that the present technique works very well for the large-scale precipitation estimation qualitatively as well as quantitatively. The results also suggest that the simple IR-based estimation technique can be used to estimate rainfall for tropical areas at a larger temporal scale for climatological applications.

Feasibility study for automatic reduction of phase change imagery

NASA Technical Reports Server (NTRS)

Nossaman, G. O.

1971-01-01

The feasibility of automatically reducing a form of pictorial aerodynamic heating data is discussed. The imagery, depicting the melting history of a thin coat of fusible temperature indicator painted on an aerodynamically heated model, was previously reduced by manual methods. Careful examination of various lighting theories and approaches led to an experimentally verified illumination concept capable of yielding high-quality imagery. Both digital and video image processing techniques were applied to reduction of the data, and it was demonstrated that either method can be used to develop superimposed contours. Mathematical techniques were developed to find the model-to-image and the inverse image-to-model transformation using six conjugate points, and methods were developed using these transformations to determine heating rates on the model surface. A video system was designed which is able to reduce the imagery rapidly, economically and accurately. Costs for this system were estimated. A study plan was outlined whereby the mathematical transformation techniques developed to produce model coordinate heating data could be applied to operational software, and methods were discussed and costs estimated for obtaining the digital information necessary for this software.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

Scale effects on the evapotranspiration estimation over a water-controlled Mediterranean ecosystem and its influence on hydrological modelling

NASA Astrophysics Data System (ADS)

Carpintero, Elisabet; González-Dugo, María P.; José Polo, María; Hain, Christopher; Nieto, Héctor; Gao, Feng; Andreu, Ana; Kustas, William; Anderson, Martha

2017-04-01

The integration of currently available satellite data into surface energy balance models can provide estimates of evapotranspiration (ET) with spatial and temporal resolutions determined by sensor characteristics. The use of data fusion techniques may increase the temporal resolution of these estimates using multiple satellites, providing a more frequent ET monitoring for hydrological purposes. The objective of this work is to analyze the effects of pixel resolution on the estimation of evapotranspiration using different remote sensing platforms, and to provide continuous monitoring of ET over a water-controlled ecosystem, the Holm oak savanna woodland known as dehesa. It is an agroforestry system with a complex canopy structure characterized by widely-spaced oak trees combined with crops, pasture and shrubs. The study was carried out during two years, 2013 and 2014, combining ET estimates at different spatial and temporal resolutions and applying data fusion techniques for a frequent monitoring of water use at fine spatial resolution. A global and daily ET product at 5 km resolution, developed with the ALEXI model using MODIS day-night temperature difference (Anderson et al., 2015a) was used as a starting point. The associated flux disaggregation scheme, DisALEXI (Norman et al., 2003), was later applied to constrain higher resolution ET from both MODIS and Landsat 7/8 images. The Climate Forecast System Reanalysis (CFSR) provided the meteorological data. Finally, a data fusion technique, the STARFM model (Gao et al., 2006), was applied to fuse MODIS and Landsat ET maps in order to obtain daily ET at 30 m resolution. These estimates were validated and analyzed at two different scales: at local scale over a dehesa experimental site and at watershed scale with a predominant Mediterranean oak savanna landscape, both located in Southern Spain. Local ET estimates from the modeling system were validated with measurements provided by an eddy covariance tower installed in the dehesa (38 ° 12 'N, 4 ° 17' W, 736 m a.s.l.). The results supported the ability of ALEXI/DisALEXI model to accurately estimate turbulent and radiative fluxes over this complex landscape, both at 1 Km and at 30 m spatial resolution. The application of the STARFM model gave significant improvement in capturing the spatio-temporal heterogeneity of ET over the different seasons, compared with traditional interpolation methods using MODIS and Landsat ET data. At basin scale, the physically-based distributed hydrological model WiMMed has been applied to evaluate ET estimates. This model focuses on the spatial interpolation of the meteorological variables and the physical modelling of the daily water balance at the cell and watershed scale, using daily streamflow rates measured at the watershed outlet for final comparison.

Reverberation Modelling Using a Parabolic Equation Method

DTIC Science & Technology

2012-10-01

the limits of their applicability. Results: Transmission loss estimates produced by the PECan parabolic equation acoustic model were used in...environments is possible when used in concert with a parabolic equation passive acoustic model . Future plans: The authors of this report recommend further...technique using other types of acoustic models should be undertaken. Furthermore, as the current method when applied as-is results in estimates that reflect

Comparing Approaches to Deal With Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

NASA Astrophysics Data System (ADS)

Cecinati, F.; Wani, O.; Rico-Ramirez, M. A.

2017-11-01

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

PubMed

Olivari, Mario; Nieuwenhuizen, Frank M; Venrooij, Joost; Bülthoff, Heinrich H; Pollini, Lorenzo

2015-12-01

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

Estimating Sobol Sensitivity Indices Using Correlations

EPA Science Inventory

Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on...

Roughness Measurement of Dental Materials

NASA Astrophysics Data System (ADS)

Shulev, Assen; Roussev, Ilia; Karpuzov, Simeon; Stoilov, Georgi; Ignatova, Detelina; See, Constantin von; Mitov, Gergo

2016-06-01

This paper presents a roughness measurement of zirconia ceramics, widely used for dental applications. Surface roughness variations caused by the most commonly used dental instruments for intraoral grinding and polishing are estimated. The applied technique is simple and utilizes the speckle properties of the scattered laser light. It could be easily implemented even in dental clinic environment. The main criteria for roughness estimation is the average speckle size, which varies with the roughness of zirconia. The algorithm used for the speckle size estimation is based on the normalized autocorrelation approach.

Spatial analysis of groundwater levels using Fuzzy Logic and geostatistical tools

NASA Astrophysics Data System (ADS)

Theodoridou, P. G.; Varouchakis, E. A.; Karatzas, G. P.

2017-12-01

The spatial variability evaluation of the water table of an aquifer provides useful information in water resources management plans. Geostatistical methods are often employed to map the free surface of an aquifer. In geostatistical analysis using Kriging techniques the selection of the optimal variogram is very important for the optimal method performance. This work compares three different criteria to assess the theoretical variogram that fits to the experimental one: the Least Squares Sum method, the Akaike Information Criterion and the Cressie's Indicator. Moreover, variable distance metrics such as the Euclidean, Minkowski, Manhattan, Canberra and Bray-Curtis are applied to calculate the distance between the observation and the prediction points, that affects both the variogram calculation and the Kriging estimator. A Fuzzy Logic System is then applied to define the appropriate neighbors for each estimation point used in the Kriging algorithm. The two criteria used during the Fuzzy Logic process are the distance between observation and estimation points and the groundwater level value at each observation point. The proposed techniques are applied to a data set of 250 hydraulic head measurements distributed over an alluvial aquifer. The analysis showed that the Power-law variogram model and Manhattan distance metric within ordinary kriging provide the best results when the comprehensive geostatistical analysis process is applied. On the other hand, the Fuzzy Logic approach leads to a Gaussian variogram model and significantly improves the estimation performance. The two different variogram models can be explained in terms of a fractional Brownian motion approach and of aquifer behavior at local scale. Finally, maps of hydraulic head spatial variability and of predictions uncertainty are constructed for the area with the two different approaches comparing their advantages and drawbacks.

Application of split window technique to TIMS data

NASA Technical Reports Server (NTRS)

Matsunaga, Tsuneo; Rokugawa, Shuichi; Ishii, Yoshinori

1992-01-01

Absorptions by the atmosphere in thermal infrared region are mainly due to water vapor, carbon dioxide, and ozone. As the content of water vapor in the atmosphere greatly changes according to weather conditions, it is important to know its amount between the sensor and the ground for atmospheric corrections of thermal Infrared Multispectral Scanner (TIMS) data (i.e. radiosonde). On the other hand, various atmospheric correction techniques were already developed for sea surface temperature estimations from satellites. Among such techniques, Split Window technique, now widely used for AVHRR (Advanced Very High Resolution Radiometer), uses no radiosonde or any kind of supplementary data but a difference between observed brightness temperatures in two channels for estimating atmospheric effects. Applications of Split Window technique to TIMS data are discussed because availability of atmospheric profile data is not clear when ASTER operates. After these theoretical discussions, the technique is experimentally applied to TIMS data at three ground targets and results are compared with atmospherically corrected data using LOWTRAN 7 with radiosonde data.

Time-Varying Delay Estimation Applied to the Surface Electromyography Signals Using the Parametric Approach

NASA Astrophysics Data System (ADS)

Luu, Gia Thien; Boualem, Abdelbassit; Duy, Tran Trung; Ravier, Philippe; Butteli, Olivier

Muscle Fiber Conduction Velocity (MFCV) can be calculated from the time delay between the surface electromyographic (sEMG) signals recorded by electrodes aligned with the fiber direction. In order to take into account the non-stationarity during the dynamic contraction (the most daily life situation) of the data, the developed methods have to consider that the MFCV changes over time, which induces time-varying delays and the data is non-stationary (change of Power Spectral Density (PSD)). In this paper, the problem of TVD estimation is considered using a parametric method. First, the polynomial model of TVD has been proposed. Then, the TVD model parameters are estimated by using a maximum likelihood estimation (MLE) strategy solved by a deterministic optimization technique (Newton) and stochastic optimization technique, called simulated annealing (SA). The performance of the two techniques is also compared. We also derive two appropriate Cramer-Rao Lower Bounds (CRLB) for the estimated TVD model parameters and for the TVD waveforms. Monte-Carlo simulation results show that the estimation of both the model parameters and the TVD function is unbiased and that the variance obtained is close to the derived CRBs. A comparison with non-parametric approaches of the TVD estimation is also presented and shows the superiority of the method proposed.

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques.

PubMed

Diwaker, Chander; Tomar, Pradeep; Poonia, Ramesh C; Singh, Vijander

2018-04-10

A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Hybrid estimation of complex systems.

PubMed

Hofbaur, Michael W; Williams, Brian C

2004-10-01

Modern automated systems evolve both continuously and discretely, and hence require estimation techniques that go well beyond the capability of a typical Kalman Filter. Multiple model (MM) estimation schemes track these system evolutions by applying a bank of filters, one for each discrete system mode. Modern systems, however, are often composed of many interconnected components that exhibit rich behaviors, due to complex, system-wide interactions. Modeling these systems leads to complex stochastic hybrid models that capture the large number of operational and failure modes. This large number of modes makes a typical MM estimation approach infeasible for online estimation. This paper analyzes the shortcomings of MM estimation, and then introduces an alternative hybrid estimation scheme that can efficiently estimate complex systems with large number of modes. It utilizes search techniques from the toolkit of model-based reasoning in order to focus the estimation on the set of most likely modes, without missing symptoms that might be hidden amongst the system noise. In addition, we present a novel approach to hybrid estimation in the presence of unknown behavioral modes. This leads to an overall hybrid estimation scheme for complex systems that robustly copes with unforeseen situations in a degraded, but fail-safe manner.

Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Yoo, S. H.

2017-12-01

Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend coda-based techniques to lower magnitude thresholds and low-yield local explosions.

[Historia magistra vitae: on the methods of historical demography].

PubMed

Botev, N

1992-01-01

Indirect estimation techniques are applied to data for Bulgaria from 1891 to 1958 to assess trends in population dynamics. An interdisciplinary approach is suggested for the study of countries where data are often incomplete. (SUMMARY IN ENG AND RUS)

Real-Time Aerodynamic Parameter Estimation without Air Flow Angle Measurements

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.

2010-01-01

A technique for estimating aerodynamic parameters in real time from flight data without air flow angle measurements is described and demonstrated. The method is applied to simulated F-16 data, and to flight data from a subscale jet transport aircraft. Modeling results obtained with the new approach using flight data without air flow angle measurements were compared to modeling results computed conventionally using flight data that included air flow angle measurements. Comparisons demonstrated that the new technique can provide accurate aerodynamic modeling results without air flow angle measurements, which are often difficult and expensive to obtain. Implications for efficient flight testing and flight safety are discussed.

Methods for estimating selected flow-duration and flood-frequency characteristics at ungaged sites in Central Idaho

USGS Publications Warehouse

Kjelstrom, L.C.

1998-01-01

Methods for estimating daily mean discharges for selected flow durations and flood discharge for selected recurrence intervals at ungaged sites in central Idaho were applied using data collected at streamflow-gaging stations in the area. The areal and seasonal variability of discharge from ungaged drainage basins may be described by estimating daily mean discharges that are exceeded 20, 50, and 80 percent of the time each month. At 73 gaging stations, mean monthly discharge was regressed with discharge at three points—20, 50, and 80—from daily mean flow-duration curves for each month. Regression results were improved by dividing the study area into six regions. Previously determined estimates of mean monthly discharge from about 1,200 ungaged drainage basins provided the basis for applying the developed techniques to the ungaged basins. Estimates of daily mean discharges that are exceeded 20, 50, and 80 percent of the time each month at ungaged drainage basins can be made by multiplying mean monthly discharges estimated at ungaged sites by a regression factor for the appropriate region. In general, the flow-duration data were less accurately estimated at discharges exceeded 80 percent of the time than at discharges exceeded 20 percent of the time. Curves drawn through the three points for each of the six regions were most similar in July and most different from December through March. Coefficients of determination of the regressions indicate that differences in mean monthly discharge largely explain differences in discharge at points on the daily mean flow-duration curve. Inherent in the method are errors in the technique used to estimate mean monthly discharge. Flood discharge estimates for selected recurrence intervals at ungaged sites upstream or downstream from gaging stations can be determined by a transfer technique. A weighted ratio of drainage area times flood discharge for selected recurrence intervals at the gaging station can be used to estimate flood discharge at the ungaged site. Best results likely are obtained when the difference between gaged and ungaged drainage areas is small.

Support vector machines for nuclear reactor state estimation

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

Zavaljevski, N.; Gross, K. C.

2000-02-14

Validation of nuclear power reactor signals is often performed by comparing signal prototypes with the actual reactor signals. The signal prototypes are often computed based on empirical data. The implementation of an estimation algorithm which can make predictions on limited data is an important issue. A new machine learning algorithm called support vector machines (SVMS) recently developed by Vladimir Vapnik and his coworkers enables a high level of generalization with finite high-dimensional data. The improved generalization in comparison with standard methods like neural networks is due mainly to the following characteristics of the method. The input data space is transformedmore » into a high-dimensional feature space using a kernel function, and the learning problem is formulated as a convex quadratic programming problem with a unique solution. In this paper the authors have applied the SVM method for data-based state estimation in nuclear power reactors. In particular, they implemented and tested kernels developed at Argonne National Laboratory for the Multivariate State Estimation Technique (MSET), a nonlinear, nonparametric estimation technique with a wide range of applications in nuclear reactors. The methodology has been applied to three data sets from experimental and commercial nuclear power reactor applications. The results are promising. The combination of MSET kernels with the SVM method has better noise reduction and generalization properties than the standard MSET algorithm.« less

Dose rate prediction methodology for remote handled transuranic waste workers at the waste isolation pilot plant.

PubMed

Hayes, Robert

2002-10-01

An approach is described for estimating future dose rates to Waste Isolation Pilot Plant workers processing remote handled transuranic waste. The waste streams will come from the entire U.S. Department of Energy complex and can take on virtually any form found from the processing sequences for defense-related production, radiochemistry, activation and related work. For this reason, the average waste matrix from all generator sites is used to estimate the average radiation fields over the facility lifetime. Innovative new techniques were applied to estimate expected radiation fields. Non-linear curve fitting techniques were used to predict exposure rate profiles from cylindrical sources using closed form equations for lines and disks. This information becomes the basis for Safety Analysis Report dose rate estimates and for present and future ALARA design reviews when attempts are made to reduce worker doses.

Analytic score distributions for a spatially continuous tridirectional Monte Carol transport problem

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

Booth, T.E.

1996-01-01

The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large-score sampling from the score distribution`s tail. Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. Here, the analytic score distribution for the exponential transform applied to a simple, spatially continuous Monte Carlo transport problem is provided.more » Anisotropic scattering and implicit capture are included in the theory. In large part, the analytic score distributions that are derived provide the basis for the ten new statistical quality checks in MCNP.« less

Experiments with recursive estimation in astronomical image processing

NASA Technical Reports Server (NTRS)

Busko, I.

1992-01-01

Recursive estimation concepts were applied to image enhancement problems since the 70's. However, very few applications in the particular area of astronomical image processing are known. These concepts were derived, for 2-dimensional images, from the well-known theory of Kalman filtering in one dimension. The historic reasons for application of these techniques to digital images are related to the images' scanned nature, in which the temporal output of a scanner device can be processed on-line by techniques borrowed directly from 1-dimensional recursive signal analysis. However, recursive estimation has particular properties that make it attractive even in modern days, when big computer memories make the full scanned image available to the processor at any given time. One particularly important aspect is the ability of recursive techniques to deal with non-stationary phenomena, that is, phenomena which have their statistical properties variable in time (or position in a 2-D image). Many image processing methods make underlying stationary assumptions either for the stochastic field being imaged, for the imaging system properties, or both. They will underperform, or even fail, when applied to images that deviate significantly from stationarity. Recursive methods, on the contrary, make it feasible to perform adaptive processing, that is, to process the image by a processor with properties tuned to the image's local statistical properties. Recursive estimation can be used to build estimates of images degraded by such phenomena as noise and blur. We show examples of recursive adaptive processing of astronomical images, using several local statistical properties to drive the adaptive processor, as average signal intensity, signal-to-noise and autocorrelation function. Software was developed under IRAF, and as such will be made available to interested users.

A new similarity measure for link prediction based on local structures in social networks

NASA Astrophysics Data System (ADS)

Aghabozorgi, Farshad; Khayyambashi, Mohammad Reza

2018-07-01

Link prediction is a fundamental problem in social network analysis. There exist a variety of techniques for link prediction which applies the similarity measures to estimate proximity of vertices in the network. Complex networks like social networks contain structural units named network motifs. In this study, a newly developed similarity measure is proposed where these structural units are applied as the source of similarity estimation. This similarity measure is tested through a supervised learning experiment framework, where other similarity measures are compared with this similarity measure. The classification model trained with this similarity measure outperforms others of its kind.

Applying a low energy HPGe detector gamma ray spectrometric technique for the evaluation of Pu/Am ratio in biological samples.

PubMed

Singh, I S; Mishra, Lokpati; Yadav, J R; Nadar, M Y; Rao, D D; Pradeepkumar, K S

2015-10-01

The estimation of Pu/(241)Am ratio in the biological samples is an important input for the assessment of internal dose received by the workers. The radiochemical separation of Pu isotopes and (241)Am in a sample followed by alpha spectrometry is a widely used technique for the determination of Pu/(241)Am ratio. However, this method is time consuming and many times quick estimation is required. In this work, Pu/(241)Am ratio in the biological sample was estimated with HPGe detector based measurements using gamma/X-rays emitted by these radionuclides. These results were compared with those obtained from alpha spectroscopy of sample after radiochemical analysis and found to be in good agreement. Copyright © 2015 Elsevier Ltd. All rights reserved.

Three-dimensional analysis of magnetometer array data

NASA Technical Reports Server (NTRS)

Richmond, A. D.; Baumjohann, W.

1984-01-01

A technique is developed for mapping magnetic variation fields in three dimensions using data from an array of magnetometers, based on the theory of optimal linear estimation. The technique is applied to data from the Scandinavian Magnetometer Array. Estimates of the spatial power spectra for the internal and external magnetic variations are derived, which in turn provide estimates of the spatial autocorrelation functions of the three magnetic variation components. Statistical errors involved in mapping the external and internal fields are quantified and displayed over the mapping region. Examples of field mapping and of separation into external and internal components are presented. A comparison between the three-dimensional field separation and a two-dimensional separation from a single chain of stations shows that significant differences can arise in the inferred internal component.

Rain Volume Estimation over Areas Using Satellite and Radar Data

NASA Technical Reports Server (NTRS)

Doneaud, A. A.; Miller, J. R., Jr.; Johnson, L. R.; Vonderhaar, T. H.; Laybe, P.

1984-01-01

The application of satellite data to a recently developed radar technique used to estimate convective rain volumes over areas on a dry environment (the northern Great Plains) is discussed. The area time integral technique (ATI) provides a means of estimating total rain volumes over fixed and floating target areas of the order of 1,000 to 100,000 km(2) for clusters lasting 40 min. The basis of the method is the existence of a strong correlation between the area coverage integrated over the lifetime of the storm (ATI) and the rain volume. One key element in this technique is that it does not require the consideration of the structure of the radar intensities inside the area coverage to generate rain volumes, but only considers the rain event per se. This fact might reduce or eliminate some sources of error in applying the technique to satellite data. The second key element is that the ATI once determined can be converted to total rain volume by using a constant factor (average rain rate) for a given locale.

Detection and Estimation of Multi-Pulse LFMCW Radar Signals

DTIC Science & Technology

2010-01-01

the Hough transform (HT) of the Wigner - Ville distribution ( WVD ), has been shown to be equivalent to the generalized likelihood ratio test (GLRT...virginia.edu Abstract— The Wigner - Ville Hough transform (WVHT) has been applied to detect and estimate the parameters of linear frequency-modulated...well studied in the literature. One of the most prominent techniques is the Wigner - Ville Hough Transform [8], [9]. The Wigner - Ville Hough transform (WVHT

Methods and Apparatus for Reducing Multipath Signal Error Using Deconvolution

NASA Technical Reports Server (NTRS)

Kumar, Rajendra (Inventor); Lau, Kenneth H. (Inventor)

1999-01-01

A deconvolution approach to adaptive signal processing has been applied to the elimination of signal multipath errors as embodied in one preferred embodiment in a global positioning system receiver. The method and receiver of the present invention estimates then compensates for multipath effects in a comprehensive manner. Application of deconvolution, along with other adaptive identification and estimation techniques, results in completely novel GPS (Global Positioning System) receiver architecture.

Lateral-Directional Parameter Estimation on the X-48B Aircraft Using an Abstracted, Multi-Objective Effector Model

NASA Technical Reports Server (NTRS)

Ratnayake, Nalin A.; Waggoner, Erin R.; Taylor, Brian R.

2011-01-01

The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control effectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of flight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and flight-generated lateral-directional parameter estimation data. A virtual effector model that uses mathematical abstractions to describe the multi-axis effects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cram r-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateral-directional model design for hybrid-wing-body aircraft, as suggested by available flight data. Based on the results of this study, linear regression parameter estimation methods using abstracted effectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task.

Ideal, nonideal, and no-marker variables: The confirmatory factor analysis (CFA) marker technique works when it matters.

PubMed

Williams, Larry J; O'Boyle, Ernest H

2015-09-01

A persistent concern in the management and applied psychology literature is the effect of common method variance on observed relations among variables. Recent work (i.e., Richardson, Simmering, & Sturman, 2009) evaluated 3 analytical approaches to controlling for common method variance, including the confirmatory factor analysis (CFA) marker technique. Their findings indicated significant problems with this technique, especially with nonideal marker variables (those with theoretical relations with substantive variables). Based on their simulation results, Richardson et al. concluded that not correcting for method variance provides more accurate estimates than using the CFA marker technique. We reexamined the effects of using marker variables in a simulation study and found the degree of error in estimates of a substantive factor correlation was relatively small in most cases, and much smaller than error associated with making no correction. Further, in instances in which the error was large, the correlations between the marker and substantive scales were higher than that found in organizational research with marker variables. We conclude that in most practical settings, the CFA marker technique yields parameter estimates close to their true values, and the criticisms made by Richardson et al. are overstated. (c) 2015 APA, all rights reserved).

Development and Experimental Application of International Affairs Indicators. Volume A

DTIC Science & Technology

1974-06-01

DEVELOPMENT ’^EXPERIMENTAL APPttcATION OF INTERNATIONAL AFFAIRS INDICATORS Volume A Final Report e June 1974 US I Sponsored by: Defense Advanced...intelligence communities were designed, techniques for estimating the future were developed and tested, and the techniques and indicators were applied to the...past year’s effort is that the intelligence community has become increasingly aware of the potential use- fulness of quantitative indicators. The

A comparison of two approaches to modelling snow cover dynamics at the Polish Polar Station at Hornsund

NASA Astrophysics Data System (ADS)

Luks, B.; Osuch, M.; Romanowicz, R. J.

2012-04-01

We compare two approaches to modelling snow cover dynamics at the Polish Polar Station at Hornsund. In the first approach we apply physically-based Utah Energy Balance Snow Accumulation and Melt Model (UEB) (Tarboton et al., 1995; Tarboton and Luce, 1996). The model uses a lumped representation of the snowpack with two primary state variables: snow water equivalence and energy. Its main driving inputs are: air temperature, precipitation, wind speed, humidity and radiation (estimated from the diurnal temperature range). Those variables are used for physically-based calculations of radiative, sensible, latent and advective heat exchanges with a 3 hours time step. The second method is an application of a statistically efficient lumped parameter time series approach to modelling the dynamics of snow cover , based on daily meteorological measurements from the same area. A dynamic Stochastic Transfer Function model is developed that follows the Data Based Mechanistic approach, where a stochastic data-based identification of model structure and an estimation of its parameters are followed by a physical interpretation. We focus on the analysis of uncertainty of both model outputs. In the time series approach, the applied techniques also provide estimates of the modeling errors and the uncertainty of the model parameters. In the first, physically-based approach the applied UEB model is deterministic. It assumes that the observations are without errors and that the model structure perfectly describes the processes within the snowpack. To take into account the model and observation errors, we applied a version of the Generalized Likelihood Uncertainty Estimation technique (GLUE). This technique also provide estimates of the modelling errors and the uncertainty of the model parameters. The observed snowpack water equivalent values are compared with those simulated with 95% confidence bounds. This work was supported by National Science Centre of Poland (grant no. 7879/B/P01/2011/40). Tarboton, D. G., T. G. Chowdhury and T. H. Jackson, 1995. A Spatially Distributed Energy Balance Snowmelt Model. In K. A. Tonnessen, M. W. Williams and M. Tranter (Ed.), Proceedings of a Boulder Symposium, July 3-14, IAHS Publ. no. 228, pp. 141-155. Tarboton, D. G. and C. H. Luce, 1996. Utah Energy Balance Snow Accumulation and Melt Model (UEB). Computer model technical description and users guide, Utah Water Research Laboratory and USDA Forest Service Intermountain Research Station (http://www.engineering.usu.edu/dtarb/). 64 pp.

Estimation of submarine mass failure probability from a sequence of deposits with age dates

USGS Publications Warehouse

Geist, Eric L.; Chaytor, Jason D.; Parsons, Thomas E.; ten Brink, Uri S.

2013-01-01

The empirical probability of submarine mass failure is quantified from a sequence of dated mass-transport deposits. Several different techniques are described to estimate the parameters for a suite of candidate probability models. The techniques, previously developed for analyzing paleoseismic data, include maximum likelihood and Type II (Bayesian) maximum likelihood methods derived from renewal process theory and Monte Carlo methods. The estimated mean return time from these methods, unlike estimates from a simple arithmetic mean of the center age dates and standard likelihood methods, includes the effects of age-dating uncertainty and of open time intervals before the first and after the last event. The likelihood techniques are evaluated using Akaike’s Information Criterion (AIC) and Akaike’s Bayesian Information Criterion (ABIC) to select the optimal model. The techniques are applied to mass transport deposits recorded in two Integrated Ocean Drilling Program (IODP) drill sites located in the Ursa Basin, northern Gulf of Mexico. Dates of the deposits were constrained by regional bio- and magnetostratigraphy from a previous study. Results of the analysis indicate that submarine mass failures in this location occur primarily according to a Poisson process in which failures are independent and return times follow an exponential distribution. However, some of the model results suggest that submarine mass failures may occur quasiperiodically at one of the sites (U1324). The suite of techniques described in this study provides quantitative probability estimates of submarine mass failure occurrence, for any number of deposits and age uncertainty distributions.

Aeroshell Design Techniques for Aerocapture Entry Vehicles

NASA Technical Reports Server (NTRS)

Dyke, R. Eric; Hrinda, Glenn A.

2004-01-01

A major goal of NASA s In-Space Propulsion Program is to shorten trip times for scientific planetary missions. To meet this challenge arrival speeds will increase, requiring significant braking for orbit insertion, and thus increased deceleration propellant mass that may exceed launch lift capabilities. A technology called aerocapture has been developed to expand the mission potential of exploratory probes destined for planets with suitable atmospheres. Aerocapture inserts a probe into planetary orbit via a single pass through the atmosphere using the probe s aeroshell drag to reduce velocity. The benefit of an aerocapture maneuver is a large reduction in propellant mass that may result in smaller, less costly missions and reduced mission cruise times. The methodology used to design rigid aerocapture aeroshells will be presented with an emphasis on a new systems tool under development. Current methods for fast, efficient evaluations of structural systems for exploratory vehicles to planets and moons within our solar system have been under development within NASA having limited success. Many systems tools that have been attempted applied structural mass estimation techniques based on historical data and curve fitting techniques that are difficult and cumbersome to apply to new vehicle concepts and missions. The resulting vehicle aeroshell mass may be incorrectly estimated or have high margins included to account for uncertainty. This new tool will reduce the guesswork previously found in conceptual aeroshell mass estimations.

Relaxation time estimation in surface NMR

DOEpatents

Grunewald, Elliot D.; Walsh, David O.

2017-03-21

NMR relaxation time estimation methods and corresponding apparatus generate two or more alternating current transmit pulses with arbitrary amplitudes, time delays, and relative phases; apply a surface NMR acquisition scheme in which initial preparatory pulses, the properties of which may be fixed across a set of multiple acquisition sequence, are transmitted at the start of each acquisition sequence and are followed by one or more depth sensitive pulses, the pulse moments of which are varied across the set of multiple acquisition sequences; and apply processing techniques in which recorded NMR response data are used to estimate NMR properties and the relaxation times T.sub.1 and T.sub.2* as a function of position as well as one-dimensional and two-dimension distributions of T.sub.1 versus T.sub.2* as a function of subsurface position.

Small area estimation of obesity prevalence and dietary patterns: a model applied to Rio de Janeiro city, Brazil.

PubMed

Cataife, Guido

2014-03-01

We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008-9 family expenditure survey with Census 2010 socio-demographic data. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich. Male and female obesity rates are uncorrelated at the small area level. The model is an effective tool to understand the complexity of the problem and to aid in policy design. © 2013 Published by Elsevier Ltd.

Modified ADALINE algorithm for harmonic estimation and selective harmonic elimination in inverters

NASA Astrophysics Data System (ADS)

Vasumathi, B.; Moorthi, S.

2011-11-01

In digital signal processing, algorithms are very well developed for the estimation of harmonic components. In power electronic applications, an objective like fast response of a system is of primary importance. An effective method for the estimation of instantaneous harmonic components, along with conventional harmonic elimination technique, is presented in this article. The primary function is to eliminate undesirable higher harmonic components from the selected signal (current or voltage) and it requires only the knowledge of the frequency of the component to be eliminated. A signal processing technique using modified ADALINE algorithm has been proposed for harmonic estimation. The proposed method stays effective as it converges to a minimum error and brings out a finer estimation. A conventional control based on pulse width modulation for selective harmonic elimination is used to eliminate harmonic components after its estimation. This method can be applied to a wide range of equipment. The validity of the proposed method to estimate and eliminate voltage harmonics is proved with a dc/ac inverter as a simulation example. Then, the results are compared with existing ADALINE algorithm for illustrating its effectiveness.

Recent advancements in GRACE mascon regularization and uncertainty assessment

NASA Astrophysics Data System (ADS)

Loomis, B. D.; Luthcke, S. B.

2017-12-01

The latest release of the NASA Goddard Space Flight Center (GSFC) global time-variable gravity mascon product applies a new regularization strategy along with new methods for estimating noise and leakage uncertainties. The critical design component of mascon estimation is the construction of the applied regularization matrices, and different strategies exist between the different centers that produce mascon solutions. The new approach from GSFC directly applies the pre-fit Level 1B inter-satellite range-acceleration residuals in the design of time-dependent regularization matrices, which are recomputed at each step of our iterative solution method. We summarize this new approach, demonstrating the simultaneous increase in recovered time-variable gravity signal and reduction in the post-fit inter-satellite residual magnitudes, until solution convergence occurs. We also present our new approach for estimating mascon noise uncertainties, which are calibrated to the post-fit inter-satellite residuals. Lastly, we present a new technique for end users to quickly estimate the signal leakage errors for any selected grouping of mascons, and we test the viability of this leakage assessment procedure on the mascon solutions produced by other processing centers.

Sampling system for wheat (Triticum aestivum L) area estimation using digital LANDSAT MSS data and aerial photographs. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Moreira, M. A.; Chen, S. C.; Batista, G. T.

1984-01-01

A procedure to estimate wheat (Triticum aestivum L) area using sampling technique based on aerial photographs and digital LANDSAT MSS data is developed. Aerial photographs covering 720 square km are visually analyzed. To estimate wheat area, a regression approach is applied using different sample sizes and various sampling units. As the size of sampling unit decreased, the percentage of sampled area required to obtain similar estimation performance also decreased. The lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation is 13.90% using 10 square km as the sampling unit. Wheat area estimation using only aerial photographs is less precise and accurate than those obtained by regression estimation.

The scale invariant generator technique for quantifying anisotropic scale invariance

NASA Astrophysics Data System (ADS)

Lewis, G. M.; Lovejoy, S.; Schertzer, D.; Pecknold, S.

1999-11-01

Scale invariance is rapidly becoming a new paradigm for geophysics. However, little attention has been paid to the anisotropy that is invariably present in geophysical fields in the form of differential stratification and rotation, texture and morphology. In order to account for scaling anisotropy, the formalism of generalized scale invariance (GSI) was developed. Until now there has existed only a single fairly ad hoc GSI analysis technique valid for studying differential rotation. In this paper, we use a two-dimensional representation of the linear approximation to generalized scale invariance, to obtain a much improved technique for quantifying anisotropic scale invariance called the scale invariant generator technique (SIG). The accuracy of the technique is tested using anisotropic multifractal simulations and error estimates are provided for the geophysically relevant range of parameters. It is found that the technique yields reasonable estimates for simulations with a diversity of anisotropic and statistical characteristics. The scale invariant generator technique can profitably be applied to the scale invariant study of vertical/horizontal and space/time cross-sections of geophysical fields as well as to the study of the texture/morphology of fields.

A practical guide to propensity score analysis for applied clinical research.

PubMed

Lee, Jaehoon; Little, Todd D

2017-11-01

Observational studies are often the only viable options in many clinical settings, especially when it is unethical or infeasible to randomly assign participants to different treatment régimes. In such case propensity score (PS) analysis can be applied to accounting for possible selection bias and thereby addressing questions of causal inference. Many PS methods exist, yet few guidelines are available to aid applied researchers in their conduct and evaluation of a PS analysis. In this article we give an overview of available techniques for PS estimation and application, balance diagnostic, treatment effect estimation, and sensitivity assessment, as well as recent advances. We also offer a tutorial that can be used to emulate the steps of PS analysis. Our goal is to provide information that will bring PS analysis within the reach of applied clinical researchers and practitioners. Copyright © 2017 Elsevier Ltd. All rights reserved.

Scatter and veiling glare corrections for quantitative digital subtraction angiography

NASA Astrophysics Data System (ADS)

Ersahin, Atila; Molloi, Sabee Y.; Qian, Yao-Jin

1994-05-01

In order to quantitate anatomical and physiological parameters such as vessel dimensions and volumetric blood flow, it is necessary to make corrections for scatter and veiling glare (SVG), which are the major sources of nonlinearities in videodensitometric digital subtraction angiography (DSA). A convolution filtering technique has been investigated to estimate SVG distribution in DSA images without the need to sample the SVG for each patient. This technique utilizes exposure parameters and image gray levels to estimate SVG intensity by predicting the total thickness for every pixel in the image. At this point, corrections were also made for variation of SVG fraction with beam energy and field size. To test its ability to estimate SVG intensity, the correction technique was applied to images of a Lucite step phantom, anthropomorphic chest phantom, head phantom, and animal models at different thicknesses, projections, and beam energies. The root-mean-square (rms) percentage error of these estimates were obtained by comparison with direct SVG measurements made behind a lead strip. The average rms percentage errors in the SVG estimate for the 25 phantom studies and for the 17 animal studies were 6.22% and 7.96%, respectively. These results indicate that the SVG intensity can be estimated for a wide range of thicknesses, projections, and beam energies.

Head movement compensation in real-time magnetoencephalographic recordings.

PubMed

Little, Graham; Boe, Shaun; Bardouille, Timothy

2014-01-01

Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimation This work explains the technical details and validates each of these steps.

Quantitative body DW-MRI biomarkers uncertainty estimation using unscented wild-bootstrap.

PubMed

Freiman, M; Voss, S D; Mulkern, R V; Perez-Rossello, J M; Warfield, S K

2011-01-01

We present a new method for the uncertainty estimation of diffusion parameters for quantitative body DW-MRI assessment. Diffusion parameters uncertainty estimation from DW-MRI is necessary for clinical applications that use these parameters to assess pathology. However, uncertainty estimation using traditional techniques requires repeated acquisitions, which is undesirable in routine clinical use. Model-based bootstrap techniques, for example, assume an underlying linear model for residuals rescaling and cannot be utilized directly for body diffusion parameters uncertainty estimation due to the non-linearity of the body diffusion model. To offset this limitation, our method uses the Unscented transform to compute the residuals rescaling parameters from the non-linear body diffusion model, and then applies the wild-bootstrap method to infer the body diffusion parameters uncertainty. Validation through phantom and human subject experiments shows that our method identify the regions with higher uncertainty in body DWI-MRI model parameters correctly with realtive error of -36% in the uncertainty values.

Entropy-based adaptive attitude estimation

NASA Astrophysics Data System (ADS)

Kiani, Maryam; Barzegar, Aylin; Pourtakdoust, Seid H.

2018-03-01

Gaussian approximation filters have increasingly been developed to enhance the accuracy of attitude estimation in space missions. The effective employment of these algorithms demands accurate knowledge of system dynamics and measurement models, as well as their noise characteristics, which are usually unavailable or unreliable. An innovation-based adaptive filtering approach has been adopted as a solution to this problem; however, it exhibits two major challenges, namely appropriate window size selection and guaranteed assurance of positive definiteness for the estimated noise covariance matrices. The current work presents two novel techniques based on relative entropy and confidence level concepts in order to address the abovementioned drawbacks. The proposed adaptation techniques are applied to two nonlinear state estimation algorithms of the extended Kalman filter and cubature Kalman filter for attitude estimation of a low earth orbit satellite equipped with three-axis magnetometers and Sun sensors. The effectiveness of the proposed adaptation scheme is demonstrated by means of comprehensive sensitivity analysis on the system and environmental parameters by using extensive independent Monte Carlo simulations.

A semi-automatic method for left ventricle volume estimate: an in vivo validation study

NASA Technical Reports Server (NTRS)

Corsi, C.; Lamberti, C.; Sarti, A.; Saracino, G.; Shiota, T.; Thomas, J. D.

2001-01-01

This study aims to the validation of the left ventricular (LV) volume estimates obtained by processing volumetric data utilizing a segmentation model based on level set technique. The validation has been performed by comparing real-time volumetric echo data (RT3DE) and magnetic resonance (MRI) data. A validation protocol has been defined. The validation protocol was applied to twenty-four estimates (range 61-467 ml) obtained from normal and pathologic subjects, which underwent both RT3DE and MRI. A statistical analysis was performed on each estimate and on clinical parameters as stroke volume (SV) and ejection fraction (EF). Assuming MRI estimates (x) as a reference, an excellent correlation was found with volume measured by utilizing the segmentation procedure (y) (y=0.89x + 13.78, r=0.98). The mean error on SV was 8 ml and the mean error on EF was 2%. This study demonstrated that the segmentation technique is reliably applicable on human hearts in clinical practice.

A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2009-01-01

A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations

PubMed Central

Simon, Aaron B.; Dubowitz, David J.; Blockley, Nicholas P.; Buxton, Richard B.

2016-01-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2′ as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2′, we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2′-based estimate of the metabolic response to CO2 of 1.4%, and R2′- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2′-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. PMID:26790354

A novel Bayesian approach to accounting for uncertainty in fMRI-derived estimates of cerebral oxygen metabolism fluctuations.

PubMed

Simon, Aaron B; Dubowitz, David J; Blockley, Nicholas P; Buxton, Richard B

2016-04-01

Calibrated blood oxygenation level dependent (BOLD) imaging is a multimodal functional MRI technique designed to estimate changes in cerebral oxygen metabolism from measured changes in cerebral blood flow and the BOLD signal. This technique addresses fundamental ambiguities associated with quantitative BOLD signal analysis; however, its dependence on biophysical modeling creates uncertainty in the resulting oxygen metabolism estimates. In this work, we developed a Bayesian approach to estimating the oxygen metabolism response to a neural stimulus and used it to examine the uncertainty that arises in calibrated BOLD estimation due to the presence of unmeasured model parameters. We applied our approach to estimate the CMRO2 response to a visual task using the traditional hypercapnia calibration experiment as well as to estimate the metabolic response to both a visual task and hypercapnia using the measurement of baseline apparent R2' as a calibration technique. Further, in order to examine the effects of cerebral spinal fluid (CSF) signal contamination on the measurement of apparent R2', we examined the effects of measuring this parameter with and without CSF-nulling. We found that the two calibration techniques provided consistent estimates of the metabolic response on average, with a median R2'-based estimate of the metabolic response to CO2 of 1.4%, and R2'- and hypercapnia-calibrated estimates of the visual response of 27% and 24%, respectively. However, these estimates were sensitive to different sources of estimation uncertainty. The R2'-calibrated estimate was highly sensitive to CSF contamination and to uncertainty in unmeasured model parameters describing flow-volume coupling, capillary bed characteristics, and the iso-susceptibility saturation of blood. The hypercapnia-calibrated estimate was relatively insensitive to these parameters but highly sensitive to the assumed metabolic response to CO2. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of observation level versus 24-hour average atmospheric loading corrections in VLBI analysis

NASA Astrophysics Data System (ADS)

MacMillan, D. S.; van Dam, T. M.

2009-04-01

Variations in the horizontal distribution of atmospheric mass induce displacements of the Earth's surface. Theoretical estimates of the amplitude of the surface displacement indicate that the predicted surface displacement is often large enough to be detected by current geodetic techniques. In fact, the effects of atmospheric pressure loading have been detected in Global Positioning System (GPS) coordinate time series [van Dam et al., 1994; Dong et al., 2002; Scherneck et al., 2003; Zerbini et al., 2004] and very long baseline interferometery (VLBI) coordinates [Rabble and Schuh, 1986; Manabe et al., 1991; van Dam and Herring, 1994; Schuh et al., 2003; MacMillan and Gipson, 1994; and Petrov and Boy, 2004]. Some of these studies applied the atmospheric displacement at the observation level and in other studies, the predicted atmospheric and observed geodetic surface displacements have been averaged over 24 hours. A direct comparison of observation level and 24 hour corrections has not been carried out for VLBI to determine if one or the other approach is superior. In this presentation, we address the following questions: 1) Is it better to correct geodetic data at the observation level rather than applying corrections averaged over 24 hours to estimated geodetic coordinates a posteriori? 2) At the sub-daily periods, the atmospheric mass signal is composed of two components: a tidal component and a non-tidal component. If observation level corrections reduce the scatter of VLBI data more than a posteriori correction, is it sufficient to only model the atmospheric tides or must the entire atmospheric load signal be incorporated into the corrections? 3) When solutions from different geodetic techniques (or analysis centers within a technique) are combined (e.g., for ITRF2008), not all solutions may have applied atmospheric loading corrections. Are any systematic effects on the estimated TRF introduced when atmospheric loading is applied?

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, Francis J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least-squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 Goddard Earth Model-T1 (GEM-T1) were employed toward application of this technique for gravity field parameters. Also GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized. The method employs subset solutions of the data associated with the complete solution to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Emulation applied to reliability analysis of reconfigurable, highly reliable, fault-tolerant computing systems

NASA Technical Reports Server (NTRS)

Migneault, G. E.

1979-01-01

Emulation techniques applied to the analysis of the reliability of highly reliable computer systems for future commercial aircraft are described. The lack of credible precision in reliability estimates obtained by analytical modeling techniques is first established. The difficulty is shown to be an unavoidable consequence of: (1) a high reliability requirement so demanding as to make system evaluation by use testing infeasible; (2) a complex system design technique, fault tolerance; (3) system reliability dominated by errors due to flaws in the system definition; and (4) elaborate analytical modeling techniques whose precision outputs are quite sensitive to errors of approximation in their input data. Next, the technique of emulation is described, indicating how its input is a simple description of the logical structure of a system and its output is the consequent behavior. Use of emulation techniques is discussed for pseudo-testing systems to evaluate bounds on the parameter values needed for the analytical techniques. Finally an illustrative example is presented to demonstrate from actual use the promise of the proposed application of emulation.

The reliability and accuracy of estimating heart-rates from RGB video recorded on a consumer grade camera

NASA Astrophysics Data System (ADS)

Eaton, Adam; Vincely, Vinoin; Lloyd, Paige; Hugenberg, Kurt; Vishwanath, Karthik

2017-03-01

Video Photoplethysmography (VPPG) is a numerical technique to process standard RGB video data of exposed human skin and extracting the heart-rate (HR) from the skin areas. Being a non-contact technique, VPPG has the potential to provide estimates of subject's heart-rate, respiratory rate, and even the heart rate variability of human subjects with potential applications ranging from infant monitors, remote healthcare and psychological experiments, particularly given the non-contact and sensor-free nature of the technique. Though several previous studies have reported successful correlations in HR obtained using VPPG algorithms to HR measured using the gold-standard electrocardiograph, others have reported that these correlations are dependent on controlling for duration of the video-data analyzed, subject motion, and ambient lighting. Here, we investigate the ability of two commonly used VPPG-algorithms in extraction of human heart-rates under three different laboratory conditions. We compare the VPPG HR values extracted across these three sets of experiments to the gold-standard values acquired by using an electrocardiogram or a commercially available pulseoximeter. The two VPPG-algorithms were applied with and without KLT-facial feature tracking and detection algorithms from the Computer Vision MATLAB® toolbox. Results indicate that VPPG based numerical approaches have the ability to provide robust estimates of subject HR values and are relatively insensitive to the devices used to record the video data. However, they are highly sensitive to conditions of video acquisition including subject motion, the location, size and averaging techniques applied to regions-of-interest as well as to the number of video frames used for data processing.

The Novel Nonlinear Adaptive Doppler Shift Estimation Technique and the Coherent Doppler Lidar System Validation Lidar

NASA Technical Reports Server (NTRS)

Beyon, Jeffrey Y.; Koch, Grady J.

2006-01-01

The signal processing aspect of a 2-m wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The lidar system is named VALIDAR (validation lidar) and its signal processing program estimates and displays various wind parameters in real-time as data acquisition occurs. The goal is to improve the quality of the current estimates such as power, Doppler shift, wind speed, and wind direction, especially in low signal-to-noise-ratio (SNR) regime. A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is developed on such behalf and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as SNR decreases. NADSET compensates such deterioration in the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in a strong SNR range and identifying sporadic range bins where good Doppler shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.

Progress in Turbulence Detection via GNSS Occultation Data

NASA Technical Reports Server (NTRS)

Cornman, L. B.; Goodrich, R. K.; Axelrad, P.; Barlow, E.

2012-01-01

The increased availability of radio occultation (RO) data offers the ability to detect and study turbulence in the Earth's atmosphere. An analysis of how RO data can be used to determine the strength and location of turbulent regions is presented. This includes the derivation of a model for the power spectrum of the log-amplitude and phase fluctuations of the permittivity (or index of refraction) field. The bulk of the paper is then concerned with the estimation of the model parameters. Parameter estimators are introduced and some of their statistical properties are studied. These estimators are then applied to simulated log-amplitude RO signals. This includes the analysis of global statistics derived from a large number of realizations, as well as case studies that illustrate various specific aspects of the problem. Improvements to the basic estimation methods are discussed, and their beneficial properties are illustrated. The estimation techniques are then applied to real occultation data. Only two cases are presented, but they illustrate some of the salient features inherent in real data.

Estimating hydraulic properties of the Floridan Aquifer System by analysis of earth-tide, ocean-tide, and barometric effects, Collier and Hendry Counties, Florida

USGS Publications Warehouse

Merritt, Michael L.

2004-01-01

Aquifers are subjected to mechanical stresses from natural, non-anthropogenic, processes such as pressure loading or mechanical forcing of the aquifer by ocean tides, earth tides, and pressure fluctuations in the atmosphere. The resulting head fluctuations are evident even in deep confined aquifers. The present study was conducted for the purpose of reviewing the research that has been done on the use of these phenomena for estimating the values of aquifer properties, and determining which of the analytical techniques might be useful for estimating hydraulic properties in the dissolved-carbonate hydrologic environment of southern Florida. Fifteen techniques are discussed in this report, of which four were applied.An analytical solution for head oscillations in a well near enough to the ocean to be influenced by ocean tides was applied to data from monitor zones in a well near Naples, Florida. The solution assumes a completely non-leaky confining unit of infinite extent. Resulting values of transmissivity are in general agreement with the results of aquifer performance tests performed by the South Florida Water Management District. There seems to be an inconsistency between results of the amplitude ratio analysis and independent estimates of loading efficiency. A more general analytical solution that takes leakage through the confining layer into account yielded estimates that were lower than those obtained using the non-leaky method, and closer to the South Florida Water Management District estimates. A numerical model with a cross-sectional grid design was applied to explore additional aspects of the problem.A relation between specific storage and the head oscillation observed in a well provided estimates of specific storage that were considered reasonable. Porosity estimates based on the specific storage estimates were consistent with values obtained from measurements on core samples. Methods are described for determining aquifer diffusivity by comparing the time-varying drawdown in an open well with periodic pressure-head oscillations in the aquifer, but the applicability of such methods might be limited in studies of the Floridan aquifer system.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan

2016-12-01

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.

Towards the estimation of effect measures in studies using respondent-driven sampling.

PubMed

Rotondi, Michael A

2014-06-01

Respondent-driven sampling (RDS) is an increasingly common sampling technique to recruit hidden populations. Statistical methods for RDS are not straightforward due to the correlation between individual outcomes and subject weighting; thus, analyses are typically limited to estimation of population proportions. This manuscript applies the method of variance estimates recovery (MOVER) to construct confidence intervals for effect measures such as risk difference (difference of proportions) or relative risk in studies using RDS. To illustrate the approach, MOVER is used to construct confidence intervals for differences in the prevalence of demographic characteristics between an RDS study and convenience study of injection drug users. MOVER is then applied to obtain a confidence interval for the relative risk between education levels and HIV seropositivity and current infection with syphilis, respectively. This approach provides a simple method to construct confidence intervals for effect measures in RDS studies. Since it only relies on a proportion and appropriate confidence limits, it can also be applied to previously published manuscripts.

Phase-Based Adaptive Estimation of Magnitude-Squared Coherence Between Turbofan Internal Sensors and Far-Field Microphone Signals

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2015-01-01

A cross-power spectrum phase based adaptive technique is discussed which iteratively determines the time delay between two digitized signals that are coherent. The adaptive delay algorithm belongs to a class of algorithms that identifies a minimum of a pattern matching function. The algorithm uses a gradient technique to find the value of the adaptive delay that minimizes a cost function based in part on the slope of a linear function that fits the measured cross power spectrum phase and in part on the standard error of the curve fit. This procedure is applied to data from a Honeywell TECH977 static-engine test. Data was obtained using a combustor probe, two turbine exit probes, and far-field microphones. Signals from this instrumentation are used estimate the post-combustion residence time in the combustor. Comparison with previous studies of the post-combustion residence time validates this approach. In addition, the procedure removes the bias due to misalignment of signals in the calculation of coherence which is a first step in applying array processing methods to the magnitude squared coherence data. The procedure also provides an estimate of the cross-spectrum phase-offset.

An Information-Based Machine Learning Approach to Elasticity Imaging

PubMed Central

Hoerig, Cameron; Ghaboussi, Jamshid; Insana, Michael. F.

2016-01-01

An information-based technique is described for applications in mechanical-property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for this purpose. The Autoprogressive method is a computational technique that combines knowledge of object shape and a sparse distribution of force and displacement measurements with finite-element analyses and artificial neural networks to estimate a complete set of stress and strain vectors. Elasticity imaging parameters are then computed from estimated stresses and strains. We introduce the technique using ultrasonic pulse-echo measurements in simple gelatin imaging phantoms having linear-elastic properties so that conventional finite-element modeling can be used to validate results. The Autoprogressive algorithm does not require any assumptions about the material properties and can, in principle, be used to image media with arbitrary properties. We show that by selecting a few well-chosen force-displacement measurements that are appropriately applied during training and establish convergence, we can estimate all nontrivial stress and strain vectors throughout an object and accurately estimate an elastic modulus at high spatial resolution. This new method of modeling the mechanical properties of tissue-like materials introduces a unique method of solving the inverse problem and is the first technique for imaging stress without assuming the underlying constitutive model. PMID:27858175

Studies on spectral analysis of randomly sampled signals: Application to laser velocimetry data

NASA Technical Reports Server (NTRS)

Sree, David

1992-01-01

Spectral analysis is very useful in determining the frequency characteristics of many turbulent flows, for example, vortex flows, tail buffeting, and other pulsating flows. It is also used for obtaining turbulence spectra from which the time and length scales associated with the turbulence structure can be estimated. These estimates, in turn, can be helpful for validation of theoretical/numerical flow turbulence models. Laser velocimetry (LV) is being extensively used in the experimental investigation of different types of flows, because of its inherent advantages; nonintrusive probing, high frequency response, no calibration requirements, etc. Typically, the output of an individual realization laser velocimeter is a set of randomly sampled velocity data. Spectral analysis of such data requires special techniques to obtain reliable estimates of correlation and power spectral density functions that describe the flow characteristics. FORTRAN codes for obtaining the autocorrelation and power spectral density estimates using the correlation-based slotting technique were developed. Extensive studies have been conducted on simulated first-order spectrum and sine signals to improve the spectral estimates. A first-order spectrum was chosen because it represents the characteristics of a typical one-dimensional turbulence spectrum. Digital prefiltering techniques, to improve the spectral estimates from randomly sampled data were applied. Studies show that the spectral estimates can be increased up to about five times the mean sampling rate.

Analysis of distortion data from TF30-P-3 mixed compression inlet test

NASA Technical Reports Server (NTRS)

King, R. W.; Schuerman, J. A.; Muller, R. G.

1976-01-01

A program was conducted to reduce and analyze inlet and engine data obtained during testing of a TF30-P-3 engine operating behind a mixed compression inlet. Previously developed distortion analysis techniques were applied to the data to assist in the development of a new distortion methodology. Instantaneous distortion techniques were refined as part of the distortion methodology development. A technique for estimating maximum levels of instantaneous distortion from steady state and average turbulence data was also developed as part of the program.

Improving Estimates Of Phase Parameters When Amplitude Fluctuates

NASA Technical Reports Server (NTRS)

Vilnrotter, V. A.; Brown, D. H.; Hurd, W. J.

1989-01-01

Adaptive inverse filter applied to incoming signal and noise. Time-varying inverse-filtering technique developed to improve digital estimate of phase of received carrier signal. Intended for use where received signal fluctuates in amplitude as well as in phase and signal tracked by digital phase-locked loop that keeps its phase error much smaller than 1 radian. Useful in navigation systems, reception of time- and frequency-standard signals, and possibly spread-spectrum communication systems.

Parameter estimation in astronomy through application of the likelihood ratio. [satellite data analysis techniques

NASA Technical Reports Server (NTRS)

Cash, W.

1979-01-01

Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.

'Enzyme Test Bench': A biochemical application of the multi-rate modeling

NASA Astrophysics Data System (ADS)

Rachinskiy, K.; Schultze, H.; Boy, M.; Büchs, J.

2008-11-01

In the expanding field of 'white biotechnology' enzymes are frequently applied to catalyze the biochemical reaction from a resource material to a valuable product. Evolutionary designed to catalyze the metabolism in any life form, they selectively accelerate complex reactions under physiological conditions. Modern techniques, such as directed evolution, have been developed to satisfy the increasing demand on enzymes. Applying these techniques together with rational protein design, we aim at improving of enzymes' activity, selectivity and stability. To tap the full potential of these techniques, it is essential to combine them with adequate screening methods. Nowadays a great number of high throughput colorimetric and fluorescent enzyme assays are applied to measure the initial enzyme activity with high throughput. However, the prediction of enzyme long term stability within short experiments is still a challenge. A new high throughput technique for enzyme characterization with specific attention to the long term stability, called 'Enzyme Test Bench', is presented. The concept of the Enzyme Test Bench consists of short term enzyme tests conducted under partly extreme conditions to predict the enzyme long term stability under moderate conditions. The technique is based on the mathematical modeling of temperature dependent enzyme activation and deactivation. Adapting the temperature profiles in sequential experiments by optimum non-linear experimental design, the long term deactivation effects can be purposefully accelerated and detected within hours. During the experiment the enzyme activity is measured online to estimate the model parameters from the obtained data. Thus, the enzyme activity and long term stability can be calculated as a function of temperature. The results of the characterization, based on micro liter format experiments of hours, are in good agreement with the results of long term experiments in 1L format. Thus, the new technique allows for both: the enzyme screening with regard to the long term stability and the choice of the optimal process temperature. The presented article gives a successful example for the application of multi-rate modeling, experimental design and parameter estimation within biochemical engineering. At the same time, it shows the limitations of the methods at the state of the art and addresses the current problems to the applied mathematics community.

Novel Method for Incorporating Model Uncertainties into Gravitational Wave Parameter Estimates

NASA Astrophysics Data System (ADS)

Moore, Christopher J.; Gair, Jonathan R.

2014-12-01

Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications, these models are incomplete, which both reduces the prospects of detection and leads to a systematic error in the parameter estimates. In the analysis of data from gravitational wave detectors, for example, accurate waveform templates can be computed using numerical methods, but the prohibitive cost of these simulations means this can only be done for a small handful of parameters. In this Letter, a novel method to fold model uncertainties into data analysis is proposed; the waveform uncertainty is analytically marginalized over using with a prior distribution constructed by using Gaussian process regression to interpolate the waveform difference from a small training set of accurate templates. The method is well motivated, easy to implement, and no more computationally expensive than standard techniques. The new method is shown to perform extremely well when applied to a toy problem. While we use the application to gravitational wave data analysis to motivate and illustrate the technique, it can be applied in any context where model uncertainties exist.

75 FR 16527 - Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-01

... applies to all of the approximately 5,178 firms registered with the Commission that effect transactions on... confirmations than larger firms because they effect fewer transactions. The Commission staff estimates the costs... of automated collection techniques or other forms of information technology. Consideration will be...

Estimating Interaction Effects With Incomplete Predictor Variables

PubMed Central

Enders, Craig K.; Baraldi, Amanda N.; Cham, Heining

2014-01-01

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques. PMID:24707955

Numerically accurate computational techniques for optimal estimator analyses of multi-parameter models

NASA Astrophysics Data System (ADS)

Berger, Lukas; Kleinheinz, Konstantin; Attili, Antonio; Bisetti, Fabrizio; Pitsch, Heinz; Mueller, Michael E.

2018-05-01

Modelling unclosed terms in partial differential equations typically involves two steps: First, a set of known quantities needs to be specified as input parameters for a model, and second, a specific functional form needs to be defined to model the unclosed terms by the input parameters. Both steps involve a certain modelling error, with the former known as the irreducible error and the latter referred to as the functional error. Typically, only the total modelling error, which is the sum of functional and irreducible error, is assessed, but the concept of the optimal estimator enables the separate analysis of the total and the irreducible errors, yielding a systematic modelling error decomposition. In this work, attention is paid to the techniques themselves required for the practical computation of irreducible errors. Typically, histograms are used for optimal estimator analyses, but this technique is found to add a non-negligible spurious contribution to the irreducible error if models with multiple input parameters are assessed. Thus, the error decomposition of an optimal estimator analysis becomes inaccurate, and misleading conclusions concerning modelling errors may be drawn. In this work, numerically accurate techniques for optimal estimator analyses are identified and a suitable evaluation of irreducible errors is presented. Four different computational techniques are considered: a histogram technique, artificial neural networks, multivariate adaptive regression splines, and an additive model based on a kernel method. For multiple input parameter models, only artificial neural networks and multivariate adaptive regression splines are found to yield satisfactorily accurate results. Beyond a certain number of input parameters, the assessment of models in an optimal estimator analysis even becomes practically infeasible if histograms are used. The optimal estimator analysis in this paper is applied to modelling the filtered soot intermittency in large eddy simulations using a dataset of a direct numerical simulation of a non-premixed sooting turbulent flame.

Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

NASA Technical Reports Server (NTRS)

Corsi, C.; Borsari, M.; Consegnati, F.; Sarti, A.; Lamberti, C.; Travaglini, A.; Shiota, T.; Thomas, J. D.

2001-01-01

OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

Error field assessment from driven rotation of stable external kinks at EXTRAP-T2R reversed field pinch

NASA Astrophysics Data System (ADS)

Volpe, F. A.; Frassinetti, L.; Brunsell, P. R.; Drake, J. R.; Olofsson, K. E. J.

2013-04-01

A new non-disruptive error field (EF) assessment technique not restricted to low density and thus low beta was demonstrated at the EXTRAP-T2R reversed field pinch. Stable and marginally stable external kink modes of toroidal mode number n = 10 and n = 8, respectively, were generated, and their rotation sustained, by means of rotating magnetic perturbations of the same n. Due to finite EFs, and in spite of the applied perturbations rotating uniformly and having constant amplitude, the kink modes were observed to rotate non-uniformly and be modulated in amplitude. This behaviour was used to precisely infer the amplitude and approximately estimate the toroidal phase of the EF. A subsequent scan permitted to optimize the toroidal phase. The technique was tested against deliberately applied as well as intrinsic EFs of n = 8 and 10. Corrections equal and opposite to the estimated error fields were applied. The efficacy of the error compensation was indicated by the increased discharge duration and more uniform mode rotation in response to a uniformly rotating perturbation. The results are in good agreement with theory, and the extension to lower n, to tearing modes and to tokamaks, including ITER, is discussed.

Determining the source characteristics of explosions near the Earth's surface

DOE PAGES

Pasyanos, Michael E.; Ford, Sean R.

2015-04-09

We present a method to determine the source characteristics of explosions near the airearth interface. The technique is an extension of the regional amplitude envelope method and now accounts for the reduction of seismic amplitudes as the depth of the explosion approaches the free surface and less energy is coupled into the ground. We first apply the method to the Humming Roadrunner series of shallow explosions in New Mexico where the yields and depths are known. From these tests, we find an appreciation of knowing the material properties for both source coupling/excitation and the free surface effect. Although there ismore » the expected tradeoff between depth and yield due to coupling effects, the estimated yields are generally close to the known values when the depth is constrained to the free surface. We then apply the method to a regionally recorded explosion in Syria. We estimate an explosive yield less than the 60 tons claimed by sources in the open press. The modifications to the method allow us to apply the technique to new classes of events, but we will need a better understanding of explosion source models and properties of additional geologic materials.« less

Review of hardware cost estimation methods, models and tools applied to early phases of space mission planning

NASA Astrophysics Data System (ADS)

Trivailo, O.; Sippel, M.; Şekercioğlu, Y. A.

2012-08-01

The primary purpose of this paper is to review currently existing cost estimation methods, models, tools and resources applicable to the space sector. While key space sector methods are outlined, a specific focus is placed on hardware cost estimation on a system level, particularly for early mission phases during which specifications and requirements are not yet crystallised, and information is limited. For the space industry, cost engineering within the systems engineering framework is an integral discipline. The cost of any space program now constitutes a stringent design criterion, which must be considered and carefully controlled during the entire program life cycle. A first step to any program budget is a representative cost estimate which usually hinges on a particular estimation approach, or methodology. Therefore appropriate selection of specific cost models, methods and tools is paramount, a difficult task given the highly variable nature, scope as well as scientific and technical requirements applicable to each program. Numerous methods, models and tools exist. However new ways are needed to address very early, pre-Phase 0 cost estimation during the initial program research and establishment phase when system specifications are limited, but the available research budget needs to be established and defined. Due to their specificity, for vehicles such as reusable launchers with a manned capability, a lack of historical data implies that using either the classic heuristic approach such as parametric cost estimation based on underlying CERs, or the analogy approach, is therefore, by definition, limited. This review identifies prominent cost estimation models applied to the space sector, and their underlying cost driving parameters and factors. Strengths, weaknesses, and suitability to specific mission types and classes are also highlighted. Current approaches which strategically amalgamate various cost estimation strategies both for formulation and validation of an estimate, and techniques and/or methods to attain representative and justifiable cost estimates are consequently discussed. Ultimately, the aim of the paper is to establish a baseline for development of a non-commercial, low cost, transparent cost estimation methodology to be applied during very early program research phases at a complete vehicle system level, for largely unprecedented manned launch vehicles in the future. This paper takes the first step to achieving this through the identification, analysis and understanding of established, existing techniques, models, tools and resources relevant within the space sector.

Temperature of the plasmasphere from Van Allen Probes HOPE

NASA Astrophysics Data System (ADS)

Genestreti, K. J.; Goldstein, J.; Corley, G. D.; Farner, W.; Kistler, L. M.; Larsen, B. A.; Mouikis, C. G.; Ramnarace, C.; Skoug, R. M.; Turner, N. E.

2017-01-01

We introduce two novel techniques for estimating temperatures of very low energy space plasmas using, primarily, in situ data from an electrostatic analyzer mounted on a charged and moving spacecraft. The techniques are used to estimate proton temperatures during intervals where the bulk of the ion plasma is well below the energy bandpass of the analyzer. Both techniques assume that the plasma may be described by a one-dimensional E→×B→ drifting Maxwellian and that the potential field and motion of the spacecraft may be accounted for in the simplest possible manner, i.e., by a linear shift of coordinates. The first technique involves the application of a constrained theoretical fit to a measured distribution function. The second technique involves the comparison of total and partial-energy number densities. Both techniques are applied to Van Allen Probes Helium, Oxygen, Proton, and Electron (HOPE) observations of the proton component of the plasmasphere during two orbits on 15 January 2013. We find that the temperatures calculated from these two order-of-magnitude-type techniques are in good agreement with typical ranges of the plasmaspheric temperature calculated using retarding potential analyzer-based measurements—generally between 0.2 and 2 eV (2000-20,000 K). We also find that the temperature is correlated with L shell and hot plasma density and is negatively correlated with the cold plasma density. We posit that the latter of these three relationships may be indicative of collisional or wave-driven heating of the plasmasphere in the ring current overlap region. We note that these techniques may be easily applied to similar data sets or used for a variety of purposes.

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

USGS Publications Warehouse

Wagener, T.; Hogue, T.; Schaake, J.; Duan, Q.; Gupta, H.; Andreassian, V.; Hall, A.; Leavesley, G.

2006-01-01

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

Thermally assisted OSL application for equivalent dose estimation; comparison of multiple equivalent dose values as well as saturation levels determined by luminescence and ESR techniques for a sedimentary sample collected from a fault gouge

NASA Astrophysics Data System (ADS)

Şahiner, Eren; Meriç, Niyazi; Polymeris, George S.

2017-02-01

Equivalent dose estimation (De) constitutes the most important part of either trap-charge dating techniques or dosimetry applications. In the present work, multiple, independent equivalent dose estimation approaches were adopted, using both luminescence and ESR techniques; two different minerals were studied, namely quartz as well as feldspathic polymineral samples. The work is divided into three independent parts, depending on the type of signal employed. Firstly, different De estimation approaches were carried out on both polymineral and contaminated quartz, using single aliquot regenerative dose protocols employing conventional OSL and IRSL signals, acquired at different temperatures. Secondly, ESR equivalent dose estimations using the additive dose procedure both at room temperature and at 90 K were discussed. Lastly, for the first time in the literature, a single aliquot regenerative protocol employing a thermally assisted OSL signal originating from Very Deep Traps was applied for natural minerals. Rejection criteria such as recycling and recovery ratios are also presented. The SAR protocol, whenever applied, provided with compatible De estimations with great accuracy, independent on either the type of mineral or the stimulation temperature. Low temperature ESR signals resulting from Al and Ti centers indicate very large De values due to bleaching in-ability, associated with large uncertainty values. Additionally, dose saturation of different approaches was investigated. For the signal arising from Very Deep Traps in quartz saturation is extended almost by one order of magnitude. It is interesting that most of De values yielded using different luminescence signals agree with each other and ESR Ge center has very large D0 values. The results presented above highly support the argument that the stability and the initial ESR signal of the Ge center is highly sample-dependent, without any instability problems for the cases of quartz resulting from fault gouge.

Cortical dipole imaging using truncated total least squares considering transfer matrix error.

PubMed

Hori, Junichi; Takeuchi, Kosuke

2013-01-01

Cortical dipole imaging has been proposed as a method to visualize electroencephalogram in high spatial resolution. We investigated the inverse technique of cortical dipole imaging using a truncated total least squares (TTLS). The TTLS is a regularization technique to reduce the influence from both the measurement noise and the transfer matrix error caused by the head model distortion. The estimation of the regularization parameter was also investigated based on L-curve. The computer simulation suggested that the estimation accuracy was improved by the TTLS compared with Tikhonov regularization. The proposed method was applied to human experimental data of visual evoked potentials. We confirmed the TTLS provided the high spatial resolution of cortical dipole imaging.

Evaluation of Methods Used for Estimating Selected Streamflow Statistics, and Flood Frequency and Magnitude, for Small Basins in North Coastal California

USGS Publications Warehouse

Mann, Michael P.; Rizzardo, Jule; Satkowski, Richard

2004-01-01

Accurate streamflow statistics are essential to water resource agencies involved in both science and decision-making. When long-term streamflow data are lacking at a site, estimation techniques are often employed to generate streamflow statistics. However, procedures for accurately estimating streamflow statistics often are lacking. When estimation procedures are developed, they often are not evaluated properly before being applied. Use of unevaluated or underevaluated flow-statistic estimation techniques can result in improper water-resources decision-making. The California State Water Resources Control Board (SWRCB) uses two key techniques, a modified rational equation and drainage basin area-ratio transfer, to estimate streamflow statistics at ungaged locations. These techniques have been implemented to varying degrees, but have not been formally evaluated. For estimating peak flows at the 2-, 5-, 10-, 25-, 50-, and 100-year recurrence intervals, the SWRCB uses the U.S. Geological Surveys (USGS) regional peak-flow equations. In this study, done cooperatively by the USGS and SWRCB, the SWRCB estimated several flow statistics at 40 USGS streamflow gaging stations in the north coast region of California. The SWRCB estimates were made without reference to USGS flow data. The USGS used the streamflow data provided by the 40 stations to generate flow statistics that could be compared with SWRCB estimates for accuracy. While some SWRCB estimates compared favorably with USGS statistics, results were subject to varying degrees of error over the region. Flow-based estimation techniques generally performed better than rain-based methods, especially for estimation of December 15 to March 31 mean daily flows. The USGS peak-flow equations also performed well, but tended to underestimate peak flows. The USGS equations performed within reported error bounds, but will require updating in the future as peak-flow data sets grow larger. Little correlation was discovered between estimation errors and geographic locations or various basin characteristics. However, for 25-percentile year mean-daily-flow estimates for December 15 to March 31, the greatest estimation errors were at east San Francisco Bay area stations with mean annual precipitation less than or equal to 30 inches, and estimated 2-year/24-hour rainfall intensity less than 3 inches.

Comparison of Brownian-dynamics-based estimates of polymer tension with direct force measurements.

PubMed

Arsenault, Mark E; Purohit, Prashant K; Goldman, Yale E; Shuman, Henry; Bau, Haim H

2010-11-01

With the aid of brownian dynamics models, it is possible to estimate polymer tension by monitoring polymers' transverse thermal fluctuations. To assess the precision of the approach, brownian dynamics-based tension estimates were compared with the force applied to rhodamine-phalloidin labeled actin filaments bound to polymer beads and suspended between two optical traps. The transverse thermal fluctuations of each filament were monitored with a CCD camera, and the images were analyzed to obtain the filament's transverse displacement variance as a function of position along the filament, the filament's tension, and the camera's exposure time. A linear Brownian dynamics model was used to estimate the filament's tension. The estimated force was compared and agreed within 30% (when the tension <0.1 pN ) and 70% (when the tension <1 pN ) with the applied trap force. In addition, the paper presents concise asymptotic expressions for the mechanical compliance of a system consisting of a filament attached tangentially to bead handles (dumbbell system). The techniques described here can be used for noncontact estimates of polymers' and fibers' tension.

Comparison of in situ and in vitro techniques for measuring ruminal degradation of animal by-product proteins.

PubMed

England, M L; Broderick, G A; Shaver, R D; Combs, D K

1997-11-01

Ruminally undegraded protein (RUP) values of blood meal (n = 2), hydrolyzed feather meal (n = 2), fish meal (n = 2), meat and bone meal, and soybean meal were estimated using an in situ method, an inhibitor in vitro method, and an inhibitor in vitro technique applying Michaelis-Menten saturation kinetics. Degradation rates for in situ and inhibitor in vitro methods were calculated by regression of the natural log of the proportion of crude protein (CP) remaining undegraded versus time. Nonlinear regression analysis of the integrated Michaelis-Menten equation was used to determine maximum velocity, the Michaelis constant, and degradation rate (the ratio of maximum velocity to the Michaelis constant). A ruminal passage rate of 0.06/h was assumed in the calculation of RUP. The in situ and inhibitor in vitro techniques yielded similar estimates of ruminal degradation. Mean RUP estimated for soybean meal, blood meal, hydrolyzed feather meal, fish meal, and meat and bone meal were, respectively, 28.6, 86.0, 77.4, 52.9, and 52.6% of CP by the in situ method and 26.4, 86.1, 76.0, 59.6, and 49.5% of CP by the inhibitor in vitro technique. The Michaelis-Menten inhibitor in vitro technique yielded more rapid CP degradation rates and decreased estimates of RUP. The inhibitor in vitro method required less time and labor than did the other two techniques to estimate the RUP values of animal by-product proteins. Results from in vitro incubations with pepsin.HCl suggested that low postruminal digestibility of hydrolyzed feather meal may impair its value as a source of RUP.

Long memory and multifractality: A joint test

NASA Astrophysics Data System (ADS)

Goddard, John; Onali, Enrico

2016-06-01

The properties of statistical tests for hypotheses concerning the parameters of the multifractal model of asset returns (MMAR) are investigated, using Monte Carlo techniques. We show that, in the presence of multifractality, conventional tests of long memory tend to over-reject the null hypothesis of no long memory. Our test addresses this issue by jointly estimating long memory and multifractality. The estimation and test procedures are applied to exchange rate data for 12 currencies. Among the nested model specifications that are investigated, in 11 out of 12 cases, daily returns are most appropriately characterized by a variant of the MMAR that applies a multifractal time-deformation process to NIID returns. There is no evidence of long memory.

AgRISTARS: Supporting research. Classification of corn: Badhwar profile similarity technique. [us corn belt

NASA Technical Reports Server (NTRS)

Austin, W. W. (Principal Investigator)

1981-01-01

The same software programs used to classify spring wheat are applied to the classification of corn in 26 segments in the corn belt. Numerical results of the acreage estimation are given. Potential problem areas defined in an earlier application are examined.

Estimating Outcomes and Consequences of Interstate Wars.

DTIC Science & Technology

1977-02-01

way to evaluate the real effectiveness of governments. Techniques for appraising the performance of national economies cannot be applied to the... outcome of any total but non-nuclear war. The four conflicts analyzed in this study are: (1) The wars between the Arabs and Israelis. (2) The war

The Inverse Problem for Confined Aquifer Flow: Identification and Estimation With Extensions

NASA Astrophysics Data System (ADS)

Loaiciga, Hugo A.; MariñO, Miguel A.

1987-01-01

The contributions of this work are twofold. First, a methodology for estimating the elements of parameter matrices in the governing equation of flow in a confined aquifer is developed. The estimation techniques for the distributed-parameter inverse problem pertain to linear least squares and generalized least squares methods. The linear relationship among the known heads and unknown parameters of the flow equation provides the background for developing criteria for determining the identifiability status of unknown parameters. Under conditions of exact or overidentification it is possible to develop statistically consistent parameter estimators and their asymptotic distributions. The estimation techniques, namely, two-stage least squares and three stage least squares, are applied to a specific groundwater inverse problem and compared between themselves and with an ordinary least squares estimator. The three-stage estimator provides the closer approximation to the actual parameter values, but it also shows relatively large standard errors as compared to the ordinary and two-stage estimators. The estimation techniques provide the parameter matrices required to simulate the unsteady groundwater flow equation. Second, a nonlinear maximum likelihood estimation approach to the inverse problem is presented. The statistical properties of maximum likelihood estimators are derived, and a procedure to construct confidence intervals and do hypothesis testing is given. The relative merits of the linear and maximum likelihood estimators are analyzed. Other topics relevant to the identification and estimation methodologies, i.e., a continuous-time solution to the flow equation, coping with noise-corrupted head measurements, and extension of the developed theory to nonlinear cases are also discussed. A simulation study is used to evaluate the methods developed in this study.

Machine learning techniques applied to the determination of road suitability for the transportation of dangerous substances.

PubMed

Matías, J M; Taboada, J; Ordóñez, C; Nieto, P G

2007-08-17

This article describes a methodology to model the degree of remedial action required to make short stretches of a roadway suitable for dangerous goods transport (DGT), particularly pollutant substances, using different variables associated with the characteristics of each segment. Thirty-one factors determining the impact of an accident on a particular stretch of road were identified and subdivided into two major groups: accident probability factors and accident severity factors. Given the number of factors determining the state of a particular road segment, the only viable statistical methods for implementing the model were machine learning techniques, such as multilayer perceptron networks (MLPs), classification trees (CARTs) and support vector machines (SVMs). The results produced by these techniques on a test sample were more favourable than those produced by traditional discriminant analysis, irrespective of whether dimensionality reduction techniques were applied. The best results were obtained using SVMs specifically adapted to ordinal data. This technique takes advantage of the ordinal information contained in the data without penalising the computational load. Furthermore, the technique permits the estimation of the utility function that is latent in expert knowledge.

Accuracy and sampling error of two age estimation techniques using rib histomorphometry on a modern sample.

PubMed

García-Donas, Julieta G; Dyke, Jeffrey; Paine, Robert R; Nathena, Despoina; Kranioti, Elena F

2016-02-01

Most age estimation methods are proven problematic when applied in highly fragmented skeletal remains. Rib histomorphometry is advantageous in such cases; yet it is vital to test and revise existing techniques particularly when used in legal settings (Crowder and Rosella, 2007). This study tested Stout & Paine (1992) and Stout et al. (1994) histological age estimation methods on a Modern Greek sample using different sampling sites. Six left 4th ribs of known age and sex were selected from a modern skeletal collection. Each rib was cut into three equal segments. Two thin sections were acquired from each segment. A total of 36 thin sections were prepared and analysed. Four variables (cortical area, intact and fragmented osteon density and osteon population density) were calculated for each section and age was estimated according to Stout & Paine (1992) and Stout et al. (1994). The results showed that both methods produced a systemic underestimation of the individuals (to a maximum of 43 years) although a general improvement in accuracy levels was observed when applying the Stout et al. (1994) formula. There is an increase of error rates with increasing age with the oldest individual showing extreme differences between real age and estimated age. Comparison of the different sampling sites showed small differences between the estimated ages suggesting that any fragment of the rib could be used without introducing significant error. Yet, a larger sample should be used to confirm these results. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Comparison of Sample Size by Bootstrap and by Formulas Based on Normal Distribution Assumption.

PubMed

Wang, Zuozhen

2018-01-01

Bootstrapping technique is distribution-independent, which provides an indirect way to estimate the sample size for a clinical trial based on a relatively smaller sample. In this paper, sample size estimation to compare two parallel-design arms for continuous data by bootstrap procedure are presented for various test types (inequality, non-inferiority, superiority, and equivalence), respectively. Meanwhile, sample size calculation by mathematical formulas (normal distribution assumption) for the identical data are also carried out. Consequently, power difference between the two calculation methods is acceptably small for all the test types. It shows that the bootstrap procedure is a credible technique for sample size estimation. After that, we compared the powers determined using the two methods based on data that violate the normal distribution assumption. To accommodate the feature of the data, the nonparametric statistical method of Wilcoxon test was applied to compare the two groups in the data during the process of bootstrap power estimation. As a result, the power estimated by normal distribution-based formula is far larger than that by bootstrap for each specific sample size per group. Hence, for this type of data, it is preferable that the bootstrap method be applied for sample size calculation at the beginning, and that the same statistical method as used in the subsequent statistical analysis is employed for each bootstrap sample during the course of bootstrap sample size estimation, provided there is historical true data available that can be well representative of the population to which the proposed trial is planning to extrapolate.

4D computerized ionospheric tomography by using GPS measurements and IRI-Plas model

NASA Astrophysics Data System (ADS)

Tuna, Hakan; Arikan, Feza; Arikan, Orhan

2016-07-01

Ionospheric imaging is an important subject in ionospheric studies. GPS based TEC measurements provide very accurate information about the electron density values in the ionosphere. However, since the measurements are generally very sparse and non-uniformly distributed, computation of 3D electron density estimation from measurements alone is an ill-defined problem. Model based 3D electron density estimations provide physically feasible distributions. However, they are not generally compliant with the TEC measurements obtained from GPS receivers. In this study, GPS based TEC measurements and an ionosphere model known as International Reference Ionosphere Extended to Plasmasphere (IRI-Plas) are employed together in order to obtain a physically accurate 3D electron density distribution which is compliant with the real measurements obtained from a GPS satellite - receiver network. Ionospheric parameters input to the IRI-Plas model are perturbed in the region of interest by using parametric perturbation models such that the synthetic TEC measurements calculated from the resultant 3D electron density distribution fit to the real TEC measurements. The problem is considered as an optimization problem where the optimization parameters are the parameters of the parametric perturbation models. Proposed technique is applied over Turkey, on both calm and storm days of the ionosphere. Results show that the proposed technique produces 3D electron density distributions which are compliant with IRI-Plas model, GPS TEC measurements and ionosonde measurements. The effect of the GPS receiver station number on the performance of the proposed technique is investigated. Results showed that 7 GPS receiver stations in a region as large as Turkey is sufficient for both calm and storm days of the ionosphere. Since the ionization levels in the ionosphere are highly correlated in time, the proposed technique is extended to the time domain by applying Kalman based tracking and smoothing approaches onto the obtained results. Combining Kalman methods with the proposed 3D CIT technique creates a robust 4D ionospheric electron density estimation model, and has the advantage of decreasing the computational cost of the proposed method. Results applied on both calm and storm days of the ionosphere show that, new technique produces more robust solutions especially when the number of GPS receiver stations in the region is small. This study is supported by TUBITAK 114E541, 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

The Optical Flow Technique on the Research of Solar Non-potentiality

NASA Astrophysics Data System (ADS)

Liu, Ji-hong; Zhang, Hong-qi

2010-06-01

Several optical flow techniques, which have being applied to the researches of solar magnetic non-potentiality recently, have been summarized here. And a few new non-potential parameters which can be derived from them have been discussed, too. The main components of the work are presented as follows: (1) The optical flow techniques refers to a series of new image analyzing techniques arisen recently on the researches of solar magnetic non-potentiality. They mainly include LCT (local correlation tracking), ILCT (inductive equation combining with LCT), MEF (minimum energy effect), DAVE (differential affine velocity estimator) and NAVE (nonlinear affine velocity estimator). Their calculating and applying conditions, merits and deficiencies, all have been discussed detailedly in this work. (2) Benefit from the optical flow techniques, the transverse velocity fields of the magnetic features on the solar surface may be determined by a time sequence of high-quality images currently produced by high-resolution observations either from the ground or in space. Consequently, several new non-potential parameters may be acquired, such as the magnetic helicity flux, the induced electric field in the photosphere, the non-potential magnetic stress (whose area integration is the Lorentz force), etc. Then we can determine the energy flux across the photosphere, and subsequently evaluate the energy budget. Former works on them by small or special samples have shown that they are probably related closely to the erupting events, such as flare, filament eruptions and coronal mass ejections.

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Prediction of lung cancer patient survival via supervised machine learning classification techniques.

PubMed

Lynch, Chip M; Abdollahi, Behnaz; Fuqua, Joshua D; de Carlo, Alexandra R; Bartholomai, James A; Balgemann, Rayeanne N; van Berkel, Victor H; Frieboes, Hermann B

2017-12-01

Outcomes for cancer patients have been previously estimated by applying various machine learning techniques to large datasets such as the Surveillance, Epidemiology, and End Results (SEER) program database. In particular for lung cancer, it is not well understood which types of techniques would yield more predictive information, and which data attributes should be used in order to determine this information. In this study, a number of supervised learning techniques is applied to the SEER database to classify lung cancer patients in terms of survival, including linear regression, Decision Trees, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), and a custom ensemble. Key data attributes in applying these methods include tumor grade, tumor size, gender, age, stage, and number of primaries, with the goal to enable comparison of predictive power between the various methods The prediction is treated like a continuous target, rather than a classification into categories, as a first step towards improving survival prediction. The results show that the predicted values agree with actual values for low to moderate survival times, which constitute the majority of the data. The best performing technique was the custom ensemble with a Root Mean Square Error (RMSE) value of 15.05. The most influential model within the custom ensemble was GBM, while Decision Trees may be inapplicable as it had too few discrete outputs. The results further show that among the five individual models generated, the most accurate was GBM with an RMSE value of 15.32. Although SVM underperformed with an RMSE value of 15.82, statistical analysis singles the SVM as the only model that generated a distinctive output. The results of the models are consistent with a classical Cox proportional hazards model used as a reference technique. We conclude that application of these supervised learning techniques to lung cancer data in the SEER database may be of use to estimate patient survival time with the ultimate goal to inform patient care decisions, and that the performance of these techniques with this particular dataset may be on par with that of classical methods. Copyright © 2017 Elsevier B.V. All rights reserved.

Analysis of randomly time varying systems by gaussian closure technique

NASA Astrophysics Data System (ADS)

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

1982-07-01

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

Effects of scale of movement, detection probability, and true population density on common methods of estimating population density

DOE PAGES

Keiter, David A.; Davis, Amy J.; Rhodes, Olin E.; ...

2017-08-25

Knowledge of population density is necessary for effective management and conservation of wildlife, yet rarely are estimators compared in their robustness to effects of ecological and observational processes, which can greatly influence accuracy and precision of density estimates. For this study, we simulate biological and observational processes using empirical data to assess effects of animal scale of movement, true population density, and probability of detection on common density estimators. We also apply common data collection and analytical techniques in the field and evaluate their ability to estimate density of a globally widespread species. We find that animal scale of movementmore » had the greatest impact on accuracy of estimators, although all estimators suffered reduced performance when detection probability was low, and we provide recommendations as to when each field and analytical technique is most appropriately employed. The large influence of scale of movement on estimator accuracy emphasizes the importance of effective post-hoc calculation of area sampled or use of methods that implicitly account for spatial variation. In particular, scale of movement impacted estimators substantially, such that area covered and spacing of detectors (e.g. cameras, traps, etc.) must reflect movement characteristics of the focal species to reduce bias in estimates of movement and thus density.« less

Effects of scale of movement, detection probability, and true population density on common methods of estimating population density

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

Keiter, David A.; Davis, Amy J.; Rhodes, Olin E.

Knowledge of population density is necessary for effective management and conservation of wildlife, yet rarely are estimators compared in their robustness to effects of ecological and observational processes, which can greatly influence accuracy and precision of density estimates. For this study, we simulate biological and observational processes using empirical data to assess effects of animal scale of movement, true population density, and probability of detection on common density estimators. We also apply common data collection and analytical techniques in the field and evaluate their ability to estimate density of a globally widespread species. We find that animal scale of movementmore » had the greatest impact on accuracy of estimators, although all estimators suffered reduced performance when detection probability was low, and we provide recommendations as to when each field and analytical technique is most appropriately employed. The large influence of scale of movement on estimator accuracy emphasizes the importance of effective post-hoc calculation of area sampled or use of methods that implicitly account for spatial variation. In particular, scale of movement impacted estimators substantially, such that area covered and spacing of detectors (e.g. cameras, traps, etc.) must reflect movement characteristics of the focal species to reduce bias in estimates of movement and thus density.« less

Impulse excitation scanning acoustic microscopy for local quantification of Rayleigh surface wave velocity using B-scan analysis

NASA Astrophysics Data System (ADS)

Cherry, M.; Dierken, J.; Boehnlein, T.; Pilchak, A.; Sathish, S.; Grandhi, R.

2018-01-01

A new technique for performing quantitative scanning acoustic microscopy imaging of Rayleigh surface wave (RSW) velocity was developed based on b-scan processing. In this technique, the focused acoustic beam is moved through many defocus distances over the sample and excited with an impulse excitation, and advanced algorithms based on frequency filtering and the Hilbert transform are used to post-process the b-scans to estimate the Rayleigh surface wave velocity. The new method was used to estimate the RSW velocity on an optically flat E6 glass sample, and the velocity was measured at ±2 m/s and the scanning time per point was on the order of 1.0 s, which are both improvement from the previous two-point defocus method. The new method was also applied to the analysis of two titanium samples, and the velocity was estimated with very low standard deviation in certain large grains on the sample. A new behavior was observed with the b-scan analysis technique where the amplitude of the surface wave decayed dramatically on certain crystallographic orientations. The new technique was also compared with previous results, and the new technique has been found to be much more reliable and to have higher contrast than previously possible with impulse excitation.

Velocity interferometer signal de-noising using modified Wiener filter

NASA Astrophysics Data System (ADS)

Rav, Amit; Joshi, K. D.; Roy, Kallol; Kaushik, T. C.

2017-05-01

The accuracy and precision of the non-contact velocity interferometer system for any reflector (VISAR) depends not only on the good optical design and linear optical-to- electrical conversion system, but also on accurate and robust post-processing techniques. The performance of these techniques, such as the phase unwrapping algorithm, depends on the signal-to-noise ratio (SNR) of the recorded signal. In the present work, a novel method of improving the SNR of the recorded VISAR signal, based on the knowledge of the noise characteristic of the signal conversion and recording system, is presented. The proposed method uses a modified Wiener filter, for which the signal power spectrum estimation is obtained using a spectral subtraction method (SSM), and the noise power spectrum estimation is obtained by taking the average of the recorded signal during the period when no target movement is expected. Since the noise power spectrum estimate is dynamic in nature, and obtained for each experimental record individually, the improved signal quality is high. The proposed method is applied to the simulated standard signals, and is not only found to be better than the SSM, but is also less sensitive to the selection of the noise floor during signal power spectrum estimation. Finally, the proposed method is applied to the recorded experimental signal and an improvement in the SNR is reported.

Estimating Spectra from Photometry

NASA Astrophysics Data System (ADS)

Kalmbach, J. Bryce; Connolly, Andrew J.

2017-12-01

Measuring the physical properties of galaxies such as redshift frequently requires the use of spectral energy distributions (SEDs). SED template sets are, however, often small in number and cover limited portions of photometric color space. Here we present a new method to estimate SEDs as a function of color from a small training set of template SEDs. We first cover the mathematical background behind the technique before demonstrating our ability to reconstruct spectra based upon colors and then compare our results to other common interpolation and extrapolation methods. When the photometric filters and spectra overlap, we show that the error in the estimated spectra is reduced by more than 65% compared to the more commonly used techniques. We also show an expansion of the method to wavelengths beyond the range of the photometric filters. Finally, we demonstrate the usefulness of our technique by generating 50 additional SED templates from an original set of 10 and by applying the new set to photometric redshift estimation. We are able to reduce the photometric redshifts standard deviation by at least 22.0% and the outlier rejected bias by over 86.2% compared to original set for z ≤ 3.

Real-time vehicle noise cancellation techniques for gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2012-06-01

Acoustical sniper positioning systems rely on the detection and direction-of-arrival (DOA) estimation of the shockwave and the muzzle blast in order to provide an estimate of a potential snipers location. Field tests have shown that detecting and estimating the DOA of the muzzle blast is a rather difficult task in the presence of background noise sources, e.g., vehicle noise, especially in long range detection and absorbing terrains. In our previous work presented in the 2011 edition of this conference we highlight the importance of improving the SNR of the gunshot signals prior to the detection and recognition stages, aiming at lowering the false alarm and miss-detection rates and, thereby, increasing the reliability of the system. This paper reports on real-time noise cancellation techniques, like Spectral Subtraction and Adaptive Filtering, applied to gunshot signals. Our model assumes the background noise as being short-time stationary and uncorrelated to the impulsive gunshot signals. In practice, relatively long periods without signal occur and can be used to estimate the noise spectrum and its first and second order statistics as required in the spectral subtraction and adaptive filtering techniques, respectively. The results presented in this work are supported with extensive simulations based on real data.

Shear wave transducer for boreholes

DOEpatents

Mao, N.H.

1984-08-23

A technique and apparatus is provided for estimating in situ stresses by measuring stress-induced velocity anisotropy around a borehole. Two sets each of radially and tangentially polarized transducers are placed inside the hole with displacement directions either parallel or perpendicular to the principal stress directions. With this configuration, relative travel times are measured by both a pulsed phase-locked loop technique and a cross correlation of digitized waveforms. The biaxial velocity data are used to back-calculate the applied stress.

Shear wave transducer for stress measurements in boreholes

DOEpatents

Mao, Nai-Hsien

1987-01-01

A technique and apparatus for estimating in situ stresses by measuring stress-induced velocity anisotropy around a borehole. Two sets each of radially and tangentially polarized transducers are placed inside the hole with displacement directions either parallel or perpendicular to the principal stress directions. With this configuration, relative travel times are measured by both a pulsed phase-locked loop technique and a cross correlation of digitized waveforms. The biaxial velocity data is used to back-calculate the applied stress.

Using the Oaxaca-Blinder Decomposition Technique to Analyze Learning Outcomes Changes over Time: An Application to Indonesia's Results in PISA Mathematics. Policy Research Working Paper 5584

ERIC Educational Resources Information Center

Barrera-Osorio, Felipe; Garcia-Moreno, Vicente; Patrinos, Harry Anthony; Porta, Emilio

2011-01-01

The Oaxaca-Blinder technique was originally used in labor economics to decompose earnings gaps and to estimate the level of discrimination. It has been applied since in other social issues, including education, where it can be used to assess how much of a gap is due to differences in characteristics (explained variation) and how much is due to…

Arched needle technique for inferior alveolar mandibular nerve block.

PubMed

Chakranarayan, Ashish; Mukherjee, B

2013-03-01

One of the most commonly used local anesthetic techniques in dentistry is the Fischer's technique for the inferior alveolar nerve block. Incidentally this technique also suffers the maximum failure rate of approximately 35-45%. We studied a method of inferior alveolar nerve block by injecting a local anesthetic solution into the pterygomandibular space by arching and changing the approach angle of the conventional technique and estimated its efficacy. The needle after the initial insertion is arched and inserted in a manner that it approaches the medial surface of the ramus at an angle almost perpendicular to it. The technique was applied to 100 patients for mandibular molar extraction and the anesthetic effects were assessed. A success rate of 98% was obtained.

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

PubMed

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

Results and Error Estimates from GRACE Forward Modeling over Antarctica

NASA Astrophysics Data System (ADS)

Bonin, Jennifer; Chambers, Don

2013-04-01

Forward modeling using a weighted least squares technique allows GRACE information to be projected onto a pre-determined collection of local basins. This decreases the impact of spatial leakage, allowing estimates of mass change to be better localized. The technique is especially valuable where models of current-day mass change are poor, such as over Antarctica. However when tested previously, the least squares technique has required constraints in the form of added process noise in order to be reliable. Poor choice of local basin layout has also adversely affected results, as has the choice of spatial smoothing used with GRACE. To develop design parameters which will result in correct high-resolution mass detection and to estimate the systematic errors of the method over Antarctica, we use a "truth" simulation of the Antarctic signal. We apply the optimal parameters found from the simulation to RL05 GRACE data across Antarctica and the surrounding ocean. We particularly focus on separating the Antarctic peninsula's mass signal from that of the rest of western Antarctica. Additionally, we characterize how well the technique works for removing land leakage signal from the nearby ocean, particularly that near the Drake Passage.

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

NASA Technical Reports Server (NTRS)

Tomberlin, T. J.

1985-01-01

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Extracting Maximum Total Water Levels from Video "Brightest" Images

NASA Astrophysics Data System (ADS)

Brown, J. A.; Holman, R. A.; Stockdon, H. F.; Plant, N. G.; Long, J.; Brodie, K.

2016-02-01

An important parameter for predicting storm-induced coastal change is the maximum total water level (TWL). Most studies estimate the TWL as the sum of slowly varying water levels, including tides and storm surge, and the extreme runup parameter R2%, which includes wave setup and swash motions over minutes to seconds. Typically, R2% is measured using video remote sensing data, where cross-shore timestacks of pixel intensity are digitized to extract the horizontal runup timeseries. However, this technique must be repeated at multiple alongshore locations to resolve alongshore variability, and can be tedious and time consuming. We seek an efficient, video-based approach that yields a synoptic estimate of TWL that accounts for alongshore variability and can be applied during storms. In this work, the use of a video product termed the "brightest" image is tested; this represents the highest intensity of each pixel captured during a 10-minute collection period. Image filtering and edge detection techniques are applied to automatically determine the shoreward edge of the brightest region (i.e., the swash zone) at each alongshore pixel. The edge represents the horizontal position of the maximum TWL along the beach during the collection period, and is converted to vertical elevations using measured beach topography. This technique is evaluated using video and topographic data collected every half-hour at Duck, NC, during differing hydrodynamic conditions. Relationships between the maximum TWL estimates from the brightest images and various runup statistics computed using concurrent runup timestacks are examined, and errors associated with mapping the horizontal results to elevations are discussed. This technique is invaluable, as it can be used to routinely estimate maximum TWLs along a coastline from a single brightest image product, and provides a means for examining alongshore variability of TWLs at high alongshore resolution. These advantages will be useful in validating numerical hydrodynamic models and improving coastal change predictions.

Estimating the spatial distribution of field-applied mushroom compost in the Brandywine-Christina River Basin using multispectral remote sensing

NASA Astrophysics Data System (ADS)

Moxey, Kelsey A.

The world's greatest concentration of mushroom farms is settled within the Brandywine-Christina River Basin in Chester County in southeastern Pennsylvania. This industry produces a nutrient-rich byproduct known as spent mushroom compost, which has been traditionally applied to local farm fields as an organic fertilizer and soil amendment. While mushroom compost has beneficial properties, the possible over-application to farm fields could potentially degrade stream water quality. The goal of this study was to estimate the spatial extent and intensity of field-applied mushroom compost. We applied a remote sensing approach using Landsat multispectral imagery. We utilized the soil line technique, using the red and near-infrared bands, to estimate differences in soil wetness as a result of increased soil organic matter content from mushroom compost. We validated soil wetness estimates by examining the spectral response of references sites. We performed a second independent validation analysis using expert knowledge from agricultural extension agents. Our results showed that the soil line based wetness index worked well. The spectral validation illustrated that compost changes the spectral response of soil because of changes in wetness. The independent expert validation analysis produced a strong significant correlation between our remotely-sensed wetness estimates and the empirical ratings of compost application intensities. Overall, the methodology produced realistic spatial distributions of field-applied compost application intensities across the study area. These spatial distributions will be used for follow-up studies to assess the effect of spent mushroom compost on stream water quality.

Real-time 3D reconstruction of road curvature in far look-ahead distance from analysis of image sequences

NASA Astrophysics Data System (ADS)

Behringer, Reinhold

1995-12-01

A system for visual road recognition in far look-ahead distance, implemented in the autonomous road vehicle VaMP (a passenger car), is described. Visual cues of a road in a video image are the bright lane markings and the edges formed at the road borders. In a distance of more than 100 m, the most relevant road cue is the homogeneous road area, limited by the two border edges. These cues can be detected by the image processing module KRONOS applying edge detection techniques and areal 2D segmentation based on resolution triangles (analogous to a resolution pyramid). An estimation process performs an update of a state vector, which describes spatial road shape and vehicle orientation relative to the road. This state vector is estimated every 40 ms by exploiting knowledge about the vehicle movement (spatio-temporal model of vehicle dynamics) and the road design rules (clothoidal segments). Kalman filter techniques are applied to obtain an optimal estimate of the state vector by evaluating the measurements of the road border positions in the image sequence taken by a set of CCD cameras. The road consists of segments with piecewise constant curvature parameters. The borders between these segments can be detected by applying methods which have been developed for detection of discontinuities during time-discrete measurements. The road recognition system has been tested in autonomous rides with VaMP on public Autobahnen in real traffic at speeds up to 130 km/h.

A method for combining passive microwave and infrared rainfall observations

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Giglio, Louis

1995-01-01

Because passive microwave instruments are confined to polar-orbiting satellites, rainfall estimates must interpolate across long time periods, during which no measurements are available. In this paper the authors discuss a technique that allows one to partially overcome the sampling limitations by using frequent infrared observations from geosynchronous platforms. To accomplish this, the technique compares all coincident microwave and infrared observations. From each coincident pair, the infrared temperature threshold is selected that corresponds to an area equal to the raining area observed in the microwave image. The mean conditional rainfall rate as determined from the microwave image is then assigned to pixels in the infrared image that are colder than the selected threshold. The calibration is also applied to a fixed threshold of 235 K for comparison with established infrared techniques. Once a calibration is determined, it is applied to all infrared images. Monthly accumulations for both methods are then obtained by summing rainfall from all available infrared images. Two examples are used to evaluate the performance of the technique. The first consists of a one-month period (February 1988) over Darwin, Australia, where good validation data are available from radar and rain gauges. For this case it was found that the technique approximately doubled the rain inferred by the microwave method alone and produced exceptional agreement with the validation data. The second example involved comparisons with atoll rain gauges in the western Pacific for June 1989. Results here are overshadowed by the fact that the hourly infrared estimates from established techniques, by themselves, produced very good correlations with the rain gauges. The calibration technique was not able to improve upon these results.

A paleointensity technique for multidomain igneous rocks

NASA Astrophysics Data System (ADS)

Wang, Huapei; Kent, Dennis V.

2013-10-01

We developed a paleointensity technique to account for concave-up Arai diagrams due to multidomain (MD) contributions to determine unbiased paleointensities for 24 trial samples from site GA-X in Pleistocene lavas from Floreana Island, Galapagos Archipelago. The main magnetization carrier is fine-grained low-titanium magnetite of variable grain size. We used a comprehensive back-zero-forth (BZF) heating technique by adding an additional zero-field heating between the Thellier two opposite in-field heating steps in order to estimate paleointensities in various standard protocols and provide internal self-consistency checks. After the first BZF experiment, we gave each sample a total thermal remanent magnetization (tTRM) by cooling from the Curie point in the presence of a low (15 µT) laboratory-applied field. Then we repeated the BZF protocol, with the laboratory-applied tTRM as a synthetic natural remanent magnetization (NRM), using the same laboratory-applied field and temperature steps to obtain the synthetic Arai signatures, which should only represent the domain-state dependent properties of the samples. We corrected the original Arai diagrams from the first BZF experiment by using the Arai signatures from the repeated BZF experiment, which neutralizes the typical MD concave-up effect. Eleven samples meet the Arai diagram post-selection criteria and provide qualified paleointensity estimates with a mean value for site GA-X of 4.23 ± 1.29 µT, consistent with an excursional geomagnetic field direction reported for this site.

An angle-dependent estimation of CT x-ray spectrum from rotational transmission measurements

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

Lin, Yuan, E-mail: yuan.lin@duke.edu; Samei, Ehsan; Ramirez-Giraldo, Juan Carlos

2014-06-15

Purpose: Computed tomography (CT) performance as well as dose and image quality is directly affected by the x-ray spectrum. However, the current assessment approaches of the CT x-ray spectrum require costly measurement equipment and complicated operational procedures, and are often limited to the spectrum corresponding to the center of rotation. In order to address these limitations, the authors propose an angle-dependent estimation technique, where the incident spectra across a wide range of angular trajectories can be estimated accurately with only a single phantom and a single axial scan in the absence of the knowledge of the bowtie filter. Methods: Themore » proposed technique uses a uniform cylindrical phantom, made of ultra-high-molecular-weight polyethylene and positioned in an off-centered geometry. The projection data acquired with an axial scan have a twofold purpose. First, they serve as a reflection of the transmission measurements across different angular trajectories. Second, they are used to reconstruct the cross sectional image of the phantom, which is then utilized to compute the intersection length of each transmission measurement. With each CT detector element recording a range of transmission measurements for a single angular trajectory, the spectrum is estimated for that trajectory. A data conditioning procedure is used to combine information from hundreds of collected transmission measurements to accelerate the estimation speed, to reduce noise, and to improve estimation stability. The proposed spectral estimation technique was validated experimentally using a clinical scanner (Somatom Definition Flash, Siemens Healthcare, Germany) with spectra provided by the manufacturer serving as the comparison standard. Results obtained with the proposed technique were compared against those obtained from a second conventional transmission measurement technique with two materials (i.e., Cu and Al). After validation, the proposed technique was applied to measure spectra from the clinical system across a range of angular trajectories [−15°, 15°] and spectrum settings (80, 100, 120, 140 kVp). Results: At 140 kVp, the proposed technique was comparable to the conventional technique in terms of the mean energy difference (MED, −0.29 keV) and the normalized root mean square difference (NRMSD, 0.84%) from the comparison standard compared to 0.64 keV and 1.56%, respectively, with the conventional technique. The average absolute MEDs and NRMSDs across kVp settings and angular trajectories were less than 0.61 keV and 3.41%, respectively, which indicates a high level of estimation accuracy and stability. Conclusions: An angle-dependent estimation technique of CT x-ray spectra from rotational transmission measurements was proposed. Compared with the conventional technique, the proposed method simplifies the measurement procedures and enables incident spectral estimation for a wide range of angular trajectories. The proposed technique is suitable for rigorous research objectives as well as routine clinical quality control procedures.« less

MFI ratio estimation of ZAP-70 in B-CLL by flow cytometry can be improved by considering the isotype-matched antibody signal.

PubMed

Marquez, M-E; Deglesne, P-A; Suarez, G; Romano, E

2011-04-01

The IgV(H) mutational status of B-cell chronic lymphocytic leukemia (B-CLL) is of prognostic value. Expression of ZAP-70 in B-CLL is a surrogate marker for IgV(H) unmutated (UM). As determination of IgV(H) mutational status involves a methodology currently unavailable for most clinical laboratories, it is important to have available a reliable technique for ZAP-70 estimation in B-CLL. Flow cytometry (FC) is a convenient technique for this purpose. However, there is still no adequate way for data analysis, which would prevent the assignment of false positive or negative expression. We have modified the currently most accepted technique, which uses the ratio of the mean fluorescent index (MFI) of B-CLL to T cells. The MFI for parallel antibody isotype staining is subtracted from the ZAP-70 MFI of both B-CLL and T cells. We validated this technique comparing the results obtained for ZAP-70 expression by FC with those obtained with quantitative PCR for the same patients. We applied the technique in a series of 53 patients. With this modification, a better correlation between ZAP-70 expression and IgV(H) UM was obtained. Thus, the MFI ratio B-CLL/T cell corrected by isotype is a reliable analysis technique to estimate ZAP-70 expression in B-CLL. © 2010 Blackwell Publishing Ltd.

LAND USE CHANGE DUE TO URBANIZATION FOR THE NEUSE RIVER BASIN

EPA Science Inventory

The Urban Growth Model (UGM) was applied to analysis of land use change in the Neuse River Basin as part of a larger project for estimating the regional and broader impact of urbanization. UGM is based on cellular automation (CA) simulation techniques developed at the University...

Separating Item and Order Information through Process Dissociation

ERIC Educational Resources Information Center

Nairne, James S.; Kelley, Matthew R.

2004-01-01

In the present paper, we develop and apply a technique, based on the logic of process dissociation, for obtaining numerical estimates of item and order information. Certain variables, such as phonological similarity, are widely believed to produce dissociative effects on item and order retention. However, such beliefs rest on the questionable…

The Long-Term Sustainability of Different Item Response Theory Scaling Methods

ERIC Educational Resources Information Center

Keller, Lisa A.; Keller, Robert R.

2011-01-01

This article investigates the accuracy of examinee classification into performance categories and the estimation of the theta parameter for several item response theory (IRT) scaling techniques when applied to six administrations of a test. Previous research has investigated only two administrations; however, many testing programs equate tests…

TEMPORAL SIGNATURES OF AIR QUALITY OBSERVATIONS AND MODEL OUTPUTS: DO TIME SERIES DECOMPOSITION METHODS CAPTURE RELEVANT TIME SCALES?

EPA Science Inventory

Time series decomposition methods were applied to meteorological and air quality data and their numerical model estimates. Decomposition techniques express a time series as the sum of a small number of independent modes which hypothetically represent identifiable forcings, thereb...

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

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

Wang, Feng, E-mail: fwang@unu.edu; Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft; Huisman, Jaco

2013-11-15

Highlights: • A multivariate Input–Output Analysis method for e-waste estimates is proposed. • Applying multivariate analysis to consolidate data can enhance e-waste estimates. • We examine the influence of model selection and data quality on e-waste estimates. • Datasets of all e-waste related variables in a Dutch case study have been provided. • Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lackmore » of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.« less

Time-Domain Receiver Function Deconvolution using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Moreira, L. P.

2017-12-01

Receiver Functions (RF) are well know method for crust modelling using passive seismological signals. Many different techniques were developed to calculate the RF traces, applying the deconvolution calculation to radial and vertical seismogram components. A popular method used a spectral division of both components, which requires human intervention to apply the Water Level procedure to avoid instabilities from division by small numbers. One of most used method is an iterative procedure to estimate the RF peaks and applying the convolution with vertical component seismogram, comparing the result with the radial component. This method is suitable for automatic processing, however several RF traces are invalid due to peak estimation failure.In this work it is proposed a deconvolution algorithm using Genetic Algorithm (GA) to estimate the RF peaks. This method is entirely processed in the time domain, avoiding the time-to-frequency calculations (and vice-versa), and totally suitable for automatic processing. Estimated peaks can be used to generate RF traces in a seismogram format for visualization. The RF trace quality is similar for high magnitude events, although there are less failures for RF calculation of smaller events, increasing the overall performance for high number of events per station.

Defect inspection of periodic patterns with low-order distortions

NASA Astrophysics Data System (ADS)

Khalaj, Babak H.; Aghajan, Hamid K.; Paulraj, Arogyaswami; Kailath, Thomas

1994-03-01

A self-reliance technique is developed for detecting defects in repeated pattern wafers and masks with low-order distortions. If the patterns are located on a perfect rectangular grid, it is possible to estimate the period of repeated patterns in both directions, and then produce a defect-free reference image for making comparison with the actual image. But in some applications, the repeated patterns are somehow shifted from their desired position on a rectangular grid, and the aforementioned algorithm cannot be directly applied. In these situations, to produce a defect-free reference image and locate the defected cells, it is necessary to estimate the amount of misalignment of each cell beforehand. The proposed technique first estimates the misalignment of repeated patterns in each row and column. After estimating the location of all cells in the image, a defect-free reference image is generated by averaging over all the cells and is compared with the input image to localize the possible defects.

Precision Parameter Estimation and Machine Learning

NASA Astrophysics Data System (ADS)

Wandelt, Benjamin D.

2008-12-01

I discuss the strategy of ``Acceleration by Parallel Precomputation and Learning'' (AP-PLe) that can vastly accelerate parameter estimation in high-dimensional parameter spaces and costly likelihood functions, using trivially parallel computing to speed up sequential exploration of parameter space. This strategy combines the power of distributed computing with machine learning and Markov-Chain Monte Carlo techniques efficiently to explore a likelihood function, posterior distribution or χ2-surface. This strategy is particularly successful in cases where computing the likelihood is costly and the number of parameters is moderate or large. We apply this technique to two central problems in cosmology: the solution of the cosmological parameter estimation problem with sufficient accuracy for the Planck data using PICo; and the detailed calculation of cosmological helium and hydrogen recombination with RICO. Since the APPLe approach is designed to be able to use massively parallel resources to speed up problems that are inherently serial, we can bring the power of distributed computing to bear on parameter estimation problems. We have demonstrated this with the CosmologyatHome project.

Estimating and Comparing Dam Deformation Using Classical and GNSS Techniques.

PubMed

Barzaghi, Riccardo; Cazzaniga, Noemi Emanuela; De Gaetani, Carlo Iapige; Pinto, Livio; Tornatore, Vincenza

2018-03-02

Global Navigation Satellite Systems (GNSS) receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure displacements. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high-precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS-estimated displacements on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D'Arborea (Cantoniera) dam, which is in Sardinia. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so as to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. These encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations.

Quantitative estimation of bioclimatic parameters from presence/absence vegetation data in North America by the modern analog technique

USGS Publications Warehouse

Thompson, R.S.; Anderson, K.H.; Bartlein, P.J.

2008-01-01

The method of modern analogs is widely used to obtain estimates of past climatic conditions from paleobiological assemblages, and despite its frequent use, this method involved so-far untested assumptions. We applied four analog approaches to a continental-scale set of bioclimatic and plant-distribution presence/absence data for North America to assess how well this method works under near-optimal modern conditions. For each point on the grid, we calculated the similarity between its vegetation assemblage and those of all other points on the grid (excluding nearby points). The climate of the points with the most similar vegetation was used to estimate the climate at the target grid point. Estimates based the use of the Jaccard similarity coefficient had smaller errors than those based on the use of a new similarity coefficient, although the latter may be more robust because it does not assume that the "fossil" assemblage is complete. The results of these analyses indicate that presence/absence vegetation assemblages provide a valid basis for estimating bioclimates on the continental scale. However, the accuracy of the estimates is strongly tied to the number of species in the target assemblage, and the analog method is necessarily constrained to produce estimates that fall within the range of observed values. We applied the four modern analog approaches and the mutual overlap (or "mutual climatic range") method to estimate bioclimatic conditions represented by the plant macrofossil assemblage from a packrat midden of Last Glacial Maximum age from southern Nevada. In general, the estimation approaches produced similar results in regard to moisture conditions, but there was a greater range of estimates for growing-degree days. Despite its limitations, the modern analog technique can provide paleoclimatic reconstructions that serve as the starting point to the interpretation of past climatic conditions.

An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics

NASA Technical Reports Server (NTRS)

imon, Donald L.; Armstrong, Jeffrey B.

2012-01-01

A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.

Nonlinear Spectral Mixture Modeling to Estimate Water-Ice Abundance of Martian Regolith

NASA Astrophysics Data System (ADS)

Gyalay, Szilard; Chu, Kathryn; Zeev Noe Dobrea, Eldar

2017-10-01

We present a novel technique to estimate the abundance of water-ice in the Martian permafrost using Phoenix Surface Stereo Imager multispectral data. In previous work, Cull et al. (2010) estimated the abundance of water-ice in trenches dug by the Mars Phoenix lander by modeling the spectra of the icy regolith using the radiative transfer methods described in Hapke (2008) with optical constants for Mauna Kea palagonite (Clancy et al., 1995) as a substitute for unknown Martian regolith optical constants. Our technique, which uses the radiative transfer methods described in Shkuratov et al. (1999), seeks to eliminate the uncertainty that stems from not knowing the composition of the Martian regolith by using observations of the Martian soil before and after the water-ice has sublimated away. We use observations of the desiccated regolith sample to estimate its complex index of refraction from its spectrum. This removes any a priori assumptions of Martian regolith composition, limiting our free parameters to the estimated real index of refraction of the dry regolith at one specific wavelength, ice grain size, and regolith porosity. We can then model mixtures of regolith and water-ice, fitting to the original icy spectrum to estimate the ice abundance. To constrain the uncertainties in this technique, we performed laboratory measurements of the spectra of known mixtures of water-ice and dry soils as well as those of soils after desiccation with controlled viewing geometries. Finally, we applied the technique to Phoenix Surface Stereo Imager observations and estimated water-ice abundances consistent with pore-fill in the near-surface ice. This abundance is consistent with atmospheric diffusion, which has implications to our understanding of the history of water-ice on Mars and the role of the regolith at high latitudes as a reservoir of atmospheric H2O.

Applying Ancestry and Sex Computation as a Quality Control Tool in Targeted Next-Generation Sequencing.

PubMed

Mathias, Patrick C; Turner, Emily H; Scroggins, Sheena M; Salipante, Stephen J; Hoffman, Noah G; Pritchard, Colin C; Shirts, Brian H

2016-03-01

To apply techniques for ancestry and sex computation from next-generation sequencing (NGS) data as an approach to confirm sample identity and detect sample processing errors. We combined a principal component analysis method with k-nearest neighbors classification to compute the ancestry of patients undergoing NGS testing. By combining this calculation with X chromosome copy number data, we determined the sex and ancestry of patients for comparison with self-report. We also modeled the sensitivity of this technique in detecting sample processing errors. We applied this technique to 859 patient samples with reliable self-report data. Our k-nearest neighbors ancestry screen had an accuracy of 98.7% for patients reporting a single ancestry. Visual inspection of principal component plots was consistent with self-report in 99.6% of single-ancestry and mixed-ancestry patients. Our model demonstrates that approximately two-thirds of potential sample swaps could be detected in our patient population using this technique. Patient ancestry can be estimated from NGS data incidentally sequenced in targeted panels, enabling an inexpensive quality control method when coupled with patient self-report. © American Society for Clinical Pathology, 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Distributed Noise Generation for Density Estimation Based Clustering without Trusted Third Party

NASA Astrophysics Data System (ADS)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

The rapid growth of the Internet provides people with tremendous opportunities for data collection, knowledge discovery and cooperative computation. However, it also brings the problem of sensitive information leakage. Both individuals and enterprises may suffer from the massive data collection and the information retrieval by distrusted parties. In this paper, we propose a privacy-preserving protocol for the distributed kernel density estimation-based clustering. Our scheme applies random data perturbation (RDP) technique and the verifiable secret sharing to solve the security problem of distributed kernel density estimation in [4] which assumed a mediate party to help in the computation.

Estimation for coefficient of variation of an extension of the exponential distribution under type-II censoring scheme

NASA Astrophysics Data System (ADS)

Bakoban, Rana A.

2017-08-01

The coefficient of variation [CV] has several applications in applied statistics. So in this paper, we adopt Bayesian and non-Bayesian approaches for the estimation of CV under type-II censored data from extension exponential distribution [EED]. The point and interval estimate of the CV are obtained for each of the maximum likelihood and parametric bootstrap techniques. Also the Bayesian approach with the help of MCMC method is presented. A real data set is presented and analyzed, hence the obtained results are used to assess the obtained theoretical results.

Ridge Regression Signal Processing

NASA Technical Reports Server (NTRS)

Kuhl, Mark R.

1990-01-01

The introduction of the Global Positioning System (GPS) into the National Airspace System (NAS) necessitates the development of Receiver Autonomous Integrity Monitoring (RAIM) techniques. In order to guarantee a certain level of integrity, a thorough understanding of modern estimation techniques applied to navigational problems is required. The extended Kalman filter (EKF) is derived and analyzed under poor geometry conditions. It was found that the performance of the EKF is difficult to predict, since the EKF is designed for a Gaussian environment. A novel approach is implemented which incorporates ridge regression to explain the behavior of an EKF in the presence of dynamics under poor geometry conditions. The basic principles of ridge regression theory are presented, followed by the derivation of a linearized recursive ridge estimator. Computer simulations are performed to confirm the underlying theory and to provide a comparative analysis of the EKF and the recursive ridge estimator.

Frequency-wavenumber processing for infrasound distributed arrays.

PubMed

Costley, R Daniel; Frazier, W Garth; Dillion, Kevin; Picucci, Jennifer R; Williams, Jay E; McKenna, Mihan H

2013-10-01

The work described herein discusses the application of a frequency-wavenumber signal processing technique to signals from rectangular infrasound arrays for detection and estimation of the direction of travel of infrasound. Arrays of 100 sensors were arranged in square configurations with sensor spacing of 2 m. Wind noise data were collected at one site. Synthetic infrasound signals were superposed on top of the wind noise to determine the accuracy and sensitivity of the technique with respect to signal-to-noise ratio. The technique was then applied to an impulsive event recorded at a different site. Preliminary results demonstrated the feasibility of this approach.

Prediction of field emitter cathode lifetime based on measurement of I- V curves

NASA Astrophysics Data System (ADS)

Bormashov, V. S.; Nikolski, K. N.; Baturin, A. S.; Sheshin, E. P.

2003-06-01

A technique is presented, which allows the prediction of field emitter cathode lifetime without long-term direct measurements of cathode parameters stability. This technique is based on periodic measurements of cathode I- V characteristics. Moreover, it allows performing a post-experiment optimization for the appropriate choice of the feedback system to provide a stable operation during a long time. The proposed technique was applied to study the emission properties of reticulated vitreous carbon (RVC) and thermo-enlarged graphite (TEG). For the given cathodes, the characteristic time of the cathode destruction was estimated.

Accurate low-cost methods for performance evaluation of cache memory systems

NASA Technical Reports Server (NTRS)

Laha, Subhasis; Patel, Janak H.; Iyer, Ravishankar K.

1988-01-01

Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

Improved Sizing of Impact Damage in Composites Based on Thermographic Response

NASA Technical Reports Server (NTRS)

Winfree, William P.; Howell Patricia A.; Leckey, Cara A.; Rogge, Matthew D.

2013-01-01

Impact damage in thin carbon fiber reinforced polymer composites often results in a relatively small region of damage at the front surface, with increasing damage near the back surface. Conventional methods for reducing the pulsed thermographic responses of the composite tend to underestimate the size of the back surface damage, since the smaller near surface damage gives the largest thermographic indication. A method is presented for reducing the thermographic data to produce an estimated size for the impact damage that is much closer to the size of the damage estimated from other NDE techniques such as microfocus x-ray computed tomography and pulse echo ultrasonics. Examples of the application of the technique to experimental data acquired on specimens with impact damage are presented. The method is also applied to the results of thermographic simulations to investigate the limitations of the technique.

Digital image classification approach for estimating forest clearing and regrowth rates and trends

NASA Technical Reports Server (NTRS)

Sader, Steven A.

1987-01-01

A technique is presented to monitor vegetation changes for a selected study area in Costa Rica. A normalized difference vegetation index was computed for three dates of Landsat satellite data and a modified parallelipiped classifier was employed to generate a multitemporal greenness image representing all three dates. A second-generation image was created by partitioning the intensity levels at each date into high, medium, and low and thereby reducing the number of classes to 21. A sampling technique was applied to describe forest and other land cover change occurring between time periods based on interpretation of aerial photography that closely matched the dates of satellite acquisition. Comparison of the Landsat-derived classes with the photo-interpreted sample areas can provide a basis for evaluating the satellite monitoring technique and the accuracy of estimating forest clearing and regrowth rates and trends.

Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise.

PubMed

Wang, Junxiang; Wang, Xianpeng; Xu, Dingjie; Bi, Guoan

2018-03-09

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method.

Uncertainty in Population Growth Rates: Determining Confidence Intervals from Point Estimates of Parameters

PubMed Central

Devenish Nelson, Eleanor S.; Harris, Stephen; Soulsbury, Carl D.; Richards, Shane A.; Stephens, Philip A.

2010-01-01

Background Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth. Methodology/Principal Findings We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort. Conclusions/Significance Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species. PMID:21049049

Machine learning approaches for estimation of prediction interval for the model output.

PubMed

Shrestha, Durga L; Solomatine, Dimitri P

2006-03-01

A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the prediction interval) of the underlying distribution of prediction errors. The idea is to partition the input space into different zones or clusters having similar model errors using fuzzy c-means clustering. The prediction interval is constructed for each cluster on the basis of empirical distributions of the errors associated with all instances belonging to the cluster under consideration and propagated from each cluster to the examples according to their membership grades in each cluster. Then a regression model is built for in-sample data using computed prediction limits as targets, and finally, this model is applied to estimate the prediction intervals (limits) for out-of-sample data. The method was tested on artificial and real hydrologic data sets using various machine learning techniques. Preliminary results show that the method is superior to other methods estimating the prediction interval. A new method for evaluating performance for estimating prediction interval is proposed as well.

New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies.

PubMed

Essa, Khalid S

2014-01-01

A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values.

Robust Angle Estimation for MIMO Radar with the Coexistence of Mutual Coupling and Colored Noise

PubMed Central

Wang, Junxiang; Wang, Xianpeng; Xu, Dingjie; Bi, Guoan

2018-01-01

This paper deals with joint estimation of direction-of-departure (DOD) and direction-of- arrival (DOA) in bistatic multiple-input multiple-output (MIMO) radar with the coexistence of unknown mutual coupling and spatial colored noise by developing a novel robust covariance tensor-based angle estimation method. In the proposed method, a third-order tensor is firstly formulated for capturing the multidimensional nature of the received data. Then taking advantage of the temporal uncorrelated characteristic of colored noise and the banded complex symmetric Toeplitz structure of the mutual coupling matrices, a novel fourth-order covariance tensor is constructed for eliminating the influence of both spatial colored noise and mutual coupling. After a robust signal subspace estimation is obtained by using the higher-order singular value decomposition (HOSVD) technique, the rotational invariance technique is applied to achieve the DODs and DOAs. Compared with the existing HOSVD-based subspace methods, the proposed method can provide superior angle estimation performance and automatically jointly perform the DODs and DOAs. Results from numerical experiments are presented to verify the effectiveness of the proposed method. PMID:29522499

Trans-dimensional and hierarchical Bayesian approaches toward rigorous estimation of seismic sources and structures in the Northeast Asia

NASA Astrophysics Data System (ADS)

Kim, Seongryong; Tkalčić, Hrvoje; Mustać, Marija; Rhie, Junkee; Ford, Sean

2016-04-01

A framework is presented within which we provide rigorous estimations for seismic sources and structures in the Northeast Asia. We use Bayesian inversion methods, which enable statistical estimations of models and their uncertainties based on data information. Ambiguities in error statistics and model parameterizations are addressed by hierarchical and trans-dimensional (trans-D) techniques, which can be inherently implemented in the Bayesian inversions. Hence reliable estimation of model parameters and their uncertainties is possible, thus avoiding arbitrary regularizations and parameterizations. Hierarchical and trans-D inversions are performed to develop a three-dimensional velocity model using ambient noise data. To further improve the model, we perform joint inversions with receiver function data using a newly developed Bayesian method. For the source estimation, a novel moment tensor inversion method is presented and applied to regional waveform data of the North Korean nuclear explosion tests. By the combination of new Bayesian techniques and the structural model, coupled with meaningful uncertainties related to each of the processes, more quantitative monitoring and discrimination of seismic events is possible.

New fast least-squares algorithm for estimating the best-fitting parameters due to simple geometric-structures from gravity anomalies

PubMed Central

Essa, Khalid S.

2013-01-01

A new fast least-squares method is developed to estimate the shape factor (q-parameter) of a buried structure using normalized residual anomalies obtained from gravity data. The problem of shape factor estimation is transformed into a problem of finding a solution of a non-linear equation of the form f(q) = 0 by defining the anomaly value at the origin and at different points on the profile (N-value). Procedures are also formulated to estimate the depth (z-parameter) and the amplitude coefficient (A-parameter) of the buried structure. The method is simple and rapid for estimating parameters that produced gravity anomalies. This technique is used for a class of geometrically simple anomalous bodies, including the semi-infinite vertical cylinder, the infinitely long horizontal cylinder, and the sphere. The technique is tested and verified on theoretical models with and without random errors. It is also successfully applied to real data sets from Senegal and India, and the inverted-parameters are in good agreement with the known actual values. PMID:25685472

Nanoporous Anodic Alumina Surface Modification by Electrostatic, Covalent, and Immune Complexation Binding Investigated by Capillary Filling.

PubMed

Eckstein, Chris; Acosta, Laura K; Pol, Laura; Xifré-Pérez, Elisabet; Pallares, Josep; Ferré-Borrull, Josep; Marsal, Lluis F

2018-03-28

The fluid imbibition-coupled laser interferometry (FICLI) technique has been applied to detect and quantify surface changes and pore dimension variations in nanoporous anodic alumina (NAA) structures. FICLI is a noninvasive optical technique that permits the determination of the NAA average pore radius with high accuracy. In this work, the technique is applied after each step of different surface modification paths of the NAA pores: (i) electrostatic immobilization of bovine serum albumin (BSA), (ii) covalent attachment of streptavidin via (3-aminipropyl)-triethoxysilane and glutaraldehyde grafting, and (iii) immune complexation. Results show that BSA attachment can be detected as a reduction in estimated radius from FICLI with high accuracy and reproducibility. In the case of the covalent attachment of streptavidin, FICLI is able to recognize a multilayer formation of the silane and the protein. For immune complexation, the technique is able to detect different antibody-antigen bindings and distinguish different dynamics among different immune species.

Assessment and Calibration of Terrestrial Water Storage in North America with GRACE Level-1B Inter-satellite Residuals

NASA Astrophysics Data System (ADS)

Loomis, B.; Luthcke, S. B.

2016-12-01

The global time-variable gravity products from GRACE continue to provide unique and important measurements of vertically integrated terrestrial water storage (TWS). Despite substantial improvements in recent years to the quality of the GRACE solutions and analysis techniques, significant disagreements can still exist between various approaches to compute basin scale TWS. Applying the GRACE spherical harmonic solutions to TWS analysis requires the selection, design, and implementation of one of a wide variety of available filters. It is common to then estimate and apply a set of scale factors to these filtered solutions in an attempt to restore lost signal. The advent of global mascon solutions, such as those produced by our group at NASA GSFC, are an important advancement in time-variable gravity estimation. This method applies data-driven regularization at the normal equation level, resulting in improved estimates of regional TWS. Though mascons are a valuable product, the design of the constraint matrix, the global minimization of observation residuals, and the arc-specific parameters, all introduce the possibility that localized basin scale signals are not perfectly recovered. The precise inter-satellite ranging instrument provides the primary observation set for the GRACE gravity solutions. Recently, we have developed an approach to analyze and calibrate basin scale TWS estimates directly from the inter-satellite observation residuals. To summarize, we compute the range-acceleration residuals for two different forward models by executing separate runs of our Level-1B processing system. We then quantify the linear relationship that exists between the modeled mass and the residual differences, defining a simple differential correction procedure that is applied to the modeled signals. This new calibration procedure does not require the computationally expensive formation and inversion of normal equations, and it eliminates any influence the solution technique may have on the determined regional time series of TWS. We apply this calibration approach to sixteen drainage basins that cover North America and present new measurements of TWS determined directly from the Level-1B range-acceleration residuals. Lastly, we compare these new solutions to other GRACE solutions and independent datasets.

Estimating groundwater recharge

USGS Publications Warehouse

Healy, Richard W.; Scanlon, Bridget R.

2010-01-01

Understanding groundwater recharge is essential for successful management of water resources and modeling fluid and contaminant transport within the subsurface. This book provides a critical evaluation of the theory and assumptions that underlie methods for estimating rates of groundwater recharge. Detailed explanations of the methods are provided - allowing readers to apply many of the techniques themselves without needing to consult additional references. Numerous practical examples highlight benefits and limitations of each method. Approximately 900 references allow advanced practitioners to pursue additional information on any method. For the first time, theoretical and practical considerations for selecting and applying methods for estimating groundwater recharge are covered in a single volume with uniform presentation. Hydrogeologists, water-resource specialists, civil and agricultural engineers, earth and environmental scientists and agronomists will benefit from this informative and practical book. It can serve as the primary text for a graduate-level course on groundwater recharge or as an adjunct text for courses on groundwater hydrology or hydrogeology.

Motion Estimation and Compensation Strategies in Dynamic Computerized Tomography

NASA Astrophysics Data System (ADS)

Hahn, Bernadette N.

2017-12-01

A main challenge in computerized tomography consists in imaging moving objects. Temporal changes during the measuring process lead to inconsistent data sets, and applying standard reconstruction techniques causes motion artefacts which can severely impose a reliable diagnostics. Therefore, novel reconstruction techniques are required which compensate for the dynamic behavior. This article builds on recent results from a microlocal analysis of the dynamic setting, which enable us to formulate efficient analytic motion compensation algorithms for contour extraction. Since these methods require information about the dynamic behavior, we further introduce a motion estimation approach which determines parameters of affine and certain non-affine deformations directly from measured motion-corrupted Radon-data. Our methods are illustrated with numerical examples for both types of motion.

Crop identification technology assessment for remote sensing (CITARS). Volume 10: Interpretation of results

NASA Technical Reports Server (NTRS)

Bizzell, R. M.; Feiveson, A. H.; Hall, F. G.; Bauer, M. E.; Davis, B. J.; Malila, W. A.; Rice, D. P.

1975-01-01

The CITARS was an experiment designed to quantitatively evaluate crop identification performance for corn and soybeans in various environments using a well-defined set of automatic data processing (ADP) techniques. Each technique was applied to data acquired to recognize and estimate proportions of corn and soybeans. The CITARS documentation summarizes, interprets, and discusses the crop identification performances obtained using (1) different ADP procedures; (2) a linear versus a quadratic classifier; (3) prior probability information derived from historic data; (4) local versus nonlocal recognition training statistics and the associated use of preprocessing; (5) multitemporal data; (6) classification bias and mixed pixels in proportion estimation; and (7) data with differnt site characteristics, including crop, soil, atmospheric effects, and stages of crop maturity.

Development of a winter wheat adjustable crop calendar model. [Colorado, Idaho, Oklahoma, Montana, Kansas, Missouri, North Dakota and Texas

NASA Technical Reports Server (NTRS)

Baker, J. R. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Least squares techniques were applied for parameter estimation of functions to predict winter wheat phenological stage with daily maximum temperature, minimum temperature, daylength, and precipitation as independent variables. After parameter estimation, tests were conducted using independent data. It may generally be concluded that exponential functions have little advantage over polynomials. Precipitation was not found to significantly affect the fits. The Robertson triquadratic form, in general use for spring wheat, yielded good results, but special techniques and care are required. In most instances, equations with nonlinear effects were found to yield erratic results when utilized with averaged daily environmental values as independent variables.

Q-adjusting technique applied to vertical deflections estimation in a single-axis rotation INS/GPS integrated system

NASA Astrophysics Data System (ADS)

Zhu, Jing; Wang, Xingshu; Wang, Jun; Dai, Dongkai; Xiong, Hao

2016-10-01

Former studies have proved that the attitude error in a single-axis rotation INS/GPS integrated system tracks the high frequency component of the deflections of the vertical (DOV) with a fixed delay and tracking error. This paper analyses the influence of the nominal process noise covariance matrix Q on the tracking error as well as the response delay, and proposed a Q-adjusting technique to obtain the attitude error which can track the DOV better. Simulation results show that different settings of Q lead to different response delay and tracking error; there exists optimal Q which leads to a minimum tracking error and a comparatively short response delay; for systems with different accuracy, different Q-adjusting strategy should be adopted. In this way, the DOV estimation accuracy of using the attitude error as the observation can be improved. According to the simulation results, the DOV estimation accuracy after using the Q-adjusting technique is improved by approximate 23% and 33% respectively compared to that of the Earth Model EGM2008 and the direct attitude difference method.

Implementation Of Fuzzy Approach To Improve Time Estimation [Case Study Of A Thermal Power Plant Is Considered

NASA Astrophysics Data System (ADS)

Pradhan, Moumita; Pradhan, Dinesh; Bandyopadhyay, G.

2010-10-01

Fuzzy System has demonstrated their ability to solve different kinds of problem in various application domains. There is an increasing interest to apply fuzzy concept to improve tasks of any system. Here case study of a thermal power plant is considered. Existing time estimation represents time to complete tasks. Applying fuzzy linear approach it becomes clear that after each confidence level least time is taken to complete tasks. As time schedule is less than less amount of cost is needed. Objective of this paper is to show how one system becomes more efficient in applying Fuzzy Linear approach. In this paper we want to optimize the time estimation to perform all tasks in appropriate time schedules. For the case study, optimistic time (to), pessimistic time (tp), most likely time(tm) is considered as data collected from thermal power plant. These time estimates help to calculate expected time(te) which represents time to complete particular task to considering all happenings. Using project evaluation and review technique (PERT) and critical path method (CPM) concept critical path duration (CPD) of this project is calculated. This tells that the probability of fifty percent of the total tasks can be completed in fifty days. Using critical path duration and standard deviation of the critical path, total completion of project can be completed easily after applying normal distribution. Using trapezoidal rule from four time estimates (to, tm, tp, te), we can calculate defuzzyfied value of time estimates. For range of fuzzy, we consider four confidence interval level say 0.4, 0.6, 0.8,1. From our study, it is seen that time estimates at confidence level between 0.4 and 0.8 gives the better result compared to other confidence levels.

GPU Acceleration of Mean Free Path Based Kernel Density Estimators for Monte Carlo Neutronics Simulations

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

Burke, TImothy P.; Kiedrowski, Brian C.; Martin, William R.

Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics formore » one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.« less

On the appropriateness of applying chi-square distribution based confidence intervals to spectral estimates of helicopter flyover data

NASA Technical Reports Server (NTRS)

Rutledge, Charles K.

1988-01-01

The validity of applying chi-square based confidence intervals to far-field acoustic flyover spectral estimates was investigated. Simulated data, using a Kendall series and experimental acoustic data from the NASA/McDonnell Douglas 500E acoustics test, were analyzed. Statistical significance tests to determine the equality of distributions of the simulated and experimental data relative to theoretical chi-square distributions were performed. Bias and uncertainty errors associated with the spectral estimates were easily identified from the data sets. A model relating the uncertainty and bias errors to the estimates resulted, which aided in determining the appropriateness of the chi-square distribution based confidence intervals. Such confidence intervals were appropriate for nontonally associated frequencies of the experimental data but were inappropriate for tonally associated estimate distributions. The appropriateness at the tonally associated frequencies was indicated by the presence of bias error and noncomformity of the distributions to the theoretical chi-square distribution. A technique for determining appropriate confidence intervals at the tonally associated frequencies was suggested.

Estimation of High-Dimensional Graphical Models Using Regularized Score Matching

PubMed Central

Lin, Lina; Drton, Mathias; Shojaie, Ali

2017-01-01

Graphical models are widely used to model stochastic dependences among large collections of variables. We introduce a new method of estimating undirected conditional independence graphs based on the score matching loss, introduced by Hyvärinen (2005), and subsequently extended in Hyvärinen (2007). The regularized score matching method we propose applies to settings with continuous observations and allows for computationally efficient treatment of possibly non-Gaussian exponential family models. In the well-explored Gaussian setting, regularized score matching avoids issues of asymmetry that arise when applying the technique of neighborhood selection, and compared to existing methods that directly yield symmetric estimates, the score matching approach has the advantage that the considered loss is quadratic and gives piecewise linear solution paths under ℓ1 regularization. Under suitable irrepresentability conditions, we show that ℓ1-regularized score matching is consistent for graph estimation in sparse high-dimensional settings. Through numerical experiments and an application to RNAseq data, we confirm that regularized score matching achieves state-of-the-art performance in the Gaussian case and provides a valuable tool for computationally efficient estimation in non-Gaussian graphical models. PMID:28638498

A potential-energy surface study of the 2A1 and low-lying dissociative states of the methoxy radical

NASA Technical Reports Server (NTRS)

Jackels, C. F.

1985-01-01

Accurate, ab initio quantum chemical techniques are applied in the present study of low lying bound and dissociative states of the methoxy radical at C3nu conformations, using a double zeta quality basis set that is augmented with polarization and diffuse functions. Excitation energy estimates are obtained for vertical excitation, vertical deexcitation, and system origin. The rate of methoxy photolysis is estimated to be too small to warrant its inclusion in atmospheric models.

Peak-Seeking Control Using Gradient and Hessian Estimates

NASA Technical Reports Server (NTRS)

Ryan, John J.; Speyer, Jason L.

2010-01-01

A peak-seeking control method is presented which utilizes a linear time-varying Kalman filter. Performance function coordinate and magnitude measurements are used by the Kalman filter to estimate the gradient and Hessian of the performance function. The gradient and Hessian are used to command the system toward a local extremum. The method is naturally applied to multiple-input multiple-output systems. Applications of this technique to a single-input single-output example and a two-input one-output example are presented.

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Polynomial elimination theory and non-linear stability analysis for the Euler equations

NASA Technical Reports Server (NTRS)

Kennon, S. R.; Dulikravich, G. S.; Jespersen, D. C.

1986-01-01

Numerical methods are presented that exploit the polynomial properties of discretizations of the Euler equations. It is noted that most finite difference or finite volume discretizations of the steady-state Euler equations produce a polynomial system of equations to be solved. These equations are solved using classical polynomial elimination theory, with some innovative modifications. This paper also presents some preliminary results of a new non-linear stability analysis technique. This technique is applicable to determining the stability of polynomial iterative schemes. Results are presented for applying the elimination technique to a one-dimensional test case. For this test case, the exact solution is computed in three iterations. The non-linear stability analysis is applied to determine the optimal time step for solving Burgers' equation using the MacCormack scheme. The estimated optimal time step is very close to the time step that arises from a linear stability analysis.

Enhancing e-waste estimates: improving data quality by multivariate Input-Output Analysis.

PubMed

Wang, Feng; Huisman, Jaco; Stevels, Ab; Baldé, Cornelis Peter

2013-11-01

Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input-Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Leakage radiation interference microscopy.

PubMed

Descrovi, Emiliano; Barakat, Elsie; Angelini, Angelo; Munzert, Peter; De Leo, Natascia; Boarino, Luca; Giorgis, Fabrizio; Herzig, Hans Peter

2013-09-01

We present a proof of principle for a new imaging technique combining leakage radiation microscopy with high-resolution interference microscopy. By using oil immersion optics it is demonstrated that amplitude and phase can be retrieved from optical fields, which are evanescent in air. This technique is illustratively applied for mapping a surface mode propagating onto a planar dielectric multilayer on a thin glass substrate. The surface mode propagation constant estimated after Fourier transformation of the measured complex field is well matched with an independent measurement based on back focal plane imaging.

Kernel analysis in TeV gamma-ray selection

NASA Astrophysics Data System (ADS)

Moriarty, P.; Samuelson, F. W.

2000-06-01

We discuss the use of kernel analysis as a technique for selecting gamma-ray candidates in Atmospheric Cherenkov astronomy. The method is applied to observations of the Crab Nebula and Markarian 501 recorded with the Whipple 10 m Atmospheric Cherenkov imaging system, and the results are compared with the standard Supercuts analysis. Since kernel analysis is computationally intensive, we examine approaches to reducing the computational load. Extension of the technique to estimate the energy of the gamma-ray primary is considered. .

Research reactor loading pattern optimization using estimation of distribution algorithms

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

Jiang, S.; Ziver, K.; AMCG Group, RM Consultants, Abingdon

2006-07-01

A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K{sub eff}) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K{sub eff} with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristicmore » Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)« less

A robust vision-based sensor fusion approach for real-time pose estimation.

PubMed

Assa, Akbar; Janabi-Sharifi, Farrokh

2014-02-01

Object pose estimation is of great importance to many applications, such as augmented reality, localization and mapping, motion capture, and visual servoing. Although many approaches based on a monocular camera have been proposed, only a few works have concentrated on applying multicamera sensor fusion techniques to pose estimation. Higher accuracy and enhanced robustness toward sensor defects or failures are some of the advantages of these schemes. This paper presents a new Kalman-based sensor fusion approach for pose estimation that offers higher accuracy and precision, and is robust to camera motion and image occlusion, compared to its predecessors. Extensive experiments are conducted to validate the superiority of this fusion method over currently employed vision-based pose estimation algorithms.

Guaranteed estimation of solutions to Helmholtz transmission problems with uncertain data from their indirect noisy observations

NASA Astrophysics Data System (ADS)

Podlipenko, Yu. K.; Shestopalov, Yu. V.

2017-09-01

We investigate the guaranteed estimation problem of linear functionals from solutions to transmission problems for the Helmholtz equation with inexact data. The right-hand sides of equations entering the statements of transmission problems and the statistical characteristics of observation errors are supposed to be unknown and belonging to certain sets. It is shown that the optimal linear mean square estimates of the above mentioned functionals and estimation errors are expressed via solutions to the systems of transmission problems of the special type. The results and techniques can be applied in the analysis and estimation of solution to forward and inverse electromagnetic and acoustic problems with uncertain data that arise in mathematical models of the wave diffraction on transparent bodies.

Percolation analysis of nonlinear structures in scale-free two-dimensional simulations

NASA Technical Reports Server (NTRS)

Dominik, Kurt G.; Shandarin, Sergei F.

1992-01-01

Results are presented of applying percolation analysis to several two-dimensional N-body models which simulate the formation of large-scale structure. Three parameters are estimated: total area (a(c)), total mass (M(C)), and percolation density (rho(c)) of the percolating structure at the percolation threshold for both unsmoothed and smoothed (with different scales L(s)) nonlinear with filamentary structures, confirming early speculations that this type of model has several features of filamentary-type distributions. Also, it is shown that, by properly applying smoothing techniques, many problems previously considered detrimental can be dealt with and overcome. Possible difficulties and prospects with the use of this method are discussed, specifically relating to techniques and methods already applied to CfA deep sky surveys. The success of this test in two dimensions and the potential for extrapolation to three dimensions is also discussed.

Framework for the mapping of the monthly average daily solar radiation using an advanced case-based reasoning and a geostatistical technique.

PubMed

Lee, Minhyun; Koo, Choongwan; Hong, Taehoon; Park, Hyo Seon

2014-04-15

For the effective photovoltaic (PV) system, it is necessary to accurately determine the monthly average daily solar radiation (MADSR) and to develop an accurate MADSR map, which can simplify the decision-making process for selecting the suitable location of the PV system installation. Therefore, this study aimed to develop a framework for the mapping of the MADSR using an advanced case-based reasoning (CBR) and a geostatistical technique. The proposed framework consists of the following procedures: (i) the geographic scope for the mapping of the MADSR is set, and the measured MADSR and meteorological data in the geographic scope are collected; (ii) using the collected data, the advanced CBR model is developed; (iii) using the advanced CBR model, the MADSR at unmeasured locations is estimated; and (iv) by applying the measured and estimated MADSR data to the geographic information system, the MADSR map is developed. A practical validation was conducted by applying the proposed framework to South Korea. It was determined that the MADSR map developed through the proposed framework has been improved in terms of accuracy. The developed MADSR map can be used for estimating the MADSR at unmeasured locations and for determining the optimal location for the PV system installation.

A general diagnostic model applied to language testing data.

PubMed

von Davier, Matthias

2008-11-01

Probabilistic models with one or more latent variables are designed to report on a corresponding number of skills or cognitive attributes. Multidimensional skill profiles offer additional information beyond what a single test score can provide, if the reported skills can be identified and distinguished reliably. Many recent approaches to skill profile models are limited to dichotomous data and have made use of computationally intensive estimation methods such as Markov chain Monte Carlo, since standard maximum likelihood (ML) estimation techniques were deemed infeasible. This paper presents a general diagnostic model (GDM) that can be estimated with standard ML techniques and applies to polytomous response variables as well as to skills with two or more proficiency levels. The paper uses one member of a larger class of diagnostic models, a compensatory diagnostic model for dichotomous and partial credit data. Many well-known models, such as univariate and multivariate versions of the Rasch model and the two-parameter logistic item response theory model, the generalized partial credit model, as well as a variety of skill profile models, are special cases of this GDM. In addition to an introduction to this model, the paper presents a parameter recovery study using simulated data and an application to real data from the field test for TOEFL Internet-based testing.

Eruption mass estimation using infrasound waveform inversion and ash and gas measurements: Evaluation at Sakurajima Volcano, Japan

NASA Astrophysics Data System (ADS)

Fee, David; Izbekov, Pavel; Kim, Keehoon; Yokoo, Akihiko; Lopez, Taryn; Prata, Fred; Kazahaya, Ryunosuke; Nakamichi, Haruhisa; Iguchi, Masato

2017-12-01

Eruption mass and mass flow rate are critical parameters for determining the aerial extent and hazard of volcanic emissions. Infrasound waveform inversion is a promising technique to quantify volcanic emissions. Although topography may substantially alter the infrasound waveform as it propagates, advances in wave propagation modeling and station coverage permit robust inversion of infrasound data from volcanic explosions. The inversion can estimate eruption mass flow rate and total eruption mass if the flow density is known. However, infrasound-based eruption flow rates and mass estimates have yet to be validated against independent measurements, and numerical modeling has only recently been applied to the inversion technique. Here we present a robust full-waveform acoustic inversion method, and use it to calculate eruption flow rates and masses from 49 explosions from Sakurajima Volcano, Japan. Six infrasound stations deployed from 12-20 February 2015 recorded the explosions. We compute numerical Green's functions using 3-D Finite Difference Time Domain modeling and a high-resolution digital elevation model. The inversion, assuming a simple acoustic monopole source, provides realistic eruption masses and excellent fit to the data for the majority of the explosions. The inversion results are compared to independent eruption masses derived from ground-based ash collection and volcanic gas measurements. Assuming realistic flow densities, our infrasound-derived eruption masses for ash-rich eruptions compare favorably to the ground-based estimates, with agreement ranging from within a factor of two to one order of magnitude. Uncertainties in the time-dependent flow density and acoustic propagation likely contribute to the mismatch between the methods. Our results suggest that realistic and accurate infrasound-based eruption mass and mass flow rate estimates can be computed using the method employed here. If accurate volcanic flow parameters are known, application of this technique could be broadly applied to enable near real-time calculation of eruption mass flow rates and total masses. These critical input parameters for volcanic eruption modeling and monitoring are not currently available.

Integrated survival analysis using an event-time approach in a Bayesian framework

USGS Publications Warehouse

Walsh, Daniel P.; Dreitz, VJ; Heisey, Dennis M.

2015-01-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Integrated survival analysis using an event-time approach in a Bayesian framework.

PubMed

Walsh, Daniel P; Dreitz, Victoria J; Heisey, Dennis M

2015-02-01

Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.

Disaster debris estimation using high-resolution polarimetric stereo-SAR

NASA Astrophysics Data System (ADS)

Koyama, Christian N.; Gokon, Hideomi; Jimbo, Masaru; Koshimura, Shunichi; Sato, Motoyuki

2016-10-01

This paper addresses the problem of debris estimation which is one of the most important initial challenges in the wake of a disaster like the Great East Japan Earthquake and Tsunami. Reasonable estimates of the debris have to be made available to decision makers as quickly as possible. Current approaches to obtain this information are far from being optimal as they usually rely on manual interpretation of optical imagery. We have developed a novel approach for the estimation of tsunami debris pile heights and volumes for improved emergency response. The method is based on a stereo-synthetic aperture radar (stereo-SAR) approach for very high-resolution polarimetric SAR. An advanced gradient-based optical-flow estimation technique is applied for optimal image coregistration of the low-coherence non-interferometric data resulting from the illumination from opposite directions and in different polarizations. By applying model based decomposition of the coherency matrix, only the odd bounce scattering contributions are used to optimize echo time computation. The method exclusively considers the relative height differences from the top of the piles to their base to achieve a very fine resolution in height estimation. To define the base, a reference point on non-debris-covered ground surface is located adjacent to the debris pile targets by exploiting the polarimetric scattering information. The proposed technique is validated using in situ data of real tsunami debris taken on a temporary debris management site in the tsunami affected area near Sendai city, Japan. The estimated height error is smaller than 0.6 m RMSE. The good quality of derived pile heights allows for a voxel-based estimation of debris volumes with a RMSE of 1099 m3. Advantages of the proposed method are fast computation time, and robust height and volume estimation of debris piles without the need for pre-event data or auxiliary information like DEM, topographic maps or GCPs.

Local measurement of error field using naturally rotating tearing mode dynamics in EXTRAP T2R

NASA Astrophysics Data System (ADS)

Sweeney, R. M.; Frassinetti, L.; Brunsell, P.; Fridström, R.; Volpe, F. A.

2016-12-01

An error field (EF) detection technique using the amplitude modulation of a naturally rotating tearing mode (TM) is developed and validated in the EXTRAP T2R reversed field pinch. The technique was used to identify intrinsic EFs of m/n  =  1/-12, where m and n are the poloidal and toroidal mode numbers. The effect of the EF and of a resonant magnetic perturbation (RMP) on the TM, in particular on amplitude modulation, is modeled with a first-order solution of the modified Rutherford equation. In the experiment, the TM amplitude is measured as a function of the toroidal angle as the TM rotates rapidly in the presence of an unknown EF and a known, deliberately applied RMP. The RMP amplitude is fixed while the toroidal phase is varied from one discharge to the other, completing a full toroidal scan. Using three such scans with different RMP amplitudes, the EF amplitude and phase are inferred from the phases at which the TM amplitude maximizes. The estimated EF amplitude is consistent with other estimates (e.g. based on the best EF-cancelling RMP, resulting in the fastest TM rotation). A passive variant of this technique is also presented, where no RMPs are applied, and the EF phase is deduced.

Program and Project Management Framework

NASA Technical Reports Server (NTRS)

Butler, Cassandra D.

2002-01-01

The primary objective of this project was to develop a framework and system architecture for integrating program and project management tools that may be applied consistently throughout Kennedy Space Center (KSC) to optimize planning, cost estimating, risk management, and project control. Project management methodology used in building interactive systems to accommodate the needs of the project managers is applied as a key component in assessing the usefulness and applicability of the framework and tools developed. Research for the project included investigation and analysis of industrial practices, KSC standards, policies, and techniques, Systems Management Office (SMO) personnel, and other documented experiences of project management experts. In addition, this project documents best practices derived from the literature as well as new or developing project management models, practices, and techniques.

Estimating air chemical emissions from research activities using stack measurement data.

PubMed

Ballinger, Marcel Y; Duchsherer, Cheryl J; Woodruff, Rodger K; Larson, Timothy V

2013-03-01

Current methods of estimating air emissions from research and development (R&D) activities use a wide range of release fractions or emission factors with bases ranging from empirical to semi-empirical. Although considered conservative, the uncertainties and confidence levels of the existing methods have not been reported. Chemical emissions were estimated from sampling data taken from four research facilities over 10 years. The approach was to use a Monte Carlo technique to create distributions of annual emission estimates for target compounds detected in source test samples. Distributions were created for each year and building sampled for compounds with sufficient detection frequency to qualify for the analysis. The results using the Monte Carlo technique without applying a filter to remove negative emission values showed almost all distributions spanning zero, and 40% of the distributions having a negative mean. This indicates that emissions are so low as to be indistinguishable from building background. Application of a filter to allow only positive values in the distribution provided a more realistic value for emissions and increased the distribution mean by an average of 16%. Release fractions were calculated by dividing the emission estimates by a building chemical inventory quantity. Two variations were used for this quantity: chemical usage, and chemical usage plus one-half standing inventory. Filters were applied so that only release fraction values from zero to one were included in the resulting distributions. Release fractions had a wide range among chemicals and among data sets for different buildings and/or years for a given chemical. Regressions of release fractions to molecular weight and vapor pressure showed weak correlations. Similarly, regressions of mean emissions to chemical usage, chemical inventory, molecular weight, and vapor pressure also gave weak correlations. These results highlight the difficulties in estimating emissions from R&D facilities using chemical inventory data. Air emissions from research operations are difficult to estimate because of the changing nature of research processes and the small quantity and wide variety of chemicals used. Analysis of stack measurements taken over multiple facilities and a 10-year period using a Monte Carlo technique provided a method to quantify the low emissions and to estimate release fractions based on chemical inventories. The variation in release fractions did not correlate well with factors investigated, confirming the complexities in estimating R&D emissions.

Development of a Single Station 6C-Approach for Array Analysis and Microzonation: Using Vertical Rotation Rate to Estimate Love-Wave Disperion Curves and Direction Finding

NASA Astrophysics Data System (ADS)

Wassermann, J. M.; Wietek, A.; Hadziioannou, C.; Igel, H.

2014-12-01

Microzonation, i.e. the estimation of (shear) wave velocity profiles of the upper few 100m in dense 2D surface grids is one of the key methods to understand the variation in seismic hazard caused by ground shaking events. In this presentation we introduce a novel method for estimating the Love-wave phase velocity dispersion by using ambient noise recordings. We use the vertical component of rotational motions inherently present in ambient noise and the well established relation to simultaneous recordings of transverse acceleration. In this relation the frequency dependent phase velocity of a plane SH (or Love)-type wave acts as a proportionality factor between the anti-correlated amplitudes of both measures. In a first step we used synthetic data sets with increasing complexity to evaluate the proposed technique and the developed algorithm to extract the direction and amplitude of the incoming ambient noise wavefield measured at a single site. Since reliable weak rotational motion sensors are not yet readily available, we apply array derived rotation measurements in order to test our method. We next use the technique to analyze different real data sets of ambient noise measurements as well as seismic recordings at active volcanoes and compare these results with findings of the Spatial AutoCorrelation technique which was applied to the same data set. We demonstrate that the newly developed technique shows comparable results to more classical, strictly array based methods. Furthermore, we show that as soon as portable weak motion rotational motion sensors are available, a single 6C-station approach will be feasible, not only for microzonation but also for general array applications, with performance comparable to more classical techniques. An important advantage, especially in urban environments, is that with this approach, the number of seismic stations needed is drastically reduced.

Estimating Ergodic Capacity of Cooperative Analog Relaying under Different Adaptive Source Transmission Techniques

DTIC Science & Technology

2011-08-01

component in an airborne platform. Authorized licensed use limited to: ROME AFB. Downloaded on August 05,2010 at 14:47:37 UTC from IEEE Xplore ...UTC from IEEE Xplore . Restrictions apply. 2 . (7) For instance, it is not difficult to show that the MGF of for Nakagami-m fading with i.n.d fading...August 05,2010 at 14:47:37 UTC from IEEE Xplore . Restrictions apply. 3 ditions. Once again, using integration by parts, (14) can be concisely expressed

WREP: A wavelet-based technique for extracting the red edge position from reflectance spectra for estimating leaf and canopy chlorophyll contents of cereal crops

NASA Astrophysics Data System (ADS)

Li, Dong; Cheng, Tao; Zhou, Kai; Zheng, Hengbiao; Yao, Xia; Tian, Yongchao; Zhu, Yan; Cao, Weixing

2017-07-01

Red edge position (REP), defined as the wavelength of the inflexion point in the red edge region (680-760 nm) of the reflectance spectrum, has been widely used to estimate foliar chlorophyll content from reflectance spectra. A number of techniques have been developed for REP extraction in the past three decades, but most of them require data-specific parameterization and the consistence of their performance from leaf to canopy levels remains poorly understood. In this study, we propose a new technique (WREP) to extract REPs based on the application of continuous wavelet transform to reflectance spectra. The REP is determined by the zero-crossing wavelength in the red edge region of a wavelet transformed spectrum for a number of scales of wavelet decomposition. The new technique is simple to implement and requires no parameterization from the user as long as continuous wavelet transforms are applied to reflectance spectra. Its performance was evaluated for estimating leaf chlorophyll content (LCC) and canopy chlorophyll content (CCC) of cereal crops (i.e. rice and wheat) and compared with traditional techniques including linear interpolation, linear extrapolation, polynomial fitting and inverted Gaussian. Our results demonstrated that WREP obtained the best estimation accuracy for both LCC and CCC as compared to traditional techniques. High scales of wavelet decomposition were favorable for the estimation of CCC and low scales for the estimation of LCC. The difference in optimal scale reveals the underlying mechanism of signature transfer from leaf to canopy levels. In addition, crop-specific models were required for the estimation of CCC over the full range. However, a common model could be built with the REPs extracted with Scale 5 of the WREP technique for wheat and rice crops when CCC was less than 2 g/m2 (R2 = 0.73, RMSE = 0.26 g/m2). This insensitivity of WREP to crop type indicates the potential for aerial mapping of chlorophyll content between growth seasons of cereal crops. The new REP extraction technique provides us a new insight for understanding the spectral changes in the red edge region in response to chlorophyll variation from leaf to canopy levels.

Application of nonlinear least-squares regression to ground-water flow modeling, west-central Florida

USGS Publications Warehouse

Yobbi, D.K.

2000-01-01

A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.

Improved quantitative analysis of spectra using a new method of obtaining derivative spectra based on a singular perturbation technique.

PubMed

Li, Zhigang; Wang, Qiaoyun; Lv, Jiangtao; Ma, Zhenhe; Yang, Linjuan

2015-06-01

Spectroscopy is often applied when a rapid quantitative analysis is required, but one challenge is the translation of raw spectra into a final analysis. Derivative spectra are often used as a preliminary preprocessing step to resolve overlapping signals, enhance signal properties, and suppress unwanted spectral features that arise due to non-ideal instrument and sample properties. In this study, to improve quantitative analysis of near-infrared spectra, derivatives of noisy raw spectral data need to be estimated with high accuracy. A new spectral estimator based on singular perturbation technique, called the singular perturbation spectra estimator (SPSE), is presented, and the stability analysis of the estimator is given. Theoretical analysis and simulation experimental results confirm that the derivatives can be estimated with high accuracy using this estimator. Furthermore, the effectiveness of the estimator for processing noisy infrared spectra is evaluated using the analysis of beer spectra. The derivative spectra of the beer and the marzipan are used to build the calibration model using partial least squares (PLS) modeling. The results show that the PLS based on the new estimator can achieve better performance compared with the Savitzky-Golay algorithm and can serve as an alternative choice for quantitative analytical applications.

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

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

Aziz, H. M. Abdul; Ukkusuri, Satish V.

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

A novel approach to estimate emissions from large transportation networks: Hierarchical clustering-based link-driving-schedules for EPA-MOVES using dynamic time warping measures

DOE PAGES

Aziz, H. M. Abdul; Ukkusuri, Satish V.

2017-06-29

We present that EPA-MOVES (Motor Vehicle Emission Simulator) is often integrated with traffic simulators to assess emission levels of large-scale urban networks with signalized intersections. High variations in speed profiles exist in the context of congested urban networks with signalized intersections. The traditional average-speed-based emission estimation technique with EPA-MOVES provides faster execution while underestimates the emissions in most cases because of ignoring the speed variation at congested networks with signalized intersections. In contrast, the atomic second-by-second speed profile (i.e., the trajectory of each vehicle)-based technique provides accurate emissions at the cost of excessive computational power and time. We addressed thismore » issue by developing a novel method to determine the link-driving-schedules (LDSs) for the EPA-MOVES tool. Our research developed a hierarchical clustering technique with dynamic time warping similarity measures (HC-DTW) to find the LDS for EPA-MOVES that is capable of producing emission estimates better than the average-speed-based technique with execution time faster than the atomic speed profile approach. We applied the HC-DTW on a sample data from a signalized corridor and found that HC-DTW can significantly reduce computational time without compromising the accuracy. The developed technique in this research can substantially contribute to the EPA-MOVES-based emission estimation process for large-scale urban transportation network by reducing the computational time with reasonably accurate estimates. This method is highly appropriate for transportation networks with higher variation in speed such as signalized intersections. Lastly, experimental results show error difference ranging from 2% to 8% for most pollutants except PM 10.« less

Optimization of the tungsten oxide technique for measurement of atmospheric ammonia

NASA Technical Reports Server (NTRS)

Brown, Kenneth G.

1987-01-01

Hollow tubes coated with tungstic acid have been shown to be of value in the determination of ammonia and nitric acid in ambient air. Practical application of this technique was demonstrated utilizing an automated sampling system for in-flight collection and analysis of atmospheric samples. Due to time constraints these previous measurements were performed on tubes that had not been well characterized in the laboratory. As a result the experimental precision could not be accurately estimated. Since the technique was being compared to other techniques for measuring these compounds, it became necessary to perform laboratory tests which would establish the reliability of the technique. This report is a summary of these laboratory experiments as they are applied to the determination of ambient ammonia concentration.

To what degree does the missing-data technique influence the estimated growth in learning strategies over time? A tutorial example of sensitivity analysis for longitudinal data.

PubMed

Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter

2017-01-01

Longitudinal data is almost always burdened with missing data. However, in educational and psychological research, there is a large discrepancy between methodological suggestions and research practice. The former suggests applying sensitivity analysis in order to the robustness of the results in terms of varying assumptions regarding the mechanism generating the missing data. However, in research practice, participants with missing data are usually discarded by relying on listwise deletion. To help bridge the gap between methodological recommendations and applied research in the educational and psychological domain, this study provides a tutorial example of sensitivity analysis for latent growth analysis. The example data concern students' changes in learning strategies during higher education. One cohort of students in a Belgian university college was asked to complete the Inventory of Learning Styles-Short Version, in three measurement waves. A substantial number of students did not participate on each occasion. Change over time in student learning strategies was assessed using eight missing data techniques, which assume different mechanisms for missingness. The results indicated that, for some learning strategy subscales, growth estimates differed between the models. Guidelines in terms of reporting the results from sensitivity analysis are synthesised and applied to the results from the tutorial example.

Use of (137)Cs technique for soil erosion study in the agricultural region of Casablanca in Morocco.

PubMed

Nouira, A; Sayouty, E H; Benmansour, M

2003-01-01

Accelerated erosion and soil degradation currently cause serious problems to the Oued El Maleh basin (Morocco). Furthermore, there is still only limited information on rates of soil loss for optimising strategies for soil conservation. In the present study we have used the (137)Cs technique to assess the soil erosion rates on an agricultural land in Oued el Maleh basin near Casablanca (Morocco). A small representative agricultural field was selected to investigate the soil degradation required by soil managers in this region. The transect approach was applied for sampling to identify the spatial redistribution of (137)Cs. The spatial variability of (137)Cs inventory has provided evidence of the importance of tillage process and the human effects on the redistribution of (137)Cs. The mean (137)Cs inventory was found about 842 Bq m(-2), this value corresponds to an erosion rate of 82 tha(-1) yr(-1) by applying simplified mass balance model in a preliminary estimation. When data on site characteristics were available, the refined mass balance model was applied to highlight the contribution of tillage effect in soil redistribution. The erosion rate was estimated about 50 tha(-1) yr(-1). The aspects related to the sampling procedures and the models for calculation of erosion rates are discussed.

Atmospheric gradients from GNSS, VLBI, and DORIS analyses and from Numerical Weather Models during CONT14

NASA Astrophysics Data System (ADS)

Heinkelmann, Robert; Dick, Galina; Nilsson, Tobias; Soja, Benedikt; Wickert, Jens; Zus, Florian; Schuh, Harald

2015-04-01

Observations from space-geodetic techniques are nowadays increasingly used to derive atmospheric information for various commercial and scientific applications. A prominent example is the operational use of GNSS data to improve global and regional weather forecasts, which was started in 2006. Atmosphere gradients describe the azimuthal asymmetry of zenith delays. Estimates of geodetic and other parameters significantly improve when atmosphere gradients are determined in addition. Here we assess the capability of several space geodetic techniques (GNSS, VLBI, DORIS) to determine atmosphere gradients of refractivity. For this purpose we implement and compare various strategies for gradient estimation, such as different values for the temporal resolution and the corresponding parameter constraints. Applying least squares estimation the gradients are usually deterministically modelled as constants or piece-wise linear functions. In our study we compare this approach with a stochastic approach modelling atmosphere gradients as random walk processes and applying a Kalman Filter for parameter estimation. The gradients, derived from space geodetic techniques are verified by comparison with those derived from Numerical Weather Models (NWM). These model data were generated using raytracing calculations based on European Centre for Medium-Range Weather Forecast (ECMWF) and National Centers for Environmental Prediction (NCEP) analyses with different spatial resolutions. The investigation of the differences between the ECMWF and NCEP gradients hereby in addition allow for an empirical assessment of the quality of model gradients and how suitable the NWM data are for verification. CONT14 (2014-05-06 until 2014-05-20) is the youngest two week long continuous VLBI campaign carried out by IVS (International VLBI Service for Geodesy and Astrometry). It presents the state-of-the-art VLBI performance in terms of number of stations and number of observations and presents thus an excellent test period for comparisons with other space geodetic techniques. During the VLBI campaign CONT14 the HOBART12 and HOBART26 (Hobart, Tasmania, Australia) VLBI antennas were involved that co-locate with each other. The investigation of the gradient estimate differences from these co-located antennas allows for a valuable empirical quality assessment. Another quality criterion for gradient estimates are the differences of parameters at the borders of adjacent 24h-sessions. Both are investigated in our study.

Structural Health Monitoring for Impact Damage in Composite Structures.

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

Roach, Dennis P.; Raymond Bond; Doug Adams

Composite structures are increasing in prevalence throughout the aerospace, wind, defense, and transportation industries, but the many advantages of these materials come with unique challenges, particularly in inspecting and repairing these structures. Because composites of- ten undergo sub-surface damage mechanisms which compromise the structure without a clear visual indication, inspection of these components is critical to safely deploying composite re- placements to traditionally metallic structures. Impact damage to composites presents one of the most signi fi cant challenges because the area which is vulnerable to impact damage is generally large and sometimes very dif fi cult to access. This workmore » seeks to further evolve iden- ti fi cation technology by developing a system which can detect the impact load location and magnitude in real time, while giving an assessment of the con fi dence in that estimate. Fur- thermore, we identify ways by which impact damage could be more effectively identi fi ed by leveraging impact load identi fi cation information to better characterize damage. The impact load identi fi cation algorithm was applied to a commercial scale wind turbine blade, and results show the capability to detect impact magnitude and location using a single accelerometer, re- gardless of sensor location. A technique for better evaluating the uncertainty of the impact estimates was developed by quantifying how well the impact force estimate meets the assump- tions underlying the force estimation technique. This uncertainty quanti fi cation technique was found to reduce the 95% con fi dence interval by more than a factor of two for impact force estimates showing the least uncertainty, and widening the 95% con fi dence interval by a fac- tor of two for the most uncertain force estimates, avoiding the possibility of understating the uncertainty associated with these estimates. Linear vibration based damage detection tech- niques were investigated in the context of structural stiffness reductions and impact damage. A method by which the sensitivity to damage could be increased for simple structures was presented, and the challenges of applying that technique to a more complex structure were identi fi ed. The structural dynamic changes in a weak adhesive bond were investigated, and the results showed promise for identifying weak bonds that show little or no static reduction in stiffness. To address these challenges in identifying highly localized impact damage, the possi- bility of detecting damage through nonlinear dynamic characteristics was also identi fi ed, with a proposed technique which would leverage impact location estimates to enable the detection of impact damage. This nonlinear damage identi fi cation concept was evaluated on a composite panel with a substructure disbond, and the results showed that the nonlinear dynamics at the damage site could be observed without a baseline healthy reference. By further developing impact load identi fi cation technology and combining load and damage estimation techniques into an integrated solution, the challenges associated with impact detection in composite struc- tures can be effectively solved, thereby reducing costs, improving safety, and enhancing the operational readiness and availability of high value assets.« less

Models of Fate and Transport of Pollutants in Surface Waters

NASA Astrophysics Data System (ADS)

Okome, Gloria Eloho

There is the need to answer very crucial questions of "what happens to pollutants in surface waters?" This question must be answered to determine the factors controlling fate and transport of chemicals and their evolutionary state in surface waters. Monitoring and experimental methods are used in establishing the environmental states. These measurements are used with the known scientific principles to identify processes and to estimate the future environmental conditions. Conceptual and computational models are needed to analyze environmental processes by applying the knowledge gained from experimentation and theory. Usually, a computational framework includes the mathematics and the physics of the phenomenon, and the measured characteristics to model pollutants interactions and transport in surface water. However, under certain conditions, the complexity of the situation in the actual environment precludes the utilization of these techniques. Pollutants in several forms: Nitrogen (Nitrate, Nitrite, Kjeldhal Nitrogen and Ammonia), Phosphorus (orthophosphate and total phosphorus), bacteria (E-coli and Fecal coliform), Salts (Chloride and Sulfate) are chosen to follow for this research. The objective of this research is to model the fate and transport of these pollutants in non-ideal conditions of surface water measurements and to develop computational methods to forecast their fate and transport. In an environment of extreme drought such as in the Brazos River basin, where small streams flow intermittently, there is added complexity due to the absence of regularly sampled data. The usual modeling techniques are no longer applicable because of sparse measurements in space and time. Still, there is a need to estimate the conditions of the environment from the information that is present. Alternative methods for this estimation must be devised and applied to this situation, which is the task of this dissertation. This research devices a forecasting technique that is based upon sparse data. The method uses the equations of functions that fit the time series data for pollutants at each water quality monitoring stations to interpolate and extrapolate the data and to make estimates of present and future pollution levels. This method was applied to data obtained from the Leon River watershed (Indian creek) and Navasota River.

Estimation of Vegetation Aerodynamic Roughness of Natural Regions Using Frontal Area Density Determined from Satellite Imagery

NASA Technical Reports Server (NTRS)

Jasinski, Michael F.; Crago, Richard

1994-01-01

Parameterizations of the frontal area index and canopy area index of natural or randomly distributed plants are developed, and applied to the estimation of local aerodynamic roughness using satellite imagery. The formulas are expressed in terms of the subpixel fractional vegetation cover and one non-dimensional geometric parameter that characterizes the plant's shape. Geometrically similar plants and Poisson distributed plant centers are assumed. An appropriate averaging technique to extend satellite pixel-scale estimates to larger scales is provided. ne parameterization is applied to the estimation of aerodynamic roughness using satellite imagery for a 2.3 sq km coniferous portion of the Landes Forest near Lubbon, France, during the 1986 HAPEX-Mobilhy Experiment. The canopy area index is estimated first for each pixel in the scene based on previous estimates of fractional cover obtained using Landsat Thematic Mapper imagery. Next, the results are incorporated into Raupach's (1992, 1994) analytical formulas for momentum roughness and zero-plane displacement height. The estimates compare reasonably well to reference values determined from measurements taken during the experiment and to published literature values. The approach offers the potential for estimating regionally variable, vegetation aerodynamic roughness lengths over natural regions using satellite imagery when there exists only limited knowledge of the vegetated surface.

Guide to testing insecticides on coniferous forest defoliators

Treesearch

Carroll B Jr. Williams; David A. Sharpnack; Liz Maxwell; Patrick J. Shea; Mark D. McGregor

1985-01-01

This report provides a guide to techniques for designing field tests of candidate insecticides, and for carrying out pilot tests and control projects. It describes experimental designs for testing hypotheses, and for sampling trees to estimate insect population densities and percent reduction after treatments. Directions for applying insecticides by aircraft and for...

Statistical description of tectonic motions

NASA Technical Reports Server (NTRS)

Agnew, Duncan Carr

1993-01-01

This report summarizes investigations regarding tectonic motions. The topics discussed include statistics of crustal deformation, Earth rotation studies, using multitaper spectrum analysis techniques applied to both space-geodetic data and conventional astrometric estimates of the Earth's polar motion, and the development, design, and installation of high-stability geodetic monuments for use with the global positioning system.

Development of scan analysis techniques employing a small computer. Final report, February 1, 1963--July 31, 1976

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

Kuhl, D.E.

1976-08-05

During the thirteen year duration of this contract the goal has been to develop and apply computer based analysis of radionuclide scan data so as to make available improved diagnostic information based on a knowledge of localized quantitative estimates of radionuclide concentration. Results are summarized. (CH)

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

NASA Astrophysics Data System (ADS)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

The application of mean field theory to image motion estimation.

PubMed

Zhang, J; Hanauer, G G

1995-01-01

Previously, Markov random field (MRF) model-based techniques have been proposed for image motion estimation. Since motion estimation is usually an ill-posed problem, various constraints are needed to obtain a unique and stable solution. The main advantage of the MRF approach is its capacity to incorporate such constraints, for instance, motion continuity within an object and motion discontinuity at the boundaries between objects. In the MRF approach, motion estimation is often formulated as an optimization problem, and two frequently used optimization methods are simulated annealing (SA) and iterative-conditional mode (ICM). Although the SA is theoretically optimal in the sense of finding the global optimum, it usually takes many iterations to converge. The ICM, on the other hand, converges quickly, but its results are often unsatisfactory due to its "hard decision" nature. Previously, the authors have applied the mean field theory to image segmentation and image restoration problems. It provides results nearly as good as SA but with much faster convergence. The present paper shows how the mean field theory can be applied to MRF model-based motion estimation. This approach is demonstrated on both synthetic and real-world images, where it produced good motion estimates.

Comparison of two methods for estimating the number of undocumented Mexican adults in Los Angeles County.

PubMed

Heer, D M; Passel, J F

1987-01-01

This article compares 2 different methods for estimating the number of undocumented Mexican adults in Los Angeles County. The 1st method, the survey-based method, uses a combination of 1980 census data and the results of a survey conducted in Los Angeles County in 1980 and 1981. A sample was selected from babies born in Los Angeles County who had a mother or father of Mexican origin. The survey included questions about the legal status of the baby's parents and certain other relatives. The resulting estimates of undocumented Mexican immigrants are for males aged 18-44 and females aged 18-39. The 2nd method, the residual method, involves comparison of census figures for aliens counted with estimates of legally-resident aliens developed principally with data from the Immigration and Naturalization Service (INS). For this study, estimates by age, sex, and period of entry were produced for persons born in Mexico and living in Los Angeles County. The results of this research indicate that it is possible to measure undocumented immigration with different techniques, yet obtain results that are similar. Both techniques presented here are limited in that they represent estimates of undocumented aliens based on the 1980 census. The number of additional undocumented aliens not counted remains a subject of conjecture. The fact that the proportions undocumented shown in the survey (228,700) are quite similar to the residual estimates (317,800) suggests that the number of undocumented aliens not counted in the census may not be an extremely large fraction of the undocumented population. The survey-based estimates have some significant advantages over the residual estimates. The survey provides tabulations of the undocumented population by characteristics other than the limited demographic information provided by the residual technique. On the other hand, the survey-based estimates require that a survey be conducted and, if national or regional estimates are called for, they may require a number of surveys. The residual technique, however, also requires a data source other than the census. However, the INS discontinued the annual registration of aliens after 1981. Thus, estimates of undocumented aliens based on the residual technique will probably not be possible for subnational areas using the 1990 census unless the registration program is reinstituted. Perhaps the best information on the undocumented population in the 1990 census will come from an improved version of the survey-based technique described here applied in selected local areas.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

Measurement of metabolizable energy in poultry feeds by an in vitro system.

PubMed

Valdes, E V; Leeson, S

1992-09-01

A two-stage in vitro system (IVDE) for estimating AMEn in poultry feeds was investigated. For 71 diets ranging from 2.2 to 3.4 kcal/g, the average AMEn was 2.889 kcal/g and the mean IVDE value was 3.005 kcal/g. From the 71 diets, 30 (42.2%) showed differences between AMEn and IVDE of less than .100 kcal/g and represented diets across the AMEn range of values. The statistical analysis of the data showed a standard error of the estimate (SEE) of .152 kcal/g for the 71 diets assayed. No clear differences in accuracy of AMEn among the diets, as related to the composition and proportion of ingredients, were observed. Thus, the IVDE method gave different AMEn for diets of similar composition. The application of the IVDE system to selected ingredients showed that the AMEn of corn was underestimated by the method. However the AMEn of roasted, extruded soybeans and oats was estimated accurately by the IVDE method. Other ingredients were greatly overestimated by the in vitro technique (soybean meal, corn gluten meal, and barley). The results of applying the IVDE method for estimating AMEn showed the limitations of this technique with regard to the universality of its application. Although the method was successful in estimating AMEn values of diets and ingredients, for many samples the IVDE technique did not give acceptable results.

Coda Wave Interferometry Method Applied in Structural Monitoring to Assess Damage Evolution in Masonry and Concrete Structures

NASA Astrophysics Data System (ADS)

Masera, D.; Bocca, P.; Grazzini, A.

2011-07-01

In this experimental program the main goal is to monitor the damage evolution in masonry and concrete structures by Acoustic Emission (AE) signal analysis applying a well-know seismic method. For this reason the concept of the coda wave interferometry is applied to AE signal recorded during the tests. Acoustic Emission (AE) are very effective non-destructive techniques applied to identify micro and macro-defects and their temporal evolution in several materials. This technique permits to estimate the velocity of ultrasound waves propagation and the amount of energy released during fracture propagation to obtain information on the criticality of the ongoing process. By means of AE monitoring, an experimental analysis on a set of reinforced masonry walls under variable amplitude loading and strengthening reinforced concrete (RC) beams under monotonic static load has been carried out. In the reinforced masonry wall, cyclic fatigue stress has been applied to accelerate the static creep and to forecast the corresponding creep behaviour of masonry under static long-time loading. During the tests, the evaluation of fracture growth is monitored by coda wave interferometry which represents a novel approach in structural monitoring based on AE relative change velocity of coda signal. In general, the sensitivity of coda waves has been used to estimate velocity changes in fault zones, in volcanoes, in a mining environment, and in ultrasound experiments. This method uses multiple scattered waves, which travelled through the material along numerous paths, to infer tiny temporal changes in the wave velocity. The applied method has the potential to be used as a "damage-gauge" for monitoring velocity changes as a sign of damage evolution into masonry and concrete structures.

Monte Carlo uncertainty analysis of dose estimates in radiochromic film dosimetry with single-channel and multichannel algorithms.

PubMed

Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen; González-López, Antonio

2018-03-01

To provide a multi-stage model to calculate uncertainty in radiochromic film dosimetry with Monte-Carlo techniques. This new approach is applied to single-channel and multichannel algorithms. Two lots of Gafchromic EBT3 are exposed in two different Varian linacs. They are read with an EPSON V800 flatbed scanner. The Monte-Carlo techniques in uncertainty analysis provide a numerical representation of the probability density functions of the output magnitudes. From this numerical representation, traditional parameters of uncertainty analysis as the standard deviations and bias are calculated. Moreover, these numerical representations are used to investigate the shape of the probability density functions of the output magnitudes. Also, another calibration film is read in four EPSON scanners (two V800 and two 10000XL) and the uncertainty analysis is carried out with the four images. The dose estimates of single-channel and multichannel algorithms show a Gaussian behavior and low bias. The multichannel algorithms lead to less uncertainty in the final dose estimates when the EPSON V800 is employed as reading device. In the case of the EPSON 10000XL, the single-channel algorithms provide less uncertainty in the dose estimates for doses higher than four Gy. A multi-stage model has been presented. With the aid of this model and the use of the Monte-Carlo techniques, the uncertainty of dose estimates for single-channel and multichannel algorithms are estimated. The application of the model together with Monte-Carlo techniques leads to a complete characterization of the uncertainties in radiochromic film dosimetry. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Uncertainty Analysis and Parameter Estimation For Nearshore Hydrodynamic Models

NASA Astrophysics Data System (ADS)

Ardani, S.; Kaihatu, J. M.

2012-12-01

Numerical models represent deterministic approaches used for the relevant physical processes in the nearshore. Complexity of the physics of the model and uncertainty involved in the model inputs compel us to apply a stochastic approach to analyze the robustness of the model. The Bayesian inverse problem is one powerful way to estimate the important input model parameters (determined by apriori sensitivity analysis) and can be used for uncertainty analysis of the outputs. Bayesian techniques can be used to find the range of most probable parameters based on the probability of the observed data and the residual errors. In this study, the effect of input data involving lateral (Neumann) boundary conditions, bathymetry and off-shore wave conditions on nearshore numerical models are considered. Monte Carlo simulation is applied to a deterministic numerical model (the Delft3D modeling suite for coupled waves and flow) for the resulting uncertainty analysis of the outputs (wave height, flow velocity, mean sea level and etc.). Uncertainty analysis of outputs is performed by random sampling from the input probability distribution functions and running the model as required until convergence to the consistent results is achieved. The case study used in this analysis is the Duck94 experiment, which was conducted at the U.S. Army Field Research Facility at Duck, North Carolina, USA in the fall of 1994. The joint probability of model parameters relevant for the Duck94 experiments will be found using the Bayesian approach. We will further show that, by using Bayesian techniques to estimate the optimized model parameters as inputs and applying them for uncertainty analysis, we can obtain more consistent results than using the prior information for input data which means that the variation of the uncertain parameter will be decreased and the probability of the observed data will improve as well. Keywords: Monte Carlo Simulation, Delft3D, uncertainty analysis, Bayesian techniques, MCMC

Shear wave elastography using Wigner-Ville distribution: a simulated multilayer media study.

PubMed

Bidari, Pooya Sobhe; Alirezaie, Javad; Tavakkoli, Jahan

2016-08-01

Shear Wave Elastography (SWE) is a quantitative ultrasound-based imaging modality for distinguishing normal and abnormal tissue types by estimating the local viscoelastic properties of the tissue. These properties have been estimated in many studies by propagating ultrasound shear wave within the tissue and estimating parameters such as speed of wave. Vast majority of the proposed techniques are based on the cross-correlation of consecutive ultrasound images. In this study, we propose a new method of wave detection based on time-frequency (TF) analysis of the ultrasound signal. The proposed method is a modified version of the Wigner-Ville Distribution (WVD) technique. The TF components of the wave are detected in a propagating ultrasound wave within a simulated multilayer tissue and the local properties are estimated based on the detected waves. Image processing techniques such as Alternative Sequential Filters (ASF) and Circular Hough Transform (CHT) have been utilized to improve the estimation of TF components. This method has been applied to a simulated data from Wave3000™ software (CyberLogic Inc., New York, NY). This data simulates the propagation of an acoustic radiation force impulse within a two-layer tissue with slightly different viscoelastic properties between the layers. By analyzing the local TF components of the wave, we estimate the longitudinal and shear elasticities and viscosities of the media. This work shows that our proposed method is capable of distinguishing between different layers of a tissue.

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) sq km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, (1999-2001). We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

NASA Technical Reports Server (NTRS)

Negri, Andrew; Starr, David OC. (Technical Monitor)

2001-01-01

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform. rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) square km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, 1999-2001. We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

Temporal information partitioning: Characterizing synergy, uniqueness, and redundancy in interacting environmental variables

NASA Astrophysics Data System (ADS)

Goodwell, Allison E.; Kumar, Praveen

2017-07-01

Information theoretic measures can be used to identify nonlinear interactions between source and target variables through reductions in uncertainty. In information partitioning, multivariate mutual information is decomposed into synergistic, unique, and redundant components. Synergy is information shared only when sources influence a target together, uniqueness is information only provided by one source, and redundancy is overlapping shared information from multiple sources. While this partitioning has been applied to provide insights into complex dependencies, several proposed partitioning methods overestimate redundant information and omit a component of unique information because they do not account for source dependencies. Additionally, information partitioning has only been applied to time-series data in a limited context, using basic pdf estimation techniques or a Gaussian assumption. We develop a Rescaled Redundancy measure (Rs) to solve the source dependency issue, and present Gaussian, autoregressive, and chaotic test cases to demonstrate its advantages over existing techniques in the presence of noise, various source correlations, and different types of interactions. This study constitutes the first rigorous application of information partitioning to environmental time-series data, and addresses how noise, pdf estimation technique, or source dependencies can influence detected measures. We illustrate how our techniques can unravel the complex nature of forcing and feedback within an ecohydrologic system with an application to 1 min environmental signals of air temperature, relative humidity, and windspeed. The methods presented here are applicable to the study of a broad range of complex systems composed of interacting variables.

Effects of red blood cell aggregates dissociation on the estimation of ultrasound speckle image velocimetry.

PubMed

Yeom, Eunseop; Nam, Kweon-Ho; Paeng, Dong-Guk; Lee, Sang-Joon

2014-08-01

Ultrasound speckle image of blood is mainly attributed by red blood cells (RBCs) which tend to form RBC aggregates. RBC aggregates are separated into individual cells when the shear force is over a certain value. The dissociation of RBC aggregates has an influence on the performance of ultrasound speckle image velocimetry (SIV) technique in which a cross-correlation algorithm is applied to the speckle images to get the velocity field information. The present study aims to investigate the effect of the dissociation of RBC aggregates on the estimation quality of SIV technique. Ultrasound B-mode images were captured from the porcine blood circulating in a mock-up flow loop with varying flow rate. To verify the measurement performance of SIV technique, the centerline velocity measured by the SIV technique was compared with that measured by Doppler spectrograms. The dissociation of RBC aggregates was estimated by using decorrelation of speckle patterns in which the subsequent window was shifted as much as the speckle displacement to compensate decorrelation caused by in-plane loss of speckle patterns. The decorrelation of speckles is considerably increased according to shear rate. Its variations are different along the radial direction. Because the dissociation of RBC aggregates changes ultrasound speckles, the estimation quality of SIV technique is significantly correlated with the decorrelation of speckles. This degradation of measurement quality may be improved by increasing the data acquisition rate. This study would be useful for simultaneous measurement of hemodynamic and hemorheological information of blood flows using only speckle images. Copyright © 2014 Elsevier B.V. All rights reserved.

A fast and accurate frequency estimation algorithm for sinusoidal signal with harmonic components

NASA Astrophysics Data System (ADS)

Hu, Jinghua; Pan, Mengchun; Zeng, Zhidun; Hu, Jiafei; Chen, Dixiang; Tian, Wugang; Zhao, Jianqiang; Du, Qingfa

2016-10-01

Frequency estimation is a fundamental problem in many applications, such as traditional vibration measurement, power system supervision, and microelectromechanical system sensors control. In this paper, a fast and accurate frequency estimation algorithm is proposed to deal with low efficiency problem in traditional methods. The proposed algorithm consists of coarse and fine frequency estimation steps, and we demonstrate that it is more efficient than conventional searching methods to achieve coarse frequency estimation (location peak of FFT amplitude) by applying modified zero-crossing technique. Thus, the proposed estimation algorithm requires less hardware and software sources and can achieve even higher efficiency when the experimental data increase. Experimental results with modulated magnetic signal show that the root mean square error of frequency estimation is below 0.032 Hz with the proposed algorithm, which has lower computational complexity and better global performance than conventional frequency estimation methods.

Development of a Trip Energy Estimation Model Using Real-World Global Positioning System Driving Data: Preprint

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

Holden, Jacob; Wood, Eric W; Zhu, Lei

A data-driven technique for estimation of energy requirements for a proposed vehicle trip has been developed. Based on over 700,000 miles of driving data, the technique has been applied to generate a model that estimates trip energy requirements. The model uses a novel binning approach to categorize driving by road type, traffic conditions, and driving profile. The trip-level energy estimations can easily be aggregated to any higher-level transportation system network desired. The model has been tested and validated on the Austin, Texas, data set used to build this model. Ground-truth energy consumption for the data set was obtained from Futuremore » Automotive Systems Technology Simulator (FASTSim) vehicle simulation results. The energy estimation model has demonstrated 12.1 percent normalized total absolute error. The energy estimation from the model can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations, to reduce energy consumption. The model can also be used to determine more accurate energy consumption of regional or national transportation networks if trip origin and destinations are known. Additionally, this method allows the estimation tool to be tuned to a specific driver or vehicle type.« less

Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

NASA Astrophysics Data System (ADS)

Adushkin, V. V.

- A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ < 150 km) from these explosions. This methodology is then applied to data recorded from a large sample of the Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.

Linear Estimation of Particle Bulk Parameters from Multi-Wavelength Lidar Measurements

NASA Technical Reports Server (NTRS)

Veselovskii, Igor; Dubovik, Oleg; Kolgotin, A.; Korenskiy, M.; Whiteman, D. N.; Allakhverdiev, K.; Huseyinoglu, F.

2012-01-01

An algorithm for linear estimation of aerosol bulk properties such as particle volume, effective radius and complex refractive index from multiwavelength lidar measurements is presented. The approach uses the fact that the total aerosol concentration can well be approximated as a linear combination of aerosol characteristics measured by multiwavelength lidar. Therefore, the aerosol concentration can be estimated from lidar measurements without the need to derive the size distribution, which entails more sophisticated procedures. The definition of the coefficients required for the linear estimates is based on an expansion of the particle size distribution in terms of the measurement kernels. Once the coefficients are established, the approach permits fast retrieval of aerosol bulk properties when compared with the full regularization technique. In addition, the straightforward estimation of bulk properties stabilizes the inversion making it more resistant to noise in the optical data. Numerical tests demonstrate that for data sets containing three aerosol backscattering and two extinction coefficients (so called 3 + 2 ) the uncertainties in the retrieval of particle volume and surface area are below 45% when input data random uncertainties are below 20 %. Moreover, using linear estimates allows reliable retrievals even when the number of input data is reduced. To evaluate the approach, the results obtained using this technique are compared with those based on the previously developed full inversion scheme that relies on the regularization procedure. Both techniques were applied to the data measured by multiwavelength lidar at NASA/GSFC. The results obtained with both methods using the same observations are in good agreement. At the same time, the high speed of the retrieval using linear estimates makes the method preferable for generating aerosol information from extended lidar observations. To demonstrate the efficiency of the method, an extended time series of observations acquired in Turkey in May 2010 was processed using the linear estimates technique permitting, for what we believe to be the first time, temporal-height distributions of particle parameters.

Tracking with time-delayed data in multisensor systems

NASA Astrophysics Data System (ADS)

Hilton, Richard D.; Martin, David A.; Blair, William D.

1993-08-01

When techniques for target tracking are expanded to make use of multiple sensors in a multiplatform system, the possibility of time delayed data becomes a reality. When a discrete-time Kalman filter is applied and some of the data entering the filter are delayed, proper processing of these late data is a necessity for obtaining an optimal estimate of a target's state. If this problem is not given special care, the quality of the state estimates can be degraded relative to that quality provided by a single sensor. A negative-time update technique is developed using the criteria of minimum mean-square error (MMSE) under the constraint that only the results of the most recent update are saved. The performance of the MMSE technique is compared to that of the ad hoc approach employed in the Cooperative Engagement Capabilities (CEC) system for processing data from multiple platforms. It was discovered that the MMSE technique is a stable solution to the negative-time update problem, while the CEC technique was found to be less than desirable when used with filters designed for tracking highly maneuvering targets at relatively low data rates. The MMSE negative-time update technique was found to be a superior alternative to the existing CEC negative-time update technique.

Abdominal fat volume estimation by stereology on CT: a comparison with manual planimetry.

PubMed

Manios, G E; Mazonakis, M; Voulgaris, C; Karantanas, A; Damilakis, J

2016-03-01

To deploy and evaluate a stereological point-counting technique on abdominal CT for the estimation of visceral (VAF) and subcutaneous abdominal fat (SAF) volumes. Stereological volume estimations based on point counting and systematic sampling were performed on images from 14 consecutive patients who had undergone abdominal CT. For the optimization of the method, five sampling intensities in combination with 100 and 200 points were tested. The optimum stereological measurements were compared with VAF and SAF volumes derived by the standard technique of manual planimetry on the same scans. Optimization analysis showed that the selection of 200 points along with the sampling intensity 1/8 provided efficient volume estimations in less than 4 min for VAF and SAF together. The optimized stereology showed strong correlation with planimetry (VAF: r = 0.98; SAF: r = 0.98). No statistical differences were found between the two methods (VAF: P = 0.81; SAF: P = 0.83). The 95% limits of agreement were also acceptable (VAF: -16.5%, 16.1%; SAF: -10.8%, 10.7%) and the repeatability of stereology was good (VAF: CV = 4.5%, SAF: CV = 3.2%). Stereology may be successfully applied to CT images for the efficient estimation of abdominal fat volume and may constitute a good alternative to the conventional planimetric technique. Abdominal obesity is associated with increased risk of disease and mortality. Stereology may quantify visceral and subcutaneous abdominal fat accurately and consistently. The application of stereology to estimating abdominal volume fat reduces processing time. Stereology is an efficient alternative method for estimating abdominal fat volume.

Terrain modeling for microwave landing system

NASA Technical Reports Server (NTRS)

Poulose, M. M.

1991-01-01

A powerful analytical approach for evaluating the terrain effects on a microwave landing system (MLS) is presented. The approach combines a multiplate model with a powerful and exhaustive ray tracing technique and an accurate formulation for estimating the electromagnetic fields due to the antenna array in the presence of terrain. Both uniform theory of diffraction (UTD) and impedance UTD techniques have been employed to evaluate these fields. Innovative techniques are introduced at each stage to make the model versatile to handle most general terrain contours and also to reduce the computational requirement to a minimum. The model is applied to several terrain geometries, and the results are discussed.

A Bayesian framework for infrasound location

NASA Astrophysics Data System (ADS)

Modrak, Ryan T.; Arrowsmith, Stephen J.; Anderson, Dale N.

2010-04-01

We develop a framework for location of infrasound events using backazimuth and infrasonic arrival times from multiple arrays. Bayesian infrasonic source location (BISL) developed here estimates event location and associated credibility regions. BISL accounts for unknown source-to-array path or phase by formulating infrasonic group velocity as random. Differences between observed and predicted source-to-array traveltimes are partitioned into two additive Gaussian sources, measurement error and model error, the second of which accounts for the unknown influence of wind and temperature on path. By applying the technique to both synthetic tests and ground-truth events, we highlight the complementary nature of back azimuths and arrival times for estimating well-constrained event locations. BISL is an extension to methods developed earlier by Arrowsmith et al. that provided simple bounds on location using a grid-search technique.

Land use/land cover mapping (1:25000) of Taiwan, Republic of China by automated multispectral interpretation of LANDSAT imagery

NASA Technical Reports Server (NTRS)

Sung, Q. C.; Miller, L. D.

1977-01-01

Three methods were tested for collection of the training sets needed to establish the spectral signatures of the land uses/land covers sought due to the difficulties of retrospective collection of representative ground control data. Computer preprocessing techniques applied to the digital images to improve the final classification results were geometric corrections, spectral band or image ratioing and statistical cleaning of the representative training sets. A minimal level of statistical verification was made based upon the comparisons between the airphoto estimates and the classification results. The verifications provided a further support to the selection of MSS band 5 and 7. It also indicated that the maximum likelihood ratioing technique can achieve more agreeable classification results with the airphoto estimates than the stepwise discriminant analysis.

NOSS/ALDCS analysis and system requirements definition. [national oceanic satellite system data collection

NASA Technical Reports Server (NTRS)

Reed, D. L.; Wallace, R. G.

1981-01-01

The results of system analyses and implementation studies of an advanced location and data collection system (ALDCS) , proposed for inclusion on the National Oceanic Satellite System (NOSS) spacecraft are reported. The system applies Doppler processing and radiofrequency interferometer position location technqiues both alone and in combination. Aspects analyzed include: the constraints imposed by random access to the system by platforms, the RF link parameters, geometric concepts of position and velocity estimation by the two techniques considered, and the effects of electrical measurement errors, spacecraft attitude errors, and geometric parameters on estimation accuracy. Hardware techniques and trade-offs for interferometric phase measurement, ambiguity resolution and calibration are considered. A combined Doppler-interferometer ALDCS intended to fulfill the NOSS data validation and oceanic research support mission is also described.

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis.

PubMed

Quintela-del-Río, Alejandro; Francisco-Fernández, Mario

2011-02-01

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis. Copyright © 2010 Elsevier Ltd. All rights reserved.

A comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement.

PubMed

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation.

Estimating impacts of plantation forestry on plant biodiversity in southern Chile-a spatially explicit modelling approach.

PubMed

Braun, Andreas Christian; Koch, Barbara

2016-10-01

Monitoring the impacts of land-use practices is of particular importance with regard to biodiversity hotspots in developing countries. Here, conserving the high level of unique biodiversity is challenged by limited possibilities for data collection on site. Especially for such scenarios, assisting biodiversity assessments by remote sensing has proven useful. Remote sensing techniques can be applied to interpolate between biodiversity assessments taken in situ. Through this approach, estimates of biodiversity for entire landscapes can be produced, relating land-use intensity to biodiversity conditions. Such maps are a valuable basis for developing biodiversity conservation plans. Several approaches have been published so far to interpolate local biodiversity assessments in remote sensing data. In the following, a new approach is proposed. Instead of inferring biodiversity using environmental variables or the variability of spectral values, a hypothesis-based approach is applied. Empirical knowledge about biodiversity in relation to land-use is formalized and applied as ascription rules for image data. The method is exemplified for a large study site (over 67,000 km(2)) in central Chile, where forest industry heavily impacts plant diversity. The proposed approach yields a coefficient of correlation of 0.73 and produces a convincing estimate of regional biodiversity. The framework is broad enough to be applied to other study sites.

Biogenic nonmethane hydrocarbon emissions estimated from tethered balloon observations

NASA Technical Reports Server (NTRS)

Davis, K. J.; Lenschow, D. H.; Zimmerman, P. R.

1994-01-01

A new technique for estimating surface fluxes of trace gases, the mixed-layer gradient technique, is used to calculate isoprene and terpene emissions from forests. The technique is applied to tethered balloon measurements made over the Amazon forest and a pine-oak forest in Alabama at altitudes up to 300 m. The observations were made during the dry season Amazon Boundary Layer Experiment (ABLE 2A) and the Rural Oxidants in the Southern Environment 1990 experiment (ROSE I). Results from large eddy simulations of scalar transport in the clear convective boundary layer are used to infer fluxes from the balloon profiles. Profiles from the Amazon give a mean daytime emission of 3630 +/- 1400 micrograms isoprene sq m/h, where the uncertainty represents the standard deviation of the mean of eight flux estimates. Twenty profiles from Alabama give emissions of 4470 +/- 3300 micrograms isoprene sq m/h, 1740 +/- 1060 micrograms alpha-pinene sq m/h, and 790 +/- 560 micrograms beta-pinene sq m/h, respectively. These results are in agreement with emissions derived from chemical budgets. The emissions may be overestimated because of uncertainty about how to incorporate the effects of the canopy on the mixed-layer gradients. The large variability in these emission estimates is probably due to the relatively short sampling times of the balloon profiles, though spatially heterogeneous emissions may also play a role. Fluxes derived using this technique are representative of an upwind footprint of several kilometers and are independent of hydrocarbon oxidation rate and mean advection.

Metrics in method engineering

NASA Astrophysics Data System (ADS)

Brinkkemper, S.; Rossi, M.

1994-12-01

As customizable computer aided software engineering (CASE) tools, or CASE shells, have been introduced in academia and industry, there has been a growing interest into the systematic construction of methods and their support environments, i.e. method engineering. To aid the method developers and method selectors in their tasks, we propose two sets of metrics, which measure the complexity of diagrammatic specification techniques on the one hand, and of complete systems development methods on the other hand. Proposed metrics provide a relatively fast and simple way to analyze the technique (or method) properties, and when accompanied with other selection criteria, can be used for estimating the cost of learning the technique and the relative complexity of a technique compared to others. To demonstrate the applicability of the proposed metrics, we have applied them to 34 techniques and 15 methods.

Experiences with Markov Chain Monte Carlo Convergence Assessment in Two Psychometric Examples

ERIC Educational Resources Information Center

Sinharay, Sandip

2004-01-01

There is an increasing use of Markov chain Monte Carlo (MCMC) algorithms for fitting statistical models in psychometrics, especially in situations where the traditional estimation techniques are very difficult to apply. One of the disadvantages of using an MCMC algorithm is that it is not straightforward to determine the convergence of the…

The Use of Invariance and Bootstrap Procedures as a Method to Establish the Reliability of Research Results.

ERIC Educational Resources Information Center

Sandler, Andrew B.

Statistical significance is misused in educational and psychological research when it is applied as a method to establish the reliability of research results. Other techniques have been developed which can be correctly utilized to establish the generalizability of findings. Methods that do provide such estimates are known as invariance or…

Implementing Restricted Maximum Likelihood Estimation in Structural Equation Models

ERIC Educational Resources Information Center

Cheung, Mike W.-L.

2013-01-01

Structural equation modeling (SEM) is now a generic modeling framework for many multivariate techniques applied in the social and behavioral sciences. Many statistical models can be considered either as special cases of SEM or as part of the latent variable modeling framework. One popular extension is the use of SEM to conduct linear mixed-effects…

A Model for Minimizing Numeric Function Generator Complexity and Delay

DTIC Science & Technology

2007-12-01

allow computation of difficult mathematical functions in less time and with less hardware than commonly employed methods. They compute piecewise...Programmable Gate Arrays (FPGAs). The algorithms and estimation techniques apply to various NFG architectures and mathematical functions. This...thesis compares hardware utilization and propagation delay for various NFG architectures, mathematical functions, word widths, and segmentation methods

Analytical estimation of ultrasound properties, thermal diffusivity, and perfusion using magnetic resonance-guided focused ultrasound temperature data

PubMed Central

Dillon, C R; Borasi, G; Payne, A

2016-01-01

For thermal modeling to play a significant role in treatment planning, monitoring, and control of magnetic resonance-guided focused ultrasound (MRgFUS) thermal therapies, accurate knowledge of ultrasound and thermal properties is essential. This study develops a new analytical solution for the temperature change observed in MRgFUS which can be used with experimental MR temperature data to provide estimates of the ultrasound initial heating rate, Gaussian beam variance, tissue thermal diffusivity, and Pennes perfusion parameter. Simulations demonstrate that this technique provides accurate and robust property estimates that are independent of the beam size, thermal diffusivity, and perfusion levels in the presence of realistic MR noise. The technique is also demonstrated in vivo using MRgFUS heating data in rabbit back muscle. Errors in property estimates are kept less than 5% by applying a third order Taylor series approximation of the perfusion term and ensuring the ratio of the fitting time (the duration of experimental data utilized for optimization) to the perfusion time constant remains less than one. PMID:26741344

Application of a Constant Gain Extended Kalman Filter for In-Flight Estimation of Aircraft Engine Performance Parameters

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.; Litt, Jonathan S.

2005-01-01

An approach based on the Constant Gain Extended Kalman Filter (CGEKF) technique is investigated for the in-flight estimation of non-measurable performance parameters of aircraft engines. Performance parameters, such as thrust and stall margins, provide crucial information for operating an aircraft engine in a safe and efficient manner, but they cannot be directly measured during flight. A technique to accurately estimate these parameters is, therefore, essential for further enhancement of engine operation. In this paper, a CGEKF is developed by combining an on-board engine model and a single Kalman gain matrix. In order to make the on-board engine model adaptive to the real engine s performance variations due to degradation or anomalies, the CGEKF is designed with the ability to adjust its performance through the adjustment of artificial parameters called tuning parameters. With this design approach, the CGEKF can maintain accurate estimation performance when it is applied to aircraft engines at offnominal conditions. The performance of the CGEKF is evaluated in a simulation environment using numerous component degradation and fault scenarios at multiple operating conditions.

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

NASA Astrophysics Data System (ADS)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

Estimation of 3-D conduction velocity vector fields from cardiac mapping data.

PubMed

Barnette, A R; Bayly, P V; Zhang, S; Walcott, G P; Ideker, R E; Smith, W M

2000-08-01

A method to estimate three-dimensional (3-D) conduction velocity vector fields in cardiac tissue is presented. The speed and direction of propagation are found from polynomial "surfaces" fitted to space-time (x, y, z, t) coordinates of cardiac activity. The technique is applied to sinus rhythm and paced rhythm mapped with plunge needles at 396-466 sites in the canine myocardium. The method was validated on simulated 3-D plane and spherical waves. For simulated data, conduction velocities were estimated with an accuracy of 1%-2%. In experimental data, estimates of conduction speeds during paced rhythm were slower than those found during normal sinus rhythm. Vector directions were also found to differ between different types of beats. The technique was able to distinguish between premature ventricular contractions and sinus beats and between sinus and paced beats. The proposed approach to computing velocity vector fields provides an automated, physiological, and quantitative description of local electrical activity in 3-D tissue. This method may provide insight into abnormal conduction associated with fatal ventricular arrhythmias.

Estimating and Comparing Dam Deformation Using Classical and GNSS Techniques

PubMed Central

Barzaghi, Riccardo; De Gaetani, Carlo Iapige

2018-01-01

Global Navigation Satellite Systems (GNSS) receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure displacements. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high-precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS-estimated displacements on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D’Arborea (Cantoniera) dam, which is in Sardinia. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so as to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. These encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations. PMID:29498650

Statistical robustness of machine-learning estimates for characterizing a groundwater-surface water system, Southland, New Zealand

NASA Astrophysics Data System (ADS)

Friedel, M. J.; Daughney, C.

2016-12-01

The development of a successful surface-groundwater management strategy depends on the quality of data provided for analysis. This study evaluates the statistical robustness when using a modified self-organizing map (MSOM) technique to estimate missing values for three hypersurface models: synoptic groundwater-surface water hydrochemistry, time-series of groundwater-surface water hydrochemistry, and mixed-survey (combination of groundwater-surface water hydrochemistry and lithologies) hydrostratigraphic unit data. These models of increasing complexity are developed and validated based on observations from the Southland region of New Zealand. In each case, the estimation method is sufficiently robust to cope with groundwater-surface water hydrochemistry vagaries due to sample size and extreme data insufficiency, even when >80% of the data are missing. The estimation of surface water hydrochemistry time series values enabled the evaluation of seasonal variation, and the imputation of lithologies facilitated the evaluation of hydrostratigraphic controls on groundwater-surface water interaction. The robust statistical results for groundwater-surface water models of increasing data complexity provide justification to apply the MSOM technique in other regions of New Zealand and abroad.

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

NASA Technical Reports Server (NTRS)

Molusis, J. A.

1982-01-01

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Development of real-time PCR technique for the estimation of population density of Pythium intermedium in forest soils.

PubMed

Li, Mingzhu; Senda, Masako; Komatsu, Tsutomu; Suga, Haruhisa; Kageyama, Koji

2010-10-20

Pythium intermedium is known to play an important role in the carbon cycling of cool-temperate forest soils. In this study, a fast, precise and effective real-time PCR technique for estimating the population densities of P. intermedium from soils was developed using species-specific primers. Specificity was confirmed both with conventional PCR and real-time PCR. The detection limit (sensitivity) was determined and amplification standard curves were generated using SYBR Green II fluorescent dye. A rapid and accurate assay for quantification of P. intermedium in Takayama forest soils of Japan was developed using a combination of a new DNA extraction method and PCR primers were developed for real-time PCR. And the distribution of P. intermedium in forest soil was investigated with both soil plating method and the developed real-time PCR technique. This new technique will be a useful tool and can be applied to practical use for studying the role of Pythium species in forest and agricultural ecosystems. Copyright © 2009 Elsevier GmbH. All rights reserved.

Uniform stable observer for the disturbance estimation in two renewable energy systems.

PubMed

Rubio, José de Jesús; Ochoa, Genaro; Balcazar, Ricardo; Pacheco, Jaime

2015-09-01

In this study, an observer for the states and disturbance estimation in two renewable energy systems is introduced. The restrictions of the gains in the proposed observer are found to guarantee its stability and the convergence of its error; furthermore, these results are utilized to obtain a good estimation. The introduced technique is applied for the states and disturbance estimation in a wind turbine and an electric vehicle. The wind turbine has a rotatory tower to catch the incoming air to be transformed in electricity and the electric vehicle has generators connected with its wheels to catch the vehicle movement to be transformed in electricity. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Sensorless position estimator applied to nonlinear IPMC model

NASA Astrophysics Data System (ADS)

Bernat, Jakub; Kolota, Jakub

2016-11-01

This paper addresses the issue of estimating position for an ionic polymer metal composite (IPMC) known as electro active polymer (EAP). The key step is the construction of a sensorless mode considering only current feedback. This work takes into account nonlinearities caused by electrochemical effects in the material. Owing to the recent observer design technique, the authors obtained both Lyapunov function based estimation law as well as sliding mode observer. To accomplish the observer design, the IPMC model was identified through a series of experiments. The research comprises time domain measurements. The identification process was completed by means of geometric scaling of three test samples. In the proposed design, the estimated position accurately tracks the polymer position, which is illustrated by the experiments.

Modified Hitschfeld-Bordan Equations for Attenuation-Corrected Radar Rain Reflectivity: Application to Nonuniform Beamfilling at Off-Nadir Incidence

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Liao, Liang

2013-01-01

As shown by Takahashi et al., multiple path attenuation estimates over the field of view of an airborne or spaceborne weather radar are feasible for off-nadir incidence angles. This follows from the fact that the surface reference technique, which provides path attenuation estimates, can be applied to each radar range gate that intersects the surface. This study builds on this result by showing that three of the modified Hitschfeld-Bordan estimates for the attenuation-corrected radar reflectivity factor can be generalized to the case where multiple path attenuation estimates are available, thereby providing a correction to the effects of nonuniform beamfilling. A simple simulation is presented showing some strengths and weaknesses of the approach.

High-resolution correlation

NASA Astrophysics Data System (ADS)

Nelson, D. J.

2007-09-01

In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.

An adaptive finite element method for the inequality-constrained Reynolds equation

NASA Astrophysics Data System (ADS)

Gustafsson, Tom; Rajagopal, Kumbakonam R.; Stenberg, Rolf; Videman, Juha

2018-07-01

We present a stabilized finite element method for the numerical solution of cavitation in lubrication, modeled as an inequality-constrained Reynolds equation. The cavitation model is written as a variable coefficient saddle-point problem and approximated by a residual-based stabilized method. Based on our recent results on the classical obstacle problem, we present optimal a priori estimates and derive novel a posteriori error estimators. The method is implemented as a Nitsche-type finite element technique and shown in numerical computations to be superior to the usually applied penalty methods.

Forensic age estimation based on development of third molars: a staging technique for magnetic resonance imaging.

PubMed

De Tobel, J; Phlypo, I; Fieuws, S; Politis, C; Verstraete, K L; Thevissen, P W

2017-12-01

The development of third molars can be evaluated with medical imaging to estimate age in subadults. The appearance of third molars on magnetic resonance imaging (MRI) differs greatly from that on radiographs. Therefore a specific staging technique is necessary to classify third molar development on MRI and to apply it for age estimation. To develop a specific staging technique to register third molar development on MRI and to evaluate its performance for age estimation in subadults. Using 3T MRI in three planes, all third molars were evaluated in 309 healthy Caucasian participants from 14 to 26 years old. According to the appearance of the developing third molars on MRI, descriptive criteria and schematic representations were established to define a specific staging technique. Two observers, with different levels of experience, staged all third molars independently with the developed technique. Intra- and inter-observer agreement were calculated. The data were imported in a Bayesian model for age estimation as described by Fieuws et al. (2016). This approach adequately handles correlation between age indicators and missing age indicators. It was used to calculate a point estimate and a prediction interval of the estimated age. Observed age minus predicted age was calculated, reflecting the error of the estimate. One-hundred and sixty-six third molars were agenetic. Five percent (51/1096) of upper third molars and 7% (70/1044) of lower third molars were not assessable. Kappa for inter-observer agreement ranged from 0.76 to 0.80. For intra-observer agreement kappa ranged from 0.80 to 0.89. However, two stage differences between observers or between staging sessions occurred in up to 2.2% (20/899) of assessments, probably due to a learning effect. Using the Bayesian model for age estimation, a mean absolute error of 2.0 years in females and 1.7 years in males was obtained. Root mean squared error equalled 2.38 years and 2.06 years respectively. The performance to discern minors from adults was better for males than for females, with specificities of 96% and 73% respectively. Age estimations based on the proposed staging method for third molars on MRI showed comparable reproducibility and performance as the established methods based on radiographs.

a Hybrid Method in Vegetation Height Estimation Using Polinsar Images of Campaign Biosar

NASA Astrophysics Data System (ADS)

Dehnavi, S.; Maghsoudi, Y.

2015-12-01

Recently, there have been plenty of researches on the retrieval of forest height by PolInSAR data. This paper aims at the evaluation of a hybrid method in vegetation height estimation based on L-band multi-polarized air-borne SAR images. The SAR data used in this paper were collected by the airborne E-SAR system. The objective of this research is firstly to describe each interferometry cross correlation as a sum of contributions corresponding to single bounce, double bounce and volume scattering processes. Then, an ESPIRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm is implemented, to determine the interferometric phase of each local scatterer (ground and canopy). Secondly, the canopy height is estimated by phase differencing method, according to the RVOG (Random Volume Over Ground) concept. The applied model-based decomposition method is unrivaled, as it is not limited to specific type of vegetation, unlike the previous decomposition techniques. In fact, the usage of generalized probability density function based on the nth power of a cosine-squared function, which is characterized by two parameters, makes this method useful for different vegetation types. Experimental results show the efficiency of the approach for vegetation height estimation in the test site.

Dominant root locus in state estimator design for material flow processes: A case study of hot strip rolling.

PubMed

Fišer, Jaromír; Zítek, Pavel; Skopec, Pavel; Knobloch, Jan; Vyhlídal, Tomáš

2017-05-01

The purpose of the paper is to achieve a constrained estimation of process state variables using the anisochronic state observer tuned by the dominant root locus technique. The anisochronic state observer is based on the state-space time delay model of the process. Moreover the process model is identified not only as delayed but also as non-linear. This model is developed to describe a material flow process. The root locus technique combined with the magnitude optimum method is utilized to investigate the estimation process. Resulting dominant roots location serves as a measure of estimation process performance. The higher the dominant (natural) frequency in the leftmost position of the complex plane the more enhanced performance with good robustness is achieved. Also the model based observer control methodology for material flow processes is provided by means of the separation principle. For demonstration purposes, the computer-based anisochronic state observer is applied to the strip temperatures estimation in the hot strip finishing mill composed of seven stands. This application was the original motivation to the presented research. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

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

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

New method for propagating the square root covariance matrix in triangular form. [using Kalman-Bucy filter

NASA Technical Reports Server (NTRS)

Choe, C. Y.; Tapley, B. D.

1975-01-01

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

Proceedings of the Meeting of the Coordinating Group on Modern Control Theory (4th) Held at Rochester, Michigan on 27-28 October 1982. Part 1

DTIC Science & Technology

1982-10-01

and time-to-go (T60) are provided from the Estimation Algorithm. The gimbal angle commands used in the first two phases are applied to the gimbal...lighting techniques are also used to simplify image understanding or to extract additional information about position, range, or shape of objects in the...motion or firing dis- turbances. Since useful muzzle position and rate information is difficult to obtain, conventional feedback techniques 447 cannot

Multiclass Bayes error estimation by a feature space sampling technique

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Computational efficiency and Amdahl’s law for the adaptive resolution simulation technique

DOE PAGES

Junghans, Christoph; Agarwal, Animesh; Delle Site, Luigi

2017-06-01

Here, we discuss the computational performance of the adaptive resolution technique in molecular simulation when it is compared with equivalent full coarse-grained and full atomistic simulations. We show that an estimate of its efficiency, within 10%–15% accuracy, is given by the Amdahl’s Law adapted to the specific quantities involved in the problem. The derivation of the predictive formula is general enough that it may be applied to the general case of molecular dynamics approaches where a reduction of degrees of freedom in a multi scale fashion occurs.

Explosion localization via infrasound.

PubMed

Szuberla, Curt A L; Olson, John V; Arnoult, Kenneth M

2009-11-01

Two acoustic source localization techniques were applied to infrasonic data and their relative performance was assessed. The standard approach for low-frequency localization uses an ensemble of small arrays to separately estimate far-field source bearings, resulting in a solution from the various back azimuths. This method was compared to one developed by the authors that treats the smaller subarrays as a single, meta-array. In numerical simulation and a field experiment, the latter technique was found to provide improved localization precision everywhere in the vicinity of a 3-km-aperture meta-array, often by an order of magnitude.

[THE MODES OF EVALUATION OF TYPE OF DEHYDRATION IN CHILDREN HOSPITALIZED BECAUSE OF ACUTE INTESTINAL INFECTION].

PubMed

Krieger, E A; Samodova, O V; Gulakova, N N; Aruiev, A B; Krylova, L A; Titova, L V

2015-11-01

Every year about 800,000 cases of intestinal infections end in lethal outcome due to dehydration. The different types of dehydration acquire differential approach to correction. Everywhere there is no application of routine detection of osmolarity of blood plasma under exicosis in children in view of absence of possibility of instrumental measurement. The search of techniques is needed to make it possible to indirectly detect types of dehydration in children hospitalized because of acute intestinal infection with purpose to apply rationale therapy of water-electrolyte disorders. The sampling of 32 patients with intestinal infections accompanied with signs of exicosis degree I-III was examined. The detection of osmolarity of blood was implemented by instrumental technique using gas analyzer ABL 800 Flex (Radiometer; Denmark) and five estimate techniques according to results of biochemical analysis of blood. The differences in precision of measurement of osmolarity of blood plasma by instrumental and estimate techniques were compared using Bland-Altman graphic technique. It is established that formula: 2x[Na+kp] + [glucosekp] (mmol/l) is the most recise. Its application provided results comparable with values detected by instrumental mode.

A methodology for airplane parameter estimation and confidence interval determination in nonlinear estimation problems. Ph.D. Thesis - George Washington Univ., Apr. 1985

NASA Technical Reports Server (NTRS)

Murphy, P. C.

1986-01-01

An algorithm for maximum likelihood (ML) estimation is developed with an efficient method for approximating the sensitivities. The ML algorithm relies on a new optimization method referred to as a modified Newton-Raphson with estimated sensitivities (MNRES). MNRES determines sensitivities by using slope information from local surface approximations of each output variable in parameter space. With the fitted surface, sensitivity information can be updated at each iteration with less computational effort than that required by either a finite-difference method or integration of the analytically determined sensitivity equations. MNRES eliminates the need to derive sensitivity equations for each new model, and thus provides flexibility to use model equations in any convenient format. A random search technique for determining the confidence limits of ML parameter estimates is applied to nonlinear estimation problems for airplanes. The confidence intervals obtained by the search are compared with Cramer-Rao (CR) bounds at the same confidence level. The degree of nonlinearity in the estimation problem is an important factor in the relationship between CR bounds and the error bounds determined by the search technique. Beale's measure of nonlinearity is developed in this study for airplane identification problems; it is used to empirically correct confidence levels and to predict the degree of agreement between CR bounds and search estimates.

Ship heading and velocity analysis by wake detection in SAR images

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Rufino, Giancarlo

2016-11-01

With the aim of ship-route estimation, a wake detection method is developed and applied to COSMO/SkyMed and TerraSAR-X Stripmap SAR images over the Gulf of Naples, Italy. In order to mitigate the intrinsic limitations of the threshold logic, the algorithm identifies the wake features according to the hydrodynamic theory. A post-detection validation phase is performed to classify the features as real wake structures by means of merit indexes defined in the intensity domain. After wake reconstruction, ship heading is evaluated on the basis of turbulent wake direction and ship velocity is estimated by both techniques of azimuth shift and Kelvin pattern wavelength. The method is tested over 34 ship wakes identified by visual inspection in both HH and VV images at different incidence angles. For all wakes, no missed detections are reported and at least the turbulent and one narrow-V wakes are correctly identified, with ship heading successfully estimated. Also, the azimuth shift method is applied to estimate velocity for the 10 ships having route with sufficient angular separation from the satellite ground track. In one case ship velocity is successfully estimated with both methods, showing agreement within 14%.

Optimum data weighting and error calibration for estimation of gravitational parameters

NASA Technical Reports Server (NTRS)

Lerch, F. J.

1989-01-01

A new technique was developed for the weighting of data from satellite tracking systems in order to obtain an optimum least squares solution and an error calibration for the solution parameters. Data sets from optical, electronic, and laser systems on 17 satellites in GEM-T1 (Goddard Earth Model, 36x36 spherical harmonic field) were employed toward application of this technique for gravity field parameters. Also, GEM-T2 (31 satellites) was recently computed as a direct application of the method and is summarized here. The method employs subset solutions of the data associated with the complete solution and uses an algorithm to adjust the data weights by requiring the differences of parameters between solutions to agree with their error estimates. With the adjusted weights the process provides for an automatic calibration of the error estimates for the solution parameters. The data weights derived are generally much smaller than corresponding weights obtained from nominal values of observation accuracy or residuals. Independent tests show significant improvement for solutions with optimal weighting as compared to the nominal weighting. The technique is general and may be applied to orbit parameters, station coordinates, or other parameters than the gravity model.

Modification of smoothing in 4253H[T

NASA Astrophysics Data System (ADS)

Azmi, Nurul Nisa'Khairol; Adam, Mohd Bakri; Shitan, Mahendran; Ali, Norhaslinda Mohd

2017-05-01

Some modified non-linear smoothers particularly 4253H[T] are explained in this paper. The modifications are focused on estimating the middle point of running median for even span by applying the following types of means; geometric, harmonic, quadratic and contraharmonic. The performance of the techniques is assessed by applying it to daily price index of a bank in Malaysia that issues sukuk for funding in Islamic banking and financial business. The results show that 4253H[T] with geometric mean modification is better than others in preserving variation and curve fitting.

Waveform inversion of acoustic waves for explosion yield estimation

DOE PAGES

Kim, K.; Rodgers, A. J.

2016-07-08

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Parameter estimation in IMEX-trigonometrically fitted methods for the numerical solution of reaction-diffusion problems

NASA Astrophysics Data System (ADS)

D'Ambrosio, Raffaele; Moccaldi, Martina; Paternoster, Beatrice

2018-05-01

In this paper, an adapted numerical scheme for reaction-diffusion problems generating periodic wavefronts is introduced. Adapted numerical methods for such evolutionary problems are specially tuned to follow prescribed qualitative behaviors of the solutions, making the numerical scheme more accurate and efficient as compared with traditional schemes already known in the literature. Adaptation through the so-called exponential fitting technique leads to methods whose coefficients depend on unknown parameters related to the dynamics and aimed to be numerically computed. Here we propose a strategy for a cheap and accurate estimation of such parameters, which consists essentially in minimizing the leading term of the local truncation error whose expression is provided in a rigorous accuracy analysis. In particular, the presented estimation technique has been applied to a numerical scheme based on combining an adapted finite difference discretization in space with an implicit-explicit time discretization. Numerical experiments confirming the effectiveness of the approach are also provided.

Waveform inversion of acoustic waves for explosion yield estimation

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

Kim, K.; Rodgers, A. J.

We present a new waveform inversion technique to estimate the energy of near-surface explosions using atmospheric acoustic waves. Conventional methods often employ air blast models based on a homogeneous atmosphere, where the acoustic wave propagation effects (e.g., refraction and diffraction) are not taken into account, and therefore, their accuracy decreases with increasing source-receiver distance. In this study, three-dimensional acoustic simulations are performed with a finite difference method in realistic atmospheres and topography, and the modeled acoustic Green's functions are incorporated into the waveform inversion for the acoustic source time functions. The strength of the acoustic source is related to explosionmore » yield based on a standard air blast model. The technique was applied to local explosions (<10 km) and provided reasonable yield estimates (<~30% error) in the presence of realistic topography and atmospheric structure. In conclusion, the presented method can be extended to explosions recorded at far distance provided proper meteorological specifications.« less

Joint OSNR monitoring and modulation format identification in digital coherent receivers using deep neural networks.

PubMed

Khan, Faisal Nadeem; Zhong, Kangping; Zhou, Xian; Al-Arashi, Waled Hussein; Yu, Changyuan; Lu, Chao; Lau, Alan Pak Tao

2017-07-24

We experimentally demonstrate the use of deep neural networks (DNNs) in combination with signals' amplitude histograms (AHs) for simultaneous optical signal-to-noise ratio (OSNR) monitoring and modulation format identification (MFI) in digital coherent receivers. The proposed technique automatically extracts OSNR and modulation format dependent features of AHs, obtained after constant modulus algorithm (CMA) equalization, and exploits them for the joint estimation of these parameters. Experimental results for 112 Gbps polarization-multiplexed (PM) quadrature phase-shift keying (QPSK), 112 Gbps PM 16 quadrature amplitude modulation (16-QAM), and 240 Gbps PM 64-QAM signals demonstrate OSNR monitoring with mean estimation errors of 1.2 dB, 0.4 dB, and 1 dB, respectively. Similarly, the results for MFI show 100% identification accuracy for all three modulation formats. The proposed technique applies deep machine learning algorithms inside standard digital coherent receiver and does not require any additional hardware. Therefore, it is attractive for cost-effective multi-parameter estimation in next-generation elastic optical networks (EONs).

Fast frequency acquisition via adaptive least squares algorithm

NASA Technical Reports Server (NTRS)

Kumar, R.

1986-01-01

A new least squares algorithm is proposed and investigated for fast frequency and phase acquisition of sinusoids in the presence of noise. This algorithm is a special case of more general, adaptive parameter-estimation techniques. The advantages of the algorithms are their conceptual simplicity, flexibility and applicability to general situations. For example, the frequency to be acquired can be time varying, and the noise can be nonGaussian, nonstationary and colored. As the proposed algorithm can be made recursive in the number of observations, it is not necessary to have a priori knowledge of the received signal-to-noise ratio or to specify the measurement time. This would be required for batch processing techniques, such as the fast Fourier transform (FFT). The proposed algorithm improves the frequency estimate on a recursive basis as more and more observations are obtained. When the algorithm is applied in real time, it has the extra advantage that the observations need not be stored. The algorithm also yields a real time confidence measure as to the accuracy of the estimator.

Detecting background changes in environments with dynamic foreground by separating probability distribution function mixtures using Pearson's method of moments

NASA Astrophysics Data System (ADS)

Jenkins, Colleen; Jordan, Jay; Carlson, Jeff

2007-02-01

This paper presents parameter estimation techniques useful for detecting background changes in a video sequence with extreme foreground activity. A specific application of interest is automated detection of the covert placement of threats (e.g., a briefcase bomb) inside crowded public facilities. We propose that a histogram of pixel intensity acquired from a fixed mounted camera over time for a series of images will be a mixture of two Gaussian functions: the foreground probability distribution function and background probability distribution function. We will use Pearson's Method of Moments to separate the two probability distribution functions. The background function can then be "remembered" and changes in the background can be detected. Subsequent comparisons of background estimates are used to detect changes. Changes are flagged to alert security forces to the presence and location of potential threats. Results are presented that indicate the significant potential for robust parameter estimation techniques as applied to video surveillance.

Applying traditional signal processing techniques to social media exploitation for situational understanding

NASA Astrophysics Data System (ADS)

Abdelzaher, Tarek; Roy, Heather; Wang, Shiguang; Giridhar, Prasanna; Al Amin, Md. Tanvir; Bowman, Elizabeth K.; Kolodny, Michael A.

2016-05-01

Signal processing techniques such as filtering, detection, estimation and frequency domain analysis have long been applied to extract information from noisy sensor data. This paper describes the exploitation of these signal processing techniques to extract information from social networks, such as Twitter and Instagram. Specifically, we view social networks as noisy sensors that report events in the physical world. We then present a data processing stack for detection, localization, tracking, and veracity analysis of reported events using social network data. We show using a controlled experiment that the behavior of social sources as information relays varies dramatically depending on context. In benign contexts, there is general agreement on events, whereas in conflict scenarios, a significant amount of collective filtering is introduced by conflicted groups, creating a large data distortion. We describe signal processing techniques that mitigate such distortion, resulting in meaningful approximations of actual ground truth, given noisy reported observations. Finally, we briefly present an implementation of the aforementioned social network data processing stack in a sensor network analysis toolkit, called Apollo. Experiences with Apollo show that our techniques are successful at identifying and tracking credible events in the physical world.

Unsupervised, Robust Estimation-based Clustering for Multispectral Images

NASA Technical Reports Server (NTRS)

Netanyahu, Nathan S.

1997-01-01

To prepare for the challenge of handling the archiving and querying of terabyte-sized scientific spatial databases, the NASA Goddard Space Flight Center's Applied Information Sciences Branch (AISB, Code 935) developed a number of characterization algorithms that rely on supervised clustering techniques. The research reported upon here has been aimed at continuing the evolution of some of these supervised techniques, namely the neural network and decision tree-based classifiers, plus extending the approach to incorporating unsupervised clustering algorithms, such as those based on robust estimation (RE) techniques. The algorithms developed under this task should be suited for use by the Intelligent Information Fusion System (IIFS) metadata extraction modules, and as such these algorithms must be fast, robust, and anytime in nature. Finally, so that the planner/schedule module of the IlFS can oversee the use and execution of these algorithms, all information required by the planner/scheduler must be provided to the IIFS development team to ensure the timely integration of these algorithms into the overall system.

Watching Grass - a Pilot Study on the Suitability of Photogrammetric Techniques for Quantifying Change in Aboveground Biomass in Grassland Experiments

NASA Astrophysics Data System (ADS)

Kröhnert, M.; Anderson, R.; Bumberger, J.; Dietrich, P.; Harpole, W. S.; Maas, H.-G.

2018-05-01

Grassland ecology experiments in remote locations requiring quantitative analysis of the biomass in defined plots are becoming increasingly widespread, but are still limited by manual sampling methodologies. To provide a cost-effective automated solution for biomass determination, several photogrammetric techniques are examined to generate 3D point cloud representations of plots as a basis, to estimate aboveground biomass on grassland plots, which is a key ecosystem variable used in many experiments. Methods investigated include Structure from Motion (SfM) techniques for camera pose estimation with posterior dense matching as well as the usage of a Time of Flight (TOF) 3D camera, a laser light sheet triangulation system and a coded light projection system. In this context, plants of small scales (herbage) and medium scales are observed. In the first pilot study presented here, the best results are obtained by applying dense matching after SfM, ideal for integration into distributed experiment networks.

Quantum correlation measurements in interferometric gravitational-wave detectors

NASA Astrophysics Data System (ADS)

Martynov, D. V.; Frolov, V. V.; Kandhasamy, S.; Izumi, K.; Miao, H.; Mavalvala, N.; Hall, E. D.; Lanza, R.; Abbott, B. P.; Abbott, R.; Abbott, T. D.; Adams, C.; Adhikari, R. X.; Anderson, S. B.; Ananyeva, A.; Appert, S.; Arai, K.; Aston, S. M.; Ballmer, S. W.; Barker, D.; Barr, B.; Barsotti, L.; Bartlett, J.; Bartos, I.; Batch, J. C.; Bell, A. S.; Betzwieser, J.; Billingsley, G.; Birch, J.; Biscans, S.; Biwer, C.; Blair, C. D.; Bork, R.; Brooks, A. F.; Ciani, G.; Clara, F.; Countryman, S. T.; Cowart, M. J.; Coyne, D. C.; Cumming, A.; Cunningham, L.; Danzmann, K.; Da Silva Costa, C. F.; Daw, E. J.; DeBra, D.; DeRosa, R. T.; DeSalvo, R.; Dooley, K. L.; Doravari, S.; Driggers, J. C.; Dwyer, S. E.; Effler, A.; Etzel, T.; Evans, M.; Evans, T. M.; Factourovich, M.; Fair, H.; Fernández Galiana, A.; Fisher, R. P.; Fritschel, P.; Fulda, P.; Fyffe, M.; Giaime, J. A.; Giardina, K. D.; Goetz, E.; Goetz, R.; Gras, S.; Gray, C.; Grote, H.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hammond, G.; Hanks, J.; Hanson, J.; Hardwick, T.; Harry, G. M.; Heintze, M. C.; Heptonstall, A. W.; Hough, J.; Jones, R.; Karki, S.; Kasprzack, M.; Kaufer, S.; Kawabe, K.; Kijbunchoo, N.; King, E. J.; King, P. J.; Kissel, J. S.; Korth, W. Z.; Kuehn, G.; Landry, M.; Lantz, B.; Lockerbie, N. A.; Lormand, M.; Lundgren, A. P.; MacInnis, M.; Macleod, D. M.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martin, I. W.; Mason, K.; Massinger, T. J.; Matichard, F.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McIntyre, G.; McIver, J.; Mendell, G.; Merilh, E. L.; Meyers, P. M.; Miller, J.; Mittleman, R.; Moreno, G.; Mueller, G.; Mullavey, A.; Munch, J.; Nuttall, L. K.; Oberling, J.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; Ottaway, D. J.; Overmier, H.; Palamos, J. R.; Paris, H. R.; Parker, W.; Pele, A.; Penn, S.; Phelps, M.; Pierro, V.; Pinto, I.; Principe, M.; Prokhorov, L. G.; Puncken, O.; Quetschke, V.; Quintero, E. A.; Raab, F. J.; Radkins, H.; Raffai, P.; Reid, S.; Reitze, D. H.; Robertson, N. A.; Rollins, J. G.; Roma, V. J.; Romie, J. H.; Rowan, S.; Ryan, K.; Sadecki, T.; Sanchez, E. J.; Sandberg, V.; Savage, R. L.; Schofield, R. M. S.; Sellers, D.; Shaddock, D. A.; Shaffer, T. J.; Shapiro, B.; Shawhan, P.; Shoemaker, D. H.; Sigg, D.; Slagmolen, B. J. J.; Smith, B.; Smith, J. R.; Sorazu, B.; Staley, A.; Strain, K. A.; Tanner, D. B.; Taylor, R.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thrane, E.; Torrie, C. I.; Traylor, G.; Vajente, G.; Valdes, G.; van Veggel, A. A.; Vecchio, A.; Veitch, P. J.; Venkateswara, K.; Vo, T.; Vorvick, C.; Walker, M.; Ward, R. L.; Warner, J.; Weaver, B.; Weiss, R.; Weßels, P.; Willke, B.; Wipf, C. C.; Worden, J.; Wu, G.; Yamamoto, H.; Yancey, C. C.; Yu, Hang; Yu, Haocun; Zhang, L.; Zucker, M. E.; Zweizig, J.; LSC Instrument Authors

2017-04-01

Quantum fluctuations in the phase and amplitude quadratures of light set limitations on the sensitivity of modern optical instruments. The sensitivity of the interferometric gravitational-wave detectors, such as the Advanced Laser Interferometer Gravitational-Wave Observatory (LIGO), is limited by quantum shot noise, quantum radiation pressure noise, and a set of classical noises. We show how the quantum properties of light can be used to distinguish these noises using correlation techniques. Particularly, in the first part of the paper we show estimations of the coating thermal noise and gas phase noise, hidden below the quantum shot noise in the Advanced LIGO sensitivity curve. We also make projections on the observatory sensitivity during the next science runs. In the second part of the paper we discuss the correlation technique that reveals the quantum radiation pressure noise from the background of classical noises and shot noise. We apply this technique to the Advanced LIGO data, collected during the first science run, and experimentally estimate the quantum correlations and quantum radiation pressure noise in the interferometer.

[A method of measuring presampled modulation transfer function using a rationalized approximation of geometrical edge slope].

PubMed

Honda, Michitaka

2014-04-01

Several improvements were implemented in the edge method of presampled modulation transfer function measurements (MTFs). The estimation technique for edge angle was newly developed by applying an algorithm for principal components analysis. The error in the estimation was statistically confirmed to be less than 0.01 even in the presence of quantum noise. Secondly, the geometrical edge slope was approximated using a rationalized number, making it possible to obtain an oversampled edge response function (ESF) with equal intervals. Thirdly, the final MTFs were estimated using the average of multiple MTFs calculated for local areas. This averaging operation eliminates the errors caused by the rationalized approximation. Computer-simulated images were used to evaluate the accuracy of our method. The relative error between the estimated MTF and the theoretical MTF at the Nyquist frequency was less than 0.5% when the MTF was expressed as a sinc function. For MTFs representing an indirect detector and phase-contrast detector, good agreement was also observed for the estimated MTFs for each. The high accuracy of the MTF estimation was also confirmed, even for edge angles of around 10 degrees, which suggests the potential for simplification of the measurement conditions. The proposed method could be incorporated into an automated measurement technique using a software application.

Invited commentary: Lost in estimation--searching for alternatives to markov chains to fit complex Bayesian models.

PubMed

Molitor, John

2012-03-01

Bayesian methods have seen an increase in popularity in a wide variety of scientific fields, including epidemiology. One of the main reasons for their widespread application is the power of the Markov chain Monte Carlo (MCMC) techniques generally used to fit these models. As a result, researchers often implicitly associate Bayesian models with MCMC estimation procedures. However, Bayesian models do not always require Markov-chain-based methods for parameter estimation. This is important, as MCMC estimation methods, while generally quite powerful, are complex and computationally expensive and suffer from convergence problems related to the manner in which they generate correlated samples used to estimate probability distributions for parameters of interest. In this issue of the Journal, Cole et al. (Am J Epidemiol. 2012;175(5):368-375) present an interesting paper that discusses non-Markov-chain-based approaches to fitting Bayesian models. These methods, though limited, can overcome some of the problems associated with MCMC techniques and promise to provide simpler approaches to fitting Bayesian models. Applied researchers will find these estimation approaches intuitively appealing and will gain a deeper understanding of Bayesian models through their use. However, readers should be aware that other non-Markov-chain-based methods are currently in active development and have been widely published in other fields.

Three-dimensional dominant frequency mapping using autoregressive spectral analysis of atrial electrograms of patients in persistent atrial fibrillation.

PubMed

Salinet, João L; Masca, Nicholas; Stafford, Peter J; Ng, G André; Schlindwein, Fernando S

2016-03-08

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in eliminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electrophysiology (EP) procedures but literature is restricted on using alternative spectral estimation techniques that can have a better frequency resolution that FFT-based spectral estimation. Autoregressive (AR) model-based spectral estimation techniques, with emphasis on selection of appropriate sampling rate and AR model order, were implemented to generate high-density 3D DF maps of atrial electrograms (AEGs) in persistent atrial fibrillation (persAF). For each patient, 2048 simultaneous AEGs were recorded for 20.478 s-long segments in the left atrium (LA) and exported for analysis, together with their anatomical locations. After the DFs were identified using AR-based spectral estimation, they were colour coded to produce sequential 3D DF maps. These maps were systematically compared with maps found using the Fourier-based approach. 3D DF maps can be obtained using AR-based spectral estimation after AEGs downsampling (DS) and the resulting maps are very similar to those obtained using FFT-based spectral estimation (mean 90.23 %). There were no significant differences between AR techniques (p = 0.62). The processing time for AR-based approach was considerably shorter (from 5.44 to 5.05 s) when lower sampling frequencies and model order values were used. Higher levels of DS presented higher rates of DF agreement (sampling frequency of 37.5 Hz). We have demonstrated the feasibility of using AR spectral estimation methods for producing 3D DF maps and characterised their differences to the maps produced using the FFT technique, offering an alternative approach for 3D DF computation in human persAF studies.

Tailored Excitation for Frequency Response Measurement Applied to the X-43A Flight Vehicle

NASA Technical Reports Server (NTRS)

Baumann, Ethan

2007-01-01

An important aspect of any flight research project is assessing aircraft stability and flight control performance. In some programs this assessment is accomplished through the estimation of the in-flight vehicle frequency response. This estimation has traditionally been a lengthy task requiring separate swept sine inputs for each control axis at a constant flight condition. Hypersonic vehicles spend little time at any specific flight condition while they are decelerating. Accordingly, it is difficult to use traditional methods to calculate the vehicle frequency response and stability margins for this class of vehicle. A technique has been previously developed to significantly reduce the duration of the excitation input by tailoring the input to excite only the frequency range of interest. Reductions in test time were achieved by simultaneously applying tailored excitation signals to multiple control loops, allowing a quick estimate of the frequency response of a particular aircraft. This report discusses the flight results obtained from applying a tailored excitation input to the X-43A longitudinal and lateral-directional control loops during the second and third flights. The frequency responses and stability margins obtained from flight data are compared with preflight predictions.

Fuzzy Modal Control Applied to Smart Composite Structure

NASA Astrophysics Data System (ADS)

Koroishi, E. H.; Faria, A. W.; Lara-Molina, F. A.; Steffen, V., Jr.

2015-07-01

This paper proposes an active vibration control technique, which is based on Fuzzy Modal Control, as applied to a piezoelectric actuator bonded to a composite structure forming a so-called smart composite structure. Fuzzy Modal Controllers were found to be well adapted for controlling structures with nonlinear behavior, whose characteristics change considerably with respect to time. The smart composite structure was modelled by using a so called mixed theory. This theory uses a single equivalent layer for the discretization of the mechanical displacement field and a layerwise representation of the electrical field. Temperature effects are neglected. Due to numerical reasons it was necessary to reduce the size of the model of the smart composite structure so that the design of the controllers and the estimator could be performed. The role of the Kalman Estimator in the present contribution is to estimate the modal states of the system, which are used by the Fuzzy Modal controllers. Simulation results illustrate the effectiveness of the proposed vibration control methodology for composite structures.

Turbulent Reconnection Rates from Cluster Observations in the Magnetosheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetosheath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

Turbulent Reconnection Rates from Cluster Observations in the Magneto sheath

NASA Technical Reports Server (NTRS)

Wendel, Deirdre

2011-01-01

The role of turbulence in producing fast reconnection rates is an important unresolved question. Scant in situ analyses exist. We apply multiple spacecraft techniques to a case of nonlinear turbulent reconnection in the magnetosheath to test various theoretical results for turbulent reconnection rates. To date, in situ estimates of the contribution of turbulence to reconnection rates have been calculated from an effective electric field derived through linear wave theory. However, estimates of reconnection rates based on fully nonlinear turbulence theories and simulations exist that are amenable to multiple spacecraft analyses. Here we present the linear and nonlinear theories and apply some of the nonlinear rates to Cluster observations of reconnecting, turbulent current sheets in the magnetos heath. We compare the results to the net reconnection rate found from the inflow speed. Ultimately, we intend to test and compare linear and nonlinear estimates of the turbulent contribution to reconnection rates and to measure the relative contributions of turbulence and the Hall effect.

Estimation of fatigue life using electromechanical impedance technique

NASA Astrophysics Data System (ADS)

Lim, Yee Yan; Soh, Chee Kiong

2010-04-01

Fatigue induced damage is often progressive and gradual in nature. Structures subjected to large number of fatigue load cycles will encounter the process of progressive crack initiation, propagation and finally fracture. Monitoring of structural health, especially for the critical components, is therefore essential for early detection of potential harmful crack. Recent advent of smart materials such as piezo-impedance transducer adopting the electromechanical impedance (EMI) technique and wave propagation technique are well proven to be effective in incipient damage detection and characterization. Exceptional advantages such as autonomous, real-time and online, remote monitoring may provide a cost-effective alternative to the conventional structural health monitoring (SHM) techniques. In this study, the main focus is to investigate the feasibility of characterizing a propagating fatigue crack in a structure using the EMI technique as well as estimating its remaining fatigue life using the linear elastic fracture mechanics (LEFM) approach. Uniaxial cyclic tensile load is applied on a lab-sized aluminum beam up to failure. Progressive shift in admittance signatures measured by the piezo-impedance transducer (PZT patch) corresponding to increase of loading cycles reflects effectiveness of the EMI technique in tracing the process of fatigue damage progression. With the use of LEFM, prediction of the remaining life of the structure at different cycles of loading is possible.

A linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Goetz, Alexander F. H.

1992-01-01

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Hierarchical models for estimating density from DNA mark-recapture studies

USGS Publications Warehouse

Gardner, B.; Royle, J. Andrew; Wegan, M.T.

2009-01-01

Genetic sampling is increasingly used as a tool by wildlife biologists and managers to estimate abundance and density of species. Typically, DNA is used to identify individuals captured in an array of traps ( e. g., baited hair snares) from which individual encounter histories are derived. Standard methods for estimating the size of a closed population can be applied to such data. However, due to the movement of individuals on and off the trapping array during sampling, the area over which individuals are exposed to trapping is unknown, and so obtaining unbiased estimates of density has proved difficult. We propose a hierarchical spatial capture-recapture model which contains explicit models for the spatial point process governing the distribution of individuals and their exposure to (via movement) and detection by traps. Detection probability is modeled as a function of each individual's distance to the trap. We applied this model to a black bear (Ursus americanus) study conducted in 2006 using a hair-snare trap array in the Adirondack region of New York, USA. We estimated the density of bears to be 0.159 bears/km2, which is lower than the estimated density (0.410 bears/km2) based on standard closed population techniques. A Bayesian analysis of the model is fully implemented in the software program WinBUGS.

Delay-and-sum beamforming for direction of arrival estimation applied to gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, António L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2011-06-01

Sniper positioning systems described in the literature use a two-step algorithm to estimate the sniper's location. First, the shockwave and the muzzle blast acoustic signatures must be detected and recognized, followed by an estimation of their respective direction-of-arrival (DOA). Second, the actual sniper's position is calculated based on the estimated DOA via an iterative algorithm that varies from system to system. The overall performance of such a system, however, is highly compromised when the first step is not carried out successfully. Currently available systems rely on a simple calculation of differences of time-of-arrival to estimate angles-of-arrival. This approach, however, lacks robustness by not taking full advantage of the array of sensors. This paper shows how the delay-and-sum beamforming technique can be applied to estimate the DOA for both the shockwave and the muzzle blast. The method has the twofold advantage of 1) adding an array gain of 10 logM, i.e., an increased SNR of 6 dB for a 4-microphone array, which is equivalent to doubling the detection range assuming free-field propagation; and 2) offering improved robustness in handling single- and multi-shots events as well as reflections by taking advantage of the spatial filtering capability.

Signal and array processing techniques for RFID readers

NASA Astrophysics Data System (ADS)

Wang, Jing; Amin, Moeness; Zhang, Yimin

2006-05-01

Radio Frequency Identification (RFID) has recently attracted much attention in both the technical and business communities. It has found wide applications in, for example, toll collection, supply-chain management, access control, localization tracking, real-time monitoring, and object identification. Situations may arise where the movement directions of the tagged RFID items through a portal is of interest and must be determined. Doppler estimation may prove complicated or impractical to perform by RFID readers. Several alternative approaches, including the use of an array of sensors with arbitrary geometry, can be applied. In this paper, we consider direction-of-arrival (DOA) estimation techniques for application to near-field narrowband RFID problems. Particularly, we examine the use of a pair of RFID antennas to track moving RFID tagged items through a portal. With two antennas, the near-field DOA estimation problem can be simplified to a far-field problem, yielding a simple way for identifying the direction of the tag movement, where only one parameter, the angle, needs to be considered. In this case, tracking of the moving direction of the tag simply amounts to computing the spatial cross-correlation between the data samples received at the two antennas. It is pointed out that the radiation patterns of the reader and tag antennas, particularly their phase characteristics, have a significant effect on the performance of DOA estimation. Indoor experiments are conducted in the Radar Imaging and RFID Labs at Villanova University for validating the proposed technique for target movement direction estimations.

Cobble cam: Grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses

USGS Publications Warehouse

Warrick, J.A.; Rubin, D.M.; Ruggiero, P.; Harney, J.N.; Draut, A.E.; Buscombe, D.

2009-01-01

A new application of the autocorrelation grain size analysis technique for mixed to coarse sediment settings has been investigated. Photographs of sand- to boulder-sized sediment along the Elwha River delta beach were taken from approximately 1??2 m above the ground surface, and detailed grain size measurements were made from 32 of these sites for calibration and validation. Digital photographs were found to provide accurate estimates of the long and intermediate axes of the surface sediment (r2 > 0??98), but poor estimates of the short axes (r2 = 0??68), suggesting that these short axes were naturally oriented in the vertical dimension. The autocorrelation method was successfully applied resulting in total irreducible error of 14% over a range of mean grain sizes of 1 to 200 mm. Compared with reported edge and object-detection results, it is noted that the autocorrelation method presented here has lower error and can be applied to a much broader range of mean grain sizes without altering the physical set-up of the camera (~200-fold versus ~6-fold). The approach is considerably less sensitive to lighting conditions than object-detection methods, although autocorrelation estimates do improve when measures are taken to shade sediments from direct sunlight. The effects of wet and dry conditions are also evaluated and discussed. The technique provides an estimate of grain size sorting from the easily calculated autocorrelation standard error, which is correlated with the graphical standard deviation at an r2 of 0??69. The technique is transferable to other sites when calibrated with linear corrections based on photo-based measurements, as shown by excellent grain-size analysis results (r2 = 0??97, irreducible error = 16%) from samples from the mixed grain size beaches of Kachemak Bay, Alaska. Thus, a method has been developed to measure mean grain size and sorting properties of coarse sediments. ?? 2009 John Wiley & Sons, Ltd.

Estimation of Regional Carbon Balance from Atmospheric Observations

NASA Astrophysics Data System (ADS)

Denning, S.; Uliasz, M.; Skidmore, J.

2002-12-01

Variations in the concentration of CO2 and other trace gases in time and space contain information about sources and sinks at regional scales. Several methods have been developed to quantitatively extract this information from atmospheric measurements. Mass-balance techniques depend on the ability to repeatedly sample the same mass of air, which involves careful attention to airmass trajectories. Inverse and adjoint techniques rely on decomposition of the source field into quasi-independent "basis functions" that are propagated through transport models and then used to synthesize optimal linear combinations that best match observations. A recently proposed method for regional flux estimation from continuous measurements at tall towers relies on time-mean vertical gradients, and requires careful trajectory analysis to map the estimates onto regional ecosystems. Each of these techniques is likely to be applied to measurements made during the North American Carbon Program. We have also explored the use of Bayesian synthesis inversion at regional scales, using a Lagrangian particle dispersion model driven by mesoscale transport fields. Influence functions were calculated for each hypothetical observation in a realistic diurnally-varying flow. These influence functions were then treated as basis functions for the purpose of separate inversions for daytime photosynthesis and 24-hour mean ecosystem respiration. Our results highlight the importance of estimating CO2 fluxes through the lateral boundaries of the model. Respiration fluxes were well constrained by one or two hypothetical towers, regardless of inflow fluxes. Time-varying assimilation fluxes were less well constrained, and much more dependent on knowledge of inflow fluxes. The small net difference between respiration and photosynthesis was the most difficult to determine, being extremely sensitive to knowledge of inflow fluxes. Finally, we explored the feasibility of directly incorporating mid-day concentration values measured at surface-layer flux towers in global inversions for regional surface fluxes. We found that such data would substantially improve the observational constraint on current carbon cycle models, especially if applied selectively to a well-designed subset of the current network of flux towers.

Estimation of deep infiltration in unsaturated limestone environments using cave lidar and drip count data

NASA Astrophysics Data System (ADS)

Mahmud, K.; Mariethoz, G.; Baker, A.; Treble, P. C.; Markowska, M.; McGuire, E.

2016-01-01

Limestone aeolianites constitute karstic aquifers covering much of the western and southern Australian coastal fringe. They are a key groundwater resource for a range of industries such as winery and tourism, and provide important ecosystem services such as habitat for stygofauna. Moreover, recharge estimation is important for understanding the water cycle, for contaminant transport, for water management, and for stalagmite-based paleoclimate reconstructions. Caves offer a natural inception point to observe both the long-term groundwater recharge and the preferential movement of water through the unsaturated zone of such limestone. With the availability of automated drip rate logging systems and remote sensing techniques, it is now possible to deploy the combination of these methods for larger-scale studies of infiltration processes within a cave. In this study, we utilize a spatial survey of automated cave drip monitoring in two large chambers of Golgotha Cave, south-western Western Australia (SWWA), with the aim of better understanding infiltration water movement and the relationship between infiltration, stalactite morphology, and unsaturated zone recharge. By applying morphological analysis of ceiling features from Terrestrial LiDAR (T-LiDAR) data, coupled with drip time series and climate data from 2012 to 2014, we demonstrate the nature of the relationships between infiltration through fractures in the limestone and unsaturated zone recharge. Similarities between drip rate time series are interpreted in terms of flow patterns, cave chamber morphology, and lithology. Moreover, we develop a new technique to estimate recharge in large-scale caves, engaging flow classification to determine the cave ceiling area covered by each flow category and drip data for the entire observation period, to calculate the total volume of cave discharge. This new technique can be applied to other cave sites to identify highly focussed areas of recharge and can help to better estimate the total recharge volume.

Estimation of deep infiltration in unsaturated limestone environments using cave LiDAR and drip count data

NASA Astrophysics Data System (ADS)

Mahmud, K.; Mariethoz, G.; Baker, A.; Treble, P. C.; Markowska, M.; McGuire, E.

2015-09-01

Limestone aeolianites constitute karstic aquifers covering much of the western and southern Australian coastal fringe. They are a key groundwater resource for a range of industries such as winery and tourism, and provide important ecosystem services such as habitat for stygofauna. Moreover, recharge estimation is important for understanding the water cycle, for contaminant transport, for water management and for stalagmite-based paleoclimate reconstructions. Caves offer a natural inception point to observe both the long-term groundwater recharge and the preferential movement of water through the unsaturated zone of such limestone. With the availability of automated drip rate logging systems and remote sensing techniques, it is now possible to deploy the combination of these methods for larger scale studies of infiltration processes within a cave. In this study, we utilize a spatial survey of automated cave drip monitoring in two large chambers of the Golgotha Cave, South-West Western Australia (SWWA), with the aim of better understanding infiltration water movement and the relationship between infiltration, stalactite morphology and unsaturated zone recharge. By applying morphological analysis of ceiling features from Terrestrial LiDAR (T-LiDAR) data, coupled with drip time series and climate data from 2012-2014, we demonstrate the nature of the relationships between infiltration through fractures in the limestone and unsaturated zone recharge. Similarities between drip-rate time series are interpreted in terms of flow patterns, cave chamber morphology and lithology. Moreover, we develop a new technique to estimate recharge in large scale caves, engaging flow classification to determine the cave ceiling area covered by each flow category and drip data for the entire observation period, to calculate the total volume of cave discharge. This new technique can be applied to other cave sites to identify highly focused areas of recharge and can help to better estimate the total recharge volume.

A Systematic Approach for Model-Based Aircraft Engine Performance Estimation

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Garg, Sanjay

2010-01-01

A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.

Phase shift method to estimate solids circulation rate in circulating fluidized beds

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

Ludlow, James Christopher; Panday, Rupen; Shadle, Lawrence J.

2013-01-01

While solids circulation rate is a critical design and control parameter in circulating fluidized bed (CFB) reactor systems, there are no available techniques to measure it directly at conditions of industrial interest. Cold flow tests have been conducted at NETL in an industrial scale CFB unit where the solids flow has been the topic of research in order to develop an independent method which could be applied to CFBs operating under the erosive and corrosive high temperatures and pressures of a coal fired boiler or gasifier. The dynamic responses of the CFB loop to modest modulated aeration flows in themore » return leg or standpipe were imposed to establish a periodic response in the unit without causing upset in the process performance. The resulting periodic behavior could then be analyzed with a dynamic model and the average solids circulation rate could be established. This method was applied to the CFB unit operated under a wide range of operating conditions including fast fluidization, core annular flow, dilute and dense transport, and dense suspension upflow. In addition, the system was operated in both low and high total solids inventories to explore the influence of inventory limiting cases on the estimated results. The technique was able to estimate the solids circulation rate for all transport circulating fluidized beds when operating above upper transport velocity, U{sub tr2}. For CFB operating in the fast fluidized bed regime (i.e., U{sub g}< U{sub tr2}), the phase shift technique was not successful. The riser pressure drop becomes independent of the solids circulation rate and the mass flow rate out of the riser does not show modulated behavior even when the riser pressure drop does.« less

An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system

NASA Astrophysics Data System (ADS)

Palanimuthu, Senthilkumar Jayalakshmi; Muthial, Chandrasekaran

2017-04-01

Channel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space-time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space-time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.

On Study of Air/Space-borne Dual-Wavelength Radar for Estimates of Rain Profiles

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert

2004-01-01

In this study, a framework is discussed to apply air/space-borne dual-wavelength radar for the estimation of characteristic parameters of hydrometeors. The focus of our study is on the Global Precipitation Measurements (GPM) precipitation radar, a dual-wavelength radar that operates at Ku (13.8 GHz) and Ka (35 GHz) bands. As the droplet size distributions (DSD) of rain are expressed as the Gamma function, a procedure is described to derive the median volume diameter (D(sub 0)) and particle number concentration (N(sub T)) of rain. The correspondences of an important quantity of dual-wavelength radar, defined as deferential frequency ratio (DFR), to the D(sub 0) in the melting region are given as a function of the distance from the 0 C isotherm. A self-consistent iterative algorithm that shows a promising to account for rain attenuation of radar and infer the DSD without use of surface reference technique (SRT) is examined by applying it to the apparent radar reflectivity profiles simulated from the DSD model and then comparing the estimates with the model (true) results. For light to moderate rain the self-consistent rain profiling approach converges to unique and correct solutions only if the same shape factors of Gamma functions are used both to generate and retrieve the rain profiles, but does not converges to the true solutions if the DSD form is not chosen correctly. To further examine the dual-wavelength techniques, the self-consistent algorithm, along with forward and backward rain profiling algorithms, is then applied to the measurements taken from the 2nd generation Precipitation Radar (PR-2) built by Jet Propulsion Laboratory. It is found that rain profiles estimated from the forward and backward approaches are not sensitive to shape factor of DSD Gamma distribution, but the self-consistent method is.

Estimating the Probability of Rare Events Occurring Using a Local Model Averaging.

PubMed

Chen, Jin-Hua; Chen, Chun-Shu; Huang, Meng-Fan; Lin, Hung-Chih

2016-10-01

In statistical applications, logistic regression is a popular method for analyzing binary data accompanied by explanatory variables. But when one of the two outcomes is rare, the estimation of model parameters has been shown to be severely biased and hence estimating the probability of rare events occurring based on a logistic regression model would be inaccurate. In this article, we focus on estimating the probability of rare events occurring based on logistic regression models. Instead of selecting a best model, we propose a local model averaging procedure based on a data perturbation technique applied to different information criteria to obtain different probability estimates of rare events occurring. Then an approximately unbiased estimator of Kullback-Leibler loss is used to choose the best one among them. We design complete simulations to show the effectiveness of our approach. For illustration, a necrotizing enterocolitis (NEC) data set is analyzed. © 2016 Society for Risk Analysis.

Inter- and Intra-method Variability of VS Profiles and VS30 at ARRA-funded Sites

NASA Astrophysics Data System (ADS)

Yong, A.; Boatwright, J.; Martin, A. J.

2015-12-01

The 2009 American Recovery and Reinvestment Act (ARRA) funded geophysical site characterizations at 191 seismographic stations in California and in the central and eastern United States. Shallow boreholes were considered cost- and environmentally-prohibitive, thus non-invasive methods (passive and active surface- and body-wave techniques) were used at these stations. The drawback, however, is that these techniques measure seismic properties indirectly and introduce more uncertainty than borehole methods. The principal methods applied were Array Microtremor (AM), Multi-channel Analysis of Surface Waves (MASW; Rayleigh and Love waves), Spectral Analysis of Surface Waves (SASW), Refraction Microtremor (ReMi), and P- and S-wave refraction tomography. Depending on the apparent geologic or seismic complexity of the site, field crews applied one or a combination of these methods to estimate the shear-wave velocity (VS) profile and calculate VS30, the time-averaged VS to a depth of 30 meters. We study the inter- and intra-method variability of VS and VS30 at each seismographic station where combinations of techniques were applied. For each site, we find both types of variability in VS30 remain insignificant (5-10% difference) despite substantial variability observed in the VS profiles. We also find that reliable VS profiles are best developed using a combination of techniques, e.g., surface-wave VS profiles correlated against P-wave tomography to constrain variables (Poisson's ratio and density) that are key depth-dependent parameters used in modeling VS profiles. The most reliable results are based on surface- or body-wave profiles correlated against independent observations such as material properties inferred from outcropping geology nearby. For example, mapped geology describes station CI.LJR as a hard rock site (VS30 > 760 m/s). However, decomposed rock outcrops were found nearby and support the estimated VS30 of 303 m/s derived from the MASW (Love wave) profile.

Satellite estimation of incident photosynthetically active radiation using ultraviolet reflectance

NASA Technical Reports Server (NTRS)

Eck, Thomas F.; Dye, Dennis G.

1991-01-01

A new satellite remote sensing method for estimating the amount of photosynthetically active radiation (PAR, 400-700 nm) incident at the earth's surface is described and tested. Potential incident PAR for clear sky conditions is computed from an existing spectral model. A major advantage of the UV approach over existing visible band approaches to estimating insolation is the improved ability to discriminate clouds from high-albedo background surfaces. UV spectral reflectance data from the Total Ozone Mapping Spectrometer (TOMS) were used to test the approach for three climatically distinct, midlatitude locations. Estimates of monthly total incident PAR from the satellite technique differed from values computed from ground-based pyranometer measurements by less than 6 percent. This UV remote sensing method can be applied to estimate PAR insolation over ocean and land surfaces which are free of ice and snow.

Experimental validation of pulsed column inventory estimators

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

Beyerlein, A.L.; Geldard, J.F.; Weh, R.

Near-real-time accounting (NRTA) for reprocessing plants relies on the timely measurement of all transfers through the process area and all inventory in the process. It is difficult to measure the inventory of the solvent contractors; therefore, estimation techniques are considered. We have used experimental data obtained at the TEKO facility in Karlsruhe and have applied computer codes developed at Clemson University to analyze this data. For uranium extraction, the computer predictions agree to within 15% of the measured inventories. We believe this study is significant in demonstrating that using theoretical models with a minimum amount of process data may bemore » an acceptable approach to column inventory estimation for NRTA. 15 refs., 7 figs.« less

Differential reliability : probabilistic engineering applied to wood members in bending-tension

Treesearch

Stanley K. Suddarth; Frank E. Woeste; William L. Galligan

1978-01-01

Reliability analysis is a mathematical technique for appraising the design and materials of engineered structures to provide a quantitative estimate of probability of failure. Two or more cases which are similar in all respects but one may be analyzed by this method; the contrast between the probabilities of failure for these cases allows strong analytical focus on the...

Differences in iron concentration in whole blood of animal models using NAA

NASA Astrophysics Data System (ADS)

Bahovschi, V.; Zamboni, C. B.; Lopes Silva, L. F. F.; Metairon, S.; Medeiros, I. M. M. A.

2015-07-01

In this study Neutron Activation Analysis technique (NAA) was applied to determine Fe concentration in whole blood samples of several animal models such as: mice (Mus musculus), Golden Hamster (Mesocricetus auratus), Wistar rats, Albinic Rabbits of New Zealand, Golden Retriever dogs and Crioulabreed horses. These results were compared with human whole blood estimation to check their similarities.

Application of Data Assimilation with the Root Zone Water Quality Model for Soil Moisture Profile Estimation

USDA-ARS?s Scientific Manuscript database

The Ensemble Kalman Filter (EnKF), a popular data assimilation technique for non-linear systems was applied to the Root Zone Water Quality Model. Measured soil moisture data at four different depths (5cm, 20cm, 40cm and 60cm) from two agricultural fields (AS1 and AS2) in northeastern Indiana were us...

A Cross-National Analysis of the Relations of School Choice and Effectiveness Differences between Private-Dependent and Public Schools

ERIC Educational Resources Information Center

Dronkers, Jaap; Avram, Silvia

2010-01-01

We apply propensity score matching to the estimation of differential school effectiveness between the publicly funded private sector and the public sector in a sample of 26 countries. This technique allows us to distinguish between school choice and school effectiveness processes and thus to account for selectivity issues involved in the…

GI-13 Integration of Methods for Air Quality and Health Data, Remote Sensed and In-Situ with Disease Estimate Techniques

EPA Science Inventory

GI-13 – A brief review of the GEO Work Plan DescriptionGlobal map examples of PM2.5 satellite measuresUS Maps showing examples of fused in-situ and satellite dataNew AQ Monitoring approach with social value – Village Green exampleComputing and Systems Applied in Energ...

Study of the effect of short ranged ordering on the magnetism in FeCr alloys

NASA Astrophysics Data System (ADS)

Jena, Ambika Prasad; Sanyal, Biplab; Mookerjee, Abhijit

2014-01-01

For the study of magnetism in systems where the local environment plays an important role, we propose a marriage between the Monte Carlo simulation and Zunger's special quasi-random structures. We apply this technique on disordered FeCr alloys and show that our estimates of the transition temperature is in good agreement with earlier experiments.

Likelihood-based inference for discretely observed birth-death-shift processes, with applications to evolution of mobile genetic elements.

PubMed

Xu, Jason; Guttorp, Peter; Kato-Maeda, Midori; Minin, Vladimir N

2015-12-01

Continuous-time birth-death-shift (BDS) processes are frequently used in stochastic modeling, with many applications in ecology and epidemiology. In particular, such processes can model evolutionary dynamics of transposable elements-important genetic markers in molecular epidemiology. Estimation of the effects of individual covariates on the birth, death, and shift rates of the process can be accomplished by analyzing patient data, but inferring these rates in a discretely and unevenly observed setting presents computational challenges. We propose a multi-type branching process approximation to BDS processes and develop a corresponding expectation maximization algorithm, where we use spectral techniques to reduce calculation of expected sufficient statistics to low-dimensional integration. These techniques yield an efficient and robust optimization routine for inferring the rates of the BDS process, and apply broadly to multi-type branching processes whose rates can depend on many covariates. After rigorously testing our methodology in simulation studies, we apply our method to study intrapatient time evolution of IS6110 transposable element, a genetic marker frequently used during estimation of epidemiological clusters of Mycobacterium tuberculosis infections. © 2015, The International Biometric Society.

Estimation et validation des derivees de stabilite et controle du modele dynamique non-lineaire d'un drone a voilure fixe

NASA Astrophysics Data System (ADS)

Courchesne, Samuel

Knowledge of the dynamic characteristics of a fixed-wing UAV is necessary to design flight control laws and to conceive a high quality flight simulator. The basic features of a flight mechanic model include the properties of mass, inertia and major aerodynamic terms. They respond to a complex process involving various numerical analysis techniques and experimental procedures. This thesis focuses on the analysis of estimation techniques applied to estimate problems of stability and control derivatives from flight test data provided by an experimental UAV. To achieve this objective, a modern identification methodology (Quad-M) is used to coordinate the processing tasks from multidisciplinary fields, such as parameter estimation modeling, instrumentation, the definition of flight maneuvers and validation. The system under study is a non-linear model with six degrees of freedom with a linear aerodynamic model. The time domain techniques are used for identification of the drone. The first technique, the equation error method is used to determine the structure of the aerodynamic model. Thereafter, the output error method and filter error method are used to estimate the aerodynamic coefficients values. The Matlab scripts for estimating the parameters obtained from the American Institute of Aeronautics and Astronautics (AIAA) are used and modified as necessary to achieve the desired results. A commendable effort in this part of research is devoted to the design of experiments. This includes an awareness of the system data acquisition onboard and the definition of flight maneuvers. The flight tests were conducted under stable flight conditions and with low atmospheric disturbance. Nevertheless, the identification results showed that the filter error method is most effective for estimating the parameters of the drone due to the presence of process noise and measurement. The aerodynamic coefficients are validated using a numerical analysis of the vortex method. In addition, a simulation model incorporating the estimated parameters is used to compare the behavior of states measured. Finally, a good correspondence between the results is demonstrated despite a limited number of flight data. Keywords: drone, identification, estimation, nonlinear, flight test, system, aerodynamic coefficient.

Probability Distribution Extraction from TEC Estimates based on Kernel Density Estimation

NASA Astrophysics Data System (ADS)

Demir, Uygar; Toker, Cenk; Çenet, Duygu

2016-07-01

Statistical analysis of the ionosphere, specifically the Total Electron Content (TEC), may reveal important information about its temporal and spatial characteristics. One of the core metrics that express the statistical properties of a stochastic process is its Probability Density Function (pdf). Furthermore, statistical parameters such as mean, variance and kurtosis, which can be derived from the pdf, may provide information about the spatial uniformity or clustering of the electron content. For example, the variance differentiates between a quiet ionosphere and a disturbed one, whereas kurtosis differentiates between a geomagnetic storm and an earthquake. Therefore, valuable information about the state of the ionosphere (and the natural phenomena that cause the disturbance) can be obtained by looking at the statistical parameters. In the literature, there are publications which try to fit the histogram of TEC estimates to some well-known pdf.s such as Gaussian, Exponential, etc. However, constraining a histogram to fit to a function with a fixed shape will increase estimation error, and all the information extracted from such pdf will continue to contain this error. In such techniques, it is highly likely to observe some artificial characteristics in the estimated pdf which is not present in the original data. In the present study, we use the Kernel Density Estimation (KDE) technique to estimate the pdf of the TEC. KDE is a non-parametric approach which does not impose a specific form on the TEC. As a result, better pdf estimates that almost perfectly fit to the observed TEC values can be obtained as compared to the techniques mentioned above. KDE is particularly good at representing the tail probabilities, and outliers. We also calculate the mean, variance and kurtosis of the measured TEC values. The technique is applied to the ionosphere over Turkey where the TEC values are estimated from the GNSS measurement from the TNPGN-Active (Turkish National Permanent GNSS Network) network. This study is supported by by TUBITAK 115E915 and Joint TUBITAK 114E092 and AS CR14/001 projects.

ELM mitigation techniques

NASA Astrophysics Data System (ADS)

Evans, T. E.

2013-07-01

Large edge-localized mode (ELM) control techniques must be developed to help ensure the success of burning and ignited fusion plasma devices such as tokamaks and stellarators. In full performance ITER tokamak discharges, with QDT = 10, the energy released by a single ELM could reach ˜30 MJ which is expected to result in an energy density of 10-15 MJ/m2on the divertor targets. This will exceed the estimated divertor ablation limit by a factor of 20-30. A worldwide research program is underway to develop various types of ELM control techniques in preparation for ITER H-mode plasma operations. An overview of the ELM control techniques currently being developed is discussed along with the requirements for applying these techniques to plasmas in ITER. Particular emphasis is given to the primary approaches, pellet pacing and resonant magnetic perturbation fields, currently being considered for ITER.

Improved importance sampling technique for efficient simulation of digital communication systems

NASA Technical Reports Server (NTRS)

Lu, Dingqing; Yao, Kung

1988-01-01

A new, improved importance sampling (IIS) approach to simulation is considered. Some basic concepts of IS are introduced, and detailed evolutions of simulation estimation variances for Monte Carlo (MC) and IS simulations are given. The general results obtained from these evolutions are applied to the specific previously known conventional importance sampling (CIS) technique and the new IIS technique. The derivation for a linear system with no signal random memory is considered in some detail. For the CIS technique, the optimum input scaling parameter is found, while for the IIS technique, the optimum translation parameter is found. The results are generalized to a linear system with memory and signals. Specific numerical and simulation results are given which show the advantages of CIS over MC and IIS over CIS for simulations of digital communications systems.

Repurposing video recordings for structure motion estimations

NASA Astrophysics Data System (ADS)

Khaloo, Ali; Lattanzi, David

2016-04-01

Video monitoring of public spaces is becoming increasingly ubiquitous, particularly near essential structures and facilities. During any hazard event that dynamically excites a structure, such as an earthquake or hurricane, proximal video cameras may inadvertently capture the motion time-history of the structure during the event. If this dynamic time-history could be extracted from the repurposed video recording it would become a valuable forensic analysis tool for engineers performing post-disaster structural evaluations. The difficulty is that almost all potential video cameras are not installed to monitor structure motions, leading to camera perspective distortions and other associated challenges. This paper presents a method for extracting structure motions from videos using a combination of computer vision techniques. Images from a video recording are first reprojected into synthetic images that eliminate perspective distortion, using as-built knowledge of a structure for calibration. The motion of the camera itself during an event is also considered. Optical flow, a technique for tracking per-pixel motion, is then applied to these synthetic images to estimate the building motion. The developed method was validated using the experimental records of the NEESHub earthquake database. The results indicate that the technique is capable of estimating structural motions, particularly the frequency content of the response. Further work will evaluate variants and alternatives to the optical flow algorithm, as well as study the impact of video encoding artifacts on motion estimates.

High resolution frequency to time domain transformations applied to the stepped carrier MRIS measurements

NASA Technical Reports Server (NTRS)

Ardalan, Sasan H.

1992-01-01

Two narrow-band radar systems are developed for high resolution target range estimation in inhomogeneous media. They are reformulations of two presently existing systems such that high resolution target range estimates may be achieved despite the use of narrow bandwidth radar pulses. A double sideband suppressed carrier radar technique originally derived in 1962, and later abandoned due to its inability to accurately measure target range in the presence of an interfering reflection, is rederived to incorporate the presence of an interfering reflection. The new derivation shows that the interfering reflection causes a period perturbation in the measured phase response. A high resolution spectral estimation technique is used to extract the period of this perturbation leading to accurate target range estimates independent of the signal-to-interference ratio. A non-linear optimal signal processing algorithm is derived for a frequency-stepped continuous wave radar system. The resolution enhancement offered by optimal signal processing of the data over the conventional Fourier Transform technique is clearly demonstrated using measured radar data. A method for modeling plane wave propagation in inhomogeneous media based on transmission line theory is derived and studied. Several simulation results including measurement of non-uniform electron plasma densities that develop near the heat tiles of a space re-entry vehicle are presented which verify the validity of the model.

A Comparative Study on Preprocessing Techniques in Diabetic Retinopathy Retinal Images: Illumination Correction and Contrast Enhancement

PubMed Central

Rasta, Seyed Hossein; Partovi, Mahsa Eisazadeh; Seyedarabi, Hadi; Javadzadeh, Alireza

2015-01-01

To investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal image quality, a comparative study was carried out. We studied and implemented a few illumination correction and contrast enhancement techniques on color retinal images to find out the best technique for optimum image enhancement. To compare and choose the best illumination correction technique we analyzed the corrected red and green components of color retinal images statistically and visually. The two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivity and specificity. The statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients of variation. The dividing method using the median filter to estimate background illumination showed the lowest Coefficients of variations in the red component. The quotient and homomorphic filtering methods after the dividing method presented good results based on their low Coefficients of variations. The contrast limited adaptive histogram equalization increased the sensitivity of the vessel segmentation algorithm up to 5% in the same amount of accuracy. The contrast limited adaptive histogram equalization technique has a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation. Three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphic filtering were found as the effective illumination correction techniques based on a statistical evaluation. Applying the local contrast enhancement technique, such as CLAHE, for fundus images presented good potentials in enhancing the vasculature segmentation. PMID:25709940

Applying spectral data analysis techniques to aquifer monitoring data in Belvoir Ranch, Wyoming

NASA Astrophysics Data System (ADS)

Gao, F.; He, S.; Zhang, Y.

2017-12-01

This study uses spectral data analysis techniques to estimate the hydraulic parameters from water level fluctuation due to tide effect and barometric effect. All water level data used in this study are collected in Belvoir Ranch, Wyoming. Tide effect can be not only observed in coastal areas, but also in inland confined aquifers. The force caused by changing positions of sun and moon affects not only ocean but also solid earth. The tide effect has an oscillatory pumping or injection sequence to the aquifer, and can be observed from dense water level monitoring. Belvoir Ranch data are collected once per hour, thus is dense enough to capture the tide effect. First, transforming de-trended data from temporal domain to frequency domain with Fourier transform method. Then, the storage coefficient can be estimated using Bredehoeft-Jacob model. After this, analyze the gain function, which expresses the amplification and attenuation of the output signal, and derive barometric efficiency. Next, find effective porosity with storage coefficient and barometric efficiency with Jacob's model. Finally, estimate aquifer transmissivity and hydraulic conductivity using Paul Hsieh's method. The estimated hydraulic parameters are compared with those from traditional pumping data estimation. This study proves that hydraulic parameter can be estimated by only analyze water level data in frequency domain. It has the advantages of low cost and environmental friendly, thus should be considered for future use of hydraulic parameter estimations.

Improving Focal Depth Estimates: Studies of Depth Phase Detection at Regional Distances

NASA Astrophysics Data System (ADS)

Stroujkova, A.; Reiter, D. T.; Shumway, R. H.

2006-12-01

The accurate estimation of the depth of small, regionally recorded events continues to be an important and difficult explosion monitoring research problem. Depth phases (free surface reflections) are the primary tool that seismologists use to constrain the depth of a seismic event. When depth phases from an event are detected, an accurate source depth is easily found by using the delay times of the depth phases relative to the P wave and a velocity profile near the source. Cepstral techniques, including cepstral F-statistics, represent a class of methods designed for the depth-phase detection and identification; however, they offer only a moderate level of success at epicentral distances less than 15°. This is due to complexities in the Pn coda, which can lead to numerous false detections in addition to the true phase detection. Therefore, cepstral methods cannot be used independently to reliably identify depth phases. Other evidence, such as apparent velocities, amplitudes and frequency content, must be used to confirm whether the phase is truly a depth phase. In this study we used a variety of array methods to estimate apparent phase velocities and arrival azimuths, including beam-forming, semblance analysis, MUltiple SIgnal Classification (MUSIC) (e.g., Schmidt, 1979), and cross-correlation (e.g., Cansi, 1995; Tibuleac and Herrin, 1997). To facilitate the processing and comparison of results, we developed a MATLAB-based processing tool, which allows application of all of these techniques (i.e., augmented cepstral processing) in a single environment. The main objective of this research was to combine the results of three focal-depth estimation techniques and their associated standard errors into a statistically valid unified depth estimate. The three techniques include: 1. Direct focal depth estimate from the depth-phase arrival times picked via augmented cepstral processing. 2. Hypocenter location from direct and surface-reflected arrivals observed on sparse networks of regional stations using a Grid-search, Multiple-Event Location method (GMEL; Rodi and Toksöz, 2000; 2001). 3. Surface-wave dispersion inversion for event depth and focal mechanism (Herrmann and Ammon, 2002). To validate our approach and provide quality control for our solutions, we applied the techniques to moderated- sized events (mb between 4.5 and 6.0) with known focal mechanisms. We illustrate the techniques using events observed at regional distances from the KSAR (Wonju, South Korea) teleseismic array and other nearby broadband three-component stations. Our results indicate that the techniques can produce excellent agreement between the various depth estimates. In addition, combining the techniques into a "unified" estimate greatly reduced location errors and improved robustness of the solution, even if results from the individual methods yielded large standard errors.

Comparison of local- to regional-scale estimates of ground-water recharge in Minnesota, USA

USGS Publications Warehouse

Delin, G.N.; Healy, R.W.; Lorenz, D.L.; Nimmo, J.R.

2007-01-01

Regional ground-water recharge estimates for Minnesota were compared to estimates made on the basis of four local- and basin-scale methods. Three local-scale methods (unsaturated-zone water balance, water-table fluctuations (WTF) using three approaches, and age dating of ground water) yielded point estimates of recharge that represent spatial scales from about 1 to about 1000 m2. A fourth method (RORA, a basin-scale analysis of streamflow records using a recession-curve-displacement technique) yielded recharge estimates at a scale of 10–1000s of km2. The RORA basin-scale recharge estimates were regionalized to estimate recharge for the entire State of Minnesota on the basis of a regional regression recharge (RRR) model that also incorporated soil and climate data. Recharge rates estimated by the RRR model compared favorably to the local and basin-scale recharge estimates. RRR estimates at study locations were about 41% less on average than the unsaturated-zone water-balance estimates, ranged from 44% greater to 12% less than estimates that were based on the three WTF approaches, were about 4% less than the age dating of ground-water estimates, and were about 5% greater than the RORA estimates. Of the methods used in this study, the WTF method is the simplest and easiest to apply. Recharge estimates made on the basis of the UZWB method were inconsistent with the results from the other methods. Recharge estimates using the RRR model could be a good source of input for regional ground-water flow models; RRR model results currently are being applied for this purpose in USGS studies elsewhere.

Comparison of Sequential and Variational Data Assimilation

NASA Astrophysics Data System (ADS)

Alvarado Montero, Rodolfo; Schwanenberg, Dirk; Weerts, Albrecht

2017-04-01

Data assimilation is a valuable tool to improve model state estimates by combining measured observations with model simulations. It has recently gained significant attention due to its potential in using remote sensing products to improve operational hydrological forecasts and for reanalysis purposes. This has been supported by the application of sequential techniques such as the Ensemble Kalman Filter which require no additional features within the modeling process, i.e. it can use arbitrary black-box models. Alternatively, variational techniques rely on optimization algorithms to minimize a pre-defined objective function. This function describes the trade-off between the amount of noise introduced into the system and the mismatch between simulated and observed variables. While sequential techniques have been commonly applied to hydrological processes, variational techniques are seldom used. In our believe, this is mainly attributed to the required computation of first order sensitivities by algorithmic differentiation techniques and related model enhancements, but also to lack of comparison between both techniques. We contribute to filling this gap and present the results from the assimilation of streamflow data in two basins located in Germany and Canada. The assimilation introduces noise to precipitation and temperature to produce better initial estimates of an HBV model. The results are computed for a hindcast period and assessed using lead time performance metrics. The study concludes with a discussion of the main features of each technique and their advantages/disadvantages in hydrological applications.

An Innovative Technique to Assess Spontaneous Baroreflex Sensitivity with Short Data Segments: Multiple Trigonometric Regressive Spectral Analysis.

PubMed

Li, Kai; Rüdiger, Heinz; Haase, Rocco; Ziemssen, Tjalf

2018-01-01

Objective: As the multiple trigonometric regressive spectral (MTRS) analysis is extraordinary in its ability to analyze short local data segments down to 12 s, we wanted to evaluate the impact of the data segment settings by applying the technique of MTRS analysis for baroreflex sensitivity (BRS) estimation using a standardized data pool. Methods: Spectral and baroreflex analyses were performed on the EuroBaVar dataset (42 recordings, including lying and standing positions). For this analysis, the technique of MTRS was used. We used different global and local data segment lengths, and chose the global data segments from different positions. Three global data segments of 1 and 2 min and three local data segments of 12, 20, and 30 s were used in MTRS analysis for BRS. Results: All the BRS-values calculated on the three global data segments were highly correlated, both in the supine and standing positions; the different global data segments provided similar BRS estimations. When using different local data segments, all the BRS-values were also highly correlated. However, in the supine position, using short local data segments of 12 s overestimated BRS compared with those using 20 and 30 s. In the standing position, the BRS estimations using different local data segments were comparable. There was no proportional bias for the comparisons between different BRS estimations. Conclusion: We demonstrate that BRS estimation by the MTRS technique is stable when using different global data segments, and MTRS is extraordinary in its ability to evaluate BRS in even short local data segments (20 and 30 s). Because of the non-stationary character of most biosignals, the MTRS technique would be preferable for BRS analysis especially in conditions when only short stationary data segments are available or when dynamic changes of BRS should be monitored.

The applicability of dental wear in age estimation for a modern American population.

PubMed

Faillace, Katie E; Bethard, Jonathan D; Marks, Murray K

2017-12-01

Though applied in bioarchaeology, dental wear is an underexplored age indicator in the biological anthropology of contemporary populations, although research has been conducted on dental attrition in forensic contexts (Kim et al., , Journal of Forensic Sciences, 45, 303; Prince et al., , Journal of Forensic Sciences, 53, 588; Yun et al., , Journal of Forensic Sciences, 52, 678). The purpose of this study is to apply and adapt existing techniques for age estimation based on dental wear to a modern American population, with the aim of producing accurate age range estimates for individuals from an industrialized context. Methodologies following Yun and Prince were applied to a random sample from the University of New Mexico (n = 583) and Universidade de Coimbra (n = 50) cast and skeletal collections. Analysis of variance (ANOVA) and linear regression analyses were conducted to examine the relationship between tooth wear scores and age. Application of both Yun et al. () and Prince et al. () methodologies resulted in inaccurate age estimates. Recalibrated sectioning points correctly classified individuals as over or under 50 years for 88% of the sample. Linear regression demonstrated 60% of age estimates fell within ±10 years of the actual age, and accuracy improved for individuals under 45 years, with 74% of predictions within ±10 years. This study demonstrates age estimation from dental wear is possible for modern populations, with comparable age intervals to other established methods. It provides a quantifiable method of seriation into "older" and "younger" adult categories, and provides more reliable age interval estimates than cranial sutures in instances where only the skull is available. © 2017 Wiley Periodicals, Inc.

Applying Deep Learning in Medical Images: The Case of Bone Age Estimation.

PubMed

Lee, Jang Hyung; Kim, Kwang Gi

2018-01-01

A diagnostic need often arises to estimate bone age from X-ray images of the hand of a subject during the growth period. Together with measured physical height, such information may be used as indicators for the height growth prognosis of the subject. We present a way to apply the deep learning technique to medical image analysis using hand bone age estimation as an example. Age estimation was formulated as a regression problem with hand X-ray images as input and estimated age as output. A set of hand X-ray images was used to form a training set with which a regression model was trained. An image preprocessing procedure is described which reduces image variations across data instances that are unrelated to age-wise variation. The use of Caffe, a deep learning tool is demonstrated. A rather simple deep learning network was adopted and trained for tutorial purpose. A test set distinct from the training set was formed to assess the validity of the approach. The measured mean absolute difference value was 18.9 months, and the concordance correlation coefficient was 0.78. It is shown that the proposed deep learning-based neural network can be used to estimate a subject's age from hand X-ray images, which eliminates the need for tedious atlas look-ups in clinical environments and should improve the time and cost efficiency of the estimation process.

Estimation of shoreline position and change using airborne topographic lidar data

USGS Publications Warehouse

Stockdon, H.F.; Sallenger, A.H.; List, J.H.; Holman, R.A.

2002-01-01

A method has been developed for estimating shoreline position from airborne scanning laser data. This technique allows rapid estimation of objective, GPS-based shoreline positions over hundreds of kilometers of coast, essential for the assessment of large-scale coastal behavior. Shoreline position, defined as the cross-shore position of a vertical shoreline datum, is found by fitting a function to cross-shore profiles of laser altimetry data located in a vertical range around the datum and then evaluating the function at the specified datum. Error bars on horizontal position are directly calculated as the 95% confidence interval on the mean value based on the Student's t distribution of the errors of the regression. The technique was tested using lidar data collected with NASA's Airborne Topographic Mapper (ATM) in September 1997 on the Outer Banks of North Carolina. Estimated lidar-based shoreline position was compared to shoreline position as measured by a ground-based GPS vehicle survey system. The two methods agreed closely with a root mean square difference of 2.9 m. The mean 95% confidence interval for shoreline position was ?? 1.4 m. The technique has been applied to a study of shoreline change on Assateague Island, Maryland/Virginia, where three ATM data sets were used to assess the statistics of large-scale shoreline change caused by a major 'northeaster' winter storm. The accuracy of both the lidar system and the technique described provides measures of shoreline position and change that are ideal for studying storm-scale variability over large spatial scales.

Evaluation of control laws and actuator locations for control systems applicable to deformable astronomical telescope mirrors

NASA Technical Reports Server (NTRS)

Ostroff, A. J.

1973-01-01

Some of the major difficulties associated with large orbiting astronomical telescopes are the cost of manufacturing the primary mirror to precise tolerances and the maintaining of diffraction-limited tolerances while in orbit. One successfully demonstrated approach for minimizing these problem areas is the technique of actively deforming the primary mirror by applying discrete forces to the rear of the mirror. A modal control technique, as applied to active optics, has previously been developed and analyzed. The modal control technique represents the plant to be controlled in terms of its eigenvalues and eigenfunctions which are estimated via numerical approximation techniques. The report includes an extension of previous work using the modal control technique and also describes an optimal feedback controller. The equations for both control laws are developed in state-space differential form and include such considerations as stability, controllability, and observability. These equations are general and allow the incorporation of various mode-analyzer designs; two design approaches are presented. The report also includes a technique for placing actuator and sensor locations at points on the mirror based upon the flexibility matrix of the uncontrolled or unobserved modes of the structure. The locations selected by this technique are used in the computer runs which are described. The results are based upon three different initial error distributions, two mode-analyzer designs, and both the modal and optimal control laws.

Application of AI techniques to infer vegetation characteristics from directional reflectance(s)

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Smith, J. A.; Harrison, P. A.; Harrison, P. R.

1994-01-01

Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.

Head-mounted active noise control system with virtual sensing technique

NASA Astrophysics Data System (ADS)

Miyazaki, Nobuhiro; Kajikawa, Yoshinobu

2015-03-01

In this paper, we apply a virtual sensing technique to a head-mounted active noise control (ANC) system we have already proposed. The proposed ANC system can reduce narrowband noise while improving the noise reduction ability at the desired locations. A head-mounted ANC system based on an adaptive feedback structure can reduce noise with periodicity or narrowband components. However, since quiet zones are formed only at the locations of error microphones, an adequate noise reduction cannot be achieved at the locations where error microphones cannot be placed such as near the eardrums. A solution to this problem is to apply a virtual sensing technique. A virtual sensing ANC system can achieve higher noise reduction at the desired locations by measuring the system models from physical sensors to virtual sensors, which will be used in the online operation of the virtual sensing ANC algorithm. Hence, we attempt to achieve the maximum noise reduction near the eardrums by applying the virtual sensing technique to the head-mounted ANC system. However, it is impossible to place the microphone near the eardrums. Therefore, the system models from physical sensors to virtual sensors are estimated using the Head And Torso Simulator (HATS) instead of human ears. Some simulation, experimental, and subjective assessment results demonstrate that the head-mounted ANC system with virtual sensing is superior to that without virtual sensing in terms of the noise reduction ability at the desired locations.

Earth science research

NASA Technical Reports Server (NTRS)

Botkin, Daniel B.

1987-01-01

The analysis of ground-truth data from the boreal forest plots in the Superior National Forest, Minnesota, was completed. Development of statistical methods was completed for dimension analysis (equations to estimate the biomass of trees from measurements of diameter and height). The dimension-analysis equations were applied to the data obtained from ground-truth plots, to estimate the biomass. Classification and analyses of remote sensing images of the Superior National Forest were done as a test of the technique to determine forest biomass and ecological state by remote sensing. Data was archived on diskette and tape and transferred to UCSB to be used in subsequent research.

A Method for Determining Pseudo-measurement State Values for Topology Observability of State Estimation in Power Systems

NASA Astrophysics Data System (ADS)

Urano, Shoichi; Mori, Hiroyuki

This paper proposes a new technique for determining of state values in power systems. Recently, it is useful for carrying out state estimation with data of PMU (Phasor Measurement Unit). The authors have developed a method for determining state values with artificial neural network (ANN) considering topology observability in power systems. ANN has advantage to approximate nonlinear functions with high precision. The method evaluates pseudo-measurement state values of the data which are lost in power systems. The method is successfully applied to the IEEE 14-bus system.

Rare event computation in deterministic chaotic systems using genealogical particle analysis

NASA Astrophysics Data System (ADS)

Wouters, J.; Bouchet, F.

2016-09-01

In this paper we address the use of rare event computation techniques to estimate small over-threshold probabilities of observables in deterministic dynamical systems. We demonstrate that genealogical particle analysis algorithms can be successfully applied to a toy model of atmospheric dynamics, the Lorenz ’96 model. We furthermore use the Ornstein-Uhlenbeck system to illustrate a number of implementation issues. We also show how a time-dependent objective function based on the fluctuation path to a high threshold can greatly improve the performance of the estimator compared to a fixed-in-time objective function.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Proposed standard-weight equations for brook trout

USGS Publications Warehouse

Hyatt, M.W.; Hubert, W.A.

2001-01-01

Weight and length data were obtained for 113 populations of brook trout Salvelinus fontinalis across the species' geographic range in North America to estimate a standard-weight (Ws) equation for this species. Estimation was done by applying the regression-line-percentile technique to fish of 120-620 mm total length (TL). The proposed metric-unit (g and mm) equation is log10Ws = -5.186 + 3.103 log10TL; the English-unit (lb and in) equivalent is log10Ws = -3.483 + 3.103 log10TL. No systematic length bias was evident in the relative-weight values calculated from these equations.

Ag electrode modified with polyhexamethylene biguanide stabilized silver nanoparticles: a new type of SERS substrates for detection of enzymatically generated thiocholine

NASA Astrophysics Data System (ADS)

Tepanov, A. A.; Nechaeva, N. L.; Prokopkina, T. A.; Kudrinskiy, A. A.; Kurochkin, I. N.; Lisichkin, G. V.

2015-11-01

The detection of thiocholine is one of the most widespread techniques for estimation of the cholinesterase activity - acetylcholinesterase and butyrylcholinesterase. Both cholinesterases can be inhibited by organophosphates and carbamates and accordingly can be considered for estimation of these pollutants in the environment. In the current work, SERS spectroscopy was applied for the thiocholine detection. The Ag electrodes modified with silver nanoparticles stabilized by polyhexamethylene biguanide were for the first time suggested as SERS-substrates for that purpose. Such electrodes can be applicable for SERS detection of submicromolar concentrations of thiocholine.

Annual report for 2004 wild horse research and field activities

USGS Publications Warehouse

Ransom, Jason; Singer, Francis J.; Zeigenfuss, Linda; Coates-Markle, Linda

2005-01-01

The Bureau of Land Management (BLM) and U.S. Geological Survey-Biological Resources Discipline (USGS/BRD) continued wild horse research in 2004, investigating the strategic research elements of fertility control and population estimation. Fertility control research was focused on the individual-based porcine zonae pellucid (PZP) field trials at the Pryor Mountain Wild Horse Range (WHR), Little Rock Cliffs WHR, and McCullough Peaks Wild Horse Management Area (WHMA). Aerial population estimation research was conducted on a number of western wild horse herds to test different survey techniques as applied to various habitat types and population sizes.

Enhancing PTFs with remotely sensed data for multi-scale soil water retention estimation

NASA Astrophysics Data System (ADS)

Jana, Raghavendra B.; Mohanty, Binayak P.

2011-03-01

SummaryUse of remotely sensed data products in the earth science and water resources fields is growing due to increasingly easy availability of the data. Traditionally, pedotransfer functions (PTFs) employed for soil hydraulic parameter estimation from other easily available data have used basic soil texture and structure information as inputs. Inclusion of surrogate/supplementary data such as topography and vegetation information has shown some improvement in the PTF's ability to estimate more accurate soil hydraulic parameters. Artificial neural networks (ANNs) are a popular tool for PTF development, and are usually applied across matching spatial scales of inputs and outputs. However, different hydrologic, hydro-climatic, and contaminant transport models require input data at different scales, all of which may not be easily available from existing databases. In such a scenario, it becomes necessary to scale the soil hydraulic parameter values estimated by PTFs to suit the model requirements. Also, uncertainties in the predictions need to be quantified to enable users to gauge the suitability of a particular dataset in their applications. Bayesian Neural Networks (BNNs) inherently provide uncertainty estimates for their outputs due to their utilization of Markov Chain Monte Carlo (MCMC) techniques. In this paper, we present a PTF methodology to estimate soil water retention characteristics built on a Bayesian framework for training of neural networks and utilizing several in situ and remotely sensed datasets jointly. The BNN is also applied across spatial scales to provide fine scale outputs when trained with coarse scale data. Our training data inputs include ground/remotely sensed soil texture, bulk density, elevation, and Leaf Area Index (LAI) at 1 km resolutions, while similar properties measured at a point scale are used as fine scale inputs. The methodology was tested at two different hydro-climatic regions. We also tested the effect of varying the support scale of the training data for the BNNs by sequentially aggregating finer resolution training data to coarser resolutions, and the applicability of the technique to upscaling problems. The BNN outputs are corrected for bias using a non-linear CDF-matching technique. Final results show good promise of the suitability of this Bayesian Neural Network approach for soil hydraulic parameter estimation across spatial scales using ground-, air-, or space-based remotely sensed geophysical parameters. Inclusion of remotely sensed data such as elevation and LAI in addition to in situ soil physical properties improved the estimation capabilities of the BNN-based PTF in certain conditions.

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Transcranial phase aberration correction using beam simulations and MR-ARFI

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

Vyas, Urvi, E-mail: urvi.vyas@gmail.com; Kaye, Elena; Pauly, Kim Butts

2014-03-15

Purpose: Transcranial magnetic resonance-guided focused ultrasound surgery is a noninvasive technique for causing selective tissue necrosis. Variations in density, thickness, and shape of the skull cause aberrations in the location and shape of the focal zone. In this paper, the authors propose a hybrid simulation-MR-ARFI technique to achieve aberration correction for transcranial MR-guided focused ultrasound surgery. The technique uses ultrasound beam propagation simulations with MR Acoustic Radiation Force Imaging (MR-ARFI) to correct skull-caused phase aberrations. Methods: Skull-based numerical aberrations were obtained from a MR-guided focused ultrasound patient treatment and were added to all elements of the InSightec conformal bone focusedmore » ultrasound surgery transducer during transmission. In the first experiment, the 1024 aberrations derived from a human skull were condensed into 16 aberrations by averaging over the transducer area of 64 elements. In the second experiment, all 1024 aberrations were applied to the transducer. The aberrated MR-ARFI images were used in the hybrid simulation-MR-ARFI technique to find 16 estimated aberrations. These estimated aberrations were subtracted from the original aberrations to result in the corrected images. Each aberration experiment (16-aberration and 1024-aberration) was repeated three times. Results: The corrected MR-ARFI image was compared to the aberrated image and the ideal image (image with zero aberrations) for each experiment. The hybrid simulation-MR-ARFI technique resulted in an average increase in focal MR-ARFI phase of 44% for the 16-aberration case and 52% for the 1024-aberration case, and recovered 83% and 39% of the ideal MR-ARFI phase for the 16-aberrations and 1024-aberration case, respectively. Conclusions: Using one MR-ARFI image and noa priori information about the applied phase aberrations, the hybrid simulation-MR-ARFI technique improved the maximum MR-ARFI phase of the beam's focus.« less

A frame selective dynamic programming approach for noise robust pitch estimation.

PubMed

Yarra, Chiranjeevi; Deshmukh, Om D; Ghosh, Prasanta Kumar

2018-04-01

The principles of the existing pitch estimation techniques are often different and complementary in nature. In this work, a frame selective dynamic programming (FSDP) method is proposed which exploits the complementary characteristics of two existing methods, namely, sub-harmonic to harmonic ratio (SHR) and sawtooth-wave inspired pitch estimator (SWIPE). Using variants of SHR and SWIPE, the proposed FSDP method classifies all the voiced frames into two classes-the first class consists of the frames where a confidence score maximization criterion is used for pitch estimation, while for the second class, a dynamic programming (DP) based approach is proposed. Experiments are performed on speech signals separately from KEELE, CSLU, and PaulBaghsaw corpora under clean and additive white Gaussian noise at 20, 10, 5, and 0 dB SNR conditions using four baseline schemes including SHR, SWIPE, and two DP based techniques. The pitch estimation performance of FSDP, when averaged over all SNRs, is found to be better than those of the baseline schemes suggesting the benefit of applying smoothness constraint using DP in selected frames in the proposed FSDP scheme. The VuV classification error from FSDP is also found to be lower than that from all four baseline schemes in almost all SNR conditions on three corpora.

Republic of Georgia estimates for prevalence of drug use: Randomized response techniques suggest under-estimation.

PubMed

Kirtadze, Irma; Otiashvili, David; Tabatadze, Mzia; Vardanashvili, Irina; Sturua, Lela; Zabransky, Tomas; Anthony, James C

2018-06-01

Validity of responses in surveys is an important research concern, especially in emerging market economies where surveys in the general population are a novelty, and the level of social control is traditionally higher. The Randomized Response Technique (RRT) can be used as a check on response validity when the study aim is to estimate population prevalence of drug experiences and other socially sensitive and/or illegal behaviors. To apply RRT and to study potential under-reporting of drug use in a nation-scale, population-based general population survey of alcohol and other drug use. For this first-ever household survey on addictive substances for the Country of Georgia, we used the multi-stage probability sampling of 18-to-64-year-old household residents of 111 urban and 49 rural areas. During the interviewer-administered assessments, RRT involved pairing of sensitive and non-sensitive questions about drug experiences. Based upon the standard household self-report survey estimate, an estimated 17.3% [95% confidence interval, CI: 15.5%, 19.1%] of Georgian household residents have tried cannabis. The corresponding RRT estimate was 29.9% [95% CI: 24.9%, 34.9%]. The RRT estimates for other drugs such as heroin also were larger than the standard self-report estimates. We remain unsure about what is the "true" value for prevalence of using illegal psychotropic drugs in the Republic of Georgia study population. Our RRT results suggest that standard non-RRT approaches might produce 'under-estimates' or at best, highly conservative, lower-end estimates. Copyright © 2018 Elsevier B.V. All rights reserved.

Frequency-domain beamformers using conjugate gradient techniques for speech enhancement.

PubMed

Zhao, Shengkui; Jones, Douglas L; Khoo, Suiyang; Man, Zhihong

2014-09-01

A multiple-iteration constrained conjugate gradient (MICCG) algorithm and a single-iteration constrained conjugate gradient (SICCG) algorithm are proposed to realize the widely used frequency-domain minimum-variance-distortionless-response (MVDR) beamformers and the resulting algorithms are applied to speech enhancement. The algorithms are derived based on the Lagrange method and the conjugate gradient techniques. The implementations of the algorithms avoid any form of explicit or implicit autocorrelation matrix inversion. Theoretical analysis establishes formal convergence of the algorithms. Specifically, the MICCG algorithm is developed based on a block adaptation approach and it generates a finite sequence of estimates that converge to the MVDR solution. For limited data records, the estimates of the MICCG algorithm are better than the conventional estimators and equivalent to the auxiliary vector algorithms. The SICCG algorithm is developed based on a continuous adaptation approach with a sample-by-sample updating procedure and the estimates asymptotically converge to the MVDR solution. An illustrative example using synthetic data from a uniform linear array is studied and an evaluation on real data recorded by an acoustic vector sensor array is demonstrated. Performance of the MICCG algorithm and the SICCG algorithm are compared with the state-of-the-art approaches.

Correlation Techniques as Applied to Pose Estimation in Space Station Docking

NASA Technical Reports Server (NTRS)

Rollins, J. Michael; Juday, Richard D.; Monroe, Stanley E., Jr.

2002-01-01

The telerobotic assembly of space-station components has become the method of choice for the International Space Station (ISS) because it offers a safe alternative to the more hazardous option of space walks. The disadvantage of telerobotic assembly is that it does not provide for direct arbitrary views of mating interfaces for the teleoperator. Unless cameras are present very close to the interface positions, such views must be generated graphically, based on calculated pose relationships derived from images. To assist in this photogrammetric pose estimation, circular targets, or spots, of high contrast have been affixed on each connecting module at carefully surveyed positions. The appearance of a subset of spots essentially must form a constellation of specific relative positions in the incoming digital image stream in order for the docking to proceed. Spot positions are expressed in terms of their apparent centroids in an image. The precision of centroid estimation is required to be as fine as 1I20th pixel, in some cases. This paper presents an approach to spot centroid estimation using cross correlation between spot images and synthetic spot models of precise centration. Techniques for obtaining sub-pixel accuracy and for shadow, obscuration and lighting irregularity compensation are discussed.

Observation of sea-ice dynamics using synthetic aperture radar images: Automated analysis

NASA Technical Reports Server (NTRS)

Vesecky, John F.; Samadani, Ramin; Smith, Martha P.; Daida, Jason M.; Bracewell, Ronald N.

1988-01-01

The European Space Agency's ERS-1 satellite, as well as others planned to follow, is expected to carry synthetic-aperture radars (SARs) over the polar regions beginning in 1989. A key component in utilization of these SAR data is an automated scheme for extracting the sea-ice velocity field from a time sequence of SAR images of the same geographical region. Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion.

Measurement of the Dynamic Shear Modulus of Mouse Brain Tissue In Vivo By Magnetic Resonance Elastography

PubMed Central

Atay, Stefan M.; Kroenke, Christopher D.; Sabet, Arash; Bayly, Philip V.

2008-01-01

In this study, the magnetic resonance elastography (MRE) technique was used to estimate the dynamic shear modulus of mouse brain tissue in vivo. The technique allows visualization and measurement of mechanical shear waves excited by lateral vibration of the skull. Quantitative measurements of displacement in three dimensions (3-D) during vibration at 1200 Hz were obtained by applying oscillatory magnetic field gradients at the same frequency during an MR imaging sequence. Contrast in the resulting phase images of the mouse brain is proportional to displacement. To obtain estimates of shear modulus, measured displacement fields were fitted to the shear wave equation. Validation of the procedure was performed on gel characterized by independent rheometry tests and on data from finite element simulations. Brain tissue is, in reality, viscoelastic and nonlinear. The current estimates of dynamic shear modulus are strictly relevant only to small oscillations at a specific frequency, but these estimates may be obtained at high frequencies (and thus high deformation rates), non-invasively throughout the brain. These data complement measurements of nonlinear viscoelastic properties obtained by others at slower rates, either ex vivo or invasively. PMID:18412500