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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Orientation processing mechanisms revealed by the plaid tilt illusion

The tilt after-effect (TAE) and tilt illusion (TI) have revealed a great deal about the nature of orientation coding of 1-dimensional (1D) lines and gratings. Comparatively little research however has addressed the mechanisms responsible for encoding the orientation of 2-dimensional (2D) plaid stimuli. A multi-stage model of edge detection has recently been proposed [Georgeson, M. A. (1998) Image & Vision Computing, 16(6-7), 389-405] to account for the perceived structure of a plaid stimulus that incorporates extraction of the zero-crossings (ZCs) of the plaid. Data is presented showing that the ZCs of a plaid inducing stimulus can interact with vertical grating test stimulus to induce a standard tilt illusion. However, by considering the second-order structure of a plaid rather than ZCs, it was shown that the perceived orientation of the vertical test grating results from the combination of orientation illusions due to the first- and second-order components of an inducing plaid. The data suggest that the mechanisms encoding the orientation of second-order contours are similar to, and interact directly with, those that encode first-order contours.

Orientation/physiology↗
NASA NTRS1992

Design of neural networks for classification of remotely sensed imagery

Classification accuracies of a backpropagation neural network are discussed and compared with a maximum likelihood classifier (MLC) with multivariate normal class models. We have found that, because of its nonparametric nature, the neural network outperforms the MLC in this area. In addition, we discuss techniques for constructing optimal neural nets on parallel hardware like the MasPar MP-1 currently at GSFC. Other important discussions are centered around training and classification times of the two methods, and sensitivity to the training data. Finally, we discuss future work in the area of classification and neural nets.

Chettri, Samir R.↗
NASA NTRS1975

The saturated activities of Na-22, Mn-54, and Co-56 and the depth of sampling of soils

A multivariate linear regression study shows that the saturated activities of Na-22, Co-56, and Mn-54 are functions of the chemical composition and the reciprocal of the cube root of the sample weight. A procedure for taking the temporal variation in these short-lived radionuclides into account is described. The regression results are used to estimate the average depths of sampling of soil material. The data indicate that all 28 samples were in the same conditions of exposure when recovered as they had been for the last approximately 10 years. The saturation activity of Mn-54 is a very weak function of time.

Keith, J. E.↗
NASA NTRS2019

Measurement of CH3D on Titan at Submillimeter Wavelengths

We present the first radio/submillimeter detection of monodeuterated methane (CH3D) in Titan's atmosphere, using archival data from of the Atacama Large Millimeter/submillimeter Array (ALMA). The J (sub K) equals 2 (sub 1) minus 1 (sub 1) and J (sub K) equals 2 (sub 0) minus 1 (sub 0) transitions at 465.235 and 465.250 gigahertz (approximately 0.644 millimeters) were measured at significance levels of 4.6 sigma and 5.7 sigma, respectively. These two lines were modeled using the Non-linear optimal Estimator for MultivariatE spectral analySIS (NEMESIS) radiative transfer code to determine the disk-averaged CH3D volume mixing ratio equals 6.157 times 10 (sup minus 6) in Titan's stratosphere (at altitudes greater than 130 kilometers). By comparison with the CH4 vertical abundance profile measured by Cassini-Huygens mass spectrometry, the resulting value for D/H in CH4 is (1.033 plus or minus 0.081) times 10 (sup minus 4). This is consistent with previous ground-based and in situ measurements from the Cassini-Huygens mission, though slightly lower than the average of the previous values. Additional CH3D observations at higher spatial resolution will be required to determine a value truly comparable with the Cassini-Huygens CH4 measurements, by measuring CH3D with ALMA close to Titan's equator. In the post-Cassini era, spatially resolved observations of CH3D with ALMA will enable the latitudinal distribution of methane to be determined, making this an important molecule for further studies.

Thelen, Alexander E.↗
NASA NTRS1979

Multivariate approximation methods and applications to geophysics and geodesy

The first report in a series is presented which is intended to be written by the author with the purpose of treating a class of approximation methods of functions in one and several variables and ways of applying them to geophysics and geodesy. The first report is divided in three parts and is devoted to the presentation of the mathematical theory and formulas. Various optimal ways of representing functions in one and several variables and the associated error when information is had about the function such as satellite data of different kinds are discussed. The framework chosen is Hilbert spaces. Experiments were performed on satellite altimeter data and on satellite to satellite tracking data.

Munteanu, M. J.↗
NASA NTRS1995

A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control

This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.

Garg, Sanjay↗
NASA NTRS2015

Assessing Wetland Hydroperiod and Soil Moisture With Remote Sensing: A Demonstration for the NASA Plum Brook Station Year 2

Primary Goal: Assist with the evaluation and measuring of wetlands hydroperiod at the PlumBrook Station using multi-source remote sensing data as part of a larger effort on projecting climate change-related impacts on the station's wetland ecosystems. MTRI expanded on the multi-source remote sensing capabilities to help estimate and measure hydroperiod and the relative soil moisture of wetlands at NASA's Plum Brook Station. Multi-source remote sensing capabilities are useful in estimating and measuring hydroperiod and relative soil moisture of wetlands. This is important as a changing regional climate has several potential risks for wetland ecosystem function. The year two analysis built on the first year of the project by acquiring and analyzing remote sensing data for additional dates and types of imagery, combined with focused field work. Five deliverables were planned and completed: 1) Show the relative length of hydroperiod using available remote sensing datasets 2) Date linked table of wetlands extent over time for all feasible non-forested wetlands 3) Utilize LIDAR data to measure topographic height above sea level of all wetlands, wetland to catchment area radio, slope of wetlands, and other useful variables 4) A demonstration of how analyzed results from multiple remote sensing data sources can help with wetlands vulnerability assessment 5) A MTRI style report summarizing year 2 results. This report serves as a descriptive summary of our completion of these our deliverables. Additionally, two formal meetings were held with Larry Liou and Amanda Sprinzl to provide project updates and receive direction on outputs. These were held on 2/26/15 and 9/17/15 at the Plum Brook Station. Principal Component Analysis (PCA) is a multivariate statistical technique used to identify dominant spatial and temporal backscatter signatures. PCA reduces the information contained in the temporal dataset to the first few new Principal Component (PC) images. Some advantages of PCA include the ability to filter out temporal autocorrelation and reduce speckle to the higher order PC images. A PCA was performed using ERDAS Imagine on a time series of PALSAR dates. Hydroperiod maps were created by separating the PALSAR dates into two date ranges, 2006-2008 and 2010, and performing an unsupervised classification on the PCAs.

Brooks, Colin↗
NASA NTRS1995

A diagnostic analysis of the VVP single-doppler retrieval technique

A diagnostic analysis of the VVP (volume velocity processing) retrieval method is presented, with emphasis on understanding the technique as a linear, multivariate regression. Similarities and differences to the velocity-azimuth display and extended velocity-azimuth display retrieval techniques are discussed, using this framework. Conventional regression diagnostics are then employed to quantitatively determine situations in which the VVP technique is likely to fail. An algorithm for preparation and analysis of a robust VVP retrieval is developed and applied to synthetic and actual datasets with high temporal and spatial resolution. A fundamental (but quantifiable) limitation to some forms of VVP analysis is inadequate sampling dispersion in the n space of the multivariate regression, manifest as a collinearity between the basis functions of some fitted parameters. Such collinearity may be present either in the definition of these basis functions or in their realization in a given sampling configuration. This nonorthogonality may cause numerical instability, variance inflation (decrease in robustness), and increased sensitivity to bias from neglected wind components. It is shown that these effects prevent the application of VVP to small azimuthal sectors of data. The behavior of the VVP regression is further diagnosed over a wide range of sampling constraints, and reasonable sector limits are established.

Boccippio, Dennis J.↗
NASA NTRS2014

Interannual Variation in Phytoplankton Class-Specific Primary Production at a Global Scale

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of 4 phytoplankton groups to the total primary production. First we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms were the group that contributed the most to the total phytoplankton production (50, the equivalent of 20 PgC y-1. Coccolithophores and chlorophytes each contributed to 20 (7 PgC y-1 of the total primary production and cyanobacteria represented about 10 (4 PgC y(sub-1) of the total primary production. Primary production by diatoms was highest in high latitude (45) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4 (1-2 PgC y-1. We assessed the effects of climate variability on the class-specific primary production using global (i.e. Multivariate El Nio Index, MEI) and regional climate indices (e.g. Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p 0.05) between the MEI and the class-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatomscyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on the class-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Chl-a↗
NASA NTRS1992

The European Southern Observatory-MIDAS table file system

The new and substantially upgraded version of the Table File System in MIDAS is presented as a scientific database system. MIDAS applications for performing database operations on tables are discussed, for instance, the exchange of the data to and from the TFS, the selection of objects, the uncertainty joins across tables, and the graphical representation of data. This upgraded version of the TFS is a full implementation of the binary table extension of the FITS format; in addition, it also supports arrays of strings. Different storage strategies for optimal access of very large data sets are implemented and are addressed in detail. As a simple relational database, the TFS may be used for the management of personal data files. This opens the way to intelligent pipeline processing of large amounts of data. One of the key features of the Table File System is to provide also an extensive set of tools for the analysis of the final results of a reduction process. Column operations using standard and special mathematical functions as well as statistical distributions can be carried out; commands for linear regression and model fitting using nonlinear least square methods and user-defined functions are available. Finally, statistical tests of hypothesis and multivariate methods can also operate on tables.

Peron, M.↗
NASA NTRS2013

Interannual Variation in Phytoplankton Primary Production at a Global Scale

We used the NASA Ocean Biogeochemical Model (NOBM) combined with remote sensing data via assimilation to evaluate the contribution of four phytoplankton groups to the total primary production. First, we assessed the contribution of each phytoplankton groups to the total primary production at a global scale for the period 1998-2011. Globally, diatoms contributed the most to the total phytoplankton production ((is)approximately 50%, the equivalent of 20 PgC·y1). Coccolithophores and chlorophytes each contributed approximately 20% ((is) approximately 7 PgC·y1) of the total primary production and cyanobacteria represented about 10% ((is) approximately 4 PgC·y1) of the total primary production. Primary production by diatoms was highest in the high latitudes ((is) greater than 40 deg) and in major upwelling systems (Equatorial Pacific and Benguela system). We then assessed interannual variability of this group-specific primary production over the period 1998-2011. Globally the annual relative contribution of each phytoplankton groups to the total primary production varied by maximum 4% (1-2 PgC·y1). We assessed the effects of climate variability on group-specific primary production using global (i.e., Multivariate El Niño Index, MEI) and "regional" climate indices (e.g., Southern Annular Mode (SAM), Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO)). Most interannual variability occurred in the Equatorial Pacific and was associated with climate variability as indicated by significant correlation (p (is) less than 0.05) between the MEI and the group-specific primary production from all groups except coccolithophores. In the Atlantic, climate variability as indicated by NAO was significantly correlated to the primary production of 2 out of the 4 groups in the North Central Atlantic (diatoms/cyanobacteria) and in the North Atlantic (chlorophytes and coccolithophores). We found that climate variability as indicated by SAM had only a limited effect on group-specific primary production in the Southern Ocean. These results provide a modeling and data assimilation perspective to phytoplankton partitioning of primary production and contribute to our understanding of the dynamics of the carbon cycle in the oceans at a global scale.

Coccolithophores↗
NASA NTRS1990

Distributed memory approaches for robotic neural controllers

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Jorgensen, Charles C.↗
NASA NTRS1999

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

Tripp, John S.↗
NASA NTRS1995

An approach to the development of numerical algorithms for first order linear hyperbolic systems in multiple space dimensions: The constant coefficient case

Two methods for developing high order single step explicit algorithms on symmetric stencils with data on only one time level are presented. Examples are given for the convection and linearized Euler equations with up to the eighth order accuracy in both space and time in one space dimension, and up to the sixth in two space dimensions. The method of characteristics is generalized to nondiagonalizable hyperbolic systems by using exact local polynominal solutions of the system, and the resulting exact propagator methods automatically incorporate the correct multidimensional wave propagation dynamics. Multivariate Taylor or Cauchy-Kowaleskaya expansions are also used to develop algorithms. Both of these methods can be applied to obtain algorithms of arbitrarily high order for hyperbolic systems in multiple space dimensions. Cross derivatives are included in the local approximations used to develop the algorithms in this paper in order to obtain high order accuracy, and improved isotropy and stability. Efficiency in meeting global error bounds is an important criterion for evaluating algorithms, and the higher order algorithms are shown to be up to several orders of magnitude more efficient even though they are more complex. Stable high order boundary conditions for the linearized Euler equations are developed in one space dimension, and demonstrated in two space dimensions.

Goodrich, John W.↗
NASA NTRS2017

Principal Modes of Precipitation Variability from Preliminary Series of IMERG Data

The Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission, IMERG, is the unified U.S. algorithm that provides merged Microwave Infrared (IR) satellite precipitation product for the U.S. GPM team. Even though IMERG record is still very short, 2014-2016, it is tempting to test if it captures ENSO and NAO signals as compared to the popular, still on-going, TRMM Multi-satellite Precipitation Analysis, TMPA. El Nino Southern Oscillation (ENSO) is the most significant mode of interannual variability of tropical ocean atmosphere. North Atlantic Oscillation (NAO) impact is on monthly scales and is mostly an atmospheric mode in the North Atlantic. There exist well-defined, multivariate, indexes that represent ENSO and NAO conditions and phase.

climate variability↗
NASA NTRS2013

Influence of El Nino Southern Oscillation on the Mesospheric Temperature

Using the middle atmosphere temperature data set observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) satellite experiment between 2002 and 2012, and temperatures simulated by the Whole Atmospheric Community Climate Model version 3.5 (WACCM3.5) between 1953 and 2005, we studied the influence of El Niño-Southern Oscillation (ENSO) on middle atmosphere temperature during the Northern Hemisphere (NH) wintertime. For the first time, a significant winter temperature response to ENSO in the middle mesosphere has been observed, with an anomalous warming of approximately 1.0 K/MEI (Multivariate ENSO Index) in the tropics and an anomalous cooling of approximately 2.0 K/MEI in the NH middle latitudes. The observed temperature responses to ENSO in the mesosphere are opposite to those in the stratosphere, in agreement with previous modeling studies. Temperature responses to ENSO observed by SABER show similar patterns to those simulated by the WACCM3.5 model. Analysis of the WACCM3.5 residual mean meridional circulation response to ENSO reveals a significant downwelling in the tropical mesosphere and upwelling in the NH middle and high latitudes during warm ENSO events, which is mostly driven by anomalous eastward gravity wave forcing in the NH mesosphere.

Li, Tao↗
NASA NTRSDate not supplied

Comparison of Prediction Modeling Methodologies for Aeroacoustic Characterization of Hovering sUAS Rotors

This work compared artificial neural network and multivariate orthogonal function modeling methodologies for the prediction and characterization of isolated hovering sUAS rotor aerodynamics and aeroacoustics. Design of Experiments was used to create input feature spaces over 9 input features: the number of rotor blades, rotor size, rotor speed, the amount of blade twist, blade taper ratio, tip chord length, collective pitch, airfoil camber, and airfoil thickness. CAMRAD~II and AARON were executed at the points defined by the input feature space to predict aerodynamic and aeroacoustic quantities. These predicted aerodynamic and aeroacoustic data were then used to generate artificial neural networks and polynomial response surface models. The two prediction model methodologies were evaluated over test data previously unseen by the models, which showed good prediction capabilities for both model types, with slightly lower prediction error for the artificial neural networks. A characterization study was performed, which showed that input features correspondent to the spanwise sectional blade lift and drag were the most significant factors to the aerodynamic thrust and power, respectively. It was also shown that the aeroacoustic quantities were highly dependent on variations in rotor speed and size, which affect the Doppler factor for tonal noise and the spanwise Reynolds number for broadband noise.

Christopher S Thurman↗
NASA NTRS1993

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance.

Iyer, Ravishankar, K.↗