Spectral analysis techniques and pattern recognition methods for electroencephalographic data
Spectral analysis techniques and pattern recognition methods for electroencephalographic data
PATTERN RECOGNITION↗
SEARCH · Engineering Papers
Results for “Data analysis methods”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
JSC Safety and Mission Assurance Data Analysis Overview
These slides describe the data analysis methods that are used to determine inputs for probabilistic risk models supporting the Space Shuttle Program. Other applications can follow a similar path probably using different data sources. Statistical approaches are different and not addressed here. Topics included here: 1) Prior Distribution; 2) Likelihood Data; 3) Bayesian Updating; and 4) Uncertainty and Error. Note: This is a high-level discussion and is not intended to be a tutorial.
Roelant, Henk↗
Vegetation and other parameters in the Brevard County bar-built estuaries
It is shown that low-altitude aerial photography, using specific interpretive techniques, can effectively delineate sea-grass beds, oyster beds, and other underwater features. Various techniques were used on several sets of aerial imagery. Imagery was tested using several data analysis methods, ground truth, and biological testing. Approximately 45,000 acres of grass beds, 2,500 acres of oyster beds, and 4,200 acres of dredged canals were mapped. This data represents selected sites only. Areas chosen have the highest quality water in Brevard County and are among the most highly recognized biologically productive waters in Florida.
Down, C.↗
Shadowgraph Study of Gradient Driven Fluctuations
A fluid or fluid mixture, subjected to a vertical temperature and/or concentration gradient in a gravitational field, exhibits greatly enhanced light scattering at small angles. This effect is caused by coupling between the vertical velocity fluctuations due to thermal energy and the vertically varying refractive index. Physically, small upward or downward moving regions will be displaced into fluid having a refractive index different from that of the moving region, thus giving rise to the enhanced scattering. The scattered intensity is predicted to vary with scattering wave vector q, as q(sup -4), for sufficiently large q, but the divergence is quenched by gravity at small q. In the absence of gravity, the long wavelength fluctuations responsible for the enhanced scattering are predicted to grow until limited by the sample dimensions. It is thus of interest to measure the mean-squared amplitude of such fluctuations in the microgravity environment for comparison with existing theory and ground based measurements. The relevant wave vectors are extremely small, making traditional low-angle light scattering difficult or impossible because of stray elastically scattered light generated by optical surfaces. An alternative technique is offered by the shadowgraph method, which is normally used to visualize fluid flows, but which can also serve as a quantitative tool to measure fluctuations. A somewhat novel shadowgraph apparatus and the necessary data analysis methods will be described. The apparatus uses a spatially coherent, but temporally incoherent, light source consisting of a super-luminescent diode coupled to a single-mode optical fiber in order to achieve extremely high spatial resolution, while avoiding effects caused by interference of light reflected from the various optical surfaces that are present when using laser sources. Results obtained for a critical mixture of aniline and cyclohexane subjected to a vertical temperature gradient will be presented. The sample was confined between two horizontal parallel sapphire plates with a vertical spacing of 1 mm. The temperatures of the sapphire plates were controlled by independent circulating water loops that used Peltier devices to add or remove heat from the room air as required. For a mixture with a temperature gradient, two effects are involved in generating the vertical refractive index gradient, namely thermal expansion and the Soret effect, which generates a concentration gradient in response to the applied temperature gradient. For the aniline/cyclohexane system, the denser component (aniline) migrates toward the colder surface. Consequently, when heating from above, both effects result in the sample density decreasing with altitude and are stabilizing in the sense that no convective motion occurs regardless of the magnitude of the applied temperature gradient. The Soret effect is strong near a binary liquid critical point, and thus the dominant effect is due to the induced concentration gradient. The results clearly show the divergence at low q and the predicted gravitational quenching. Results obtained for different applied temperature gradients at varying temperature differences from the critical temperature, clearly demonstrate the predicted divergence of the thermal diffusion ratio. Thus, the more closely the critical point is approached, the smaller becomes the temperature gradient required to generate the same signal. Two different methods have been used to generate pure concentration gradients. In the first, a sample cell was filled with a single fluid, ethylene glycol, and a denser miscible fluid, water, was added from below thus establishing a sharp interface to begin the experiment. As time went on the two fluids diffused into each other, and large amplitude fluctuations were clearly observed at low q. The effects of gravitational quenching were also evident. In the second method, the aniline/cyclohexane sample was used, and after applying a vertical temperature gradient for several hours, the top and bottom temperatures were set equal and the thermal gradient died on a time scale of seconds, leaving the Soret induced concentration gradient in place. Again, large-scale fluctuations were observed and died away slowly in amplitude as diffusion destroyed the initial concentration gradient.
Cannell, David↗
On the Unusually High Temperature of the Cluster of Galaxies 1E 0657-56
A recent X-ray observation of the cluster 1E 0657-56 (z = 0.296) with ASC,4 implied an unusually high temperature of approx. 17 keV. Such a high temperature would make it the hottest known cluster and severely constrain cosmological models since, in a Universe with critical density (Omega = 1) the probability of observing such a cluster is only approx. 4 x 10(exp -5). Here we test the robustness of this observational result since it has such important implications. We analysed the data using a variety of different data analysis methods and spectral analysis assumptions and find a temperature of approx. 11 - 12 keV in all cases, except for one class of spectral fits. These are fits in which the absorbing column density is fixed at the Galactic value. Using simulated data for a 12 keV cluster, we show that a high temperature of approx. 17 keV is artificially obtained if the true spectrum has a stronger low-energy cut-off than that for Galactic absorption only. The apparent extra absorption may be astrophysical in origin, (either intrinsic or line-of-sight), or it may be a problem with the low-energy CCD efficiency. Although significantly lower than previous measurements, this temperature of kT approx. 11 - 12 keV is still relatively high since only a few clusters have been found to have temperatures higher than 10 keV and the data therefore still present some difficulty for an Omega = 1 Universe. Our results will also be useful to anyone who wants to estimate the systematic errors involved in different methods of background subtraction of ASCA data for sources with similar signal-to-noise to that of the IE 0657-56 data reported here.
Yaqoob, Tahir↗
Method of representation of acoustic spectra and reflection corrections applied to externally blown flap noise
A computer method for obtaining a rational function representation of an acoustic spectrum and for correcting reflection effects is introduced. The functional representation provides a means of compact storage of data and the nucleus of the data analysis method. The method is applied to noise from a full-scale externally blown flap system with a quiet 6:1 bypass ratio turbofan engine and a three-flap wing section designed to simulate the take-off condition of a conceptual STOL aircraft.
Miles, J. H.↗
New techniques for experimental generation of two-dimensional blade-vortex interaction at low Reynolds numbers
An experimental investigation of two dimensional blade vortex interaction was held at NASA Langley Research Center. The first phase was a flow visualization study to document the approach process of a two dimensional vortex as it encountered a loaded blade model. To accomplish the flow visualization study, a method for generating two dimensional vortex filaments was required. The numerical study used to define a new vortex generation process and the use of this process in the flow visualization study were documented. Additionally, photographic techniques and data analysis methods used in the flow visualization study are examined.
Booth, E., Jr.↗
Quantitative radiography for determining density fluctuations in HED experiments
We have developed a method to extract density fluctuation measurements from x-ray radiographs of high-energy density (HED) instability growth and turbulence experiments. We use this information to calculate density fluctuation statistics for constraining the performance of turbulent mix models in HED systems. The density calculation combines image filtering, removal of systemic effects such as backlighter variation, calculation of transmission across multiple materials, and use of tracer materials to generate an approximate single-material density field. From the density map, we calculate both average density and a variance-like moment b (density-specific-volume covariance), which we compare to our models. We infer both quantities from a single image, which is significantly more information than the historic single scalar mix width measurements. We also develop a method of analyzing simulation outputs that incorporate both the density fluctuation metric from a turbulence model and the bulk material maps from the hydrodynamic code. This analysis helps address the question of how to initialize the simulations for best comparison to data from systems with large separations of scale in the mixing perturbation initial condition. We find that our data analysis method yields 1D average density and b curves with similar morphology and amplitudes as those from preliminary simulation comparisons.
47 OTHER INSTRUMENTATION↗
The Alpha Particle X-Ray Spectrometer (APXS): Results from Gusev Crater and Calibration Report
The chemical composition of rocks and soils on Mars analyzed during the Mars Exploration Rover Spirit Mission was determined by X-ray analyses with the Alpha Particle X-Ray Spectrometer (APXS). Details of the data analysis method and the instrument calibration are presented. Measurements performed on Mars to address geometry effects and background contributions are shown. Cross calibration measurements among several instrument sensors and sources are discussed. An unintentional swap of the two flight instruments is evaluated. New concentration data acquired during the first 470 sols of rover Spirit in Gusev Crater are presented. There are two geological regions, the Gusev plains and the Columbia Hills. The plains contain soils that are very similar to previous landing sites on Mars. A meteoritic component in the soil is identified. Rocks in the plains revealed thin weathering rinds. The underlying abraded rock was classified as primitive basalt. One of these rocks contained significant Br that is probably associated with vein-filling material of different composition. One of the trenches showed large subsurface enrichments of Mg, S, and Br. Disturbed soils and rocks in the Columbia Hills revealed different elemental compositions. These rocks are significantly weathered and enriched in mobile elements, such as P, S, Cl, or Br. Even abraded rock surfaces have high Br concentrations. Thus, in contrast to the rocks and soils in the Gusev Plains, the Columbia Hills material shows more significant evidence of ancient aqueous alteration.
Gellert, R.↗
Spectral Analysis Techniques and Pattern Recognition Methods for Electroencephalographic Data
Spectral analysis techniques and pattern recognition methods for automatic processing of electroencephalographic data
PATTERN RECOGNITION↗
The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods
Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.
Canfield, Richard C.↗
On the geodetic applications of simultaneous range differences to Lageos
While the majority of the currently deployed satellite laser systems are of centimeter level precision, the accuracy of the geodetic products corresponds to the accuracy in which geodesists are interested. On several occasions, the best models are either not good enough or result in tedious computations which are required to achieve accuracies comparable to those of the observations. A possible alternative is related to the development of a new method of data analysis. This method involves the minimization of the effect of the systematic errors and, in particular, the minimization of errors arising from an incorrectly modeled orbit. The present paper provides a summary of the results of a study of this option, taking into account laser ranging data from Lageos.
Pavlis, E. C.↗
Earth Radiation Budget Research at the NASA Langley Research Center
In the 1970s research studies concentrating on satellite measurements of Earth's radiation budget started at the NASA Langley Research Center. Since that beginning, considerable effort has been devoted to developing measurement techniques, data analysis methods, and time-space sampling strategies to meet the radiation budget science requirements for climate studies. Implementation and success of the Earth Radiation Budget Experiment (ERBE) and the Clouds and the Earth's Radiant Energy System (CERES) was due to the remarkable teamwork of many engineers, scientists, and data analysts. Data from ERBE have provided a new understanding of the effects of clouds, aerosols, and El Nino/La Nina oscillation on the Earth's radiation. CERES spacecraft instruments have extended the time coverage with high quality climate data records for over a decade. Using ERBE and CERES measurements these teams have created information about radiation at the top of the atmosphere, at the surface, and throughout the atmosphere for a better understanding of our climate. They have also generated surface radiation products for designers of solar power plants and buildings and numerous other applications
Smith, G. Louis↗
A method for data base management and analysis for wind tunnel data
To respond to the need for improved data base management and analysis capabilities for wind-tunnel data at the Langley 16-Foot Transonic Tunnel, research was conducted into current methods of managing wind-tunnel data and a method was developed as a solution to this need. This paper describes the development of the data base management and analysis method for wind-tunnel data. The design and implementation of the software system are discussed and examples of its use are shown.
Biser, Aileen O.↗
Scattering Calorimeter FY24 Deliverable Report
A simulation-based method has been developed to prototype new detector designs for nuclear data measurements utilizing neutron scattering. This method uses representative physics inputs for signal and background generation, full detector resolution smearing benchmarked by experimental data, and a neutron beam timing simulation to produce analyzable output like a physical measurement. A test case has been studied using a hybrid time-of-flight calorimeter detector for scattering cross-section measurements on 239 Pu with 1-5 MeV incident monoenergetic neutrons. Data analysis methods have been developed to perform event-level particle reconstruction and reaction channel discrimination. This analysis has been used to estimate the capability of the test detector to perform simultaneous scattering and fission cross section measurements, as well as its ability to provide neutron spectra and particle angular information.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Static calibration for measurement of loads in wind tunnel tests on Shuttle surface tiles
A description is given of the procedures used for the static calibrations of the Coe (1981) sensor array to determine normal force, pitching moment, and rolling moment from the ensemble of sensor outputs. The use of independent data to confirm the validity of the calibration is also described. Two methods are used in calibrating the Coe sensors. In the first, calibration loads and readings are arranged in matrix form and are assumed to be related in a linear fashion. In the second, each Coe sensor reading is regarded as a sum of contributions from each of the calibration loads. It is shown that the Coe load sensors, in conjunction with either of two data analysis methods, can be used to determine the forces and moments experienced by a Shuttle TPS tile.
Rummler, D. R.↗
Hybrid Automated Diagnosis of Discrete/Continuous Systems
A recently conceived method of automated diagnosis of a complex electromechanical system affords a complete set of capabilities for hybrid diagnosis in the case in which the state of the electromechanical system is characterized by both continuous and discrete values (as represented by analog and digital signals, respectively). The method is an integration of two complementary diagnostic systems: (1) beacon-based exception analysis for multi-missions (BEAM), which is primarily useful in the continuous domain and easily performs diagnoses in the presence of transients; and (2) Livingstone, which is primarily useful in the discrete domain and is typically restricted to quasi-steady conditions. BEAM has been described in several prior NASA Tech Briefs articles: "Software for Autonomous Diagnosis of Complex Systems" (NPO-20803), Vol. 26, No. 3 (March 2002), page 33; "Beacon-Based Exception Analysis for Multimissions" (NPO-20827), Vol. 26, No. 9 (September 2002), page 32; "Wavelet-Based Real-Time Diagnosis of Complex Systems" (NPO-20830), Vol. 27, No. 1 (January 2003), page 67; and "Integrated Formulation of Beacon-Based Exception Analysis for Multimissions" (NPO-21126), Vol. 27, No. 3 (March 2003), page 74. Briefly, BEAM is a complete data-analysis method, implemented in software, for real-time or off-line detection and characterization of faults. The basic premise of BEAM is to characterize a system from all available observations and train the characterization with respect to normal phases of operation. The observations are primarily continuous in nature. BEAM isolates anomalies by analyzing the deviations from nominal for each phase of operation. Livingstone is a model-based reasoner that uses a model of a system, controller commands, and sensor observations to track the system s state, and detect and diagnose faults. Livingstone models a system within the discrete domain. Therefore, continuous sensor readings, as well as time, must be discretized. To reason about continuous systems, Livingstone uses monitors that discretize the sensor readings using trending and thresholding techniques. In development of the a hybrid method, BEAM results were sent to Livingstone to serve as an independent source of evidence that is in addition to the evidence gathered by Livingstone standard monitors. The figure depicts the flow of data in an early version of a hybrid system dedicated to diagnosing a simulated electromechanical system. In effect, BEAM served as a "smart" monitor for Livingstone. BEAM read the simulation data, processed the data to form observations, and stored the observations in a file. A monitor stub synchronized the events recorded by BEAM with the output of the Livingstone standard monitors according to time tags. This information was fed to a real-time interface, which buffered and fed the information to Livingstone, and requested diagnoses at the appropriate times. In a test, the hybrid system was found to correctly identify a failed component in an electromechanical system for which neither BEAM nor Livingstone alone yielded the correct diagnosis.
Park, Han↗
Physical Interpretation of Early Battery Life Prediction Models
Early battery life prediction models are most useful for R&D if they help us understand the early changes in battery electrochemical response that correspond with long-term degradation and failure. Linear regression models such as Fused lasso and Partial Least Squares can fit coefficients directly to high-dimensional electrochemical data like capacity-voltage and ΔV–state-of-charge, i.e., Q(V) and ΔV(SOC) curves, learning coefficients that can be physically interpreted. We leverage the ISU-ILCC battery aging data set to learn high-dimensional coefficients for early battery life prediction from traditional slow-rate capacity check data, demonstrating learning on Q(V), d Q· d V −1 , and ΔV(SOC) curves. A thorough study on the dependence of coefficient values on train/test size and data preprocessing methods is made, demonstrating the reliability of high-dimensional regression approaches unless very small amounts of data are used for model training. For this data set, coefficients from Q(V) and d Q· d V −1 models highlight changes in electrode stoichiometry due to lithium loss, while ΔV(SOC) coefficients highlight changes in positive electrode diffusivity due to particle cracking as well as electrode stoichiometry shifts. By directly interpreting the coefficients of a regression model, we make physical insights into battery degradation mechanisms without requiring the assumptions of traditional battery data analysis methods.
25 ENERGY STORAGE↗