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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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

DHARMA - Discriminant hyperplane abstracting residuals minimization algorithm for separating clusters with fuzzy boundaries

Learning of discriminant hyperplanes in imperfectly supervised or unsupervised training sample sets with unreliably labeled samples along the fuzzy joint boundaries between sample clusters is discussed, with the discriminant hyperplane designed to be a least-squares fit to the unreliably labeled data points. (Samples along the fuzzy boundary jump back and forth from one cluster to the other in recursive cluster stabilization and are considered unreliably labeled.) Minimization of the distances of these unreliably labeled samples from the hyperplanes does not sacrifice the ability to discriminate between classes represented by reliably labeled subsets of samples. An equivalent unconstrained linear inequality problem is formulated and algorithms for its solution are indicated. Landsat earth sensing data were used in confirming the validity and computational feasibility of the approach, which should be useful in deriving discriminant hyperplanes separating clusters with fuzzy boundaries, given supervised training sample sets with unreliably labeled boundary samples.

Dasarathy, B. V.↗
NASA NTRS1977

Feature discrimination and detection probability in synthetic aperture radar imaging system

Images obtained using synthetic aperture radar (SAR) systems can only represent the intensities of resolution cells in the scene of interest probabilistically since radar receiver noise and Rayleigh scattering of the transmitted radiation are always present. Consequently, when features to be identified differ only by their contribution to the mean power of the radar return, discrimination can be treated by detection theory. In this paper, we develop a 'sufficient statistic' for discriminating between competing features and compare it with some suboptimal methods frequently used. Discrimination is measured by probability of detection error and depends on number of samples or 'looks', signal-to-noise ratio (SNR), and ratio of mean power returns from the competing features. Our results show discrimination and image quality rapidly saturate with SNR (very small improvement for SNR not less than 10 dB) but continue to improve with increasing number of looks.

Lipes, R. G.↗
NASA NTRS1980

Role of the middle ear muscle apparatus in mechanisms of speech signal discrimination

A method of impedance reflexometry was used to examine 101 students with hearing impairment in order to clarify the interrelation between speech discrimination and the state of the middle ear muscles. Ability to discriminate speech signals depends to some extent on the functional state of intraaural muscles. Speech discrimination was greatly impaired in the absence of stapedial muscle acoustic reflex, in the presence of low thresholds of stimulation and in very small values of reflex amplitude increase. Discrimination was not impeded in positive AR, high values of relative thresholds and normal increase of reflex amplitude in response to speech signals with augmenting intensity.

Moroz, B. S.↗
NASA NTRS1981

Mass discrimination during weightlessness

An experiment concerned with the ability of astronauts to discriminate between the mass of objects when both the objects and the astronauts are in weightless states is described. The main object of the experiment is to compare the threshold for weight-discrimination on Earth with that for mass-discrimination in orbit. Tests will be conducted premission and postmission and early and late during the mission while the crew is experiencing weightlessness. A comparison of early and late tests inflight and postflight will reveal the rate of adaptation to zero-gravity and 1-g. The mass discrimination box holds 24 balls which the astronaut will compare to one another in a random routine.

Ross, H.↗
NASA NTRS1985

Color measurement and discrimination

Theories of color measurement attempt to provide a quantative means for predicting whether two lights will be discriminable to an average observer. All color measurement theories can be characterized as follows: suppose lights a and b evoke responses from three color channels characterized as vectors, v(a) and v(b); the vector difference v(a) - v(b) corresponds to a set of channel responses that would be generated by some real light, call it *. According to theory a and b will be discriminable when * is detectable. A detailed development and test of the classic color measurement approach are reported. In the absence of a luminance component in the test stimuli, a and b, the theory holds well. In the presence of a luminance component, the theory is clearly false. When a luminance component is present discrimination judgements depend largely on whether the lights being discriminated fall in separate, categorical regions of color space. The results suggest that sensory estimation of surface color uses different methods, and the choice of method depends upon properties of the image. When there is significant luminance variation a categorical method is used, while in the absence of significant luminance variation judgments are continuous and consistant with the measurement approach.

Wandell, B. A.↗
NASA NTRS1997

Spatial layout affects speed discrimination

We address a surprising result in a previous study of speed discrimination with multiple moving gratings: discrimination thresholds decreased when the number of stimuli was increased, but remained unchanged when the area of a single stimulus was increased [Verghese & Stone (1995). Vision Research, 35, 2811-2823]. In this study, we manipulated the spatial- and phase relationship between multiple grating patches to determine their effect on speed discrimination thresholds. In a fusion experiment, we merged multiple stimulus patches, in stages, into a single patch. Thresholds increased as the patches were brought closer and their phase relationship was adjusted to be consistent with a single patch. Thresholds increased further still as these patches were fused into a single patch. In a fission experiment, we divided a single large patch into multiple patches by superimposing a cross with luminance equal to that of the background. Thresholds decreased as the large patch was divided into quadrants and decreased further as the quadrants were maximally separated. However, when the cross luminance was darker than the background, it was perceived as an occluder and thresholds, on average, were unchanged from that for the single large patch. A control experiment shows that the observed trend in discrimination thresholds is not due to the differences in perceived speed of the stimuli. These results suggest that the parsing of the visual image into entities affects the combination of speed information across space, and that each discrete entity effectively provides a single independent estimate of speed.

NASA Discipline Neuroscience↗
NASA NTRS2013

Discriminating Phytoplankton Functional Types (PFTs) in the Coastal Ocean Using the Inversion Algorithm Phydotax and Airborne Imaging Spectrometer Data

There is a need in the Biological Oceanography community to discriminate among phytoplankton groups within the bulk chlorophyll pool to understand energy flow through ecosystems, to track the fate of carbon in the ocean, and to detect and monitor-for harmful algal blooms (HABs). The ocean color community has responded to this demand with the development of phytoplankton functional type (PFT) discrimination algorithms. These PFT algorithms fall into one of three categories depending on the science application: size-based, biogeochemical function, and taxonomy. The new PFT algorithm Phytoplankton Detection with Optics (PHYDOTax) is an inversion algorithm that discriminates taxon-specific biomass to differentiate among six taxa found in the California Current System: diatoms, dinoflagellates, haptophytes, chlorophytes, cryptophytes, and cyanophytes. PHYDOTax was developed and validated in Monterey Bay, CA for the high resolution imaging spectrometer, Spectroscopic Aerial Mapping System with On-board Navigation (SAMSON - 3.5 nm resolution). PHYDOTax exploits the high spectral resolution of an imaging spectrometer and the improved spatial resolution that airborne data provides for coastal areas. The objective of this study was to apply PHYDOTax to a relatively lower resolution imaging spectrometer to test the algorithm's sensitivity to atmospheric correction, to evaluate capability with other sensors, and to determine if down-sampling spectral resolution would degrade its ability to discriminate among phytoplankton taxa. This study is a part of the larger Hyperspectral Infrared Imager (HyspIRI) airborne simulation campaign which is collecting Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery aboard NASA's ER-2 aircraft during three seasons in each of two years over terrestrial and marine targets in California. Our aquatic component seeks to develop and test algorithms to retrieve water quality properties (e.g. HABs and river plumes) in both marine and in-land water bodies. Results presented are from the 10 April 2013 overflight of the Monterey Bay region and focus primarily on the first objective - sensitivity to atmospheric correction. On-going and future work will continue to evaluate if PHYDOTax can be applied to historical (SeaWiFS and MERIS), existing (MODIS, VIIRS, and HICO), and future (PACE, GEO-CAPE, and HyspIRI) satellite sensors. Demonstration of cross-platform continuity may aid in calibration and validation efforts of these sensors.

Biological Oceanography↗
NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗
DOE OSTI2026

Pushing the Limits of Pulse Shape Discrimination in a Large Liquid Xenon Detector

The LUX-ZEPLIN (LZ) experiment is a direct-detection dark matter experiment, optimized to search for weakly interacting massive particles (WIMPs) through WIMP-nucleon interactions. The main challenge in dark matter detection is differentiating between WIMP signals and background events. In LZ, the ratio of ionization to scintillation signals (charge-to-light) is the primary method for rejecting electronic recoil (ER) background. Pulse shape discrimination (PSD) offers a method for additional ER backgrounds rejection in liquid xenon detectors. In this paper, the discrimination power of PSD with the LZ experiment is discussed. To precisely characterize the scintillation pulse shape, an analysis framework is developed to reconstruct the detection time of individual photons. Using LZ calibration data, the photon-timing prompt fraction discriminator is optimized and achieves ER leakage as low as $15\%$. For specific background processes such as $^{124}$Xe double electron capture, the leakage is reduced further to about $5\%$. PSD is combined with charge-to-light to form two-factor discrimination (TFD). The optimized TFD performance is compared with the performance of the charge-to-light method, with the corresponding false positive rate reduced by up to a factor of two for large scintillation pulses. Finally, PSD and TFD are applied to data from LZ's WS2024 run and their performance is summarized.

Akerib, D. S. [SLAC; KIPAC, Menlo Park]↗
DOE OSTI2026

ML–Enabled FPGA Framework for Fast Quantum State Discrimination in Mid-Circuit Measurement Regimes

Accurate and low-latency quantum state discrimination is essential for protocols involving mid-circuit measurement (MCM) and conditional feed-forward. In superconducting quantum systems, conventional readout pipelines transfer measurement data to host processors for post-processing, introducing millisecond-scale delays that far exceed qubit coherence times. To overcome this bottleneck, we present an in-situ machine learning (ML) inference engine implemented on an FPGA for real-time quantum state discrimination. Our design performs inference directly on digitized readout signals with 40 ns latency, supports both qubit and qutrit readout, and enables conditional operations without host-side intervention. This capability is critical for MCM and for feedback-driven protocols such as quantum error correction. We validate the system on superconducting transmon hardware, demonstrating robust discrimination fidelity across multiple qubit and qutrit channels. We further demonstrate conditional qutrit logic driven by FPGA-resident classification, highlighting the potential of low-latency ML-on-FPGA control for NISQ applications and scalable fault-tolerant quantum computing.

Vora, Neel [Lawrence Berkeley National Laboratory ↗
DOE OSTI2025

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗
NASA NTRS1970

Wide-range pulse-height discriminator

Improved pulse amplitude discriminator has discriminator level in millivolt range, permits simple adjustment over wide range, and is stable within one percent at temperatures between minus 20 degrees and plus 60 degrees C. The discriminator responds to narrow pulses /500 nsec/, draws little power /milliwatts/, and requires simple circuitry.

Cancro, C. A.↗
NASA NTRS1972

The elusive tradeoff - Speed vs accuracy in visual discrimination tasks.

Explicit payoffs were used to control pressures for speed and accuracy in experiments seeking tradeoffs for difficult visual discrimination tasks. The experiments involved stimuli on a cathode ray tube display controlled by a PDP-1 computer, with the subjects performing increasingly complex discrimination tasks and their earnings increasing with their performance. Models for discrimination under time pressure are proposed on the basis of the results.

Swensson, R. G.↗
NASA NTRS1974

Iron-absorption band analysis for the discrimination of iron-rich zones

The author has identified the following significant results. Most major rock units and unaltered and altered areas in the study area can be discriminated on the basis of visible and near-infrared spectral reflectivity differences recorded from satellite altitude. These subtle spectral differences are detectable by digital ratioing of the MSS bands and subsequent stretching to increase the contrast to enhance spectral differences. Hydrothermally altered areas appear as anomalous color patches within the volcanic-rock areas. A map has been prepared which can be regarded as an excellent reconnaissance exploration map, for use in targeting areas for more detailed geological, geochemical, and geophysical studies. Mafic and felsic rock types are easily discriminated on the color stretched-ratio composite. The ratioing process minimizes albedo effects, leaving only the recorded characteristic spectral response. The spectra of unaltered rocks appear different from those of altered rocks, which are typically dominated by limonite and clay minerals. It seems clear that differences in spectral shape can provide a basis for discrimination of geologic material, although the relations between visible and near-infrared spectral reflectivity and mineralogical composition are not yet entirely understood.

Rowan, L. C.↗
NASA NTRS1974

An evaluation of multiband photography for rock discrimination

The author has identified the following significant results. With the advent of ERTS and Skylab satellites, multiband imagery and photography have become readily available to geologists. The ability of multiband photography to discriminate sedimentary rocks was examined. More than 8600 in situ measurements of band reflectance of the sedimentary rocks of the Front Range, Colorado, were acquired. Statistical analysis of these measurements showed that: (1) measurements from one site can be used at another site 100 miles away; (2) there is basically only one spectral reflectance curve for these rocks, with constant amplitude differences between the curves; and (3) the natural variation is so large that at least 150 measurements per formation are required to select best filters. These conclusions are supported by subjective tests with aerial multiband photography. The designed multiband photography concept for rock discrimination is not a practical method of improving sedimentary rock discrimination capabilities.

Lee, K.↗
NASA NTRS1982

Mass estimation and discrimination during brief periods of zero gravity

Under zero gravity, the gravitational cues to mass are removed, but the inertial cues remain. A sensation of heaviness is generated if objects are shaken, and hence given a changing acceleration. A magnitude estimation experiment was conducted during the 0-G phase of parabolic flight and on the ground, and the results suggested that objects felt lighter under 0 G than under 1 G. Mass discrimination was also measured in flight, and yielded Weber fractions of .18 under 0 G, .16 under 1.8 G, and .09 under 1 G. Poor performance under microgravity and macrogravity was probably due mainly to lack of time for adaptation to changed G levels. It is predicted that discrimination should improve during the course of prolonged spaceflight, and that there should be an aftereffect of poor discrimination on return to earth.

Ross, H. E.↗
NASA NTRS1982

Linear discriminant analysis with misallocation in training samples

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Chhikara, R.↗
NASA NTRS1984

An evaluation of thematic mapper simulator data for the geobotanical discrimination of rock types in Southwest Oregon

Rock type identification may be assisted by the use of remote sensing of associated vegetation, particularly in areas of dense vegetative cover where surface materials are not imaged directly by the sensor. The geobotanical discrimination of ultramafic parent materials was investigated and analytical techniques for lithologic mapping and mineral exploration were developed. The utility of remotely sensed data to discriminate vegetation types associated with ultramafic parent materials in a study area in southwest Oregon were evaluated. A number of specific objectives were identified, which include: (1) establishment of the association between vegetation and rock types; (2) examination of the spectral separability of vegetation types associated with rock types; (3) determination of the contribution of each TMS band for discriminating vegetation associated with rock types and (4) comparison of analytical techniques for spectrally classifying vegetation.

Weinstock, K. J.↗