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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

Visual signal detection in structured backgrounds. II. Effects of contrast gain control, background variations, and white noise

Studies of visual detection of a signal superimposed on one of two identical backgrounds show performance degradation when the background has high contrast and is similar in spatial frequency and/or orientation to the signal. To account for this finding, models include a contrast gain control mechanism that pools activity across spatial frequency, orientation and space to inhibit (divisively) the response of the receptor sensitive to the signal. In tasks in which the observer has to detect a known signal added to one of M different backgrounds grounds due to added visual noise, the main sources of degradation are the stochastic noise in the image and the suboptimal visual processing. We investigate how these two sources of degradation (contrast gain control and variations in the background) interact in a task in which the signal is embedded in one of M locations in a complex spatially varying background (structured background). We use backgrounds extracted from patient digital medical images. To isolate effects of the fixed deterministic background (the contrast gain control) from the effects of the background variations, we conduct detection experiments with three different background conditions: (1) uniform background, (2) a repeated sample of structured background, and (3) different samples of structured background. Results show that human visual detection degrades from the uniform background condition to the repeated background condition and degrades even further in the different backgrounds condition. These results suggest that both the contrast gain control mechanism and the background random variations degrade human performance in detection of a signal in a complex, spatially varying background. A filter model and added white noise are used to generate estimates of sampling efficiencies, an equivalent internal noise, an equivalent contrast-gain-control-induced noise, and an equivalent noise due to the variations in the structured background.

NASA Discipline Space Human Factors↗
NASA NTRS1997

In-Flight Flow Visualization Using Infrared Thermography

The feasibility of remote infrared thermography of aircraft surfaces during flight to visualize the extent of laminar flow on a target aircraft has been examined. In general, it was determined that such thermograms can be taken successfully using an existing airplane/thermography system (NASA Dryden's F-18 with infrared imaging pod) and that the transition pattern and, thus, the extent of laminar flow can be extracted from these thermograms. Depending on the in-flight distance between the F-18 and the target aircraft, the thermograms can have a spatial resolution of as little as 0.1 inches. The field of view provided by the present remote system is superior to that of prior stationary infrared thermography systems mounted in the fuselage or vertical tail of a subject aircraft. An additional advantage of the present experimental technique is that the target aircraft requires no or minimal modifications. An image processing procedure was developed which improves the signal-to-noise ratio of the thermograms. Problems encountered during the analog recording of the thermograms (banding of video images) made it impossible to evaluate the adequacy of the present imaging system and image processing procedure to detect transition on untreated metal surfaces. The high reflectance, high thermal difussivity, and low emittance of metal surfaces tend to degrade the images to an extent that it is very difficult to extract transition information from them. The application of a thin (0.005 inches) self-adhesive insulating film to the surface is shown to solve this problem satisfactorily. In addition to the problem of infrared based transition detection on untreated metal surfaces, future flight tests will also concentrate on the visualization of other flow phenomena such as flow separation and reattachment.

vanDam, C. P.↗
NASA NTRS2006

Embedded Sensors for Measuring Surface Regression

The development and evaluation of new hybrid and solid rocket motors requires accurate characterization of the propellant surface regression as a function of key operational parameters. These characteristics establish the propellant flow rate and are prime design drivers affecting the propulsion system geometry, size, and overall performance. There is a similar need for the development of advanced ablative materials, and the use of conventional ablatives exposed to new operational environments. The Miniature Surface Regression Sensor (MSRS) was developed to serve these applications. It is designed to be cast or embedded in the material of interest and regresses along with it. During this process, the resistance of the sensor is related to its instantaneous length, allowing the real-time thickness of the host material to be established. The time derivative of this data reveals the instantaneous surface regression rate. The MSRS could also be adapted to perform similar measurements for a variety of other host materials when it is desired to monitor thicknesses and/or regression rate for purposes of safety, operational control, or research. For example, the sensor could be used to monitor the thicknesses of brake linings or racecar tires and indicate when they need to be replaced. At the time of this reporting, over 200 of these sensors have been installed into a variety of host materials. An MSRS can be made in either of two configurations, denoted ladder and continuous (see Figure 1). A ladder MSRS includes two highly electrically conductive legs, across which narrow strips of electrically resistive material are placed at small increments of length. These strips resemble the rungs of a ladder and are electrically equivalent to many tiny resistors connected in parallel. A substrate material provides structural support for the legs and rungs. The instantaneous sensor resistance is read by an external signal conditioner via wires attached to the conductive legs on the non-eroding end of the sensor. The sensor signal can be transmitted from inside a high-pressure chamber to the ambient environment, using commercially available feedthrough connectors. Miniaturized internal recorders or wireless data transmission could also potentially be employed to eliminate the need for producing penetrations in the chamber case. The rungs are designed so that as each successive rung is eroded away, the resistance changes by an amount that yields a readily measurable signal larger than the background noise. (In addition, signal-conditioning techniques are used in processing the resistance readings to mitigate the effect of noise.) Hence, each discrete change of resistance serves to indicate the arrival of the regressing host material front at the known depth of the affected resistor rung. The average rate of regression between two adjacent resistors can be calculated simply as the distance between the resistors divided by the time interval between their resistance jumps. Advanced data reduction techniques have also been developed to establish the instantaneous surface position and regression rate when the regressing front is between rungs.

Gramer, Daniel J.↗
DOE OSTI2022

Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk

We present damped harmonic oscillator (DHO) light-curve modeling for a sample of 12,714 spectroscopically confirmed quasars in the Sloan Digital Sky Survey Stripe 82 region. DHO is a second-order continuous-time autoregressive moving-average process, which can be fully described using four independent parameters: a natural oscillation frequency (ω 0 ), a damping ratio (ξ), a characteristic perturbation timescale (τ perturb ), and an amplitude for the perturbing white noise (σ ϵ ). The asymptotic variability amplitude of a DHO process is quantified by σ DHO —a function of ω 0 , ξ, τ perturb , and σ ϵ . We find that both τ perturb and σ ϵ follow different dependencies with rest-frame wavelength (λ RF ) on either side of 2500 Å, whereas σ DHO follows a single power-law relation with λ RF . After correcting for wavelength dependence, σ DHO exhibits anticorrelations with both the Eddington ratio and the black hole mass, while τ perturb —with a typical value of days in the rest frame—shows an anticorrelation with the bolometric luminosity. Modeling active galactic nuclei (AGN) variability as a DHO offers more insight into the workings of accretion disks close to the supermassive black holes at the center of AGN. The newly discovered short-term variability (characterized by τ perturb and σ ϵ ) and its correlation with bolometric luminosity pave the way for new algorithms that will derive fundamental properties (e.g., Eddington ratio) of AGN using photometric data alone.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2014

Acoustic Data Processing and Transient Signal Analysis for the Hybrid Wing Body 14- by 22-Foot Subsonic Wind Tunnel Test

An advanced vehicle concept, the HWB N2A-EXTE aircraft design, was tested in NASA Langley's 14- by 22-Foot Subsonic Wind Tunnel to study its acoustic characteristics for var- ious propulsion system installation and airframe con gurations. A signi cant upgrade to existing data processing systems was implemented, with a focus on portability and a re- duction in turnaround time. These requirements were met by updating codes originally written for a cluster environment and transferring them to a local workstation while en- abling GPU computing. Post-test, additional processing of the time series was required to remove transient hydrodynamic gusts from some of the microphone time series. A novel automated procedure was developed to analyze and reject contaminated blocks of data, under the assumption that the desired acoustic signal of interest was a band-limited sta- tionary random process, and of lower variance than the hydrodynamic contamination. The procedure is shown to successfully identify and remove contaminated blocks of data and retain the desired acoustic signal. Additional corrections to the data, mainly background subtraction, shear layer refraction calculations, atmospheric attenuation and microphone directivity corrections, were all necessary for initial analysis and noise assessments. These were implemented for the post-processing of spectral data, and are shown to behave as expected.

Bahr, Christopher J.↗
NASA NTRS2008

Symmetric Phase-Only Filtering in Particle-Image Velocimetry

Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.

Wemet, Mark P.↗
DOE OSTI2020

Three-dimensional super line-localization in low signal-to-noise microscope images via prior-apprised unsupervised learning (PAUL)

Biological processes such as processive enzyme turnover and intracellular cargo tracking involve the dynamic motion of a small "article" along a curvilinear biopolymer track. To understand these processes that occur across multiple length and time scales, one must acquire both the trajectory of the particle and the position of the track along which it moves, possibly by combining high-resolution single-particle tracking with conventional microscopy. Yet, usually there is a significant resolution mismatch between these modalities: while the tracked particle is localized with a precision of 10 nm, the image of the surroundings is limited by optical difraction, with 200 nm lateral and 500 nm axial resolutions. Compared to the particle's trajectory, the surrounding curvilinear structure appears as a blurred and noisy image. This disparity in the spatial resolutions of the particle trajectory and the surrounding curvilinear structure image makes data reconstruction, as well as interpretation, particularly challenging. Analysis is further complicated when the curvilinear structures are oriented arbitrarily in 3D space. Here, we present a prior-apprised unsupervised learning (PAUL) approach to extract information from 3D images where the underlying features resemble a curved line such as a filament or microtubule. This three-stage framework starts with a Hessian-based feature enhancement, which is followed by feature registration, where local line segments are detected on repetitively sampled subimage tiles. In the final stage, statistical learning, segments are clustered based on their geometric relationships. Principal curves are then approximated from each segment group via statistical tools including principal component analysis, bootstrap and kernel transformation. This procedure is characterized on simulated images, where sub-voxel medium deviations from true curves have been achieved. The 3D PAUL approach has also been implemented for successful line localization in experimental 3D images of gold nanowires obtained using a multifocal microscope. Lastly, this work not only bridges the resolution gap between two microscopy modalities, but also allows us to conduct 3D super line-localization imaging experiments, without using super-resolution techniques.

42 ENGINEERING↗
DOE OSTI2020

Cryogenic C-band wavelength division multiplexing system using an AIM Photonics Foundry process design kit

Cryogenic environments make superconducting computing possible by reducing thermal noise, electrical resistance and heat dissipation. Heat generated by the electronics and thermal conductivity of electrical transmission lines to the outside world constitute two main sources of thermal load in such systems. As a result, higher data rates require additional transmission lines which come at an increasingly higher cooling power cost. Hybrid or monolithic integration of silicon photonics with the electronics can be the key to higher data rates and lower power costs in these systems. We present a 4-channel wavelength division multiplexing photonic integrated circuit (PIC) built from modulators in the AIM Photonics process development kit (PDK) that operate at 25 Gbps at room temperature and 10 Gbps at 40 K. We further demonstrate 2-channel operation for 20 Gbps aggregate data rate at 40 K using two different modulators/wavelengths, with the potential for higher aggregate bit rates by utilizing additional channels.

42 ENGINEERING↗
DOE OSTI2020

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This paper describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1978

Theory on data processing and instrumentation

A selection of NASA Earth observations programs are reviewed, emphasizing hardware capabilities. Sampling theory, noise and detection considerations, and image evaluation are discussed for remote sensor imagery. Vision and perception are considered, leading to numerical image processing. The use of multispectral scanners and of multispectral data processing systems, including digital image processing, is depicted. Multispectral sensing and analysis in application with land use and geographical data systems are also covered.

Billingsley, F. C.↗
DOE OSTI2022

Assessment methods for determining small changes in hearing performance over time

Although the behavioral pure-tone threshold audiogram is considered the gold standard for quantifying hearing loss, assessment of speech understanding, especially in noise, is more relevant to quality of life but is only partly related to the audiogram. Metrics of speech understanding in noise are therefore an attractive target for assessing hearing over time. However, speech-in-noise assessments have more potential sources of variability than pure-tone threshold measures, making it a challenge to obtain results reliable enough to detect small changes in performance. Here, this review examines the benefits and limitations of speech-understanding metrics and their application to longitudinal hearing assessment, and identifies potential sources of variability, including learning effects, differences in item difficulty, and between- and within-individual variations in effort and motivation. We conclude by recommending the integration of non-speech auditory tests, which provide information about aspects of auditory health that have reduced variability and fewer central influences than speech tests, in parallel with the traditional audiogram and speech-based assessments.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Signal Processing Based Method for Real-Time Anomaly Detection in High-Performance Computing

Performance anomalies can manifest as irregular execution times or abnormal execution events for many reasons, including network congestion and resource contention. Detecting such anomalies in real-time by analyzing the details of performance traces at scale is impractical due to the sheer volume of data High-Performance Computing (HPC) applications produce. In this paper, we propose formulating HPC performance anomaly detection as a signal-processing problem where anomalies can be treated as noise. We evaluate our proposed method in comparison with two other commonly used anomaly detection techniques of varying complexity based on their detection accuracy and scalability. Since real-time in-situ anomaly detection at a large scale requires lightweight methods that can handle a large volume of streaming data, we find that our proposed method provides the best trade-off. We then implement the proposed method in Chimbuko, the first online, distributed, and scalable workflow-level performance trace analysis framework. We compare our proposed signal-based anomaly detection algorithm with two other methods using a function of their accuracy, F1 score, and detection overhead. Our experiments demonstrate that our proposed approach achieves a 99% improvement for the benchmark datasets and a 93% improvement with Chimbuko traces.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1973

The Apollo 17 Lunar Sounder

The Apollo Lunar Sounder Experiment, a coherent radar operated from lunar orbit during the Apollo 17 mission, has scientific objectives of mapping lunar subsurface structure, surface profiling, surface imaging, and galactic noise measurement. Representative results from each of the four disciplines are presented. Subsurface reflections have been interpreted in both optically and digitally processed data. Images and profiles yield detailed selenomorphological information. The preliminary galactic noise results are consistent with earlier measurements by other workers.

Phillips, R. J.↗
NASA NTRS1994

Thunderstorm Hypothesis Reasoner

THOR is a knowledge-based system which incorporates techniques from signal processing, pattern recognition, and artificial intelligence (AI) in order to determine the boundary of small thunderstorms which develop and dissipate over the area encompassed by KSC and the Cape Canaveral Air Force Station. THOR interprets electric field mill data (derived from a network of electric field mills) by using heuristics and algorithms about thunderstorms that have been obtained from several domain specialists. THOR generates two forms of output: contour plots which visually describe the electric field activity over the network and a verbal interpretation of the activity. THOR uses signal processing and pattern recognition to detect signatures associated with noise or thunderstorm behavior in a near real time fashion from over 31 electrical field mills. THOR's AI component generates hypotheses identifying areas which are under a threat from storm activity, such as lightning. THOR runs on a VAX/VMS at the Kennedy Space Center. Its software is a coupling of C and FORTRAN programs, several signal processing packages, and an expert system development shell.

Mulvehill, Alice M.↗
NASA NTRS2003

Adaptive Suppression of Noise in Voice Communications

A subsystem for the adaptive suppression of noise in a voice communication system effects a high level of reduction of noise that enters the system through microphones. The subsystem includes a digital signal processor (DSP) plus circuitry that implements voice-recognition and spectral- manipulation techniques. The development of the adaptive noise-suppression subsystem was prompted by the following considerations: During processing of the space shuttle at Kennedy Space Center, voice communications among test team members have been significantly impaired in several instances because some test participants have had to communicate from locations with high ambient noise levels. Ear protection for the personnel involved is commercially available and is used in such situations. However, commercially available noise-canceling microphones do not provide sufficient reduction of noise that enters through microphones and thus becomes transmitted on outbound communication links.

Kozel, David↗
NASA NTRS2013

Integrated High-Speed Torque Control System for a Robotic Joint

A control system for achieving high-speed torque for a joint of a robot includes a printed circuit board assembly (PCBA) having a collocated joint processor and high-speed communication bus. The PCBA may also include a power inverter module (PIM) and local sensor conditioning electronics (SCE) for processing sensor data from one or more motor position sensors. Torque control of a motor of the joint is provided via the PCBA as a high-speed torque loop. Each joint processor may be embedded within or collocated with the robotic joint being controlled. Collocation of the joint processor, PIM, and high-speed bus may increase noise immunity of the control system, and the localized processing of sensor data from the joint motor at the joint level may minimize bus cabling to and from each control node. The joint processor may include a field programmable gate array (FPGA).

Davis, Donald R.↗
DOE OSTI2020

A 30‐GHz low‐power CMOS LNA for 5G communication systems

Abstract This paper presents theoretical analysis and design procedures for low noise amplifiers (LNAs) in advanced CMOS technologies. For demonstration, a 30‐GHz LNA designed for 5G millimeter‐wave communication systems was fabricated in a 65‐nm CMOS process. It provides a power gain of 22.6 dB with a noise figure of 3.2 dB while drawing 7.3 mW from a 1.2 V supply.

Liu, Jiye↗