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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

Optical alignment of electrodes on electrical discharge machines

Shadowgraph system projects magnified image on screen so that alignment of small electrodes mounted on electrical discharge machines can be corrected and verified. Technique may be adapted to other machine tool equipment where physical contact cannot be made during inspection and access to tool limits conventional runout checking procedures.

Boissevain, A. G.↗
NASA NTRS1974

User oriented ERTS-1 images

Photographic reproduction of ERTS-1 images are capable of displaying only a portion of the total information available from the multispectral scanner. Methods are being developed to generate ERTS-1 images oriented towards special users such as agriculturists, foresters, and hydrologists by applying image enhancement techniques and interactive statistical classification schemes. Spatial boundaries and linear features can be emphasized and delineated using simple filters. Linear and nonlinear transformations can be applied to the spectral data to emphasize certain ground information. An automatic classification scheme was developed to identify particular ground cover classes such as fallow, grain, rape seed or various vegetation covers. The scheme applies the maximum likelihood decision rule to the spectral information and classifies the ERTS-1 image on a pixel by pixel basis. Preliminary results indicate that the classifier has limited success in distinguishing crops, but is well adapted for identifying different types of vegetation.

Shlien, S.↗
NASA NTRS1974

On the development of an interactive resource information management system for analysis and display of spatiotemporal data

The recent availability of timely synoptic earth imagery from the Earth Resources Technology Satellites (ERTS) provides a wealth of information for the monitoring and management of vital natural resources. Formal language definitions and syntax interpretation algorithms were adapted to provide a flexible, computer information system for the maintenance of resource interpretation of imagery. These techniques are incorporated, together with image analysis functions, into an Interactive Resource Information Management and Analysis System, IRIMAS, which is implemented on a Texas Instruments 980A minicomputer system augmented with a dynamic color display for image presentation. A demonstration of system usage and recommendations for further system development are also included.

Schell, J. A.↗
NASA NTRS1975

Perception of linear horizontal self-motion induced by peripheral vision /linearvection/ - Basic characteristics and visual-vestibular interactions

The basic characteristics of the sensation of linear horizontal motion have been studied. Objective linear motion was induced by means of a moving cart. Visually induced linear motion perception (linearvection) was obtained by projection of moving images at the periphery of the visual field. Image velocity and luminance thresholds for the appearance of linearvection have been measured and are in the range of those for image motion detection (without sensation of self motion) by the visual system. Latencies of onset are around 1 sec and short term adaptation has been shown. The dynamic range of the visual analyzer as judged by frequency analysis is lower than the vestibular analyzer. Conflicting situations in which visual cues contradict vestibular and other proprioceptive cues show, in the case of linearvection a dominance of vision which supports the idea of an essential although not independent role of vision in self motion perception.

Berthoz, A.↗
NASA NTRS2008

NASA Tech Briefs, February 2008

Topics discussed include: Optical Measurement of Mass Flow of a Two-Phase Fluid; Selectable-Tip Corrosion-Testing Electrochemical Cell; Piezoelectric Bolt Breakers and Bolt Fatigue Testers; Improved Measurement of B(sub 22) of Macromolecules in a Flow Cell; Measurements by a Vector Network Analyzer at 325 to 508 GHz; Using Light to Treat Mucositis and Help Wounds Heal; Increasing Discharge Capacities of Li-(CF)(sub n) Cells; Dot-in-Well Quantum-Dot Infrared Photodetectors; Integrated Microbatteries for Implantable Medical Devices; Oxidation Behavior of Carbon Fiber-Reinforced Composites; GIDEP Batching Tool; Generic Spacecraft Model for Real-Time Simulation; Parallel-Processing Software for Creating Mosaic Images; Software for Verifying Image-Correlation Tie Points; Flexcam Image Capture Viewing and Spot Tracking; Low-Pt-Content Anode Catalyst for Direct Methanol Fuel Cells; Graphite/Cyanate Ester Face Sheets for Adaptive Optics; Atomized BaF2-CaF7 for Better-Flowing Plasma-Spray Feedstock; Nanophase Nickel-Zirconium Alloys for Fuel Cells; Vacuum Packaging of MEMS With Multiple Internal Seal Rings; Compact Two-Dimensional Spectrometer Optics; and Fault-Tolerant Coding for State Machines.

Source record↗
NASA NTRS2021

Spectrum – An Instrument for Multispectral Biological Fluorescence Imaging on the International Space Station

Spectrum is a compact instrument for fluorescent imaging of biological specimens in microgravity and capable of operating within the constraints of an EXPRESS Rack on the International Space Station (ISS). The Spectrum Flight Unit (SFU) was launched to ISSin November 2019 and is available for science investigations as a general instrument. A duplicate Engineering Development Unit (EDU) is available at NASA Kennedy Space Center (KSC). Science Verification Testing (SVT) performed at KSCdemonstrated all required functions including five (5) fluorescence excitation wavelengths, growth lighting, environmental controls and monitoring, and high-resolution imaging using a 71 Megapixel camera with flat field lens. The design features key Orbital Replaceable Unit (ORU) components, which may be adapted or changed by future investigators for tailored science experiments.

Bradley Burns↗
DOE OSTI2021

Absorptive Weak Plume Detection on Gaussian and Non-Gaussian Background Clutter

For additive signals on Gaussian clutter, the optimal detector is a linear matched filter that is adapted to the known signal and the covariance of the background. This adaptive matched filter is widely used for gas-phase plume detection, even though the effect of the plume on the background is not strictly additive. Here, a derivation of the matched filter for a strictly absorptive plume produces, in the weak plume limit, a quadratic filter. This quadratic matched filter is extended in two ways: an elliptically-contoured multivariate t distribution is used to generalize the Gaussian background clutter, and a generalized likelihood ratio test detector is derived to extend applicability to stronger plumes. In addition to detectors whose purpose is to identify presence versus absence of a plume, expressions are also derived for estimating plume strength. The performance of these various detectors is evaluated by implanting simulated plume into background images that are either real hyperspectral images or simulated images based on different (Gaussian, multivariate t, and lognormal) clutter distributions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Adaptive hyperparameter updating for training restricted Boltzmann machines on quantum annealers

Restricted Boltzmann Machines (RBMs) have been proposed for developing neural networks for a variety of unsupervised machine learning applications such as image recognition, drug discovery, and materials design. The Boltzmann probability distribution is used as a model to identify network parameters by optimizing the likelihood of predicting an output given hidden states trained on available data. Training such networks often requires sampling over a large probability space that must be approximated during gradient based optimization. Quantum annealing has been proposed as a means to search this space more efficiently which has been experimentally investigated on D-Wave hardware. D-Wave implementation requires selection of an effective inverse temperature or hyperparameter (β) within the Boltzmann distribution which can strongly influence optimization. Here, we show how this parameter can be estimated as a hyperparameter applied to D-Wave hardware during neural network training by maximizing the likelihood or minimizing the Shannon entropy. We find both methods improve training RBMs based upon D-Wave hardware experimental validation on an image recognition problem. Neural network image reconstruction errors are evaluated using Bayesian uncertainty analysis which illustrate more than an order magnitude lower image reconstruction error using the maximum likelihood over manually optimizing the hyperparameter. The maximum likelihood method is also shown to out-perform minimizing the Shannon entropy for image reconstruction.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Adapting In Situ Accelerators for Sparsity With Granular Matrix Reordering

Neural network (NN) inference is an essential part of modern systems and is found at the heart of numerous applications ranging from image recognition to natural language processing. In situ NN accelerators can efficiently perform NN inference using resistive crossbars, which makes them a promising solution to the data movement challenges faced by conventional architectures. Although such accelerators demonstrate significant potential for dense NNs, they often do not benefit from sparse NNs, which contain relatively few non-zero weights. Processing sparse NNs on in situ accelerators results in wasted energy to charge the entire crossbar where most elements are zeros. To address this limitation, this paper proposes Granular Matrix Reordering (GMR): a preprocessing technique that enables an energy-efficient computation of sparse NNs on in situ accelerators. GMR reorders the rows and columns of sparse weight matrices to maximize the crossbars' utilization and minimize the total number of crossbars needed to be charged. The reordering process does not rely on sparsity patterns and incurs no accuracy loss. Finally, GMR achieves an average of 28% and up to 34% reduction in energy consumption over seven pruned NNs across four different pruning methods and network architectures.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

A PC-based multispectral scanner data evaluation workstation: Application to Daedalus scanners

In late 1989, a personal computer (PC)-based data evaluation workstation was developed to support post flight processing of Multispectral Atmospheric Mapping Sensor (MAMS) data. The MAMS Quick View System (QVS) is an image analysis and display system designed to provide the capability to evaluate Daedalus scanner data immediately after an aircraft flight. Even in its original form, the QVS offered the portability of a personal computer with the advanced analysis and display features of a mainframe image analysis system. It was recognized, however, that the original QVS had its limitations, both in speed and processing of MAMS data. Recent efforts are presented that focus on overcoming earlier limitations and adapting the system to a new data tape structure. In doing so, the enhanced Quick View System (QVS2) will accommodate data from any of the four spectrometers used with the Daedalus scanner on the NASA ER2 platform. The QVS2 is designed around the AST 486/33 MHz CPU personal computer and comes with 10 EISA expansion slots, keyboard, and 4.0 mbytes of memory. Specialized PC-McIDAS software provides the main image analysis and display capability for the system. Image analysis and display of the digital scanner data is accomplished with PC-McIDAS software.

Jedlovec, Gary J.↗
DOE OSTI2022

Enabling reactive microscopy with MicroMator

Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.

47 OTHER INSTRUMENTATION↗
NASA NTRS1995

Schlieren optics for leak detection

The purpose of this research was to develop an optical method of leak detection. Various modifications of schlieren optics were explored with initial emphasis on leak detection of the plumbing within the orbital maneuvering system of the space shuttle (OMS pod). The schlieren scheme envisioned for OMS pod leak detection was that of a high contrast pattern on flexible reflecting material imaged onto a negative of the same pattern. We find that the OMS pod geometry constrains the characteristic length scale of the pattern to the order of 0.001 inch. Our experiments suggest that optical modulation transfer efficiency will be very low for such patterns, which will limit the sensitivity of the technique. Optical elements which allow a negative of the scene to be reversibly recorded using light from the scene itself were explored for their potential in adaptive single-ended schlieren systems. Elements studied include photochromic glass, bacteriorhodopsin, and a transmissive liquid crystal display. The dynamics of writing and reading patterns were studied using intensity profiles from recorded images. Schlieren detection of index gradients in air was demonstrated.

Peale, Robert E.↗
NASA NTRS2017

Stroboscopic Goggles as a Countermeasure for Dynamic Visual Acuity and Landing Sickness in Crewmembers Returning from Long-Duration Spaceflight

Long-term exposure to microgravity causes sensorimotor adaptations that result in functional deficits upon returning to a gravitational environment. At landing, the vestibular system and the central nervous system, responsible for coordinating head and eye movements via the vestibulo-occular reflex (VOR), are adapted to microgravity and must re-adapt to the Earth's gravitational environment. This re-adaptation causes decrements in gaze control and dynamic visual acuity, with astronauts reporting oscillopsia and blurred vision. These effects are caused by retinal slip, or the inability to keep an image focused on their retina, which is thought to drive motion sickness symptoms experienced upon landing. Retinal slip can be estimated by dynamic visual acuity (DVA); visual acuity while in motion. Peters et al. (2011) find that DVA is worsened in astronauts by an average of 0.75 eye-chart lines one day after landing. Previously, the use of stroboscopic goggles has shown to be effective in minimizing motion sickness symptoms due to retinal slip (Reschke et al. 2007). In this study, we simulated the decrement in DVA caused by sensorimotor re-adaptation by using minifying lenses and then testing the efficacy of stroboscopic goggles in preventing retinal slip and improving DVA. Dynamic visual acuity is assessed using an oscillating chair developed in the Neuroscience Laboratory at JSC. This chair is motor-driven and oscillates vertically at 2 Hz with a vertical displacement of +/- 2 cm to simulate the vertical translations that occur while walking. As the subject is being oscillated, they are asked to discern the direction of Landolt-C optotypes of varying sizes and record their direction using a gamepad. The visual acuity thresholds are determined using an algorithm that alters the size of the optotype based on the previous responses of the subject using a forced-choice best parameter estimation that is able to rapidly converge on the threshold value. Visual acuity thresholds were determined both for static (seated) and dynamic (oscillating) conditions. Dynamic visual acuity is defined as the difference between the dynamic and static conditions. We found that healthy subjects (n=20) have a significantly impaired DVA while wearing the minifying lenses, demonstrating that the VOR is in an adaptive state and retinal slip is occurring. When subjects' acuity was tested wearing the stroboscopic goggles with the minifying lenses, there was no significant difference in their DVA compared to their baseline DVA. This suggests that stroboscopic goggles are preventing retinal slip and would function as an efficient countermeasure for VOR adaptations and thus help mitigate landing sickness symptoms experienced by long-duration crewmembers. These goggles might also be used to counter blurred vision (caused by retinal slip) experienced by crewmembers during launch where the vehicle vibrations are greatest. The stroboscopic effect could be built into a section of their head mounted displays on the visor of their helmets to be used in these high vibration situation if a mission critical task is necessary.

Rosenberg, M. J. F.↗
DOE OSTI2025

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding

Decoding visual experiences from fMRI offers a powerful avenue to understand human perception and develop advanced brain-computer interfaces. However, current progress often prioritizes maximizing reconstruction fidelity while overlooking interpretability, an essential aspect for deriving neuroscientific insight. To address this gap, we propose MoRE-Brain, a neuro-inspired framework designed for high-fidelity, adaptable, and interpretable visual reconstruction. MoRE-Brain uniquely employs a hierarchical Mixture-of-Experts architecture where distinct experts process fMRI signals from functionally related voxel groups, mimicking specialized brain networks. The experts are first trained to encode fMRI into the frozen CLIP space. A finetuned diffusion model then synthesizes images, guided by expert outputs through a novel dual-stage routing mechanism that dynamically weighs expert contributions across the diffusion process. MoRE-Brain offers three main advancements: First, it introduces a novel Mixture-of-Experts architecture grounded in brain network principles for neuro-decoding. Second, it achieves efficient cross-subject generalization by sharing core expert networks while adapting only subject-specific routers. Third, it provides enhanced mechanistic insight, as the explicit routing reveals precisely how different modeled brain regions shape the semantic and spatial attributes of the reconstructed image. Extensive experiments validate MoRE-Brain’s high reconstruction fidelity, with bottleneck analyses further demonstrating its effective utilization of fMRI signals, distinguishing genuine neural decoding from over-reliance on generative priors. Consequently, MoRE-Brain marks a substantial advance towards more generalizable and interpretable fMRI-based visual decoding.

Wei, Yuxiang [Georgia Institute of Technology]↗
DOE OSTI2025

An on-chip phased array for non-classical light

Abstract Quantum science and technology can offer fundamental enhancements in sensing, communications and computing. The expansion from wired to wireless links is an exciting prospect for quantum technologies. For classical technologies, the advent of phased arrays enabled directional and adaptive wireless links by manipulating electromagnetic waves over free space. Here we demonstrate a phased array system on a chip that can receive, image and manipulate non-classical light over free space. We use an integrated photonic-electronic system with more than 1000 functional components on-chip to detect squeezed light. By integrating an array of 32 sub-wavelength engineered metamaterial antennas, we demonstrate a direct free-space-to-chip interface for reconfigurable quantum links. On the same chip, we implement a large-scale array of quantum-limited coherent receivers that can resolve non-classical signals simultaneously across 32 channels. With coherent readout and manipulation of these signals, we demonstrate 32-pixel imaging and spatially configurable reception of squeezed light over free space. Our work advances wireless quantum technologies that could enable practical applications in quantum communications and sensing.

Science & Technology - Other Topics↗
NASA NTRS1993

Development Of Software To Recognize Parts Of Plants

Report describes first phase in development of digital image-processing subsystem recognizing parts of plants. Subsystem part of robotic system tending and harvesting plants in automated plant-growth chamber. Initial focus on image-processing software that distinguishes among seed heads, stems, and leaves of wheat plants and further distinguishes between these parts and background. Software adaptable to other types of plants.

Despain, Ronald R.↗
NASA NTRS1993

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

Paola, Justin D.↗