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At least 145 records · Page 8

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NASA NTRS2012

Design and fabrication of a stereoscopic rear-viewing endoscopic tool (MARVEL)

The use of minimally invasive neurosurgical techniques has experienced a growing interest among patients and surgeons alike due their the numerous advantages over more traditional operations. Current methods employ the use either rigid or articulating endoscopes, both of which are inserted through a small diameter opening in the skull near the intended surgical region. Although these devices aid the surgeon in viewing the operating site, they are severely limited by their inability to provide dimensional awareness to the user. The Multi-Angle Rear-Viewing Endoscopic TooL (MARVEL) has been designed such that the compact form of existing endoscopes is maintained while also providing the user with an enhanced 3-dimensional stereo view. The design of the alpha prototype for MARVEL was completed over the course of three months. In parallel with development, the device's optics were characterized and several software programs were generated. Once assembled, MARVEL will hold many advantages over existing endoscopic tools. It is expected that the device will greatly outperform its traditional counterparts by both increasing safety and decreasing the duration of surgical procedures. After completion, the device will be demonstrated to the project sponsors at the Skull Base Institute where it will undergo full evaluation and a feasibility analysis.

Strongrich, Andrew↗

NASA NTRS2018

Towards a Unified View of Modeling and Programming (ISoLA 2018 Track Introduction)

The article provides an introduction to the track: Towards a Uniﬁed View of Modeling and Programming, organized by the authors of this paper as part of ISoLA 2018: the 8th International Symposium On Leveraging Applications of Formal Methods, Veriﬁcation and Validation. A total of 19 researchers were invited to present their views on the two questions: what are the commonalities between modeling and programming languages, and should we strive towards a uniﬁed view of modeling and programming? The idea behind the track, which is a continuation of a similar track at ISoLA 2016, emerged as a result of experiences gathered in the three ﬁelds: formal methods, model-based software engineering, and programming languages, and from the observation that these technologies share a large common part, to the extent where one may ask, does the following equation hold: modeling = programming?

Steffen, Bernhard↗

NASA NTRSDate not supplied

Shape Approximation in Camera Fields of View for Parachute Visibility Applications

The ability to simulate camera line of sight and field of view is a powerful capability for flight mechanics simulations. This paper improves upon an existing camera visibility implementation that leverages geometry to estimate parachute visibility from a singular point by introducing a shape discretization method. The new method approximates a shape as a set of analytical points relative to a target marker within any number of camera fields of view. The method is developed in such a way to be generalized to a myriad of spacecraft applications. This effort focuses on an implementation to simulate parachute canopy visibility within the combined field of view of three cameras but additional applications are discussed. Monte Carlo analysis is used to assess the parachute canopy visibility example and demonstrate its improved performance over the previous method.

Evan Roelke↗

NASA NTRSDate not supplied

Shape Approximation in Camera Fields of View for Parachute Visibility Applications

Evan Roelke↗

DOE OSTI2025

Heterogeneous Point Set Transformers for Segmentation of Multiple View Particle Detectors

NOvA is a long-baseline neutrino oscillation experiment that detects neutrino particles from the NuMI beam at Fermilab. Before data from this experiment can be used in analyses, raw hits in the detector must be matched to their source particles, and the type of each particle must be identified. This task has commonly been done using a mix of traditional clustering approaches and convolutional neural networks (CNNs). Due to the construction of the detector, the data is presented as two sparse 2D images: an XZ and a YZ view of the detector, rather than a 3D representation. We propose a point set neural network that operates on the sparse matrices with an operation that mixes information from both views. Our model uses less than 10% of the memory required using previous methods while achieving a 96.8% AUC score, a higher score than obtained when both views are processed independently (85.4%).

Robles, Edgar E. [UC, Irvine (main)]↗

NASA NTRS2011

Using Ensemble Decisions and Active Selection to Improve Low-Cost Labeling for Multi-View Data

This paper seeks to improve low-cost labeling in terms of training set reliability (the fraction of correctly labeled training items) and test set performance for multi-view learning methods. Co-training is a popular multiview learning method that combines high-confidence example selection with low-cost (self) labeling. However, co-training with certain base learning algorithms significantly reduces training set reliability, causing an associated drop in prediction accuracy. We propose the use of ensemble labeling to improve reliability in such cases. We also discuss and show promising results on combining low-cost ensemble labeling with active (low-confidence) example selection. We unify these example selection and labeling strategies under collaborative learning, a family of techniques for multi-view learning that we are developing for distributed, sensor-network environments.

machine learning↗

NASA NTRS2013

Derivation of Sky-View Factors from LIDAR Data

The use of Lidar (Light Detection and Ranging), an active light-emitting instrument, is becoming increasingly common for a range of potential applications. Its ability to provide fine resolution spatial and vertical resolution elevation data makes it ideal for a wide range of studies. This paper demonstrates the capability of Lidar data to measure sky view factors (SVF). The Lidar data is used to generate a spatial map of SVFs which are then compared against photographically-derived SVF at selected point locations. At each location three near-surface elevations measurements were taken and compared with collocated Lidar-derived estimated. It was found that there was generally good agreement between the two methodologies, although with decreasing SVF the Lidar-derived technique tended to overestimate the SVF: this can be attributed in part to the spatial resolution of the Lidar sampling. Nevertheless, airborne Lidar systems can map sky view factors over a large area easily, improving the utility of such data in atmospheric and meteorological models.

spatial map↗

NASA NTRS2012

View Angle Effects on MODIS Snow Mapping in Forests

Binary snow maps and fractional snow cover data are provided routinely from MODIS (Moderate Resolution Imaging Spectroradiometer). This paper investigates how the wide observation angles of MODIS influence the current snow mapping algorithm in forested areas. Theoretical modeling results indicate that large view zenith angles (VZA) can lead to underestimation of fractional snow cover (FSC) by reducing the amount of the ground surface that is viewable through forest canopies, and by increasing uncertainties during the gridding of MODIS data. At the end of the MODIS scan line, the total modeled error can be as much as 50% for FSC. Empirical analysis of MODIS/Terra snow products in four forest sites shows high fluctuation in FSC estimates on consecutive days. In addition, the normalized difference snow index (NDSI) values, which are the primary input to the MODIS snow mapping algorithms, decrease as VZA increases at the site level. At the pixel level, NDSI values have higher variances, and are correlated with the normalized difference vegetation index (NDVI) in snow covered forests. These findings are consistent with our modeled results, and imply that consideration of view angle effects could improve MODIS snow monitoring in forested areas.

MODIS↗

DOE OSTI2022

Fluorescence strobo-stereoscopy for specular reflection-suppressed full field of view imaging

This report introduces fluorescence strobo-stereoscopy (FSS) to suppress strong specular reflection and enable the full field of view (FFOV) 3D surface imaging while the part is rotating. Specular reflection off the target surface significantly degrades the image quality and becomes critical for highly reflective surface measurements. In FSS, the fluorescent dye-doped fluid applied on the machined surface is excited upon incident ultra-violet light and becomes a new light source by Stokes' Law. Thus, specular reflection off of smooth surface can be suppressed by separating the fluorescent light from the excitation light. The developed FSS comprises a pair of imaging cameras, spatial filters, and an excitation light source. As a result, FSS effectively rejected the specular reflection and improved the FFOV 3D surface image quality of the machined part by enhancing contrast in the rotating target surface. Such enhancements in 3D imaging allowed to identify manufacturing tolerance of the part and to detect the surface features. The axial and lateral accuracy errors of FSS were 2.3% and 1.4% with the target size of 4.07 mm and 0.215 mm, respectively. A whole view reconstruction of the cylindrical target sample was performed, and the corresponding cylindricity and diameter deviation were assessed. The fluid media effect and the target surface quality effect were discussed.

3D surface imaging↗

DOE OSTI2023

Probing three-dimensional mesoscopic interfacial structures in a single view using multibeam X-ray coherent surface scattering and holography imaging

Abstract Visualizing surface-supported and buried planar mesoscale structures, such as nanoelectronics, ultrathin-film quantum dots, photovoltaics, and heterogeneous catalysts, often requires high-resolution X-ray imaging and scattering. Here, we discovered that multibeam scattering in grazing-incident reflection geometry is sensitive to three-dimensional (3D) structures in a single view, which is difficult in conventional scattering or imaging approaches. We developed a 3D finite-element-based multibeam-scattering analysis to decode the heterogeneous electric-field distribution and to faithfully reproduce the complex scattering and surface features. This approach further leads to the demonstration of hard-X-ray Lloyd’s mirror interference of scattering waves, resembling dark-field, high-contrast surface holography under the grazing-angle scattering conditions. A first-principles calculation of the single-view holographic images resolves the surface patterns’ 3D morphology with nanometer resolutions, which is critical for ultrafine nanocircuit metrology. The holographic method and simulations pave the way for single-shot structural characterization for visualizing irreversible and morphology-transforming physical and chemical processes in situ or operando .

47 OTHER INSTRUMENTATION↗

DOE OSTI2019

Searching for dark matter in the Galactic halo with a wide field of view TeV gamma-ray observatory in the Southern Hemisphere

Although there is mounting evidence that dark matter (DM) exists in the Universe, its fundamental nature remains unknown. We present sensitivity estimates to detect DM particles with a future very-high-energy (gsim TeV) wide field-of-view gamma-ray observatory in the Southern Hemisphere. This observatory would search for gamma rays from the annihilation or decay of DM particles in the Galactic halo. With a wide field of view, both the Galactic Center and a large fraction of the Galactic halo will be detectable with unprecedented sensitivity to DM in the mass range of ~500 GeV to ~2 PeV . These results, combined with those from other present and future gamma-ray observatories, will likely probe the thermal relic annihilation cross section of Weakly Interacting Massive Particles for all masses from ~80 TeV down to the GeV range in most annihilation channels.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Revealing Phase Heterogeneity in Vertically Aligned Nanocomposites via Plan-View Electron Energy Loss Spectroscopy

Hydrogen utilization in clean energy technologies is challenged by limited storage and transport within materials, owing to the complex hydrogen kinetics at interfaces [1]. Understanding these interfacial mechanisms at the nanoscale is crucial for developing improved materials for hydrogen applications, particularly proton-conducting fuel cells (PCFCs). Vertically aligned nanocomposites (VANs) grown by pulsed laser deposition (PLD) offer a unique platform for investigating the interfacial effects on hydrogen transport due to their well-defined interfaces parallel to the direction of charge transport [2-4]. To investigate hydrogen transport, the two phases within the VANs were chosen as BaZr 0.9 Y 0.1 O 3-x (BZY), a known proton conductor, and Pr 0.1 Ce 0.9 O 2-x (PCO), a mixed ionic-electronic conductor [5]. This PCO-BZY VANs architecture allows the investigation of how the interface between a proton conductor and a mixed conductor influences hydrogen transport. However, because of the small size of hydrogen, it is difficult to discern the nature of its interactions with interfaces from bulk measurements at the macroscale, thus necessitating nanoscale measurements [6]. Electron energy loss spectroscopy (EELS) allows for nanometer-resolution probing of the local atomic structure and chemistry at the BZY/PCO interface. In this study, plan-view analysis of PCO-BZY VANs films was employed to characterize the structure and phase distribution of the VANs and investigate the interface between the nanostructures. The films were imaged using scanning electron microscopy (SEM) in the Hitachi S-4800 SEM, collecting secondary electron images using mixed upper and lower detectors. Then, plan-view transmission electron microscopy (TEM) and scanning transmission electron microscopy (STEM) EELS were employed using a JEOL ARM300 microscope operated at 300kV with a Gatan K3 GIF Continuum detector to study the distribution of the BZY and PCO phases through the film. As a result, spectrum images were acquired at a dispersion of 0.18eV per channel and denoised afterward by principal component analysis (PCA) method.

Griffin, Elizabeth [Northwestern University, Evans↗

DOE OSTI2024

Towards Full Field-of-View Fourier Ptychography for Extreme Ultraviolet Microscope

We evaluate various Fourier ptychographic microscopy (FPM) reconstruction algorithms using both simulated and experimental data acquired from an Extreme Ultraviolet (EUV, 13.5 nm wavelength) microscope. We specifically focus on the algorithms' ability to robustly address field-dependent aberrations, which enables increased spatial resolution and quantitative phase imaging across an expanded field of view. We systematically compare the algorithms' performance under aberrations for a single zoneplate imaging system, utilizing Fourier Ring Correlation (FRC) as a systematic metric for assessing reconstruction quality. Furthermore, we explore the impact of systematic errors on the reconstruction of experimental data, aiming to increase the effective field of view by 25-fold, from the nominal 5x5 um2 diffraction-limited area. Additionally, our evaluation incorporates innovative FPM-adjacent methodologies, including the Angular Ptychographic Imaging with Closed-form method (APIC), for reconstructing EUV images.

Gu, Chaoying↗

DOE OSTI2026

EnergyPlus View Factor Calculation

The Python code takes EnergyPlus input files and creates input for the View3D program, executes the View3D program, then inserts the respective view factors into the EnergyPlus input file, thus streamlining the process of view factor calculation and modification of the EnergyPlus input file.

Kunwar, Niraj [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2025

AmeriFlux FLUXNET-1F US-UTV UFLUX Desert View

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-UTV UFLUX Desert View. This is the FLUXNET version of the carbon flux data for the site US-UTV UFLUX Desert View produced by applying the standard ONEFlux (1F) software. Site Description - This station is located alongside a large pivot that irrigate alfalpha.

Ladig, Kathryn [Utah Geological Survey]↗

DOE OSTI2021

Chamber Interior Viewing System (CIVS 2.0)

The NIF facility is used to conduct fusion and high-density scientific research. The experiments are conducted inside of a 10-meter diameter vacuum chamber called the “Target Chamber”. The target chamber is covered in ports to permit adding equipment to the exterior. Some of this equipment extends into the target chamber such as the target positioners and diagnostics. Other equipment sits on the surface and looks inward, such as the CIVS system. CIVS stands for Chamber Interior Viewing System. The CIVS system provides simple black and white digital images of the interior of the target chamber in real time. These images are used for positioner alignment, trouble shooting and observing for positioner collision. The views through these cameras need to be clear enough for the operators to safely conduct these tasks. One of the products of the experiments conducted in the target chamber are neutrons. These neutrons expand outward from the center of the target chamber with great energy. If the neutrons hit the sensor chip on a digital camera they will “kill” the sensor pixel where they contact, and the result will be a permanently bright white pixel on the image. Over time these “dead” pixels will build up and make the camera less and less usable providing a “staticky” image. The current solution of replacing the cameras when they become damaged is unsustainable due to both the cameras being out of production and the increased rate of camera failure based upon the increased number and energy of neutrons being generated. Current supplies of the correct camera type are dwindling with no source of replacement and the projected rate of replacement is unsustainable. Without a redesign, the function provided by the current CIVS system will be lost.

42 ENGINEERING↗

DOE OSTI2025

Vehicular Re-Identification from Uncontrolled Multiple Views

Vehicle re-identification (re-ID) across disparate sensing modalities remains a fundamental challenge for transportation research. In this work, we introduce a deep multi-view vehicle re-ID framework that leverages Siamese networks to compare pairs of vehicle images and produce matching scores, enabling robust association across drastically different viewpoints such as those from UAVs, surveillance cameras, and ground sensors. The model exploits convolutional neural networks to learn features that remain discriminative under changes in angle, distance, and illumination, supporting more generalizable re-ID performance. As part of this effort, we also developed an automated pipeline to synchronize roadside and UAV video streams, producing a multi-perspective dataset that complements preexisting real collections and a synthetic dataset generated in this study. Together, these contributions advance the capability to re-identify vehicles across wide viewing baselines; establish a foundation for scalable, reproducible research in vehicle re-ID; and open pathways for future applications, such as inferring routine behaviors, movement patterns, and daily habits of the individual associated with the vehicle.

convolutional neural networks↗

DOE OSTI2025

The Roman View of Strong Gravitational Lenses

Galaxy–galaxy strong gravitational lenses can constrain dark matter models and the Lambda cold dark matter cosmological paradigm at subgalactic scales. Currently, there is a dearth of images of these rare systems with high signal-to-noise ratio (SNR) and angular resolution. The Nancy Grace Roman Space Telescope (hereafter Roman), scheduled for launch in late 2026, will play a transformative role in strong-lensing science with its planned wide-field surveys. With its remarkable 0.281 square degree field of view and diffraction-limited angular resolution of ~0$^{''}_.$1, Roman is uniquely suited to characterizing dark matter substructure from a robust population of strong lenses. We present a yield simulation of detectable strong lenses in Roman’s planned High Latitude Wide Area Survey (HLWAS). We simulate a population of galaxy–galaxy strong lenses across cosmic time with cold dark matter subhalo populations, select those detectable in the HLWAS, and generate simulated images accounting for realistic Wide Field Instrument detector effects. For a fiducial case of single 146 s exposures, we predict around 160,000 detectable strong lenses in the HLWAS, of which about 500 will have sufficient SNR to be amenable to detailed substructure characterization. We investigate the effect of variation of the point-spread function across Roman’s field of view on detecting individual subhalos and the suppression of the subhalo mass function at low masses. Our simulation products are available to support strong-lens science with Roman, such as training neural networks and validating dark matter substructure analysis pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗