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At least 1,261 records · Page 70

Metric Learning for Hyperspectral Image Segmentation

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Compact Reconnaissance Imaging Spectrometer (CRISM↗

Measurement of Deformation Heterogeneity During Shale Swelling Using Digital Image Correlation

Abstract Rock-fluid interactions in shale formations are one of the main sources of wellbore instability issues and inadequate stimulation performance. For better planning of fracturing operations and optimizing production from these reservoirs, it is important to understand the mechanisms behind these interactions. These issues are especially prevalent in clay-rich shales, such as Tuscaloosa Marine Shale, which is the subject of this study. Conventional techniques to quantify these shale-fluid interactions comprise of measuring swelling in powdered rock grains or measurement of deformation in the whole pieces of the core using a linear variable differential transformer and strain gages. However, the contribution from individual laminae to overall deformation cannot be evaluated using these methods. In this study, we developed an experimental setup to evaluate the spatial deformation in shale during interaction with water using digital image correlation (DIC). Deformation of two shale samples, with 34 wt% to 51 wt% clay content, was studied. White paint was used to generate a random speckle pattern on the specimen and then immersed in deionized water. The deformation process was captured using a digital camera and images were analyzed using DIC to quantify the deformation. The implementation of the DIC technique enables the visualization and quantification of spatial deformation in the specimen during interacting with water. The results show the localization of large strains in select laminations. The results provide a better understanding of shale deformation when interacting with water in comparison to traditional measurements that can provide only an average strain value.

Energy & Fuels↗

Digital techniques for processing Landsat imagery

An overview of the basic techniques used to process Landsat images with a digital computer, and the VICAR image processing software developed at JPL and available to users through the NASA sponsored COSMIC computer program distribution center is presented. Examples of subjective processing performed to improve the information display for the human observer, such as contrast enhancement, pseudocolor display and band rationing, and of quantitative processing using mathematical models, such as classification based on multispectral signatures of different areas within a given scene and geometric transformation of imagery into standard mapping projections are given. Examples are illustrated by Landsat scenes of the Andes mountains and Altyn-Tagh fault zone in China before and after contrast enhancement and classification of land use in Portland, Oregon. The VICAR image processing software system which consists of a language translator that simplifies execution of image processing programs and provides a general purpose format so that imagery from a variety of sources can be processed by the same basic set of general applications programs is described.

Green, W. B.↗

Application of a Metal Artifact Reduction Algorithm for C-Arm Cone-Beam CT: Impact on Image Quality and Diagnostic Confidence for Bronchial Artery Embolization

Objective: The objective of this study was to evaluate the potential benefit of a dedicated cone-beam-CT streak metal artifact removal technique (SMART) in terms of both image quality and diagnostic confidence in patients undergoing bronchial artery embolization. Methods: A total of 17 patients were included in this retrospective study. The SMART algorithm was applied to images containing streak artifacts generated by a radiopaque intra-arterial catheter tip. Quantitative evaluation of artifact severity was performed via measurement of the Hounsfield units along a closed loop surrounding the catheter tip and was conducted in the frequency domain following the application of the discrete Fourier transform to the measured data. A high proportion of power in the low frequencies of the resulting spectrum indicated a high level of streak artifacts. Qualitative evaluation of diagnostic confidence was performed using a 4-point Likert scale. Results: Both quantitative and qualitative evaluation demonstrated a significant reduction in artifact severity using the SMART algorithm. Quantitative evaluation demonstrated a mean artifact reduction of 22.5% using SMART compared to non-SMART images (p < 0.001). Qualitative evaluation demonstrated the greatest artifact reduction at the inner and outer aortic curvature, as well as immediately surrounding the tip of the catheter. In 6 of 17 cases, the use of the SMART algorithm yielded additional clinical information, increasing mean diagnostic confidence from 3.17 to 3.78 (p < 0.001). Conclusion: The SMART algorithm allows for efficient reduction of metal artifacts introduced by radiopaque catheter tips during cone-beam CT. Using this algorithm, diagnostic images of the aortic arch were significantly improved both quantitatively and qualitatively, yielding clinically relevant levels of enhanced diagnostic confidence. These results demonstrate that the SMART algorithm improves diagnostic and clinical characterization of the course of bronchial arteries on CBCT images, potentially improving the accuracy and clinical efficacy of bronchial artery embolization. Level of Evidence: 3.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Microwave Imaging and Holographic Diagnostic to Antennas in Cylindrical Near-Field Measurement

In this paper, the issues pertaining to microwave imaging and holographic diagnostic to antennas in cylindrical near-field measurements are addressed. The theoretical approach is based on expanding the work in [1] and [2] where a cylindrical wave expansion of the field on a cylindrical near-field surface is given. The sampling probe is modeled by its equivalent aperture current (idealized circular aperture) and incorporated into the near-field to far-field transformation. The method of steepest decent is applied to obtain the far-field. In its implementation, however, one could specify directly the angular spectrum at which the far-field is desired to be calculated without resorting to interpolation. The microwave imaging and holographic diagnostic is based on back projection where a plane wave expansion of the far-field is obtained. This approach necessitates the knowledge of the far-field at exact angular spectrum resulting from application of 2-D FFT. Hence, we were able to construct simply the near-field on a plane not necessarily on the aperture plane of the test antenna but also on planes perpendicular to the aperture plane [3]. And a 3-D high resolution and high precision antenna imaging of the test antenna is obtained from cylindrical near-field simulated measurements. In addition microwave holographic diagnostic of large NASA scatterometer radar antenna obtained from measured near-field on a cylindrical surface will be given if time permits.

Microwave Imaging Holographic↗

Effects of Strain and Strain Rate on Dynamic Grain Growth and Subgrain Evolution During Plastic Deformation of an Interstitial-Free Steel at 850 ° C

Here, the effects of strain and strain rate on dynamic grain growth (DGG) and subgrain evolution are reported for an interstitial-free steel deformed at 850 ° C. Microstructures produced during tension tests at true-strain rates of 10 -4 and to 10 -3 s -1 true strains ranging from 0.02 to 0.2 were preserved following deformation. These were characterized using electron backscatter diffraction (EBSD), including the application of spherical harmonic transform indexing to produce high-angular-resolution EBSD (HR-EBSD) data. HR-EBSD data resolved the small misorientation angles of subgrain boundaries while imaging much larger data fields than possible with previously available techniques. The resulting data confirmed that steady-state flow stress is inversely proportional to the average subgrain size and that subgrain boundary misorientation angle increases with strain. The following new observations are reported. The rate of DGG increased with respect to time but decreased with respect to strain as strain rate increased. This behavior is rationalized through a simple model using separate rate parameters for the effects of time and strain. Subgrain size was not constant during steady-state deformation, but decreased slowly with increasing strain. Subgrain size distributions and subgrain boundary misorientation angle distributions were measured, and both remained approximately log-normal during steady-state deformation. Subgrain evolution demonstrated no dependence on parent grain size, crystallographic orientation, or Taylor factor. These new data suggest that steady-state flow stress is more likely controlled by the dislocation density internal to subgrains than by the spacing between subgrain boundaries.

dynamic grain growth↗

Nanostructural evolution of Al(OH)3 gel formed by the cubic and orthorhombic ye'elimite clinkers of calcium sulfoaluminate cements in an ultra-wide hydration temperature range

This paper investigated the influence of hydration temperature on the nanostructure of the AH{sub 3} phase formed in calcium sulfoaluminate cements. Orthorhombic ye'elimite (st-ye'elimite) and cubic ye'elimite (ss-ye'elimite) were hydrated in an ultra-wide temperature range (5–220 °C). Results showed that the AH{sub 3} phase formed by ss-ye'elimite was always microcrystalline in nature at various curing temperatures (5–130 °C), and transformed into the AlOOH phase at 150 °C and above. However, the AH{sub 3} phase formed by st-ye'elimite grew from a microcrystal to a favorable crystal as the temperature increased, and transformed into the AlOOH phase at 170 °C and above. The nanostructure of hydration products was further investigated using TEM/SAED analysis together with FE-SEM images, directly evidencing that the formed AFm-12 phase was single-crystal in nature, and the formed AH{sub 3} phase was microcrystalline at low temperatures and grew into single-crystal hexagonal prisms with the preferred growth direction along [001] direction at high temperatures.

36 MATERIALS SCIENCE↗

Organic and Organometallic Chemistry at the Single-Molecule, -Particle, and -Molecular-Catalyst-Turnover Level by Fluorescence Microscopy

Mechanistic studies have historically played a key role in the discovery and optimization of reactions in organic and organometallic chemistry. However, even apparently simple organic and organometallic transformations may have surprisingly complicated multistep mechanisms, increasing the difficulty of extracting this mechanistic information. The resulting reaction intermediates often constitute a small fraction of the total reaction mixture, for example, creating a long-term analytical challenge of detection. This challenge is particularly pronounced in cases where the positions of intermediates on the reaction energy surface mean that they do not “build up” to the quantities needed for observation by traditional ensemble analytical tools. Thus, their existence and single-step elementary reactivity cannot be studied directly. New approaches for obtaining this otherwise-missing mechanistic information are therefore needed. Single-turnover, single-molecule, single-particle, and other subensemble fluorescence microscopy techniques are ideally suited for this role because of their sensitivity and spatiotemporal resolution. Inspired by the robust development of single-molecule fluorescence microscopy tools for studying enzyme catalysis, our laboratory has developed analogous fluorescence microscopy techniques to overcome mechanistic challenges in synthetic chemistry, with sensitivity as high as the single-complex, single-turnover, and single-molecule level. These techniques free the experimenter from the previous restriction that intermediates must “build up” to quantities needed for detection by ensemble analytical tools and are suited to systems where synchronization through flash photolysis or stopped flow would be inconvenient or inaccessible. In this process, the techniques transform certain previously “unobservable” intermediates and their elementary single-step reactivities into “observable” ones through sensitive and selective spectral handles. Our program has focused on imaging reactions in small-molecule, organic, and polymer synthetic chemistry with an accent on the reactivity of molecular transition metal complexes and catalysts. Our laboratory initiated studies in this area in 2008 with the imaging of individual palladium complexes that were tagged with spectator fluorophores. To enable imaging, we started with fluorophore selection and development, overcame challenges with imaging in organic solvents, and developed strategies compatible with air-sensitive chemistry and concentrations of reagents generally used in small-molecule synthesis. These studies grew to include characterization of previously unknown organometallic intermediates in the synthesis of organozinc reagents and the direct study of their elementary-step reactivity. The ability to directly observe this behavior generated predictive power for selecting salts that accelerated organozinc reagent formation in synthesis, including salts that had not yet been reported synthetically. In 2017 we also developed the first single-turnover imaging of molecular (chemo)catalysts, which through the technique’s spatiotemporal resolution revealed abruptly time-variable polymerization kinetics wherein molecular ruthenium ring-opening metathesis polymerization (ROMP) catalysts changed rates independently from other catalysts less than 1 μm away. Individual catalytic turnovers, each corresponding to one single-chain-elongation reaction arising from insertion of single ROMP or enyne monomers at individual Grubbs II molecular ruthenium catalysts, were spatiotemporally resolved as green flashes in growing polymers. In this work, we discuss the development of this technique from idea to application, including challenges overcome and strategies created to image synthetic organic and organometallic molecular chemistry at the highest levels of detection sensitivity. We also describe challenges not yet solved and provide an outlook for this growing field at the intersection of microscopy and synthetic/molecular chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Experimental Assessment of Mammalian Lipidome Complexity Using Multimodal 21 T FTICR Mass Spectrometry Imaging

Herein, we assess the complementarity and complexity of data that can be detected within mammalian lipidome mass spectrometry imaging (MSI) via matrix-assisted laser desorption ionization (MALDI) and nanospray desorption electrospray ionization (nano-DESI). We do so by employing 21 T Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) with absorption mode FT processing in both cases, allowing unmatched mass resolving power per unit time (≥613k at m/z 760, 1.536 s transients). While our results demonstrated that molecular coverage and dynamic range capabilities were greater in MALDI analysis, nano-DESI provided superior mass error, and all annotations for both modes had sub-ppm error. Taken together, these experiments highlight the coverage of 1676 lipids and serve as a functional guide for expected lipidome complexity within nano-DESI-MSI and MALDI-MSI. To further assess the lipidome complexity, mass splits (i.e., the difference in mass between neighboring peaks) within single pixels were collated across all pixels from each respective MSI experiment. The spatial localization of these mass splits was powerful in informing whether the observed mass splits were biological or artificial (e.g., matrix related). Mass splits down to 2.4 mDa were observed (i.e., sodium adduct ambiguity) in each experiment, and both modalities highlighted comparable degrees of lipidome complexity. Further, we highlight the persistence of certain mass splits (e.g., 8.9 mDa; double bond ambiguity) independent of ionization biases. Here, we also evaluate the need for ultrahigh mass resolving power for mass splits ≤4.6 mDa (potassium adduct ambiguity) at m/z > 1000, which may only be resolved by advanced FTICR-MS instrumentation.

21T-FTICR-MS↗

Real-time tracking of structural evolution in 2D MXenes using theory-enhanced machine learning

In situ Electron Energy Loss Spectroscopy (EELS) combined with Transmission Electron Microscopy (TEM) has traditionally been pivotal for understanding how material processing choices affect local structure and composition. However, the ability to monitor and respond to ultrafast transient changes, now achievable with EELS and TEM, necessitates innovative analytical frameworks. Here, we introduce a machine learning (ML) framework tailored for the real-time assessment and characterization of in operando EELS Spectrum Images (EELS-SI). We focus on 2D MXenes as the sample material system, specifically targeting the understanding and control of their atomic-scale structural transformations that critically influence their electronic and optical properties. This approach requires fewer labeled training data points than typical deep learning classification methods. By integrating computationally generated structures of MXenes and experimental datasets into a unified latent space using Variational Autoencoders (VAE) in a unique training method, our framework accurately predicts structural evolutions at latencies pertinent to closed-loop processing within the TEM. This study presents a critical advancement in enabling automated, on-the-fly synthesis and characterization, significantly enhancing capabilities for materials discovery and the precision engineering of functional materials at the atomic scale.

47 OTHER INSTRUMENTATION↗

Multispectral, thermal infrared satellite data for geologic applications

The value of multispectral thermal infrared satellite data for geologic mapping was assessed, applying the principal component and canonical analysis techniques to the images of the central part of the Arabian Peninsula (a 200 x 300 km area). Low resolution thermal infrared (TIR) data from the Nimbus 5 Surface Composition Mapping Radiometer (SCMR) and the NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) were used. Color images included an 8.8 micrometer (SCMR) and 3.7 and 10.8 micrometer (AVHRR-night) data, ratioed AVHRR day/night TIR data, ratioed AVHRR reflected radiation data, and transformed 8- and 10-band TIR plus reflected radiation data. The results clearly demonstrated the potential geologic value of multispectral TIR data. Igneous and metamorphic units could be separated as a class (although not from each other except for young calc-alkaline granites). Some previously unmapped extensions of mapped faults below thick sedimentary units could be delineated. No single enhancement technique displayed all the potential information, implying that they should be used together.

Blodget, H. W.↗

Estimation of forest canopy characteristics and nitrogen cycling using imaging spectrometry

Canopy lignin concentration is strongly related to annual rates of nitrogen mineralization in a series of Wisconsin forest ecosystems. High spectral resolution Airborne Imaging Spectrometer (AIS) data were acquired over these forests to investigate the potential of remotely estimating canopy lignin content. Analysis of the data using a derivative transformation and correlative techniques suggests that lignin or a closely associated cellular constituent is influential in canopy reflectance. Spatial distributions of percent canopy lignin and annual rates of nitrogen mineralization for Blackhawk Island, WI, have been estimated from a mosaic of AIS imagery.

Wessman, Carol A.↗

Efficient Two-Dimensional-FFT Program

Program computes 64 X 64-point fast Fourier transform in less than 17 microseconds. Optimized 64 X 64 Point Two-Dimensional Fast Fourier Transform combines performance of real- and complex-valued one-dimensional fast Fourier transforms (FFT's) to execute two-dimensional FFT and coefficients of power spectrum. Coefficients used in many applications, including analyzing spectra, convolution, digital filtering, processing images, and compressing data. Source code written in C, 8086 Assembly, and Texas Instruments TMS320C30 Assembly languages.

Miko, J.↗

Automated detection of jet contrails using the AVHRR split window

This paper investigates the automated detection of jet contrails using data from the Advanced Very High Resolution Radiometer. A preliminary algorithm subtracts the 11.8-micron image from the 10.8-micron image, creating a difference image on which contrails are enhanced. Then a three-stage algorithm searches the difference image for the nearly-straight line segments which characterize contrails. First, the algorithm searches for elevated, linear patterns called 'ridges'. Second, it applies a Hough transform to the detected ridges to locate nearly-straight lines. Third, the algorithm determines which of the nearly-straight lines are likely to be contrails. The paper applies this technique to several test scenes.

Engelstad, M.↗

Automatic Fringe Detection for Oil Film Interferometry Measurement of Skin Friction

This report summarizes two years of work on investigating algorithms for automatically detecting fringe patterns in images acquired using oil-drop interferometry for the determination of skin friction. Several different analysis methods were tested, and a combination of a windowed Fourier transform followed by a correlation was found to be most effective. The implementation of this method is discussed and details of the process are described. The results indicate that this method shows promise for automating the fringe detection process, but further testing is required.

Naughton, Jonathan W.↗

Method and Apparatus for Evaluating the Visual Quality of Processed Digital Video Sequences

A Digital Video Quality (DVQ) apparatus and method that incorporate a model of human visual sensitivity to predict the visibility of artifacts. The DVQ method and apparatus are used for the evaluation of the visual quality of processed digital video sequences and for adaptively controlling the bit rate of the processed digital video sequences without compromising the visual quality. The DVQ apparatus minimizes the required amount of memory and computation. The input to the DVQ apparatus is a pair of color image sequences: an original (R) non-compressed sequence, and a processed (T) sequence. Both sequences (R) and (T) are sampled, cropped, and subjected to color transformations. The sequences are then subjected to blocking and discrete cosine transformation, and the results are transformed to local contrast. The next step is a time filtering operation which implements the human sensitivity to different time frequencies. The results are converted to threshold units by dividing each discrete cosine transform coefficient by its respective visual threshold. At the next stage the two sequences are subtracted to produce an error sequence. The error sequence is subjected to a contrast masking operation, which also depends upon the reference sequence (R). The masked errors can be pooled in various ways to illustrate the perceptual error over various dimensions, and the pooled error can be converted to a visual quality measure.

Watson, Andrew B.↗

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment.

Source record↗

Self-Similar Outflows at the Source of the Fast Solar Wind: A Smoking Gun of Multiscale Impulsive Reconnection?

We present results of a quantitative analysis of structured plasma outflows above a polar coronal hole observed by the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) spacecraft. In a 6 hr interval of continuous high-cadence SDO/AIA images, we identified more than 2300 episodes of small-scale plasma flows in the polar corona. The mean upward flow speed measured by the surfing transform technique is estimated to be 122 ± 34 km s−1, which is comparable to the local sound speed. The typical recurrence period of the flow episodes is 10–30 minutes, and the mean duration and transverse size of each episode are about 3–5 minutes and 3–4 Mm, respectively. The largest identifiable episodes last for tens of minutes and reach widths up to 40 Mm. For the first time, we demonstrate that the polar coronal-hole outflows obey a family of power-law probability distributions characteristic of impulsive interchange magnetic reconnection. Turbulent photospheric driving may play a crucial role in releasing magnetically confined plasma onto open field. The estimated occurrence rate of the detected self-similar coronal outflows is sufficient for them to make a dominant contribution to the fast-wind mass and energy fluxes and to account for the wind's small-scale structure.

jets↗