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DOE OSTI2024

EPCAPE-PT-LANL Measurements: Wideband Integrated Bioaerosol Sensor

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Wideband Integrated Bioaerosol Sensor (Droplet Measurements Technology) Data Notes: The WIBS is an online single-particle measurement that detects FBAPs (within a size range of 0.5 - 30 microns in diameter) based on the excitation and emission wavelengths of the individual particles. Using two xenon lamps, the WIBS excites FBAPs at 280 nm and 370 nm. Their emission is detected across two wavebands of 310-400 nm and 420-650 nm. We classified the FBAPs into seven different categories (A, B, C, AB, BC, AC, and ABC) using the classification scheme in Perring et. al. (2015) [1]. Averaged number concentration of FBAPs (total and by category) and particles that non-fluorescent bioaerosols particles (NFBAPs). In separate files, we also present one-minute-averaged size distributions and the asymmetry factor (AF, a surrogate for shape) of all FBAPs and NFBAPs. The logarithmic bin width of the size bins are the same as the average bin width of the AOS's optical particle counter (OPC, Grimm) for the range of sizes in which they overlap (26 bins from 0.5 - 30 microns). AF of the particles ranges from 0-100 and is divided into five bins with a linear spacing at increments of 20. The smallest AF bin represents more spherical particles while the largest bin represents more rod-shaped particles. [1] Perring, A. E., et al. (2015), Airborne observations of regional variation in fluorescent aerosol across the United States, J. Geophys. Res. Atmos., 120, 1153–1170, doi:10.1002/2014JD022495. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2023epcape-pt-lanl. Files data_10min_WIBS_AFDist.csv Header: - FBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of FBAPs detected during the measurement. - NFBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of non-fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of NFBAPs detected during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. AF Bins: • Bin 1: 0 – 20 [unitless] • Bin 2: 21 – 40 [unitless] • Bin 3: 41 – 60 [unitless] • Bin 4: 61 – 80 [unitless] • Bin 5: 81 – 100 [unitless] Files data_10min_WIBS_Conc.csv Header: - NumberConcentrationA[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel A, measured in particles per cubic centimeter. - NumberConcentrationB[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel B, measured in particles per cubic centimeter. - NumberConcentrationC[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel C, measured in particles per cubic centimeter. - NumberConcentrationAB[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and B, measured in particles per cubic centimeter. - NumberConcentrationBC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels B and C, measured in particles per cubic centimeter. - NumberConcentrationAC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and C, measured in particles per cubic centimeter. - NumberConcentrationABC[/cm3]: Combined number concentration of bioaerosol particles detected by all three fluorescence channels A, B, and C, measured in particles per cubic centimeter. - NumberConcentrationNFBAP[/cm3]: Number concentration of non-fluorescent bioaerosol particles, measured in particles per cubic centimeter. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Files data_10min_WIBS_SizeDist.csv Header: - FBAP_SizeDist[/cm3]_Bin_1 to FBAP_SizeDist[/cm3]_Bin_26: Number concentrations of FBAP in each of 26 size bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle sizes, capturing the size distribution of FBAPs detected during the measurement. - NFBAP_SizeDist[/cm3]_Bin_1 to NFBAP_SizeDist[/cm3]_Bin_26: Number concentrations of NFBAP in each of 26 size bins, measured in particles per cubic centimeter. Similar to FBAP, each bin covers a specific range of particle sizes, detailing the size distribution of NFBAPs detected. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Size Bins: • Bin 1: 0.48 to 0.57 μm • Bin 2: 0.57 to 0.67 μm • Bin 3: 0.67 to 0.79 μm • Bin 4: 0.79 to 0.93 μm • Bin 5: 0.93 to 1.1 μm • Bin 6: 1.1 to 1.29 μm • Bin 7: 1.29 to 1.52 μm • Bin 8: 1.52 to 1.8 μm • Bin 9: 1.8 to 2.11 μm • Bin 10: 2.11 to 2.5 μm • Bin 11: 2.5 to 2.94 μm • Bin 12: 2.94 to 3.46 μm • Bin 13: 3.46 to 4.08 μm • Bin 14: 4.08 to 4.81 μm • Bin 15: 4.81 to 5.67 μm • Bin 16: 5.67 to 6.68 μm • Bin 17: 6.68 to 7.88 μm • Bin 18: 7.88 to 9.29 μm • Bin 19: 9.29 to 10.96 μm • Bin 20: 10.96 to 12.92 μm • Bin 21: 12.92 to 15.23 μm • Bin 22: 15.23 to 17.96 μm • Bin 23: 17.96 to 21.17 μm • Bin 24: 21.17 to 24.96 μm • Bin 25: 24.96 to 29.43 μm • Bin 26: 29.43 to 34.70 μm

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

The luminosity function for different morphological types in the CfA Redshift Survey

We derive the luminosity function for different morphological types in the original CfA Redshift Survey (CfA1) and in the first two slices of the CfA Redshift Survey Extension (CfA2). CfA1 is a complete sample containing 2397 galaxies distributed over 2.7 steradians with m(sub z) less than or equal 14.5. The first two complete slices of CfA2 contain 1862 galaxies distributed over 0.42 steradians with m(sub z)=15.5. The shapes of the E-S0 and spiral luminosity functions (LF) are indistinguishable. We do not confirm the steeply decreasing faint end in the E-S0 luminosity function found by Loveday et al. for an independent sample in the southern hemisphere. We demonstrate that incomplete classification in deep redshift surveys can lead to underestimates of the faint end of the elliptical luminosity function and could be partially responsible for the difference between the CfA survey and other local field surveys. The faint end of the LF for the Magellanic spirals and irregulars is very steep. The Sm-Im luminosity function is well fit by a Schechter function with M*=-18.79, alpha=-1.87, and phi*=0.6x10(exp -3) for M(sub z) less than or equal to -13. These galaxies are largely responsible for the excess at the faint end of the general CfA luminosity function. The abundance of intrinsically faint, blue galaxies nearby affects the interpretation of deep number counts. The dwarf population increases the expected counts at B=25 in a no-evolution, q(sub 0)=0.05 model by a factor of two over standard no-evolution estimates. These dwarfs change the expected median redshift in deep redshift surveys by less than 10 percent . Thus the steep Sm-Im LF may contribute to the reconciliation of deep number counts with deep redshift surveys.

Marzke, Ronald O.↗
DOE OSTI2026

Toward memory-efficient melt pool monitoring: a classification framework using event-based imaging and sparse sensing technique

Vision sensors like CMOS and CCD cameras are often used for in-process monitoring of melt pools in laser-based additive and welding processes, but they require transferring large amounts of data and computational processing resources. Event-based neuromorphic imagery, on the other hand, detects only the change in pixel intensity, thus potentially reducing the data amount and latency. With an event imager, this study develops a framework for melt pool condition classification, including image construction, time scale selection, optimal pixel selection, and sparse classification, to achieve a highly memory-efficient scheme. These are based on sparse sensing techniques with singular value decomposition (SVD) and QR pivoting, the two fundamental matrix transformations for linear dimensionality reduction. The framework is then validated by classifying a controlled experiment by exciting various mode shapes of liquid gallium pools of varying depths (3, 6, and 8 mm). At 200 pixels, the classifier can reach overall accuracy of 75%, while at 2000 pixels (0.013% of the total possible pixels), the accuracy is nearly 90% (89.86%). At the same number of pixels, random selection can only achieve 46% and 67%, respectively. The memory savings of the sparsely sampled event data compared to a conventional imager is about 500 times. In addition to performance, implementation and limitations of the framework are also discussed.

42 ENGINEERING↗
NASA NTRS1986

Stratospheric dust collections: Valuable resources for space and atmospheric scientists

The stratospheric collection at the Johnson Space Center Curatorial Facility offers a unique opportunity to study well-documented, individual particles (or groups of particles) from a wide variety of sources. The nature of the collection and curation process, as well as the timeliness of some sampling periods, ensures that all data obtained from stratospheric particles is a valuable resource for scientists from a wide range of disciplines. A few samples of the uses of these stratospheric dust collections are outlined. An understanding of global parameters at a particular point in time in the stratosphere can be obtained from a study of complete collection surfaces. For example, an accurate assessment of particle concentration over a wide range of sizes was experimentally determined for the stratospheric cloud formed one month after the eruption of El Chichon. Additional studies on the El Chichon cloud over a six-month period showed that volcanic ash settles out of the stratosphere at a rate determined primarily by particle shape and density. Another study during a volcanically quiescent period has shown that total particle number density during the summer of 1981 was approx. 2.7 x 10(-1) cm(-3), for particles 1 micron diameter. However, 95% of these particles were 5 micrometers diameter. With the above classification scheme, an estimate of micrometeorite number density at 20km altitude can also be made. Continuation of these types of studies, for shorter collection periods at regular intervals, can provide important experimental data on the contributions of orbital debris, rocket firings and transient events on the total stratospheric particle budget.

Mackinnon, I. D. R.↗
NASA NTRS1990

Coronae on Venus - Morphology, classification, and distribution

Venera 15/16 radar images of Venus show two circular features having no analog among the terrestrial planets: 21 coronae, which have a complex interior zone, and 11 corona-like features, which lack the ridge annuli of the coronae. Each of these two groups of features is subdivisible into three classes; coronae may be symmetrical, asymmetrical, and subdued, while corona-like structures are double, irregular, and heart-shaped. The various classes of both types of classes are interpreted as having a similar mode of origin, namely the uplift and volcanism generated by a thermal anomaly at depth, followed by gravitational relaxation.

Pronin, A. A.↗
DOE OSTI2018

Chaotic edge density fluctuations in the Alcator C-Mod tokamak

Analysis of the time series obtained with the O-Mode reflectometer [Rhodes et al., 1997 Plasma Phys. Controlled Fusion 40, 493–510 (1998)] and the gas puff imaging [Cziegler et al., Phys. Plasmas 17(5), 056120 (2010)] systems on the Alcator C-Mod tokamak reveals that the turbulent edge density fluctuations are chaotic. Supporting evidence for this conclusion includes the observation of exponential power spectra (which is associated with Lorentzian-shaped pulses in the time series), the population of the corresponding Bandt-Pompe probability distributions [Bandt and Pompe, Phys. Rev. Lett. 88, 174102 (2002)], and the location of the signal on the complexity-entropy plane (C-H plane) [Rosso et al., Phys. Rev. Lett. 99, 154102 (2007)]. The classification of edge turbulence as chaotic opens the door for further work to understand the underlying process and the impact on turbulent transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Underwater unexploded ordnance discrimination based on intrinsic target polarizabilities – A case study

Seabed unexploded ordnance that resulted partly from the high failure rate among munitions from more than 80 years ago and from decades of military training and testing of weapons systems poses an increasing concern all around the world. Although existing magnetic systems can detect clusters of debris, they are not able to tell whether a munition is still intact requiring special removal (e.g. in situ detonation) or is harmless scrap metal. The marine environment poses unique challenges, and transferring knowledge and approaches from land to a marine environment has not been easy and straightforward. On land, the background soil conductivity is much lower than the conductivity of the unexploded ordnance and the electromagnetic response of a target is essentially the same as that in free space. For those frequencies required for target characterization in the marine environment, the seawater response must be accounted for and removed from the measurements. The system developed for this study uses fields from three orthogonal transmitters to illuminate the target and four three-component receivers to measure the signal arranged in a configuration that inherently cancels the system's response due to the enclosing seawater, the sea–bottom interface and the air–sea interface for shallow deployments. The system was tested as a cued system on land and underwater in San Francisco Bay – it was mounted on a simple platform on top of a support structure that extended 1 m below and allowed the diver to place metal objects to a specific location even in low-visibility conditions. The measurements were stable and repeatable. Furthermore, target responses estimated from marine measurements matched those from land acquisition, confirming that the seawater and air–sea interface responses were removed successfully. Thirty-six channels of normalized induction responses were used for the classification, which was done by estimating the target principal dipole polarizabilities. Our results demonstrated that the system can resolve the intrinsic polarizabilities of the target, with clear distinctions between those of symmetric intact unexploded ordnance and irregular scrap metal. The prototype system was able to classify an object based on its size, shape and metal content and correctly estimate its location and orientation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1975

Quantitative models of magnetic and electric fields in the magnetosphere

In order to represent the magnetic field B in the magnetosphere various auxiliary functions can be used: the current density, the scalar potential, toroidal and poloidal potentials, and Euler potentials -- or else, the components of B may be expanded directly. The most versatile among the linear representations is the one based on toroidal and poloidal potentials; it has seen relatively little use in the past but appears to be the most promising one for future work. Other classifications of models include simple testbed models vs. comprehensive ones and analytical vs. numerical representations. The electric field E in the magnetosphere is generally assumed to vary only slowly and to be orthogonal to B, allowing the use of a scalar potential which may be deduced from observations in the ionosphere, from the shape of the plasmapause, or from particle observations in synchronous orbits.

Stern, D. P.↗
NASA NTRS1984

Hyperbolic umbilic diffraction catastrophe and rainbow scattering from spheroidal drops

Short-wavelength scattering from drops whose shapes closely approximate that of an oblate spheroid with a vertical short or symmetry axis have been studied. The drops were illuminated by a horizontally propagating gaussian beam with a wavelength of 633 nm. The drops were observed to scatter in the horizontal rainbow region with patterns like those of hyperbolic-umblic (classification D4(+)) diffraction catastrophes. Visible D4(+) diffraction patterns observed previously include light transmitted by frosted glass surfaces and by liquid lenses clinging to tilted glass plates.

Marston, P. L.↗
NASA NTRS2012

Characterization of Hayabusa II Target Asteroid (162173) 1999 JU3

The Japanese Hayabusa II mission is planned to rendezvous with and return a sample from the near-Earth asteroid (162173) 1999 JU3. Previous mid-infrared studies have constrained the albedo and thermal properties of this object (Muller et al. 2011; Campins et al. 2011; Hasegawa et al. 2008). Visible wavelength spectra from 1999 and 2007 reveal a C-type asteroid that displays pronounced spectroscopic variability around 0.7 microns. Variability in the strength of a 0.7 micron band could be due to heterogeneous concentrations of iron-bearing phyllosilicates across its surface (Vilas 2008). We will present new observations from the favorable 2012 apparition to further characterize this object. In June of 2012 spectroscopic observations were conducted with the LDSS3 and FIRE instruments on the Magellan telescopes at Las Campanas Observatory in Chile. Between April and July of 2012 broadband visible-wavelength photometry was obtained with the Tenagra II telescope in Arizona and with the IMACS, Megacam and LDSS3 instruments on the Magellan telescopes. Our visible and near-infrared spectra confirm a C-type taxonomic classification, but do not show evidence for the presence of a 0.7 micron phyllosilicate band. Our time series of visible spectra cover approximately 60% of the rotational phases of 1999 JU3, but do not display any pronounced variability. We use our new optical light curves, combined with photometry from 2007, to refine a shape model of the asteroid. This shape model provides a means for mapping surface regions accessed by the spectroscopic observations from both 2007 and 2012, and thus to directly address the possibility of surface heterogeneity. This surface map, in conjunction with the newly measured photometric phase curve of the asteroid, will be used to make predictions regarding composition and surface properties that will ultimately be tested upon arrival of the Hayabusa II spacecraft.

Moskovitz, Abe↗
DOE OSTI2026

NanoPSD: A software for automatic detection of Nano-Particle Shape Distribution in electron microscopy images

Accurate quantification of the size and morphology of nanoparticles from electron microscopy (EM) images is essential to understand growth mechanisms, surface reactivity, and functional behavior in nanoscale materials. Manual analysis remains slow, subjective, and difficult to reproduce in large datasets. We introduce NanoPSD (Nano-Particle Shape Distribution), an open-source and fully automated framework for quantitative particle detection and morphology analysis from EM images. NanoPSD integrates adaptive contrast enhancement, polarity-agnostic scale-bar detection, Optical Character Recognition (OCR)-based calibration, and classical segmentation via Otsu thresholding with morphological refinement. Particle contours are used to extract geometric descriptors, including equivalent circular diameter, aspect ratio, circularity, and solidity, enabling automated classification into spherical, rod-like, and aggregate morphologies. The framework supports both single-image and batch processing, generating publication-quality visualizations, LaTeX-ready tables, and structured comma-separated values (CSV) datasets. As a demonstration, we applied NanoPSD to plasma-synthesized nanoparticle samples diagnosed via transmission electron microscopy (TEM). The code produced statistically robust size and morphology distributions spanning a few to tens of nanometers with minimal user supervision. The pipeline demonstrates high reproducibility and scalability, processing large image collections with consistent calibration and output formatting. Its modular design enables seamless integration of future deep-learning-based segmentation models, providing a pathway toward intelligent, data-driven electron microscopy analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Demonstration of object location, classification, and characterization by developed deep learning dust ablation trail analysis code package using plasma jets

Based on deep learning, a Dust Ablation Trail Analysis (DATA) code package is developed to detect dust ablation trails in tokamaks, which is intended to analyze a large amount data of tokamak dusts. To validate and benchmark the DATA code package, 2440 plasma jet images are exploited for the training and test of the deep learning DATA code package, since plasma jets resemble the shape and size of dust ablation clouds in tokamaks. After being trained by 1920 plasma jet images, the DATA code package is able to locate 100% plasma jets, classify plasma jets with the accuracy of >99.9%, and output image skeleton information for classified plasma jets. The DATA code package trained by the plasma jet images is also used to analyze the dust ablation trails captured in the Experimental Advanced Superconducting (EAST) tokamak with the satisfactory performance, further verifying its applicability in the fusion dust ablation investigation. Based on its excellent performance presented here, it is demonstrated that our DATA code package is able to automatically identify and analyze dust ablation trails in tokamaks, which can be used for further detailed investigations, such as the three-dimensional reconstruction of dusts and their ablation trails.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

A Review of Current and Prospective Factors for Classification of Civil Unmanned Aircraft Systems

While progress is being made on integrating unmanned aircraft systems (UAS) into our national airspace on a broad scale, much work remains to establish appropriate certification standards and operational procedures, particularly with respect to routine commercial operations. This paper summarizes research to examine the extent to which today's civil aircraft taxonomy applies to UAS, and, if needed, how that taxonomy could be amended to better cover different UAS designs and operations. Factors that shape the current taxonomy, as defined in the Federal Aviation Regulations, were assessed for applicability to UAS, potential incompatibilities were identified, and additional factors were proposed that might be useful for an updated aircraft taxonomy intended to cover UAS. The results suggest the possibility of constructing new groups in the taxonomy for UAS under a restricted category that share common airworthiness standards. Establishing distinct groups for UAS and associated standards that enable low risk operations for compensation or hire could be a timely step toward full integration. Such a step would allow the civil aviation industry and regulators to gain valuable experience with UAS while carefully controlling access and potential harm to the aviation system as a whole.

Hayhurst, Kelly J.↗
DOE OSTI2015

Forensic Applicability of Femur Subtrochanteric Shape to Ancestry Assessment in Thai and White American Males

Abstract Ancestry assessment from the postcranial skeleton presents a significant challenge to forensic anthropologists. However, metric dimensions of the femur subtrochanteric region are believed to distinguish between individuals of Asian and non‐Asian descent. This study tests the discriminatory power of subtrochanteric shape using modern samples of 128 Thai and 77 White American males. Results indicate that the samples' platymeric index distributions are significantly different ( p ≤ 0.001), with the Thai platymeric index range generally lower and the White American range generally higher. While the application of ancestry assessment methods developed from Native American subtrochanteric data results in low correct classification rates for the Thai sample (50.8–57.8%), adapting these methods to the current samples leads to better classification. The Thai data may be more useful in forensic analysis than previously published subtrochanteric data derived from Native American samples. Adapting methods to include appropriate geographic and contemporaneous populations increases the accuracy of femur subtrochanteric ancestry methods.

Tallman, Sean D.↗
DOE OSTI2016

WE-AB-209-05: Development of an Ultra-Fast High Quality Whole Breast Radiotherapy Treatment Planning System

Purpose: To enable near-real-time (<20sec) and interactive planning without compromising quality for whole breast RT treatment planning using tangential fields. Methods: Whole breast RT plans from 20 patients treated with single energy (SE, 6MV, 10 patients) or mixed energy (ME, 6/15MV, 10 patients) were randomly selected for model training. Additional 20 cases were used as validation cohort. The planning process for a new case consists of three fully automated steps:1. Energy Selection. A classification model automatically selects energy level. To build the energy selection model, principle component analysis (PCA) was applied to the digital reconstructed radiographs (DRRs) of training cases to extract anatomy-energy relationship.2. Fluence Estimation. Once energy is selected, a random forest (RF) model generates the initial fluence. This model summarizes the relationship between patient anatomy’s shape based features and the output fluence. 3. Fluence Fine-tuning. This step balances the overall dose contribution throughout the whole breast tissue by automatically selecting reference points and applying centrality correction. Fine-tuning works at beamlet-level until the dose distribution meets clinical objectives. Prior to finalization, physicians can also make patient-specific trade-offs between target coverage and high-dose volumes.The proposed method was validated by comparing auto-plans with manually generated clinical-plans using Wilcoxon Signed-Rank test. Results: In 19/20 cases the model suggested the same energy combination as clinical-plans. The target volume coverage V100% was 78.1±4.7% for auto-plans, and 79.3±4.8% for clinical-plans (p=0.12). Volumes receiving 105% Rx were 69.2±78.0cc for auto-plans compared to 83.9±87.2cc for clinical-plans (p=0.13). The mean V10Gy, V20Gy of the ipsilateral lung was 24.4±6.7%, 18.6±6.0% for auto plans and 24.6±6.7%, 18.9±6.1% for clinical-plans (p=0.04, <0.001). Total computational time for auto-plans was < 20s. Conclusion: We developed an automated method that generates breast radiotherapy plans with accurate energy selection, similar target volume coverage, reduced hotspot volumes, and significant reduction in planning time, allowing for near-real-time planning.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2010

New Neighbours: Modelling the Growing Population of gamma-ray Millisecond Pulsars

The Fermi Large Area Telescope, in collaboration with several groups from the radio community. have had marvelous success at uncovering new gamma-ray millisecond pulsars (MSPs). In fact, MSPs now make up a sizable fraction of the total number of known gamma-ray pulsars. The MSP population is characterized by a variety of pulse profile shapes, peak separations, and radio-to-gamma phase lags, with some members exhibiting nearly phase-aligned radio and gamma-ray light curves (LCs). The MSPs' short spin periods underline the importance of including special relativistic effects in LC calculations, even for emission originating from near the stellar surface. We present results on modelling and classification of MSP LCs using standard pulsar model geometries.

Venter, C.↗
NASA NTRS1993

A new clustering algorithm applicable to multispectral and polarimetric SAR images

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

Wong, Yiu-Fai↗
DOE OSTI2020

Deep Learning for Automated Identification of Eels in Sonar Data

Freshwater eels, such as the American eel (Anguilla rostrata) present numerous challenges related to safe downstream fish passage at hydroelectric facilities. One of those challenges is effective monitoring of their abundance, movements, and behavior to facilitate design and operation of eel protection and passage facilities. A previous EPRI study documented the ability of human analysts to reliably identify American eels in data obtained with a 1100/1800 kHz, multibeam sonar. This report describes a project to develop deep learning (a subset of artificial intelligence) tools to automate the time-consuming, subjective process of eel identification in multibeam sonar data. The project exploited new data collected in the laboratory and the existing data from the prior EPRI field study to develop and test deep learning and other data analytic tools, including wavelet filtering, differencing for static object removal, and convolutional neural network analysis. The analysis of the laboratory data demonstrated feasibility of the approach, revealed object characteristics observed with the sonar that distinguish eels from similarly sized and shaped acoustic targets, and provided additional data for algorithm selection and training. Deep learning algorithms trained and tested on the laboratory data alone achieved accuracy rates of greater than 98% when classifying acoustic images of eels and similar-sized neutrally buoyant sticks. The algorithm trained and tested on the pre-existing field data alone, and yielded classification accuracy of 9.3% false positives and 13.3% false negatives when distinguishing between eels and sticks/PVC pipes based on video clips (i.e., multiple, consecutive images). This performance is comparable to the classification accuracy achieved by human analysts in the prior study. The deep learning algorithm trained on a combination of video clips obtained in the laboratory and the field and tested on video clips from the field, was able to distinguish eels from sticks and PVC pipes (a river debris analog) of similar size with 100% accuracy. Outreach to the hardware, software, and end-user communities early in the project helped to identify needs and specify the application space. Outreach to those communities at the end of the project communicated project results and opportunities for further development. The project achieved proof of concept for automated identification of eel in multibeam sonar data. Future work should focus on acquisition of additional data for more robust algorithm training and testing; modification of the software tools to accommodate multiple acoustic targets in the acoustic field at a given time; identification of additional object classes; incorporation of motion in the object identification and classification algorithms; operationalizing the software tools, including integration with other existing sonar data analysis tools; and partnering with hardware and software providers for distribution of the software tools with their commercial products.

13 HYDRO ENERGY↗