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DOE OSTI2022

Detecting anomalous sequences in electronic health records using higher-order tensor networks

Detecting anomalous sequences is an integral part of building and protecting modern large-scale health information technology (HIT) systems. These HIT systems generate a large volume of records of patients’ state and significant events, which provide a valuable resource to help improve clinical decisions, patient care processes, and other issues. However, detecting anomalous sequences in electronic health records (EHR) remains a challenge in healthcare applications for several reasons, including imbalances in the data, complexity of relationships between events in the sequence, and the curse of dimensionality. Conventional anomaly detection methods use the finite sequence of events to discriminate sequences. They fail to incorporate salient event details under variable higher-order dependencies (e.g., duration between events) that can provide better discrimination of sequences in their models. To address this problem, we propose event sequence and subsequence anomaly detection algorithms that (1) use network-based representations of interactions in the data, (2) account for variable higher-order dependencies in the data, and (3) incorporate events duration for adequate discrimination of the data. The proposed approach identifies anomalies by monitoring the change in the graph after the test sequence is removed from the network. The change is quantified using graph distance metrics so that dramatic changes in the network can be attributed to the removed sequence. Furthermore, the proposed subsequence algorithm recommends plausible paths and salient information for the detected anomalous subsequences. Our results show that the proposed event sequence anomaly detection algorithm outperforms the baseline methods for both synthetic data and real-world EHR data.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS2022

Rapid Glacier Retreat Rates Observed in West Antarctica

The Pope, Smith, and Kohler glaciers, in the Amundsen Sea Embayment of West Antarctica, have experienced enhanced ocean-induced ice-shelf melt, glacier acceleration, ice thinning, and grounding line retreat in the past thirty years. Here we present observations of the grounding line retreat of these glaciers since 2014 using a constellation of interferometric radar satellites combined with precision surface elevation data. We find that the grounding lines develop spatially-variable, kilometre-scale, tidally-induced migration zones. After correction for tidal effects, we detect a sustained pattern of retreat coincident with high melt rates of un-grounded ice, marked by episodes of more rapid retreat. In 2017, Pope Glacier retreated 3.5 km in 3.6 months, or 11.7 km/yr. In 2016-2018, Smith West retreated at 2 km/yr and Kohler at 1.3 km/yr. While the retreat slowed down in 2018-2020, these retreat rates are faster than anticipated by numerical models on yearly time scales. We hypothesize that the rapid retreat is caused by un-represented, vigorous ice-ocean interactions acting within newly-formed cavities at the ice-ocean boundary.

Climate change↗

DOE OSTI2025

Unsupervised Process Anomaly Detection and Identification Using the Leave-One-Variable-Out Approach

Automated anomaly detection and identification can signal equipment issues and pinpoint causes in large-scale industrial systems. For systems with limited failure history, unsupervised machine learning methods can be utilized as they do not require past failures. This study introduces the leave-one-variable-out (LOVO) model, which masks one variable at a time to predict the others, learning underlying process correlations. Detection performance was assessed with synthetic and experimental data, while identification performance used only synthetic data due to its ability to generate labeled anomaly types. For detection using synthetic data, the LOVO model generally outperformed comparative models; while using experimental data, the comparative methods outperformed the LOVO model. However, the comparative methods required selecting a latent size, and these conclusions pertain to using the optimal size. In practice, it would not be feasible to always select the optimal value, and incorrect selections impacted performance. In contrast, the LOVO model does not require a latent space. For identification using synthetic data, the LOVO model was slightly outperformed in interpretability and repeatability but still demonstrated impressive results. These outcomes suggest that the LOVO model is an effective model and may be more easily implemented without the challenging tuning process of selecting a latent size.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

3D Localization of Defects in Facility Inspection

Wind tunnels are crucial facilities that support the aerospace industry. However, these facilities are large, complex, and pose unique maintenance and inspection requirements. Manual inspections to identify defects such as cracks, missing fasteners, leaks, and foreign objects are important but labor and schedule intensive. Our goal is to utilize small Unmanned Aircraft Systems (sUAS) and computer vision-based analysis to automate the inspection of the interior and exterior of NASA’s critical wind tunnel facilities. We detect missing fasteners as our defect class, and detect existing fasteners to provide potential future missing fastener sites for preventative maintenance. These detections are done on both 2D raw images and in 3D space to provide a visual reference and real world location to facilitate repairs. A dataset was created consisting of images taken along a grid-like pattern of an interior tunnel section in the AEDC National Full-Scale Aerodynamics Complex (NFAC) at NASA Ames Research Center. Our method uses object detection to create image level bounding boxes of the fasteners and missing fasteners, then uses photogrammetry to create a mapping from 2D image locations to 3D real world locations. The image level bounding boxes and the 2D to 3D mapping are then combined to determine the 3D location of the defects. We describe the data collection, photogrammetry, and computer vision techniques used for object detection as well as a quantitative analysis of the method.

Small Unmanned Aircraft Systems (sUAS)↗

DOE OSTI2017

PVT Degradation Studies: NMR Analysis

Under certain environmental conditions, polyvinyl toluene (PVT) plastic scintillator has been observed to undergo internal fogging. Nuclear magnetic resonance spectroscopy has been used to elucidate the state of water inside the PVT. The deuterium NMR results show that water absorbed by PVT under warm, humid conditions enters several distinct environments, and when the PVT is transferred from incubation to ambient temperature and humidity the water is lost on a time scale of a few hours from these samples. Most of the deuterium NMR peaks can be assigned to bulk liquid water, but almost 35% of the detected signal intensity is contained in a resonance that resembles spectra of water contained in nanometer-scale pores in mesoporous carbon.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

A search for warm/hot gas filaments between pairs of SDSS Luminous Red Galaxies

Abstract We search the Planck data for a thermal Sunyaev–Zel’dovich (tSZ) signal due to gas filaments between pairs of Luminous Red Galaxies (LRGs) taken from the Sloan Digital Sky Survey Data Release 12 (SDSS/DR12). We identify ∼260 000 LRG pairs in the DR12 catalogue that lie within 6–10 $h^{-1} \, \mathrm{Mpc}$ of each other in tangential direction and within 6 $h^{-1} \, \mathrm{Mpc}$ in radial direction. We stack pairs by rotating and scaling the angular positions of each LRG so they lie on a common reference frame, then we subtract a circularly symmetric halo from each member of the pair to search for a residual signal between the pair members. We find a statistically significant (5.3σ) signal between LRG pairs in the stacked data with a magnitude Δy = (1.31 ± 0.25) × 10−8. The uncertainty is estimated from two Monte Carlo null tests which also establish the reliability of our analysis. Assuming a simple, isothermal, cylindrical filament model of electron overdensity with a radial density profile proportional to rc/r (as determined from simulations), where r is the perpendicular distance from the cylinder axis and rc is the core radius of the density profile, we constrain the product of overdensity and filament temperature to be $\delta _\mathrm{ c} \times (T_{\rm e}/10^7 \, {\rm K}) \times (r_\mathrm{ c}/0.5h^{-1} \, {\rm Mpc}) = 2.7 \pm 0.5$. To our knowledge, this is the first detection of filamentary gas at overdensities typical of cosmological large-scale structure. We compare our result to the BAHAMAS suite of cosmological hydrodynamic simulations (McCarthy et al. 2017) and find a slightly lower, but marginally consistent Comptonization excess, Δy = (0.84 ± 0.24) × 10−8.

Tanimura, Hideki↗

DOE OSTI2024

Report from the Workshop on Xenon Detector $0\nu\beta\beta$ Searches: Steps Towards the Kilotonne Scale

These proceedings summarize the program and discussions of the ``Workshop on Xenon Detector $0\nu\beta\beta$ Searches: Steps Towards the Kilotonne Scale'' held on October 25-27 2023 at SLAC National Accelerator Laboratory. This workshop brought together experts from the communities of neutrinoless double-beta decay and dark matter detection, to discuss paths forward for the realization of monolithic experiments with xenon approaching the kilotonne scale.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

How to detect lensing rotation

Gravitational lensing rotation of images is predicted to be negligible at linear order in density perturbations, but can be produced by the post-Born lens-lens coupling at second order. This rotation is somewhat enhanced for Cosmic Microwave Background (CMB) lensing due to the large source path length, but remains small and very challenging to detect directly by CMB lensing reconstruction alone. We show the rotation may be detectable at high significance as a cross-correlation signal between the curl reconstructed with Simons Observatory (SO) or CMB-S4 data, and a template constructed from quadratic combinations of large-scale structure (LSS) tracers. Equivalently, the lensing rotation-tracer-tracer bispectrum can also be detected, where LSS tracers considered include the CMB lensing convergence, galaxy density, and the Cosmic Infrared Background (CIB), or optimal combinations thereof. We forecast that an optimal combination of these tracers can probe post-Born rotation at the level of 5.7σ–6.1σ with SO and 13.6σ–14.7σ for CMB-S4, depending on whether standard quadratic estimators or maximum a posteriori iterative methods are deployed. We also show possible improvement up to 21.3σ using a CMB-S4 deep patch observation with polarization-only iterative lensing reconstruction. However, these cross-correlation signals have non-zero bias because the rotation template is quadratic in the tracers, and exists even if the lensing is rotation free. We estimate this bias analytically, and test it using simple null-hypothesis simulations to confirm that the bias remains subdominant to the rotation signal of interest. Detection and then measurement of the lensing rotation cross-spectrum is therefore a realistic target for future observations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

All-electrical detection of spin dynamics in magnetic antidot lattices by the inverse spin Hall effect

The understanding of spin dynamics in laterally confined structures on sub-micron length scales has become a significant aspect of the development of novel magnetic storage technologies. Numerous ferromagnetic resonance measurements, optical characterization by Kerr microscopy and Brillouin light scattering spectroscopy and x-ray studies were carried out to detect the dynamics in patterned magnetic antidot lattices. Here, we investigate Oersted-field driven spin dynamics in rectangular Ni80Fe20/Pt antidot lattices with different lattice parameters by electrical means. When the system is driven to resonance, a dc voltage across the length of the sample is detected that changes its sign upon field reversal, which is in agreement with a rectification mechanism based on the inverse spin Hall effect. Furthermore, we show that the voltage output scales linearly with the applied microwave drive in the investigated range of powers. Lastly, our findings have direct implications on the development of engineered magnonics applications and devices.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Time-frequency based cyber security defense of wide-area control system for fast frequency reserve

Global power systems are transiting from conventional fossil fuel energy to renewable energies due to their environmental benefits. The increasing penetration of renewable energies presents challenges for power system operation. The efficiency and sufficiency of responsive reserves have become increasingly important for power systems with a high proportion of renewable energies. The Fast Frequency Reserve (FFR), especially the Wide-area Monitoring System (WAMS)-based FFR, is a promising and effective solution to secure and enhance the stability of power systems. However, cyber security has become a new challenge for the WAMS-based FFR system. Cyber attacks on the FFR control system may threaten the safety of power system operation due to the rapid power controllability requirement of FFR. Therefore, to address this problem, a time-frequency based cyber security defense framework is proposed to detect the cyber spoofing of synchrophasor data in WAMS-based FFR control systems. This paper first introduces the Continuous Wavelet Transforms (CWTs) to decompose spoofing signals. Then, the Dual-frequency Scale Convolutional Neural Networks (DSCNN) is proposed to identify the time-frequency domains matrix from two frequency scales. Integrating CWTs and DSCNN, an identification framework called CWTs-DSCNN is further proposed to detect the spoofing attacks in the WAMS-based FFR system. Multiple experiments using the actual data from FNET/GridEye are performed to verify the effectiveness of the framework in securing WAMS-based FFR systems.

25 ENERGY STORAGE↗

DOE OSTI2023

Synthesis and processing of lithium-loaded plastic scintillators on the kilogram scale

Plastic scintillators that can discriminate between gamma rays, fast neutrons, and thermal neutrons were synthesized and characterized while considering the performance at the kilogram scale. The synthesis and processing of these plastic scintillators on the kilogram scale required examination of several factors. The examination of these factors was necessitated by the inclusion of 0.1 wt.% lithium-6 to enable detection of thermal neutrons. First, methacrylic acid was used as an additive to solubilize salts of lithium-6, which allow for a thermal-neutron capture reaction that produces scintillation light following energy transfer. Second, a trade-off between scintillation performance and processability was considered because the increasing content of the methacrylic acid that aided processability resulted in a sharp decrease in the light output. The use of small amounts of methacrylic acid (≤3 wt.%) resulted in better performance but required high processing temperatures. At large scales, these high temperatures could initiate exothermic polymerization that results in premature curing and/or defects. Additionally, the deleterious effects of the methacrylic acid may be mitigated by using m-terphenyl as a primary dye rather than 2,5-diphenyloxazole (PPO), which has been traditionally used in organic scintillators. Finally, the curing environment was controlled to avoid defects like cracking and discolouration while maintaining solubility of dopants during curing. For scintillators that were produced from kilogram-scale batches of precursors, the effective attenuation of scintillation light was characterized.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Optimal filters for the moving lens effect

We assess the prospects for detecting the moving lens effect using cosmological surveys. The bulk motion of cosmological structure induces a small-scale dipolar temperature anisotropy of the cosmic microwave radiation, centered around halos and oriented along the transverse velocity field. We introduce a set of optimal filters for this signal and forecast that a high significance detection can be made with upcoming experiments. We discuss the prospects for reconstructing the bulk transverse velocity field on large scales using matched filters, finding good agreement with previous work using quadratic estimators.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Overcoming Communications Outages in Inverter Downtime Analysis: Preprint

Inverters are often reported to be the highest-impact failure point in PV systems. This importance is belied by the simplistic assumptions about inverter downtime losses used in industrial energy modeling. Energy models often assume the extent of inverter-related losses is limited to 1% of annual production from scheduled inverter preventative maintenance. In reality, inverter-related production losses are much more variable, although data from large-scale surveys of fielded systems are rare. Here we present a method of detecting inverter downtime events and estimating the associated lost production using inverter- and meter-level power data. Because communications outages are of similar frequency to true production outages, the method pays particular attention to distinguishing communications outages from true production outages. The results of applying the method at fleet-scale are presented and discussed.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2020

Online Event Detection in Synchrophasor Data with Graph Signal Processing

Online detection of anomalies is crucial to enhancing the reliability and resiliency of power systems. We propose a novel data-driven online event detection algorithm with synchrophasor data using graph signal processing. In addition to being extremely scalable, our proposed algorithm can accurately capture and leverage the spatio-temporal correlations of the streaming PMU data. This paper also develops a general technique to decouple spatial and temporal correlations in multiple time series. Finally, we develop a unique framework to construct a weighted adjacency matrix and graph Laplacian for product graph. Case studies with real-world, large-scale synchrophasor data demonstrate the scalability and accuracy of our proposed event detection algorithm. Compared to the state-of-the-art benchmark, the proposed method not only achieves higher detection accuracy but also yields higher computational efficiency.

Event detection↗

DOE OSTI2020

Online Event Detection in Synchrophasor Data with Graph Signal Processing

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

Improved twin detection via tracking of individual Kikuchi band intensity of EBSD patterns

Twin detection via EBSD can be particularly challenging due to the fine scale of certain twin types – for example, compression and double twins in Mg. Even when a grid of sufficient resolution is chosen to ensure scan points within the twins, the interaction volume of the electron beam often encapsulates a region that contains both the parent grain and the twin, confusing the twin identification process. The degradation of the EBSD pattern results in a lower image quality metric, which has long been used to imply potential twins. However, not all bands within the pattern are degraded equally. This paper exploits the fact that parent and twin lattices share common planes that lead to the quality of the associated bands not degrading; i.e. common planes that exist in both grains lead to bands of consistent intensity for scan points adjacent to twin boundaries. Hence, twin boundaries in a microstructure can be recognized, even when they are associated with thin twins. Proof of concept was performed on known twins in Inconel 600, Tantalum, and Magnesium AZ31. This method was then used to search for undetected twins in a Mg AZ31 structure, revealing nearly double the number of twins compared with those initially detected by standard procedures.

47 OTHER INSTRUMENTATION↗

NASA NTRS1990

Local gravity and large-scale structure

The magnitude and direction of the observed dipole anisotropy of the galaxy distribution can in principle constrain the amount of large-scale power present in the spectrum of primordial density fluctuations. This paper confronts the data, provided by a recent redshift survey of galaxies detected by the IRAS satellite, with the predictions of two cosmological models with very different levels of large-scale power: the biased Cold Dark Matter dominated model (CDM) and a baryon-dominated model (BDM) with isocurvature initial conditions. Model predictions are investigated for the Local Group peculiar velocity, v(R), induced by mass inhomogeneities distributed out to a given radius, R, for R less than about 10,000 km/s. Several convergence measures for v(R) are developed, which can become powerful cosmological tests when deep enough samples become available. For the present data sets, the CDM and BDM predictions are indistinguishable at the 2 sigma level and both are consistent with observations. A promising discriminant between cosmological models is the misalignment angle between v(R) and the apex of the dipole anisotropy of the microwave background.

Juszkiewicz, Roman↗

DOE OSTI2019

Numerical study of the temperature dependence of the NMR relaxation rate across the superfluid–Bose glass transition in one dimension

Here, we study the nuclear magnetic resonance (NMR) spin-lattice relaxation rate 1/ T 1 1 in random one-dimensional spin chains as a function of the temperature and disorder strength. In the zero temperature limit, the system displays a disorder-induced quantum phase transition between a critical Tomonaga-Luttinger liquid (TLL) phase and a localized Bose glass phase. The 1/ T 1 is investigated across this transition using large-scale simulations based on matrix product state techniques. We find that this quantity can detect the transition and probe the value of the dimensionless TLL parameter K . We also compute the NMR relaxation rate distributions for each temperature and disorder strength considered. In particular, we discuss the applicability of the stretched exponential fit to the return-to-equilibrium function to extract the 1/ T 1 experimentally. The results presented here should provide valuable insights in regards of future NMR experiments in realistic disordered spin compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗