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At least 127 records · Page 7

Creative Analytics of Mission Ops Event Messages

Historically, tremendous effort has been put into processing and displaying mission health and safety telemetry data; and relatively little attention has been paid to extracting information from missions time-tagged event log messages. Todays missions may log tens of thousands of messages per day and the numbers are expected to dramatically increase as satellite fleets and constellations are launched, as security monitoring continues to evolve, and as the overall complexity of ground system operations increases. The logs may contain information about orbital events, scheduled and actual observations, device status and anomalies, when operators were logged on, when commands were resent, when there were data drop outs or system failures, and much much more. When dealing with distributed space missions or operational fleets, it becomes even more important to systematically analyze this data. Several advanced information systems technologies make it appropriate to now develop analytic capabilities which can increase mission situational awareness, reduce mission risk, enable better event-driven automation and cross-mission collaborations, and lead to improved operations strategies: Industry Standard for Log Messages. The Object Management Group (OMG) Space Domain Task Force (SDTF) standards organization is in the process of creating a formal standard for industry for event log messages. The format is based on work at NASA GSFC. Open System Architectures. The DoD, NASA, and others are moving towards common open system architectures for mission ground data systems based on work at NASA GSFC with the full support of the commercial product industry and major integration contractors. Text Analytics. A specific area of data analytics which applies statistical, linguistic, and structural techniques to extract and classify information from textual sources. This presentation describes work now underway at NASA to increase situational awareness through the collection of non-telemetry mission operations information into a common log format and then providing display and analytics tools to provide in-depth assessment of the log contents. The work includes: Common interface formats for acquiring time-tagged text messages Conversion of common files for schedules, orbital events, and stored commands to the common log format Innovative displays to depict thousands of messages on a single display Structured English text queries against the log message data store, extensible to a more mature natural language query capability Goal of speech-to-text and text-to-speech additions to create a personal mission operations assistant to aid on-console operations. A wide variety of planned uses identified by the mission operations teams will be discussed.

events↗

A petabyte size electronic library using the N-Gram memory engine

A model library containing petabytes of data is proposed by Triada, Ltd., Ann Arbor, Michigan. The library uses the newly patented N-Gram Memory Engine (Neurex), for storage, compression, and retrieval. Neurex splits data into two parts: a hierarchical network of associative memories that store 'information' from data and a permutation operator that preserves sequence. Neurex is expected to offer four advantages in mass storage systems. Neurex representations are dense, fully reversible, hence less expensive to store. Neurex becomes exponentially more stable with increasing data flow; thus its contents and the inverting algorithm may be mass produced for low cost distribution. Only a small permutation operator would be recalled from the library to recover data. Neurex may be enhanced to recall patterns using a partial pattern. Neurex nodes are measures of their pattern. Researchers might use nodes in statistical models to avoid costly sorting and counting procedures. Neurex subsumes a theory of learning and memory that the author believes extends information theory. Its first axiom is a symmetry principle: learning creates memory and memory evidences learning. The theory treats an information store that evolves from a null state to stationarity. A Neurex extracts information data without a priori knowledge; i.e., unlike neural networks, neither feedback nor training is required. The model consists of an energetically conservative field of uniformly distributed events with variable spatial and temporal scale, and an observer walking randomly through this field. A bank of band limited transducers (an 'eye'), each transducer in a bank being tuned to a sub-band, outputs signals upon registering events. Output signals are 'observed' by another transducer bank (a mid-brain), except the band limit of the second bank is narrower than the band limit of the first bank. The banks are arrayed as n 'levels' or 'time domains, td.' The banks are the hierarchical network (a cortex) and transducers are (associative) memories. A model Neurex was built and studied. Data were 50 MB to 10 GB samples of text, data base, and images: black/white, grey scale, and high resolution in several spectral bands. Memories at td, S(m(sub td)), were plotted against outputs of memories at td-1. S(m(sub td)) was Boltzman distributed, and memory frequencies exhibited self-organized criticality (SOC); i.e., 'l/f(sup beta)' after long exposures to data. Whereas output signals from level n may be encoded with B(sub output) = O(-log(2)f(sup beta)) bits, and input data encoded with B(sub input) = O((S(td)/S(td-1))(sup n)), B(sup output)/B(sub input) is much less than 1 always, the Neurex determines a canonical code for data and it is a lossless data compressor. Further tests are underway to confirm these results with more data types and larger samples.

Bugajski, Joseph M.↗

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗

TERSSE: Definition of the Total Earth Resources System for the Shuttle Era. Volume 7: User Models: A System Assessment

User models defined as any explicit process or procedure used to transform information extracted from remotely sensed data into a form useful as a resource management information input are discussed. The role of the user models as information, technological, and operations interfaces between the TERSSE and the resource managers is emphasized. It is recommended that guidelines and management strategies be developed for a systems approach to user model development.

Source record↗

Space and Earth Science Data Compression Workshop

The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The focus was on scientists' data requirements, as well as constraints imposed by the data collection, transmission, distribution, and archival systems. The workshop consisted of several invited papers; two described information systems for space and Earth science data, four depicted analysis scenarios for extracting information of scientific interest from data collected by Earth orbiting and deep space platforms, and a final one was a general tutorial on image data compression.

Tilton, James C.↗

Unleashing the Power of Knowledge Extraction from Scientific Literature in Catalysis

Valuable knowledge of catalysis is often hidden in a large amount of scientific literature. There is an urgent need to extract useful knowledge to facilitate scientific discovery. Here this work takes the first step toward the goal in the field of catalysis. Specifically, we construct the first information extraction benchmark data set that covers the field of catalysis and also develop a general extraction framework that can accurately extract catalysis-related entities from scientific literature with 90% extraction accuracy. We further demonstrate the feasibility of leveraging the extracted knowledge to help users better access relevant information in catalysis through an entity-aware search engine and a correlation analysis system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Theory of the phase transition in random unitary circuits with measurements

Here, we present a theory of the entanglement transition tuned by measurement strength in qudit chains evolved by random unitary circuits and subject to either weak or random projective measurements. The transition can be understood as a nonanalytic change in the amount of information extracted by the measurements about the initial state of the system, quantified by the Fisher information. To compute the von Neumann entanglement entropy $\textit{S}$ and the Fisher information $\mathcal{F}$, we apply a replica method based on a sequence of quantities $\tilde{S}^{(n)}$ and $\mathcal{F}^{(n)}$ that depend on the $\textit{n}$th moments of density matrices and reduce to $\textit{S}$ and $\mathcal{F}$ in the limit $\textit{n}$ → 1. These quantities with $\textit{n}$ ≥ 2 are mapped to free energies of a classical spin model with $\textit{n}$! internal states in two dimensions with specific boundary conditions. In particular, $\tilde{S}^{(n)}$ is the excess free energy of a domain wall terminating on the top boundary, and $\mathcal{F}^{(n)}$ is related to the magnetization on the bottom boundary. Phase transitions occur as the spin models undergo ordering transitions in the bulk. Taking the limit of large local Hilbert space dimension $\textit{q}$ followed by the replica limit $\textit{n}$ → 1, we obtain the critical measurement probability $p_c$ = 1/2 and identify the transition as a bond percolation in the 2D square lattice in this limit. Finally, we show there is no phase transition if the measurements are allowed in an arbitrary nonlocal basis, thereby highlighting the relation between the phase transition and information scrambling. We establish an explicit connection between the entanglement phase transition and the purification dynamics of a mixed state evolution and discuss implications of our results to experimental observations of the transition and simulability of quantum dynamics.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Extraction of quantitative surface characteristics from AIRSAR data for Death Valley, California

Polarimetric Airborne Synthetic Aperture Radar (AIRSAR) data were collected for the Geologic Remote Sensing Field Experiment (GRSFE) over Death Valley, California, USA, in Sep. 1989. AIRSAR is a four-look, quad-polarization, three frequency instrument. It collects measurements at C-band (5.66 cm), L-band (23.98 cm), and P-band (68.13 cm), and has a GIFOV of 10 meters and a swath width of 12 kilometers. Because the radar measures at three wavelengths, different scales of surface roughness are measured. Also, dielectric constants can be calculated from the data. The AIRSAR data were calibrated using in-scene trihedral corner reflectors to remove cross-talk; and to calibrate the phase, amplitude, and co-channel gain imbalance. The calibration allows for the extraction of accurate values of rms surface roughness, dielectric constants, sigma(sub 0) backscatter, and polarization information. The radar data sets allow quantitative characterization of small scale surface structure of geologic units, providing information about the physical and chemical processes that control the surface morphology. Combining the quantitative information extracted from the radar data with other remotely sensed data sets allows discrimination, identification and mapping of geologic units that may be difficult to discern using conventional techniques.

Kierein-Young, K. S.↗

Automatic recognition system for document digitization in nuclear power plants

With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Doppler extraction with a digital VCO

Digitally controlled oscillator in phased-locked loop may be useful for data communications systems, or may be modified to serve as information extraction component of microwave or optical system for collision avoidance or automatic braking. Instrument is frequency-synthesizing device with output specified precisely by digital number programmed into frequency register.

Starner, E. R.↗

Agricultural land cover mapping in the context of a geographically referenced digital information system

The introduction of soil map information to the land cover mapping process can improve discrimination of land cover types and reduce confusion among crop types that may be caused by soil-specific management practices and background reflectance characteristics. Multiple dates of LANDSAT MSS digital were analyzed for three study areas in northern Missouri to produce cover types for major agricultural land cover classes. Digital data bases were then developed by adding ancillary data such as digitized soil and transportation network information to the LANDSAT-derived cover type map. Procedures were developed to manipulate the data base parameters to extract information applicable to user requirements. An agricultural information system combining such data can be used to determine the productive capacity of land to grow crops, fertilizer needs, chemical weed control rates, irrigation suitability, and trafficability of soil for planting.

Stoner, E. R.↗

The velocity and the density spectrum of the solar wind from simultaneous three-frequency IPS observations

Density inhomogeneities in the solar wind cause fluctuations regarding the emission of small diameter radio sources. Such fluctuations are called interplanetary scintillation (IPS). IPS has been studied to obtain information on both the solar wind and on the radio sources. In the present investigation it is attempted to extract information about the solar wind from simultaneous IPS observations at three radio frequencies and a single antenna. Data were recorded at frequencies of 270 MHz, 340 MHz, and 470 MHz on a 91 m telescope. Five different radio sources were observed. The observations are compared with theoretical predictions for spectra, cross-spectra, and cross-correlations using weak scattering theory and various models for the wavenumber spectrum of density inhomogeneities in the solar wind. Good fits are obtained over the observed wavenumbers to a spectrum modeled as a power law.

Scott, S. L.↗

Extraction of Profile Information from Cloud Contaminated Radiances

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Smith, W. L.↗

DOCU-TEXT: A tool before the data dictionary

DOCU-TEXT, a proprietary software package that aids in the production of documentation for a data processing organization and can be installed and operated only on IBM computers is discussed. In organizing information that ultimately will reside in a data dictionary, DOCU-TEXT proved to be a useful documentation tool in extracting information from existing production jobs, procedure libraries, system catalogs, control data sets and related files. DOCU-TEXT reads these files to derive data that is useful at the system level. The output of DOCU-TEXT is a series of user selectable reports. These reports can reflect the interactions within a single job stream, a complete system, or all the systems in an installation. Any single report, or group of reports, can be generated in an independent documentation pass.

Carter, B.↗

Low- ν method with LHC neutrinos

The Forward Physics Facility (FPF) plans to use neutrinos produced at the Large Hadron Collider to make a variety of measurements at previously unexplored TeV energies. Its primary goals include precision measurements of the neutrino cross section and using the measured neutrino flux both to uncover information about far-forward hadron production and to search for various beyond standard model scenarios. However, these goals have the potential to conflict: Extracting information about the flux or cross section relies upon an assumption about the other. In this paper, we demonstrate that the FPF can use the low- ν method—a technique for constraining the flux shape by isolating neutrino interactions with low energy transfer to the nucleus—to break this degeneracy. We show that the low- ν method is effective for extracting the ν μ flux shape, in a model-independent way. We discuss its application for extracting the ν ¯ μ flux shape but find that this is significantly more model dependent. Finally, we explore the precision to which the ν μ flux shape could be constrained at the FPF for a variety of proposed detector options. We find that the precision would be sufficient to discriminate between various realistic flux models. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

computer vision↗

A systematic feature extraction and selection framework for data-driven whole-building automated fault detection and diagnostics in commercial buildings

In data-driven automated fault detection and diagnostics (AFDD) modeling for building energy systems, feature engineering is a critical process of extracting information from high-dimensional and noisy sensor measurement and turning it into informative and representative inputs or features for data-driven modeling. However, few studies specifically discuss the feature engineering, especially the interactions between feature extraction and feature selection in whole-building AFDD. We developed a systematic feature extraction and selection framework for whole-building AFDD. In this framework, features are aggressively extracted from raw sensor data using statistical feature extraction techniques with various window sizes and statistics. With many features extracted, a hybrid feature selection algorithm that combines the filter and wrapper method then selects the best feature set. The framework considers diversity in the duration of fault behavior among fault types in whole-building AFDD, thus achieving high model generalization. We implemented our developed framework in a virtual testbed calibrated with measured data from Oak Ridge National Laboratory's Flexible Research Platform designed to mimic the operation of a typical small commercial building. The AFDD model is trained by the simulation data generated from the virtual testbed. The results show that (1) the developed framework improves the generalization of the AFDD model by 10.7% compared with literature-reported feature extraction and selection methods and (2) features with diverse window sizes and statistics are selected, providing insight into physical systems beyond the current understanding of buildings and faults and improving the detection and diagnostics of multiple fault types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

PhysBERT: A text embedding model for physics scientific literature

The specialized language and complex concepts in physics pose significant challenges for information extraction through Natural Language Processing (NLP). Central to effective NLP applications is the text embedding model, which converts text into dense vector representations for efficient information retrieval and semantic analysis. In this work, we introduce PhysBERT, the first physics-specific text embedding model. Pre-trained on a curated corpus of 1.2 × 106 arXiv physics papers and fine-tuned with supervised data, PhysBERT outperforms leading general-purpose models on physics-specific tasks, including the effectiveness in fine-tuning for specific physics subdomains.

Hellert, Thorsten (ORCID:0000000227970926)↗