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NASA NTRS2005

Contour Error Map Algorithm

The contour error map (CEM) algorithm and the software that implements the algorithm are means of quantifying correlations between sets of time-varying data that are binarized and registered on spatial grids. The present version of the software is intended for use in evaluating numerical weather forecasts against observational sea-breeze data. In cases in which observational data come from off-grid stations, it is necessary to preprocess the observational data to transform them into gridded data. First, the wind direction is gridded and binarized so that D(i,j;n) is the input to CEM based on forecast data and d(i,j;n) is the input to CEM based on gridded observational data. Here, i and j are spatial indices representing 1.25-km intervals along the west-to-east and south-to-north directions, respectively; and n is a time index representing 5-minute intervals. A binary value of D or d = 0 corresponds to an offshore wind, whereas a value of D or d = 1 corresponds to an onshore wind. CEM includes two notable subalgorithms: One identifies and verifies sea-breeze boundaries; the other, which can be invoked optionally, performs an image-erosion function for the purpose of attempting to eliminate river-breeze contributions in the wind fields.

Merceret, Francis↗

NASA NTRS1981

Software for universal noiseless coding

An overview is provided of the universal noiseless coding algorithms as well as their relationship to the now available FORTRAN implementations. It is suggested that readers considering investigating the utility of these algorithms for actual applications should consult both NASA's Computer Software Management and Information Center (COSMIC) and descriptions of coding techniques provided by Rice (1979). Examples of applying these techniques have also been given by Rice (1975, 1979, 1980). Attention is given to reversible preprocessing, general implementation instructions, naming conventions, and calling arguments. A general applicability of the considered algorithms to solving practical problems is obtained because most real data sources can be simply transformed into the required form by appropriate preprocessing.

Rice, R. F.↗

NASA NTRS1999

Problems Associated with Statistical Pattern Recognition of Acoustic Emission Signals in a Compact Tension Fatigue Specimen

Acoustic emission (AE) data were acquired during fatigue testing of an aluminum 2024-T4 compact tension specimen using a commercially available AE system. AE signals from crack extension were identified and separated from noise spikes, signals that reflected from the specimen edges, and signals that saturated the instrumentation. A commercially available software package was used to train a statistical pattern recognition system to classify the signals. The software trained a network to recognize signals with a 91-percent accuracy when compared with the researcher's interpretation of the data. Reasons for the discrepancies are examined and it is postulated that additional preprocessing of the AE data to focus on the extensional wave mode and eliminate other effects before training the pattern recognition system will result in increased accuracy.

Hinton, Yolanda L.↗

NASA NTRS2002

Onboard Processor for Compressing HSI Data

With EO-1 Hyperion and MightySat in orbit NASA and the DoD are showing their continued commitment to hyperspectral imaging (HSI). As HSI sensor technology continues to mature, the ever-increasing amounts of sensor data generated will result in a need for more cost effective communication and data handling systems. Lockheed Martin, with considerable experience in spacecraft design and developing special purpose onboard processors, has teamed with Applied Signal & Image Technology (ASIT), who has an extensive heritage in HSI, to develop a real-time and intelligent onboard processing (OBP) system to reduce HSI sensor downlink requirements. Our goal is to reduce the downlink requirement by a factor greater than 100, while retaining the necessary spectral fidelity of the sensor data needed to satisfy the many science, military, and intelligence goals of these systems. Our initial spectral compression experiments leverage commercial-off-the-shelf (COTS) spectral exploitation algorithms for segmentation, material identification and spectral compression that ASIT has developed. ASIT will also support the modification and integration of this COTS software into the OBP. Other commercially available COTS software for spatial compression will also be employed as part of the overall compression processing sequence. Over the next year elements of a high-performance reconfigurable OBP will be developed to implement proven preprocessing steps that distill the HSI data stream in both spectral and spatial dimensions. The system will intelligently reduce the volume of data that must be stored, transmitted to the ground, and processed while minimizing the loss of information.

Cook, Sid↗

NASA NTRS1995

Gravity Sensors and the Role of 3-D Visualization and Simulation in Biomedical Research

Ross 3.0 software was developed in the Biocomputation Center for semi-automated reconstruction of objects from serial thin sections. Data are captured directly from a transmission electron microscope via a video camera to a graphics workstation where the sections are mosaicked and contours are traced, registered and displayed by semi-automated methods. For the first time, macular type II cells are described completely for their innervation patterns. The purposes are to learn more about the fundamental circuitry of the macula and to demonstrate whether the terminals are altered morphologically by space flight. Current examples, from the medial part of the macula, are from maculas collected in-flight on the Space Life Sciences-2 mission, 4.5 hrs post-flight, and from a ground control. Results show that the typical type 11 cell receives processes from up to six nearby calyces or afferents. Nearly all the processes are elongated; some have bouton-like swellings and numerous vesicles. Multiple (2 to 4) processes from a single calyx to a type II cell are common, and approx. 1/3 of the processes innervate 2 type II cells of a neighboring cluster of 3 cells. About 2% of type II cells resemble type I cells morphologically and are surrounded by demicalyces. Differences in size or shape of the terminals under flight conditions could not be determined because the sample size is still too small; but it is clear that reconstruction methods provide insights into macular circuitry not obtainable by other techniques. The results demonstrate a morphological basis for interactions between adjacent receptive fields, through feedback-feedforward connections, during preprocessing of linear acceleratory information by the maculas. While the methods are currently being tested using vestibular maculas as the model system, it is clear that the technology is applicable to any tissue that can be physically or optically sectioned. ROSS software has already been implemented for reconstructing objects from tissues studied by confocal and by transmitted light microscopy, and research into magnetic resonance imaging-computational tomography combined visualization are underway.

Ross, Muriel D.↗

NASA NTRS2004

Using Automated Theorem Provers to Certify Auto-Generated Aerospace Software

We describe a system for the automated certification of safety properties of NASA software. The system uses Hoare-style program verification technology to generate proof obligations which are then processed by an automated first-order theorem prover (ATP). For full automation, however, the obligations must be aggressively preprocessed and simplified We describe the unique requirements this places on the ATP and demonstrate how the individual simplification stages, which are implemented by rewriting, influence the ability of the ATP to solve the proof tasks. Experiments on more than 25,000 tasks were carried out using Vampire, Spass, and e-setheo.

Denney, Ewen↗

NASA NTRS1977

A technique for real-time data preprocessing

A processing system is presented that implements simultaneously the efficiency of the special-purpose processor and the total applicability of the general-purpose computer - characteristics commonly thought of as being mutually exclusive. The solution adopted is that of specializing the machine by programming the hardware structure, rather than by adding software systems to it. Data are organized in circulating pages which form a plurality of local dynamic memories for each process. Programs are made up of modules, each describing a transient special-purpose machine. Applications to real-time processing of radar signals are referred to.

Schaffner, M. R.↗

DOE OSTI2026

Asi Nuclear Energy Sensors Data Portal Chatbot And Data Structuring Tool

The Idaho National Laboratory (INL) is advancing the development of an AI-powered chatbot and data structuring tool specifically designed to accelerate data mining processes for sensor-related information and seamlessly integrate the results into the ASI Sensors Data Portal (https://nes.energy.gov/). By doing so, the software aims to enhance the accessibility, usability, and organization of sensor data for nuclear energy applications. The software initial phase focuses on retrieving comprehensive datasets, prioritizing the past five years of publicly available information from the Office of Scientific and Technical Information (OSTI). These datasets will be meticulously processed to ensure compatibility, employing cleaning and preprocessing steps to eliminate irrelevant, incomplete, or corrupted information, thus establishing a robust foundation for subsequent AI use. The data will serve as the backbone for training an AI model and chatbot, which will act as an interactive tool enabling users to ask complex, context-specific questions and receive accurate, validated answers derived from constrained literature. In parallel, the project incorporates a data structuring process supported by AI to organize sensor information from multiple sources into a standardized format. This structured data will include detailed sensor specifications, such as measurement range, applications, accuracy, and operating conditions, generated and documented with AI. These specifications will be systematically integrated into the sensor portal. To maintain the highest levels of accuracy and relevance, all AI-generated outputs will be reviewed and validated by subject matter experts (SMEs), with additional fields or parameters added as needed. Future stages of the project aim to expand the dataset beyond OSTI to include other sources and potentially incorporate unclassified controlled information (UCI) with restricted access protocols to address security and confidentiality requirements.

Mapes, NormanJ. [Idaho National Laboratory (INL), ↗

NASA NTRS1984

Storage, retrieval, and analysis of ST data

Space Telescope can generate multidimensional image data, very similar in nature to data produced with microdensitometers. An overview is presented of the ST science ground system between carrying out the observations and the interactive analysis of preprocessed data. The ground system elements used in data archival and retrieval are described and operational procedures are discussed. Emphasis is given to aspects of the ground system that are relevant to the science user and to general principles of system software development in a production environment. While the system being developed uses relatively conservative concepts for the launch baseline, concepts were developed to enhance the ground system. This includes networking, remote access, and the utilization of alternate data storage technologies.

Albrecht, R.↗

DOE OSTI2021

Utah FORGE InSAR Data from 2021

Interferometric Synthetic Aperture Radar data from the TerraSAR-X and the TanDEM-X satellite missions operated by the German Space Agency (DLR). Interferometric pairs (interferograms) were created using generic mapping tool GMT-SAR processing software (see link in Resources). Data from January through November 2021.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

Utah FORGE InSAR Data from 2022

15 GEOTHERMAL ENERGY↗

NASA NTRS1985

The Watchdog Task: Concurrent error detection using assertions

The Watchdog Task, a software abstraction of the Watchdog-processor, is shown to be a powerful error detection tool with a great deal of flexibility and the advantages of watchdog techniques. A Watchdog Task system in Ada is presented; issues of recovery, latency, efficiency (communication) and preprocessing are discussed. Different applications, one of which is error detection on a single processor, are examined.

Ersoz, A.↗

NASA NTRS1997

Light microscopic image analysis system to quantify immunoreactive terminal area apposed to nerve cells

The present report describes a desktop computer-based method for the quantitative assessment of the area occupied by immunoreactive terminals in close apposition to nerve cells in relation to the perimeter of the cell soma. This method is based on Fast Fourier Transform (FFT) routines incorporated in NIH-Image public domain software. Pyramidal cells of layer V of the somatosensory cortex outlined by GABA immunolabeled terminals were chosen for our analysis. A Leitz Diaplan light microscope was employed for the visualization of the sections. A Sierra Scientific Model 4030 CCD camera was used to capture the images into a Macintosh Centris 650 computer. After preprocessing, filtering was performed on the power spectrum in the frequency domain produced by the FFT operation. An inverse FFT with filter procedure was employed to restore the images to the spatial domain. Pasting of the original image to the transformed one using a Boolean logic operation called 'AND'ing produced an image with the terminals enhanced. This procedure allowed the creation of a binary image using a well-defined threshold of 128. Thus, the terminal area appears in black against a white background. This methodology provides an objective means of measurement of area by counting the total number of pixels occupied by immunoreactive terminals in light microscopic sections in which the difficulties of labeling intensity, size, shape and numerical density of terminals are avoided.

Non-NASA Center↗

NASA NTRS1992

Expert-System Consultant To Operating Personnel

Artificial intelligence aids engineers and technicians in controlling and monitoring complicated systems. Operations Analyst for Distributed Systems (OPERA) software is developmental suite of expert-system computer programs helping engineers and technicians operating from number of computer workstations to control and monitor spacecraft during prelaunch and launch phases of operation. OPERA designed to serve as consultant to operating engineers and technicians. It preprocesses incoming data, using expertise collected from conglomerate of specialists in design and operation of various parts of system. Driven by menus and mouse-activated commands. Modified versions of OPERA used in chemical-processing plants, factories, banks, and other enterprises in which there are distributed-computer systems including computers that monitor or control other computers.

Heard, Astrid E.↗

NASA NTRS1980

Alternative approach to multisensor navigation

An alternative to the Kalman filtering technique, based on logical rather than numerical techniques, is presented. It can be implemented on one or more microprocessors (with a fixed communications protocol between the individual microprocessors); requires only limited preprocessing of the input data; can have its constituent subsystem changed without major revision to the combiner as new or better navigation techniques, such as the global positioning system (GPS) or Loran-C, become available; and tolerates a wide variety of sensor, hardware, and software errors. The basic structure of the method and results of simulations of its performance in the presence of errors common to low-cost sensors (such as VOR or basic Omega) are presented, along with a discussion of possible extensions.

Cannon, M. J.↗

NASA NTRS2005

An Automated Flying-Insect-Detection System

An automated flying-insect-detection system (AFIDS) was developed as a proof-of-concept instrument for real-time detection and identification of flying insects. This type of system has use in public health and homeland security decision support, agriculture and military pest management, and/or entomological research. Insects are first lured into the AFIDS integrated sphere by insect attractants. Once inside the sphere, the insect's wing beats cause alterations in light intensity that is detected by a photoelectric sensor. Following detection, the insects are encouraged (with the use of a small fan) to move out of the sphere and into a designated insect trap where they are held for taxonomic identification or serological testing. The acquired electronic wing beat signatures are preprocessed (Fourier transformed) in real-time to display a periodic signal. These signals are sent to the end user where they are graphically displayed. All AFIDS data are pre-processed in the field with the use of a laptop computer equipped with LABVIEW. The AFIDS software can be programmed to run continuously or at specific time intervals when insects are prevalent. A special DC-restored transimpedance amplifier reduces the contributions of low-frequency background light signals, and affords approximately two orders of magnitude greater AC gain than conventional amplifiers. This greatly increases the signal-to-noise ratio and enables the detection of small changes in light intensity. The AFIDS light source consists of high-intensity Al GaInP light-emitting diodes (LEDs). The AFIDS circuitry minimizes brightness fluctuations in the LEDs and when integrated with an integrating sphere, creates a diffuse uniform light field. The insect wing beats isotropically scatter the diffuse light in the sphere and create wing beat signatures that are detected by the sensor. This configuration minimizes variations in signal associated with insect flight orientation.

Vann, Timi↗

NASA NTRS2012

Sampling Technique for Robust Odorant Detection Based on MIT RealNose Data

This technique enhances the detection capability of the autonomous Real-Nose system from MIT to detect odorants and their concentrations in noisy and transient environments. The lowcost, portable system with low power consumption will operate at high speed and is suited for unmanned and remotely operated long-life applications. A deterministic mathematical model was developed to detect odorants and calculate their concentration in noisy environments. Real data from MIT's NanoNose was examined, from which a signal conditioning technique was proposed to enable robust odorant detection for the RealNose system. Its sensitivity can reach to sub-part-per-billion (sub-ppb). A Space Invariant Independent Component Analysis (SPICA) algorithm was developed to deal with non-linear mixing that is an over-complete case, and it is used as a preprocessing step to recover the original odorant sources for detection. This approach, combined with the Cascade Error Projection (CEP) Neural Network algorithm, was used to perform odorant identification. Signal conditioning is used to identify potential processing windows to enable robust detection for autonomous systems. So far, the software has been developed and evaluated with current data sets provided by the MIT team. However, continuous data streams are made available where even the occurrence of a new odorant is unannounced and needs to be noticed by the system autonomously before its unambiguous detection. The challenge for the software is to be able to separate the potential valid signal from the odorant and from the noisy transition region when the odorant is just introduced.

Duong, Tuan A.↗

DOE OSTI2025

Distribution Substation Planning Toolkit (dsp-toolkit) v1.0

The Distribution Substation Planning Toolkit (DSP Toolkit) is a software suite designed to streamline the planning and optimization of distribution substations. This toolkit offers a comprehensive set of tools and APIs for data curation, short-term electric load forecasting, and weather-sensitive load adjustment, making it an essential resource for utility companies, engineers, and researchers. Features • Data Preprocessing and Curation: Efficiently manage and preprocess large datasets to ensure high-quality input for analysis. • Short-Term Load Forecasting: Utilize data-driven models to predict short-term electric loads accurately. • Weather-Sensitive Modeling: Automatically adjust load forecasts based on weather data to predict future peak demands more precisely. Uses The DSP Toolkit is ideal for planning and optimizing distribution substations, providing a user-friendly interface and comprehensive documentation. It is suitable for both novice and experienced users, facilitating efficient and accurate planning processes. Advantages • Efficiency: Automates complex planning tasks, reducing manual effort and minimizing errors. • Scalability: Handles large datasets and complex models, making it suitable for large-scale projects. • Community and Support: Open-source with active community contributions, ensuring continuous improvement and support. • Extensibility: Easily extendable with custom modules and plugins, allowing users to tailor the toolkit to their specific needs. The DSP Toolkit stands out by offering a robust, flexible, and user-friendly solution for distribution substation planning. Public Abstract

Li, Han [Lawrence Berkeley National Laboratory (LB↗