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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

An Automated Classification Technique for Detecting Defects in Battery Cells

Battery cell defect classification is primarily done manually by a human conducting a visual inspection to determine if the battery cell is acceptable for a particular use or device. Human visual inspection is a time consuming task when compared to an inspection process conducted by a machine vision system. Human inspection is also subject to human error and fatigue over time. We present a machine vision technique that can be used to automatically identify defective sections of battery cells via a morphological feature-based classifier using an adaptive two-dimensional fast Fourier transformation technique. The initial area of interest is automatically classified as either an anode or cathode cell view as well as classified as an acceptable or a defective battery cell. Each battery cell is labeled and cataloged for comparison and analysis. The result is the implementation of an automated machine vision technique that provides a highly repeatable and reproducible method of identifying and quantifying defects in battery cells.

McDowell, Mark↗
NASA NTRS2016

Empirical Analysis and Automated Classification of Security Bug Reports

With the ever expanding amount of sensitive data being placed into computer systems, the need for effective cybersecurity is of utmost importance. However, there is a shortage of detailed empirical studies of security vulnerabilities from which cybersecurity metrics and best practices could be determined. This thesis has two main research goals: (1) to explore the distribution and characteristics of security vulnerabilities based on the information provided in bug tracking systems and (2) to develop data analytics approaches for automatic classification of bug reports as security or non-security related. This work is based on using three NASA datasets as case studies. The empirical analysis showed that the majority of software vulnerabilities belong only to a small number of types. Addressing these types of vulnerabilities will consequently lead to cost efficient improvement of software security. Since this analysis requires labeling of each bug report in the bug tracking system, we explored using machine learning to automate the classification of each bug report as a security or non-security related (two-class classification), as well as each security related bug report as specific security type (multiclass classification). In addition to using supervised machine learning algorithms, a novel unsupervised machine learning approach is proposed. An ac- curacy of 92%, recall of 96%, precision of 92%, probability of false alarm of 4%, F-Score of 81% and G-Score of 90% were the best results achieved during two-class classification. Furthermore, an accuracy of 80%, recall of 80%, precision of 94%, and F-score of 85% were the best results achieved during multiclass classification.

Cybersecurity↗
NASA NTRS1982

Automated pixel screening and selection technique

One approach for estimating crop acreage on the basis of Landsat data involves the sampling of portions of Landsat imagery which represent 5 x 6-n mi areas on the ground, taking into account acreage estimates for each of these areas. Difficulties concerning the estimating procedures are related to labeling. These difficulties arise in particular in connection with mixed pixels. The present investigation is concerned with the employment of a suitable automated technique for overcoming these difficulties. A description of the selected technique is presented, and the test conducted for the evaluation of the technique is discussed. It is found that the employed automated pixel screening and selection procedure provides representative samples of the scene. The amount of time spent on pure pixel selection is significantly reduced by using the automated method.

Dailey, C. L.↗
NASA NTRS2003

Proof Rules for Automated Compositional Verification through Learning

Compositional proof systems not only enable the stepwise development of concurrent processes but also provide a basis to alleviate the state explosion problem associated with model checking. An assume-guarantee style of specification and reasoning has long been advocated to achieve compositionality. However, this style of reasoning is often non-trivial, typically requiring human input to determine appropriate assumptions. In this paper, we present novel assume- guarantee rules in the setting of finite labelled transition systems with blocking communication. We show how these rules can be applied in an iterative and fully automated fashion within a framework based on learning.

Barringer, Howard↗
NASA NTRS2005

Fluorescent Approaches to High Throughput Crystallography

X-ray crystallography remains the primary method for determining the structure of macromolecules. The first requirement is to have crystals, and obtaining them is often the rate-limiting step. The numbers of crystallization trials that are set up for any one protein for structural genomics, and the rate at which they are being set up, now overwhelm the ability for strictly human analysis of the results. Automated analysis methods are now being implemented with varying degrees of success, but these typically cannot reliably extract intermediate results. By covalently modifying a subpopulation, 51%, of a macromolecule solution with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination the crystals show up as bright objects against a dark background. As crystalline packing is more dense than amorphous precipitate, the fluorescence intensity can be used as a guide in distinguishing different types of precipitated phases, even in the absence of obvious crystalline features, widening the available potential lead conditions in the absence of clear hits. Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Also, brightly fluorescent crystals are readily found against less fluorescent precipitated phases, which under white light illumination may serve to obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries and by having the protein or protein structures all that show up. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons. This presentation will focus on the methodology for fluorescent labeling, the crystallization results, and the effects of the trace labeling on the crystal quality.

Pusey, Marc L.↗
NASA NTRS2004

Fluorescent Approaches to High Throughput Crystallography

X-ray crystallography remains the primary method for determining the structure of macromolecules. The first requirement is to have crystals, and obtaining them is often the rate-limiting step. The numbers of crystallization trials that are set up for any one protein for structural genomics, and the rate at which they are being set up, now overwhelm the ability for strictly human analysis of the results. Automated analysis methods are now being implemented with varying degrees of success, but these typically cannot reliably extract intermediate results. By covalently modifying a subpopulation, less than or = 1%, of a macromolecule solution with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of a macromolecules purification. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination the crystals will show up as bright objects against a dark background. As crystalline packing is more dense than amorphous precipitate, the fluorescence intensity can be used as a guide in distinguishing different types of precipitated phases, even in the absence of obvious crystalline features, widening the available potential lead conditions in the absence of clear "bits." Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Also, brightly fluorescent crystals are readily found against less fluorescent precipitated phases, which under white light illumination may serve to obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries and by having the protein or protein structures all that show up. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons. This presentation will focus on the methodology for fluorescent labeling, the crystallization results, and the effects of the trace labeling on the crystal quality.

Minamitani, Elizabeth Forsythe↗
NASA NTRS2015

Preliminary Radiation Testing of a State-of-the-Art Commercial 14nm CMOS Processor - System-on-a-Chip

Hardness assurance test results of Intel state-of-the-art 14nm Broadwell U-series processor System-on-a-Chip (SoC) for total dose are presented, along with first-look exploratory results from trials at a medical proton facility. Test method builds upon previous efforts by utilizing commercial laptop motherboards and software stress applications as opposed to more traditional automated test equipment (ATE).

14nm↗
NASA NTRS2015

Preliminary Radiation Testing of a State-of-the-Art Commercial 14nm CMOS Processor/System-on-a-Chip

Hardness assurance test results of Intel state-of-the-art 14nm “Broadwell” U-series processor / System-on-a-Chip (SoC) for total ionizing dose (TID) are presented, along with exploratory results from trials at a medical proton facility. Test method builds upon previous efforts [1] by utilizing commercial laptop motherboards and software stress applications as opposed to more traditional automated test equipment (ATE).

microprocessor↗
NASA NTRS2004

Fluorescent Approaches to High Throughput Crystallography

X-ray crystallography remains the primary method for determining the structure of macromolecules. The first requirement is to have crystals, and obtaining them is often the rate-limiting step. The numbers of crystallization trials that are set up for any one protein for structural genomics, and the rate at which they are being set up, now overwhelm the ability for strictly human analysis of the results. Automated analysis methods are now being implemented with varying degrees of success, but these typically can not reliably extract intermediate results. By covalently modifying a subpopulation, less than or = 1%, of a macromolecule solution with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination the crystals show up as bright objects against a dark background. As crystalline packing is more dense than amorphous precipitate, the fluorescence intensity can be used as a guide in distinguishing different types of precipitated phases, even in the absence of obvious crystalline features, widening the available potential lead conditions in the absence of clear "hits." Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Also, brightly fluorescent crystals are readily found against less fluorescent precipitated phases, which under white light illumination may serve to obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries and by having the protein or protein structures all that show up. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons. This presentation will focus on the methodology for fluorescent labeling, the crystallization results, and the effects of the trace labeling on the crystal quality.

Pusey, Marc L.↗
NASA NTRS2005

Fluorescent Approaches to High Throughput Crystallography

X-ray crystallography remains the primary method for determining the structure of macromolecules. The first requirement is to have crystals, and obtaining them is often the rate-limiting step. The numbers of crystallization trials that are set up for any one protein for structural genomics, and the rate at which they are being set up, now overwhelm the ability for strictly human analysis of the results. Automated analysis methods are now being implemented with varying degrees of success, but these typically cannot reliably extract intermediate results. By covalently modifying a subpopulation, less than or = 1 %, of a macromolecule solution with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination the crystals show up as bright objects against a dark background. As crystalline packing is more dense than amorphous precipitate, the fluorescence intensity can be used as a guide in distinguishing different types of precipitated phases, even in the absence of obvious crystalline features, widening the available potential lead conditions in the absence of clear "hits." Non-protein structures, such as salt crystals, will not incorporate the probe and will not show up under fluorescent illumination. Also, brightly fluorescent crystals are readily found against less fluorescent precipitated phases, which under white light illumination may serve to obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries and by having the protein or protein structures all that show up. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons. Preliminary experiments show that the presence of the fluorescent probe does not affect the nucleation process or the quality of the X-ray data obtained.

Pusey, Marc L.↗
NASA NTRS2019

Automatically Finding Ship-Tracks to Enable Large-Scale Analysis of Aerosol-Cloud Interactions

Ship tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship tracks from satellite data on a large scale is prohibitively costly while a large number of samples are required to improve our understanding. Here we train a deep neural network to automate finding ship tracks. The neural network model generalizes well as it not only finds ship tracks labeled by human experts but also detects those that are occasionally missed by humans. It finds more ship tracks than all previous studies combined and produces a map of ship track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship tracks on a large scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.

aerosol cloud interactions↗
NASA NTRS1973

Automated Microbial Metabolism Laboratory

Development of the automated microbial metabolism laboratory (AMML) concept is reported. The focus of effort of AMML was on the advanced labeled release experiment. Labeled substrates, inhibitors, and temperatures were investigated to establish a comparative biochemical profile. Profiles at three time intervals on soil and pure cultures of bacteria isolated from soil were prepared to establish a complete library. The development of a strategy for the return of a soil sample from Mars is also reported.

Source record↗
NASA NTRS1980

Crop identification studies using Landsat data Separation of barley from other spring small grains and corn and soybean decision logic

Two labeling procedures were developed which identify various agricultural crops through the use of Landsat data. One procedure separates barley from other spring small grains, and the other identifies corn and soybeans. For both procedures, a minimum data set (critical acquisition time) has been designated. Landsat data in both image format and various graphic displays were used along with ancillary data to obtain information which aided in labeling the spectral signatures. The corn and soybean procedure also employed a structured decision logic. Test results for the barley separation procedure emphasized the importance of obtaining a critical acquisition and showed some success especially in areas where spring crops followed the expected growth patterns. Two tests of the corn and soybean procedure produced good labeling accuracies. Problems with the procedure were easy to identify, and some solutions were implemented for the second test. Automation of various parts of the procedure and extension to other crops and regions were recommended.

Dailey, C. L.↗
NASA NTRSDate not supplied

REACTER 2.0: Quantum-Informed Reaction Constraints and Automated Interaction Typing

REACTER is a heuristic method for modeling chemical reactions in classical molecular dynamics simulations, implemented in LAMMPS as fix bond/react. The authors recently extended LAMMPS to support alphanumeric labels for atom types, bond types etc., which enables the pre- and post-reaction templates required by the REACTER protocol to be portable between different simulations and greatly simplifies the task of creating simulation-ready reaction templates. To further increase the generality of reaction templates, support for wildcard characters within atom types has been added, along with the automatic assignment of interaction types for new bonds, angles, etc. based on the involved atom types. In some cases, this feature can express a class of reactions with one pair of reaction templates, where previously dozens may have been required. Advanced reaction constraints have also been added, including an Arrhenius constraint to enforce an effective activation energy, a root-mean-square-deviation option for complex geometrical constraints, as well as a custom constraint that leverages LAMMPS’ powerful built-in variable framework. Other new features include variable support for various inputs (e.g., to allow reaction rates or cutoffs to be dependent on overall conversion), on-the-fly update of molecule IDs, and the ability to create new atoms positioned with respect to the reaction site. The new features are applied to modeling polymeric, thermosetting and composite materials, and advanced applications of the new reaction constraints are demonstrated. For example, REACTER is shown to accurately reproduce mechanically-induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a constraint on the total potential energy of the involved atoms.

polymer simulations↗
NASA NTRS1980

AgRISTARS: Foreign commodity production forecasting. Corn/soybean decision logic development and testing

The development and testing of an analysis procedure which was developed to improve the consistency and objectively of crop identification using Landsat data is described. The procedure was developed to identify corn and soybean crops in the U.S. corn belt region. The procedure consists of a series of decision points arranged in a tree-like structure, the branches of which lead an analyst to crop labels. The specific decision logic is designed to maximize the objectively of the identification process and to promote the possibility of future automation. Significant results are summarized.

Dailey, C. L.↗
NASA NTRS2006

Fluorescent Applications to Crystallization

By covalently modifying a subpopulation, less than or equal to 1%, of a macromolecule with a fluorescent probe, the labeled material will add to a growing crystal as a microheterogeneous growth unit. Labeling procedures can be readily incorporated into the final stages of purification, and tests with model proteins have shown that labeling u to 5 percent of the protein molecules does not affect the X-ray data quality obtained . The presence of the trace fluorescent label gives a number of advantages. Since the label is covalently attached to the protein molecules, it "tracks" the protein s response to the crystallization conditions. The covalently attached probe will concentrate in the crystal relative to the solution, and under fluorescent illumination crystals show up as bright objects against a darker background. Non-protein structures, such as salt crystals, do not show up under fluorescent illumination. Crystals have the highest protein concentration and are readily observed against less bright precipitated phases, which under white light illumination may obscure the crystals. Automated image analysis to find crystals should be greatly facilitated, without having to first define crystallization drop boundaries as the protein or protein structures is all that shows up. Fluorescence intensity is a faster search parameter, whether visually or by automated methods, than looking for crystalline features. Preliminary tests, using model proteins, indicates that we can use high fluorescence intensity regions, in the absence of clear crystalline features or "hits", as a means for determining potential lead conditions. A working hypothesis is that more rapid amorphous precipitation kinetics may overwhelm and trap more slowly formed ordered assemblies, which subsequently show up as regions of brighter fluorescence intensity. Experiments are now being carried out to test this approach using a wider range, of proteins. The trace fluorescently labeled crystals will also emit with sufficient intensity to aid in the automation of crystal alignment using relatively low cost optics, further increasing throughput at synchrotrons.

Pusey, Marc L.↗
NASA NTRS2014

State Event Models for the Formal Analysis of Human-Machine Interactions

The work described in this paper was motivated by our experience with applying a framework for formal analysis of human-machine interactions (HMI) to a realistic model of an autopilot. The framework is built around a formally defined conformance relation called "fullcontrol" between an actual system and the mental model according to which the system is operated. Systems are well-designed if they can be described by relatively simple, full-control, mental models for their human operators. For this reason, our framework supports automated generation of minimal full-control mental models for HMI systems, where both the system and the mental models are described as labelled transition systems (LTS). The autopilot that we analysed has been developed in the NASA Ames HMI prototyping tool ADEPT. In this paper, we describe how we extended the models that our HMI analysis framework handles to allow adequate representation of ADEPT models. We then provide a property-preserving reduction from these extended models to LTSs, to enable application of our LTS-based formal analysis algorithms. Finally, we briefly discuss the analyses we were able to perform on the autopilot model with our extended framework.

State-event Models↗