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At least 109 records · Page 6

A Bayesian approach to tracking patients having changing pharmacokinetic parameters

This paper considers the updating of Bayesian posterior densities for pharmacokinetic models associated with patients having changing parameter values. For estimation purposes it is proposed to use the Interacting Multiple Model (IMM) estimation algorithm, which is currently a popular algorithm in the aerospace community for tracking maneuvering targets. The IMM algorithm is described, and compared to the multiple model (MM) and Maximum A-Posteriori (MAP) Bayesian estimation methods, which are presently used for posterior updating when pharmacokinetic parameters do not change. Both the MM and MAP Bayesian estimation methods are used in their sequential forms, to facilitate tracking of changing parameters. Results indicate that the IMM algorithm is well suited for tracking time-varying pharmacokinetic parameters in acutely ill and unstable patients, incurring only about half of the integrated error compared to the sequential MM and MAP methods on the same example.

Bayes Theorem↗

Simulation and analyses of the aeroassist flight experiment attitude update method

A method which will be used to update the alignment of the Aeroassist Flight Experiment's Inertial Measuring Unit is simulated and analyzed. This method, the Star Line Maneuver, uses measurements from the Space Shuttle Orbiter star trackers along with an extended Kalman filter to estimate a correction to the attitude quaternion maintained by an Inertial Measuring Unit in the Orbiter's payload bay. This quaternion is corrupted by on-orbit bending of the Orbiter payload bay with respect to the Orbiter navigation base, which is incorporated into the payload quaternion when it is initialized via a direct transfer of the Orbiter attitude state. The method of updating this quaternion is examined through verification of baseline cases and Monte Carlo analysis using a simplified simulation, The simulation uses nominal state dynamics and measurement models from the Kalman filter as its real world models, and is programmed on Microvax minicomputer using Matlab, and interactive matrix analysis tool. Results are presented which confirm and augment previous performance studies, thereby enhancing confidence in the Star Line Maneuver design methodology.

Carpenter, J. R.↗

First measurement of the yield of 8 He isotopes produced in liquid scintillator by cosmic-ray muons at Daya Bay

Here, Daya Bay presents the first measurement of cosmogenic 8 He isotope production in liquid scintillator, using an innovative method for identifying cascade decays of 8 He and its child isotope, 8 Li. We also measure the production yield of 9 Li isotopes using well-established methodology. The results, in units of 10 –8 μ –1 ⁢g –1 cm 2 , are 0.307 ± 0.042, 0.341 ± 0.040, and 0.546 ± 0.076 for 8 He, and 6.73 ± 0.73, 6.75 ± 0.70, and 13.74 ± 0.82 for 9 Li at average muon energies of 63.9 GeV, 64.7 GeV, and 143.0 GeV, respectively. The measured production rate of 8 He isotopes is more than an order of magnitude lower than any other measurement of cosmogenic isotope production. It replaces the results of previous attempts to determine the ratio of 8 He to 9 Li production that yielded a wide range of limits from 0% to 30%. The results provide future liquid-scintillator-based experiments with improved ability to predict cosmogenic backgrounds.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Interrelationships Between Receiver/Relative Operating Characteristics Display, Binomial, Logit, and Bayes' Rule Probability of Detection Methodologies

Unknown risks are introduced into failure critical systems when probability of detection (POD) capabilities are accepted without a complete understanding of the statistical method applied and the interpretation of the statistical results. The presence of this risk in the nondestructive evaluation (NDE) community is revealed in common statements about POD. These statements are often interpreted in a variety of ways and therefore, the very existence of the statements identifies the need for a more comprehensive understanding of POD methodologies. Statistical methodologies have data requirements to be met, procedures to be followed, and requirements for validation or demonstration of adequacy of the POD estimates. Risks are further enhanced due to the wide range of statistical methodologies used for determining the POD capability. Receiver/Relative Operating Characteristics (ROC) Display, simple binomial, logistic regression, and Bayes' rule POD methodologies are widely used in determining POD capability. This work focuses on Hit-Miss data to reveal the framework of the interrelationships between Receiver/Relative Operating Characteristics Display, simple binomial, logistic regression, and Bayes' Rule methodologies as they are applied to POD. Knowledge of these interrelationships leads to an intuitive and global understanding of the statistical data, procedural and validation requirements for establishing credible POD estimates.

Generazio, Edward R.↗

External impacts of an intraurban air transportation system in the San Francisco Bay area

The effects are studied of an intraurban V/STOL commuter system on the economic, social, and physical environment of the San Francisco Bay Area. The Bay Area was chosen mainly for a case study; the real intent of the analysis is to develop methods by which the effects of such a system could be evaluated for any community. Aspects of the community life affected include: income and employment, benefits and costs, noise, air pollution, and road congestion.

Lu, J. Y.↗

Comparison Of Downscaled CMIP5 Precipitation Datasets For Projecting Changes In Extreme Precipitation In The San Francisco Bay Area.

Water resource managers planning for the adaptation to future events of extreme precipitation now have access to high resolution downscaled daily projections derived from statistical bias correction and constructed analogs. We also show that along the Pacific Coast the Northern Oscillation Index (NOI) is a reliable predictor of storm likelihood, and therefore a predictor of seasonal precipitation totals and likelihood of extremely intense precipitation. Such time series can be used to project intensity duration curves into the future or input into stormwater models. However, few climate projection studies have explored the impact of the type of downscaling method used on the range and uncertainty of predictions for local flood protection studies. Here we present a study of the future climate flood risk at NASA Ames Research Center, located in South Bay Area, by comparing the range of predictions in extreme precipitation events calculated from three sets of time series downscaled from CMIP5 data: 1) the Bias Correction Constructed Analogs method dataset downscaled to a 1/8 degree grid (12km); 2) the Bias Correction Spatial Disaggregation method downscaled to a 1km grid; 3) a statistical model of extreme daily precipitation events and projected NOI from CMIP5 models. In addition, predicted years of extreme precipitation are used to estimate the risk of overtopping of the retention pond located on the site through simulations of the EPA SWMM hydrologic model. Preliminary results indicate that the intensity of extreme precipitation events is expected to increase and flood the NASA Ames retention pond. The results from these estimations will assist flood protection managers in planning for infrastructure adaptations.

Storm↗

Vibration characteristics of a deployable controllable-geometry truss boom

An analytical study was made to evaluate changes in the fundamental frequency of a two dimensional cantilevered truss boom at various stages of deployment. The truss could be axially deployed or retracted and undergo a variety of controlled geometry changes by shortening or lengthening the telescoping diagonal members in each bay. Both untapered and tapered versions of the truss boom were modeled and analyzed by using the finite element method. Large reductions in fundamental frequency occurred for both the untapered and tapered trusses when they were uniformly retracted or maneuvered laterally from their fully deployed position. These frequency reductions can be minimized, however, if truss geometries are selected which maintain cantilever root stiffness during truss maneuvers.

Dorsey, J. T.↗

Algorithm for automatic atmospheric corrections to visible and near-IR satellite imagery

An algorithm for automatic atmospheric correction of satellite imagery of the earth's surface is proposed which is applicable to low-resolution and high-resolution imagery of land areas. The algorithm is based on the satellite image being corrected and on the climatology of the area, and it requires that some pixels in the image correspond to dense dark vegetation as the surface cover. The algorithm is sensitive to the assumed reflectance of the dense dark vegetation, and the accuracy of the corrected surface reflectance is expected to be + or - 0.01. Using the method, aerosol optical thicknesses were derived from clear and hazy Landsat MSS images in the Washington, D.C. and Chesapeake Bay region, and the results are found to agree well with simultaneous sunphotometer ground measurements.

Kaufman, Yoram J.↗

Crystal-Chemical Analysis Martian Minerals in Gale Crater

The CheMin instrument on the Mars Science Laboratory rover Curiosity performed X-ray diffraction analyses on scooped soil at Rocknest and on drilled rock fines at Yellowknife Bay (John Klein and Cumberland samples), The Kimberley (Windjana sample), and Pahrump (Confidence Hills sample) in Gale crater, Mars. Samples were analyzed with the Rietveld method to determine the unit-cell parameters and abundance of each observed crystalline phase. Unit-cell parameters were used to estimate compositions of the major crystalline phases using crystal-chemical techniques. These phases include olivine, plagioclase and clinopyroxene minerals. Comparison of the CheMin sample unit-cell parameters with those in the literature provides an estimate of the chemical compositions of the major crystalline phases. Preliminary unit-cell parameters, abundances and compositions of crystalline phases found in Rocknest and Yellowknife Bay samples were reported in. Further instrument calibration, development of 2D-to- 1D pattern conversion corrections, and refinement of corrected data allows presentation of improved compositions for the above samples.

Morrison, S. M.↗

In Situ Water Quality Data for the Chesapeake Bay

This paper examines in situ water quality datameasured during2020-2021in the Chesapeake Bay for comparison with optical satellite data. Thiscollection was performed as part of a NASA project aiming to develop new methods for water quality monitoring from satellite remote sensingusing artificial intelligence. Our objective is to use insitu data as ground-truth to provide water quality classifications, or labels,to their overlapping (in time and location)satellite imagery. Having such labeled data, can help us achieve our project’s longer-termgoal:to train artificial intelligencemodelsto recognize features in spectral informationfor monitoringwater qualityfrom satellites. Because routine monitoring by state agencies is conducted at discrete locations, we obtained a flow-through system operated from small boats to measure waterquality parameters along transects for comparison with two-dimensional maps collected from space, with an initial focus on low oxygenevents, due to their large spatial extent and regular occurrence each summer.We also evaluated similar in situ data collected during 1984-2021by the Chesapeake Program.

Nargess Memarsadeghi↗

The development of a method for predicting the noise exposure of payloads in the space shuttle orbiter vehicle

The development of an analytical model for the prediction of sound levels in the payload bay of the space shuttle orbiter vehicle is outlined. Formulation of the analytical model and its validation by means of model scale and full scale tests are included. It is shown that the approach used in the development effort has resulted in a prediction procedure which can be expected to give reliable estimates of payload bay sound levels, even when a payload is present. Furthermore, the analytical model has the capability of being readily modified to include other excitations such as turbulent boundary layers and propeller near-field pressures, and to other aerospace vehicles.

Wilby, J. F.↗

A recent case study in system identification

Results of a recent study of a ten-bay truss structure at the NASA Langley Research Center are reported. First, the conditioning of complex eigenvectors derived by the ERA method is discussed. Results of parameter estimation using the SSID (Structural System Identification) code are then presented. Based on the results of the study, it is concluded that (1) parameter estimation based on modal data should include eigenvectors as well as eigenvalues; (2) the eigenvectors should be orthogonalized when orthogonality is poor due to closely spaced modes; and (3) the parameters used in the estimation should enable the model to match the data.

Hasselman, T. K.↗

NASA Kennedy Space Center Swamp Works 10th Anniversary: Innovative Research & Technology Development Summary

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes rapid, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up fast, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This paper will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Robotic Mining↗

Swamp Works Technology Development 10th Anniversary: 2013-2023

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes efficient, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up momentum, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This presentation will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Swamp Works↗

Swamp Works Technology Development 10th Anniversary: 2013-2023 - Innovative Research & Technology Development Summary

Kennedy Space Center’s (KSC) Swamp Works, provides government and commercial space ventures with the technologies required for working and living on the surfaces of the Moon or other planets and bodies in our solar system. The Swamp Works team establishes rapid, innovative and cost-effective exploration mission solutions through leveraging of partnerships across NASA, industry and academia. Concepts start small and build up efficiently, with lean development processes and a hands-on approach. Testing is performed in early stages to drive design improvements and progressively increase Technology Readiness Levels (TRL). Swamp Works provides concepts, architecture studies and trades, designs, data, technology development, technology demonstration hardware, flight hardware, testing, flight support and knowledge in support of the development of surface systems. It consists of several teams with associated laboratories and test capabilities. The Granular Mechanics and Regolith Operations (GMRO) Laboratory and the Electrostatics and Surface Physics Laboratory (ESPL) are co-located in the Engineering Development Lab (EDL) facility high bay. The Applied Chemistry Lab (ACL) is in an adjacent facility and other KSC labs are being influenced by the innovation methods pioneered at the Swamp Works. The Swamp Works was founded in January 2013 by a group of scientists and engineers at KSC with the over-arching vision of expanding humanity and civilization into the solar system by the use of space resources via advanced technology. Ultimately, this will create a solar system economy that will improve the human condition due to the abundance of energy and resources. This presentation will summarize the projects and technology development that have been performed by the Swamp Works to celebrate its 10th Anniversary of innovation success.

Swamp Works↗

Document Classification Techniques for Aviation Letters of Agreement

Often when working with technical documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques, including Transfer Learning, for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

Aayushi Batra↗

Document Classification Techniques for Aviation Letters of Agreement

Often when working with historic air traffic management (ATM) documents, it is helpful to classify them into specific categories. In this paper, we conduct a thorough review of natural language processing techniques to perform this classification task on Letters of Agreement (LOAs), technical aviation documents outlining rules for utilizing US airspace. We evaluate multiple techniques for representing the text in the documents as embeddings: unigram and bigram Term Frequency Inverse Document Frequency (TFIDF), Word2Vec, Doc2Vec, GloVe and RoBERTa. We investigate a wide range of classification models: K-Nearest Neighbors, Random Forest, Support Vector Machines (SVM), Logistic Regression, Naive Bayes, Feed-Forward Neural Network, Convolutional Neural Networks (CNNs) and Long-Short Term Memory (LSTM). By comparing the different methods, we found the best overall approach for our task was to use unigram TFIDF representations with SVM while also gaining insight into how the other methodologies performed on a small technical datasets.

ATM↗