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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Head and Trunk Movement Control During Locomotion After Long-Duration Spaceflight

Exposure to the microgravity environment encountered during spaceflight induces adaptive alteration in sensorimotor function that leads to postflight disturbances in locomotor control. Head and trunk movement control plays a central role in maintaining gaze stability and in providing a stable reference system to permit spatial navigation in a complex and constantly varying environment. The goal of the present study was to investigate the effects of long-duration spaceflight (3-6 months) on head and trunk movement control during postflight terrestrial locomotion. Before and after spaceflight, subjects walked on a motorized treadmill while performing a challenging gaze stabilization task requiring number recognition. Head and trunk kinematic data were collected with a video-based motion analysis system. Analysis of roll, pitch and yaw head and trunk movements during treadmill walking revealed postflight alterations in head and trunk movement control in all three planes of motion. Subjects also experienced oscillopsia during postflight walking which led to impairment in performance of the number recognition task. These data indicate that exposure to long-duration space flight causes alteration in head and trunk movement control during postflight locomotion. These changes have implications for the control of gaze and maintenance of dynamic stability during walking after long-duration spaceflight.

Bloomberg, Jacob J.↗
NASA NTRS1974

An analysis of pilot error-related aircraft accidents

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Kowalsky, N. B.↗
NASA NTRS2000

A Balanced Model for Exploration of the Terrestrial Planets: Lessons from the Lunar Experience

The Moon is the only extraterrestrial rocky body for which we have a combination of surface-selected samples, high-resolution orbital photography (Lunar Orbiter), manned and robotic surface exploration (Surveyor, Apollo, Luna), and global compositional, mineralogical, and geophysical data (Galileo, Clementine, Lunar Prospector). Beginning in 1998, CAPTEM organized a series of workshops and conference sessions aimed at integrating these diverse data sets. The insights gained by bringing together scientists from the remote-sensing and sample-analysis communities have been singularly rewarding. Not least of these has been the recognition by both groups that having both kinds of data maximizes the scientific return and permits reconciling information from diverse scales and perspectives. The 20-20 hindsight of the Lunar experience thus provides important lessons; learning from mistakes as well as successes, we can derive a sensible scientific program for Mars exploration. In this abstract, we describe examples of key information from (a) in-situ geologic investigation, (b) laboratory analysis of returned samples whose geologic context and location are known, and (c) global remote sensing of mineralogy, composition, and geophysical parameters. We then show the value of integrating these diverse data sets.

Jolliff, B. L.↗
NASA NTRS1973

Fracture trends identified by ERTS-1 imagery in Utah and Nevada

The author has identified the following significant results. In the Utah-Nevada area, linear structural trends recorded on ERTS-1 imagery conform in part to previously recognized structures. In addition, the ERTS-1 imagery reveals cryptic structures not previously identified and not readily apparent in other imagery. These structures are illustrated by prominent east-west trending structures which appear to be concentrated in pre-volcanic rocks. This suggests that the structures are older than many of those with other trends which are equally prominent in volcanic and non-volcanic terrain. Since the older east-west structures may have controlled early Tertiary emplacement of magma or the ascent of mineralizing fluids, their recognition is important in minerial exploration. Soil-gas sampling and analysis for mercury content is being continued over structures, and projected trends of buried structures which appear, from studies of ERTS-1 imagery, to be favorable to mineralization. Comparison of ERTS-1 and Skylab imagery indicated that ERTS-1 imagery records more previously unrecognized linear structures than the Skylab imagery. In differentiating and identifying different rock types, the Skylab imagery appears to be more effective.

Jensen, M. L.↗
NASA NTRS1973

Correlation of ERTS MSS data and earth coordinate systems

The author has identified the following significant results. Experience has revealed a problem in the analysis and interpretation of ERTS-1 multispectral scanner (MSS) data. The problem is one of accurately correlating ERTS-1 MSS pixels with analysis areas specified on aerial photographs or topographic maps for training recognition computers and/or evaluating recognition results. It is difficult for an analyst to accurately identify which ERTS-1 pixels on a digital image display belong to specific areas and test plots, especially when they are small. A computer-aided procedure to correlate coordinates from topographic maps and/or aerial photographs with ERTS-1 data coordinates has been developed. In the procedure, a map transformation from earth coordinates to ERTS-1 scan line and point numbers is calculated using selected ground control points nad the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS-1 point and line numbers. An optional provision allows moving the boundaries of the plots inward by variable distances so the selected pixels will not overlap adjacent features.

Malila, W. A.↗
NASA NTRS1973

Correlation of ERTS MSS data and earth coordinate systems

Experience has revealed a problem in the analysis and interpretation of ERTS multispectral scanner (MSS) data. The problem is one of accurately correlating ERTS MSS pixels (picture elements) with analysis areas specified on aerial photographs or topographic maps for training recognition computers and/or evaluating recognition results. A computer-aided procedure to correlate coordinates from topographic maps and/or aerial photographs with ERTS data coordinates has been developed. In the procedure, a map transformation from earth coordinates to ERTS scan line and point numbers is calculated using selected ground control points and the method of least squares. The map transformation is then applied to the earth coordinates of selected areas to obtain the corresponding ERTS point and line numbers.

Malila, W. A.↗
NASA NTRS1975

Bringing remote sensing technology to the user community

The procedures and services available for educating and training potential users of remote sensing technology are discussed along with approaches for achieving an in-house capability for the analysis of remotely sensed data using numerical techniques based on pattern recognition principles. Cost estimates are provided where appropriate.

Lindenlaub, J. C.↗
NASA NTRS1973

Geometric aspects in digital analysis of Multi-Spectral Scanner (MSS) data

Present automated systems of interpretation which apply pattern recognition techniques on MSS data do not fully consider the geometry of the acquisition system. In an effort to improve the usefulness of the MSS data when digitally treated, geometric aspects are analyzed and discussed. Attempts to correct for scanner instabilities in position and orientation by affine and polynomial transformations, as well as by modified collinearity equations are described. Methods of accounting for panoramic and relief effects are also discussed. It is anticipated that reliable area as well as position determinations can be accomplished during the process of automatic interpretation. A concept for a unified approach to the treatment of remote sensing data, both metric and nonmetric is presented.

Mikhail, E. M.↗
NASA NTRS1992

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Houlahan, Padraig↗
NASA NTRS1992

Multiresolution pattern recognition of small volcanos in Magellan data

The Magellan data is a treasure-trove for scientific analysis of venusian geology, providing far more detail than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations. However, at this point, planetary scientists are being overwhelmed by the sheer quantities of data collected--data analysis technology has not kept pace with our ability to collect and store it. In particular, 'small-shield' volcanos (less than 20 km in diameter) are the most abundant visible geologic feature on the planet. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanos visible in the Magellan data. Identifying and studying these volcanos is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is very time-consuming. Hence, we have undertaken the development of techniques to partially automate this task. The goal is not the unrealistic one of total automation, but rather the development of a useful tool to aid the project scientists. The primary constraints for this particular problem are as follows: (1) the method must be reasonably robust; and (2) the method must be reasonably fast. Unlike most geological features, the small volcanos of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include the following: (1) a circular planimetric outline; (2) known diameter frequency distribution from preliminary studies; (3) a limited number of basic morphological shapes; and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Smyth, P.↗
NASA NTRS2000

Real Time Intelligent Target Detection and Analysis with Machine Vision

We present an algorithm for detecting a specified set of targets for an Automatic Target Recognition (ATR) application. ATR involves processing images for detecting, classifying, and tracking targets embedded in a background scene. We address the problem of discriminating between targets and nontarget objects in a scene by evaluating 40x40 image blocks belonging to an image. Each image block is first projected onto a set of templates specifically designed to separate images of targets embedded in a typical background scene from those background images without targets. These filters are found using directed principal component analysis which maximally separates the two groups. The projected images are then clustered into one of n classes based on a minimum distance to a set of n cluster prototypes. These cluster prototypes have previously been identified using a modified clustering algorithm based on prior sensed data. Each projected image pattern is then fed into the associated cluster's trained neural network for classification. A detailed description of our algorithm will be given in this paper. We outline our methodology for designing the templates, describe our modified clustering algorithm, and provide details on the neural network classifiers. Evaluation of the overall algorithm demonstrates that our detection rates approach 96% with a false positive rate of less than 0.03%.

Howard, Ayanna↗
NASA NTRS2018

The Ocean Carbon States Database: A Proof-of-Concept Application of Cluster Analysis in the Ocean Carbon Cycle

In this paper, we present a database of the basic regimes of the carbon cycle in the ocean, the 'ocean carbon states', as obtained using a data mining/pattern recognition technique in observation-based as well as model data. The goal of this study is to establish a new data analysis methodology, test it and assess its utility in providing more insights into the regional and temporal variability of the marine carbon cycle. This is important as advanced data mining techniques are becoming widely used in climate and Earth sciences and in particular in studies of the global carbon cycle, where the interaction of physical and biogeochemical drivers confounds our ability to accurately describe, understand, and predict CO2 concentrations and their changes in the major planetary carbon reservoirs. In this proof-of-concept study, we focus on using well-understood data that are based on observations, as well as model results from the NASA Goddard Institute for Space Studies (GISS) climate model. Our analysis shows that ocean carbon states are associated with the subtropical-subpolar gyre during the colder months of the year and the tropics during the warmer season in the North Atlantic basin. Conversely, in the Southern Ocean, the ocean carbon states can be associated with the subtropical and Antarctic convergence zones in the warmer season and the coastal Antarctic divergence zone in the colder season. With respect to model evaluation, we find that the GISS model reproduces the cold and warm season regimes more skillfully in the North Atlantic than in the Southern Ocean and matches the observed seasonality better than the spatial distribution of the regimes. Finally, the ocean carbon states provide useful information in the model error attribution. Model air-sea CO2 flux biases in the North Atlantic stem from wind speed and salinity biases in the subpolar region and nutrient and wind speed biases in the subtropics and tropics. Nutrient biases are shown to be most important in the Southern Ocean flux bias.

carbon cycle↗
NASA NTRS1971

Automated geologic mapping using rock reflectances.

Investigation of the feasibility of preparing geologic maps automatically through computer processing of calibrated narrow-band visible and near IR reflectivity data collected with a 12-channel scanner. Five procedures were followed in the computer analysis of the radiances recorded as voltages on analog magnetic tape. Three recognition maps have been generated iteratively using a progressively more complex classification scheme. The overall accuracy of the first recognition map was 80%, but the discrimination of the limestone and dolomite was only 50-60%. All three maps are very accurate outcrop maps. The results demonstrate the feasibility of automated geologic mapping in this relatively simple setting.

Watson, R. D.↗
NASA NTRS1974

Burke County wheat feasibility study

A feasibility study was conducted to determine whether wheat could be distinguished from other small grain crops in a selected spring wheat growing area in Burke County, North Dakota using a maximum likelihood classification program and ERTS 1 multispectral band scanner data. ERTS 1 data scenes were selected from passes made on June 5, 1973 and June 23, 1973. The Univac 1108 computer and the LARSYS pattern recognition software package were used in performing the classification. Results of the analysis are provided.

Kunkel, W. A.↗
NASA NTRS1988

Evidence against the involvement of ionically bound cell wall proteins in pea epicotyl growth

Ionically bound cell wall proteins were extracted from 7 day old etiolated pea (Pisum sativum L. cv Alaska) epicotyls with 3 molar LiCl. Polyclonal antiserum was raised in rabbits against the cell wall proteins. Growth assays showed that treatment of growing region segments (5-7 millimeters) of peas with either dialyzed serum, serum globulin fraction, affinity purified immunoglobulin, or papain-cleaved antibody fragments had no effect on growth. Immunofluorescence microscopy confirmed antibody binding to cell walls and penetration of the antibodies into the tissues. Western blot analysis, immunoassay results, and affinity chromatography utilizing Sepharose-bound antibodies confirmed recognition of the protein preparation by the antibodies. Experiments employing in vitro extension as a screening measure indicated no effect upon extension by antibodies, by 50 millimolar LiCl perfusion of the apoplast or by 3 molar LiCl extraction. Addition of cell wall protein to protease pretreated segments did not restore extension nor did addition of cell wall protein to untreated segments increase extension. It is concluded that, although evidence suggests that protein is responsible for the process of extension, the class(es) of proteins which are extracted from pea cell walls with 3 molar LiCl are probably not involved in this process.

NASA Program Space Biology↗
NASA NTRS1973

Relation of ERTS-1 detected geologic structure to known economic ore deposits

A preliminary analysis of ERTS-1 imagery of the Northern Coast Ranges and Sacramento Valley, California, has disclosed a potentially important fracture system which may be one of the controlling factors in the location of known mercury deposits in the Coast Ranges and which appears to be associated with some of the oil and gas fields within the Sacramento Valley. Recognition of this fracture system may prove to be an extremely useful exploration tool, hence careful analysis of subsequent ERTS imagery might delineate areas for field evaluation.

Rich, E. I.↗
NASA NTRS1974

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented.

Kriegler, F. J.↗
NASA NTRS1974

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

Kriegler, F. J.↗