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At least 37 records · Page 2

Pattern-recognition techniques applied to performance monitoring of the DSS 13 34-meter antenna control assembly

The results of applying pattern recognition techniques to diagnose fault conditions in the pointing system of one of the Deep Space network's large antennas, the DSS 13 34-meter structure, are discussed. A previous article described an experiment whereby a neural network technique was used to identify fault classes by using data obtained from a simulation model of the Deep Space Network (DSN) 70-meter antenna system. Described here is the extension of these classification techniques to the analysis of real data from the field. The general architecture and philosophy of an autonomous monitoring paradigm is described and classification results are discussed and analyzed in this context. Key features of this approach include a probabilistic time-varying context model, the effective integration of signal processing and system identification techniques with pattern recognition algorithms, and the ability to calibrate the system given limited amounts of training data. Reported here are recognition accuracies in the 97 to 98 percent range for the particular fault classes included in the experiments.

Mellstrom, J. A.↗

The noon and midnight mid-latitude trough as seen by Ariel 4

The electron density data returned by the polar orbiting satellites Ariel 3 and Ariel 4 revealed that the midlatitude trough is one of the distinct large-scale features of the ionosphere at about 550 km. Recent work (e.g., Tulunay and Grebowsky, 1975) on the data included the investigation of the temporal development of the latitudinal position of the midlatitude electron density trough at dawn and dusk during the large magnetic storms of May 1967 and May 1972. Model calculations which assumed that the equatorial convection E-field varies in step with the Kp index reproduced on the average the observed behavior. In the present paper, trough observations made at noon and midnight during the period, 12-21 December 1971 which encompassed a relatively large magnetic storm are discussed. In this context, model calculations have been employed as a guide of average approximations of the actual situation in predicting the plasmapause location. It is also shown that the trough observed on the noon passes is not generally plasmapause-related as the nightside troughs are expected to be.

Tulunay, Y. K.↗

Development of NASA's Accident Precursor Analysis Process Through Application on the Space Shuttle Orbiter

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system. APA docs more than simply track experience: it systematically evaluates experience, looking for under-appreciated risks that may warrant changes to design or operational practice. This paper presents the pilot application of the NASA APA process to Space Shuttle Orbiter systems. In this effort, the working sessions conducted at Johnson Space Center (JSC) piloted the APA process developed by Information Systems Laboratories (ISL) over the last two years under the auspices of NASA's Office of Safety & Mission Assurance, with the assistance of the Safety & Mission Assurance (S&MA) Shuttle & Exploration Analysis Branch. This process is built around facilitated working sessions involving diverse system experts. One important aspect of this particular APA process is its focus on understanding the physical mechanism responsible for an operational anomaly, followed by evaluation of the risk significance of the observed anomaly as well as consideration of generalizations of the underlying mechanism to other contexts. Model completeness will probably always be an issue, but this process tries to leverage operating experience to the extent possible in order to address completeness issues before a catastrophe occurs.

Maggio, Gaspare↗

Atmospheric model development in support of SEASAT. Volume 5: Test results with fine-mesh (187 by 187 by 10) model

A model (187 x 187 grid with ten layers) was used to produce a 24 hour forecast using initial conditions for 1200Z, 20 May 1976. This forecast was compared to its five layer counterpart on the 187 x 187 grid and to its 63 x 63 coarse mesh counterpart having the same number of layers. Increases in horizontal resolution lead to significant differences in a one day forecast. Many of these differences represent improvements. Increases in vertical resolution tend to produce smaller impacts on the forecast, except in the region near and above the tropopause. The effect on forecast precipitation is in the 10-20% range, as opposed to the 100% for increases in the horizontal resolution. With respect to model energetics (kinetic energy; square vorticity; square divergence), the model tend to group according to horizontal resolution. The time variations of these parameters show that dynamic initialization is needed to: (1) minimize initialization shock; and (2) stabilize the model context to prevent wash-out of small scale information during the adjustment period (first 6-12 forecast hours).

Kesel, P. G.↗

Studies on image compression and image reconstruction

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Sayood, Khalid↗

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Kiely, A.↗

Lossless Compression of Classification-Map Data

A lossless image-data-compression algorithm intended specifically for application to classification-map data is based on prediction, context modeling, and entropy coding. The algorithm was formulated, in consideration of the differences between classification maps and ordinary images of natural scenes, so as to be capable of compressing classification- map data more effectively than do general-purpose image-data-compression algorithms. Classification maps are typically generated from remote-sensing images acquired by instruments aboard aircraft (see figure) and spacecraft. A classification map is a synthetic image that summarizes information derived from one or more original remote-sensing image(s) of a scene. The value assigned to each pixel in such a map is the index of a class that represents some type of content deduced from the original image data for example, a type of vegetation, a mineral, or a body of water at the corresponding location in the scene. When classification maps are generated onboard the aircraft or spacecraft, it is desirable to compress the classification-map data in order to reduce the volume of data that must be transmitted to a ground station.

Hua, Xie↗

NASA Tech Briefs, February 2010

Topics covered include: Insulation-Testing Cryostat With Lifting Mechanism; Optical Testing of Retroreflectors for Cryogenic Applications; Measuring Cyclic Error in Laser Heterodyne Interferometers; Self-Referencing Hartmann Test for Large-Aperture Telescopes; Measuring a Fiber-Optic Delay Line Using a Mode-Locked Laser; Reconfigurable Hardware for Compressing Hyperspectral Image Data; Spatio-Temporal Equalizer for a Receiving-Antenna Feed Array; High-Speed Ring Bus; Nanoionics-Based Switches for Radio-Frequency Applications; Lunar Dust-Tolerant Electrical Connector; Compact, Reliable EEPROM Controller; Quad-Chip Double-Balanced Frequency Tripler; Ka-Band Waveguide Two-Way Hybrid Combiner for MMIC Amplifiers; Radiation-Hardened Solid-State Drive; Use of Nanofibers to Strengthen Hydrogels of Silica, Other Oxides, and Aerogels; Two Concepts for Deployable Trusses; Concentric Nested Toroidal Inflatable Structures; Investigating Dynamics of Eccentricity in Turbomachines; Improved Low-Temperature Performance of Li-Ion Cells Using New Electrolytes; Integrity Monitoring of Mercury Discharge Lamps; White-Light Phase-Conjugate Mirrors as Distortion Correctors; Biasable, Balanced, Fundamental Submillimeter Monolithic Membrane Mixer; ICER-3D Hyperspectral Image Compression Software; and Context Modeler for Wavelet Compression of Spectral Hyperspectral Images.

Source record↗

Climatic History of the Northeastern United States During the Past 3000 Years

Many ecosystem processes that influence Earth system feedbacks - vegetation growth, water and nutrient cycling, disturbance regimes - are strongly influenced by multidecadal- to millennial-scale climate variations that cannot be directly observed. Paleoclimate records provide information about these variations, forming the basis of our understanding and modeling of them. Fossil pollen records are abundant in the NE US, but cannot simultaneously provide information about paleoclimate and past vegetation in a modeling context because this leads to circular logic. If pollen data are used to constrain past vegetation changes, then the remaining paleoclimate archives in the northeastern US (NE US) are quite limited. Nonetheless, a growing number of diverse reconstructions have been developed but have not yet been examined together. Here we conduct a systematic review, assessment, and comparison of paleotemperature and paleohydrological proxies from the NE US for the last 3000 years. Regional temperature reconstructions (primarily summer) show a long-term cooling trend (1000BCE - 1700CE) consistent with hemispheric-scale reconstructions, while hydroclimate data show gradually wetter conditions through the present day. Multiple proxies suggest that a prolonged, widespread drought occurred between 550 and 750CE. Dry conditions are also evident during the Medieval Climate Anomaly, which was warmer and drier than the Little Ice Age and drier than today. There is some evidence for an acceleration of the longer-term wetting trend in the NE US during the past century; coupled with an abrupt shift from decreasing to increasing temperatures in the past century, these changes could have wide-ranging implications for species distributions, ecosystem dynamics, and extreme weather events. More work is needed to gather paleoclimate data in the NE US to make inter-proxy comparisons and to improve estimates of uncertainty in reconstructions.

Marlon, Jennifer R.↗

A comparative study of atmospheric density models in the context of definitive and predictive earth satellite orbit determination

The results of a comparative orbit determination study of four global atmospheric density models (modified Harris-Priester, Jacchia-Roberts, Mass Spectrometer/Incoherent Scatter (MSIS), and Simple Exponential Model (SEM)) are presented. Utilizing these models, definitive orbit determination consistency and accuracy are evaluated using the maximum position differences that occur during 6-hour overlap periods between ephemerides generated from 30-hour data arcs. Propagated ephemerides are compared with definitive orbit solutions to evaluate predictive accuracy. The results indicate that, for satellites above 300 kilometers, all four atmospheric density models produce comparable orbit determination accuracies when an atmospheric drag scaling factor and the satellite state vector are estimated in the orbit determination process.

Shanklin, R. E., Jr.↗

The effects of context on multidimensional spatial cognitive models

Spatial cognitive models obtained by multidimensional scaling represent cognitive structure by defining alternatives as points in a coordinate space based on relevant dimensions such that interstimulus dissimilarities perceived by the individual correspond to distances between the respective alternatives. The dependence of spatial models on the context of the judgments required of the individual was investigated. Context, which is defined as a perceptual interpretation and cognitive understanding of a judgment situation, was analyzed and classified with respect to five characteristics: physical environment, social environment, task definition, individual perspective, and temporal setting. Four experiments designed to produce changes in the characteristics of context and to test the effects of these changes upon individual cognitive spaces are described with focus on experiment design, objectives, statistical analysis, results, and conclusions. The hypothesis is advanced that an individual can be characterized as having a master cognitive space for a set of alternatives. When the context changes, the individual appears to change the dimension weights to give a new spatial configuration. Factor analysis was used in the interpretation and labeling of cognitive space dimensions.

Dupnick, E. G.↗

Information access in a dual-task context: testing a model of optimal strategy selection

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

User-Computer Interface↗

Hidden Markov Models for Fault Detection in Dynamic Systems

Continuous monitoring of complex dynamic systems is an increasingly important issue in diverse areas such as nuclear plant safety, production line reliability, and medical health monitoring systems. Recent advances in both sensor technology and computational capabilities have made on-line permanent monitoring much more feasible than it was in the past. In this paper it is shown that a pattern recognition system combined with a finite-state hidden Markov model provides a particularly useful method for modelling temporal context in continuous monitoring. The parameters of the Markov model are derived from gross failure statistics such as the mean time between failures. The model is validated on a real-world fault diagnosis problem and it is shown that Markov modelling in this context offers significant practical benefits.

Smyth, Padhraic↗

Analytical model for orbital debris environmental management

A differential equation, also referred to as the PIB (particle-in-a-box) model, expressing the time rate of change of the number of objects in orbit, is developed, and its applicability is illustrated. The model can be used as a tool for the assessment of LEO environment stability, and as a starting point for the development of numerical evolutionary models. Within the context of the model, evolutionary scenarios are examined, and found to be sensitive to the growth rate. It is determined that the present environment is slightly unstable to catastrophic growth, and that the number of particles on orbit will continue to increase until approximately 2250-2350 AD, with a maximum of 2,000,000. The model is expandable to the more realistic (complex) case of multiple species in a multiple-tier system.

Talent, David L.↗

Software Helps Retrieve Information Relevant to the User

The Adaptive Indexing and Retrieval Agent (ARNIE) is a code library, designed to be used by an application program, that assists human users in retrieving desired information in a hypertext setting. Using ARNIE, the program implements a computational model for interactively learning what information each human user considers relevant in context. The model, called a "relevance network," incrementally adapts retrieved information to users individual profiles on the basis of feedback from the users regarding specific queries. The model also generalizes such knowledge for subsequent derivation of relevant references for similar queries and profiles, thereby, assisting users in filtering information by relevance. ARNIE thus enables users to categorize and share information of interest in various contexts. ARNIE encodes the relevance and structure of information in a neural network dynamically configured with a genetic algorithm. ARNIE maintains an internal database, wherein it saves associations, and from which it returns associated items in response to a query. A C++ compiler for a platform on which ARNIE will be utilized is necessary for creating the ARNIE library but is not necessary for the execution of the software.

Mathe, Natalie↗

Noise-driven sidebranching in the boundary-layer model of dendritic solidification

In the context of local models of solidification, it is suggested that the sidebranching which appears to be a characteristic feature of dendritic processes may be generated by selective amplification of noise near the tip and that, under some circumstances, thermal fluctuations may be strong enough to explain the observed effects. This proposal is discussed based on the two-dimensional boundary-layer model with kinetic crystalline anisotropy. Experimental methods to distinguish this stochastic process from a deterministic, dynamical sidebranching mechanism are suggested, including the possibility of space-based experiments.

Pieters, R.↗