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At least 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Preconditioning electromyographic data for an upper extremity model using neural networks

A back propagation neural network has been employed to precondition the electromyographic signal (EMG) that drives a computational model of the human upper extremity. This model is used to determine the complex relationship between EMG and muscle activation, and generates an optimal muscle activation scheme that simulates the actual activation. While the experimental and model predicted results of the ballistic muscle movement are very similar, the activation function between the start and the finish is not. This neural network preconditions the signal in an attempt to more closely model the actual activation function over the entire course of the muscle movement.

Roberson, D. J.↗
NASA NTRS1993

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗
NASA NTRS1996

Research and Technology Report. Goddard Space Flight Center

This issue of Goddard Space Flight Center's annual report highlights the importance of mission operations and data systems covering mission planning and operations; TDRSS, positioning systems, and orbit determination; ground system and networks, hardware and software; data processing and analysis; and World Wide Web use. The report also includes flight projects, space sciences, Earth system science, and engineering and materials.

Soffen, Gerald↗
NASA NTRS2007

Solutions Network Formulation Report. Visible/Infrared Imager/Radiometer Suite and Landsat Data Continuity Mission Simulated Data Products for the Great Lakes Basin Ecological Team

The proposed solution would simulate VIIRS and LDCM sensor data for use in the USGS/USFWS GLBET DST. The VIIRS sensor possesses a spectral range that provides water-penetrating bands that could be used to assess water clarity on a regional spatial scale. The LDCM sensor possesses suitable spectral bands in a range of wavelengths that could be used to map water quality at finer spatial scales relative to VIIRS. Water quality, alongshore sediment transport and pollutant discharge tracking into the Great Lakes system are targeted as the primary products to be developed. A principal benefit of water quality monitoring via satellite imagery is its economy compared to field-data collection methods. Additionally, higher resolution satellite imagery provides a baseline dataset(s) against which later imagery can be overlaid in GIS-based DST programs. Further, information derived from higher resolution satellite imagery can be used to address public concerns and to confirm environmental compliance. The candidate solution supports the Public Health, Coastal Management, and Water Management National Applications.

Estep, Leland↗
NASA NTRS1993

Applications of CCSDS recommendations to Integrated Ground Data Systems (IGDS)

This paper describes an application of the CCSDS Principle Network (CPH) service model to communications network elements of a postulated Integrated Ground Data System (IGDS). Functions are drawn principally from COSMICS (Cosmic Information and Control System), an integrated space control infrastructure, and the Earth Observing System Data and Information System (EOSDIS) Core System (ECS). From functional requirements, this paper derives a set of five communications network partitions which, taken together, support proposed space control infrastructures and data distribution systems. Our functional analysis indicates that the five network partitions derived in this paper should effectively interconnect the users, centers, processors, and other architectural elements of an IGDS. This paper illustrates a useful application of the CCSDS (Consultive Committee for Space Data Systems) Recommendations to ground data system development.

Mizuta, Hiroshi↗
NASA NTRS1988

Development of an integrated set of research facilities for the support of research flight test

The Ames-Dryden Flight Research Facility (DFRF) serves as the site for high-risk flight research on many one-of-a-kind test vehicles like the X-29A advanced technology demonstrator, F-16 advanced fighter technology integration (AFTI), AFTI F-111 mission adaptive wing, and F-18 high-alpha research vehicle (HARV). Ames-Dryden is on a section of the historic Muroc Range. The facility is oriented toward the testing of high-performance aircraft, as shown by its part in the development of the X-series aircraft. Given the cost of research flight tests and the complexity of today's systems-driven aircraft, an integrated set of ground support experimental facilities is a necessity. In support of the research flight test of highly advanced test beds, the DFRF is developing a network of facilities to expedite the acquisition and distribution of flight research data to the researcher. The network consists of an array of experimental ground-based facilities and systems as nodes and the necessary telecommunications paths to pass research data and information between these facilities. This paper presents the status of the current network, an overview of current developments, and a prospectus on future major enhancements.

Moore, Archie L.↗
NASA NTRS1988

Development of an integrated set of research facilities for the support of research flight test

The Ames-Dryden Flight Research Facility (DFRF) serves as the site for the conduct of high-risk flight research on many one-of-a-kind test vehicles like the X-29A advanced technology demonstrator, F-16 advanced fighter technology integration (AFTI), AFTI F-111 mission adaptive wing, and F-18 high-alpha research vehicle (HARV). Ames-Dryden is on a section of the historic Muroc Range. The facility is oriented toward the testing of high-performance aircraft, as shown by its part in the development of the X-series aircraft. Given the cost of research flight test and the complexity of today's systems-driven aircraft, an integrated set of ground support experimental facilities is a necessity. In support of the research flight test of highly advanced test beds, the DFRF is developing a network of facilities to expedite the acquisition and distribution of flight research data to the researcher. This network consists of an array of experimental ground-based facilities and systems as nodes and the necessary telecommunications paths to pass research data and information between these facilities. This paper presents a status of the current network, an overview of current developments, and a prospectus on future major enhancements.

Moore, Archie L.↗
NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗
NASA NTRS2006

Impact of Asian Dust on Global Surface Air Quality and Radiation Budget

Dust originating from Asian deserts and desertification areas can be transported regionally and globally to affect surface air quality, visibility, and radiation budget not only at immediate downwind locations (e.g., eastern Asia) but also regions far away from the sources (e.g., North America). Deposition of Asian dust to the North Pacific Ocean basin influences the ocean productivity. In this study, we will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, remote sensing data form satellite and from the ground-based network, and in-situ data from aircraft and surface observations to address the following questions: - What are the effects of Asian dust on the surface air quality and visibility over Asia and North America? - What are the seasonal and spatial variations of dust deposition to the North Pacific Ocean? How does the Asian dust affect surface radiation budget?

Chin, Mian↗
NASA NTRS2022

Drought Monitoring with Drones: A Hundred Fields at a Time

Drought frequency and severity are likely to increase due to global warming. Droughts already have a substantial negative influence on agriculture and the economy and finding ways to reduce their effects could have a monumental impact. Although NASA already has satellites deployed to collect drought data, these satellites are more for global drought indexing than local. To alleviate droughts on a local level, this paper proposes the use of drones to map soil moisture, plant health, and other drought indicators. The proposed drone design is a fixed-wing UAV equipped with a hyperspectral camera, a LiDAR sensor, and an array of weather sensors. These tools will permit it to reliably capture the necessary data to enhance suggestions on improving drought management practices. The collected data from the drones will be deployable in many ways, including for agricultural and non-agricultural applications. The hyperspectral camera has applications in monitoring the health of crops within a field to direct relief measures to the crops most in need. Thermal and LiDAR imaging can be deployed for locating leaks, predicting shortages of water bodies, and determining a field’s water needs. To implement a drought-monitoring drone, the recommended steps include building a prototype drone design that is equipped with the outlined instruments. The prototype drone could then be deployed to collect training data to guide a neural network that would provide interpretations and predictions from the data for users. After the prototype design is iterated upon, it will be ready for deployment and inform water management methods to serve the world in our battle against drought.

climate change↗
NASA NTRS1973

Geometric adjustment of the South American satellite densification (PC-1000) network

Reduced normal equations were computed from observation data and combined with reduced normal equations of other satellite networks to provide station coordinates from a single least square adjustment. Terrestrial data, which include base-lines, heights, and survey coordinates, provide the necessary relative position constraints between collocated stations of two satellite networks. Survey information regarding the observation stations is summarized, and constraints used in the solution are given. Geoidal undulations are computed by using the formula and constants shown.

Mueller, I. I.↗
NASA NTRS2014

Concepts to Support HRP Integration Using Publications and Modeling

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Mindock, J.↗
NASA NTRS1997

Scientific Visualization in High Speed Network Environments

In several cases, new visualization techniques have vastly increased the researcher's ability to analyze and comprehend data. Similarly, the role of networks in providing an efficient supercomputing environment have become more critical and continue to grow at a faster rate than the increase in the processing capabilities of supercomputers. A close relationship between scientific visualization and high-speed networks in providing an important link to support efficient supercomputing is identified. The two technologies are driven by the increasing complexities and volume of supercomputer data. The interaction of scientific visualization and high-speed networks in a Computational Fluid Dynamics simulation/visualization environment are given. Current capabilities supported by high speed networks, supercomputers, and high-performance graphics workstations at the Numerical Aerodynamic Simulation Facility (NAS) at NASA Ames Research Center are described. Applied research in providing a supercomputer visualization environment to support future computational requirements are summarized.

Vaziri, Arsi↗
NASA NTRS1977

Network functions and facilities

Objectives, functions, and organization of the Deep Space Network are summarized. A deep space station, ground communication, and network operations control capabilities are described. Data system configurations for testing, training, and network operations control functions are outlined.

Renzetti, N. A.↗
NASA NTRS1990

Experience with abstract notation one

The development of computer science has produced a vast number of machine architectures, programming languages, and compiler technologies. The cross product of these three characteristics defines the spectrum of previous and present data representation methodologies. With regard to computer networks, the uniqueness of these methodologies presents an obstacle when disparate host environments are to be interconnected. Interoperability within a heterogeneous network relies upon the establishment of data representation commonality. The International Standards Organization (ISO) is currently developing the abstract syntax notation one standard (ASN.1) and the basic encoding rules standard (BER) that collectively address this problem. When used within the presentation layer of the open systems interconnection reference model, these two standards provide the data representation commonality required to facilitate interoperability. The details of a compiler that was built to automate the use of ASN.1 and BER are described. From this experience, insights into both standards are given and potential problems relating to this development effort are discussed.

Harvey, James D.↗
NASA NTRS1989

Applications of MST radars: Meteorological applications

Applications of mesosphere stratosphere troposphere radar to mesoscale meteorology are discussed. The applications include using the radar either as a research tool to improve our understanding of certain dynamical systems or as part of a network used to provide input data for weather forecasting. The workhorse of the operational observing network is the radiosonde balloon which provides measurements of pressure, temperature, humidity, and winds up to heights of 16 to 20 km. Horizontal and vertical measurement capabilities, reflectivity data, derivable quantities and parameters, and special operational requirements are surveyed.

Larsen, M. F.↗
NASA NTRS1975

Air motion determination by tracking humidity patterns in isentropic layers

Determining air motions by tracking humidity patterns in isentropic layers was investigated. Upper-air rawinsonde data from the NSSL network and from the AVE-II pilot experiment were used to simulate temperature and humidity profile data that will eventually be available from geosynchronous satellites. Polynomial surfaces that move with time were fitted to the mixing-ratio values of the different isentropic layers. The velocity components of the polynomial surfaces are part of the coefficients that are determined in order to give an optimum fitting of the data. In the mid-troposphere, the derived humidity motions were in good agreement with the winds measured by rawinsondes so long as there were few or no clouds and the lapse rate was relatively stable. In the lower troposphere, the humidity motions were unreliable primarily because of nonadiabatic processes and unstable lapse rates. In the upper troposphere, the humidity amounts were too low to be measured with sufficient accuracy to give reliable results. However, it appears that humidity motions could be used to provide mid-tropospheric wind data over large regions of the globe.

Mancuso, R. L.↗
NASA NTRS2005

Data-Rate Estimation for Autonomous Receiver Operation

In this article, we present a series of algorithms for estimating the data rate of a signal whose admissible data rates are integer base, integer powered multiples of a known basic data rate. These algorithms can be applied to the Electra radio currently used in the Deep Space Network (DSN), which employs data rates having the above relationship. The estimation is carried out in an autonomous setting in which very little a priori information is assumed. It is done by exploiting an elegant property of the split symbol moments estimator (SSME), which is traditionally used to estimate the signal-to-noise ratio (SNR) of the received signal. By quantizing the assumed symbol-timing error or jitter, we present an all-digital implementation of the SSME which can be used to jointly estimate the data rate, SNR, and jitter. Simulation results presented show that these joint estimation algorithms perform well, even in the low SNR regions typically encountered in the DSN.

Tkacenko, A.↗