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At least 487 records · Page 27

System of Experts for Intelligent Data Management (SEIDAM)

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

System of experts for intelligent data management (SEIDAM)

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Goodenough, David G.↗

Resources Management System

Delta Data Systems, Inc. was originally formed by NASA and industry engineers to produce a line of products that evolved from ELAS, a NASA-developed computer program. The company has built on that experience, using ELAS as the basis for other remote sensing products. One of these is AGIS, a computer package for geographic and land information systems. AGIS simultaneously processes remotely sensed and map data. The software is designed to operate on a low cost microcomputer, putting resource management tools within reach of small operators.

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A global model of carbon-nutrient interactions

The global biogeochemical model presented has two primary objectives. First, it characterizes natural elemental cycles and their linkages for the four elements significant to Earth's biota: C, N, S, and P. Second, it describes changes in these cycles due to human activity. Global nutrient cycles were studied within the drainage basins of several major world rivers on each continent. The initial study region was the Mississippi drainage basin, concentrating on carbon and nitrogen. The model first establishes the nutrient budgets of the undisturbed ecosystems in a study region. It then uses a data set of land use histories for that region to document the changes in these budgets due to land uses. Nutrient movement was followed over time (1800 to 1980) for 30 ecosystems and 10 land use categories. A geographically referenced ecological information system (GREIS) was developed to manage the digital global data bases of 0.5 x 0.5 grid cells needed to run the model: potential vegetation, drainage basins, precipitation, runoff, contemporary land cover, and FAO soil maps of the world. The results show the contributions of land use categories to river nutrient loads on a continental scale; shifts in nutrient cycling patterns from closed, steady state systems to mobile transient or open, steady state systems; soil organic matter depletion patterns in U.S. agricultural lands; changing nutrient ratios due to land use changes; and the effect of using heavy fertilizer on aquatic systems.

Moore, Berrien, III↗

Overview of the Astrophysics Data System

The Astrophysics Division of NASA has built a geographically and logically distributed heterogeneous information system for the dissemination and coordinated multispectral analysis of data from astrophysics missions. The Astrophysics Data System (ADS) is a truly distributed system in which the data and the required processing are physically distributed. To accommodate the anticipated growth and changes in both requirements and technology, the ADS employs a server/client architecture which allows services and data to be added or replaced without having to change the basic architecture or interfaces. Current datasets accessible through the system include all the tabular astronomical data available at each of six existing astrophysics data centers. Additional data nodes, at both NASA data centers and academic institutions, will be added shortly. The future evolution of the system will be driven in large part by user services mounted both by the ADS project itself and by members of the astrophysics community.

Good, John C.↗

Displaying Geographically-Based Domestic Statistics

Decision Information Display System (DIDS) is rapid-response information-retrieval and color-graphics display system. DIDS transforms tables of geographically-based domestic statistics (such as population or unemployment by county, energy usage by county, or air-quality figures) into high-resolution, color-coded maps on television display screen.

Quann, J.↗

Overview of the Astrophysics Data System

The Astrophysics Division of NASA has built a geographically- and logically-distributed heterogeneous information system for the dissemination and coordinated multispectral analysis of data from astrophysics missions. The Astrophysics Data System (ADS) is a truly distributed system in which the data and the required processing are physically distributed. To accommodate the anticipated growth and changes in both requirements and technology, the ADS employs a server/client architecture which allows services and data to be added or replaced without having to change the basic architecture or interfaces. Current datasets accessible through the system include all the tabular astronomical data available at each of six existing astrophysics data centers. Additional data nodes, at both NASA data centers and academic institutions, will be added shortly. The future evolution of the system will be driven in large part by user services mounted both by the ADS project itself and by members of the astrophysics community.

Good, John C.↗

Pilot study of the domestic information display system in state and local government

An interactive computer based system that can retrieve a wide range of data (demographic, environmental, socio-economic, etc.,) from a large data base and display these data for different geographic units in the form of choropleth maps was developed. The system was designed to display statistical information in a geographic format for national policy makers.

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The natural resources inventory system ASVT project

The hardware/software and the associated procedures for a natural resource inventory and information system based on the use of LANDSAT-acquired multispectral scanner digital data is described. The system is designed to derive land cover/vegetation information from LANDSAT data and geographically reference this information for the production of various types of maps and for the compilation of acreage by land cover/vegetation category. The system also provides for data base building so that the LANDSAT-derived information can be related to information digitized from other sources (e.g., soils maps) in a geographic context in order to address specific applications. These applications include agricultural crop production estimation, erosion hazard-reforestation need assessment, whitetail deer habitat assessment, and site selection. The system is tested in demonstration areas located in the state of Mississippi, and the results of these application demonstrations are presented. A cost-efficiency comparison of producing land cover/vegetation maps and statistics with this system versus the use of small-scale aerial photography is made.

Joyce, A. T.↗

A National Virtual Specimen Database for Early Cancer Detection

Access to biospecimens is essential for enabling cancer biomarker discovery. The National Cancer Institute's (NCI) Early Detection Research Network (EDRN) comprises and integrates a large number of laboratories into a network in order to establish a collaborative scientific environment to discover and validate disease markers. The diversity of both the institutions and the collaborative focus has created the need for establishing cross-disciplinary teams focused on integrating expertise in biomedical research, computational and biostatistics, and computer science. Given the collaborative design of the network, the EDRN needed an informatics infrastructure. The Fred Hutchinson Cancer Research Center, the National Cancer Institute,and NASA's Jet Propulsion Laboratory (JPL) teamed up to build an informatics infrastructure creating a collaborative, science-driven research environment despite the geographic and morphology differences of the information systems that existed within the diverse network. EDRN investigators identified the need to share biospecimen data captured across the country managed in disparate databases. As a result, the informatics team initiated an effort to create a virtual tissue database whereby scientists could search and locate details about specimens located at collaborating laboratories. Each database, however, was locally implemented and integrated into collection processes and methods unique to each institution. This meant that efforts to integrate databases needed to be done in a manner that did not require redesign or re-implementation of existing system

distributed↗

Development of a Web-Based Visualization Platform for Climate Research Using Google Earth

Recently, it has become easier to access climate data from satellites, ground measurements, and models from various data centers, However, searching. accessing, and prc(essing heterogeneous data from different sources are very tim -consuming tasks. There is lack of a comprehensive visual platform to acquire distributed and heterogeneous scientific data and to render processed images from a single accessing point for climate studies. This paper. documents the design and implementation of a Web-based visual, interoperable, and scalable platform that is able to access climatological fields from models, satellites, and ground stations from a number of data sources using Google Earth (GE) as a common graphical interface. The development is based on the TCP/IP protocol and various data sharing open sources, such as OPeNDAP, GDS, Web Processing Service (WPS), and Web Mapping Service (WMS). The visualization capability of integrating various measurements into cE extends dramatically the awareness and visibility of scientific results. Using embedded geographic information in the GE, the designed system improves our understanding of the relationships of different elements in a four dimensional domain. The system enables easy and convenient synergistic research on a virtual platform for professionals and the general public, gr$tly advancing global data sharing and scientific research collaboration.

Sun, Xiaojuan↗

NASA's Information Power Grid: Large Scale Distributed Computing and Data Management

Large-scale science and engineering are done through the interaction of people, heterogeneous computing resources, information systems, and instruments, all of which are geographically and organizationally dispersed. The overall motivation for Grids is to facilitate the routine interactions of these resources in order to support large-scale science and engineering. Multi-disciplinary simulations provide a good example of a class of applications that are very likely to require aggregation of widely distributed computing, data, and intellectual resources. Such simulations - e.g. whole system aircraft simulation and whole system living cell simulation - require integrating applications and data that are developed by different teams of researchers frequently in different locations. The research team's are the only ones that have the expertise to maintain and improve the simulation code and/or the body of experimental data that drives the simulations. This results in an inherently distributed computing and data management environment.

Johnston, William E.↗

Forest Resource Information System (FRIS)

The technological and economical feasibility of using multispectral digital image data as acquired from the LANDSAT satellites in an ongoing operational forest information system was evaluated. Computer compatible multispectral scanner data secured from the LANDSAT satellites were demonstrated to be a significant contributor to ongoing information systems by providing the added dimensions of synoptic and repeat coverage of the Earth's surface. Major forest cover types of conifer, deciduous, mixed conifer-deciduous and non-forest, were classified well within the bounds of the statistical accuracy of the ground sample. Further, when overlayed with existing maps, the acreage of cover type retains a high level of positional integrity. Maps were digitized by a graphics design system, overlayed and registered onto LANDSAT imagery such that the map data with associated attributes were displayed on the image. Once classified, the analysis results were converted back to map form as a cover type of information. Existing tabular information as represented by inventory is registered geographically to the map base through a vendor provided data management system. The notion of a geographical reference base (map) providing the framework to which imagery and tabular data bases are registered and where each of the three functions of imagery, maps and inventory can be accessed singly or in combination is the very essence of the forest resource information system design.

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The State and Development Direction of the Geodetic VLBI Station in Korea

A permanent geodetic VLBI station with a 22-m diameter antenna will be newly constructed in Korea by the National Geographic Information Institute (NGII) under the project Korea VLBI system for Geodesy (KVG) that aims at maintaining the Korean geodetic datum accurately on the International Terrestrial Reference Frame (ITRF). KVG can receive 2, 8, 22, and 43 GHz bands simultaneously in order to conduct geodetic and astronomical VLBI observations with Korea astronomical VLBI stations along with geodetic observations with IVS stations. This simultaneous four-band receiving capability is a unique feature of the KVG system. The KVG has started officially in October 2008. A new geodetic VLBI station will be constructed at Sejong city (about 120 km south of Seoul and about 20 km north-northwest of Daejeon) and construction of all systems will be completed in 2011.

Ju, Hyunhee↗

Evaluation of Extreme Weather Impacts on Utility-scale Photovoltaic Plant Performance in the United States

The global energy system is undergoing significant changes, including a shift in energy generating technologies to more renewable energy sources. However, the dependence of renewable energy sources on local environmental conditions could also increase disruptions in service through exposures to compound, extreme weather events. By fusing three diverse datasets (operations and maintenance tickets, weather data, and production data), this analysis presents a novel methodology to identify and evaluate performance impacts arising from extreme weather events across diverse geographical regions. Text analysis of maintenance tickets identified snow, hurricanes, and storms as the leading extreme weather events affecting photovoltaic plants in the United States. Statistical techniques and machine learning were then implemented to identify the magnitude and variability of these extreme weather impacts on site performance. Impacts varied between event and non-event days, with snow events causing the greatest reductions in performance (54.5%), followed by hurricanes (12.6%) and storms (1.1%). Machine learning analysis identified key features in determining if a day is categorized as low performing, such as low irradiance, geographic location, weather features, and site size. The analysis improves our understanding of compound, extreme weather event impacts on photovoltaic systems, which can inform planning activities, especially as the industry continues to expand into new geographic and climatic regions around the world.

14 SOLAR ENERGY↗

Exploiting Expertise and Knowledge Sharing Online for the Benefit of NASA's GN&C Community of Practice

In 2004, NASA faced major knowledge sharing challenges due to geographically isolated field centers that inhibited engineers from sharing their experiences, expertise, ideas, and lessons learned. The necessity to collaborate on complex development projects and the reality of constrained project resources together drove the need for ensuring that personnel at all NASA centers had comparable skill sets and that engineers could find resources in a timely fashion. Mission failures and new directions for the Agency also demanded better collaborative tools for NASA's engineering workforce. In response to these needs, the online NASA Engineering Network (NEN) was formed by the NASA Office of the Chief Engineer to provide a multi-faceted system for overcoming geographic and cultural barriers. NEN integrates communities of practice with a cross-repository search and the Lessons Learned Information System. This paper describes the features of the GN&C engineering discipline CoP site which went live on NEN in May of 2008 as an online means of gathering input and guidance from practitioners. It allows GN&C discipline expertise captured at one field center to be shared in a collaborative way with the larger discipline CoP spread across the entire Agency. The site enables GN&C engineers to find the information they need quickly, to find solutions to questions from experienced engineers, and to connect with other practitioners regardless of geographic location, thus increasing the probability of project success.

control↗

Field Evaluations of Sampling, Interviewing, and Flight Tracking of NASA's Low Boom Flight Demonstrator Aircraft

The first year’s effort identified sampling and interviewing as the principal risks to assessment of prompt reactions to overflights producing low-amplitude sonic booms. It also 1) established the utility of geo-information system-based route planning for LBFD flight missions, 2) developed and demonstrated a prototype of a geographically-distributed, Internet-enabled instrumentation system capable of wide-area tracking of LBFD aircraft in near-real time. The latter system permits synchronizing the conduct of interviews in multiple overflown communities with arrival times of shock waves at interviewing sites; and of measuring, archiving, and processing their acoustic signatures. Means were also recommended for constructing representative, telephone-based samples of eligible respondents living in households within carpet boom corridors adjacent to LBFD flight tracks, and for conducting interviews with cross-sectional (independent) samples of such respondents about their prompt reactions to exposure to low-amplitude sonic booms. A detailed study design was prepared and accepted by NASA for a set of single-contact attempt telephone interviews with a nationally representative sample of households. The study design focused on testing automated and live agent interview completion rates obtainable without callbacks. A minimal (two monitoring station) version of the aircraft tracking system was built and installed near a civil airport in a successful demonstration of the system’s ability to detect and track aircraft movements. The field exercise also demonstrated the ability of the system to capture the acoustic emissions of departing aircraft, and to serve aircraft position and sound level information to remote, geographically-distributed analysts in near-real time. Upon approval of OMB and IRB of the detailed study plan, a stratified, nationally representative sample of landline and wireless telephone-subscribing households was constructed. A total of 12,734 telephone interview contact attempts of the sort required by a straightforward cross-sectional study design were then made. These contact attempts demonstrated the impracticality of conducting a time-critical, cross-sectional study of prompt community response to low-amplitude sonic booms by means of “independent” (single contact attempt per respondent for each LBFD flight mission) telephone samples of respondents. The observed interview completion rates for these single telephone contact attempts were so low (~ 1% to 3% for automated and live agent interviews, respectively) that: 1) the representativeness of collected opinions would be susceptible to intuitive challenge as inadequate, even absent conclusive evidence of non-representativeness. Refuting challenges to representativeness would have to demonstrate that the composition of the actual sample did not differ from that of the target population, a task that is tantamount to proving a negative; 2) the information required to refute allegations of non-representativeness would require a questionnaire considerably lengthier than that required simply to determine the prevalence of boom-induced startle and annoyance. Such a questionnaire would have to inquire about potentially sensitive and intrusive matters, including respondents’ age, gender, education, employment, home ownership, income, ethnicity, family size, and other demographic factors; and 3) unreasonable numbers of attempts would be required to re-contact households with unsuccessful initial contact attempts, given the limited time available for doing so. For example, if about 500 completed interviews were desired in a supersonically overflown community, approximately 50,000 automated interview attempts would have to be made within ten to fifteen minutes of each LBFD overflight. Such large numbers of contact attempts could well exceed the numbers of households available for interview in areas of similar boom exposure levels in some communities near LBFD flight tracks. Such large numbers of interviews could be cost-effectively undertaken only by means of automated (i.e., outgoing interactive voice response) interviewing, a data collection method ill-suited for complex and sensitive questionnaire items. The infeasibility of independent sampling for evaluating prompt responses to LBFD overflights in a cross-sectional study is due in large part to simple non-response: that is, potential respondents – particularly those contacted on wireless telephones – refusing to answer calls with unfamiliar caller IDs. It is also due in part, however, to 1) the lack of time to attempt to contact the same respondent more than once within a few minutes after the arrival of a shock wave at the respondent’s location; and 2) the need to place calls during weekday/daytime hours, when response rates are notably lower than during evenings and weekends. Despite the poor interview completion rates achieved under the above constraints, cross sectional assessments of delayed reactions to LBFD overflights could still be feasible, if multiple attempts could be made to contact respondents during evening and weekend time periods, over extended time periods. Detailed plans for a longitudinal (panel) sample were developed as an alternative to a cross sectional sample design.

Fidell, Sanford↗

A Goddard Multi-Scale Modeling System with Unified Physics

Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.

Tao, W.K.↗