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At least 541 records · Page 30

Whole-cell biocomputing

The ability to manipulate systems on the molecular scale naturally leads to speculation about the rational design of molecular-scale machines. Cells might be the ultimate molecular-scale machines and our ability to engineer them is relatively advanced when compared with our ability to control the synthesis and direct the assembly of man-made materials. Indeed, engineered whole cells deployed in biosensors can be considered one of the practical successes of molecular-scale devices. However, these devices explore only a small portion of cellular functionality. Individual cells or self-organized groups of cells perform extremely complex functions that include sensing, communication, navigation, cooperation and even fabrication of synthetic nanoscopic materials. In natural systems, these capabilities are controlled by complex genetic regulatory circuits, which are only partially understood and not readily accessible for use in engineered systems. Here, we focus on efforts to mimic the functionality of man-made information-processing systems within whole cells.

Non-NASA Center↗

A systems approach to computer-based training

This paper describes the hardware and software systems approach used in the Automated Recertification Training System (ARTS), a Phase 2 Small Business Innovation Research (SBIR) project for NASA Kennedy Space Center (KSC). The goal of this project is to optimize recertification training of technicians who process the Space Shuttle before launch by providing computer-based training courseware. The objectives of ARTS are to implement more effective CBT applications identified through a need assessment process and to provide an ehanced courseware production system. The system's capabilities are demonstrated by using five different pilot applications to convert existing classroom courses into interactive courseware. When the system is fully implemented at NASA/KSC, trainee job performance will improve and the cost of courseware development will be lower. Commercialization of the technology developed as part of this SBIR project is planned for Phase 3. Anticipated spin-off products include custom courseware for technical skills training and courseware production software for use by corporate training organizations of aerospace and other industrial companies.

Drape, Gaylen W.↗

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗

EnDEVR: An Environment for Data Engineering in VR

Organizations within the public and private sectors are looking to improve their data science operations for research, development, and operational purposes. As this interest in data science grows, so too does interest in tools and programs that facilitating such operations. This paper presents EnDEVR, the Environment for Data Engineering in Virtual Reality, a user-extensible system that allows for the execution of custom data science functions. We describe the user-centered design process for the EnDEVR system, based on the needs of subject matter experts within the aerospace and aviation industries. Fundamental to this design is a method for users to integrate their existing analysis code (that may leverage third-party vendors) as usable objects in the virtual environment; this allows organizations to operate without the price tag and lifetime obligations associated with commercial data science toolkits, a concept known as “vendor lock-in”. We then present our system design with iterative implementations, and conclude with lessons learned. The presented work may provide insight into future user-centered design processes for VR applications, particularly for digital transformation stakeholders to circumvent vendor lock-in.

Human-centered computing↗

Computer simulation and evaluation of edge detection algorithms and their application to automatic path selection

The construction of an autonomous roving vehicle requires the development of complex data-acquisition and processing systems, which determine the path along which the vehicle travels. Thus, a vehicle must possess algorithms which can (1) reliably detect obstacles by processing sensor data, (2) maintain a constantly updated model of its surroundings, and (3) direct its immediate actions to further a long range plan. The first function consisted of obstacle recognition. Obstacles may be identified by the use of edge detection techniques. Therefore, the Kalman Filter was implemented as part of a large scale computer simulation of the Mars Rover. The second function consisted of modeling the environment. The obstacle must be reconstructed from its edges, and the vast amount of data must be organized in a readily retrievable form. Therefore, a Terrain Modeller was developed which assembled and maintained a rectangular grid map of the planet. The third function consisted of directing the vehicle's actions.

Longendorfer, B. A.↗

Organics in water contamination analyzer, phase 1

The requirements which would result in identifying the components of an automatic analytical system for the analysis of specific organic compounds in the space station potable water supply are defined. The gas chromatographic system for such an analysis is limited to commercially available off-the-shelf hardware and includes the sample inlet, an ionization detector, capillary columns as well as computerized compound identification. The sampling system will be a special variation of the purge and trap Tenax mode using six-port valves and a 500 microliter water sample. Capillary columns used for the separating of contaminants will be bonded phase fused silica with a silicone stationary phase. Two detectors can be used: photoionization and far ultraviolet, since they are sensitive and compatible with capillary columns. A computer system evaluation and program with the principle of compound identification based on the retention index is presented.

Source record↗

Vehicle Design Data Format and Process for a Complete TARIS and OLTARIS Radiation Analysis for Designers and Engineers

Protecting astronauts from space radiation is a complex task when it comes to modeling and simulation. This document shows what information is needed from a spacecraft designer using CAD (Computer-Assisted Design) at each phase of the design to enable the engineers to evaluate the design phase against space radiation limits to determine the suitability of the design for space flight. The current personal exposure limits are listed in NASA STD-3001. A proxy to determine the REID (Radiation Exposure Induced Death) in NASA STD-3001 is the whole body effective dose equivalent (E or effective dose). For short-term tissue effects, organ-averaged gray equivalent (G (sub T)) is used. The TARIS (Tool for the Assessment of Radiation In Space - for LaRC (Langley Research Center) engineers) and OLTARIS (On-Line TARIS) - for designers) systems are used to generate these response functions. The E can use ICRP60 or NASA Q-values. A possible space radiation design basis environment for short-term tissue effects is described and used in all analyses. A single space vehicle was designed with three astronaut configurations and two of those configurations were used in a storm shelter thickness perturbation analysis. Conversion of the data from the CAD model to input necessary for TARIS and OLTARIS is also discussed in detail with relevant examples.

Singleterry, Robert C.↗

Microbial Communities in Microgravity: Simulation in Lab and on the Computer

Microorganisms grow differently in spaceflight than they do on Earth. While much remains unexplained about how microgravity affects microbial growth, one dominant hypothesis is that the lack of density-driven convection in the liquid growth environment makes mixing diffusion-limited, and therefore slower. This is supported by evidence that individual microbial strains experience starvation and acid stress in microgravity. However, if it is true, then microgravity would also have measurable effects on microbes in mixed communities, because many interspecies interactions involve the exchange of soluble metabolites through the medium (cross-feeding). Specifically, cooperative cross-feeding communities would grow more slowly in microgravity, and cooperation would be less stable on evolutionary timescales. Here we describe our efforts to test this hypothesis by simulating microgravity in silico and in the lab, using a model system of Eschericia coli and Salmonella enterica that grow only when they can exchange methionine and acetate. We created CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) as an extension of CFDEM®coupling software, to carry out computational modeling of biological flows, growth, and mass transfer in microgravity and also in laboratory artificial microgravity devices (rotating wall vessels, RWV). Using CAMDLES, we found distinct differences in growth rates between RWV and true microgravity, and we were able to identify several features, such as spatial distribution, biofilm formation, and product yield parameters, that influence the degree to which RWV growth recapitulates microgravity growth. In addition, we report on the development of a laboratory system for monitoring growth rates and species ratios of the community in RWVs, using fluorescent strains. Pairing CAMDLES with the laboratory model system allows us to generate quantitative predictions about the effects of spaceflight on organisms that will be essential to sustaining human space exploration in the long term.

microbiology↗

Subgrid Scale Modeling in Solar Convection Simulations using the ASH Code

The turbulent solar convection zone has remained one of the most challenging and important subjects in physics. Understanding the complex dynamics in the solar con- vection zone is crucial for gaining insight into the solar dynamo problem. Many solar observatories have generated revealing data with great details of large scale motions in the solar convection zone. For example, a strong di erential rotation is observed: the angular rotation is observed to be faster at the equator than near the poles not only near the solar surface, but also deep in the convection zone. On the other hand, due to the wide range of dynamical scales of turbulence in the solar convection zone, both theory and simulation have limited success. Thus, cutting edge solar models and numerical simulations of the solar convection zone have focused more narrowly on a few key features of the solar convection zone, such as the time-averaged di erential rotation. For example, Brun & Toomre (2002) report computational finding of differential rotation in an anelastic model for solar convection. A critical shortcoming in this model is that the viscous dissipation is based on application of mixing length theory to stellar dynamics with some ad hoc parameter tuning. The goal of our work is to implement the subgrid scale model developed at CTR into the solar simulation code and examine how the differential rotation will be a affected as a result. Specifically, we implement a Smagorinsky-Lilly subgrid scale model into the ASH (anelastic spherical harmonic) code developed over the years by various authors. This paper is organized as follows. In x2 we briefly formulate the anelastic system that describes the solar convection. In x3 we formulate the Smagorinsky-Lilly subgrid scale model for unstably stratifed convection. We then present some preliminary results in x4, where we also provide some conclusions and future directions.

Young, Y.-N.↗

Thermal radiation analysis system (TRASYS)

The Thermal Radiation Analysis System, TRASYS, is a digital computer software system with generalized capability to solve the radiation-related aspects of thermal analysis problems. When used in conjunction with a generalized thermal analyzer program any thermal problem that can be expressed in terms of a lumped parameter R-C thermal network can be solved. The function of TRASYS is twofold. It provides: (1) internode radiation interchange data; and (2) incident and absorbed heat rate data from environmental radiant heat sources. Data of both types is provided in a format directly usable by the thermal analyzer programs. One of the primary features of TRASYS is that it allows the user to write his own executive or driver program which organizes and directs the program library routines toward solution of each specific problem in the most expeditious manner. The user also may write his own output routines, thus the system data output can directly interface with any thermal analyzer using the R-C network concept.

Jensen, C. L.↗

User's Manual: Thermal Radiation Analysis System TRASYS 2

A digital computer software system with generalized capability to solve the radiation related aspects of thermal analysis problems is presented. When used in conjunction with a generalized thermal analysis program such as the systems improved numerical differencing analyzer program, any thermal problem that can be expressed in terms of a lumped parameter R-C thermal network can be solved. The function of TRASYS is twofold. It provides: (a) Internode radiation interchange data; and (b) Incident and absorbed heat rate data from environmental radiant heat sources. Data of both types is provided in a format directly usable by the thermal analyzer programs. The system allows the user to write his own executive or driver program which organizes and directs the program library routines toward solution of each specific problem in the most expeditious manner. The user also may write his own output routines, thus the system data output can directly interface with any thermal analyzer using the R-C network concept.

Jensen, C. L.↗

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes nearly 150 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies. Remote Sensing; Earth Science Informatics, Data Systems; Data Services; Metadata

Remote Sensing; Earth Science Informatics↗

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.

Data Systems↗

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.The talk will present an overview of current efforts in ESI, the role members of IEEE GRSS play, and discuss recent developments in data preservation and provenance.

Remote Sensing↗

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.The talk will present an overview of current efforts in ESI, the role members of IEEE GRSS play, and discuss recent developments in data preservation and provenance.

Remote Sensing↗

Performance of the engineering analysis and data system 2 common file system

The Engineering Analysis and Data System (EADS) was used from April 1986 to July 1993 to support large scale scientific and engineering computation (e.g. computational fluid dynamics) at Marshall Space Flight Center. The need for an updated system resulted in a RFP in June 1991, after which a contract was awarded to Cray Grumman. EADS II was installed in February 1993, and by July 1993 most users were migrated. EADS II is a network of heterogeneous computer systems supporting scientific and engineering applications. The Common File System (CFS) is a key component of this system. The CFS provides a seamless, integrated environment to the users of EADS II including both disk and tape storage. UniTree software is used to implement this hierarchical storage management system. The performance of the CFS suffered during the early months of the production system. Several of the performance problems were traced to software bugs which have been corrected. Other problems were associated with hardware. However, the use of NFS in UniTree UCFM software limits the performance of the system. The performance issues related to the CFS have led to a need to develop a greater understanding of the CFS organization. This paper will first describe the EADS II with emphasis on the CFS. Then, a discussion of mass storage systems will be presented, and methods of measuring the performance of the Common File System will be outlined. Finally, areas for further study will be identified and conclusions will be drawn.

Debrunner, Linda S.↗

Fundamental procedures of geographic information analysis

Analytical procedures common to most computer-oriented geographic information systems are composed of fundamental map processing operations. A conceptual framework for such procedures is developed and basic operations common to a broad range of applications are described. Among the major classes of primitive operations identified are those associated with: reclassifying map categories as a function of the initial classification, the shape, the position, or the size of the spatial configuration associated with each category; overlaying maps on a point-by-point, a category-wide, or a map-wide basis; measuring distance; establishing visual or optimal path connectivity; and characterizing cartographic neighborhoods based on the thematic or spatial attributes of the data values within each neighborhood. By organizing such operations in a coherent manner, the basis for a generalized cartographic modeling structure can be developed which accommodates a variety of needs in a common, flexible and intuitive manner. The use of each is limited only by the general thematic and spatial nature of the data to which it is applied.

Berry, J. K.↗

Ulysses mission operations

The Ulysses mission is described in terms of in-Shuttle operations, initial in-orbit operations, routine operations, operational organization, and data gathering and production. The configuration of the Ulysses payload is illustrated, and the flight to orbit is described including a three-hour on-orbit checkout. The first contact was reported at the Deep Space Network station followed by an adjustment of the spacecraft solar-aspect angle and the acquisition of ranging and Doppler data. In-orbit operations include the earth acquisition maneuver, a trajectory correction maneuver, and a payload switch. Continuous data gathering is discussed with reference to the Jupiter encounter and the first and second oppositions and conjunctions. The data-gathering components comprise ground stations, a data-processing computer, and a data-records system. Data production is performed in an off-line mode that does not interfere with the real-time operations.

Beech, P.↗