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At least 55 records · Page 3

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES, AVHRR, and SSM/I sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗

Advanced data visualization and sensor fusion: Conversion of techniques from medical imaging to Earth science

Hughes Aircraft Company and the University of Chicago propose to transfer existing medical imaging registration algorithms to the area of multi-sensor data fusion. The University of Chicago's algorithms have been successfully demonstrated to provide pixel by pixel comparison capability for medical sensors with different characteristics. The research will attempt to fuse GOES (Geostationary Operational Environmental Satellite), AVHRR (Advanced Very High Resolution Radiometer), and SSM/I (Special Sensor Microwave Imager) sensor data which will benefit a wide range of researchers. The algorithms will utilize data visualization and algorithm development tools created by Hughes in its EOSDIS (Earth Observation SystemData/Information System) prototyping. This will maximize the work on the fusion algorithms since support software (e.g. input/output routines) will already exist. The research will produce a portable software library with documentation for use by other researchers.

Savage, Richard C.↗

NASA GIBS and Worldview: Leveraging FOSS for NASA Earth Science Data Visualizations

The NASA Global Imagery Browse Services (GIBS) and Worldview interactive mapping site leverage scientific and community best practices, open source software, and public standards to provide a scalable, compliant, and authoritative source for NASA Earth Observing System (EOS) Earth science data visualizations. GIBS and Worldview allow end users to easily and quickly interact with more than 800 full resolution pre-generated raster- and vector-based visualizations. This interactive discovery approach relies on visual observation and identification of phenomena that are not as simply identified otherwise. This eLightning presentation will exhibit the broad set of capabilities and visualization layers made possible through the GIBS and Worldview open source software. Specific dependencies on, and contributions to, open source software will be highlighted. Additionally, opportunities for future improvements for better interoperability and reuse through open source software will be discussed.

NASA Global Imagery Browse Services (GIBS)↗

Data Visualization and Animation Lab (DVAL): Applications

A wide variety of software tools has been successfully used to visualize, analyze and present computational and experimental data at Langley Research Center. These tools can be categorized according to five primary uses: (1) 2-D image analysis, (2) conventional 3-D visualization, (3) volume visualization, (4) photo-realistic rendering, or (5) special purpose applications. Software is accessible in each of these categories for Langley personnel, and training or consultation can be arranged with the Data Visualization and Animation laboratory staff.

Severance, Kurt↗

Creating a Prototype Web Application for Spacecraft Real-Time Data Visualization on Mobile Devices

Mobile devices (smart phones, tablets) have become commonplace among almost all sectors of the workforce, especially in the technical and scientific communities. These devices provide individuals the ability to be constantly connected to any area of interest they may have, whenever and wherever they are located. The Huntsville Operations Support Center (HOSC) is attempting to take advantage of this constant connectivity to extend the data visualization component of the Payload Operations and Integration Center (POIC) to a person's mobile device. POIC users currently have a rather unique capability to create custom user interfaces in order to view International Space Station (ISS) payload health and status telemetry. These displays are used at various console positions within the POIC. The Software Engineering team has created a Mobile Display capability that will allow authenticated users to view the same displays created for the console positions on the mobile device of their choice. Utilizing modern technologies including ASP.net, JavaScript, and HTML5, we have created a web application that renders the user's displays in any modern desktop or mobile web browser, regardless of the operating system on the device. Additionally, the application is device aware which enables it to render its configuration and selection menus with themes that correspond to the particular device. The Mobile Display application uses a communication mechanism known as signalR to push updates to the web client. This communication mechanism automatically detects the best communication protocol between the client and server and also manages disconnections and reconnections of the client to the server. One benefit of this application is that the user can monitor important telemetry even while away from their console position. If expanded to the scientific community, this application would allow a scientist to view a snapshot of the state of their particular experiment at any time or place. Because the web application renders the displays that can currently be created with the POIC ground system, the user can tailor their displays for a particular device using tools that they are already trained to use.

Lang, Jeremy S.↗

Human and Technology Integration Evaluation of Advanced Automation and Data Visualization

While the existing United States (U.S.) light water reactors are highly reliable, safe, and provide a significant proportion of carbon-free electricity, the cost of operating and maintaining them has become less competitive compared to other electricity generating sources. The reason for the gap in operating and maintenance (O&M) costs can be at least in part attributed to the advent of new digital technologies that other electricity generating industries are currently using. Advanced capabilities including digital instrumentation and control (I&C) systems, advanced automation and analytics, and greater span of data integration (i.e., connectedness) across these non-nuclear plants has transformed the way work is performed and ultimately given them a competitive advantage in terms of the cost required for operating, maintaining, and supporting them. To reduce O&M cost and address obsolescence of the aging I&C infrastructure of the existing U.S. light water reactors, the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program Plant Modernization Pathway is conducting targeting multidisciplinary research that 1) delivers a sustainable business model to enable a cost-competitive U.S. nuclear industry and 2) is developing technology modernization solutions that address aging and obsolescence challenges. The work described in this report supports these two objectives and describes the demonstration of human and technology integration across recent industry collaborations to support their large-scale digital I&C modifications. This technical report describes the demonstration of the human and technology integration methodology in performing full-scale performance-based human-in-the-loop tests to evaluate plant-specific advanced automation and data visualization applications within these collaborators’ digital modifications. This technical report also documents future applications of human and technology integration that expand beyond main control room modernization and digital I&C upgrades, which have been a central focus to date. Thus, this technical report discusses how to implement human and technology integration across new business opportunities and how to develop an evaluation plan that defines measures and criteria, and documents key assumptions to support full plant modernization.

99 GENERAL AND MISCELLANEOUS↗

Exploratory Climate Data Visualization and Analysis Using DV3D and UVCDAT

Earth system scientists are being inundated by an explosion of data generated by ever-increasing resolution in both global models and remote sensors. Advanced tools for accessing, analyzing, and visualizing very large and complex climate data are required to maintain rapid progress in Earth system research. To meet this need, NASA, in collaboration with the Ultra-scale Visualization Climate Data Analysis Tools (UVCOAT) consortium, is developing exploratory climate data analysis and visualization tools which provide data analysis capabilities for the Earth System Grid (ESG). This paper describes DV3D, a UV-COAT package that enables exploratory analysis of climate simulation and observation datasets. OV3D provides user-friendly interfaces for visualization and analysis of climate data at a level appropriate for scientists. It features workflow inte rfaces, interactive 40 data exploration, hyperwall and stereo visualization, automated provenance generation, and parallel task execution. DV30's integration with CDAT's climate data management system (COMS) and other climate data analysis tools provides a wide range of high performance climate data analysis operations. DV3D expands the scientists' toolbox by incorporating a suite of rich new exploratory visualization and analysis methods for addressing the complexity of climate datasets.

Maxwell, Thomas↗

Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary

Deep learning (DL) is a subdomain of artificial intelligence algorithms capable of automatically evaluating subtle graphical features to make highly accurate predictions, which was recently popularized in multiple imaging-related tasks. Because of its capabilities to analyze medical imaging such as radiology scans and digitized pathology specimens, DL has significant clinical potential as a diagnostic or prognostic tool. Coupled with rapidly increasing quantities of digital medical data, numerous novel research questions and clinical applications of DL within medicine have already been explored. Similarly, DL research and applications within hematology are rapidly emerging, although these are still largely in their infancy. Given the exponential rise of DL research for hematologic conditions, it is essential for the practising hematologist to be familiar with the broad concepts and pitfalls related to these new computational techniques. This narrative review provides a visual glossary for key deep learning principles, as well as a systematic review of published investigations within malignant and non-malignant hematologic conditions, organized by the different phases of clinical care. In order to assist the unfamiliar reader, this review highlights key portions of current literature and summarizes important considerations for the critical understanding of deep learning development and implementations in clinical practice.

60 APPLIED LIFE SCIENCES↗

Improving Spacecraft Data Visualization Using Splunk

EPOXI, like all spacecraft missions, receives large volumes of telemetry data from its spacecraft, DIF. It is extremely important for this data to be updated quickly and presented in a readable manner so that the flight team can monitor the status of the spacecraft. Existing DMD pages for monitoring spacecraft telemetry, while functional, are limited and do not take advantage of modern search technology. For instance, they only display current data points from instruments on the spacecraft and have limited graphing capabilities, making it difficult to see historical data. The DMD pages have fixed refresh rates so the team must often wait several minutes to see the most recent data, even after it is received on the ground. The pages are also rigid and require an investment of time and money to update. To more easily organize and visualize spacecraft telemetry, the EPOXI team has begun experimenting with Splunk, a commercially-available data mining system. Splunk can take data received from the spacecraft's different data channels, often in different formats, and index all the data into a common format. Splunk allows flight team members to search through the different data formats from a single interface and to filter results by time range and data field to make finding specific spacecraft events quick and easy. Furthermore, Splunk provides functions to create custom interfaces which help team members visualize the data in charts and graphs to show how the health of the spacecraft has changed over time.One of the goals of my internship with my mentor, Victor Hwang, was to develop new Splunk interfaces to replace the DMD pages and give the spacecraft team access to historical data and visualizations that were previously unavailable. The specific requirements of these pages are discussed in the next section.

spacecraft missions↗

Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

AIRS↗

Multimission image processing and science data visualization

The Operational Science Analysis (OSA) Functional area supports science instrument data display, analysis, visualization and photo processing in support of flight operations of planetary spacecraft managed by the Jet Propulsion Laboratory (JPL). This paper describes the data products generated by the OSA functional area, and the current computer system used to generate these data products. The objectives on a system upgrade now in process are described. The design approach to development of the new system are reviewed, including use of the Unix operating system and X-Window display standards to provide platform independence, portability, and modularity within the new system, is reviewed. The new system should provide a modular and scaleable capability supporting a variety of future missions at JPL.

Green, William B.↗

Got Graphs? An Assessment of Data Visualization Tools

Graphs are powerful tools for simplifying complex data. They are useful for quickly assessing patterns and relationships among one or more variables from a dataset. As the amount of data increases, it becomes more difficult to visualize potential associations. Lifetime Surveillance of Astronaut Health (LSAH) was charged with assessing its current visualization tools along with others on the market to determine whether new tools would be useful for supporting NASA's occupational surveillance effort. It was concluded by members of LSAH that the current tools hindered their ability to provide quick results to researchers working with the department. Due to the high volume of data requests and the many iterations of visualizations requested by researchers, software with a better ability to replicate graphs and edit quickly could improve LSAH's efficiency and lead to faster research results.

Schaefer, C. M.↗

Visual data of minor meteor showers limits of the method

Visual meteor observations are carried out on a regular basis by many experienced observers worldwide, thus supplying information about activity of meteor showers. The limits of the method are determined by the accuracy of the detection of the meteor trail. This study shows that visual meteor observations provide reliable data for an observable hourly rate of greater than or equal to 3.

Rendtel, Jurgen↗

Flow visualization and interpretation of visualization data for deflected thrust V/STOL nozzles

Flow visualization studies were made for four deflected thrust nozzle models at subsonic speeds. Based on topological rules and the assumption that observed streaks constitute continuous vector fields, available visualization pictures are interpreted and flow patterns on interior surfaces of the nozzles are synthesized. In particular, three dimensional flow structure and separations are discussed. From the synthesized patterns, the overall features of the flow field in a given nozzle can be approximately perceived.

Kao, H. C.↗

Flow visualization and interpretation of visualization data for deflected thrust V/STOL nozzles

Flow visualization studies were made for four deflected thrust nozzle models at subsonic speeds. Based on topological rules and the assumption that observed streaks constitute continuous vector fields, available visualization pictures are interpreted and flow patterns on interior surfaces of the nozzles are synthesized. In particular, three dimensional flow structure and separations are discussed. From the synthesized patterns, the overall features of the flow field in a given nozzle can be approximately perceived. Previously announced in STAR as N84-14147

Kao, H. C.↗

Mars Data Visualization and E/PO with Marsoweb

Marsoweb is a collaborative web environment that has been developed for the Mars research community to better visualize and analyze Mars orbiter data. Its goal is to enable online data discovery by providing an intuitive, interactive interface to data from the Mars Global Surveyor and other orbiters. Recently Marsoweb has served a prominent role as a resource center for the site selection process for the Mars Explorer Rover 2003 missions. In addition to hosting a repository of landing site memoranda and workshop talks, it includes a Java-based interface to a variety of datamaps and images. This interface enables the display and numerical querying of data, and allows data profiles to be rendered from user-drawn cross-sections. High-resolution Mars Orbiter Camera (MOC) images (currently, over 100,000) can be graphically perused; browser-based image processing tools can be used on MOC images of potential landing sites. An automated VRML atlas allows users to construct 'flyovers' of their own regions-of-interest in 3D. These capabilities enable Marsoweb to be used for general global data studies, in addition to those specific to landing site selection. As of September 2002, over 70,000 distinct users from NASA, USGS, academia, and the general public have accessed Marsoweb.

Gulick, V. C.↗

Technical Track on Biomass Carbon Removal and Storage (BiCRS): Mapping bioresources, phase 1 - Consistency check comparing Mission Innovation’s Data Visualization Tool for Bioresources and the Clean Energy Ministerial Biofuture Initiative Global Biomass data accessible via the US Department of Energy’s Bioenergy Knowledge Discovery Framework (KDF)

The Mission Innovation (MI) Carbon Dioxide Removal (CDR) Mission, Technical Track on Biomass Carbon Dioxide Removal and Storage (BiCRS), has produced a biomass resource database for its members. In parallel, Oak Ridge National Laboratory (ORNL) developed the International Feedstock Reporting data portal—herein referred to as the CEM Biofuture-KDF data—on behalf of the Clean Energy Ministerial Biofuture Initiative (CEM Biofuture), as a specific task under Biofuture’s 2024–25 Action Plan. This work was conducted at the request of CEM Biofuture and funded by the U.S. Department of Energy in support of that initiative, and it is hosted within DOE’s Knowledge Discovery Framework (KDF).

09 BIOMASS FUELS↗

Visual data mining for quantized spatial data

In previous papers we've shown how a well known data compression algorithm called Entropy-constrained Vector Quantization ( can be modified to reduce the size and complexity of very large, satellite data sets. In this paper, we descuss how to visualize and understand the content of such reduced data sets.

cluster analysis↗