Ease of use and deployment for a fast, scalable data movement infrastructure
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42 ENGINEERING↗
SEARCH · Engineering Papers
Results for “analysis and visualization”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Tracktable
Tracktable is a toolkit for analysis and visualization of the trajectories of moving objects. Its main focus is on air and sea traffic. It can also work with more abstract trajectories such as eye tracking data. We supply a set of core data structures, input/output routines, math and machine learning algorithms that operate on those data structures, and visualization algorithms to produce movies and still images of the results.
Wilson, Andrew↗
Finite Element Modeling Techniques for Analysis of VIIP
Visual Impairment and Intracranial Pressure (VIIP) syndrome is a major health concern for long-duration space missions. Currently, it is thought that a cephalad fluid shift in microgravity causes elevated intracranial pressure (ICP) that is transmitted along the optic nerve sheath (ONS). We hypothesize that this in turn leads to alteration and remodeling of connective tissue in the posterior eye which impacts vision. Finite element (FE) analysis is a powerful tool for examining the effects of mechanical loads in complex geometries. Our goal is to build a FE analysis framework to understand the response of the lamina cribrosa and optic nerve head to elevations in ICP in VIIP.
eye (anatomy)↗
Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions
In this work, we seek new insights into the underlying challenges of the scene graph generation (SGG) task. Quantitative and qualitative analysis of the visual genome (VG) dataset implies: 1) ambiguity: even if interobject relationship contains the same object (or predicate), they may not be visually or semantically similar; 2) asymmetry: despite the nature of the relationship that embodied the direction, it was not well addressed in previous studies; and 3) higher-order contexts: leveraging the identities of certain graph elements can help generate accurate scene graphs. Motivated by the analysis, we design a novel SGG framework, Local-to-global interaction networks (LOGINs). Locally, interactions extract the essence between three instances of subject, object, and background, while baking direction awareness into the network by explicitly constraining the input order of subject and object. Globally, interactions encode the contexts between every graph component (i.e., nodes and edges). Finally, Attract and Repel loss is utilized to fine-tune the distribution of predicate embeddings. By design, our framework enables predicting the scene graph in a bottom-up manner, leveraging the possible complementariness. To quantify how much LOGIN is aware of relational direction, a new diagnostic task called Bidirectional Relationship Classification (BRC) is also proposed. Overall, experimental results demonstrate that LOGIN can successfully distinguish relational direction than existing methods (in BRC task), while showing state-of-the-art results on the VG benchmark (in SGG task).
97 MATHEMATICS AND COMPUTING↗
Visual Understanding of COVID-19 Knowledge Graph for Predictive Analysis
This study aims to effectively analyze and visualize the concept to concept network derived from the COVID-19 Open Research Dataset (CORD-19) dataset, where we have more than 48,000 concepts with more than 300,000 relationships between concepts. In analyzing networks, we focus on finding relationship patterns between the coronavirus disease 2019 (COVID-19) concepts and other concepts. Given the node and edge datasets, we construct directional graphs and calculate all pair shortest paths based on multiple edge weight schemes. However, statistical metrics are not sufficient to identify specific relationships represented in the network. Therefore, we also propose a visual analytics approach to effectively understand the knowledge graph. Our highly interactive visual analytics allows users to effectively analyze the evolving graphs and (COVID-19) concept nodes and other nodes related to the COVID-19 nodes. We envision that this study will pave the path to develop strategies to provide more accurate and scalable predictive analysis on knowledge graphs related to CORD19 and other biomedical knowledge graphs.
Lim, Seung-Hwan↗
NGEE Arctic Rainfall Simulator Validation Data from Los Alamos National Laboratory, New Mexico, Summer 2022
Experiments evaluating the uniformity and intensity of rainfall produced by the NGEE Arctic Rainfall Simulator (NARS) were conducted at Los Alamos National Laboratory, New Mexico, over summer 2022. Petri dishes were placed in a grid within the NARS plot. Simulated rainfall was collected in each petri dish and the intensity and uniformity of the simulator was subsequently calculated. This data package contains two .csv files, one that summarizes the rainfall intensity and uniformity for each experiment, the other that contains individual petri dish water volume and intensity for each plot location and experiment. The Python scripts to control NARS are also included. The NGEE Arctic Rainfall Simulator (NARS) is a variable intensity rainfall simulator (RFS) with a frame design based on the Humphry et al. (2002) RFS and a water delivery system based on the Walnut Gulch (Paige et al., 2004) RFS. The NARS uses an aluminum frame that is fully deconstructable for transportation to field locations and a water system that enables variable rain intensity. Rain intensity control and data collection are automated using a Raspberry Pi microcomputer. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
epicsuite(EAS)
Software, Documentation, Tutorials, Testing data, Example data for processing, analysis, filtering, querying, visualization and otherwise transforming genomic data for scientific analysis and discovery.
Rogers, David H.↗
Visualization techniques to aid in the analysis of multi-spectral astrophysical data sets
This report describes our project activities for the period Sep. 1991 - Oct. 1992. Our activities included stabilizing the software system STAR, porting STAR to IDL/widgets (improved user interface), targeting new visualization techniques for multi-dimensional data visualization (emphasizing 3D visualization), and exploring leading-edge 3D interface devices. During the past project year we emphasized high-end visualization techniques, by exploring new tools offered by state-of-the-art visualization software (such as AVS3 and IDL4/widgets), by experimenting with tools still under research at the Department of Computer Science (e.g., use of glyphs for multidimensional data visualization), and by researching current 3D input/output devices as they could be used to explore 3D astrophysical data. As always, any project activity is driven by the need to interpret astrophysical data more effectively.
Domik, Gitta↗
Data Understanding Applied to Optimization
The goal of this research is to explore and develop software for supporting visualization and data analysis of search and optimization. Optimization is an ever-present problem in science. The theory of NP-completeness implies that the problems can only be resolved by increasingly smarter problem specific knowledge, possibly for use in some general purpose algorithms. Visualization and data analysis offers an opportunity to accelerate our understanding of key computational bottlenecks in optimization and to automatically tune aspects of the computation for specific problems. We will prototype systems to demonstrate how data understanding can be successfully applied to problems characteristic of NASA's key science optimization tasks, such as central tasks for parallel processing, spacecraft scheduling, and data transmission from a remote satellite.
Buntine, Wray↗
SPICE Module for the Satellite Orbit Analysis Program (SOAP)
A SPICE module for the Satellite Orbit Analysis Program (SOAP) precisely represents complex motion and maneuvers in an interactive, 3D animated environment with support for user-defined quantitative outputs. (SPICE stands for Spacecraft, Planet, Instrument, Camera-matrix, and Events). This module enables the SOAP software to exploit NASA mission ephemeris represented in the JPL Ancillary Information Facility (NAIF) SPICE formats. Ephemeris types supported include position, velocity, and orientation for spacecraft and planetary bodies including the Sun, planets, natural satellites, comets, and asteroids. Entire missions can now be imported into SOAP for 3D visualization, playback, and analysis. The SOAP analysis and display features can now leverage detailed mission files to offer the analyst both a numerically correct and aesthetically pleasing combination of results that can be varied to study many hypothetical scenarios. The software provides a modeling and simulation environment that can encompass a broad variety of problems using orbital prediction. For example, ground coverage analysis, communications analysis, power and thermal analysis, and 3D visualization that provide the user with insight into complex geometric relations are included. The SOAP SPICE module allows distributed science and engineering teams to share common mission models of known pedigree, which greatly reduces duplication of effort and the potential for error. The use of the software spans all phases of the space system lifecycle, from the study of future concepts to operations and anomaly analysis. It allows SOAP software to correctly position and orient all of the principal bodies of the Solar System within a single simulation session along with multiple spacecraft trajectories and the orientation of mission payloads. In addition to the 3D visualization, the user can define numeric variables and x-y plots to quantitatively assess metrics of interest.
Coggi, John↗
Visualization Within the Department of Energy: NREL IEEE VIS Application Spotlight
This presentation highlights the role of advanced visualization techniques at the National Renewable Energy Laboratory (NREL) in supporting cutting-edge research across diverse energy domains. From immersive analytics and uncertainty visualization to high-resolution and real-time data analysis, NREL's visualization capabilities enable scientists to explore complex datasets more effectively. These tools are critical for advancing research in materials science, renewable energy technologies, biofuels, electric vehicle infrastructure, energy efficiency - from industrial processes to entire communities - and then bringing these innovations to practice through energy systems integration. NREL's visualization tools drive innovation across renewable energy and grid modernization efforts by providing deeper insights and improving decision-making.
grid modernization↗
Spectroscopic studies of very old hot stars. III - Atmospheric properties of seven planetary nuclei
The atmospheric properties of seven planetary nuclei which have O or Of-type spectra were determined by use of the Zanstra method and by analysis of the visual line spectra. One finding is that the O-type spectral sequence may extend to effective temperatures of 90,000 kelvins or more, if the results of the Zanstra method are to be believed. However, there are some indications of internal inconsistency in the Zanstra method and some outstanding discrepancies between the effective temperatures indicated by the Zanstra method and those indicated from analysis of the visual line spectra. Two ways to resolve these discrepancies are to postulate an excess of extreme-UV stellar flux or to postulate a hot binary companion for some central stars. In either case the validity of the Harmon-Seaton evolutionary sequence for central stars becomes questionable.
Heap, S. R.↗
On Development of Three-Dimensional Visualization Capabilities in Glenn Research Center Communication Analysis Suite
With NASA’s upcoming mission to return to the Moon sustainably by 2024 and using that success as a means to step onto the barren world of Mars, it remains more important than ever to conduct research and planning as thoroughly and efficiently as possible. In a mission as complex as landing humans onto another celestial body, a network of orbiting satellites and ground stations must accurately and reliably communicate with each other, enabling crucial data communications throughout the mission. Visualizing this important data communication increases the understanding of the data and can accelerate analyses efforts. The purpose of this software development is to create an interactive visualization with data taken MATLAB® scripts in the GRC Communication Analysis Suite that is easy to understand, can show all necessary data, and display the data accurately. The main types of data to visualize are from the State Propagation, Line of Sight and Dynamic Link Margin scripts. These all show positions and orbits of satellites and ground stations, while the Line of Sight data shows when they have the ability to communicate with each other based on their respective antenna positions and fields of view. Additionally, the Dynamic Link Margin mode color-codes the communication link performance onto the Line of Sight access lines. Visualization requires a graphics language that is easily accessible, has the needed features, and able to easily read data produced by the GRC Communication Analysis Suite MATLAB® scripts. ThreeJS, a graphics library for Web Graphics Library, coded in JavaScript was selected for the visualization. The next part of the software development was to move the data from MATLAB® to the JavaScript. The best way to accomplish this was to implement a MATLAB® function converting the output data of the scripts to a JavaScript Object Notation file. A key part of the development was creating the visualization within JavaScript and ThreeJS to visualize any combination of planets, moons, orbits, satellites, ground stations, line of sight links, and handle future features without changing major parts of the code. The current visualization capability runs directly from MATLAB®, and can dynamically create any scene. This software development currently supports the lunar communications analysis underway by NASA, and can be easily expanded upon in the future to aid any analysis requirements to help plan current and future space missions.
Visualization↗
Reliable automatic plan selection for visual robotic positioning
Reliability analysis techniques developed for robotics are applied to a six-DOF (degree-of-freedom) visual positioning system. The task is to measure an object's pose and then grip the object reliably subject to time and accuracy constraints. Errors due to pixel truncation in the stadimetric vision system, forward kinematic and inverse kinematic uncertainties, and joint position and velocity noise are stochastically modeled. Simulation results for PUMA 500 kinematic and dynamic characteristics are presented.
Mcinroy, John E.↗
NASA GeneLab Multi-study Visualization Portal
NASA GeneLab has helped advance the field of Space Biology by providing a public repository where researchers can store, share, analyze and visualize the results of space flight related omics experiments. The GeneLab data visualization portal allows any user, regardless of bioinformatics knowledge or access to computational resources, to interact with the experimental data, draw their own conclusions, and gain insights about the effects of space on living systems. These tools help democratize scientific research and foster the NASA Open Science initiative. The new multi-study feature of the GeneLab visualization platform allows users to mine study metadata from RNA sequencing (RNA-seq) experiments to identify samples of interest by filtering datasets based on organism, tissue, assay technology type, and/or factor. Once samples are selected from multiple datasets, users can combine and normalize the sample data, then utilize the visualization displays, including Principal Component Analysis (PCA) plots, to assess sample distributions. Finally, users can perform differential gene expression analysis on the combined data and visualize the results through PCA plots, Volcano plots, Pair plots, Heatmap, Ideogram and Gene Set Enrichment Analysis. All user-generated results and visualizations will be available for download. Here, we present a biological study using samples from multiple GeneLab RNA-seq datasets and analyzed using the multi-study visualization platform to demonstrate inter- and intra-study variability, as well as commonly differentially expressed genes between spaceflight and ground control conditions across datasets. This new feature opens a wide range of possibilities and opportunities for further development including combining other assay technology types and integration with batch effect correction techniques and machine learning applications. Overall, this tool allows users to increase the statistical power of individual experiments, validate hypothesis, identify patterns, and opens the door to new and exciting research.
space biology↗
A multivariate approach to the analysis of average evoked potentials.
Statistical analysis of average evoked visual potential induced by light stimulus of varying intensity and duration
VISUAL SYSTEM↗
Analysis of Apollo 8 Photography and Visual Observations
Apollo 8 was launched from Cape Kennedy, Fla., at 7 :50 a.m., e.s.t., on December 21, 1968. Two hours 50 minutes later, translunar injection was performed; and astronauts Col. Frank Borman, the commander; Capt. James A. Lovell, Jr., the command module pilot; and Maj. (now Lt. Col.) William A. Anders, the lunar module pilot, were on their way to the Moon. The spacecraft was placed in an elliptical lunar orbit at 69 hours 8 minutes after liftoff. After flying two elliptical orbits of 168.5 by 60 nautical miles with an inclination of 12° to the Equator, the spacecraft was placed in a nearly circular orbit of 59.7 by 60.7 nautical miles, in which it remained for eight orbits. At 89 hours 19 minutes, trans earth injection was performed from behind the Moon. A nearly flawless mission was completed on the morning of December 27 when splashdown occurred in the Pacific Ocean after a total elapsed time of 147 hours. Lt. Gen. Sam C. Phillips, the Director of the Apollo Program, announced that such a mission was being considered at a press conference on August 19, 1968. Formal announcement that NASA was preparing Apollo 8 for an orbital flight around the Moon was released to the press on November 12, 1968. The primary purpose of this mission was to further progress toward the goal of landing men on the Moon by gaining operational experience and testing the Apolio systems. However, a great effort was also made to accomplish worthwhile scientific tasks with photography and visual observations by the astronauts. In planning the scientific tasks to be attempted on this mission, it was obvious that one of the prime tasks should be photography of the lunar surface. Such photography would furnish valuable information on the following : 1. Approach topography and landmarks for the early Apollo landings 2. The scientific merit and the roughness of areas for possible follow-on Apollo landings 3. The broad structure and characteristics of the lunar surface During the orbital part of the mission, a major portion of the lunar far side would be in sunlight. Although almost all of the far side of the Moon has been photographed by the automated Lunar Orbiter spacecraft, the photography generally was made with the spacecraft relatively far from the Moon, limiting the Lunar Orbiter photographs to an average resolution of approximately 100 meters. Thus, Apollo photographs of the far side would have much better resolution than existing pictures. Finally, it was recognized that contamination, both as it relates to window fogging (which did occur) and to contamination clouds around t he spacecraft, should be studied for both scientific and operational interests.
Richard J. Allenby↗
Wetlands ecology
The author has identified the following significant results. The ERTS imagery analyzed provides approximately 2/3 coverage of the test site. Analysis was made using visual methods, density slicing, and multispectral analysis. Preliminary conclusions reached are that most, if not all, of the investigation objectives can be met. Saline and near-saline wetlands can be delineated from ERTS-1 images as the wetland-upland boundaries and land-water interface are clearly defined. Major plant species or communities such as Spartina alterniflora (high and low vigor forms), Spartina patens/Distichlis spicata, and Juncus roemarianus can be discriminated and spoil disposal areas identified.
Anderson, R. R.↗