PNNL OMICS
The PNNL Omics Library (PNNLOmics.dll) is a collection of data analysis, file I/O, and visualization routines used by several of the omics-related software developed at PNNL.
Degan, Michael↗
SEARCH · Engineering Papers
Results for “Data visualization and analysis”
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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Develop feedback system for intelligent dynamic resource allocation to improve application performance.
This report provides documentation for the completion of the Sandia Level II milestone 'Develop feedback system for intelligent dynamic resource allocation to improve application performance'. This milestone demonstrates the use of a scalable data collection analysis and feedback system that enables insight into how an application is utilizing the hardware resources of a high performance computing (HPC) platform in a lightweight fashion. Further we demonstrate utilizing the same mechanisms used for transporting data for remote analysis and visualization to provide low latency run-time feedback to applications. The ultimate goal of this body of work is performance optimization in the face of the ever increasing size and complexity of HPC systems.
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Usage of Electric Vehicle Supply Equipment Along the Corridors between the EV Project Major Cities
The report explains how the EVSE are being used along the corridors between the EV Project cities. The EV Project consists of a nationwide collaboration between Idaho National Laboratory (INL), ECOtality North America, Nissan, General Motors, and more than 40 other city, regional and state governments, and electric utilities. The purpose of the EV Project is to demonstrate the deployment and use of approximately 14,000 Level II (208-240V) electric vehicle supply equipment (EVSE) and 300 fast chargers in 16 major cities. This research investigates the usage of all currently installed EV Project commercial EVSE along major interstate corridors. ESRI ArcMap software products are utilized to create geographic EVSE data layers for analysis and visualization of commercial EVSE usage. This research locates the crucial interstate corridors lacking sufficient commercial EVSE and targets locations for future commercial EVSE placement. The results and methods introduced in this research will be used by INL for the duration of the EV Project.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
An Information-Theoretic Framework for Enabling Extreme-scale Science Discovery
In this final technical report, we describe the major research goals, activities, and findings under this grant. We also report a list of publications resulted from this project.
97 MATHEMATICS AND COMPUTING↗
IDC Re-Engineering Phase 2 Iteration E1 Use Cases version 1.1.
This document contains 21 use cases generated from the model contained in Rational Software Architect.
97 MATHEMATICS AND COMPUTING↗
Recent developments at JPL in the application of digital image processing techniques to astronomical images
Several techniques of a digital image-processing nature are illustrated which have proved useful in visual analysis of astronomical pictorial data. Processed digital scans of photographic plates of Stephans Quintet and NGC 4151 are used as examples to show how faint nebulosity is enhanced by high-pass filtering, how foreground stars are suppressed by linear interpolation, and how relative color differences between two images recorded on plates with different spectral sensitivities can be revealed by generating ratio images. Analyses are outlined which are intended to compensate partially for the blurring effects of the atmosphere on images of Stephans Quintet and to obtain more detailed information about Saturn's ring structure from low- and high-resolution scans of the planet and its ring system. The employment of a correlation picture to determine the tilt angle of an average spectral line in a low-quality spectrum is demonstrated for a section of the spectrum of Uranus.
Lorre, J. J.↗
Flow visualization of mast-mounted-sight/main rotor aerodynamic interactions
Flow visualization tests were conducted on a 27 percent-scale AH-64 attack helicopter model fitted with various mast-mounted-sight configurations in an attempt to identify the cause of adverse vibration encountered during full-scale flight tests of an Apache/Longbow configuration. The tests were conducted at the NASA Langley Research Center in the 14- by 22-Foot Subsonic Tunnel. A symmetric and an asymmetric mast-mounted-sight oriented at several skew angles were tested at forward and rearward flight speeds of 30 and 45 knots. A laser light sheet seeded with vaporized propylene glycol was used to visualize the wake of the sight in planes parallel and perpendicular to the freestream flow. Analysis of the flow visualization data identified the frequency of the wake shed from the sight, the angle-of-attack at the sight, and the location where the sight wake crossed the rotor plane. Differences in wake structure were observed between the various sight configurations and slew angles. Postulations into the cause of the adverse vibration found in flight test are given along with considerations for future tests.
Ghee, Terence A.↗
Method for Visually Integrating Multiple Data Acquisition Technologies for Real Time and Retrospective Analysis
A system for display on a single video display terminal of multiple physiological measurements is provided. A subject is monitored by a plurality of instruments which feed data to a computer programmed to receive data, calculate data products such as index of engagement and heart rate, and display the data in a graphical format simultaneously on a single video display terminal. In addition live video representing the view of the subject and the experimental setup may also be integrated into the single data display. The display may be recorded on a standard video tape recorder for retrospective analysis.
Bogart, Edward H.↗
N-Dimensional Visualization and Spectral Mixture Analysis Applied to Imager for Mars Pathfinder Data: Detection and Mapping of Rocks and Soils
Sub-pixel analysis techniques applied to MPF IMP data indicate the presence of several rock and soil types. These techniques confirm the presence of a "black" rock type and indicate a new soil type. Additional information is contained in the original extended abstract.
Farrand, W. H.↗
Supporting Multidisciplinary Science wtihin NASA's Discipline Data Systems
Many current and future NASA and non-NASA missions are focusing on multidisciplinary science. The current paradigm for data identification and effective use by the NASA science community is based on the CODMAC model proposed in 1986.
paradigm visualization tools data analysis data lo↗
NASA GES DISC Level 2 Aerosol Analysis and Visualization Services
Overview of NASA GES DISC Level 2 aerosol analysis and visualization services: DQViz (Data Quality Visualization)MAPSS (Multi-sensor Aerosol Products Sampling System), and MAPSS_Explorer (Multi-sensor Aerosol Products Sampling System Explorer).
OMI↗
Giovanni-4: The Next Generation
This talk discusses the new aspects of Giovanni-4. Covered in the talk are new features in Giovanni-4, including shape fileservices, seasonal analysis services, the Omnibus Portal, navigation among variables, and comparison services.
analysis↗
Before the Battlefield: Competition Spurs Warfighter Innovations
In an effort funded by the Defense Threat Reduction Agency’s (DTRA) Joint Science and Technology Office, Pacific Northwest National Laboratory’s Dr. Lauren Charles and Mr. Michael Henry run an Intern-based Biosurveillance Ecosystem (BSVE) Web Application Development Contest. The competition topics target specific gaps in data collection, integration, analysis, and visualization of essential information needed for situational awareness of chemical and biological threats. The 10-week long summer internship program leverages the creativity and talent of graduate students as well as exposes bright, young professionals to the field of biosurveillance. For this past summer’s competition, Dr. Charles decided to try something different. She devised a new way to inspire innovation and gain higher quality results for the development of novel applications to aid in chemical and biological situational awareness. To this end, Dr. Charles developed and instantiated an Innovation Bootcamp Program aimed at training the student interns how to work effectively in interdisciplinary teams and quickly tackle new challenging problems while still producing top quality products. This new program was founded on three main components for success: people, tools, and application.
Innovation, Innovation, Biosurveillance, Intern Co↗
An Integrated Testbed for Trojans in Printed Circuit Boards with Fuzzing Capabilities
This paper showcases an all-in-one testing environment that combines Trojan detection and fuzzing capabilities for printed circuit boards using the OpenPLC “NYU Trojan Edition” and a dedicated Trojan detection framework. The demo system is self-contained and equipped with two OpenPLC-based boards (one with a Trojan and one without), and automated tools for inserting the Trojan and collecting side-channel data. We developed a graphical user interface for interactive Trojan selection, data visualization, and anomaly detection analysis.
Trojan detection, anomaly detection, PCB, timing l↗
gcxgclab: Two Dimensional Gas Chromatography Preprocessing and Analysis
The goal of gcxgclab is to provide a comprehensive program for preprocessing and analysis of two dimensional gas chromatography data. It is equipped with functions for baseline correction, smoothing, peak identification, peak alignment, identification of EICs, Mass Spectra, targeted analysis, compound identification with NIST and non-targeted analysis, plus plotting and data visualization.
GAMBLE, STEPHANIE↗
A Visual Analytics Approach for Correlation, Classification, and Regression Analysis
New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today s increasing complex, multivariate data sets. In this paper, a visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today s data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. This chapter provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.
Steed, Chad A↗
Wavelet-Based Interpolation and Representation of Non-Uniformly Sampled Spacecraft Mission Data
A well-documented problem in the analysis of data collected by spacecraft instruments is the need for an accurate, efficient representation of the data set. The data may suffer from several problems, including additive noise, data dropouts, an irregularly-spaced sampling grid, and time-delayed sampling. These data irregularities render most traditional signal processing techniques unusable, and thus the data must be interpolated onto an even grid before scientific analysis techniques can be applied. In addition, the extremely large volume of data collected by scientific instrumentation presents many challenging problems in the area of compression, visualization, and analysis. Therefore, a representation of the data is needed which provides a structure which is conducive to these applications. Wavelet representations of data have already been shown to possess excellent characteristics for compression, data analysis, and imaging. The main goal of this project is to develop a new adaptive filtering algorithm for image restoration and compression. The algorithm should have low computational complexity and a fast convergence rate. This will make the algorithm suitable for real-time applications. The algorithm should be able to remove additive noise and reconstruct lost data samples from images.
Bose, Tamal↗
Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)
In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.
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