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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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At least 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

ER-2 lidar measurements of stratocumulus cloud top structure on July 14, 1987

On July 14, 1987 NASA's ER-2 high altitude aircraft flew a mission to measure the structure of stratocumulus clouds off the coast of California. A flight pattern was executed so that the two-dimensional variability of the clouds could be detected. The technique of analysis of the lidar data to measure cloud tops follows. First each signal is searched for its maximum in return strength. This maximum is caused by scattering of the laser light off cloud particles or from the ocean surface. Next the variance of the signal return above the level of maximum backscatter is determined. Cloud top is assigned to a level (above the level of maximum backscatter) where the backscatter exceeds the average variance. This two-step process is necessary because the level of maximum backscatter does not correspond to the cloud top. Ocean surface returns are easily separated from cloud returns in this process, described in detail by Boers, Spinhirne, and Hart (1988). Analysis of the data so far has shown that there were very few breaks in the clouds. Furthermore the layer top was very flat with local oscillations not exceeding 30 m. Such small cloud top variations are still well within the range of detectability, because the precision of this technique of cloud top detection has previously been established to be 13 to 15 m. Data are presently being analyzed to compute cloud top distributions and fractional cloudiness. The aim of this research is to relate the fractional cloudiness to the mean thermodynamic structure of the boundary layer. Researchers plan to compute spectral scales of the cloud top variability in two dimensions to determine the orientation of the clouds with respect to the mean wind. Furthermore the lidar derived cloud top distribution will be used in the computation of the thermodynamic and radiation budget of the boundary layer.

Boers, Reinout↗
NASA NTRS1995

Numerical Study of Boundary Layer Interaction with Shocks: Method Improvement and Test Computation

The objective is the development of a high-order and high-resolution method for the direct numerical simulation of shock turbulent-boundary-layer interaction. Details concerning the spatial discretization of the convective terms can be found in Adams and Shariff (1995). The computer code based on this method as introduced in Adams (1994) was formulated in Cartesian coordinates and thus has been limited to simple rectangular domains. For more general two-dimensional geometries, as a compression corner, an extension to generalized coordinates is necessary. To keep the requirements or limitations for grid generation low, the extended formulation should allow for non-orthogonal grids. Still, for simplicity and cost efficiency, periodicity can be assumed in one cross-flow direction. For easy vectorization, the compact-ENO coupling algorithm as used in Adams (1994) treated whole planes normal to the derivative direction with the ENO scheme whenever at least one point of this plane satisfied the detection criterion. This is apparently too restrictive for more general geometries and more complex shock patterns. Here we introduce a localized compact-ENO coupling algorithm, which is efficient as long as the overall number of grid points treated by the ENO scheme is small compared to the total number of grid points. Validation and test computations with the final code are performed to assess the efficiency and suitability of the computer code for the problems of interest. We define a set of parameters where a direct numerical simulation of a turbulent boundary layer along a compression corner with reasonably fine resolution is affordable.

Adams, N. A.↗
NASA NTRS2001

Updated Electronic Testbed System

As we continue to advance in exploring space frontiers, technology must also advance. The need for faster data recovery and data processing is crucial. In this, the less equipment used, and lighter that equipment is, the better. Because integrated circuits become more sensitive in high altitude, experimental verification and quantification is required. The Center for Applied Radiation Research (CARR) at Prairie View A&M University was awarded a grant by NASA to participate in the NASA ER-2 Flight Program, the APEX balloon flight program, and the Student Launch Program. These programs are to test anomalous errors in integrated circuits due to single event effects (SEE). CARR had already begun experiments characterizing the SEE behavior of high speed and high density SRAM's. The research center built a error testing system using a PC-104 computer unit, an Iomega Zip drive for storage, a test board with the components under test, and a latchup detection and reset unit. A test program was written to continuously monitor a stored data pattern in the SRAM chip and record errors. The devices under test were eight 4Mbit memory chips totaling 4Mbytes of memory. CARR was successful at obtaining data using the Electronic TestBed System (EBS) in various NASA ER-2 test flights. These series of high altitude flights of up to 70,000 feet, were effective at yielding the conditions which single event effects usually occur. However, the data received from the series of flights indicated one error per twenty-four hours. Because flight test time is very expensive, the initial design proved not to be cost effective. The need for orders of magnitude with more memory became essential. Therefore, a project which could test more memory within a given time was created. The goal of this project was not only to test more memory within a given time, but also to have a system with a faster processing speed, and which used less peripherals. This paper will describe procedures used to build an updated Electronic Testbed System.

Brewer, Kevin L.↗
NASA NTRS2004

Segmenting Images for a Better Diagnosis

NASA's Hierarchical Segmentation (HSEG) software has been adapted by Bartron Medical Imaging, LLC, for use in segmentation feature extraction, pattern recognition, and classification of medical images. Bartron acquired licenses from NASA Goddard Space Flight Center for application of the HSEG concept to medical imaging, from the California Institute of Technology/Jet Propulsion Laboratory to incorporate pattern-matching software, and from Kennedy Space Center for data-mining and edge-detection programs. The Med-Seg[TM] united developed by Bartron provides improved diagnoses for a wide range of medical images, including computed tomography scans, positron emission tomography scans, magnetic resonance imaging, ultrasound, digitized Z-ray, digitized mammography, dental X-ray, soft tissue analysis, and moving object analysis. It also can be used in analysis of soft-tissue slides. Bartron's future plans include the application of HSEG technology to drug development. NASA is advancing it's HSEG software to learn more about the Earth's magnetosphere.

Source record↗
NASA NTRS2004

A Holding Function for Conflict Probe Appiications

Conflict Alerts for aircraft in holding patterns are often missed or in error due to fact that holding trajectories are not modeled in Conflict Alert or Conflict Probe logic. In addition, a controller in one sector may not know when aircraft are holding in a neighboring sector. These factors can lead to an increased potential for loss of separation while aircraft are flying in holding patterns. A holding function for conflict probe applications has been developed and tested with air traffic data from Fort Worth Center. The holding function automatically determines when an aircraft enters a holding pattern, builds a holding region around the pattern and then probes the region for conflict with other traffic. The operational concept of use assumes that air traffic controllers are very busy during periods when aircraft are in holding and therefore don't have time to manually enter information which defines a holding pattern and activates conflict probing. For this reason, it is important the holding function automatically detect aircraft in holding and compute a holding region for conflict analysis. The controller is then alerted if other aircraft are predicted to fly through the holding region at the holding altitude.

McNally, Dave↗
NASA NTRS2006

Spacecraft Environment May Reduce Resistance To Infection

Living and working in a spacecraft exposes the crew to a unique environment. This environment includes microgravity, increased radiation, chemical and biological contamination, and a variety of stressors. Disturbances in this balance are often manifested by diminished immunity in astronauts/cosmonauts. Reactivation of Epstein- Barr virus (EBV), cytomegalovirus (CMV), and varicella-zoster virus (VZV) has been used as an indicator of immune status. Reactivation of EBV and VZV were detected and quantified in saliva. CMV was measured in urine. The DNA was extracted using a Qiagen Inc. kit and viral DNA was detected by real time polymerase chain reaction (PCR) based assay with Taqman 7700 (PE Biosystems). Patterns of Epstein-Barr virus (EBV) reactivation in 32 astronauts and 18 healthy age-matched control subjects were characterized by quantifying EBV shedding. Saliva samples were collected before, during, and after 10 space shuttle missions of 5 to 14 d duration. Of 1398 saliva specimens from 32 astronauts, 314 (23%) were positive for EBV DNA. Examination by flight phase showed that 29% of the saliva specimens collected from 28 astronauts before flight were positive for EBV DNA, as were 16% of those collected from 25 astronauts during flight and 16% of those collected after flight from 23 astronauts. The mean number of EBV copies/mL from samples taken during the flights was 417, ten-fold greater (p < 0.05) than the copies from the preflight (40) and post flight (44) phases. In contrast, the control subjects shed EBV DNA with a frequency of 3.7% and mean EBV copies of 40 per mL of saliva. Ten days before flight and on landing day, titers of antibody to EBV viral capsid antigen were significantly (p < 0.05) greater than baseline levels. Increases in the number of viral copies and in the amount of EBV-specific antibody were consistent with EBV reactivation before, during, and after space flight. Similarly, CMV and VZV reactivation increased in response to space flight conditions. Data indicates that space flight is a unique stress environment that may produce stress-induced changes in the host-microbe relationship resulting in increased risk of infection.

Pierson, Duane L.↗
NASA NTRS2003

cWINNOWER Algorithm for Finding Fuzzy DNA Motifs

The cWINNOWER algorithm detects fuzzy motifs in DNA sequences rich in protein-binding signals. A signal is defined as any short nucleotide pattern having up to d mutations differing from a motif of length l. The algorithm finds such motifs if multiple mutated copies of the motif (i.e., the signals) are present in the DNA sequence in sufficient abundance. The cWINNOWER algorithm substantially improves the sensitivity of the winnower method of Pevzner and Sze by imposing a consensus constraint, enabling it to detect much weaker signals. We studied the minimum number of detectable motifs qc as a function of sequence length N for random sequences. We found that qc increases linearly with N for a fast version of the algorithm based on counting three-member sub-cliques. Imposing consensus constraints reduces qc, by a factor of three in this case, which makes the algorithm dramatically more sensitive. Our most sensitive algorithm, which counts four-member sub-cliques, needs a minimum of only 13 signals to detect motifs in a sequence of length N = 12000 for (l,d) = (15,4).

Liang, Shoudan↗
NASA NTRS2009

Evaluation of an Interferometric Sensor for In-Space Detection of Gas Leaks

Space mission planning often involves long-term storage of volatile liquids or high-pressure gases. These may include cryogenic fuels and oxidizers, high-pressure gases, and life-support-critical consumables. The risk associated with the storage of fluids and gases in space systems has long been an issue and the ability to retain these fluids is often tied to mission success. A leak in the storage or distribution system can cause many different problems, including a simple, but mission endangering, loss of inventory or, in severe cases, unbalanced thrust loads on a flight vehicle. Cryogenic propellants are especially difficult to store, especially over a long duration. The propellant can boil off and be lost through the insulating walls of the tank or simple thermal cycling of the fittings, valves, and propellant feed lines may unseat seals allowing the fluid to escape. Current NASA missions call for long-duration in-space storage of propellants, oxidizers, and life support supplies. Leaks of a scale detectable through a pressure drop in the storage tank are often catastrophic and have long been the focus of ground-based mitigation efforts where redundant systems are often employed. However, there is presently no technology available for detecting and monitoring low-level, but still mission-endangering, gas leaks in space. Standard in-space gas detection methods either have a very limited pressure range over which they operate effectively or are limited to certain gases. Mass spectrometer systems are able to perform the detection tasks, but their size, mass and use of high voltage, which could potentially lead to an arc that ignites a combustible propellent, severely limit their usefulness in a space system. In this paper, we present results from testing of the light-based interferometric gas monitoring and leak detection sensor shown in Fig. 1. The output of the sensor is an interference fringe pattern that is a function of the gas density, and commensurate index of refraction, in the sample region. Changes in the density of gas cause the interference fringes to move across a photodiode detector, providing a temporal history of the leak. The sensor is fiber coupled and constructed from solid optics, allowing for placement almost anywhere on the spacecraft. It is also advantageous in that it consumes very little power and does not introduce an ignition source. Data are presented demonstrating the capability of the sensor to measure density variations in different gas species. In addition, the transient response of the sensor in vacuum is demonstrated. These data extend and improve upon the results previously presented by the authors in Ref. [1].

Polzin, Kurt A.↗
NASA NTRS2010

Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

Cook, Bruce D.↗
NASA NTRS2006

Covering a Crucible with Metal Containing Channels

In a procedure that partly resembles the lost-wax casting process, a crucible made of a brittle material (ceramic, quartz, or glass) is covered with a layer of metal containing channels. The metal cover and the channels can serve any or all of several purposes, depending upon the application: Typically, the metal would serve at least partly to reinforce the crucible. The channels could be used as passages for narrow objects that could include thermocouples and heat-transfer strips. Alternatively or in addition, channels could be used as flow paths for liquid or gaseous coolants and could be positioned and oriented for position- or direction-selective cooling. In some cases, the channels could be filled with known gases and sealed so that failure of the crucibles could be indicated by instruments that detect the gases. The process consists of three main steps. In the first step, a pattern defining the channels is formed by wrapping or depositing a material in the desired channel pattern on the outer surface of the crucible. The pattern material can be a plastic, wax, low-ash fibrous material, a soluble material, or other suitable material that can subsequently be removed easily. In a proof-of-concept demonstration (see figure), the crucible was an alumina cylinder and the mold material was plastic tie-down tape. In the second step, the patterned crucible is coated with metal. In one variation of the second step, a very thin layer containing or consisting of an electrically conductive material (e.g., gold, silver, or carbon) is painted or otherwise deposited on the mold-covered crucible, then the covering metal required for the specific application is electrodeposited on the very thin conducting layer. In another variation of the second step, the metal coat is formed by chemical vapor deposition. In the proof-of-concept demonstration, a layer of nickel 0.003 in. ( 0.08 mm) thick was electrodeposited. In the third step, the patterned material is removed. This is generally done by heating the crucible assembly until the patterned material melts and runs out, vaporizes, and/or decomposes to an ash, leaving the channels. Alternatively, if the patterned material is soluble, it can be removed by use of a suitable solvent. In the proof-of-concept demonstration, the tape was burned away by heating the assembly to a temperature of 600 C.

Grugel, Richard N.↗
NASA NTRS2012

Field and Satellite Observations of the Formation and Distribution of Arctic Atmospheric Bromine Above a Rejuvenated Sea Ice Cover

Recent drastic reduction of the older perennial sea ice in the Arctic Ocean has resulted in a vast expansion of younger and saltier seasonal sea ice. This increase in the salinity of the overall ice cover could impact tropospheric chemical processes. Springtime perennial ice extent in 2008 and 2009 broke the half-century record minimum in 2007 by about one million km2. In both years seasonal ice was dominant across the Beaufort Sea extending to the Amundsen Gulf, where significant field and satellite observations of sea ice, temperature, and atmospheric chemicals have been made. Measurements at the site of the Canadian Coast Guard Ship Amundsen ice breaker in the Amundsen Gulf showed events of increased bromine monoxide (BrO), coupled with decreases of ozone (O3) and gaseous elemental mercury (GEM), during cold periods in March 2008. The timing of the main event of BrO, O3, and GEM changes was found to be consistent with BrO observed by satellites over an extensive area around the site. Furthermore, satellite sensors detected a doubling of atmospheric BrO in a vortex associated with a spiral rising air pattern. In spring 2009, excessive and widespread bromine explosions occurred in the same region while the regional air temperature was low and the extent of perennial ice was significantly reduced compared to the case in 2008. Using satellite observations together with a Rising-Air-Parcel model, we discover a topographic control on BrO distribution such that the Alaskan North Slope and the Canadian Shield region were exposed to elevated BrO, whereas the surrounding mountains isolated the Alaskan interior from bromine intrusion.

Nghiem, Son V.↗
NASA NTRS2012

Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly

A paper describes the Thermal Infrared Sensor (TIRS), a QWIP-based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a far-infrared imager operating in the pushbroom mode with two IR channels: 10.8 and 12 microns. The focal plane will contain three 640x512 QWIP arrays mounted on a silicon substrate. The silicon substrate is a custom-fabricated carrier board with a single layer of aluminum interconnects. The general fabrication process starts with a 4-in. (approx.10-cm) diameter silicon wafer. The wafer is oxidized, a single substrate contact is etched, and aluminum is deposited, patterned, and alloyed. This technology development is aimed at incorporating three large-format infrared detecting arrays based on GaAs QWIP technology onto a common focal plane with precision alignment of all three arrays. This focal plane must survive the rigors of flight qualification and operate at a temperature of 43 K (-230 C) for five years while orbiting the Earth. The challenges presented include ensuring thermal compatibility among all the components, designing and building a compact, somewhat modular system and ensuring alignment to very tight levels. The multi-array focal plane integrated onto a single silicon substrate is a new application of both QWIP array development and silicon wafer scale integration. The Invar-based assembly has been tested to ensure thermal reliability.

Jhabvala, Murzy↗
NASA NTRS2018

NeMO-Net & Fluid Lensing: The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment Using Fluid Lensing Augmentation of NASA EOS Data

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low-resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

satellite data↗
NASA NTRS2018

NASA NeMO-Net

We present preliminary results from NASA NeMO-Net, the first neural multi-modal observation and training network for global coral reef assessment. NeMO-Net is an open-source deep convolutional neural network (CNN) and interactive active learning training software in development which will assess the present and past dynamics of coral reef ecosystems. NeMO-Net exploits active learning and data fusion of mm-scale remotely sensed 3D images of coral reefs captured using fluid lensing with the NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as hyperspectral airborne remote sensing data from the ongoing NASA CORAL mission and lower-resolution satellite data to determine coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. Aquatic ecosystems, particularly coral reefs, remain quantitatively misrepresented by low- resolution remote sensing as a result of refractive distortion from ocean waves, optical attenuation, and remoteness. Machine learning classification of coral reefs using FluidCam mm-scale 3D data show that present satellite and airborne remote sensing techniques poorly characterize coral reef percent living cover, morphology type, and species breakdown at the mm, cm, and meter scales. Indeed, current global assessments of coral reef cover and morphology classification based on km-scale satellite data alone can suffer from segmentation errors greater than 40%, capable of change detection only on yearly temporal scales and decameter spatial scales, significantly hindering our understanding of patterns and processes in marine biodiversity at a time when these ecosystems are experiencing unprecedented anthropogenic pressures, ocean acidification, and sea surface temperature rise. NeMO-Net leverages our augmented machine learning algorithm that demonstrates data fusion of regional FluidCam (mm, cm-scale) airborne remote sensing with global low-resolution (m, km-scale) airborne and spaceborne imagery to reduce classification errors up to 80% over regional scales. Such technologies can substantially enhance our ability to assess coral reef ecosystems dynamics.

NASA↗
NASA NTRS2024

Alaska Ecological Conservation: Using NASA Earth Observations to Identify Recent Changes in River Ice Phenology and Its Impacts on Caribou Migration

Each fall, caribou (Rangifer tarandus) in the Western Arctic Herd migrate hundreds of kilometers across northwestern Alaska to acquire seasonal resources and reach wintering grounds. Various rivers intersect migration paths, and caribou can only cross over open water or high-ice extents but are unable to cross rivers in stages of partial freezing. Recent temperature increases in Alaska can alter the timing and duration of ice formation periods, impeding migratory patterns. The Massachusetts NASA DEVELOP team partnered with the National Park Service in Alaska to detect river ice onset dates and formation periods using Landsat 8 Operational Land Imager and Landsat 9 Operational Land Imager-2, Sentinel-1 C-band Synthetic Aperture Radar and Sentinel-2A/B MultiSpectral Instrument imagery in Google Earth Engine. This feasibility analysis measured ice coverage using the Normalized Difference Infrared Index, Relative Difference River Ice, and Vertical-Vertical/Vertical-Horizontal backscatter values based on the spectral and surface characteristics of rivers. The team produced annual freezing timelines, time series plots, and maps at three river stretches to analyze river ice phenology changes. Radar imagery assessed ice coverage more accurately, while optical imagery better identified ice onset dates. Meanwhile indices were unable to robustly establish ice formation thresholds across the study period. These study results can help the National Park Service to better evaluate spatiotemporal migratory shifts and contextualize recent regional caribou declines.

river phenology↗
NASA NTRS1988

Optical Image Subtraction

Report reviews optical image subtraction techniques developed during years 1975 through 1985. Useful in such disciplines as studies of earth resources, meteorology, automatic surveillance, pattern recognition, studies of urban growth, and compression of bandwidth in communication systems. Describes following real-time techniques: source encoding, polarization modulation, pseudocolor image-difference detection, holographic-shear-lens technique, and nonlinear electro-optics. Reported non-real-time image-subtraction techniques are following, all of which involve intensity subtraction: speckle-diffuser encoding, speckle-pattern encoding, halftone-screen encoding,and polarization-shifted carrier encoding. Offers an attractive alternative to digital electronic image subtraction, is faster and treats all parts of images simultaneously.

Liu, Hua-Kuang↗
DOE OSTI2022

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗
DOE OSTI2016

SeekAView: An Intelligent Dimensionality Reduction Strategy for Navigating High-Dimensional Data Spaces

Dealing with the curse of dimensionality is a key challenge in high-dimensional data visualization. We present SeekAView to address three main gaps in the existing research literature. First, automated methods like dimensionality reduction or clustering suffer from a lack of transparency in letting analysts interact with their outputs in real-time to suit their exploration strategies. The results often suffer from a lack of interpretability, especially for domain experts not trained in statistics and machine learning. Second, exploratory visualization techniques like scatter plots or parallel coordinates suffer from a lack of visual scalability: it is difficult to present a coherent overview of interesting combinations of dimensions. Third, the existing techniques do not provide a flexible workflow that allows for multiple perspectives into the analysis process by automatically detecting and suggesting potentially interesting subspaces. In SeekAView we address these issues using suggestion based visual exploration of interesting patterns for building and refining multidimensional subspaces. Compared to the state-of-the-art in subspace search and visualization methods, we achieve higher transparency in showing not only the results of the algorithms, but also interesting dimensions calibrated against different metrics. We integrate a visually scalable design space with an iterative workflow guiding the analysts by choosing the starting points and letting them slice and dice through the data to find interesting subspaces and detect correlations, clusters, and outliers. We present two usage scenarios for demonstrating how SeekAView can be applied in real-world data analysis scenarios.

Krause, Josua↗