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At least 145 records · Page 8

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NASA NTRS2005

Goddard Atmospheric Composition Data Center: Aura Data and Services in One Place

The Goddard Atmospheric Composition Data and Information Services Center (AC-DISC) is a portal to the Atmospheric Composition specific, user driven, multi-sensor, on-line, easy access archive and distribution system employing data analysis and visualization, data mining, and other user requested techniques for the better science data usage. It provides convenient access to Atmospheric Composition data and information from various remote-sensing missions, from TOMS, UARS, MODIS, and AIRS, to the most recent data from Aura OMI, MLS, HIRDLS (once these datasets are released to the public), as well as Atmospheric Composition datasets residing at other remote archive site.

Leptoukh, G.↗

NASA NTRS2004

Microwave-Spectral Signatures Would Reveal Concealed Objects

A proposed technique for locating concealed objects (especially small antipersonnel land mines) involves the acquisition and processing of spectral signatures over broad microwave frequency bands. This technique was conceived to overcome the weaknesses of older narrow- band electromagnetic techniques like ground-probing radar and low-frequency electromagnetic induction. Ground-probing radar is susceptible to false detections and/or interference caused by rocks, roots, air pockets, soil inhomogeneities, ice, liquid water, and miscellaneous buried objects other than those sought. Moreover, if the radar frequency happens to be one for which the permittivity of a sought object matches the permittivity of the surrounding soil or there is an unfavorable complex-amplitude addition of the radar reflection at the receiver, then the object is not detected. Low-frequency electromagnetic induction works well for detecting metallic objects, but the amounts of metal in plastic mines are often too small to be detectable. The potential advantage of the proposed technique arises from the fact that wideband spectral signatures generally contain more relevant information than do narrow-band signals. Consequently, spectral signatures could be used to make better decisions regarding whether concealed objects are present and whether they are the ones sought. In some cases, spectral signatures could provide information on the depths, sizes, shapes, and compositions of objects. An apparatus to implement the proposed technique (see Figure 1) could be assembled from equipment already in common use. Typically, such an apparatus would include a radio-frequency (RF) transmitter/receiver, a broad-band microwave antenna, and a fast personal computer loaded with appropriate software. In operation, the counter would be turned on, the antenna would be aimed at the ground or other mass suspected to contain a mine or other sought object, and the operating frequency would be swept over the band of interest.

Arndt, G.↗

NASA NTRS2013

Forward-Looking IED Detector Ground Penetrating Radar

There have been many developments of mine or metal detectors based on ground penetrating radar techniques, usually in hand-held or rover-mounted devices. In most mine or metal detector applications, conditions are in a stationary mode and detection speed is not an important factor. A novel, forward-looking, stepped-frequency ground penetrating radar (GPR) has been developed with a capability to detect improvised explosive devices (IEDs) at vehicular speeds of 15 to 20 mph (24 to 32 km/h), 10 to 20 m ahead of the vehicle, to ensure adequate time for response. The GPR system employs two horn antennas (1.7 to 2.6 GHz, 20 dBi) as transmit and receive. The detector system features a user-friendly instantaneous display on a laptop PC and is a low-power-consumption (3 W) compact system with minimal impact on vehicle operations. In practice, the whole GPR system and a laptop PC can be powered by plugging into a cigarette lighter of a vehicle. The stepped-frequency continuous-wave (CW) radar scans frequency from 1.7 to 2.6 GHz in 1,000 steps of 0.9 MHz, with the full frequency scan in 60 ms. The GPR uses a bi-static configuration with one horn antenna used as a transmitter and the other used as a receiver so that isolation between transmitter and receiver is improved. Since the horn antennas (20 dBi) are mounted on the roof of a vehicle at a shallow inclination angle (15 to 25 with respect to horizontal), there is a first-order reduction in ground reflection so that a significant amount of the total reflected power received by the GPR comes from the scattering of RF energy off of buried objects. The stepped-frequency technique works by transmitting a tone at a particular frequency, while the received signal is mixed with the transmitted tone. As a result, the output of the mixer produces a signal that indicates the strength of the received signal and the extent to which it is in phase or out of phase with the transmitted tone. By taking measurements of the phase relationship between the transmitted and received signals over a wide frequency range, an interference pattern is produced showing all target reflections. When a Fourier transform is performed on this pattern, the result is a time-domain representation of targets. Among the advantages of this technique over impulse radar is the ability to transmit and receive much more total energy, and to use non-damped, highly focused horn antennas. The novelty of the IED detector GPR has been achieved by miniaturization of GPR electronics (single electronics board, 10x5x2 cm), low power consumption (3 W), faster signal processing capability, and minimal impact on vehicle operations.

Kim, Soon Sam↗

NASA NTRS1979

Development of a tree classifier for discrimination of surface mine activity from Landsat digital data

In a cooperative project with the Geological Survey of Alabama, the Mississippi State Remote Sensing Applications Program has developed a single purpose, decision-tree classifier using band-ratioing techniques to discriminate various stages of surface mining activity. The tree classifier has four levels and employs only two channels in classification at each level. An accurate computation of the amount of disturbed land resulting from the mining activity can be made as a product of the classification output. The utilization of Landsat data provides a cost-efficient, rapid, and accurate means of monitoring surface mining activities.

Solomon, J. L.↗

NASA NTRS2005

Searching for 'Unknown Unknowns'

The NASA Engineering and Safety Center (NESC) was established to improve safety through engineering excellence within NASA programs and projects. As part of this goal, methods are being investigated to enable the NESC to become proactive in identifying areas that may be precursors to future problems. The goal is to find unknown indicators of future problems, not to duplicate the program-specific trending efforts. The data that is critical for detecting these indicators exist in a plethora of dissimilar non-conformance and other databases (without a common format or taxonomy). In fact, much of the data is unstructured text. However, one common database is not required if the right standards and electronic tools are employed. Electronic data mining is a particularly promising tool for this effort into unsupervised learning of common factors. This work in progress began with a systematic evaluation of available data mining software packages, based on documented decision techniques using weighted criteria. The four packages, which were perceived to have the most promise for NASA applications, are being benchmarked and evaluated by independent contractors. Preliminary recommendations for "best practices" in data mining and trending are provided. Final results and recommendations should be available in the Fall 2005. This critical first step in identifying "unknown unknowns" before they become problems is applicable to any set of engineering or programmatic data.

Parsons, Vickie S.↗

DOE OSTI2026

An ICP-OES method for the precise and accurate quantification of rare earth elements in natural water: A comparative study from mine waste sites in New Mexico, USA

Inductively coupled plasma techniques such as ICP-OES and ICP-MS are routinely used to determine the concentrations of rare earth elements (REE) in water samples. However, their performance for the determination of REE concentration in mine drainage waters from epithermal vein and porphyry copper mining districts has not been evaluated extensively. In this work, we develop an REE analysis method on an Agilent 5900 ICP-OES instrument and assess the accuracy and precision for the quantification of REE in the natural waters collected from mine adits and an acid seep of mine sites in the Steeple Rock and Hillsboro mining districts, New Mexico, USA. The total REE concentrations in the water samples were measured using the methods we developed for both ICP-OES and ICP-MS. The power of the new ICP-OES method lies in routine analysis of μg/L level concentrations normally analyzed using ICP-MS, including a U.S. Geological Survey standard reference sample, laboratory blank samples spiked with a National Institute of Standards and Technology traceable standard, and surface water samples from mine waste sites. This ICP-OES method achieves low quantification limits ranging from 0.2 to 5 μg/L and excellent analytical accuracy and precision for REE analysis. The precision of light (La-Gd) and heavy (Tb-Lu) REE analysis using this method are better than 5% at average concentrations above 5 ± 4 μg/L and 3 ± 2 μg/L, respectively, and 3% at average concentrations above 10 ± 9 μg/L and 5 ± 4 μg/L, respectively. This method also shows excellent sensitivity and reproducibility for our laboratory and field samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1973

Study of application of ERTS-A imagery to fracture-related mine safety hazards in the coal mining industry

The author has identified the following significant results. The Kings Station Mine in Gibson County, Indiana has experienced considerable roof fall problems. Detailed fracture mapping of the mine area was done with ERTS-1 and aircraft imagery, and a prediction map of roof problem areas was produced in advance of a visit. The visit to the mine and discussions with the operator indicated that of four zones mapped as potential problem areas, three coincided with areas of excessive roof fall. This positive correlation of 75% lends confidence to the validity of the technique being applied in the investigation. The mine officials expressed an interest in the project and are anxious to see the final product maps which are forthcoming.

Wier, C. E.↗

DOE OSTI2021

Data Mining of Polymer Phase Transitions upon Temperature Changes by Small and Wide-Angle X-ray Scattering Combined with Raman Spectroscopy

The complex physical transformations of polymers upon external thermodynamic changes are related to the molecular length of the polymer and its associated multifaceted energetic balance. The understanding of subtle transitions or multistep phase transformation requires real-time phenomenological studies using a multi-technique approach that covers several length-scales and chemical states. A combination of X-ray scattering techniques with Raman spectroscopy and Differential Scanning Calorimetry was conducted to correlate the structural changes from the conformational chain to the polymer crystal and mesoscale organization. Current research applications and the experimental combination of Raman spectroscopy with simultaneous SAXS/WAXS measurements coupled to a DSC is discussed. In particular, we show that in order to obtain the maximum benefit from simultaneously obtained high-quality data sets from different techniques, one should look beyond traditional analysis techniques and instead apply multivariate analysis. Data mining strategies can be applied to develop methods to control polymer processing in an industrial context. Crystallization studies of a PVDF blend with a fluoroelastomer, known to feature complex phase transitions, were used to validate the combined approach and further analyzed by MVA.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Significant DBSCAN+: Statistically Robust Density-based Clustering

Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes and varying densities. As a classical topic in data mining and learning, a myriad of techniques have been developed to detect clusters with both varying shapes and densities (e.g., density-based, hierarchical, spectral, or deep clustering methods). However, the vast majority of these techniques do not consider statistical rigor and are susceptible to detecting spurious clusters formed as a result of natural randomness. On the other hand, scan statistic approaches explicitly control the rate of spurious results, but they typically assume a single “hotspot” of over-density and many rely on further assumptions such as a tessellated input space. To unite the strengths of both lines of work, we propose a statistically robust formulation of a multi-scale DBSCAN, namely Significant DBSCAN+, to identify significant clusters that are density connected. As we will show, incorporation of statistical rigor is a powerful mechanism that allows the new Significant DBSCAN+ to outperform state-of-the-art clustering techniques in various scenarios. We also propose computational enhancements to speed-up the proposed approach. Experiment results show that Significant DBSCAN+ can simultaneously improve the success rate of true cluster detection (e.g., 10–20% increases in absolute F1 scores) and substantially reduce the rate of spurious results (e.g., from thousands/hundreds of spurious detections to none or just a few across 100 datasets), and the acceleration methods can improve the efficiency for both clustered and non-clustered data.

Computer Science↗

DOE OSTI2016

diamond-sampling

This software provides a means for computing only the largest few entries of the product of two matrices, both exactly and approximately (using randomized sampling techniques). The purpose of the code is to demonstrate both the time it takes to solve the problem as well as the accuracy of the approximate approach. It is also meant to serve as a foundation to test the applicability of the sampling technique to related problems in data mining, including maximum inner product search, nearest neighbor search, and maximum cosine similarity.

Ballard, Grey↗

DOE OSTI2020

High-dimensional and high-resolution x-ray tomography for energy materials science

At the forefront of developments in synchrotron x-ray microscopy, we report nanoscale-resolution high-dimensional spectrotomography under controlled sample environments has been demonstrated. Such cutting-edge experimental capability has been broadly applied to scientific studies in the field of energy materials science, where the dynamically evolving structural and chemical defects play a vital role in the functionality. In this article, we review novel developments of this technique from both experimental and data/information mining perspectives. Using studies on lithium-ion battery electrode materials as examples, we highlight the rich information in the high-dimensional and high-resolution x-ray tomographic data, which can be used to interpret the complicated thermal-electro-chemo-mechanical interplay that occurs under the operating conditions and collectively determines battery performance. We also discuss the frontier challenges in this field and our perspectives of the future directions in the context of projected major developments in the landscape of largescale x-ray facilities across the globe.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Artificial-Intelligence Aided Design and Synthesis of Novel Layered 2D Multi-Principal Element Materials for Energy Storage (Final Report)

This DOE-EPSCoR project aimed to predict, synthesize, and characterize novel layered two-dimensional (2D) high-entropy materials (HEMs). These 2D-HEMs, composed of multiple principal elements in nearly equal concentrations, are distinct from traditional 2D materials (typically containing two or three elements) and conventional alloys (dominated by a single primary element with minor secondary additions). Their unique structural and compositional features enable significant lattice strain accommodation, resulting in enhanced electrode performance and potential applications in catalysis, hydrogen storage, sensing, quantum information technologies, and flexible electronics. The research focused on addressing four fundamental questions: (i) What combinations of elements can form stable and synthesizable 2D-HEMs? (ii) What mechanisms drive the stability and synthesizability of crystalline single-phase 2D-HEMs? (iii) How do local chemical disorder and defects influence the macroscopic electronic and mechanical properties? and (iv) What charge storage mechanisms are active in selectively synthesized 2D-HEMs for battery and supercapacitor electrode applications? To achieve these goals, the project employed an integrated theory-experiment approach, incorporating high-throughput first-principles calculations, theoretical modeling, data mining, experimental synthesis, and advanced characterization techniques. The advanced computing resources and state-of-the-art experimental characterization facilities at Oak Ridge National Laboratory (ORNL) were leveraged through collaboration. Beyond scientific advancements, the project contributed to workforce development. Two postdoctoral researchers and three graduate students at the University of Maine were trained through co-advising by ORNL scientists and collaborative interactions, strengthening their expertise in cutting-edge materials science.

36 MATERIALS SCIENCE↗

NASA NTRS2008

Estimating Software-Development Costs With Greater Accuracy

COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.

Baker, Dan↗

NASA NTRS1984

Final Comparison of TM and MSS Data for Surface Mine Assessment in Logan County, West Virginia

A variety of classifications during both raw and transformed MSS and TM data sets from 4 September 1982 were performed for the Logan County, West Virginia study area. The object was to compare the utility of TM and MSS data for delineating small, irregular ground features, particularly surface mines, and also to test data reduction/transformation techniques (band selection, canonical analysis, and principal components) in relation to a traditional means of unsupervised classification. Statistical results demonstrate that, on the average, the TM classifications yielded an overall .53 factor of improvement relative to the MSS classifications. When the accuracies for only three minor (in terms of areal extent) land use categories are examined, the factor of improvement for TM over MSS increases to 1.48; i.e., the TM is nearly one and one-half times better than the MSS for delineating small and irregular ground features such as contour strip mines.

Witt, R. G.↗

DOE OSTI2021

Critical review of functionalized silica sorbent strategies for selective extraction of rare earth elements from acid mine drainage

We report the ubiquitous and growing global reliance on rare earth elements (REEs) for modern technology and the need for reliable domestic sources underscore the rising trend in REE-related research. Adsorption-based methods for REE recovery from liquid waste sources are well-positioned to compete with those of solvent extraction, both because of their expected lower negative environmental impact and simpler process operations. Functionalized silica represents a rising category of low cost and stable sorbents for heavy metal and REE recovery. These materials have collectively achieved high capacity and/or high selective removal of REEs from ideal solutions and synthetic or real coal wastewater and other leachate source. These sorbents are competitive with conventional materials, such as ion exchange resins, activated carbon; and novel polymeric materials like ion-imprinted particles and metal organic frameworks (MOFs). This critical review first presents a data mining analysis for rare earth element recovery publications indexed in Web of science, highlighting changes in REE recovery research foci and confirming the sharply growing interest in functionalized silica sorbents. A detailed examination of sorbent formulation and operation strategies to selectively separate heavy (HREE), middle (MREE), and light (LREE) REEs from the aqueous sources is presented. Selectivity values for sorbents were largely calculated from available figure data and gauged the success of the associated strategies, primarily: (1) silane-grafted ligands, (2) impregnated ligands, and (3) bottom-up ligand/silica hybrids. These were often accompanied by successful co-strategies, especially bite angle control, site saturation, and selective REE elution. Recognizing the need to remove competing fouling metals to achieve purified REE “baskets,” we highlight techniques for eliminating these species from acid mine drainage (AMD) and suggest a novel adsorption-based process for purified REE extraction that could be adapted to different water systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Automated Construction of a Photocatalysis Dataset for Water-Splitting Applications

We present an automatically generated dataset of 15,755 records that were extracted from 47,357 papers. These records contain water-splitting activity in the presence of certain photocatalysts, along with additional information about the chemical reaction conditions under which this activity was recorded. These conditions include any co-catalysts and additives that were present during water splitting, the length of time for which the photocatalytic experiment was conducted, and the type of light source used, including its wavelength. Despite the text extraction of such a wide range of chemical reaction attributes, the dataset afforded good precision (71.2%) and recall (36.3%). These figures-of-merit were calculated based on a random sample of open-access papers from the corpus. Mining such a complex set of attributes required the development of novel techniques in knowledge extraction and interdependency resolution, leveraging inter- and intra-sentence relations, which are also described in this paper. We present a new version (version 2.2) of the chemistry-aware text-mining toolkit ChemDataExtractor, in which these new techniques are included.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Genetic Transfer in Action: Uncovering DNA Flow in an Extremophilic Microbial Community

ABSTRACT Horizontal genetic transfer (HGT) is a significant driver of genomic novelty in all domains of life. HGT has been investigated in many studies however, the focus has been on conspicuous protein‐coding DNA transfers that often prove to be adaptive in recipient organisms and are therefore fixed longer‐term in lineages. These results comprise a subclass of HGTs and do not represent exhaustive (coding and non‐coding) DNA transfer and its impact on ecology. Uncovering exhaustive HGT can provide key insights into the connectivity of genomes in communities and how these transfers may occur. In this study, we use the term frequency‐inverse document frequency (TF‐IDF) technique, that has been used successfully to mine DNA transfers within real and simulated high‐quality prokaryote genomes, to search for exhaustive HGTs within an extremophilic microbial community. We establish a pipeline for validating transfers identified using this approach. We find that most DNA transfers are within‐domain and involve non‐coding DNA. A relatively high proportion of the predicted protein‐coding HGTs appear to encode transposase activity, restriction‐modification system components, and biofilm formation functions. Our study demonstrates the utility of the TF‐IDF approach for HGT detection and provides insights into the mechanisms of recent DNA transfer.

Microbiology↗

DOE OSTI2020

Provenance infrastructure for multimodal x-ray experiments and reproducible analysis

Exploring relationships between material structures and desired properties for material discovery and synthesis requires mining machine-readable databases and linking experimental data with sufficiently rich annotations. There are vast gaps both in these data sources and in the connections between them. We present a provenance-based data management and analysis framework that enables capturing, persisting, and reanalyzing experimental data from the BNL National Synchrotron Light Source II (NSLS-II). Our system leverages NSLS-II Bluesky for experimental data acquisition, captures analysis parameters, and enriches the search space with results from the scientific literature. We describe in detail the challenges and benefits of data-driven approaches when comparing computational and experimental data, such as the multiple possible scenarios of interest in often ill-posed inverse problems and missing data. Our infrastructure utilizes the NSLS-II event model and includes discovery mechanisms across multiple beamlines. A text and data mining module using natural language processing classification techniques extracts relevant information from the literature that is added to data sources. We describe a provenance acquisition and analysis rerun workflow based on a directed acyclic graph that keeps track of process and data provenance and allows to replay analysis.

97 MATHEMATICS AND COMPUTING↗