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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Fast and Flexible Multivariate Time Series Subsequence Search

Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical monitoring, and financial systems. Domain experts are often interested in searching for interesting multivariate patterns from these MTS databases which often contain several gigabytes of data. Surprisingly, research on MTS search is very limited. Most of the existing work only supports queries with the same length of data, or queries on a fixed set of variables. In this paper, we propose an efficient and flexible subsequence search framework for massive MTS databases, that, for the first time, enables querying on any subset of variables with arbitrary time delays between them. We propose two algorithms to solve this problem (1) a List Based Search (LBS) algorithm which uses sorted lists for indexing, and (2) a R*-tree Based Search (RBS) which uses Minimum Bounding Rectangles (MBR) to organize the subsequences. Both algorithms guarantee that all matching patterns within the specified thresholds will be returned (no false dismissals). The very few false alarms can be removed by a post-processing step. Since our framework is also capable of Univariate Time-Series (UTS) subsequence search, we first demonstrate the efficiency of our algorithms on several UTS datasets previously used in the literature. We follow this up with experiments using two large MTS databases from the aviation domain, each containing several millions of observations. Both these tests show that our algorithms have very high prune rates (>99%) thus needing actual disk access for only less than 1% of the observations. To the best of our knowledge, MTS subsequence search has never been attempted on datasets of the size we have used in this paper.

Bhaduri, Kanishka↗
NASA NTRS2001

Portfolios in Stochastic Local Search: Efficiently Computing Most Probable Explanations in Bayesian Networks

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) and different search operators (greedy and noisy heuristics), thereby enabling new analytical and experimental results. Analytically, we introduce a novel Markov chain model tailored to portfolio-based SLS algorithms including SGS, thereby enabling us to analytically form expected hitting time results that explain empirical run time results. For a specific BN, we show the benefit of using a homogenous initialization portfolio. To further illustrate the portfolio approach, we consider novel additive search heuristics for handling determinism in the form of zero entries in conditional probability tables in BNs. Our additive approach adds rather than multiplies probabilities when computing the utility of an explanation. We motivate the additive measure by studying the dramatic impact of zero entries in conditional probability tables on the number of zero-probability explanations, which again complicates the search process. We consider the relationship between MAXSAT and MPE, and show that additive utility (or gain) is a generalization, to the probabilistic setting, of MAXSAT utility (or gain) used in the celebrated GSAT and WalkSAT algorithms and their descendants. Utilizing our Markov chain framework, we show that expected hitting time is a rational function - i.e. a ratio of two polynomials - of the probability of applying an additive search operator. Experimentally, we report on synthetically generated BNs as well as BNs from applications, and compare SGSs performance to that of Hugin, which performs BN inference by compilation to and propagation in clique trees. On synthetic networks, SGS speeds up computation by approximately two orders of magnitude compared to Hugin. In application networks, our approach is highly competitive in Bayesian networks with a high degree of determinism. In addition to showing that stochastic local search can be competitive with clique tree clustering, our empirical results provide an improved understanding of the circumstances under which portfolio-based SLS outperforms clique tree clustering and vice versa.

Mengshoel, Ole J.↗
NASA NTRS2012

All-Sky Search for Gravitational-Wave Bursts in the First Joint LIGO-GEO-Virgo Run

We present results from an aU-sky search for unmodeled gravitational-wave bursts in the data collected by the LIGO, GEO 600 and Virgo detectors between November 2006 and October 2007. The search is performed. by three different analysis algorithms over the frequency band 50 - 6000 Hz. Data are analyzed for times with at least two of the four LIGO-Virgo detectors in coincident operation, with a total live time of 266 days, No events produced by the search algorithms survive the selection cuts. We set a frequentist upper limit on the rate of gravitational-wave bursts impinging on our network of detectors. When combined with the previous LIGO search of the data collected between November 2005 and November 2006, the upper limit on the rate of detectable gra.vitational. wave bursts in the 64-2048 Hz band is 2,0 events per year at 90% confidence. We also present event rate versus strength exclusion plots for several types of plausible burst waveforms. The sensitivity of the combined search is expressed in terms of the root-sum-squared strain amplitude for a variety of simulated waveforms and lies in the range 6 X 10(exp -22) Hz(exp - 1/2) to 2 X 10(exp -20) Hz(exp -l/2). This is the first untriggered burst search to use data from the LIGO and Virgo detectors together, and the most sensitive untriggered burst search performed so far.

Camp, J. B.↗
NASA NTRS2014

JSC Search System Usability Case Study

The advanced nature of "search" has facilitated the movement from keyword match to the delivery of every conceivable information topic from career, commerce, entertainment, learning... the list is infinite. At NASA Johnson Space Center (JSC ) the Search interface is an important means of knowledge transfer. By indexing multiple sources between directorates and organizations, the system's potential is culture changing in that through search, knowledge of the unique accomplishments in engineering and science can be seamlessly passed between generations. This paper reports the findings of an initial survey, the first of a four part study to help determine user sentiment on the intranet, or local (JSC) enterprise search environment as well as the larger NASA enterprise. The survey is a means through which end users provide direction on the development and transfer of knowledge by way of the search experience. The ideal is to identify what is working and what needs to be improved from the users' vantage point by documenting: (1) Where users are satisfied/dissatisfied (2) Perceived value of interface components (3) Gaps which cause any disappointment in search experience. The near term goal is it to inform JSC search in order to improve users' ability to utilize existing services and infrastructure to perform tasks with a shortened life cycle. Continuing steps include an agency based focus with modified questions to accomplish a similar purpose

Meza, David↗
NASA NTRS2014

Search for Gravitational Waves Associated with Gamma-Ray Bursts Detected by the Interplanetary Network

We present the results of a search for gravitational waves associated with 223 gamma ray bursts (GRBs) detected by the InterPlanetary Network (IPN) in 2005-2010 during LIGO's fifth and sixth science runs and Virgo's first, second, and third science runs. The IPN satellites provide accurate times of the bursts and sky localizations that vary significantly from degree scale to hundreds of square degrees. We search for both a well-modeled binary coalescence signal, the favored progenitor model for short GRBs, and for generic, unmodeled gravitational wave bursts. Both searches use the event time and sky localization to improve the gravitational wave search sensitivity as compared to corresponding all-time, all-sky searches. We find no evidence of a gravitational wave signal associated with any of the IPN GRBs in the sample, nor do we find evidence for a population of weak gravitational wave signals associated with the GRBs. For all IPN-detected GRBs, for which a sufficient duration of quality gravitational wave data are available, we place lower bounds on the distance to the source in accordance with an optimistic assumption of gravitational wave emission energy of 10(exp−2) solar mass c(exp 2) at 150 Hz, and find a median of 13 Mpc. For the 27 short-hard GRBs we place 90% confidence exclusion distances to two source models: a binary neutron star coalescence, with a median distance of 12 Mpc, or the coalescence of a neutron star and black hole, with a median distance of 22 Mpc. Finally, we combine this search with previously published results to provide a population statement for GRB searches in first-generation LIGO and Virgo gravitational wave detectors and a resulting examination of prospects for the advanced gravitational wave detectors.

gravitational wave detectors↗
NASA NTRS1994

Search Space Characterization for a Telescope Scheduling Application

This paper presents a technique for statistically characterizing a search space and demonstrates the use of this technique within a practical telescope scheduling application. The characterization provides the following: (i) an estimate of the search space size, (ii) a scaling technique for multi-attribute objective functions and search heuristics, (iii) a "quality density function" for schedules in a search space, (iv) a measure of a scheduler's performance, and (v) support for constructing and tuning search heuristics. This paper describes the random sampling algorithm used to construct this characterization and explains how it can be used to produce this information. As an example, we include a comparative analysis of an heuristic dispatch scheduler and a look-ahead scheduler that performs greedy search.

Bresina, John↗
NASA NTRS2006

A Comprehensive Search for Gamma-Ray Lines in the First Year of Data from the INTEGRAL Spectrometer

Gamma-ray lines are produced in nature by a variety of different physical processes. They can be valuable astrophysical diagnostics providing information the may be unobtainable by other means. We have carried out an extensive search for gamma-ray lines in the first year of public data from the Spectrometer (SPI) on the INTEGRAL mission. INTEGRAL has spent a large fraction of its observing time in the Galactic Plane with particular concentration in the Galactic Center (GC) region (approximately 3 Msec in the first year). Hence the most sensitive search regions are in the Galactic Plane and Center. The phase space of the search spans the energy range 20-8000 keV, and line widths from 0-1000 keV (FWHM) and includes both diffuse and point-like emission. We have searched for variable emission on time scales down to approximately 1000 sec. Diffuse emission has been searched for on a range of different spatial scales from approximately 20 degrees (the approximate field-of-view of the spectrometer) up to the entire Galactic Plane. Our search procedures were verified by the recovery of the known gamma-ray lines at 511 keV and 1809 keV at the appropriate intensities and significances. We find no evidence for any previously unknown gamma-ray lines. The upper limits range from a few x10(exp -5) per square centimeter per second to a few x10(exp -3) per square centimeter per second depending on line width, energy and exposure. Comparison is made between our results and various prior predictions of astrophysical lines

Teegarden, B. J.↗
NASA NTRS2012

All Sky Search for Gravitational-Wave Bursts in the Second Joint LIGO-Virgo Run

We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration approx. < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal wa.veform, polarization, direction or occurrence time. All identified events are c.onsistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGOVirgo search on the data collected "between November 2005 and October 2007. The upper limit on the rate of strong gravita.tional-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per yea.r and Mpc3 for sample popula.tions of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range approx 5 x 10(exp -22 Hz(exp-1/2) approx 1 X 10(exp -20) Hz(exp -1/2) . The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.

Abadie, J.↗
NASA NTRS2012

Improved Search Techniques

Thousands of millions of documents are stored and updated daily in the World Wide Web. Most of the information is not efficiently organized to build knowledge from the stored data. Nowadays, search engines are mainly used by users who rely on their skills to look for the information needed. This paper presents different techniques search engine users can apply in Google Search to improve the relevancy of search results. According to the Pew Research Center, the average person spends eight hours a month searching for the right information. For instance, a company that employs 1000 employees wastes $2.5 million dollars on looking for nonexistent and/or not found information. The cost is very high because decisions are made based on the information that is readily available to use. Whenever the information necessary to formulate an argument is not available or found, poor decisions may be made and mistakes will be more likely to occur. Also, the survey indicates that only 56% of Google users feel confident with their current search skills. Moreover, just 76% of the information that is available on the Internet is accurate.

Albornoz, Caleb Ronald↗
NASA NTRS2013

Einstein@Home All-Sky Search for Periodic Gravitational Waves in LIGO S5 Data

This paper presents results of an all-sky search for periodic gravitational waves in the frequency range [50, 1 190] Hzand and with frequency derivative range of approx. [-20,1.1] x 10(exp-10) H(sub 0)z s(exp-1) for the fifth LIGO science run (S5). The search uses a noncoherent Hough-transform method to combine the information from coherent searches on time scales of about one day. Because these searches are very computationally intensive, they have been carried out with the Einstein@Home volunteer distributed computing project. Postprocessing identifies eight candidate signals; deeper follow-up studies rule them out. Hence, since no gravitational wave signals have been found, we report upper limits on the intrinsic gravitational wave strain amplitude ho. For example, in the 0.5 Hz-wide band at 152.5 Hz, we can exclude the presence of signals with h(exp 0) greater than 7.6 x 10(exp-25) at a 90% confidence level. This search is about a factor 3 more sensitive than the previous Einstein@Home search of early S5 LIGO data.

J Aasi↗
NASA NTRS2017

Stochastic Template Bank for Gravitational Wave Searches for Precessing Neutron Star-Black Hole Coalescence Events

Gravitational wave searches to date have largely focused on non-precessing systems. Including precession effects greatly increases the number of templates to be searched over. This leads to a corresponding increase in the computational cost and can increase the false alarm rate of a realistic search. On the other hand, there might be astrophysical systems that are entirely missed by non-precessing searches. In this paper we consider the problem of constructing a template bank using stochastic methods for neutron star-black hole binaries allowing for precession, but with the restrictions that the total angular momentum of the binary is pointing toward the detector and that the neutron star spin is negligible relative to that of the black hole. We quantify the number of templates required for the search, and we explicitly construct the template bank. We show that despite the large number of templates, stochastic methods can be adapted to solve the problem. We quantify the parameter space region over which the non-precessing search might miss signals.

gravitational wave↗
NASA NTRS2016

A Dark Energy Camera Search for an Optical Counterpart to the First Advanced LIGO Gravitational Wave Event GW150914

We report the results of a deep search for an optical counterpart to the gravitational wave (GW) event GW150914, the first trigger from the Advanced LIGO GW detectors. We used the Dark Energy Camera (DECam) to image a 102 deg(exp 2) area, corresponding to 38% of the initial trigger high-probability sky region and to 11% of the revised high-probability region. We observed in the i and z bands at 4-5, 7, and 24 days after the trigger. The median 5(sigma) point-source limiting magnitudes of our search images are i = 22.5 and z = 21.8 mag. We processed the images through a difference-imaging pipeline using templates from pre-existing Dark Energy Survey data and publicly available DECam data. Due to missing template observations and other losses, our effective search area subtends 40 deg(exp 2), corresponding to a 12% total probability in the initial map and 3% in the final map. In this area, we search for objects that decline significantly between days 4-5 and day 7, and are undetectable by day 24, finding none to typical magnitude limits of i = 21.5, 21.1, 20.1 for object colors (i-z)= 1, 0, -1, respectively. Our search demonstrates the feasibility of a dedicated search program with DECam and bodes well for future research in this emerging field.

binaries: close – catalogs – gravitational wav↗
NASA NTRS2020

Optimal Multi-Agent Search and Rescue Using Potential Field Theory

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used to weight the attractiveness of these points in the potential field, and collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. The algorithm generates velocity commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. Simulation results are presented to demonstrate the ability of the algorithm to cover the search area effectively. The algorithm is also compared to an exhaustive lawn-mower search pattern. This comparison is done via a Monte Carlo simulation with randomized target initial conditions and trajectories. The time to find the target improved by 16 and 30% in the mean and median, respectively. Additionally, this paper presents a method for analyzing the upper bound for time to find a target under the potential field guidance algorithm assuming a radially expanding search area.

John R Cooper↗
NASA NTRS2020

Development of VBA Tool for Document Term Search

Employees throughout different agencies such as NASA, have identified that the search of determined terms/words through documents, consume substantial research time of such. These types of searches are substantially limited towards one word in a one document identification; forward one, these usual types of searches lack efficiency & optimization through research aspects of work. Consequently, this reflects in the decrease productivity during work hours etc. The application of VBA (Visual Basic for Applications) is the programming language of Excel, which was conducted for the development of optimized tool for document term search. The project enables the search of single & multiple word/term search through single format documents for paragraph data extraction.

Ssytems Development↗
NASA NTRS2019

Search for Gravitational Waves From Scorpius X-1 in the Second Advanced LIGO Observing Run With an Improved Hidden Markov Model

We present results from a semi coherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO’s second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) ofh95%0¼3.47×10−25when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering.

B P Abbott↗
NASA NTRSDate not supplied

Multi-Agent Search and Rescue Applied to a Swarm of Ground Vehicles

This paper presents an algorithm for efficient search and rescue using a multi-agent system of vehicles. The algorithm uses an artificial potential field combined with a time-varying reward function for visiting various points within the search area. The reward function is used as a weight for the attractiveness of these points in the potential field. The reward value increases while the point is not being observed, and decreases while the point is observed. Collision avoidance terms are used to repel vehicles from each other, which has the additional effect of reducing duplication of searching efforts. Gradient descent of the potential field results in persistent surveillance of the search area. The algorithm generates position commands in real-time based on communication with the other vehicles. This framework allows vehicles to react in a dynamic environment, which is a significant advantage to simply following a-priori defined trajectories. The algorithm is applied to a swarm of ground robots, and experimental data is presented showing that the swarm effectively searches the entire area and self-allocates search regions to individual vehicles.

multi-agent↗
NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗
NASA NTRS1974

The effect of a visual indicator on rate of visual search Evidence for processing control

Search rates were estimated from response latencies in a visual search task of the type used by Atkinson et al. (1969), in which a subject searches a small set of letters to determine the presence or absence of a predesignated target. Half of the visual displays contained a marker above one of the letters. The marked letter was the only one that had to be checked to determine whether or not the display contained the target. The presence of a marker in a display significantly increased the estimated rate of search, but the data clearly indicated that subjects did not restrict processing to the marked item. Letters in the vicinity of the marker were also processed. These results were interpreted as showing that subjects are able to exercise some degree of control over the search process in this type of task.

Holmgren, J. E.↗