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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Abort Trigger False Positive and False Negative Analysis Methodology for Threshold-Based Abort Detection

This paper describes a quantitative methodology for bounding the false positive (FP) and false negative (FN) probabilities associated with a human-rated launch vehicle abort trigger (AT) that includes sensor data qualification (SDQ). In this context, an AT is a hardware and software mechanism designed to detect the existence of a specific abort condition. Also, SDQ is an algorithmic approach used to identify sensor data suspected of being corrupt so that suspect data does not adversely affect an AT's detection capability. The FP and FN methodologies presented here were developed to support estimation of the probabilities of loss of crew and loss of mission for the Space Launch System (SLS) which is being developed by the National Aeronautics and Space Administration (NASA). The paper provides a brief overview of system health management as being an extension of control theory; and describes how ATs and the calculation of FP and FN probabilities relate to this theory. The discussion leads to a detailed presentation of the FP and FN methodology and an example showing how the FP and FN calculations are performed. This detailed presentation includes a methodology for calculating the change in FP and FN probabilities that result from including SDQ in the AT architecture. To avoid proprietary and sensitive data issues, the example incorporates a mixture of open literature and fictitious reliability data. Results presented in the paper demonstrate the effectiveness of the approach in providing quantitative estimates that bound the probability of a FP or FN abort determination.

risk assessment↗
NASA NTRS2017

Kepler Certified False Positive Table

This document describes the Kepler Certied False Positive table hosted at the Exoplanet Archive1, herein referred to as the CFP table. This table is the result of detailed examination by the Kepler False Positive Working Group (FPWG) of declared false positives in the Kepler Object of Interest (KOI) tables (see, for example, Batalha et al. (2012); Burke et al.(2014); Rowe et al. (2015); Mullally et al. (2015); Coughlin et al. (2015b)) at the Exoplanet Archive. A KOI is considered a false positive if it is not due to a planet orbiting the KOI's target star. The CFP table contains all KOIs in the Exoplanet Archive cumulative KOI table. The purpose of the CFP table is to provide a list of certified false positive KOIs. A KOI is certified as a false positive when, in the judgement of the FPWG, there is no plausible planetary interpretation of the observational evidence, which we summarize by saying that the evidence for a false positive is compelling. This certification process involves detailed examination using all available data for each KOI, establishing a high-reliability ground truth set. The CFP table can be used to estimate the reliability of, for example, the KOI tables which are created using only Kepler photometric data, so the disposition of individual KOIs may differ in the KOI and CFP tables. Follow-up observers may find the CFP table useful to avoid observing false positives.

Kepler↗
NASA NTRS2018

Abiotic O2 Levels on Planets Around F, G, K, and M Stars: Effects of Lightning-Produced Catalysts in Eliminating Oxygen False Positives

Over the last few years, a number of authors have suggested that, under certain circumstances, molecular oxygen (O2) or ozone (O3) generated by abiotic processes may accumulate to detectable concentrations in a habitable terrestrial planet's atmosphere, producing so-called "false positives" for life. But the models have occasionally disagreed with each other, with some predicting false positives, and some not, for the same apparent set of circumstances. We show here that photochemical false positives derive either from inconsistencies in the treatment of atmospheric and global redox balance or from the treatment (or lack thereof) of lightning. For habitable terrestrial planets with even trace amounts of atmospheric N2, NO produced by lightning catalyzes the recombination of CO and O derived from CO2 photolysis and should be sufficient to eliminate all reported false positives. Molecular oxygen thus remains a useful biosignature gas for Earth-like extrasolar planets, provided that the planet resides within the conventional liquid water habitable zone and has not experienced distinctly non-Earth- like, irrecoverable water loss.

planets and satellites↗
NASA NTRS2018

Abiotic O2 Levels on Planets around F, G, K, and M Stars: Effects of Lightning-Produced Catalysts in Eliminating Oxygen False Positives

Within the last several years, a number of authors (Hu et al., 2012; Tian et al., 302014; Harman et al., 2015; Domagal-Goldman et al., 2015;Gao et al., 2015) have suggested that, under certain circumstances, molecular oxygen (O 2 ) or ozone (O 3 ) generated by abiotic processes may accumulate to detectable concentrations in a habitable terrestrial planet’s atmosphere, producing so-called ‘false positives’ for life. But the models have occasionally disagreed with each other, with some predicting false positives, and some not, for the same apparent set of circumstances. We show here that photochemical false positives derive either from inconsistencies in the treatment of atmospheric and global redox balance or from the treatment (or lack thereof) of lightning. For habitable terrestrial planets with even trace amounts of atmospheric N 2 , NO produced by lightning catalyzes the recombination of CO and O derived from CO 2 photolysis and should be sufficient to eliminate all reported false positives. O 2 thus remains a useful biosignature gas for Earth-like extrasolar planets, provided that the planet resides within the conventional liquid water habitable zone and did not experience distinctly non-Earth-like, irrecoverable water loss.

planet–star interactions↗
NASA NTRS2002

Reducing False Positives in Runtime Analysis of Deadlocks

This paper presents an improvement of a standard algorithm for detecting dead-lock potentials in multi-threaded programs, in that it reduces the number of false positives. The standard algorithm works as follows. The multi-threaded program under observation is executed, while lock and unlock events are observed. A graph of locks is built, with edges between locks symbolizing locking orders. Any cycle in the graph signifies a potential for a deadlock. The typical standard example is the group of dining philosophers sharing forks. The algorithm is interesting because it can catch deadlock potentials even though no deadlocks occur in the examined trace, and at the same time it scales very well in contrast t o more formal approaches to deadlock detection. The algorithm, however, can yield false positives (as well as false negatives). The extension of the algorithm described in this paper reduces the amount of false positives for three particular cases: when a gate lock protects a cycle, when a single thread introduces a cycle, and when the code segments in different threads that cause the cycle can actually not execute in parallel. The paper formalizes a theory for dynamic deadlock detection and compares it to model checking and static analysis techniques. It furthermore describes an implementation for analyzing Java programs and its application to two case studies: a planetary rover and a space craft altitude control system.

Bensalem, Saddek↗
NASA NTRS2011

Modeling Kepler Transit Light Curves as False Positives: Rejection of Blend Scenarios for Kepler-9, and Validation of Kepler-9 d, a Super-Earth-Size Planet in a Multiple System

Light curves from the Kepler Mission contain valuable information on the nature of the phenomena producing the transit-like signals. To assist in exploring the possibility that they are due to an astrophysical false positive we describe a procedure (BLENDER) to model the photometry in terms of a blend rather than a planet orbiting a star. A blend may consist of a background or foreground eclipsing binary (or star-planet pair) whose eclipses are attenuated by the light of the candidate and possibly other stars within the photometric aperture. We apply BLENDER to the case of Kepler-9 (KIC 3323887), a target harboring two previously confirmed Saturn-size planets (Kepler-9 b and Kepler-9 c) showing transit timing variations, and an additional shallower signal with a 1.59 day period suggesting the presence of a super-Earth-size planet. Using BLENDER together with constraints from other follow-up observations we are able to rule out all blends for the two deeper signals and provide independent validation of their planetary nature. For the shallower signal, we rule out a large fraction of the false positives that might mimic the transits. The false alarm rate for remaining blends depends in part (and inversely) on the unknown frequency of small-size planets. Based on several realistic estimates of this frequency, we conclude with very high confidence that this small signal is due to a super-Earth-size planet (Kepler-9 d) in a multiple system, rather than a false positive. The radius is determined to be 1.64(exp)(sub-14),R, and current spectroscopic observations are as yet insufficient to establish its mass.

PLANETARY SYSTEMS↗
NASA NTRS2013

A Discovery of a Candidate Companion to a Transiting System KOI-94: A Direct Imaging Study for a Possibility of a False Positive

We report a discovery of a companion candidate around one of Kepler Objects of Interest (KOIs), KOI-94, and results of our quantitative investigation of the possibility that planetary candidates around KOI-94 are false positives. KOI-94 has a planetary system in which four planetary detections have been reported by Kepler, suggesting that this system is intriguing to study the dynamical evolutions of planets. However, while two of those detections (KOI-94.01 and 03) have been made robust by previous observations, the others (KOI-94.02 and 04) are marginal detections, for which future confirmations with various techniques are required. We have conducted high-contrast direct imaging observations with Subaru/HiCIAO in H band and detected a faint object located at a separation of approximately 0.6 sec from KOI-94. The object has a contrast of approximately 1 × 10(exp −3) in H band, and corresponds to an M type star on the assumption that the object is at the same distance of KOI-94. Based on our analysis, KOI-94.02 is likely to be a real planet because of its transit depth, while KOI-94.04 can be a false positive due to the companion candidate. The success in detecting the companion candidate suggests that high-contrast direct imaging observations are important keys to examine false positives of KOIs. On the other hand, our transit light curve reanalyses lead to a better period estimate of KOI-94.04 than that on the KOI catalogue and show that the planetary candidate has the same limb darkening parameter value as the other planetary candidates in the KOI-94 system, suggesting that KOI-94.04 is also a real planet in the system.

Subaru/HiCIAO↗
NASA NTRS2018

Biosignature False Positives

In our search for life - whether within the earliest part of Earth's geologic record, on planets within our solar system such Mars, or especially for extrasolar planets - we must infer the presence of life from its impact on the local or global environment. These "biosignatures," often identified from the known influence of terrestrial organisms on the Earth's atmosphere and surface, could be misdiagnosed when we apply them to alien worlds. The so-called false positives may occur when another process or suite of processes masks or mimics a biosignature. Here, we examine several leading biosignatures, then introduce potential false positives for these signals, and finally discuss methods to discriminate between the two using current and future detection technologies. We conclude that it is the astrobiology community's responsibility to thoroughly exhaust all possibilities before we resort to "life" as an explanation.

Harman, Chester E.↗
NASA NTRS2018

Follow-up Imaging of Disk Candidates from the Disk Detective Citizen Science Project: New Discoveries and False Positives in WISE Circumstellar Disk Surveys

The Disk Detective citizen science project aims to find new stars with excess 22 m emission from circumstellar dust in the All WISE data release from the Wide-field Infrared Survey Explorer. We evaluated 261 Disk Detective objects of interest with imaging with the Robo-AO adaptive optics instrument on the 1.5 m telescope at Palomar Observatory and with RetroCam on the 2.5 m du Pont Telescope at Las Campanas Observatory to search for background objects at 0 15–12 separations from each target. Our analysis of these data leads us to reject 7% of targets. Combining this result with statistics from our online image classification efforts implies that at most7.9%±0.2% of All WISE-selected infrared excesses are good disk candidates. Applying our false-positive rates to other surveys, we find that the infrared excess searches of McDonald et al. and Marton et al. all have false-positiverates >70%. Moreover, we find that all 13 disk candidates in Theissen & West with W4 signal-to-noise ratio >3are false positives. We present 244 disk candidates that have survived vetting by follow-up imaging. Of these,213 are newly identified disk systems. Twelve of these are candidate members of comoving pairs based on Gaia astrometry, supporting the hypothesis that warm dust is associated with binary systems. We also note the discovery of 22 m excess around two known members of the Scorpius–Centaurus association, and we identifyknown disk host WISEA J164540.79-310226.6 as a likely Sco-Cen member. Thirty of these disk candidates arecloser than 125 pc (including 26 debris disks), making them good targets for both direct-imaging exoplanetsearches.

Wide-field Infrared Survey Explorer↗
NASA NTRS2020

A Habitable-zone Earth-sized Planet Rescued from False Positive Status

We report the discovery of an Earth-sized planet in the habitable zone of a low-mass star called Kepler-1649. The planet, Kepler-1649 c, is 1.06(+0.15, -0.10.) times the size of Earth and transits its 0.1977 ± 0.0051 Mʘ “mid” M-dwarf host star every 19.5 days. It receives 74% ± 3% the incident flux of Earth, giving it an equilibrium temperature of 234 ± 20 K and placing it firmly inside the circumstellar habitable zone. Kepler-1649 also hosts a previously known inner planet that orbits every 8.7 days and is roughly equivalent to Venus in size and incident flux. Kepler-1649 c was originally classified as a false positive (FP) by the Kepler pipeline, but was rescued as part of a systematic visual inspection of all automatically dispositioned Kepler FPs. This discovery highlights the value of human inspection of planet candidates even as automated techniques improve, and hints that terrestrial planets around mid to late M-dwarfs may be more common than those around more massive stars.

Andrew Vanderburg↗
NASA NTRS2012

Direct Imaging of Extra-Solar Planets in Star Forming Regions: Lessons Learned from a False Positive Around IM Lup

Context. Most exoplanet imagers consist of ground-based adaptive optics coronagraphic cameras which are currently limited in contrast, sensitivity and astrometric precision, but advantageously observe in the near-infrared window (1 5 m). Because of these practical limitations, our current observational aim at detecting and characterizing planets puts heavy constraints on target selection, observing strategies, data reduction, and follow-up. Most surveys so far have thus targeted young systems (1 100 Myr) to catch the putative remnant thermal radiation of giant planets, which peaks in the near-infrared. They also favor systems in the solar neighborhood (d less than 80 pc), which eases angular resolution requirements but also ensures a good knowledge of the distance and proper motion, which are critical to secure the planet status, and enable subsequent characterization. Aims. Because of their youth, it is very tempting to target the nearby star forming regions, which are typically twice as far as the bulk of objects usually combed for planets by direct imaging. Probing these interesting reservoirs sets additional constraints that we review in this paper by presenting the planet search that we initiated in 2008 around the disk-bearing T Tauri star IM Lup, which is part of the Lupus star forming region (140-190 pc). Methods. We show and discuss why age determination, the choice of evolutionary model for both the central star and the planet, precise knowledge of the host star proper motion, relative or absolute (between different instruments) astrometric accuracy (including plate scale calibration), and patience are the key ingredients for exoplanet searches around more distant young stars. Results. Unfortunately, most of the time, precision and perseverance are not paying off: we discovered a candidate companion around IM Lup in 2008, which we report here to be an unbound background object. We nevertheless review in details the lessons learned from our endeavor, and additionally present the best detection limits ever calculated for IM Lup. We also accessorily report on the successful use of innovative data reduction techniques, such as the damped-LOCI and iterative roll subtraction.

D Mawet↗
NASA NTRS2016

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗
NASA NTRS2010

Testing of Haar-Like Feature in Region of Interest Detection for Automated Target Recognition (ATR) System

The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.

neural network↗
DOE OSTI2024

Blind QC trend presentation

Blind testing is used to evaluate performance of the radiobioassay laboratory. DOE-STD-1112-2019 requires a radiobioassay program to perform blind testing at a documented frequency including accuracy, false positive, false negative, and sensitivity evaluations. INL trends accuracy determinations over time for bias, agreement, and precision. Trends have been identified for certain isotopes in urine and feces that have not been fully explained. This presentation will review those identified trends and discuss possible causes and solutions.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Orthogonal chemical genomics approaches reveal genomic targets for increasing anaerobic chemical tolerance in Zymomonas mobilis

Genetically engineered microbes have the potential to increase efficiency in the bioeconomy by overcoming growth-limiting production stress. Screens of gene perturbation libraries against production stressors can identify high-value engineering targets, but follow-up experiments needed to guard against false positives are slow and resource-intensive. In principle, the use of orthogonal gene perturbation approaches could increase recovery of true positives over false positives because the strengths of one technique compensate for the weaknesses of the other, but, in practice, two parallel screens are rarely performed at the genome scale. Here, we screen genome-scale CRISPRi (CRISPR interference) knockdown and transposon insertion libraries of the bioenergy-relevant Alphaproteobacterium, Zymomonas mobilis, against growth inhibitors commonly found in deconstructed plant material. Integrating data from the two gene perturbation techniques, we established an approach for defining engineering targets with high specificity. This allowed us to identify all known genes in the cytochrome bc1 and cytochrome c synthesis pathway as potential targets for engineering resistance to phenolic acids under anaerobic conditions, a subset of which we validated using precise gene deletions. Strikingly, this finding is specific to the cytochrome bc1 and cytochrome c pathway and does not extend to other branches of the electron transport chain. We further show that exposure of Z. mobilis to ferulic acid causes substantial remodeling of the cell envelope proteome, as well as the downregulation of TonB-dependent transporters. Our work provides a generalizable strategy for identifying high-value engineering targets from gene perturbation screens that is broadly applicable.

CRISPRi↗
NASA NTRS2010

Multi-Stage System for Automatic Target Recognition

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

Chao, Tien-Hsin↗