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In situ detection of tropospheric OH, HO2, NO2, and NO by laser-induced fluorescence in detection chambers at reduced pressures

This report is a brief summary of the status of work on the grant entitled 'In situ detection of tropospheric OH, HO2, NO2, and NO by laser induced fluorescence in detection chambers at low pressures'. The first version of the instrument is essentially complete and operational for about six months, and we continue to make improvements on the instrument sensitivity and reliability. We are focusing our efforts on improving our understanding of the operating characteristics of the instrument - particularly the inlet transmission for OH and HO2, the exact character of the air flow around and within the instrument, and the efficiency of the chemical conversion of HO2 to OH. We are also in the process of converting this laboratory instrument into a field worthy instrument that we can take to remote sites for measurements.

Brune, William H.

NASA airborne radar wind shear detection algorithm and the detection of wet microbursts in the vicinity of Orlando, Florida

The algorithms used in the NASA experimental wind shear radar system for detection, characterization, and determination of windshear hazard are discussed. The performance of the algorithms in the detection of wet microbursts near Orlando is presented. Various suggested algorithms that are currently being evaluated using the flight test results from Denver and Orlando are reviewed.

Britt, Charles L.

In situ detection of tropospheric OH, HO2, NO2, and NO by laser-induced fluorescence in detection chambers at reduced pressures

This report is a brief summary of the status of work on the grant entitled 'In situ detection of tropospheric OH, HO2, NO2, and NO by laser induced fluorescence in detection chambers at low pressures.' The basic instrument characteristics have been established, and have been reported in a manuscript, included as an appendix to this report, that has been accepted by the Journal of Geophysical Research. Currently, two efforts are under way. First, instrument tests and calibrations are continuing. These efforts include field measurements and an informal inter comparison in Colorado last August and September. Second, new technologies in lasers and detectors are being implemented to make the instrument smaller, lighter, and more energy efficient. Such instrument modifications are essential for measurements from aircraft, high scaffolding in forests, and ships.

Brune, William H.

Detection of Deforestation and Land Conversion in Rondonia, Brazil Using Change Detection Techniques

Fires associated with tropical deforestation, land conversion, and land use greatly contribute to emissions as well as the depletion of carbon and nutrient pools. The objective of this research was to compare change detection techniques for identifying deforestation and cattle pasture formation during a period of early colonization and agricultural expansion in the vicinity of Jamari, Rond6nia. Multi-date Landsat Thematic Mapper (TM) data between 1984 and 1992 was examined in a 94 370-ha area of active deforestation to map land cover change. The Tasseled Cap (TC) transformation was used to enhance the contrast between forest, cleared areas, and regrowth. TC images were stacked into a composite multi-date TC and used in a principal components (PC) transformation to identify change components. In addition, consecutive TC image pairs were differenced and stacked into a composite multi-date differenced image. A maximum likelihood classification of each image composite was compared for identification of land cover change. The multi-date TC composite classification had the best accuracy of 78.1% (kappa). By 1984, only 5% of the study area had been cleared, but by 1992, 11% of the area had been deforested, primarily for pasture and 7% lost due to hydroelectric dam flooding. Finally, discrimination of pasture versus cultivation was improved due to the ability to detect land under sustained clearing opened to land exhibiting regrowth with infrequent clearing.

Guild, Liane S.

Searches for new interstellar molecules, including a tentative detection of aziridine and a possible detection of propenal

Rotational spectroscopy at millimeter wavelengths is a powerful means of investigating the chemistry of dense interstellar clouds. These regions can exhibit an interesting complement of gas phase molecules, including relatively complex organics. Here we report the tentative first astronomical detection of aziridine (ethylenimine), the possible detection of propenal (acrolein), and upper limits on the abundances of cyclopropenone, furan, hydroxyethanal (glycolaldehyde), thiohydroxylamine (NH2SH), and ethenol (vinyl alcohol) in various interstellar clouds.

Acrolein/analysis

Detection and Modeling of High-Dimensional Thresholds for Fault Detection and Diagnosis

Many Fault Detection and Diagnosis (FDD) systems use discrete models for detection and reasoning. To obtain categorical values like oil pressure too high, analog sensor values need to be discretized using a suitablethreshold. Time series of analog and discrete sensor readings are processed and discretized as they come in. This task isusually performed by the wrapper code'' of the FDD system, together with signal preprocessing and filtering. In practice,selecting the right threshold is very difficult, because it heavily influences the quality of diagnosis. If a threshold causesthe alarm trigger even in nominal situations, false alarms will be the consequence. On the other hand, if threshold settingdoes not trigger in case of an off-nominal condition, important alarms might be missed, potentially causing hazardoussituations. In this paper, we will in detail describe the underlying statistical modeling techniques and algorithm as well as the Bayesian method for selecting the most likely shape and its parameters. Our approach will be illustrated by several examples from the Aerospace domain.

Computer Systems

Kepler Planet Detection Metrics: Pixel-Level Transit Injection Tests of Pipeline Detection Efficiency for Data Release 25

This document describes the results of the fourth pixel-level transit injection experiment, which was designed to measure the detection efficiency of both the Kepler pipeline (Jenkins 2002, 2010; Jenkins et al. 2017) and the Robovetter (Coughlin 2017). Previous transit injection experiments are described in Christiansen et al. (2013, 2015a,b, 2016).In order to calculate planet occurrence rates using a given Kepler planet catalogue, produced with a given version of the Kepler pipeline, we need to know the detection efficiency of that pipeline. This can be empirically determined by injecting a suite of simulated transit signals into the Kepler data, processing the data through the pipeline, and examining the distribution of successfully recovered transits. This document describes the results for the pixel-level transit injection experiment performed to accompany the final Q1-Q17 Data Release 25 (DR25) catalogue (Thompson et al. 2017)of the Kepler Objects of Interest. The catalogue was generated using the SOC pipeline version 9.3 and the DR25 Robovetter acting on the uniformly processed Q1-Q17 DR25 light curves (Thompson et al. 2016a) and assuming the Q1-Q17 DR25 Kepler stellar properties (Mathur et al. 2017).

Pixel-Level Transit Injection

Unmanned Aircraft Systems (UAS) and Light Detection and Ranging (LiDAR)/Camera Technologies to Detect Avian Events and Other Environmental Measures at Utility- Scale Power Plants (Final Report)

The goal of this project was to develop and validate two complementary, cost-effective remote sensing technologies to monitor avian fatalities at utility-scale solar facilities: fixed platform (Animal Activity Monitoring-AAM) and aerial-based (Uncrewed Aircraft Systems-UAS). This project used these features with machine learning to automate the detection of avian carcasses and nests at solar facilities.

14 SOLAR ENERGY

BOS Gas Detection Pipeline (Integrated System for Optical Hydrogen Detection Using Background Oriented Schlieren and Machine Learning) [SWR-26-007]

This software is the world's first integrated background oriented schlieren and machine learning-based leak detection system. The system provides real time visualization of gas leaks and machine learning interpenetration of leak severity. The software is supplemented by SWR-25-177, "gpu_piv (Graphics Processing Unit Accelerated Background Oriented Schlieren Algorithm", also developed by the National Laboratory of the Rockies. SEE DOECODE ID 182832.

Palin, Ian [National Laboratory of the Rockies (NL

Detectability of Varied Hybridization Scenarios Using Genome-Scale Hybrid Detection Methods

Hybridization events complicate the accurate reconstruction of phylogenies, as they lead to patterns of genetic heritability that are unexpected under traditional, bifurcating models of species trees. This phenomenon has led to the development of methods to infer these varied hybridization events, both methods that reconstruct networks directly, as well as summary methods that predict individual hybridization events from a subset of taxa. However, a lack of empirical comparisons between methods – especially those pertaining to large networks with varied hybridization scenarios – hinders their practical use. Here, we provide a comprehensive review of popular summary methods: TICR, MSCquartets, HyDe, Patterson’s D-Statistic (ABBA-BABA), D3, and Dp. TICR and MSCquartets are based on quartet concordance factors gathered from gene tree topologies and HyDe, Patterson’s D-Statistic, D3, and Dp use site pattern frequencies to identify hybridization events between sets of three taxa. We then use simulated data to address questions of method accuracy and ideal use scenarios by testing methods against complex networks which depict gene flow events that differ in depth (timing), quantity (single vs. multiple, overlapping hybridizations), and rate of gene flow (γ). We find that deeper or multiple hybridization events may introduce noise and weaken the signal of hybridization, leading to higher relative false negative rates across all methods. Despite some forms of hybridization eluding quartet-based detection methods, MSCquartets displays high precision in most scenarios. While HyDe results in high false negative rates when tested on hybridizations involving extinct or unsampled ghost lineages, HyDe is the only method able to identify the direction of hybridization, distinguishing the source parental lineages from recipient hybrid lineages. Lastly, we test the methods on a dataset of ultraconserved elements from the bee subfamily Nomiinae, finding possible hybridization events between clades which correspond to regions of poor support in the species tree estimated in a previous study.

Bjorner, Marianne B.

Near optimum delay-line detection filters for serial detection of MSK signals

A method for designing transversal delay-line filter approximations to the matched filter for the serial detection of minimum-shift keyed (MSK) modulated signals is given. Two configurations are characterized in terms of signal-to-noise ratio degradation at a bit error rate (BER) of 10 to the -6th. One is shown to depart less than 0.3 dB from the ideal matched filter performance when its parameter values are optimized. A lumped-element equivalent is also given and shown to provide a degradation of less than 0.4 dB at a BER of 10 to the -6th

Ziemer, R. E.

A Feasibility Study for Perioperative Ventricular Tachycardia Prognosis and Detection and Noise Detection Using a Neural Network and Predictive Linear Operators

To locate the accessory pathway(s) in preexicitation syndromes, epicardial and endocardial ventricular mapping is performed during anterograde ventricular activation via accessory pathway(s) from data originally received in signal form. As the number of channels increases, it is pertinent that more automated detection of coherent/incoherent signals is achieved as well as the prediction and prognosis of ventricular tachywardia (VT). Today's computers and computer program algorithms are not good in simple perceptual tasks such as recognizing a pattern or identifying a sound. This discrepancy, among other things, has been a major motivating factor in developing brain-based, massively parallel computing architectures. Neural net paradigms have proven to be effective at pattern recognition tasks. In signal processing, the picking of coherent/incoherent signals represents a pattern recognition task for computer systems. The picking of signals representing the onset ot VT also represents such a computer task. We attacked this problem by defining four signal attributes for each potential first maximal arrival peak and one signal attribute over the entire signal as input to a back propagation neural network. One attribute was the predicted amplitude value after the maximum amplitude over a data window. Then, by using a set of known (user selected) coherent/incoherent signals, and signals representing the onset of VT, we trained the back propagation network to recognize coherent/incoherent signals, and signals indicating the onset of VT. Since our output scheme involves a true or false decision, and since the output unit computes values between 0 and 1, we used a Fuzzy Arithmetic approach to classify data as coherent/incoherent signals. Furthermore, a Mean-Square Error Analysis was used to determine system stability. The neural net based picking coherent/incoherent signal system achieved high accuracy on picking coherent/incoherent signals on different patients. The system also achieved a high accuracy of picking signals which represent the onset of VT, that is, VT immediately followed these signals. A special binary representation of the input and output data allowed the neural network to train very rapidly as compared to another standard decimal or normalized representations of the data.

Moebes, T. A.

Kepler Planet Detection Metrics: Automatic Detection of Background Objects Using the Centroid Robovetter

We present an automated method of identifying background eclipsing binaries masquerading as planet candidates in the Kepler planet candidate catalogs. We codify the manual vetting process for Kepler Objects of Interest (KOIs) described in Bryson et al. (2013) with a series of measurements and tests that can be performed algorithmically. We compare our automated results with a sample of manually vetted KOIs from the catalog of Burke et al. (2014) and find excellent agreement. We test the performance on a set of simulated transits and find our algorithm correctly identifies simulated false positives approximately 50 of the time, and correctly identifies 99 of simulated planet candidates.

Centroid