Results for “Alert” — Page 8

NASA NTRS2015

Cockpit Interfaces, Displays, and Alerting Messages for the Interval Management Alternative Clearances (IMAC) Experiment

This document describes the IM cockpit interfaces, displays, and alerting capabilities that were developed for and used in the IMAC experiment, which was conducted at NASA Langley in the summer of 2015. Specifically, this document includes: (1) screen layouts for each page of the interface; (2) step-by-step instructions for data entry, data verification and input error correction; (3) algorithm state messages and error condition alerting messages; (4) aircraft speed guidance and deviation indications; and (5) graphical display of the spatial relationships between the Ownship aircraft and the Target aircraft. The controller displays for IM will be described in a separate document.

Baxley, Brian T.↗

NASA NTRS2015

System and Method for Providing Model-Based Alerting of Spatial Disorientation to a Pilot

A system and method monitor aircraft state parameters, for example, aircraft movement and flight parameters, applies those inputs to a spatial disorientation model, and makes a prediction of when pilot may become spatially disoriented. Once the system predicts a potentially disoriented pilot, the sensitivity for alerting the pilot to conditions exceeding a threshold can be increased and allow for an earlier alert to mitigate the possibility of an incorrect control input.

Conner, Kevin J↗

NASA NTRS2015

DAIDALUS: Detect and Avoid Alerting Logic for Unmanned Systems

This paper presents DAIDALUS (Detect and Avoid Alerting Logic for Unmanned Systems), a reference implementation of a detect and avoid concept intended to support the integration of Unmanned Aircraft Systems into civil airspace. DAIDALUS consists of self-separation and alerting algorithms that provide situational awareness to UAS remote pilots. These algorithms have been formally specified in a mathematical notation and verified for correctness in an interactive theorem prover. The software implementation has been verified against the formal models and validated against multiple stressing cases jointly developed by the US Air Force Research Laboratory, MIT Lincoln Laboratory, and NASA. The DAIDALUS reference implementation is currently under consideration for inclusion in the appendices to the Minimum Operational Performance Standards for Unmanned Aircraft Systems presently being developed by RTCA Special Committee 228.

Munoz, Cesar↗

NASA NTRS2017

The Effects of Primary Light Sources on Worker Performance and Alertness

Traditional office buildings use a variety of primary light sources (e.g., LED/fluorescent lights). As interest in LEED certified office buildings increase and research has shown that enhanced lighting design improves human performance and alertness (Viola et al., 2008; Juslén & Tenner, 2005; Edwards & Torcellini, 2002), more office buildings are incorporating a daylighting design. We investigated the differences between employee performance and alertness in two different building types (daylight vs. artificial light). We hypothesized that employee performance and sleep duration would be improved in a building designed to increase exposure to natural daylight compared to traditional office settings.

cognitive performance↗

NASA NTRS2020

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

UAS↗

NASA NTRSDate not supplied

Alert Timing Assessment for Unmanned Aircraft System Terminal Area Operations

A Detect and Avoid (DAA) system is an essential enabler for integrating Unmanned Aircraft Systems (UAS) into the U.S. National Airspace System. A DAA system uses a suite of sensors, trackers and alerting and guidance algorithms to assist a remote pilot in maintaining separation from airborne traffic. The initial minimum performance standards focused on en route operations; in order to facilitate operations in and around the airport environment, this paper presents the derivation of the early alert threshold for UAS terminal operations.

Unmanned Aircraft Systems↗

NASA NTRSDate not supplied

UAS Pilot Assessments of Display and Alerting for the Airborne Collision Avoidance System XU

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗

NASA NTRS2020

UAS Pilot Assessments of Display and Alerting for the Next Generation Airborne Avoidance System

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗

NASA NTRSDate not supplied

UAS Pilot Assessments of Display and Alerting for the Next Generation Airborne Collision Avoidance System Xu

Unmanned aircraft systems (UAS) must comply with specific standards to operate in the National Airspace System (NAS). Among the requirements are the detect and avoid (DAA) capabilities, which include display, alerting, and guidance specifications. Previous studies have queried pilots for their subjective feedback on these display elements on earlier systems; the present study sought pilot evaluations with an initial iteration of the unmanned variant of a Next Generation Airborne Collision Avoidance System (ACAS XU). Sixteen participants piloted simulated aircraft with both standalone and integrated DAA displays. Their opinions were gathered using post-block and post-simulation questionnaires as well as guided debriefs. The data showed pilots had better understanding and comfort with the system when using an integrated display. Pilots also rated ACAS Xu alerting and guidance as generally acceptable and effective. Implications for further development of ACAS XU and DAA displays are discussed.

unmanned aircraft systems↗

DOE OSTI2015

Rapid deployable global sensing hazard alert system

A rapid deployable global sensing hazard alert system and associated methods of operation are provided. An exemplary system includes a central command, a wireless backhaul network, and a remote monitoring unit. The remote monitoring unit can include a positioning system configured to determine a position of the remote monitoring unit based on one or more signals received from one or more satellites located in Low Earth Orbit. The wireless backhaul network can provide bidirectional communication capability independent of cellular telecommunication networks and the Internet. An exemplary method includes instructing at least one of a plurality of remote monitoring units to provide an alert based at least in part on a location of a hazard and a plurality of positions respectively associated with the plurality of remote monitoring units.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

DisasterAWARE – A Global Alerting Platform for Flood Events

The rising number of flooding events combined with increased urbanization is contributing to significant economic losses due to damages to structures and infrastructures. From a risk reduction and resilience perspective, it is not only essential to forecast flood risk and potential impacts, but also to disseminate the information to stakeholders on the ground for rapid implementation of mitigation and response measures. This paper provides (i) an introduction to DisasterAWARE®, a global alerting system, that is used to disseminate flood risk information to stakeholders across the globe, and (ii) a discussion of the models implemented using earth observation data (Synthetic Aperture Radar and optical imagery) for near real-time assessment of flood severity and potential flood impacts to infrastructures. While the models are still in their nascent stage, a case study implementation of the models for the 2020 flooding event in Africa is presented to showcase the model integration with DisasterAWARE®.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

The IceCube realtime alert system

Although high-energy astrophysical neutrinos were discovered in 2013, their origin is still unknown. Aiming for the identification of an electromagnetic counterpart of a rapidly fading source, we have implemented a realtime analysis framework for the IceCube neutrino observatory. Several analyses selecting neutrinos of astrophysical origin are now operating in realtime at the detector site in Antarctica and are producing alerts for the community to enable rapid follow-up observations. The goal of these observations is to locate the astrophysical objects responsible for these neutrino signals. This paper highlights the infrastructure in place both at the South Pole site and at IceCube facilities in the north that have enabled this fast follow-up program to be implemented. Additionally, this paper presents the first realtime analyses to be activated within this framework, highlights their sensitivities to astrophysical neutrinos and background event rates, and presents an outlook for future discoveries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Design of COVID-19 staged alert systems to ensure healthcare capacity with minimal closures

Community mitigation strategies to combat COVID-19, ranging from healthy hygiene to shelter-in-place orders, exact substantial socioeconomic costs. Judicious implementation and relaxation of restrictions amplify their public health benefits while reducing costs. We derive optimal strategies for toggling between mitigation stages using daily COVID-19 hospital admissions. With public compliance, the policy triggers ensure adequate intensive care unit capacity with high probability while minimizing the duration of strict mitigation measures. In comparison, we show that other sensible COVID-19 staging policies, including France’s ICU-based thresholds and a widely adopted indicator for reopening schools and businesses, require overly restrictive measures or trigger strict stages too late to avert catastrophic surges. As proof-of-concept, we describe the optimization and maintenance of the staged alert system that has guided COVID-19 policy in a large US city (Austin, Texas) since May 2020. As cities worldwide face future pandemic waves, our findings provide a robust strategy for tracking COVID-19 hospital admissions as an early indicator of hospital surges and enacting staged measures to ensure integrity of the health system, safety of the health workforce, and public confidence.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2013

Superorbital periodic modulation in wind-accretion high-mass X-ray binaries from swift burst alert telescope observations

We report the discovery using data from the Swift-Burst Alert Telescope (BAT) of superorbital modulation in the wind-accretion supergiant high-mass X-ray binaries 4U 1909+07 (= X 1908+075), IGR J16418–4532, and IGR J16479–4514. Together with already known superorbital periodicities in 2S 0114+650 and IGR J16493–4348, the systems exhibit a monotonic relationship between superorbital and orbital periods. These systems include both supergiant fast X-ray transients and classical supergiant systems, and have a range of inclination angles. This suggests an underlying physical mechanism which is connected to the orbital period. In addition to these sources with clear detections of superorbital periods, IGR J16393–4643 (= AX J16390.4–4642) is identified as a system that may have superorbital modulation due to the coincidence of low-amplitude peaks in power spectra derived from BAT, Rossi X-Ray Timing Explorer Proportional Counter Array, and International Gamma-Ray Astrophysics Laboratory light curves. 1E 1145.1–6141 may also be worthy of further attention due to the amount of low-frequency modulation of its light curve. However, we find that the presence of superorbital modulation is not a universal feature of wind-accretion supergiant X-ray binaries.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Herschel far-infrared photometry of the swift burst alert telescope active galactic nuclei sample of the local universe. I. PACS observations

Far-Infrared (FIR) photometry from the Photodetector Array Camera and Spectrometer on the Herschel Space Observatory is presented for 313 nearby, hard X-ray selected galaxies from the 58 month Swift Burst Alert Telescope (BAT) Active Galactic Nuclei catalog. The present data do not distinguish between the FIR luminosity distributions at 70 and 160 μm for Seyfert 1 and Seyfert 2 galaxies. This result suggests that if the FIR emission is from the nuclear obscuring material surrounding the accretion disk, then it emits isotropically, independent of orientation. Alternatively, a significant fraction of the 70 and 160 μm luminosity could be from star formation, independent of active galactic nucleus (AGN) type. Using a non-parametric test for partial correlation with censored data, we find a statistically significant correlation between the AGN intrinsic power (in the 14-195 keV band) and the FIR emission at 70 and 160 μm for Seyfert 1 galaxies. We find no correlation between the 14-195 keV and FIR luminosities in Seyfert 2 galaxies. The observed correlations suggest two possible scenarios: (1) if we assume that the FIR luminosity is a good tracer of star formation, then there is a connection between star formation and the AGN at sub-kiloparsec scales, or (2) dust heated by the AGN has a statistically significant contribution to the FIR emission. Using a Spearman rank-order analysis, the 14-195 keV luminosities for the Seyfert 1 and 2 galaxies are weakly statistically correlated with the F {sub 70}/F {sub 160} ratios.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

A Morphological Model to Separate Resolved–Unresolved Sources in the DESI Legacy Surveys: Application in the LS4 Alert Stream

Separating resolved and unresolved sources in large imaging surveys is a fundamental step to enable downstream science, such as searching for extragalactic transients in wide-field time-domain surveys. Here we present our method to effectively separate point sources from the resolved, extended sources in the Dark Energy Spectroscopic Instrument (DESI) Legacy Surveys (LS). We develop a supervised machine learning model based on the Gradient Boosting algorithm XGBoost. The features input to the model are purely morphological and are derived from the tabulated LS data products. We train the model using ∼2 × 10 5 LS sources in the COSMOS field with HST morphological labels and evaluate the model performance on LS sources with spectroscopic classification from the DESI Data Release 1 (∼2 × 10 7 objects) and the Sloan Digital Sky Survey Data Release 17 (∼3 × 10 6 objects), as well as on ∼2 × 10 8 Gaia stars. A significant fraction of LS sources are not observed in every LS filter, and we therefore build a “Hybrid” model as a linear combination of two XGBoost models, each containing features combining aperture flux measurements from the “blue” (gr) and “red” (iz) filters. The Hybrid model shows a reasonable balance between sensitivity and robustness, and achieves higher accuracy and flexibility compared to the LS morphological typing. With the Hybrid model, we provide classification scores for ∼3 × 10 9 LS sources, making this the largest ever machine learning catalog separating resolved and unresolved sources. The catalog has been incorporated into the real-time pipeline of the La Silla Schmidt Southern Survey (LS4), enabling the identification of extragalactic transients within the LS4 alert stream.

astrostatistics↗

DOE OSTI2018

ALERT AATR Final Report: Lawrence Livermore National Laboratory

This report addresses the problem of automatically recognizing objects of interest (OOIs) in x-ray computed tomography (CT) images of baggage (plastic bins in our case). The discussion draws heavily from the material in [1]. The material composition and basic physical features of interest (FOIs, such as mass and thickness) of the OOIs are defined in an object requirement specification (ORS). The ORS may also provide a detection – false alarm probability goal for each material of interest (MOI). Automatic threat recognition (ATR) systems identify CT images of baggage that contain OOIs. ATRs must also identify locations of OOIs within baggage. The current ATR certification process used by DHS requires the ATR hardware and software to be certified on a specific ORS. When the ORS changes, the ATR hardware and software must be recertified. To pass re-certification, the hardware, algorithms and codes may need to be modified. Because ATR-based certification and re-certification are so time-consuming, the current process cannot quickly adapt to changing requirements. Unlike ATRs, adaptive automatic threat recognition (AATR) systems can quickly adapt to an ORS that changes or evolves over time [2]. The proposed AATR-based certification process would require the AATR hardware and software to be certified on a specific baseline ORS. Once certified, the same AATR hardware, algorithms and codes would be applied (by TSA or its delegates) to any ORS supplied in the future as input without going through lengthy recertification. This proposed process would enable the AATR to quickly adapt to changing requirements. This report describes the AATR developed at the Lawrence Livermore National Laboratory (LLNL) for x-ray CT images of baggage. The need and technical requirements for an AATR were developed in collaboration with DHS’s Explosives Division and Northeastern University’s Awareness and Localization of Explosives-Related Threats (ALERT) Center, a DHS Center of Excellence (http://www.northeastern.edu/alert/).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

Deep Learning Based Approach to Integrate MyShake's Trigger Data with ShakeAlert for Faster and Robust EEW Alerts

Earthquake Early Warning (EEW) systems depend on the dense seismic network to make fast and accurate earthquake detections to issue useful early alerts. The recent development and implementation of the ShakeAlert system is relying on the west coast seismic network to detect and estimate the earthquake parameters in real-time. While working on making improvements on the current system, one potential approach is to include more seismic recordings from various sources, such as the low-cost smartphone seismic network, such as the MyShake network, or the Google Android smartphones, since these smartphone seismic networks have much more portable stations (phones) to potentially provide useful data to the system. This report summarizes the initial exploration of using a deep learning approach to combine the data from both traditional seismic stations and the smartphone data in California. Due to the heterogeneity nature of the data, we aggregate data from the phones (using simulation data), as well as that from traditional seismic stations to grid cells. By generating real-time triggering ratio grid cell maps, the designed deep learning algorithm can process the data from multiple sources and detect the earthquake faster than only using that from a traditional seismic network.

58 GEOSCIENCES↗