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At least 613 records · Page 34
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NASA NTRS2022

TruePAL – An AI Assistant for First Responder Safety

This paper presents the development of an AI assistant, Trusted and Explainable Artificial Intelligence for Saving Lives (TruePAL), to provide real-time warning of risks of potential crashes to the first responders. The TruePAL system employs an AI and deep learning technology for saving first responders and roadside crews lives in and around active traffic. A deep neural network (DNN) and a Non-Axiomatic Reasoning System (NARS) are implemented as an AI system. A mobile app with AI interface is developed to perform verbal communication with the first responders. The TruePAL team has developed an explainable AI approach by opening up the DNN blackbox to extract the activation filters of various features and parts of the targeted objects. The combination of DNN and NARS makes the TruePAL system explainable to the users. TruePAL ingests on-board cameras, radar, and other sensor signals, analyzes the environment and traffic patterns to generate timely warning to drivers and roadside crews to avoid crashes. The TruePAL team, in collaboration with the Miami/Dade Police Dept., has designed five use cases and multiple sub-scenarios in a CARLA driving simulator to test the capability of TruePAL in timely warning to the first responder drivers in potential crash scenarios. We have successfully demonstrated its capability of timely warning in over a dozen scenarios based on the use cases. The preliminary test simulation results show that TruePAL could provide the drivers and crew members advanced warning before a crash occurs.

Chow, Edward↗
NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗
NASA NTRS2015

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

As temperatures increase, the onset and severity of droughts is likely to become more intense. Improved tools for understanding, monitoring and predicting droughts will be a key component of 21st century climate adaption. The best drought monitoring systems will bring together accurate precipitation estimates with skillful climate and weather forecasts. Such systems combine the predictive power inherent in the current land surface state with the predictive power inherent in low frequency ocean-atmosphere dynamics. To this end, researchers at the Climate Hazards Group (CHG), in collaboration with partners at the USGS and NASA, have developed i) a long (1981-present) quasi-global (50degS-50degN, 180degW-180degE) high resolution (0.05deg) homogenous precipitation data set designed specifically for drought monitoring, ii) tools for understanding and predicting East African boreal spring droughts, and iii) an integrated land surface modeling (LSM) system that combines rainfall observations and predictions to provide effective drought early warning. This talk briefly describes these three components. Component 1: CHIRPS The Climate Hazards group InfraRed Precipitation with Stations (CHIRPS), blends station data with geostationary satellite observations to provide global near real time daily, pentadal and monthly precipitation estimates. We describe the CHIRPS algorithm and compare CHIRPS and other estimates to validation data. The CHIRPS is shown to have high correlation, low systematic errors (bias) and low mean absolute errors. Component 2: Hybrid statistical-dynamic forecast strategies East African droughts have increased in frequency, but become more predictable as Indo- Pacific SST gradients and Walker circulation disruptions intensify. We describe hybrid statistical-dynamic forecast strategies that are far superior to the raw output of coupled forecast models. These forecasts can be translated into probabilities that can be used to generate bootstrapped ensembles describing future climate conditions. Component 3: Assimilation using LSMs CHIRPS rainfall observations (component 1) and bootstrapped forecast ensembles (component 2) can be combined using LSMs to predict soil moisture deficits. We evaluate the skill such a system in East Africa, and demonstrate results for 2013.

Funk, Chris↗
NASA NTRS2003

Air Monitoring for Hazardous Gas Detection

The Hazardous Gas Detection Lab is involved in the design and development of instrumentation that can detect and quantify various hazardous gases. Traditionally these systems are designed for leak detection of the cryogenic gases used for the propulsion of the Shuttle and other vehicles. Mass spectrometers are the basis of these systems, which provide excellent quantitation, sensitivity, selectivity, response and limits of detection. Unfortunately, these systems are large, heavy and expensive. This feature limits the ability to perform gas analysis in certain applications. Smaller and lighter mass spectrometer systems could be used in many more applications primarily due to the portability of the system. Such applications would include air analysis in confined spaces, in-situ environmental analysis and emergency response. In general, system cost is lowered as size is reduced. With a low cost air analysis system, several systems could be utilized for monitoring large areas. These networked systems could be deployed at job-sites for worker safety, throughout a community for pollution warnings, or dispersed in a battlefield for early warning of chemical or biological threats. Presented will be information on the first prototype of this type of system. Included will be field trial data, with this prototype performing air analysis autonomously from an aircraft.

Arkin, C. Richard↗
NASA NTRS2017

An Unobtrusive System to Measure, Assess, and Predict Cognitive Workload in Real-World Environments

Across many careers, individuals face alternating periods of high and low attention and cognitive workload, which can result in impaired cognitive functioning and can be detrimental to job performance. For example, some professions (e.g., fire fighters, emergency medical personnel, doctors and nurses working in an emergency room, pilots) require long periods of low workload (boredom), followed by sudden, high-tempo operations during which they may be required to respond to an emergency and perform at peak cognitive levels. Conversely, other professions (e.g., air traffic controllers, market investors in financial industries, analysts) require long periods of high workload and multitasking during which the addition of just one more task results in cognitive overload resulting in mistakes. An unobtrusive system to measure, assess, and predict cognitive workload could warn individuals, their teammates, or their supervisors when steps should be taken to augment cognitive readiness. In this talk I will describe an approach to this problem that we have found to be successful across work domains including: (1) a suite of unobtrusive, field-ready neurophysiological, physiological, and behavioral sensors that are chosen to best suit the target environment; (2) custom algorithms and statistical techniques to process and time-align raw data originating from the sensor suite; (3) probabilistic and statistical models designed to interpret the data into the human state of interest (e.g., cognitive workload, attention, fatigue); (4) and machine-learning techniques to predict upcoming performance based on the current pattern of events, and (5) display of each piece of information depending on the needs of the target user who may or may not want to drill down into the functioning of the system to determine how conclusions about human state and performance are determined. I will then focus in on our experimental results from our custom functional near-infrared spectroscopy sensor, designed to operate in real-world environments to be worn comfortably (e.g., positioned into a baseball cap or a surgeons cap) to measure changes in brain blood oxygenation without adding burden to the individual being assessed.

workload collection↗
NASA NTRS1991

Weather Information Processing

Science Communications International (SCI), formerly General Science Corporation, has developed several commercial products based upon experience acquired as a NASA Contractor. Among them are METPRO, a meteorological data acquisition and processing system, which has been widely used, RISKPRO, an environmental assessment system, and MAPPRO, a geographic information system. METPRO software is used to collect weather data from satellites, ground-based observation systems and radio weather broadcasts to generate weather maps, enabling potential disaster areas to receive advance warning. GSC's initial work for NASA Goddard Space Flight Center resulted in METPAK, a weather satellite data analysis system. METPAK led to the commercial METPRO system. The company also provides data to other government agencies, U.S. embassies and foreign countries.

Source record↗
NASA NTRS1996

Detecting Faults In Helicopter Gearboxes By The MVIM Method

Multivalued influence-matrix (MVIM) method potential utility as theoretical basis of proposed automated monitoring systems detecting faults in helicopter gearboxes. Applied to recognize patterns in vibration measurements. Fault-recognition system required to operate continuously while helicopter airborne, analyzing measurements of vibrations for signs of trouble to provide real-time warning of any dangerous or potentially dangerous fault like cracked case or fractured gear tooth. System also required not to give false alarms to prevent unnecessary emergency landings.

Chin, Hsinyung↗
NASA NTRS2002

Runway Safety Monitor Algorithm for Runway Incursion Detection and Alerting

The Runway Safety Monitor (RSM) is an algorithm for runway incursion detection and alerting that was developed in support of NASA's Runway Incursion Prevention System (RIPS) research conducted under the NASA Aviation Safety Program's Synthetic Vision System element. The RSM algorithm provides pilots with enhanced situational awareness and warnings of runway incursions in sufficient time to take evasive action and avoid accidents during landings, takeoffs, or taxiing on the runway. The RSM currently runs as a component of the NASA Integrated Display System, an experimental avionics software system for terminal area and surface operations. However, the RSM algorithm can be implemented as a separate program to run on any aircraft with traffic data link capability. The report documents the RSM software and describes in detail how RSM performs runway incursion detection and alerting functions for NASA RIPS. The report also describes the RIPS flight tests conducted at the Dallas-Ft Worth International Airport (DFW) during September and October of 2000, and the RSM performance results and lessons learned from those flight tests.

Green, David F., Jr.↗
NASA NTRS1993

The detection and measurement of microburst wind shear by an airborne lidar system

The NASA Lockheed Missiles and Space Company (LMSC) Coherent Lidar Airborne Shear Sensor (CLASS) employs coherent lidar technology as a basis for a forward-looking predictive wind shear detection system. Line of sight wind velocities measured ahead of the aircraft are combined with aircraft state parameters to relate the measured wind change (or shear) ahead of an aircraft to its performance loss or gain. In this way the system can predict whether a shear detected ahead of the aircraft poses a significant threat to the aircraft and provide an advance warning to the flight crew. Installed aboard NASA's Boeing 737 research aircraft, the CLASS system is flown through convective microburst wind shears in Denver, Co., and Orlando, Fl. Some preliminary flight test results are presented. It is seen that the system was able to detect and measure wind shears ahead of the aircraft in the relatively dry Denver environment, but its performance was degraded in the high humidity and heavy rain in Orlando.

Robinson, Paul A.↗
NASA NTRS2004

Air System Information Management

I flew to Washington last week, a trip rich in distributed information management. Buying tickets, at the gate, in flight, landing and at the baggage claim, myriad messages about my reservation, the weather, our flight plans, gates, bags and so forth flew among a variety of travel agency, airline and Federal Aviation Administration (FAA) computers and personnel. By and large, each kind of information ran on a particular application, often specialized to own data formats and communications network. I went to Washington to attend an FAA meeting on System-Wide Information Management (SWIM) for the National Airspace System (NAS) (http://www.nasarchitecture.faa.gov/Tutorials/NAS101.cfm). NAS (and its information infrastructure, SWIM) is an attempt to bring greater regularity, efficiency and uniformity to the collection of stovepipe applications now used to manage air traffic. Current systems hold information about flight plans, flight trajectories, weather, air turbulence, current and forecast weather, radar summaries, hazardous condition warnings, airport and airspace capacity constraints, temporary flight restrictions, and so forth. Information moving among these stovepipe systems is usually mediated by people (for example, air traffic controllers) or single-purpose applications. People, whose intelligence is critical for difficult tasks and unusual circumstances, are not as efficient as computers for tasks that can be automated. Better information sharing can lead to higher system capacity, more efficient utilization and safer operations. Better information sharing through greater automation is possible though not necessarily easy.

Filman, Robert E.↗
NASA NTRS1989

Performance of Lempel-Ziv compressors with deferred innovation

The noiseless data-compression algorithms introduced by Lempel and Ziv (LZ) parse an input data string into successive substrings each consisting of two parts: The citation, which is the longest prefix that has appeared earlier in the input, and the innovation, which is the symbol immediately following the citation. In extremal versions of the LZ algorithm the citation may have begun anywhere in the input; in incremental versions it must have begun at a previous parse position. Originally the citation and the innovation were encoded, either individually or jointly, into an output word to be transmitted or stored. Subsequently, it was speculated that the cost of this encoding may be excessively high because the innovation contributes roughly 1g(A) bits, where A is the size of the input alphabet, regardless of the compressibility of the source. To remedy this excess, it was suggested to store the parsed substring as usual, but encoding for output only the citation, leaving the innovation to be encoded as the first symbol of the next substring. Being thus included in the next substring, the innovation can participate in whatever compression that substring enjoys. This strategy is called deferred innovation. It is exemplified in the algorithm described by Welch and implemented in the C program compress that has widely displaced adaptive Huffman coding (compact) as a UNIX system utility. The excessive expansion is explained, an implicit warning is given against using the deferred innovation compressors on nearly incompressible data.

Cohn, Martin↗
NASA NTRS1999

A Flight/Ground/Test Event Logging Facility

The onboard control software for spacecraft such as Mars Pathfinder and Cassini is composed of many subsystems including executive control, navigation, attitude control, imaging, data management, and telecommunications. The software in all of these subsystems needs to be instrumented for several purposes: to report required telemetry data, to report warning and error events, to verify internal behavior during system testing, and to provide ground operators with detailed data when investigating in-flight anomalies. Events can range in importance from purely informational events to major errors. It is desirable to provide a uniform mechanism for reporting such events and controlling their subsequent processing. Since radiation-hardened flight processors are several years behind the speed and memory of their commercial cousins, and since most subsystems require real-time control, and since downlink rates to earth can be very low from deep space, there are limits to how much of the data can be saved and transmitted. Some kinds of events are more important than others and should therefore be preferentially retained when memory is low. Some faults can cause an event to recur at a high rate, but this must not be allowed to consume the memory pool. Some event occurrences may be of low importance when reported but suddenly become more important when a subsequent error event gets reported. Some events may be so low-level that they need not be saved and reported unless specifically requested by ground operators.

Dvorak, Daniel↗
NASA NTRS1999

Assessment of Selected CERES Electronic Component Survivability under Simulated Overvoltage Conditions

In August, 1998 a Clouds and the Earth's Radiant Energy System (CERES) instrument telemetry housekeeping parameter generated a yellow warning message that indicated an on-board + 15V Data Acquisition Assembly (DAA) power converter deregulation anomaly. An exhaustive investigation was undertaken to understand this anomaly and the long-term consequences which have severely reduced CERES operations on the Tropical Rainfall Measuring Mission (TRMM) spacecraft. Among investigations performed were ground tests that approximated the on-board electronic circuitry using a small quantity of flight identical components exposed to maximum spacecraft bus over-voltage conditions. These components include monolithic integrated microcircuits that perform analog signal conditioning on instrument sensor signals and an analog- to-digital converter (ADC) for the entire DAA. All microcircuit packages have either a bipolar silicon design with internal current limiting protections or have a complementary metal oxide semiconductor (CMOS) design with bias protections. Ground tests that have been running for approximately 8 months have indicated that these components are capable of withstanding as much as twice their input supply voltage ratings without noticeable performance degradation. These data provide CERES operators with confidence of being able to continue science operations over the remaining life of the TRMM mission. This paper will discuss this anomaly and some possible causes, a simulator of affected electronics, test results, prognosis for future CERES operations, and conclusions.

Chapman, John J.↗
NASA NTRS2007

Array Phase Shifters: Theory and Technology

While there are a myriad of applications for microwave phase shifters in instrumentation and metrology, power combining, amplifier linearization, and so on, the most prevalent use is in scanning phased-array antennas. And while this market continues to be dominated by military radar and tracking platforms, many commercial applications have emerged in the past decade or so. These new and potential applications span low-Earth-orbit (LEO) communications satellite constellations and collision warning radar, an aspect of the Intelligent Vehicle Highway System or Automated Highway System. In any case, the phase shifters represent a considerable portion of the overall antenna cost, with some estimates approaching 40 percent for receive arrays. Ferrite phase shifters continue to be the workhorse in military-phased arrays, and while there have been advances in thin film ferrite devices, the review of this device technology in the previous edition of this book is still highly relevant. This chapter will focus on three types of phase shifters that have matured in the past decade: GaAs MESFET monolithic microwave integrated circuit (MMIC), micro-electromechanical systems (MEMS), and thin film ferroelectric-based devices. A brief review of some novel devices including thin film ferrite phase shifters and superconducting switches for phase shifter applications will be provided. Finally, the effects of modulo 2 phase shift limitations, phase errors, and transient response on bit error rate degradation will be considered.

Romanofsky, Robert R.↗
NASA NTRS2012

Design of Spacecraft Missions to Test Kinetic Impact for Asteroid Deflection

Earth has previously been struck with devastating force by near-Earth asteroids (NEAs) and will be struck again. Telescopic search programs aim to provide advance warning of such an impact, but no techniques or systems have yet been tested for deflecting an incoming NEA. To begin addressing this problem, we have analyzed the more than 8000 currently known NEAs to identify those that offer opportunities for safe and meaningful near-term tests of the proposed kinetic impact asteroid deflection technique. In this paper we present our methodology and results, including complete mission designs for the best kinetic impactor test mission opportunities.

Barbee, Brent W.↗
NASA NTRS2002

NASA Runway Incursion Prevention System (RIPS) Dallas-Fort Worth Demonstration Performance Analysis

NASA's Aviation Safety Program Synthetic Vision System project conducted a Runway Incursion Prevention System (RIPS) flight test at the Dallas-Fort Worth International Airport in October 2000. The RIPS research system includes advanced displays, airport surveillance system, data links, positioning system, and alerting algorithms to provide pilots with enhanced situational awareness, supplemental guidance cues, a real-time display of traffic information, and warnings of runway incursions. This report describes the aircraft and ground based runway incursion alerting systems and traffic positioning systems (Automatic Dependent Surveillance - Broadcast (ADS-B) and Traffic Information Service - Broadcast (TIS-B)). A performance analysis of these systems is also presented.

Cassell, Rick↗
NASA NTRS1979

Satellite communications for disaster relief operations

The use of communication satellite systems to provide assistance in disaster relief operations on a global basis is presented. Disaster problem phases such as detection, warning, and relief; requirements for the communication capability including remote data collection, imaging and voice broadcast; and the global disaster network are discussed. Utilization of Intelsat and Marisat systems and the size and type of ground terminals required for satellite access is considered, and estimates of communication requirements for a global system and of costs for satellite services to support relief operations are given. NASA disaster related activities including studies of direct-to-home disaster warning and determination of disaster response times are described, and it is concluded that existing international satellite communication systems offer real potential for the establishment of a reliable and flexible network devoted to disaster related communication services.

Sivo, J. N.↗
NASA NTRS2010

The Geostationary Lighting Mapper (GLM) for GOES-R: A New Operational Capability to Improve Storm Forecasts and Warnings

The next generation Geostationary Operational Environmental Satellite (GOES-R) series is a follow on to the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved spectral (3x), spatial (4x), and temporal (5x) resolution for the Advanced Baseline Imager (ABI). The GLM, an optical transient detector and imager operating in the near-IR at 777.4 nm will map all (in-cloud and cloud-to-ground) lighting flashes continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions, from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) national centers and forecast offices via the GOES-R Proving Ground to help improve our understanding of the application of these data in operational settings and facilitate Day-1 user readiness for this new capability.

Goodman, Steven J.↗