Engineering topics

McIntosh, Dawn M.

Publications and source records attributed to McIntosh, Dawn M..

6 records

NASA NTRS2006

SSRL Emergency Response Shore Tool

The SSRL Emergency Response Shore Tool (wherein SSRL signifies Smart Systems Research Laboratory ) is a computer program within a system of communication and mobile-computing software and hardware being developed to increase the situational awareness of first responders at building collapses. This program is intended for use mainly in planning and constructing shores to stabilize partially collapsed structures. The program consists of client and server components, runs in the Windows operating system on commercial off-the-shelf portable computers, and can utilize such additional hardware as digital cameras and Global Positioning System devices. A first responder can enter directly, into a portable computer running this program, the dimensions of a required shore. The shore dimensions, plus an optional digital photograph of the shore site, can then be uploaded via a wireless network to a server. Once on the server, the shore report is time-stamped and made available on similarly equipped portable computers carried by other first responders, including shore wood cutters and an incident commander. The staff in a command center can use the shore reports and photographs to monitor progress and to consult with structural engineers to assess whether a building is in imminent danger of further collapse.

Mah, Robert W.↗

NASA NTRS2006

Enabling the Discovery of Recurring Anomalies in Aerospace System Problem Reports using High-Dimensional Clustering Techniques

This paper describes the results of a significant research and development effort conducted at NASA Ames Research Center to develop new text mining techniques to discover anomalies in free-text reports regarding system health and safety of two aerospace systems. We discuss two problems of significant importance in the aviation industry. The first problem is that of automatic anomaly discovery about an aerospace system through the analysis of tens of thousands of free-text problem reports that are written about the system. The second problem that we address is that of automatic discovery of recurring anomalies, i.e., anomalies that may be described m different ways by different authors, at varying times and under varying conditions, but that are truly about the same part of the system. The intent of recurring anomaly identification is to determine project or system weakness or high-risk issues. The discovery of recurring anomalies is a key goal in building safe, reliable, and cost-effective aerospace systems. We address the anomaly discovery problem on thousands of free-text reports using two strategies: (1) as an unsupervised learning problem where an algorithm takes free-text reports as input and automatically groups them into different bins, where each bin corresponds to a different unknown anomaly category; and (2) as a supervised learning problem where the algorithm classifies the free-text reports into one of a number of known anomaly categories. We then discuss the application of these methods to the problem of discovering recurring anomalies. In fact the special nature of recurring anomalies (very small cluster sizes) requires incorporating new methods and measures to enhance the original approach for anomaly detection. ?& pant 0-

Srivastava, Ashok, N.↗

NASA NTRS2006

Improving Neural Network Generalization Ability Using Outlier Analysis and Voronoi Tessellation

The data used in this study was obtained from the Sloan Digital Sky Survey (SDSS), which provides astronomers with what is currently the most extensive mapping of the universe, covering 25% of the sky and cataloging the spectral properties (e.g., luminosity, color, surface temperature) of over 100 million celestial objects. Images generated by the SDSS are collected through 5 filters named u, g, r, l, and z that have respective wavelengths of 3540, 4750, 6222, 7632, and 9049 A. By measuring the photometric redshifts of the aforementioned wavelengths of a galaxy, astronomers can ascertain the extent to which galaxy is receding from which the distance to the galaxy can be calculated. Data collected for a small select group of galaxies (approximately 30, 000) contains accurate measurements of the galaxies' redshifts, in addition to measurements of their spectral properties. The above dataset containing both redshift measurements as well as spectral properties of the selected galaxies served as the training set for the purposes of this study; the data set containing only the spectra properties of a separate group of galaxies served as the test set.

Ho, Michelle↗

NASA NTRS2006

Improving Situational Awareness for First Responders via Mobile Computing

This project looks to improve first responder incident command, and an appropriately managed flow of situational awareness using mobile computing techniques. The prototype system combines wireless communication, real-time location determination, digital imaging, and three-dimensional graphics. Responder locations are tracked in an outdoor environment via GPS and uploaded to a central server via GPRS or an 802. II network. Responders can also wireless share digital images and text reports, both with other responders and with the incident commander. A pre-built three dimensional graphics model of the emergency scene is used to visualize responder and report locations. Responders have a choice of information end points, ranging from programmable cellular phones to tablet computers. The system also employs location-aware computing to make responders aware of particular hazards as they approach them. The prototype was developed in conjunction with the NASA Ames Disaster Assistance and Rescue Team and has undergone field testing during responder exercises at NASA Ames.

Betts, Bradley J.↗

NASA NTRS2005

Improving Situational Awareness for First Responders via Mobile Computing

This project looks to improve first responder situational awareness using tools and techniques of mobile computing. The prototype system combines wireless communication, real-time location determination, digital imaging, and three-dimensional graphics. Responder locations are tracked in an outdoor environment via GPS and uploaded to a central server via GPRS or an 802.11 network. Responders can also wirelessly share digital images and text reports, both with other responders and with the incident commander. A pre-built three dimensional graphics model of a particular emergency scene is used to visualize responder and report locations. Responders have a choice of information end points, ranging from programmable cellular phones to tablet computers. The system also employs location-aware computing to make responders aware of particular hazards as they approach them. The prototype was developed in conjunction with the NASA Ames Disaster Assistance and Rescue Team and has undergone field testing during responder exercise at NASA Ames.

Betts, Bradley J.↗

NASA NTRS2003

Procedure Visualization to Augment Space Mission Training

The Intelligent Virtual Station (IVS) has been developed by the Smart Systems Research Laboratory at the NASA Ames Research Center as a solution to some of the training and operations challenges faced by organizations like the International Space Station training facilities and Mission Control engineering teams. At present, astronaut crews are constrained by limited access to physical mockups, which themselves have a built-in 1-g limitation. Mission operations team are faced with the daunting task of controlling the operations and maintenance of an ever-changing Station in space. Many operations teams create and follow textual procedures without the ability to visualize the given actions or alternatives. The NS allows users to easily generate and view procedures to enhance training and operations. Because training and mission operations are of crucial importance to the International Space Station and other similarly sophisticated programs, this paper is focused on the NS integrated procedure tool.

McIntosh, Dawn M.↗