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Overview

The Discovery and Systems Health (DaSH) technical area focuses on challenges in understanding engineering and science data. The engineering data understanding work is centered around the emerging systems engineering discipline of Integrated Systems Health Management (ISHM). Ames is NASA's premier ISHM research and development facility, with strengths in design of health management systems, ISHM systems engineering, sensor selection and optimization, monitoring, data analysis, prognostics, diagnostics, failure recovery, diagnostic decision aids, data and knowledge management, and ISHM human factors.

Scientific data understanding work targets large-scale data analysis problems in data-rich domains such as earth science and cosmology. In addition, DaSH is involved in data analysis and mining for a variety of other NASA missions including aviation safety and security, the Space Shuttle program, and the NASA Engineering Safety Center. Resident expertise includes machine learning, data mining, text mining, statistical pattern recognition, and exploratory data analysis.

News

AMISS Certified for ISS Flight Control Room Deployment
The Anomaly Monitoring Inductive Software System (AMISS), based on the Ames Research Center (ARC)-developed Inductive Monitoring System (IMS), underwent and passed Mission Control acceptance (certification) testing at Johnson Space Center ...
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Ares I-X Ground Diagnostic Prototype Demo at KSC
Mark Schwabacher and John Ossenfort traveled to Kennedy Space Center (KSC), where they had a successful demo of the Ares I-X Ground Diagnostic Prototype on May 14, 2009. It was ...
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AMISS
Inductive Monitoring System Released to ISS Mission Evaluation Room
The Inductive Monitoring System (IMS) and IMS-based Anomaly Monitoring Inductive Software System (AMISS) have been released to the Boeing International Space Station (ISS) Mission Evaluation Room (MER) engineering staff for ...
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Presentations on Machine Learning Work Given to ACM
Mark Schwabacher gave a two-hour invited talk to the San Francisco Bay Area Chapter of the Association for Computing Machinery (ACM) Data Mining Special Interest Group (SIG) entitled “Using Supervised ...
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Technical Area Lead

Ann Patterson-Hine, Ph.D, P.E.

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Prognostics Center of Excellence

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ISHEM Forum 2005

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