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<https://data.nasa.gov/dataset/6072ae56-ed87-4431-ac6c-da1dc43348b5> a dcat:Dataset ;
    dct:description """Electrical power systems play a critical role in spacecraft and aircraft. This paper discusses our development of a diagnostic capability for an electrical power system testbed, ADAPT, using probabilistic techniques. In the context of ADAPT, we present two challenges, regarding modelling and real-time performance, often encountered in real-world diagnostic applications. To meet the modelling challenge, we discuss our novel high-level specification language which supports auto-generation of Bayesian networks. To meet the real-time challenge, we compile Bayesian networks into arithmetic circuits.  Arithmetic circuits typically have small footprints and are optimized for the real-time avionics systems found in spacecraft and aircraft. Using our approach, we present how Bayesian networks with over 400 nodes are auto-generated and then compiled into arithmetic circuits. Using real-world data from ADAPT as well as simulated data, we obtain average inference times smaller than one millisecond when computing diagnostic queries using arithmetic circuits that model our real-world electrical power system.\r
\r
Reference:\r
\r
 O. J. Mengshoel, A. Darwiche, K. Cascio, M. Chavira, S. Poll, and S. Uckun, “Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft”, In Proc. of the Twentieth Innovative Applications of Artificial Intelligence, Conference (IAAI-08), Chicago, IL, 2008.\r
\r
BibTex Reference:  \r
\r
 @inproceedings{mengshoel08diagnosing,\r
  author    = {Mengshoel, O. J. and Darwiche, A. and Cascio, K. and Chavira, M. and Poll, S. and Uckun, S.},\r
  title     = {Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft},\r
  booktitle     = {Proceedings of the Twentieth Innovative Applications of Artificial Intelligence\r
                      Conference (IAAI-08)},\r
  pages = {1699--1705},\r
  address = {Chicago, IL},\r
  year      = {2008}\r
}""" ;
    dct:identifier "DASHLINK_11" ;
    dct:issued "2010-09-09"^^xsd:date ;
    dct:modified "2020-01-29"^^xsd:date ;
    dct:publisher <https://data.nasa.gov/organization/dbb294e4-8597-44f5-aaf4-c0baac12cdbc> ;
    dct:title "Probabilistic Fault Diagnosis in Electrical Power Systems" ;
    dcat:contactPoint [ a vcard:Organization ;
            vcard:fn "Ole Mengshoel" ;
            vcard:hasEmail <mailto:ole.j.mengshoel@nasa.gov> ] ;
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    dcat:keyword "ames",
        "dashlink",
        "nasa" .

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    dct:format "PDF" ;
    dct:identifier "4baa9bba-9b8b-4a7f-a0d9-7cf61b3bbe57" ;
    dct:issued "2025-04-01T01:11:24.751592"^^xsd:dateTime ;
    dct:modified "2025-04-01T01:11:24.734954"^^xsd:dateTime ;
    dct:title "IAAI2008.pdf" ;
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    dcat:mediaType "application/pdf" .

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