---
res:
  bibo_abstract:
  - Sensor and information fusion is recently a major topic which becomes important
    in machine diagnosis and conditioning for complex production machines and process
    engineering. It is a known fact that distributed automation systems have a major
    impact on signal processing and pattern recognition for machine diagnosis. Therefore,
    it is necessary to research and develop smart diagnosis methods which are applicable
    for distributed systems like resource-limited cyber-physical systems. In this
    paper we propose an new approach for sensor and information fusion based on Evidence
    Theory and socio-psychological decision-making. We show that context based condition
    monitoring is instantiated even in conflict situations, oc-curing in real life
    scenarios permanently. A simple but effective importance measure is proposed which
    controls the significance of conditioning propositions in a system.@eng
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Uwe
      foaf_name: Mönks, Uwe
      foaf_surname: Mönks
      foaf_workInfoHomepage: http://www.librecat.org/personId=1825
  - foaf_Person:
      foaf_givenName: Volker
      foaf_name: Lohweg, Volker
      foaf_surname: Lohweg
      foaf_workInfoHomepage: http://www.librecat.org/personId=1804
    orcid: 0000-0002-3325-7887
  bibo_doi: 10.1109/ETFA.2013.6647984
  dct_date: 2013^xs_gYear
  dct_isPartOf:
  - 'http://id.crossref.org/issn/1946-0740 '
  - 'http://id.crossref.org/issn/1946-0759 '
  - http://id.crossref.org/issn/978-1-4799-0862-2
  dct_language: eng
  dct_subject:
  - Decision making
  - Robot sensing systems
  - Reliability
  - Production
  - Context
  - Fuzzy set theory
  - Data integration
  dct_title: Machine Conditioning by Importance Controlled Information Fusion@
...