An interactive ontology-driven information system for simulating background radiation and generating scenarios for testing special nuclear materials detection algorithms. (August 2015)

• Record Type: Journal Article
• Authors: Sorokine, Alexandre; Schlicher, Bob G.; Ward, Richard C.; Wright, Michael C.; Kruse, Kara L.; Bhaduri, Budhendra; Slepoy, Alexander
• Is Part Of: Engineering applications of artificial intelligence. Volume 43(2015:Jul.)
• Page Start: 157
• Page End: 165
• Publication Date: 2015-08
• Subjects: Ontology -- Ontology driven information system -- Scenario -- Geographical information system -- Database; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2015.04.010
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: This paper describes an original approach to generate scenarios for the purpose of testing the algorithms used to detect special nuclear materials (SNM) that incorporates the use of ontologies. Separating the signal of SNM from the background requires sophisticated algorithms. To assist in developing such algorithms, there is a need for scenarios that capture a very wide range of variables affecting the detection process, depending on the type of detector being used. To provide such a capability, we developed an ontology-driven information system (ODIS) for generating scenarios that can be used for testing of algorithms for SNM detection. The Ontology-Driven Scenario Generator (ODSG) is an ODIS based on information supplied by subject matter experts and other documentation. The details of the creation of the ontology, the development of the ontology-driven information system, and the design of the web user interface (UI) are presented along with specific examples of scenarios generated using the ODSG. We demonstrate that the paradigm behind the ODSG is capable of addressing the problem of semantic complexity at both the user and developer levels. Compared to traditional approaches, an ODIS provides benefits such as faithful representation of the users׳ domain conceptualization, simplified management of very large and semantically diverse datasets, and the ability to handle frequent changes to the application and the UI. The approach makes possible the generation of a much larger number of specific scenarios based on limited user-supplied information.