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Coordinated machine learning and decision support for situation awareness

Draelos, Timothy J.; Brannon, Nathan; Conrad, Gregory N.; Zhang, Pengchu

For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

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Natural language processing-based COTS software and related technologies survey

Eaton, Shelley M.; Stickland, Michael; Conrad, Gregory N.

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Pattern Discovery in Time-Ordered Data

Conrad, Gregory N.; Britanik, John M.; Deland, Sharon M.; Witcher, Christina J.

This report describes the results of a Laboratory-Directed Research and Development project on techniques for pattern discovery in discrete event time series data. In this project, we explored two different aspects of the pattern matching/discovery problem. The first aspect studied was the use of Dynamic Time Warping for pattern matching in continuous data. In essence, DTW is a technique for aligning time series along the time axis to optimize the similarity measure. The second aspect studied was techniques for discovering patterns in discrete event data. We developed a pattern discovery tool based on adaptations of the A-priori and GSP (Generalized Sequential Pattern mining) algorithms. We then used the tool on three different application areas--unattended monitoring system data from a storage magazine, computer network intrusion detection, and analysis of robot training data.

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7 Results
7 Results