Douglas Boulware

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Situation awareness involves the identification and monitoring of relationships among level-one objects. This problem in general is intractable (i.e., there is a potentially infinite number of relations that could be tracked) and thus requires additional constraints and guidance defined by the user if there is to be any hope of creating practical situation(More)
There has been much activity over the past two decades in developing conceptual models under the titles of data fusion and situation awareness. In this paper we will explore the two most popular models and show how they complement each other in developing an overall framework for situation awareness. We will also demonstrate how this framework has been(More)
SAWA is a situation awareness assistant being developed by Versatile Information Systems, Inc. During the process of its development, several lessons were learned about advantages and limitations of certain approaches, techniques, and technologies as they are applied to situation awareness. This paper begins with an overview of SAWA and then focuses on some(More)
This paper considers a system architecture referred to as the mobile agent-based distributed fusion (MADFUSION) system. The system environment consists of a peer-to-peer ad-hoc network in which information may be dynamically distributed and collected via publish/subscribe functionality implemented at each node of the network to facilitate data sharing and(More)
Spatial association mining has been used for discovering frequent spatial association patterns from large static spatial databases. When a large spatial database is updated, it is computationally expensive to redo the pattern discovery process for the updated database. This work presents the problem of finding spatial association patterns incrementally from(More)
Spatial association rule mining is a useful tool for discovering correlations and interesting relationships among spatial objects. Co-locations, or sets of spatial events which are frequently observed together in close proximity, are particularly useful for discovering their spatial dependencies. Although a number of spatial co-location mining algorithms(More)
Full spectrum dominance (FSD), as defined by Joint Vision 2020, is the ability to be persuasive in peace, decisive in war and preeminent in any form of conflict. FSD cannot be accomplished without the capability to know what the adversary is currently doing as well as the capacity to correctly anticipate the adversary's future actions. This ability has been(More)