Jose B Cruz - Academia.edu (original) (raw)
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Papers by Jose B Cruz
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Iahs Aish Publication, 2008
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Http Dx Doi Org 10 1080 00207177308932486, Apr 6, 2007
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Circuit Theory Ieee Transactions on, Jun 1, 1963
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Proceedings of the Institution of Electrical Engineers, 1970
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Journal of Optimization Theory and Applications, Jan 31, 1996
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Proceedings of the Institution of Electrical Engineers, 1969
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Biocomp, 2010
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Iahs Aish Publication, 2008
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Http Dx Doi Org 10 1080 00207177308932486, Apr 6, 2007
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Circuit Theory Ieee Transactions on, Jun 1, 1963
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Proceedings of the Institution of Electrical Engineers, 1970
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Journal of Optimization Theory and Applications, Jan 31, 1996
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Proceedings of the Institution of Electrical Engineers, 1969
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Biocomp, 2010
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The strategy of data fusion has been applied in threat prediction and situation awareness and the... more The strategy of data fusion has been applied in threat prediction and situation awareness and the terminology has been standardized by the Joint Directors of Laboratories (JDL) in the form of a so-called JDL Data Fusion Model, which currently called DFIG model. Higher levels of the DFIG model callfor prediction offuture development and awareness of the development of a situation. It is known that Bayesian Network is an insightful approach to determine optimal strategies against asymmetric adversarial opponent. However, it lacks the essential adversarial decision processes perspective. In this paper, a highly innovative data-fusion framework for asymmetric-threat detection and prediction based on advanced knowledge infrastructure and stochastic (Markov) game theory is proposed. In particular, asymmetric and adaptive threats are detected and grouped by intelligent agent and Hierarchical Entity Aggregation in Level 2 and their intents are predicted by a decentralized Markov (stochastic) game model with deception in Level 3. We have verified that our proposed algorithms are scalable, stable, and perform satisfactorily according to the situation awareness performance metric.
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