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Early detection and prediction of the size and the peak time of an epidemic outbreak (malicious or natural) is of crucial importance for a timely medical response (quarantine, vaccination, etc). A conventional approach to this problem is based on large scale agent-based computer simulations. This paper proposes an alternative framework formulated in the context of stochastic nonlinear filtering. The...
The paper presents an analytical study of the effects of dynamic collaboration in a network of chemical sensors using a simple population and physics based model. The approach is based on the known analogy between the information spread in a sensor network and the epidemics propagation across a population. In this framework we derive analytical expressions which relate the parameters of the network...
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