Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
We study the problem of localizing and tracking multiple moving targets in wireless sensor networks, from a network design perspective i.e. towards estimating the least possible n...
In this demonstration, we present a prototype content-based dissemination broker, called Sonnet, which is built upon structured overlay network. It combines approximate filtering ...
In this paper, we present a variational Bayesian (VB) approach to computing the interval estimates for nonhomogeneous Poisson process (NHPP) software reliability models. This appr...
Hiroyuki Okamura, Michael Grottke, Tadashi Dohi, K...
Minimum m-connected k-dominating set problem is as follows: Given a graph G = (V,E) and two natural numbers m and k, find a subset S V of minimal size such that every vertex in V ...
Weiping Shang, F. Frances Yao, Peng-Jun Wan, Xiaod...