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We have developed a set of path integral quantum Monte Carlo techniques for studying self-assembled quantum dots. The simulations can be run in two or three dimensions, with a variety of different effective mass models. Our most realistic simulations start from an atomistic model of dot shape, size, and composition, then compute strain-modified band offsets(More)
In this paper we present an experimental study exploiting structural Bayesian adaptation for handling potential mismatches between training and test conditions for real-world applications to be realized in our multilingual very large vocabulary speech recognition (VLVSR) system project sponsored by MOTIE (The Ministry of Trade, Industry and Energy),(More)
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