IMS Learning Design (IMS LD) is a powerful and expressive educational modeling language, which is becoming a “de facto” encoding and interchange standard for activity-based co...
In this paper, we describe a decompositional approach to convergence proofs for stochastic hybrid systems given as probabilistic hybrid automata. We focus on a concept called “st...
High-speed smooth and accurate visual tracking of objects in arbitrary, unstructured environments is essential for robotics and human motion analysis. However, building a system th...
Rendering networks and distributed systems self-managing and self-optimizing has become a major research focus. This task is especially important for systems, such as publish/subsc...
The optimization method is one of key issues in discriminative learning of pattern classifiers. This paper proposes a hybrid approach of the Covariance Matrix Adaptation Evolution...