This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large v...
Abstract. We discuss a case study for the hospital scenario where workflow model components are distributed across various computers or devices (e.g. mobile phones, PDAs, sensors, ...
In region surveillance applications, sensors oftentimes accumulate an overwhelmingly large amount of data, making it infeasible to process all of the collected data in real-time. ...
In the study of information flow in the nervous system, component processes can be investigated using a range of electrophysiological and imaging techniques. Although data is diff...
This paper describes and empirically evaluates a new model-driven development framework, called Modeling Turnpike (or mTurnpike). It allows developers to model and program domain-s...