The authors argue that "true" models that aim at faithfully mimicking or reproducing every property of the sensorimotor system cannot be compact as they need many free parameters. Consequently, most scientists in motor control use what are called "false" models--models that derive from well-defined approximations. The authors conceptualize these models as a priori limited in scope and approxima...

Hidden Markov Models (HMM) are probabilistic graphical models for interdependent classification. In this paper we experiment with different ways of combining the components of an HMM for document analysis applications, in particular for finding tables in text. We show: a) how to integrate different document structure finders into the HMM; b) that transition probabilities should vary along the c...

Business process models play an important role in the development of large IT systems, since they are easy to understand by all project stakeholders. High-level process models may be created by domain experts, which are stepwise refined in later development phases until they become executable. To establish such model-driven development (MDD) approaches in praxis, a comprehensive tool support of...

The automated processing of 3D models of cultural artifacts can be significantly improved with formally defined high-level structured descriptors. Despite the large number of multimedia ontologies, however, the semantic enrichment of 3D models still has open issues. Many 3D ontologies are semistructured only, cover a very narrow knowledge domain, do not provide comprehensive coverage for geomet...

Acknowledgements This dissertation would not have been possible without the help and support from many people to whom I am greatly indebted. First of all, I thank my advisor, Bud Mishra for his support, encouragement and collaboration. It is Bud who introduced me to the computational world, and guided me into the exciting interdisciplinary field of computational biology. He has taught me the va...

In this paper, dynamical systems theory and bifurcation theory are applied to investigate the rich dynamical behaviours observed in three simple disease models. The 2and 3-dimensional models we investigate have arisen in previous investigations of epidemiology, in-host disease, and autoimmunity. These closely related models display interesting dynamical behaviors including bistability, recurren...

With the advent of the Web, search has become the prominent paradigm for information seeking, not only across the online space but also within enterprises. Search engine functionality has been unbundled into software frameworks and components that can be used to build search-based applications in the most diverse vertical fields. This paper explores the usage of Model Driven Development and of ...

Protecting sensitive data stored behind online websites is a major challenge, but existing techniques are inadequate. Automated website builders typically offer very limited options for specifying custom access policies. Manually adding access policy checks to website code is tedious and error-prone, and it is currently not feasible to automatically verify that a website conforms to its require...

The computational costs of inference and planning have confined Bayesian model-based reinforcement learning to one of two dismal fates: powerful Bayes-adaptive planning but only for simplistic models, or powerful, Bayesian non-parametric models but using simple, myopic planning strategies such as Thompson sampling. We ask whether it is feasible and truly beneficial to combine rich probabilistic...