BACKGROUND The calibration of several cardiac clinical prediction models has deteriorated over time. We compare different model fitting approaches for in-hospital mortality after cardiac surgery that adjust for cross-sectional case mix in a heterogeneous patient population. METHODS AND RESULTS Data from >300 000 consecutive cardiac surgery procedures performed at all National Health Service a...

This paper focuses on applications of Bayesian approaches to acoustic modeling for speech recognition and related speechprocessing applications. Bayesian approaches have been widely studied in the fields of statistics and machine learning, and one of their advantages is that their generalization capability is better than that of conventional approaches (e.g., maximum likelihood). On the other h...

The purpose of this chapter is to provide an overview of domain modeling approaches and techniques used in information systems (IS) engineering. IS engineering is an area where different types of domain models were used as a basis for software development long before the name of model driven approach and model driven architecture was coined (MDA, 2009; Miller & Mukerji, 2003). IS engineering vi...

A Bayesian-based methodology is presented which automatically penalizes overcomplex models being fitted to unknown data. We show that, with a Gaussian mixture model, the approach is able to select an “optimal” number of components in the model and so partition data sets. The performance of the Bayesian method is compared to other methods of optimal model selection and found to give good results...

M. N. Gevorkyan,1, * A. V. Demidova,1, † Robert A. Sobolewski,2, ‡ I. S. Zaryadov,1, 3, S A. V. Korolkova,1, ¶ D. S. Kulyabov,1, 4, ** and L. A. Sevastianov1, 5, †† Department of Applied Probability and Informatics, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya str., Moscow, 117198, Russia Department of Power Engineering, Fotonics and Lighting Technology, Bialys...

Cellular components interact with each other to form networks that process information and evoke biological responses. A deep understanding of the behavior of these networks requires the development and analysis of mathematical models. In this article, different types of mathematical representations for modeling signaling networks are described, and the advantages and disadvantages of each type...

We analyze differences between two information-theoretically motivated ap­ proaches to statistical inference and model selection: the Minimum Description Length (MDL) principle, and the Minimum Message Length (MML) principle. Based on this analysis, we present two revised versions of MML: a pointwise estimator which gives the MML-optimal single parameter model, and a volumewise estimator which ...

Security is never perfect, security deals with a lot of uncertainty, and security is complex. Nevertheless, security is one of the non-functional properties, that we, as software architects, have to consider. It is needed to include security in many trade-off decisions (usability, performance, costs, etc. versus security), to compare the security of different architectures, and to check whether...

Hair is a relevant characteristic of virtual characters, therefore the modeling of plausible facial hair and hairstyles is an essential step in the generation of computer generated (CG) avatars. However, the inherent geometric complexity of hair together with the huge number of filaments of an average human head make the task of modeling hairstyles a very challenging one. To date this is common...

We describe our participation in the TREC 2005 Enterprise track. We provide a detailed account of the ideas underlying our language modeling approaches to these tasks, report on our results, and give a summary of our findings so far.