We propose a framework for Bayesian unsupervised image segmentation with descriptive, learnable models. Our approach is based on learning descriptive models for segmentation and applying Monte Carlo Markov chain to traverse the solution space. Swendsen-Wang cuts are adapted to make meaningful jumps in solution space.

By applying descriptive set theory to the Wagner’s fine structure of regular ω-languages we get quite different proofs of his results and obtain new results. We give an automata-free description of the fine structure. We present also a simple property of a deterministic Muller automaton equivalent to the condition that the corresponding regular ω-language belongs to any given level of the fine ...

OBJECTIVES Polyarteritis nodosa (PAN) is a term that has been used to describe a wide variety of vasculitic conditions. In 1994, the Chapel Hill Consensus Conference on the nomenclature of systemic vasculitides proposed that the name classical PAN should be restricted to diseases where there is arteritis in small and medium-sized arteries without the involvement of smaller vessels. Our aim was ...

Abst rac t By applying descriptive set theory we get several facts on the fine structure of regular w-languages considered by K.Wagner. We present quite different, shorter proofs for main his results and get new results. Our description of the fine structure is new, very clear and automata-free. We prove also a closure property of the fine structure under Boolean operations. Our results demonst...

Corporate fraud these days represents a huge cost to our economy. Academic literature already concentrated on how data mining techniques can be of value in the fight against fraud. All this research focusses on fraud detection, mostly in a context of external fraud. In this paper we discuss the use of a data mining approach to reduce the risk of internal fraud. Reducing fraud risk comprehends b...