Abstract
In this paper the so-called Event Cube is introduced, a multidimensional data structure that can hold information about all business dimensions. Like the data cubes of online analytic processing (OLAP) systems, the Event Cube can be used to improve the business analysis quality by providing immediate results under different levels of abstraction. An exploratory analysis of the application of process mining on multidimensional process data is the focus of this paper. The feasibility and potential of this approach is demonstrated through some practical examples. © 2011 Springer-Verlag.

Abstract
The consequences of regulatory T cell (Treg) inhibition of interleukine 2 secretion are examined by mathematical modelling. We find a transcritical bifurcation that might explain two alternative scenarios: in one case the appearance of autoimmune responses and in another the suppression of the immune response.

Abstract
We present the construction of new pseudo-smooth structures, near the singularities, such that the pseudo-Anosov maps are diffeomorphisms, in this pseudo-smooth structures, and have the property that the stable and unstable foliations are uniformly contracted and expanded by the pseudo-Anosov dynamics. We construct the C(1+) orthogonal charts of such pseudo-Anosov diffeomoprhisms.

Abstract

Abstract
The successive approximation Linear Parameter Varying systems subspace identification algorithm for discrete-time systems is based on a convergent sequence of linear time invariant deterministic-stochastic state-space approximations. In this chapter, this method is modified to cope with continuous-time LPV state-space models. To do this, the LPV system is discretised, the discrete-time model is identified by the successive approximations algorithm and then converted to a continuous-time model. Since affine dependence is preserved only for fast sampling, a subspace downsampling approach is used to estimate the linear time invariant deterministic-stochastic state-space approximations. A second order simulation example, with complex poles, illustrates the effectiveness of the new algorithm. © 2012 by World Scientific Publishing Co. Pte. Ltd.

Abstract
The HATS project aims at developing a model-centric methodology for the design, implementation and verification of highly configurable systems, such as software product lines, centred around the Abstract Behavioural Specification (ABS) modelling Language. This article describes the variability modelling features of the ABS Modelling framework. It consists of four languages, namely, µTVL for describing feature models at a high level of abstraction, the Delta Modelling Language DML for describing variability of the 'code' base in terms of delta modules, the Product Line Configuration Language CL for linking feature models and delta modules together and the Product Selection Language PSL for describing a specific product to extract from a product line. Both formal semantics and examples of each language are presented. © 2011 Springer-Verlag Berlin Heidelberg.