Learn More
The Pain Catastrophizing Scale (PCS; Sullivan et al., Psychol. Assess. 7, 524-532, 1995) has recently been developed to assess three components of catastrophizing: rumination, magnification, and helplessness. We conducted three studies to evaluate the factor structure, reliability, and validity of the PCS. In Study I, we conducted principal-components(More)
In this paper we present the Urban Computing challenge and in particular we exemplify it in the context of traffic management. From our previous experiences in the field we draw requirements in terms of capacity to cope with heterogeneity in representation, semantics and defaults; with scale; with time-dependency of data; and with noisy, uncertain and(More)
In this paper we present the challenging problem of realizing the Urban Computing vision and in particular we describe the requirements for future mobility management systems. We show that novel multidisciplinary ideas are required to address the Urban Computing challenge and that only partial solutions can be found today. The Urban Computing challenge is(More)
This paper discusses a machine learning approach for binary classification problems which satisfies the specific requirements of safety-related applications. The approach is based on ensembles of local models. Each local model utilizes only a small subspace of the complete input space. This ensures the interpretability and verifiability of the local models,(More)