Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-a ...
Context and activity recognition in complex scenarios is prone to data loss due to disconnections, sensor failure, transmission problems, etc. This generally implies significant changes in the recognition performance. In the case of classifier fusion fault ...
The large variability of the drop size distribution (DSD) in space and time must be taken into account to improve remote sensing of precipitation. The ability to simulate a large number of 2D fields of DSD sharing the same statistical properties provides a ...
The thesis is a contribution to extreme-value statistics, more precisely to the estimation of clustering characteristics of extreme values. One summary measure of the tendency to form groups is the inverse average cluster size. In extreme-value context, th ...
A classification methodology for the automatic detection of start- and endpoints of chemical and biotechnological reaction systems from spectral reaction data is proposed. In the calibration phase, several batch experiments must be conducted covering the e ...
To aid assessments of climate change impacts on water related activities in the case study regions (CSRs) of the EC funded project SWURVE, estimates of uncertainty in climate model data need to be developed. In this paper, two methods to estimate uncertain ...
