The human faculty of moral judgment is not well suited to address problems, like climate change, that are global in scope and remote in time. Advocates of ‘moral bioenhancement’ have proposed that we should investigate the use of medical technologies to make human beings more trusting and altruistic, and hence more willing to cooperate in efforts to mitigate the impacts of climate change. We su...

A supply network structure design, that is resilient to any adverse, fast changing, or unexpected conditions, serves as a catalyst to propel a business forward while competition sits still. Complex systems theory provides an approach to capture the evolution of supply chains over times, where companies co-evolve with their suppliers, customers and competitors to adapt to changing business envir...

Many background modelling approaches are based on mixtures of multivariate Gaussians with diagonal covariance matrices. This often yields good results, but complex backgrounds are not adequately captured, and postprocessing techniques are needed. Here we propose the use of mixtures of uniform distributions and multivariate Gaussians with full covariance matrices. These mixtures are able to cope...

The systematic test is an inevitable part of the verification and validation process for software. The most important prerequisite for a thorough software test is the design of relevant test cases, since they determine the kind and scope and hence the quality of the test. The graphical editor CTE (classification-tree editor) presented in this paper supports the systematic design of black-box te...

A new detection algorithm for decoding multiple-input multiple-output (MIMO) transmission is proposed and analyzed. The method is based on combining sphere decoding (SD) and zero forcing (ZF) techniques. The proposed method performs a fixed number of operations to detect the signal, independent of the noise level, and hence provides a fixed complexity near optimal performance. The algorithm is ...

Affinity propagation constitutes an exemplar based clustering technique which reliably optimizes the quantization error given a matrix of pairwise data dissimilarities by means of the max-sum algorithm for factor graphs. Albeit very efficient for sparse matrices, it displays squared complexity in the worst case, hence it is not suited as high throughput method due to time and memory constraints...