Data flow models are used for specifying and analysing signal processing and streaming applications. However, traditional data flow models are either not capable of expressing t...
Bart D. Theelen, Marc Geilen, Twan Basten, Jeroen ...
In recent years, the number of patents filed by the business enterprises in the technology industry are growing rapidly, thus providing unprecedented opportunities for knowledge d...
Mohammad Al Hasan, W. Scott Spangler, Thomas D. Gr...
With the exploding volume of microarray experiments comes increasing interest in mining repositories of such data. Meaningfully combining results from varied experiments on an equ...
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
Abstract. Artificial systems with a high degree of autonomy require reliable semantic information about the context they operate in. State interpretation, however, is a difficult ...
Daniel Meyer-Delius, Christian Plagemann, Georg vo...