Abstract. Separation kernels are key components in embedded applications. Their small size and widespread use in high-integrity environments make them good targets for formal model...
Manifold learning is an effective methodology for extracting nonlinear structures from high-dimensional data with many applications in image analysis, computer vision, text data a...
With the explosive growth of proteomic and expression data of homologous genes, it becomes necessary to explore new methods to visualize and analyze related gene expression data t...
Li Jin, Karl V. Steiner, Carl J. Schmidt, Keith...
Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer visio...
A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200ft long main span and the south tower of the Golden...
Sukun Kim, Shamim Pakzad, David E. Culler, James D...