With resource-efficient summarization and accurate reconstruction of the historic traffic sensor data, one can effectively manage and optimize transportation systems (e.g., road n...
Bei Pan, Ugur Demiryurek, Farnoush Banaei Kashani,...
In this paper, an efficient technique for test data volume reduction based on the shared scan-in (Illinois Scan) architecture and the scan chain reconfiguration (Dynamic Scan) arc...
Samitha Samaranayake, Emil Gizdarski, Nodari Sitch...
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
Scientific workflow systems are increasingly used to automate complex data analyses, largely due to their benefits over traditional approaches for workflow design, optimization, a...