In this paper, we explore flexible name resolution as a way of supporting extensibility for wide-area distributed services. Our approach, called Active Names, maps names to a cha...
Amin Vahdat, Michael Dahlin, Thomas E. Anderson, A...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
In this paper we introduce a system called e-Fuzion based on using computing devices, such as Tablet PCs, that empower students and teachers with better technologies for education...
Chad Peiper, Ellick Chan, Roy H. Campbell, Jim Bre...
This paper proposes a novel secure query processing model for semantic sensor networks. A semantic sensor network (SSN) is a sensor network which includes semantics of sensory dat...
– This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning al...