For many KDD applications, such as detecting criminal activities in E-commerce, finding the rare instances or the outliers, can be more interesting than finding the common patterns. Existing work in outlier detection regards being an outlier as a binary property. In this paper, we contend

In this paper we address the issue of privacy preserving data mining. Specifically, we consider a scenario in which two parties owning confidential databases wish to run a data mining algorithm on the union of their databases, without revealing any unnecessary information. Our work is motivated

-time features and integrate such representations with SVM classification schemes for recognition. For the purpose of evaluation we introduce a new video database containing 2391 sequences of six human actions performed by 25 people in four different scenarios. The presented results of action recognition justify

;coherent". We examine the measures of risk provided and the related actions required by SPAN, by the SEC/NASD rules and by quantile based methods. We demonstrate the universality of scenario-based methods for providing coherent measures. We offer suggestions concerning the SEC method. We also suggest a method

In this paper we compare the performance of descriptors computed for local interest regions, as for example extracted by the Harris-Affine detector [32]. Many different descriptors have been proposed in the literature. However, it is unclear which descriptors are more appropriate and how

-riding are in place. We demonstrate through simulations of scenarios of practical interest that the expected file download time improves by more than 20-30 % with network coding compared to coding at the server only and, by more than 2-3 times compared to sending unencoded information. Moreover, we show that network

multicast) under the investigated scenarios.

. There does, however, exist a number of scenarios where connectivity is intermittent, but where the possibility of communication still is desirable. Thus, there is a need for a way to route through networks with these properties. We propose PROPHET, a probabilistic routing protocol for intermittently

that researchers are currently resolving. The current state of the art of sensor networks is captured in this article, where solutions are discussed under their related protocol stack layer sections. This article also points out the open research issues and intends to spark new interests and developments

this paper we first discuss the wire metrics of interest and examine them in a contemporary 0.25m process. We then discuss technology scaling over the next several generations, from SIA and other predictions, and how our wire metrics trend over that time. We will examine the delay and bandwidth