Data streams and their applications appear in several fields such as physics, finance, medicine, environmental science, etc. As sensor technology improves, sensor data rates continue to increase. Consequently, analyzing data streams becomes ever more challenging. Fast online response is a must for applications that involve multiple data streams, especially when the number of data streams is lar...

Video retrieval continues to be one of the most exciting research areas in the field of multimedia technology. With the advancement of sensing and tracking technologies it is possible to generate multiple personal video streams during events from different perspectives. This paper presents the first prototype of the MyView system that provides on-demand personalized video streams with multiple ...

In this paper, a novel method for analyzing time-series data and extracting time-correlations among multiple time-series data streams is described. The time-correlations tell us the relationships and dependencies among time-series data streams. Reusable time-correlation rules can be fed into various analysis tools, such as forecasting or simulation tools, for further analysis. Statistical techn...

Analyzing information is recently becoming much more important than ever, as it is produced massively in every area. In the past years, data streams became more and more important and so were algorithms that can mine hidden patterns out of those non static data bases. Those algorithms can also be used to simulate processes and to find important information step by step. The translation of an En...

Introduction: Emergency Department (ED) records and over-the-counter (OTC) sales data are two of the most commonly used data sources for syndromic surveillance. Most current detection algorithms monitor these data sources separately, and either do not combine them, or combine them in an ad hoc fashion. This paper introduces a causal model that coherently combines the two data sources in order t...

In multicast applications such as video conference which consist of multiple streams, not all streams are of equal interest to all receivers. In this case we believe that this disparity in receiver interest should be reflected in the rate adaptation. This paper presents collaborative rate management architecture, named CRM, for layered multicast streams. CRM estimates shared bottleneck links am...

Processing and querying streams, XML streams in particular, has recently become a widely recognized area of interest both in research and in industry. In contrast to traditional query evaluation for databases, where multiple queries against the same data can be evaluated sequentially, for a streamed environment only the simultaneous execution of multiple queries is feasible, as the sequential e...

Query processing for data streams should be continuous and rapid, which requires strict time constraint. In most previous researches, in order to guarantee this constraint, the evaluation order of join predicates in a continuous query is optimized by a greedy. However, the greedy strategy traces only the first promising plan, so that it often finds a sub-optimal plan. This paper proposes an imp...

Given m groups of streams which consist of n1, . . . , nm coevolving streams in each group, we want to: (i) incrementally find local patterns within a single group, (ii) efficiently obtain global patterns across groups, and more importantly, (iii) efficiently do that in real time while limiting shared information across groups. In this paper, we present a distributed, hierarchical algorithm add...