We investigate the problem of deterministic pattern matching in multiple streams. In this model, one symbol arrives at a time and is associated with one of s streaming texts. The task at each time step is to report if there is a new match between a fixed pattern of length m and a newly updated stream. As is usual in the streaming context, the goal is to use as little space as possible while sti...

Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes which serve as features may be divided into classes based on their membership in gene families or pathways. When labeling words with senses for word sense disambiguation, features fall into classes including adjacent wor...

in this paper, a new systematic design methodology has been developed for thes imultaneous energy and water minimization in multiple-contaminant systems that also feature maximum re-use of water. in addition to allowing re-use of water in multiple-contaminant systems, issues about heat losses and flowrate changes inside unit operations have also been incorporated in this new design method. to i...

In this paper we address the issue of continuous keyword queries on multiple textual streams and explore techniques for extracting useful information from them. The paper represents, to our best knowledge, the first approach that performs keyword search on a multiplicity of textual streams. The scenario that we consider is quite intuitive; let's assume that a research or financial analyst is se...