This paper deals with path-wise performance analysis rather than a nodal one to enrich results previously obtained in the literature under simple but unsatisfactory assumptions, e.g., Poisson processes. First deriving the per-stream loss probability, delay, and delay variance of an isolated queue with multi-class input streams modeled by heterogeneous two-state Markovmodulated Poisson processes...

We present a novel method of integrating the likelihoods of multiple feature streams for robust speech recognition. The integration algorithm dynamically calculates a frame-wise stream weight so that a heavier weight is given to a stream that is robust to a variety of noisy environments or speaking styles. Such a robust stream is expected to bring out discriminative ability. The weight is calcu...

What does a data stream mean? Much of the extensive work on query operators and query processing for data streams has proceeded without the benefit of an answer to this question. While such imprecision may be tolerable when dealing with simple cases, such as flat data, guaranteed physical order and element-wise operations, it can lead to ambiguities when dealing with nested data, disordered str...

We consider two popular, permutation-based, step-down procedures of p-values adjustment in multiple testing problems known as min P and max T and intended for strong control of the family-wise error rate, under the so-called subset pivotality property (SPP). We examine key but subtle issues involved in ascertaining validity of these methods, and also introduce a new, slightly narrower notion of...

When looking at domains with several building densities, the resulting average concentrations caused by traffic when unknown, are often linearised between known building densities. To verify if this assumption is correct, several cases of street canyons with intersections, are simulated using the DALESURBAN model. The traffic is represented by a constant emission line source spanning the entire...

We present a unifying approach to multiple testing procedures for sequential (or streaming) data by giving sufficient conditions for a sequential multiple testing procedure to control the familywise error rate (FWER). Together we call these conditions a "rejection principle for sequential tests," which we then apply to some existing sequential multiple testing procedures to give simplified unde...

High utility pattern (HUP) mining over data streams has become a challenging research issue in data mining. The existing sliding window-based HUP mining algorithms over stream data suffer from the level-wise candidate generationand-test problem. Therefore, they need a large amount of execution time and memory. Moreover, their data structures are not suitable for interactive mining. To solve the...

Min-wise independent hashing is a powerful sampling technique for estimating the similarity between sets. In particular, it has proved to be ubiquitous for mining data streams of large volume where the input sets are revealed in arbitrary order and the elements in a given set do not arrive consecutively. More precisely, for sets of elements E and attributes A the input is a stream of element-at...

This work proposes innovative permutation-based procedures controlling the Familywise Error rate (FWE). It is proofed that weighted procedures control the FWE if weights are a function of the sufficient statistic. Particularly, we focus on the use of the additional information given by the total variance of each variables. The first proposal considers the use of weights applied to the combining...