Burst detection and location in water

Burst detection is the activity of finding abnormal aggregates in data streams. Such aggregates are based on sliding windows over data streams. In some applications, we want to monitor many sliding window sizes simultaneously and to report those windows with aggregates significantly different from

Detecting bursts in data streams is an important and challenging task. Due to the complexity of this task, usually burst detection cannot be formulated using standard query operators. Therefore, we show how to integrate burst detection for stationary as well as non-stationary data into query

Detection of burst-related impulses, such as those accompanying plosive stop consonants, is an important problem for accurate measurement of acoustic features for recogntion (e.g., voice-onset-time) and for accurate automatic phonetic alignment. The proposed method of burst detection utilizes

Aims. The durations of 388 gamma-ray bursts, detected by the Swift satellite, are studied statistically in order to search for their subgroups. Then the results are compared with the results obtained earlier from the BATSE database. Methods. The standard χ 2 test is used. Results. Similarly

Abstract-This paper presents Random Early Detection (RED) gateways for congestion avoidance in packet-switched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving

Detecting bursts in data streams is an important and challenging task, especially in stock market, traffic control or sensor network streams. Burst detection means the identification of non regular behavior within data streams. A specifically crucial challenge on burst detection is to identify

The spectrometer SPI, one of the two main instruments of the INTEGRAL spacecraft, has strong capabilities in the field of Gamma-Ray Burst (GRB) detections. In its 16 o field of view (FoV) SPI is able to trigger and to localize GRBs. With its large anticoincidence shield (ACS) of 512 kg of BGO

. In this paper, we propose to explicitly detect the visual bursts in an image at an early stage. We compare several detection strategies jointly taking into account feature sim-ilarity and geometrical quantities. The bursty groups are merged into meta-features, which are used as input to state-of-the-art image

This is taken from [SZ04, Chap. 7]. It is the third of three applications they develop based on their review of timeseries techniques in the first four chapters. 1. Bursts are sudden occurrences of high values over a continuous duration of time in a timeseries. For example, in 1 3 5 11 12 13 0 1