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Results 11 - 20
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2,993
Analysis of Open Source Software Development Iterations by means of Burst Detection Techniques
"... Abstract. A highly efficient bug fixing process and quick release cycles are considered key properties of the open source software development methodology. In this paper, we study the relation between code activities (such as lines of code added per commit), bug fixing activities, and software rele ..."
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release dates in a subset of open source projects. To study the phenomenon, we gathered a large data set about the evolution of 5 major open source projects. We compared activities by means of a burst detection technique to discover temporal peaks in time-series. We found quick adaptation of issue
Possible EGRET Gamma-Ray Burst Detection Independent of BATSE Triggering
"... EGRET spark chamber data collected between 1991 April 22 and 1994 August 29 have been analyzed for gamma-ray burst events independent of BATSE triggering. To date, five gamma-ray bursts that are coincident with a trigger from the BATSE instrument have been detected in the EGRET spark chamber. The EG ..."
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EGRET spark chamber data collected between 1991 April 22 and 1994 August 29 have been analyzed for gamma-ray burst events independent of BATSE triggering. To date, five gamma-ray bursts that are coincident with a trigger from the BATSE instrument have been detected in the EGRET spark chamber
POST-DETECTION INTERFERENCE REJECTION AND WEAK BURST DETECTION IN TIME-FREQUENCY SPECTROGRAMS
"... In the frame of a radio search for extrasolar planets, we analyze dynamic spectra obtained with an acousto-optical spectrograph connected to the UTR-2 decameter array in Kharkov, attempting to reach maximum sensitivity. Data consist of two dynamic spectra, made of 10000 consecutive spectra acquired ..."
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-correlations. Then spectral integration is perfomed for increasing the S/N ratio, before statistical detection of weak bursts. INSTRUMENTS AND OBSERVATIONS The observation system consists of the T-shaped UTR-2 array (Kharkov, Ukraine). It can observe in the range 7-35 MHz, with effective areas about 60000 m2 for the NS
Post-Launch Analysis of Swzft’s Gamma-Ray Burst Detection Sensitivity
"... The dependence of Swift’s detection sensitivity on a k irst’s t mporal and spectral properties shapes the detected burst population. Using simplified models of the detector hardware and the burst trigger system I find that Swij? is more sensitive to long, soft bursts than CGRO’s BATSE, a reference m ..."
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The dependence of Swift’s detection sensitivity on a k irst’s t mporal and spectral properties shapes the detected burst population. Using simplified models of the detector hardware and the burst trigger system I find that Swij? is more sensitive to long, soft bursts than CGRO’s BATSE, a reference
Post-Launch Analysis of Swift’s Gamma-Ray Burst Detection Sensitivity
, 2006
"... The dependence of Swift’s detection sensitivity on a burst’s temporal and spectral properties shapes the detected burst population. Using simplified models of the detector hardware and the burst trigger system I find that Swift is more sensitive to long, soft bursts than CGRO’s BATSE, a reference de ..."
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The dependence of Swift’s detection sensitivity on a burst’s temporal and spectral properties shapes the detected burst population. Using simplified models of the detector hardware and the burst trigger system I find that Swift is more sensitive to long, soft bursts than CGRO’s BATSE, a reference
An Exemplar-based Approach to Automatic Burst Detection in Spontaneous Speech
"... This paper introduces a novel algorithm for detecting burst in voiceless stops in spontaneous speech. This algorithm uses an exemplar-based approach for detecting aspiration noise, and avoids the normalization problem since the exemplars are inherently speaker-specific and environment-specific. The ..."
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Cited by 1 (1 self)
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This paper introduces a novel algorithm for detecting burst in voiceless stops in spontaneous speech. This algorithm uses an exemplar-based approach for detecting aspiration noise, and avoids the normalization problem since the exemplars are inherently speaker-specific and environment
Guervós. Genetic algorithm for burst detection and activity tracking in event streams
- In PPSN
, 2006
"... Abstract. We introduce a new model for detection and tracking of bursts of events in a discrete temporal sequence, its only requirement being that the time scale of events is long enough to make a discrete time description meaningful. A model for the occurrence of events using with Poisson distribut ..."
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Cited by 2 (0 self)
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Abstract. We introduce a new model for detection and tracking of bursts of events in a discrete temporal sequence, its only requirement being that the time scale of events is long enough to make a discrete time description meaningful. A model for the occurrence of events using with Poisson
Heat Burst Detection by a Temporally Fine-Scale Mesonet
, 2007
"... A heat burst which occurred at Sioux Falls, South Dakota, early in the morning of 11 August 2007, took place in close proximity to both the KFSD WSR-88D and to privately owned mesonet sensors which record data in 1-min increments. The event began with the decay of a thunderstorm, when precipitation ..."
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Cited by 1 (0 self)
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A heat burst which occurred at Sioux Falls, South Dakota, early in the morning of 11 August 2007, took place in close proximity to both the KFSD WSR-88D and to privately owned mesonet sensors which record data in 1-min increments. The event began with the decay of a thunderstorm, when precipitation
Tracking Triadic Cardinality Distributions for Burst Detection in Social Activity Streams
"... Abstract—In online social networks (OSNs), we often observe abnormally frequent interactions among people before or during some important day, e.g., we receive/send more greetings from/to friends on Christmas Day than usual. We also often observe some viral videos suddenly become worldwide popular t ..."
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triangles in networks. This finding provokes a new method for detecting bursts in OSNs. We first introduce a new measure, named triadic cardinality distribution, which measures the fraction of nodes with certain number of triangles, i.e., triadic cardinality, in a network. The distribution will change when
Results 11 - 20
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2,993
