scholarly journals Filtering features for a composite event definition language

Author(s):  
S.D. Urban ◽  
I. Biswas ◽  
S.W. Dietrich
2019 ◽  
Vol 28 (5) ◽  
pp. 625-631
Author(s):  
Jea Young Min ◽  
Caroline A. Presley ◽  
Jennifer Wharton ◽  
Marie R. Griffin ◽  
Robert A. Greevy ◽  
...  

2008 ◽  
Vol 25 (1) ◽  
pp. 43-56 ◽  
Author(s):  
Jianxin Wang ◽  
Brad L. Fisher ◽  
David B. Wolff

Abstract This paper describes the cubic spline–based operational system for the generation of the Tropical Rainfall Measuring Mission (TRMM) 1-min rain-rate product 2A-56 from tipping-bucket (TB) gauge measurements. A simulated TB gauge from a Joss–Waldvogel disdrometer is employed to evaluate the errors of the TB rain-rate estimation. These errors are very sensitive to the time scale of rain rates. One-minute rain rates suffer substantial errors, especially at low rain rates. When 1-min rain rates are averaged over 4–7-min intervals or longer, the errors dramatically reduce. Estimated lower rain rates are sensitive to the event definition whereas the higher rates are not. The median relative absolute errors are about 22% and 32% for 1-min rain rates higher and lower than 3 mm h−1, respectively. These errors decrease to 5% and 14% when rain rates are used at the 7-min scale. The radar reflectivity–rain-rate distributions drawn from the large amount of 7-min rain rates and radar reflectivity data are mostly insensitive to the event definition. The time shift due to inaccurate clocks can also cause rain-rate estimation errors, which increase with the shifted time length. Finally, some recommendations are proposed for possible improvements of rainfall measurements and rain-rate estimations.


2021 ◽  
Vol 49 (4) ◽  
pp. 24-27
Author(s):  
Alexander Artikis ◽  
Thomas Eiter ◽  
Alessandro Margara ◽  
Stijn Vansummeren

Composite event recognition (CER) is concerned with continuously matching patterns in streams of 'event' data over (geographically) distributed sources. This paper reports the results of the Dagstuhl Seminar "Foundations of Composite Event Recognition" held in 2020.


2011 ◽  
Vol 219-220 ◽  
pp. 927-931
Author(s):  
Jun Qiang Liu ◽  
Xiao Ling Guan

In recent years the processing of composite event queries over data streams has attracted a lot of research attention. Traditional database techniques were not designed for stream processing system. Furthermore, example continuous queries are often formulated in declarative query language without specifying the semantics. To overcome these deficiencies, this article presents the design, implementation, and evaluation of a system that executes data streams with semantic information. Then, a set of optimization techniques are proposed for handling query. So, our approach not only makes it possible to express queries with a sound semantics, but also provides a solid foundation for query optimization. Experiment results show that our approach is effective and efficient for data streams and domain knowledge.


2013 ◽  
Vol 13 (1) ◽  
pp. 115-123 ◽  
Author(s):  
Pythagoras Karampiperis ◽  
Giannis Mouchakis ◽  
Georgios Paliouras ◽  
Vangelis Karkaletsis

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