An Improved AFF Algorithm for Continuous Monitoring for Changepoints in Data Streams

Author(s):  
Junlong Zhao ◽  
Mengying An ◽  
Xiaoling Lu ◽  
Yiwei Fan ◽  
Menghang Liu
2012 ◽  
Vol 184 (1) ◽  
pp. 196-214 ◽  
Author(s):  
Xiaofeng Ding ◽  
Xiang Lian ◽  
Lei Chen ◽  
Hai Jin

Algorithmica ◽  
2011 ◽  
Vol 62 (3-4) ◽  
pp. 1088-1111 ◽  
Author(s):  
Ho-Leung Chan ◽  
Tak-Wah Lam ◽  
Lap-Kei Lee ◽  
Hing-Fung Ting

Author(s):  
Maria Kontaki ◽  
Anastasios Gounaris ◽  
Apostolos N. Papadopoulos ◽  
Kostas Tsichlas ◽  
Yannis Manolopoulos

Data streams pose several computational challenges due to their large volume of massive data arriving at a very fast rate. Data streams are gaining the attention of today’s research community for their utility in almost all fields. In turn, organizing the data into groups enables the researchers to derive with many useful and valuable information and conclusions based on the categories that were discovered. Clustering makes this organization or grouping easier and plays an important role in exploratory data analysis. This paper focuses on the amalgamation of two very important algorithms namely Density Based clustering used to group the data and the dissimilarity matrix algorithm used to find the outlier among the data. Before feeding the data, the algorithm filters out the sparse data and a continuous monitoring system provides the frequent outlier and inlier checks on the live stream data using buffer timer. This approach provides an optimistic solution in recognizing the outlier data which may later get reverted as inlier based on certain criteria. The concept of DenDis approach will pave a new innovation world of considering every data which “May Get Life in Future”.


2020 ◽  
Vol 245 ◽  
pp. 01024
Author(s):  
Chiara Rovelli

The CMS experiment at the LHC features an electromagnetic calorimeter (ECAL) made of lead tungstate scintillating crystals. The ECAL energy response is fundamental for both triggering purposes and offline analysis. Due to the challenging LHC radiation environment, the response of both crystals and photodetectors to particles evolves with time. Therefore continuous monitoring and correction of the ageing effects are crucial. Fast, reliable and efficient workflows are set up to have a first set of corrections computed within 48 hours from data-taking, making use of dedicated data streams and processing. Such corrections, stored in relational databases, are then accessed during the prompt offline reconstruction of the CMS data. Twice a week, the calibrations used in the trigger are also updated in the database and accessed during the data-taking. In this note, the design of the CMS ECAL data handling and processing is reviewed.


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