@Article{LeonorDosSBomfRosa:2018:NoTiSe,
author = "Leonor, Bruno Bustamente Ferreira and Dos Santos, Walter
Abrah{\~a}o and Bomfin J{\'u}nior, Asiel and Rosa, Reinaldo
Roberto",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)}",
title = "Nonlinear time series analysis of complex systems using an
e-science web framework",
journal = "Discontinuity, Nonlinearity, and Complexity",
year = "2018",
volume = "7",
number = "2",
pages = "129--141",
abstract = "The analysis of time series in the era of Big Data has become a
major challenge for computational framework research. Furthemore,
in the areas of space science which deals with a large variety of
data, the practical consistence between workload, workflow and
cloud computing is crucial. Here, such consistence is provided by
an innovative e-Science framework project named Sentinel which is
based on a NoSQL data base (MongoDB) and a containerization
platform (Docker). This web framework supports researchers for
time series analysis in a cloud environment where they can easily
access, parameterize, initialize and monitor their applications.
As a case study in the Brazilian Space Weather Program, we
consider the intensive analysis of time series from a complex
information system for solar activity monitoring and forecasting.
As a prototype for implementing the framework, the DFA (detrended
fluctuation analysis) technique was used as a nonlinear spectrum
analyzer applied to the solar irradiance measurements from 1978 to
2012. Moreover, new applications can be added and managed by
researchers on the portal easily to complement their data analysis
purposes.",
doi = "10.5890/DNC.2018.06.002",
url = "http://dx.doi.org/10.5890/DNC.2018.06.002",
issn = "2164-6376",
language = "en",
urlaccessdate = "06 maio 2024"
}