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Discontinuity, Nonlinearity, and Complexity

Dimitry Volchenkov (editor), Dumitru Baleanu (editor)

Dimitry Volchenkov(editor)

Mathematics & Statistics, Texas Tech University, 1108 Memorial Circle, Lubbock, TX 79409, USA

Email: dr.volchenkov@gmail.com

Dumitru Baleanu (editor)

Cankaya University, Ankara, Turkey; Institute of Space Sciences, Magurele-Bucharest, Romania

Email: dumitru.baleanu@gmail.com


Nonlinear Time Series Analysis of Complex Systems Using an e-Science Web Framewor

Discontinuity, Nonlinearity, and Complexity 7(2) (2018) 129--141 | DOI:10.5890/DNC.2018.06.002

Bruno B. F. Leonor; Walter A. dos Santos; Asiel Bomfin Jr.; Reinaldo R. Rosa

National Institute for Space Research, São José dos Campos, Brazil

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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.

Acknowledgments

The authors would like to thank Vanessa C. Oliveira de Souza for providing the DFA code used in the case study presented. The authors are greatful to the PMOD/WRC, Davos, Switzerland for the dataset provided (composite d41 62 1204.txt) from the VIRGO Experiment on the cooperative ESA/NASA Mission SOHO. RRR acknowledge financial support from FAPESP through the grant No 2014/11156.

References

  1. [1]  Shadbolt, N., Hall, W., Hendler, J.A., and Dutton, W.H. (2013), Web science: a new frontier, The Royal Society, 371(1987).
  2. [2]  Alisson, E., eScience revoluciona a forma como se faz ciência., available at: http://agencia.fapesp.br/17279, accessed January 2016.
  3. [3]  Tolle, K., Tansley, S., and Hey, T. (2011), O Quarto Paradigma: Descobertas Científicas na era da eSciente, Oficina de Textos.
  4. [4]  Kantz, H. and Schreiber, T. (2004), Nonlinear Time Series Analysis, Cambridge University Press.
  5. [5]  Dantas, M.S., Rosa, R.R., SantAnna, N., Cereja Jr,M.G., Veronese, T.B., Bianchi, S., Rosa, J.C., Alexiev, K.M., and da Silva, J.D.S. (2011), The VLADA white paper: building an active Virtual Lab for Advanced Data Analysis, J. Comp. Int. Sci., 2(1), 47-56.
  6. [6]  Pinheiro, F.J.G., Barata, M.T., and Fernandes, J.M. (2016), Comparison of space weather services: information systems, activity and forecasts, J. Comp. Int. Sci., 7(2), 3-24, doi: 10.6062/jcis.2016.07.02.0106
  7. [7]  INPE, O Programa Embrace, available at: http://www2.inpe.br/climaespacial/portal/, accessed January 2016.
  8. [8]  Zell, H., What is solar activity?, available at: https://www.nasa.gov/content/goddard/what-is-solar-activity, accessed August 2016.
  9. [9]  Young, C.A., Solar Activity, available at: http://www.thesuntoday.org/the-sun/solar-activity/, accessed July 2016.
  10. [10]  Veronese, T.B., Rosa, R.R., Bolzan,M.J.A., Rocha Fernandes, F.C., Sawant, H.S., and Karlicky,M. (2011), Fluctuation analysis of solar radio bursts associated with geoeffective X-class flares, Journal of Atmospheric and Solar-Terrestrial Physics, 73(11-12), 1311-1316, available at: http://www.sciencedirect.com/science/article/pii/S1364682610002907.
  11. [11]  Kirchner, R.M., Souza, R.C., and Ziegelmann, F.A. (2008), Identificação de estruturas não-lineares de séries temporais através de regressão linear local e modelos aditivos, Pesquisa Operacional, available at: http://dx.doi.org/10.1590/S0101-74382008000100003, 28.
  12. [12]  Peng, C.K., Buldyrev, S.V., Havlin, S., Simons,M., Stanley, M.H.E., and Goldberger,A.L. (1994),Mosaic organization of DNA nucleotides, Phys. Rev. E, 49(2), 1685-1689.
  13. [13]  Morariu, V.V., Buimaga-Iarinca, L., Vamos, C., and Soltuz, S. (2007), Detrended Fluctuation Analysis of Autoregressive Processes , Cornell University Library.
  14. [14]  Schwenn, R. (2006), Space Weather: The Solar Perspective, Living Reviews in Solar Physics, 3(2), available at: http://www.livingreviews.org/lrsp-2006-2.
  15. [15]  Cade III, W.B. and Chan-Park,C. (2015), The Origin of Space Weather, Space Weather, 13(2), 99-103.
  16. [16]  MetOffice, Space Weather Impacts, available at: http://www.metoffice.gov.uk/publicsector/emergencies/spaceweather/ impacts, accessed July 2016.
  17. [17]  AWS, Overview of Amazon Web Services, available at: https://d0.awsstatic.com/whitepapers/aws-overview.pdf, accessed August 2016.
  18. [18]  Wilkinson, D. (2012), Extreme Space Weather Events, National Geophysical Data Center, available at: https://commons.wikimedia.org/wiki/File:ExtremeEvent 20031026-00h 20031106-24h.jpg.
  19. [19]  Palazzi, D., Silva, L., Mendes, L F., Gaspar, W., Matos, E., Campos, F., and Braga, R. (2009), "Uso de ontologias em projetos de e-science", BDBComp.
  20. [20]  Fapesp, Programa FAPESP de Pesquisa em eScience, available at: http://www.fapesp.br/publicacoes/2015/folder escience.pdf, accessed December 2015.
  21. [21]  Tiobe, TIOBE Index for February 2016, available at: http://www.tiobe.com/tiobe index, accessed February 2016.
  22. [22]  RedMonk, The RedMonk Programming Language Rankings: January 2016, available at: https://redmonk.com/sogrady/category/programming-languages/, accessed February 2016.
  23. [23]  Spectrum, The 2015 Top Ten Programming Languages, available at: http://spectrum.ieee.org/computing/software/the- 2015-top-ten-programming-languages, accessed February 2016.
  24. [24]  MongoDB, Introduction to MongoDB, available at: available at: https://docs.mongodb.com/manual/introduction/, accessed August 2016.
  25. [25]  Frohlich, C. and Lean, J. (1998), The Sun's total irradiance: Cycles, trends and related climate change uncertainties since 1976, Geophysical Research Letters, 25(23), 4377-4380, available at: http://dx.doi.org/10.1029/1998GL900157.
  26. [26]  ACRIM, (2012), composite d41 62 1204.txt, available at: acrim.com/TSI/composite d41 62 1204.txt.
  27. [27]  NOOA, (2014), Space Environment Overview, available at: http://satdat.ngdc.noaa.gov/sem/goes/data/new plots/special/Overview 19830101-00h 20141231-24h.png.
  28. [28]  Docker,What is Docker?, available at: https://www.docker.com/what-docker, accessed August 2016.
  29. [29]  Cirrus Tech Ltd, Docker: Reorganizing the Data Center, available at: http://www.cirrushosting.com/cloud-hostingblog, accessed August 2016.
  30. [30]  Oppenheim, A.V. and Verghese, G.C. (2015), Signals, Systems and Inference, Prentice-Hall signal processing series, Pearson Education.
  31. [31]  Bolzan, M.J.A., Tardelli, A., Pillat, V.G., Fagundes, P.R., and Rosa, R.R. (2013), Multifractal analysis of vertical total electron content (VTEC) at equatorial region and low latitude, during low solar activity, Annales Geophysicae, 31(1), 127-133.
  32. [32]  Gu, G.F. and Zhou, W.X. (2006), Detrended fluctuation analysis for fractals and multifractals in higher dimensions, Phys. Rev. E, 74(6), American Physical Society.
  33. [33]  Rosa, R.R., Sharma, A.S., and Valdivia, J.A. (1999), Characterization of Asymmetric Fragmentation Patterns in Spatially Extended Systems, International Journal of Modern Physics C, 10(01), 147-163, World Scientific Publishing Company.
  34. [34]  Rosa, R.R., Carvalho, R.R., Sautter, R.A., Barchi, P.H., Stalder, D.H., Moura, T.C., Rembold, S.B., Morell, D.R.F., and Ferreira, N.C. (2018), Gradient Pantern Analysis Applied to Galaxy Morphology, MNRAS, https://doi.org/10.1093/mnrasl/sly054.