Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Pessa, Arthur A. B."'
In recent years, digital games have become increasingly present in people's lives both as a leisure activity or in gamified activities of everyday life. Despite this growing presence, large-scale, data-driven analyses of video games remain a small fr
Externí odkaz:
http://arxiv.org/abs/2406.10241
Autor:
Voltarelli, Leonardo G. J. M., Pessa, Arthur A. B., Zunino, Luciano, Zola, Rafael S., Lenzi, Ervin K., Perc, Matjaz, Ribeiro, Haroldo V.
Publikováno v:
Chaos 34, 053130 (2024)
Permutation entropy and its associated frameworks are remarkable examples of physics-inspired techniques adept at processing complex and extensive datasets. Despite substantial progress in developing and applying these tools, their use has been predo
Externí odkaz:
http://arxiv.org/abs/2403.13122
Publikováno v:
Sci. Rep. 13, 12695 (2023)
While extensive literature exists on the COVID-19 pandemic at regional and national levels, understanding its dynamics and consequences at the city level remains limited. This study investigates the pandemic in Maring\'a, a medium-sized city in Brazi
Externí odkaz:
http://arxiv.org/abs/2307.11015
Autor:
Ribeiro, Haroldo V., Lopes, Diego D., Pessa, Arthur A. B., Martins, Alvaro F., da Cunha, Bruno R., Goncalves, Sebastian, Lenzi, Ervin K., Hanley, Quentin S., Perc, Matjaz
Publikováno v:
Chaos, Solitons & Fractals 172, 113579 (2023)
Recent advances in deep learning methods have enabled researchers to develop and apply algorithms for the analysis and modeling of complex networks. These advances have sparked a surge of interest at the interface between network science and machine
Externí odkaz:
http://arxiv.org/abs/2304.08457
Publikováno v:
Sci. Rep. 13, 3351 (2023)
Cryptocurrencies are considered the latest innovation in finance with considerable impact across social, technological, and economic dimensions. This new class of financial assets has also motivated a myriad of scientific investigations focused on un
Externí odkaz:
http://arxiv.org/abs/2302.12319
Publikováno v:
EPL 138, 30003 (2022)
Many simple natural phenomena are characterized by complex motion that appears random at first glance, but that often displays underlying patterns and behavior that can be clustered in groups. The movement of small pieces of paper falling through the
Externí odkaz:
http://arxiv.org/abs/2204.14097
Publikováno v:
Chaos, Solitons & Fractals 154, 111607 (2022)
Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these systems is still recent and underexplored, especially in materials often st
Externí odkaz:
http://arxiv.org/abs/2201.05597
Publikováno v:
Chaos 31, 063110 (2021)
Since Bandt and Pompe's seminal work, permutation entropy has been used in several applications and is now an essential tool for time series analysis. Beyond becoming a popular and successful technique, permutation entropy inspired a framework for ma
Externí odkaz:
http://arxiv.org/abs/2102.06786
Publikováno v:
Phys. Rev. E 102, 052312 (2020)
An increasing abstraction has marked some recent investigations in network science. Examples include the development of algorithms that map time series data into networks whose vertices and edges can have different interpretations, beyond the classic
Externí odkaz:
http://arxiv.org/abs/2007.03090
Publikováno v:
Phys. Rev. E 100, 042304 (2019)
Approaches for mapping time series to networks have become essential tools for dealing with the increasing challenges of characterizing data from complex systems. Among the different algorithms, the recently proposed ordinal networks stand out due to
Externí odkaz:
http://arxiv.org/abs/1910.01406