An Approach for Estimating Border Length in Marine Coasts From MODIS Data

Cipolletti, Marina P.; Genchi, Sibila Andrea; Delrieux, Claudio; Perillo, Gerardo M. E.

doi:10.1109/lgrs.2019.2916620

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…The spectral exponent (), H, D, and  of the SERV-1 and SERV-2 time series estimated with the PSA method are tabulated in Table 3. It is emphasized that the spectral exponent is defined in (12) and is related to H and D by means (13); it stands out that  is related to H through (6).…”

Section: Fractal Analysismentioning

confidence: 99%

Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation

Millán¹,

Lefranc²,

Osorio-Comparán³

et al. 2021

Preprint

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Fractal behavior and long-range dependence are widely observed in measurements and characterization of traffic flow in high-speed computer networks of different technologies and coverage levels. This paper presents the results obtained when applying fractal analysis techniques on a time series obtained from traffic captures coming from an application server connected to the Internet through a high-speed link. The results obtained show that traffic flow in the dedicated high-speed network link have fractal behavior when the Hurst exponent is in the range of 0.5, 1, the fractal dimension between 1, 1.5, and the correlation coefficient between –0.5, 0. Based on these results, it is ideal to characterize both the singularities of the traffic and its impulsiveness during a fractal analysis of temporal scales. Finally, based on the results of the time series analyses, the fact that the traffic flows of current computer networks exhibit fractal behavior with a long-range dependency is reaffirmed.

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Section: Fractal Analysismentioning

confidence: 99%

Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation

Millán¹,

Lefranc²,

Osorio-Comparán³

et al. 2021

Preprint

View full text Add to dashboard Cite

show abstract

Imaging sciences R&D laboratories in Argentina

et al. 2020

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WE USE THE term imaging sciences to refer to the overarching spectrum of scientific and technological contexts which involve images in digital format including, among others, image and video processing, scientific visualization, computer graphics, animations in games and simulators, remote sensing imagery, and also the wide set of associated application areas that have become ubiquitous during the last decade in science, art, human-computer interaction, entertainment, social networks, and many others. As an area that combines mathematics, engineering, and computer science, this discipline arose in a few universities in Argentina mostly in the form of elective classes and small research projects in electrical engineering or computer science departments. Only in the mid-2000s did some initiatives aiming to generate joint activities and to provide identity and visibility to the discipline start to appear. In this short paper, we present a brief history of the three laboratories with the most relevant research and development (R&D) activities in the discipline in Argentina, namely the Imaging Sciences Laboratory of the Universidad Nacional del Sur, the PLADEMA Institute at the

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An Approach for Estimating Border Length in Marine Coasts From MODIS Data

Cited by 2 publications

References 15 publications

Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation

Time Series Analysis of Computer Network Traffic in a Dedicated Link Aggregation

Imaging sciences R&D laboratories in Argentina

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