Monitoring of qualitative changes of network traffic states based on the heteroscedasticity effect

Skatkov, A. V.; Bryukhovetskiy, A. A.; Shevchenko, V.; Voronin, Dmitry

doi:10.1109/icaict.2016.7991765

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…The obtained results allow to state that the established gamma distribution parameters allow to ensure the adequacy of the simulation model. The simulation results for the gamma distribution confirm the stable detection regions of the G-effect obtained earlier [6] for the normal law of the distribution of requests' intensities. Moreover, in the model, based on the gamma distribution of the hetero regions, they have a bigger time length than the model using the normal distribution law.…”

Section: Experimental Researches Of Qualitative Change In Technologicsupporting

confidence: 84%

Detecting changes simulation of the technological objects’ information states

et al. 2018

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The purpose of the production processes’ states simulation has two constituents. The first is to ensure the effective operation of technological facilities. The second is to improve the quality and competitiveness of the produced products. The proposed new scientific approach aims to develop the known statistical methods in the following direction. They are to be adopted for monitoring accuracy and stability of production processes: real-time processing of large amount of current data, large volumes of a priori information used for decision-making, adjusting the parameters of the monitoring system, critical technological conditions detection. It can prevent great economic damage or even catastrophic consequences.

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Section: Experimental Researches Of Qualitative Change In Technologicsupporting

confidence: 84%

Detecting changes simulation of the technological objects’ information states

et al. 2018

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“…At this stage it is assumed to use the principal component and multidimensional scaling methods. At the stage of "data analysis", hidden insights are supposed to be identified by the mutual correlation (quantitative and qualitative) of the user's characteristics of the media environment [13][14]. To do this, we plan to use the canonical correlation method.…”

Section: Figure 1: Classification Of Influence Modelsmentioning

confidence: 99%

Models of the threat of virus idea dissemination in information-telecommunication networks

2021

Proceedings of the III International Workshop on Modeling, Information Processing and Computing (MIP: Computing-2021)

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The work is devoted to solving the problems associated with the spread of viruses and ideas in the field of research on the processes of reintegration of post-conflict societies. As you know, information and telecommunication networks currently include all kinds of means of switching subscribers, the most common and popular are social networks, which in fact provide an almost complete set of opportunities for exchanging multimedia information between users. The virus must be aware that some «information networks" and "are instantly perceived by active participants in social networks». Effective protection of subscribers from the threat of spreading the virus idea is a serious problem, especially for the development and reintegration of post-conflict societies, since the modern Internet provides not only mobilization and technological opportunities, but also has an informational and psychological impact on individual and mass consciousness. The virus idea, in turn, should be understood as a certain information message, which is often "thrown in" by the media and instantly picked up by the active part of social network subscribers.

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Monitoring of qualitative changes of network traffic states based on the heteroscedasticity effect

Cited by 2 publications

References 6 publications

Detecting changes simulation of the technological objects’ information states

Detecting changes simulation of the technological objects’ information states

Models of the threat of virus idea dissemination in information-telecommunication networks

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