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The article presents results of studies using simulations on computer network devices, designed to examine the effectiveness of routing protocols with the video streaming and generated traffic for Jperf applications. In order to demonstrate the effectiveness of the selected protocols several simulation scenarios were made using different sized UDP packets. The traffic was analyzed in terms of statistical self-similarity. Multifractal analysis has also been made, using two kinds of spectrums. The study determined the relationship between them. These tasks were designed to determine the multifractal and long-term relationship for a given process.

Rapidly developing of internet technologies and digitalization of government generate more and more data. Databases from various public institutions and private sectors, e.g. in the fields of economics, transport, environment and public safety are publishing in the global Internet network, so that any user can browse them without additional charges. Most of this data is published on the open data portals. Open data - that is, “open”, public data can allow the processing and analysis of information contained in them completely free of charge. This article is an introduction to a fairly new area of issues such as “open data” or “open government”, presents the main mechanisms of accessing to data in public open data portals and also propose a conceptual open data/government model.

This study aimed to determine the applicability of using selected libraries of computing environment R to establish the coefficient of self-similarity. R environment is an analytical environment with rich functionality that is used in many research and practical works concerning data analysis and knowledge discovery. Such an issue is significant in the context of contemporary wide area computer networks and the emerging type of network infrastructure IoT. This originates directly from the new nature of IoT traffic, which also has a substantial impact on Industry 4.0. It provides built-in operations facilitating data processing. The Hurst coefficient is used to evaluate traffic behavior and analyze its character. The study analyzed two cases of IoT network traffic: high and low intensity. For different sizes of time windows, we dermined the statistical Hurst exponent and compared it with standard, smoothed, and Robinson methods. The accuracy of the methods used was evaluated. Spectral regression graphs were additionally generated for selected motion variants. The obtained results were verified by Higuchi and Aggvar methods. [ABSTRACT FROM AUTHOR]

Background: Using data collected by the Office for Civil Rights, Department of Health and Human Services (HHS), over half of the population in the USA might have been affected by security breaches since Oct 2009. This study provided analysis of the data, presenting the numbers of individuals affected in one breach and the number of breaches., Methods: Statistical analysis has been conducted with visualizations. Visualizations include categorized histograms and tables. Histograms are presented as bar charts with categories: location and breach type. Tables show case counts (across top 10 breaches and those with more than one million stolen records) in successive years and covered entity types. All statistics were calculated with the use of package R. Analyzed data were collected from Oct 2009 till Jun 2017., Results: This study presents evidence of health data breaches taking place at an unprecedented level. Medical records of at least 173 million of people, gathered since Oct 2009, have been breached and might have adversely influenced over half of the population in the USA., Conclusion: Results of this study are expected to motivate public care authorities to develop similar laws and regulations as the USA while striving for better law enforcement. It takes a considerable amount of time to educate public and it takes substantial financial resources to prevent data breaches., Competing Interests: Conflict of interest The authors declare that there is no conflict of interests.