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The paper analyzes the maximum discharge, and in some cases, the floods caused by them, observed in the Ijevan section of the Aghstev River Basin during the period of 2010-2020 and an attempt was made to predict the expected floods based on the forecast of a high-resolution digital weather forecast, WRF precipitation, temperature, and other elements. The observation data of the Ijevan hydrological observatory of the Aghstev River were used for the work, and the actual meteorological values were taken from the observations of the Ijevan meteorological station. [ABSTRACT FROM AUTHOR]

The usage of traditional high-performance computing (HPC) is a challenge for scientific workflows because of the high cost of acquisition and a lack of expertise to deploy and support such in-house infrastructures. HPC as a Service cloud model has tremendous potential of spreading the outreach of HPC to the broader scientific and industrial community considering the advantages of elasticity, flexibility, and customization. The mismatch between performance-oriented HPC and cost and resource-utilization oriented cloud an infrastructure is an additional barrier to build a cloud-based optimized HPC environment. Therefore, we aim to provision HPC capabilities over the cloud, combining scientific discoveries in cloud data fusion, algorithms, methods, and SaaS through comprehensive performance and energy efficiency analysis. [ABSTRACT FROM AUTHOR]

Investigation and control of epidemic phenomena, as well as introduction of methods for preventing the spread of viruses, are always up-to-date. In this context, the paper presents newer methods of modeling the dynamics of epidemics in self-organizing systems based on cellular automata. Methods and approaches for behavioral analysis of epidemic waves, also for statistical data processing, are promoted and validated in terms of obtained theoretical results. Recovery of causality in multilevel graphs simulating epidemic situations observed over time is given ac-cordingly. A multi-user software platform designed for the purpose enables collective observation and operation of dynamic processes. This also makes it possible to conduct comprehensive analysis of epidemiological procedures and dynamical prediction of target parameters. Cryptographic algorithms and data anonymization techniques of proven security have been suggested to protect personal information at all levels of data acquisition, storage, transfer and processing. A method for synthetic data generation enabling simulation and investigation of the spread of viruses has been introduced and estimated accordingly. [ABSTRACT FROM AUTHOR]