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In energy economy forecasts of different time series are rudimentary. In this study, a prediction for the German day-ahead spot market is created with Apache Spark and R. It is just an example for many different applications in virtual power plant environments. Other examples of use as intraday price processes, load processes of machines or electric vehicles, real time energy loads of photovoltaic systems and many more time series need to be analysed and predicted.
This work gives a short introduction into the project where this study is settled. It describes the time series methods that are used in energy industry for forecasts shortly. As programming technique Apache Spark, which is a strong cluster computing technology, is utilised. Today, single time series can be predicted. The focus of this work is on developing a method to parallel forecasting, to process multiple time series simultaneously with R and Apache Spark.
The sorption of LPS toxic shock by nanoparticles on base of carbonized vegetable raw materials
(2008)
Immobilization of lactobacillus on high temperature carbonizated vegetable raw material (rice husk, grape stones) increases their physiological activity and the quantity of the antibacterial metabolits, that consequently lead to increase of the antagonistic activity of lactobacillus. It is implies that the use of the nanosorbents for the attachment of the probiotical microorganisms are highly perspective for decision the important problems, such as the probiotical preparations delivery to the right address and their attachment to intestines mucosa with the following detoxication of gastro-intestinal tract and the normalization of it’s microecology. Besides that, thus, the received carbonizated nanoparticles have peculiar properties – ability to sorption of LPS toxical shock and, hence, to the detoxication of LPS.
Structural design analyses are conducted with the aim of verifying the exclusion of ratcheting. To this end it is important to make a clear distinction between the shakedown range and the ratcheting range. In cyclic plasticity more sophisticated hardening models have been suggested in order to model the strain evolution observed in ratcheting experiments. The hardening models used in shakedown analysis are comparatively simple. It is shown that shakedown analysis can make quite stable predictions of admissible load ranges despite the simplicity of the underlying hardening models. A linear and a nonlinear kinematic hardening model of two-surface plasticity are compared in material shakedown analysis. Both give identical or similar shakedown ranges. Structural shakedown analyses show that the loading may have a more pronounced effect than the hardening model.