Intelligent networks include particularly the design of active management in standardized structures, designing smart grid concepts for autonomous units (micro grid, small grid, active micro-region, or modelling the impact of smart grid utilization on the economic and social level of the population inside and outside of smart grids with active management.
Evolution of fuzzy predictors and classifiers for data collection
Fuzzy predictors and classifiers enable e.g. estimating the quality of steel products, predicting the power output of photovoltaic power plant, estimating voltage for power plant generator, estimating severity of traffic accidents, detecting computer system disruptions.
Telemedicine applications in the project include both hardware and software solutions for biotelemetry measurements using small mobile devices and large-signal processing. The aim is to innovate and develop a functional prototype system for remote home care that will include devices monitoring vital functions.
The main objective of studying EEG signals is to measure and analyze the electric activity on the surface of scalp. The human brain contains around 100 billion neurons. EEG signal is a very simplified sum of the electrical activities of these neurons. Conventional devices for scanning brain activity have usually 24 measuring electrodes. We have a modern laboratory device that allows scanning EEG using as many as 128 sensors and this enables us to get a more complex view of the brain activity. Such devices are able to scan and generate large data in real time and analyzing the data requires adequate computing power. For this reason in the application area we focus on using modern hardware with an emphasis on possible parallelization of computations. Currently we use nVIDIA graphic processors (GPU) and plan on using supercomputer cluster Anselm.
Analysis of complex networks
Analysis of complex networks (social, information, technological), e.g. using a DBLP analysis.