10 citations · 18 across the 5 of their papers we have counts for
5 papers
Evaluation of Data Enrichment Methods for Distributed Stream Processing Systems
Dominik Scheinert, Fabian Casares, Morgan K. Geldenhuys +2
Stream processing has become a critical component in the architecture of modern applications. With the exponential growth of data generation from sources such as the Internet of Th…
Federated Learning for Autoencoder-based Condition Monitoring in the Industrial Internet of Things
Soeren Becker, Kevin Styp-Rekowski, Oliver Vincent Leon Stoll +1
Enabled by the increasing availability of sensor data monitored from production machinery, condition monitoring and predictive maintenance methods are key pillars for an efficient…
Macaw: The Machine Learning Magnetometer Calibration Workflow
Jonathan Bader, Kevin Styp-Rekowski, Leon Doehler +2
In Earth Systems Science, many complex data pipelines combine different data sources and apply data filtering and analysis steps. Typically, such data analysis processes are histor…
Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
Sabtain Ahmad, Kevin Styp-Rekowski, Sasho Nedelkoski +1
Rotating machines like engines, pumps, or turbines are ubiquitous in modern day societies. Their mechanical parts such as electrical engines, rotors, or bearings are the major comp…
Optimizing Convergence for Iterative Learning of ARIMA for Stationary Time Series
Kevin Styp-Rekowski, Florian Schmidt, Odej Kao
Forecasting of time series in continuous systems becomes an increasingly relevant task due to recent developments in IoT and 5G. The popular forecasting model ARIMA is applied to a…