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A web page for publishing process-specific hydrogen potentials, using GitLab pages.

We developed a hardware setup that captures short, wideband snapshots in both E1 and E6 GNSS bands. This setup is mounted to a bridge over a motorway. The setup records 20 ms raw IQ snapshots triggered from the energy with a sample rate of 62.5 MHz, an analog bandwidth of 50MHz and an 8 bit bit-width. At certain frequencies the GPS/Galileo or GLONASS signals can easily be seen as a slight increase in the spectrum. Note that experts manually analyzed the datastreams by thresholding CN/0 and AGC values. Manual labeling of these snapshots has resulted in 11 classes: classes 0 to 2 represent samples with no interferences, distinguished by variations in background intensity, while classes 3 to 10 contain different interferences. The challenge lies in adapting to positive class labels with only a limited number of samples available. We partition the dataset into a 64% training set, 16% validation set, and a 20% test set split (balanced over the classes).

This is the code developed by Dr.-Ing. Dominique Koster and contributed to by Dr. Mariam R. Rizkallah for the workshop "Data Reconciliation: Integration of Electrochemical Data and Optical Sensor Data for Health Diagnostics of Lithium-Ion Batteries" https://www.bremen-research.de/data-train/courses/course-details?event_id=88

Guides for setup gitlab, python, etc.

Conversion of MDBW data from GraphDesigner-Excel to RDF

Bash scripts to automatically establish a connection to Nokia and b<>com 5G networks