vlator/scientific-python-lectures
Lectures on scientific computing with python, as IPython notebooks.
A Catrobat IDE for Android.
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Lectures on scientific computing with python, as IPython notebooks.
Android App for Fraunhofer Mobility Challenge. This app collects and ad-hoc analyzes GPS sensor records. It identifies and label bike tracks automatically while storing the GPS data points on the SD cards of the phone. The app is intelligent enough to distinguish between bike and not bike movements. Example, if someone carries his bike up the hill it shall be able to detect this and does not count this part of the full track as a bike track. At the end it can be used to produce a short summary of records for the current day, and the running total till that day: - Number of GPS points recorded - Number of bike tracks to work - Length of bike tracks - Average and top speed See task description pdf [CPels_Mobility Challenge]
Base project providing required data structures and basic functionality. To be included in build path of all MobilityChallenge specific projects
Does feature extraction on GPS logs created with the GPSSampler Android app. Creates training data .csv file to be used in RapidMiner.