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The biggest business process management problems to solve before we die., , , , , , , , , and 32 other author(s). Comput. Ind., (April 2023)Enabling runtime flexibility in data-centric and data-driven process execution engines., , and . Inf. Syst., (2021)Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices., , and . Sensors, 22 (1): 170 (2022)Dealing With Inaccurate Sensor Data in the Context of Mobile Crowdsensing and mHealth., , , and . IEEE J. Biomed. Health Informatics, 26 (11): 5439-5449 (2022)CPD: Crowd-based Pothole Detection., , , and . VEHITS, page 33-42. SciTePress, (2019)Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus–stress associations based on the TrackYourTinnitus mobile platform, , , , , , , and . International Journal of Data Science and Analytics, (2018)Prospective crowdsensing versus retrospective ratings of tinnitus variability and tinnitus--stress associations based on the TrackYourTinnitus mobile platform, , , , , , , and . International Journal of Data Science and Analytics, 8 (4): 327--338 (Nov 1, 2019)Anomaly Detections for Manufacturing Systems Based on Sensor Data - Insights into Two Challenging Real-World Production Settings., , , , , and . Sensors, 19 (24): 5370 (2019)Editorial: Smart Mobile Data Collection in the Context of Neuroscience, , , , , and . Frontiers in Neuroscience, (2021)Towards Quantifying the Effects of Robotic Process Automation., and . EDOC Workshops, page 11-19. IEEE, (2020)