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Supporting Sensing Application in Vehicular Networks, and . CoRR, (2013)Entropy and Compression Capture Different Complexity Features: The Case of Fetal Heart Rate., , , , , and . Entropy, 19 (12): 688 (2017)Metalearning to choose the level of analysis in nested data: A case study on error detection in foreign trade statistics., and . IJCNN, page 1-8. IEEE, (2015)Using Metalearning for Prediction of Taxi Trip Duration Using Different Granularity Levels., and . IDA, volume 9385 of Lecture Notes in Computer Science, page 205-216. Springer, (2015)Collaborative Data Analysis in Hyperconnected Transportation Systems., and . PRO-VE, volume 480 of IFIP Advances in Information and Communication Technology, page 13-23. Springer, (2016)Numerical limits for data gathering in wireless networks., and . PIMRC, page 3397-3402. IEEE, (2013)On the prediction of foetal acidaemia: A spectral analysis-based approach., , , , , and . Comput. Biol. Medicine, (2019)Architectural Aspects of Sensing Applications for Vehicular Networks: from Data Collection to Data Model Management. University of Porto, Portugal, (2016)Heart Sounds Classification Using Images from Wavelet Transformation., , , , and . EPIA (1), volume 11804 of Lecture Notes in Computer Science, page 311-322. Springer, (2019)Data gathering for sensing applications in vehicular networks (poster)., and . VNC, page 222-229. IEEE, (2011)