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DB-SMoT: A direction-based spatio-temporal clustering method.

, , , , and . IEEE Conf. of Intelligent Systems, page 114-119. IEEE, (2010)

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An Experimental Assessment of Three Point-Insertion Sequences for 3-D Incremental Delaunay Tessellations., , , , and . ICCS (1), volume 10860 of Lecture Notes in Computer Science, page 614-623. Springer, (2018)DB-SMoT: A direction-based spatio-temporal clustering method., , , , and . IEEE Conf. of Intelligent Systems, page 114-119. IEEE, (2010)Behavior-driven development benefits and challenges: reports from an industrial study., , , , , and . XP Companion, page 42:1-42:4. ACM, (2018)How to Evaluate BDD Scenarios' Quality?, , and . SBES, page 481-490. ACM, (2019)Developing neural networks library in RSCAD for real-time power system simulation., , and . CIASG, page 130-137. IEEE, (2013)On the Understanding of BDD Scenarios' Quality: Preliminary Practitioners' Opinions., and . REFSQ, volume 10753 of Lecture Notes in Computer Science, page 290-296. Springer, (2018)A Framework for Trajectory Data Preprocessing for Data Mining., , , and . SEKE, page 698-702. Knowledge Systems Institute Graduate School, (2009)Machine Learning Prediction of Hospitalization due to COVID-19 based on Self-Reported Symptoms: A Study for Brazil., , , , and . BHI, page 1-5. IEEE, (2021)On the Empirical Evaluation of BDD Scenarios Quality: Preliminary Findings of an Empirical Study., and . RE Workshops, page 299-302. IEEE Computer Society, (2017)MAD-STEC: a method for multiple automatic detection of space-time emerging clusters., , , , and . Stat. Comput., 27 (4): 1099-1110 (2017)