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Under Pressure Benchmark for DDBMS Availability., , , , , and . J. Inf. Data Manag., 4 (3): 266-278 (2013)The Challenge of Non-Technical Loss Detection Using Artificial Intelligence: A Survey., , , , and . Int. J. Comput. Intell. Syst., 10 (1): 760-775 (2017)Towards Privacy Preserving Data Centric Super App., , , and . MedComNet, page 1-4. IEEE, (2020)A PetriNet mechanism for OLAP in NUMA., , and . DaMoN, page 7:1-7:4. ACM, (2017)Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations., , , , , , and . ICDM Workshops, page 258-265. IEEE Computer Society, (2017)A state machine for database non-functional testing., , and . IDEAS, page 378-379. ACM, (2014)Stress Testing of Transactional Database Systems., , , , and . J. Inf. Data Manag., 4 (3): 279-294 (2013)Is Big Data Sufficient for a Reliable Detection of Non-Technical Losses?, , , , , , and . CoRR, (2017)Överloaded!" - A Model-Based Approach to Database Stress Testing., , , , and . DEXA (1), volume 9827 of Lecture Notes in Computer Science, page 207-222. Springer, (2016)An Image Processing Tool to Support Gestational Age Determination., , , , and . CBMS, page 867-874. IEEE Computer Society, (2006)