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Dynamic Event Observation and Partial State-Change Perception for Distributed Supervisory Control.

, , , , and . ECC, page 644-649. IEEE, (2020)

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Infinite-step opacity of stochastic discrete-event systems., , , and . ASCC, page 102-107. IEEE, (2017)On Reductions Among Observation Properties of Discrete Event Systems., , , , and . ICARCV, page 478-482. IEEE, (2020)A Polynomial Algorithm for Minimizing Communication in a Distributed Discrete Event System with a Central Station., , and . CDC, page 6034-6040. IEEE, (2006)Sequential bayesian classification decisions for mobile sensors., , , and . CDC, page 1378-1383. IEEE, (2010)An algorithm for maximising covered area., and . Int. J. Control, 81 (9): 1493-1505 (2008)ImpactMiner: a tool for change impact analysis., , , , , , and . ICSE Companion, page 540-543. ACM, (2014)Dual-Level Selective Transfer Learning for Intrahepatic Cholangiocarcinoma Segmentation in Non-enhanced Abdominal CT., , , , , , , , , and . MICCAI (1), volume 12261 of Lecture Notes in Computer Science, page 64-73. Springer, (2020)Dynamic Event Observation and Partial State-Change Perception for Distributed Supervisory Control., , , , and . ECC, page 644-649. IEEE, (2020)A Model for Dynamic Knowledge Representation and Learning., , and . ECC, page 1051-1056. IEEE, (2024)Optimum Partition of Sensing Field with Given Probability on Event Locations., , , , and . ICARCV, page 1206-1209. IEEE, (2020)