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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3

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    Optimizing digital twin synchronization in a finite horizon
    (IEEE, 2022) Matta, Andrea; Department of Business Administration; Tan, Barış; Department of Business Administration; College of Administrative Sciences and Economics
    Given the tendency to increase the complexity of digital twins to capture a manufacturing system in the most detailed way, synchronizing and using a complex digital twin with the real-time data may require significant resources. We define the optimal synchronization problem to operate the digital twins in the most effective way by balancing the trade-off between improving the accuracy of the simulation prediction and using more resources. We formulate and solve the optimal synchronization problem for a special case. We analyze the characteristics of the state-dependent and state-independent optimal policies that indicate when to synchronize the simulation at each decision epoch. Our numerical experiments show that the number of synchronizations decreases with the synchronization cost and with the system variability. Furthermore, a lower average number of synchronizations can be achieved by using a state-dependent policy.
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    Context-sensitive mental model aggregation in a second-order adaptive network model for organisational learning
    (Springer International Publishing AG, 2022) Treur, Jan; Department of Computer Engineering; Canbaloğlu, Gülay; Undergraduate Student; Department of Computer Engineering; College of Engineering; N/A
    Organisational learning processes often exploit developed individual mental models in order to obtain shared mental models for the organisation by some form of unification or aggregation. The focus in this paper is on this aggregation process, which may depend on a number of contextual factors. It is shown how a second-order adaptive network model for organisation learning can be used to model this process of aggregation of individual mental models in a context-dependent manner.
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    Contact 3-manifolds with infinitely many stein fillings
    (American Mathematical Society (AMS), 2004) Stipsicz, Andras; Department of Mathematics; Özbağcı, Burak; Faculty Member; Department of Mathematics; College of Sciences; 197389
    Infinitely many contact 3-manifolds each admitting infinitely many pairwise non-diffeomorphic Stein fillings are constructed. We use Lefschetz fibrations in our constructions and compute their first homologies to distinguish the fillings.