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Conference Object An automata network reverse engineering algorithm using system statics and dynamics(int inst informatics & Systemics, 2003) Kilic, HAn automata network reverse engineering algorithm that considers not only the change events (dynamics) but also their no-change events (statics) is proposed. The time complexity for the algorithm is theta(m(2)n(2)) where m is the number of given global system states and n is the number of system components. Experiments on stock exchange data showed that the extracted state transition rules for the components may reveal some hidden relations coming from statics of the system. The extracted automaton information about the interacting set of stocks is particularly valuable as it can be used for index tracking purposes.Article Citation - WoS: 3Citation - Scopus: 5Evaluating the Sustainability of Complex Health System Transformation in the Context of Population Ageing: an Empirical System Dynamics Study(Taylor & Francis Ltd, 2023) Selcuk, Gozdem Dural; Vasilakis, ChristosDemographic changes, particularly population ageing, and rising morbidity from chronic conditions contribute to ever-increasing pressures on health and care systems in developed countries. Partly as a response, new models of care and service innovations are being piloted and introduced. However, the effectiveness and sustainability of these complex health system transformations are often not well understood and most modelling studies fail to capture both system configuration and populating dynamics. In this paper, we present a comprehensive system dynamics modelling approach to capture both population ageing and the organisation of the health and care services from a whole system perspective. The development of the model was directly informed by an ambitious care system transformation project designed to offer a different pathway for those patients deemed to be complex. The model input parameters were populated using estimates from empirical data. A series of simulation experiments were conducted to inform the design of the new service and its sustainability. We found that, subject to the model's limitations and assumptions, the new pathway could have a stabilising effect against increasing demand provided hospital readmission fractions and length of stay for complex patients can be managed effectively.
