Mamadou Kaba Traoré

A model-driven framework for multi-paradigm modeling and holistic simulation of healthcare systems:

The domain of healthcare is characterized by a high degree of complexity and a diversity of perspectives, and modelers are often confronted with the challenge of formulating a simulation model that captures this complexity in a systematic and manageable manner. Most often, the diverse perspectives of healthcare systems are studied in isolation and using specific formalisms. As it turns out, answering questions concerning behavioral properties of the overall system becomes difficult and therefore not sufficient for an efficient design and analysis of the system under study. In this article, we propose a framework for multi-paradigm modeling and holistic simulation of healthcare systems. We present a modeling methodology with a plethora of formalisms to allow the modeler to choose an appropriate formalism at a given level of abstraction while model transformation relates the different formalisms. Furthermore, we develop an integrative approach for the interactions between models of different perspectives through dynamic update of model output-to-parameter integration during concurrent simulations. Such an approach provides multiple levels of explanation for the same system, while offering, at the same time, an integrated view of the whole. The framework has successfully been applied to study part of the Nigerian healthcare system.

Modeling and Simulation Framework for Value-based Healthcare Systems

Regardless of the coordination of its activities, a healthcare system is composed of a large number of distributed components that are interrelated by complex processes. Understanding the behavior of the overall system is becoming a major concern among healthcare managers and decision-makers. This paper presents a modeling and simulation framework to support a holistic analysis of healthcare systems through a stratification of the levels of abstraction into multiple perspectives and their integration in a common simulation framework. In each of the perspectives, models of different components of a healthcare system can be developed and coupled together. Concerns from other perspectives are abstracted as parameters, that is, we reflect the parameter values of other perspectives through explicit assumptions and simplifications in such models. Consequently, the resulting top model within each perspective can be coupled with its experimental frame to run simulations and derive results. Components of the various perspectives are integrated to provide a holistic view of the healthcare problem and system under study. The resulting global model can be coupled with a holistic experimental frame to derive results that cannot be accurately addressed in any of the perspectives taken alone. Furthermore, as we endeavored to allow perspective-specific experts to contribute to the modeling process, we took benefit of results originating from research efforts that Norbert Giambiasi initiated in the 2000s, which his PhD students further developed with their own PhD students.

Formation of gel of preformed size-selected titanium-oxo-alkoxy nanoparticles: towards organic-inorganic hybrid material with efficient interfacial electron transfer

We report on preparation of a new organic–inorganic hybrid material with high photonic sensitivity, of which the inorganic component is gel of preformed size-selected titanium-oxo-alkoxy (TOA) nanoparticles. The inorganic nanoparticles of 5 nm size are generated in perfect micromixing conditions and assembled into the gel network in monomer HEMA (2-hydroxyethyl methacrylate) solutions at sufficiently slow input of water molecules in neutral pH conditions. The gelation is found to compete with precipitation and is promoted by an increase of the nanoparticle concentration. As a result, homogeneous optical-grade gels are obtained at titanium molar concentrations of 1.5 M and higher. After the organic polymerization, the organicinorganic pHEMA-TOA hybrids (pHEMA = poly(2-hydroxyethyl methacrylate)) show a high quantum yield of photoinduced charges separation (Ti3+/absorbed photons) and storage capacity (Ti3+/Ti4+), respectively 75% and 25%, which confirm the importance of the material nanoscale morphology control.

A tool for mining discrete event simulation model

Mining a discrete event simulation model from data has always been a big challenge, which is related to the problem of system inference in systems theory. D2FD (Data to Fuzzy-DEVS model) method can be used to discover a discrete event simulation model. This method not only provides a way of data mining but also integrates process mining with the modularity, frequency, timing aspects and event data. This paper presents a mature tool applying D2FD method. This tool is implemented as an available and dedicated plug-in within the open-source process mining toolkit ProM. The simulation tool SimStudio is embedded in this plug-in and it can simulate Fuzzy-DEVS atomic and coupled model. Two case studies of real life processes, taken from Rabobank Group ICT and Dutch Employee Insurance Agency, are analyzed to evaluate this tool.