A case study and method development research of online simulation gaming to enhance youth care knowlegde exchange. Youth care professionals affirm that the application used has enough relevance as an additional tool for knowledge construction about complex cases. They state that the usability of the application is suitable, however some remarks are given to adapt the virtual environment to the special needs of youth care knowledge exchange. The method of online simulation gaming appears to be useful to improve network competences and to explore the hidden professional capacities of the participant as to the construction of situational cognition, discourse participation and the accountability of intervention choices.
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When it comes to hard to solve problems, the significance of situational knowledge construction and network coordination must not be underrated. Professional deliberation is directed toward understanding, acting and analysis. We need smart and flexible ways to direct systems information from practice to network reflection, and to guide results from network consultation to practice. This article presents a case study proposal, as follow-up to a recent dissertation about online simulation gaming for youth care network exchange (Van Haaster, 2014).
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Short description of a mindtools project on simulation software.
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Dit essay geeft een systeemvisie op het ontwikkelen van embedded software voor slimme systemen: (mobiele) robots en sensornetwerken.
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To prepare medical students appropriately for the management of toxicological emergencies, we have developed a simulation-based medical education (SBME) training in acute clinical toxicology. Our aim is to report on the feasibility, evaluation and lessons learned of this training. Since 2019, each year approximately 180 fifth-year medical students are invited to participate in the SBME training. The training consists of an interactive lecture and two SBME stations. For each station, a team of students had to perform the primary assessment and management of an intoxicated patient. After the training, the students completed a questionnaire about their experiences and confidence in clinical toxicology. Overall, the vast majority of students agreed that the training provided a fun, interactive and stimulating way to teach about clinical toxicology. Additionally, they felt more confident regarding their skills in this area. Our pilot study shows that SBME training was well-evaluated and feasible over a longer period.
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This paper focuses on the use of discrete event simulation (DES) as a decision support tool for airport land use development. As a study case, Querétaro Airport (Mexico) is used, due to its rapid growth and the different services it offers. The SIMIO® software was used to carry out a macro-level simulation of the airport’s processes, considering generic process times, flight types and demand schedules. The resulting strategic simulation model can be used to diagnose the current growth situation, analyse the airport's growth potential, and evaluate different expansion scenarios using the available land, including the expansion of the terminal building, cargo operations or MRO. The arrival and departure of aircraft (commercial, cargo, maintenance, aviation school and private aviation) at the airport were simulated to detect bottlenecks for different expansion scenarios, that aim to find an optimal balance between the growth options in the different airport grounds. The objective is to compare the potential growth of different layout expansion possibilities. Preliminary results indicate that land use options have a great impact on the growth potential of the airport and some general aviation activities, such as the aviation school, are interfering with the potential growth of other activities at Querétaro Airport.
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Complex situations and systems can be studied by using adequate models in simulation. An important aspect of models and the simulation software is the ability to use a wide range of possible input parameters. The simulation described in this paper is based on agile manufacturing by using transport robots and cheap reconfigurable production platforms, called equiplets. This setup makes agile manufacturing of different products in parallel possible.The simulation showed the maximum load of such a production environment as well as a proof of concept for the distributed approach for transport used. (from IEEE) / paid version: https://doi.org/10.1109/ISADS.2017.54
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The Maritime Spatial Planning (MSP) Challenge simulation platform helps planners and stakeholders understand and manage the complexity of MSP. In the interactive simulation, different data layers covering an entire sea region can be viewed to make an assessment of the current status. Users can create scenarios for future uses of the marine space over a period of several decades. Changes in energy infrastructure, shipping, and the marine environment are then simulated, and the effects are visualized using indicators and heat maps. The platform is built with advanced game technology and uses aspects of role-play to create interactive sessions; it can thus be referred to as serious gaming. To calculate and visualize the effects of planning decisions on the marine ecology, we integrated the Ecopath with Ecosim (EwE) food web modeling approach into the platform. We demonstrate how EwE was connected to MSP, considering the range of constraints imposed by running scientific software in interactive serious gaming sessions while still providing cascading ecological feedback in response to planning actions. We explored the connection by adapting two published ecological models for use in MSP sessions. We conclude with lessons learned and identify future developments of the simulation platform.
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Assigning gates to flights considering physical, operational, and temporal constraints is known as the Gate Assignment Problem. This article proposes the novelty of coupling a commercial stand and gate allocation software with an off-the-grid optimization algorithm. The software provides the assignment costs, verifies constraints and restrictions of an airport, and provides an initial allocation solution. The gate assignment problem was solved using a genetic algorithm. To improve the robustness of the allocation results, delays and early arrivals are predicted using a random forest regressor, a machine learning technique and in turn they are considered by the optimization algorithm. Weather data and schedules were obtained from Zurich International Airport. Results showed that the combination of the techniques result in more efficient and robust solutions with higher degree of applicability than the one possible with the sole use of them independently.
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