Publications HAL

Some planetary boundaries have been crossed, making it urgent to act on climate change and biodiversity, among others. We are at a crossroads where imagining a desirable and possible future is necessary. Acting on sustainable cities and communities falls under the 11th UN SDG and responds to the growing challenge of urbanization worldwide. In this Special Issue, we invite multidisciplinary contributions on current trends and perspectives in ecosystems, innovations, models and (possibly replicable) good practices in smart cities and territories that improve the environment, the economy, and social wellbeing. Advances in simulation methods and data analysis, forecasting techniques, scenario planning, future design, and complex system models are also particularly welcome as long as they can participate to improve critical thinking and decision making on cities’ and territories’ resilience and sustainable development.

Over the last decade, Higher Education has focused more of its attention toward soft skills compared to traditional technical skills. Nevertheless, there are not many studies concerning the relation between the courses followed within an academic program and the development of soft skills. This work presents a practical approach to model the effects of courses on soft skills proficiency. Multiple Membership Ordinal Logistic Regression models are trained with real data from students of the 2021, 2022, and 2023 cohorts from the general engineering program in a French Higher Education institution. The results show that attending a postgraduate course in average increases the odds of being more proficient in terms of soft skills. Nonetheless, there is considerable variability in the individual effect of courses, which suggest there can be huge differences between courses. Moreover, the data also suggest great dispersion in the students' initial soft skill proficiency.

In recent years, the number of robotic applications in public spaces has been growing. Decades of research have given rise to various methods of human-aware robotic navigation. There are a lot of different navigation solutions to guide a robot in presence of humans. Despite multiple surveys comparing existing navigation solutions, few of them take social criteria into account. In this sense, it is difficult to evaluate existing methods and select the one that performs better in a given context. In this article, we first provide a thorough classification of state-of-the-art solutions regarding human-aware robotic navigation solutions. Then, we select a set of measurable criteria to evaluate both the efficiency and the social-compliance of navigation solutions. Using these criteria, we finally compare representative off-the-shelf navigation solutions using the SEAN Simulator to identify the most suitable for human-aware navigation.

Over the last few years, the educational interest of soft skills has steadily increased. Nonetheless, there is no considerable literature concerning the impact of followed courses on them. This simulation explores the modelling of the effects of courses over the students' soft skill proficiency, considering interaction effects and confounding variables through nine different scenarios. Moreover, the study compares the model with and without propensity scores as predictors, which are proposed as alternatives to handle the selection bias issue of the students' course choices. The simulation results show that in general models without propensity scores produce less bias, nonetheless the higher the effect of interactions between courses the better propensity scores become in reducing the bias.

L'importance croissante prise ces dernières années par les soft skills dans l'enseignement supérieur a encouragé les recherches sur leur relation avec les activités pédagogiques. Ce travail s'intéresse à l'incidence des soft skills sur la recommandation d'un ensemble de cours aux étudiants en fonction à la fois du profil de formation souhaité et des attentes du monde professionnel. Trois fonctions d'évaluation et deux méthodes de compensation sont proposées pour simuler différentes réalités socio-professionnelle et exprimer la différence entre la maîtrise des soft skills estimés heuristiquement et le score attendu à la fin du programme.

In order to monitor and assess the spread of the Omicron variant of COVID-19, we propose a Distributed Digital Twin that virtually mirrors a hemodialysis unit in a hospital in Toronto, Canada. Since the solution involves heterogeneous components, we rely on the IEEE HLA distributed simulation standard. Based on the standard, we use an agent-based/discrete event simulator together with a virtual reality environment in order to provide to the medical staff an immersive experience that incorporates a platform showing predictive analytics during a simulation run. This can help professionals monitor the number of exposed, symptomatic, asymptomatic, recovered, and deceased agents. Agents are modeled using a redesigned version of the susceptible-exposed-infected-recovered (SEIR) model. A contact matrix is generated to help identify those agents that increase the risk of the virus transmission within the unit.

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