In this paper, a general approach for modeling airport operations is presented. Airport operations have been extensively studied in the last decades ranging from airspace, airside and landside operations. Due to the nature of the system, simulation techniques have emerged as a powerful approach for dealing with the variability of these operations. However, in most of the studies, the different elements are studied in an individual fashion. The aim of this paper, is to overcome this limitation by presenting a methodological approach where airport operations are modeled together, such as airspace and airside. The contribution of this approach is that the resolution level for the different elements is similar therefore the interface issues between them is minimized. The framework can be used by practitioners for simulating complex systems like airspace-airside operations or multi-airport systems. The framework is illustrated by presenting a case study analyzed by the authors.
Researchers worldwide have identified affective benefits of improvisational drama techniques (IDTs) on foreign language (FL) learners. Yet the characteristics of professional development programmes (PDPs) that could lead to long-term integration of drama among FL teachers appear largely undiscovered. Through expert interviews, a needs analysis questionnaire and a literature review, this study aimed to determine which design principles a PDP must fulfil to effectively address educational challenges surrounding IDT-implementation. The findings revealed that such training calls for a symbiosis between practical considerations, namely school environment and training conditions, and tapping into a mindset among FL teachers that allows them to (re)discover core beliefs and carry out IDTs with ‘artistry’.
Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.
The composition of diets and supplements given to bovine cattle are constantly evolving. These changes are driven by the social call for a more sustainable beef and dairy production, interests to influence the nutritional value of bovine products for human consumption, and to increase animal health. These adaptations can introduce (new) compounds in the beef and milk supply chain. Currently, the golden standard to study transfer of compounds from feed or veterinary medicine to cows and consequences for human health is performing animal studies, which are time consuming, costly and thus limited. Although animal studies are increasingly debated for ethical reasons, cows are still in the top 10 list of most used animals for animal experiments in Europe. There is, however, no widely applicable alternative modelling tool available to rapidly predict transfer of compounds, apart from individual components like cattle kinetic models and simple in vitro kinetic assays. Therefore, this project aims to develop a first-of-a-kind generic bovine kinetic modelling platform that predicts the transfer of compounds from medicine/supplements and feed to bovine tissues. This will provide new tools for the efficacy and safety evaluation of veterinary medicine and feed and facilitates a rapid evaluation of human health effects of bovine origin food products, thereby contributing to an increased safety in the cattle production chain and supporting product innovations, all without animal testing. This will be accomplished by integrating existing in silico and in vitro techniques into a generic bovine modelling platform and further developing state-of-the-art in vitro bovine organoid cell culturing systems. The platform can be used world-wide by stakeholders involved in the cattle industry (feed-/veterinary medicine industry, regulators, risk assessors). The project partners involve a strong combination of academia, knowledge institutes, small and medium enterprises, industry, branche-organisations and Proefdiervrij, all driven by their pursuit for animal free innovations.
