Modern airport management is challenged by the task of operating aircraft parking positions most efficiently while complying with environmental policies, restrictions, schedule disruptions, and capacity limitations. This study proposes a novel framework for the stand allocation problem that uses a divide-and-conquer approach in combination with Bayesian modelling, simulation, and optimisation to produce less-pollutant solutions under realistic conditions. The framework presents three innovative aspects. First, inputs from the stochastic analysis module are used in a multivariate optimisation for generating variability-robust solutions. Second, a combination of optimisation and simulation is used to finely explore the impact of realistic uncertainty uncaptured by the framework. Lastly, the framework considers the role of human beings as the final control of operational conditions. A case study is presented as a proof of concept and demonstrates results achievable and benefits of the framework proposed. The experimental results demonstrate that the framework generates less-pollutant solutions under realistic conditions.
Artificial Intelligence (AI) offers organizations unprecedented opportunities. However, one of the risks of using AI is that its outcomes and inner workings are not intelligible. In industries where trust is critical, such as healthcare and finance, explainable AI (XAI) is a necessity. However, the implementation of XAI is not straightforward, as it requires addressing both technical and social aspects. Previous studies on XAI primarily focused on either technical or social aspects and lacked a practical perspective. This study aims to empirically examine the XAI related aspects faced by developers, users, and managers of AI systems during the development process of the AI system. To this end, a multiple case study was conducted in two Dutch financial services companies using four use cases. Our findings reveal a wide range of aspects that must be considered during XAI implementation, which we grouped and integrated into a conceptual model. This model helps practitioners to make informed decisions when developing XAI. We argue that the diversity of aspects to consider necessitates an XAI “by design” approach, especially in high-risk use cases in industries where the stakes are high such as finance, public services, and healthcare. As such, the conceptual model offers a taxonomy for method engineering of XAI related methods, techniques, and tools.
MULTIFILE
Business rule models are widely applied, standalone and embedded in smart objects. They have become segregated from information technology and they are now a valuable asset in their own right. As more business rule models are becoming assets, business models to monetize these assets are designed. The goal of this work is to present a step towards business model classification for organizations for which its value position is characterized by business rule models. Based on a survey we propose a business model categorization that is aligned to different types of assets and business model archetypes. The results show five main categories of business models: The value adding business rule model, the ‘create me a business rule model’ business model, the KAAS business model, the bait and hook business model and the market place business model.
Mode heeft een cruciale functie in de samenleving: zij maakt diversiteit en inclusiviteit mogelijk en is een middel voor individuen om zich uit te drukken. Desalniettemin is mode ook een raadsel op het gebied van duurzaamheid, zowel aan de sociale als aan de milieukant. Er bestaan echter alternatieven voor de huidige praktijken in de mode. Dit project heeft tot doel de ontwikkeling van een van die initiatieven te ondersteunen. In samenwerking met twee Nederlandse MKB bedrijven in de mode-industrie, willen we een of meer business modellen co-designen voor het vermarkten van circulair ontworpen laser geprinte T-shirts. Door lasertechnologie te introduceren in plaats van traditionele inktopties, kunnen de T- shirts hun CO2 voetafdruk verder verkleinen en een verstandig alternatief zijn voor individuen, die op zoek zijn naar duurzame modekeuzes. Maar hoewel de technologische haalbaarheid vaststaat, vereist het vermarkten sterke, schaalbare, bedrijfsmodellen. Via een haalbaarheidsstudie willen we dergelijke businessmodellen ontwikkelen en de commercialisering van deze producten ondersteunen. Wij zijn van plan de reacties van de consument op een dergelijke innovatie te bestuderen, evenals de belemmeringen en stimulansen vanuit het oogpunt van de consument, en de inkoop-, toeleveringsketen- en financiële kwesties die kunnen voortvloeien uit de schaalbaarheid van een potentieel bedrijfsmodel. Om praktische relevantie voor de bredere industrie te verzekeren, streven we ernaar om de resultaten te presenteren op evenementen georganiseerd door een van de consortiumpartners (in 2023), als ook om een teaching case en een wetenschappelijk artikel te ontwikkelen op basis van de resultaten van het project.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
Every year in the Netherlands around 10.000 people are diagnosed with non-small cell lung cancer, commonly at advanced stages. In 1 to 2% of patients, a chromosomal translocation of the ROS1 gene drives oncogenesis. Since a few years, ROS1+ cancer can be treated effectively by targeted therapy with the tyrosine kinase inhibitor (TKI) crizotinib, which binds to the ROS1 protein, impairs the kinase activity and thereby inhibits tumor growth. Despite the successful treatment with crizotinib, most patients eventually show disease progression due to development of resistance. The available TKI-drugs for ROS1+ lung cancer make it possible to sequentially change medication as the disease progresses, but this is largely a ‘trial and error’ approach. Patients and their doctors ask for better prediction which TKI will work best after resistance occurs. The ROS1 patient foundation ‘Stichting Merels Wereld’ raises awareness and brings researchers together to close the knowledge gap on ROS1-driven oncogenesis and increase the options for treatment. As ROS1+ lung cancer is rare, research into resistance mechanisms and the availability of cell line models are limited. Medical Life Sciences & Diagnostics can help to improve treatment by developing new models which mimic the situation in resistant tumor cells. In the current proposal we will develop novel TKI-resistant cell lines that allow screening for improved personalized treatment with TKIs. Knowledge of specific mutations occurring after resistance will help to predict more accurately what the next step in patient treatment could be. This project is part of a long-term collaboration between the ROS1 patient foundation ‘Stichting Merels Wereld’, the departments of Pulmonary Oncology and Pathology of the UMCG and the Institute for Life Science & Technology of the Hanzehogeschool. The company Vivomicx will join our consortium, adding expertise on drug screening in complex cell systems.
