Data mining seems to be a promising way to tackle the problem of unpredictability in MRO organizations. The Amsterdam University of Applied Sciences therefore cooperated with the aviation industry for a two-year applied research project exploring the possibilities of data mining in this area. Researchers studied more than 25 cases at eight different MRO enterprises, applying a CRISP-DM methodology as a structural guideline throughout the project. They explored, prepared and combined MRO data, flight data and external data, and used statistical and machine learning methods to visualize, analyse and predict maintenance. They also used the individual case studies to make predictions about the duration and costs of planned maintenance tasks, turnaround time and useful life of parts. Challenges presented by the case studies included time-consuming data preparation, access restrictions to external data-sources and the still-limited data science skills in companies. Recommendations were made in terms of ways to implement data mining – and ways to overcome the related challenges – in MRO. Overall, the research project has delivered promising proofs of concept and pilot implementations
MULTIFILE
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for developing personalized apps. In this paper, we describe the design and development of the Playful data-driven Active Urban Living (PAUL): a personalized PA application.Methods: The two-phased development process of the PAUL apps rests on principles from the behavior change model; the Integrate, Design, Assess, and Share (IDEAS) framework; and the behavioral intervention technology (BIT) model. During the first phase, we explored whether location-specific information on performing PA in the built environment is an enhancement to a PA app. During the second phase, the other modules of the app were developed. To this end, we first build the theoretical foundation for the PAUL intervention by performing a literature study. Next, a focus group study was performed to translate the theoretical foundations and the needs and wishes in a set of user requirements. Since the participants indicated the need for reminders at a for-them-relevant moment, we developed a self-learning module for the timing of the reminders. To initialize this module, a data-mining study was performed with historical running data to determine good situations for running.Results: The results of these studies informed the design of a personalized mobile health (mHealth) application for running, walking, and performing strength exercises. The app is implemented as a set of modules based on the persuasive strategies “monitoring of behavior,” “feedback,” “goal setting,” “reminders,” “rewards,” and “providing instruction.” An architecture was set up consisting of a smartphone app for the user, a back-end server for storage and adaptivity, and a research portal to provide access to the research team.Conclusions: The interdisciplinary research encompassing psychology, human movement sciences, computer science, and artificial intelligence has led to a theoretically and empirically driven leisure time PA application. In the current phase, the feasibility of the PAUL app is being assessed.
CILOLAB contributes to the transition of the UFT-system towards zero emission city logistics in 2025 by examining, developing and enabling alternatives for urban logistics activities. Specifically, CILOLAB focuses on the transferability and scaling-up of successful logistics initiatives; i.e. concepts that facilitate decoupling between transport towards and in cities. CILOLAB is an action-driven partnership where cities cooperate with transport operators, interest groups, research institutes and societal partners and collaboratively develop new approaches for urban logistical solutions. Through continuous monitoring and impact assessment these solutions are evaluated and further developed within this experimentation environment, all contributing to the CILOLAB ambition.
CILOLAB contributes to the transition of the UFT-system towards zero emission city logistics in 2025 by examining, developing and enabling alternatives for urban logistics activities. Specifically, CILOLAB focuses on the transferability and scaling-up of successful logistics initiatives; i.e. concepts that facilitate decoupling between transport towards and in cities. CILOLAB is an action-driven partnership where cities cooperate with transport operators, interest groups, research institutes and societal partners and collaboratively develop new approaches for urban logistical solutions. Through continuous monitoring and impact assessment these solutions are evaluated and further developed within this experimentation environment, all contributing to the CILOLAB ambition.
Restoring rivers with an integrated approach that combines water safety, nature development and gravel mining remains a challenge. Also for the Grensmaas, the most southern trajectory of the Dutch main river Maas, that crosses the border with Belgium in the south of Limburg. The first plans (“Plan Ooievaar”) were already developed in the 1980s and were highly innovative and controversial, as they were based on the idea of using nature-based solutions combined with social-economic development. Severe floodings in 1993 and 1995 came as a shock and accelerated the process to implement the associated measures. To address the multifunctionality of the river, the Grensmaas consortium was set up by public and private parties (the largest public-private partnership ever formed in the Netherlands) to have an effective, scalable and socially accepted project. However, despite the shared long term vision and the further development of plans during the process it was hard to satisfy all the goals in the long run. While stakeholders agreed on the long-term goal, the path towards that goal remains disputed and depends on the perceived status quo and urgency of the problem. Moreover, internal and external pressures and disturbances like climate change or the economic crisis influenced perception and economic conditions of stakeholders differently. In this research we will identify relevant system-processes connected to the implementation of nature-based solutions through the lens of social-ecological resilience. This knowledge will be used to co-create management plans that effectively improve the long-term resilience of the Dutch main water systems.
