Accurate localization in autonomous robots enables effective decision-making within their operating environment. Various methods have been developed to address this challenge, encompassing traditional techniques, fiducial marker utilization, and machine learning approaches. This work proposes a deep-learning …

The studies in this thesis aim to increase understanding of the effects of various characteristics of scientific news about a common chronic disease, i.e., diabetes, on the cognitive responses (e.g., emotions, attitudes, intentions) of diabetes patients. The research questions presented in this thesis …

The urban energy transition is crucial for a sustainable future. To support this transition, Digital Twins are employed in an increasing fashion, providing decision makers with data-driven insights from mainly technological perspectives. Based on a case study of a neighbourhood in a Dutch municipality, …

Accurate modeling of end-users’ decision-making behavior is crucial for validating demand response (DR) policies. However, existing models usually represent the decision-making behavior as an optimization problem, neglecting the impact of human psychology on decisions. In this paper, we propose …

Universal school-based social-emotional learning (SEL) programs target several social-emotional skills assuming a relationship between the skills and psychosocial health outcomes. However, greater insight into the relationship is required to clarify the skills that are most crucial to address. It will …

The aim of this constructive study was to develop model-based principles to provide guidance to managers and policy makers when making decisions about team size and composition in the context of home healthcare. Six model-based principles were developed based on extensive data analysis and in close interaction …

Social workers focus on changes and improvements in people’s social functioning and the social quality of society. To do so, they intervene at different levels: individuals and households (micro), groups, neighbourhoods and communities (meso), and organisations and policies (macro). Opportunities for …

The following paper refers to the final thesis for the curriculum at HZ University of Applied Science and was carried out at the request of the Italian firm Aig Associati and Partner. The structural team of the architecture and engineering firm requested a study on the most effective and least time-consuming …

The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on …

Industry 4.0 has placed an emphasis on real-time decision making in the execution of systems, such as semiconductor manufacturing. This article will evaluate a scheduling methodology called Evolutionary Learning Based Simulation Optimization (ELBSO) using data generated by a Manufacturing Execution System …