Exploring the influence of perceived extroversion in embodied virtual agents on trust and likability

Embodied virtual agents (EVAs) are beginning to be researched to improve human–computer interaction. As EVAs become increasingly integrated into various aspects of daily life, understanding how to optimize their design to foster trust and likability among users is paramount. Leveraging insights from social psychology, particularly the concept of homophily, this study investigates the impact of perceived personality traits on user perceptions of EVAs. Specifically, we explore whether aligning the personality traits of EVAs with those of users increases engagement and fosters positive interactions. Drawing on a sample of 382 participants recruited through Amazon Mechanical Turk, we assessed participants' personality traits using the Big Five Inventory—2S, while the perceived extroversion of the agent was manipulated through facial expressions and body posture. Our findings suggest that participants were able to accurately identify the perceived extroversion of the agent (p = .014), and significant results indicate a homophily effect on trust, with participants exhibiting greater trust in agents perceived as having a similar level of extroversion (p < .01). However, no significant effect on likability was detected, suggesting a more nuanced relationship between perceived personality traits and user preferences. These findings highlight the potential of leveraging homophily in designing more engaging EVAs and underscore the importance of considering user–agent compatibility in human–computer interaction

Classifying sediments on Dutch riverbeds using multi-beam echo-sounder systems

The economic importance of the Dutch rivers is very high as they are heavily used for inland waterway transport between the Netherlands and their neighbouring countries. A minimum depth must be guaranteed to keep the rivers navigable but also to ensure that the ships can carry maximum cargo. An attractive system for obtaining information about the riverbed bathymetry is the multi-beam echo-sounder (MBES). Furthermore, the MBES received echoes due to acoustic backscatter from the sediments in theory also allow for discriminating between different sediments. The aim of the research presented in this thesis was to develop methods for discriminating between different river sediments using MBES measurements. In order to fulfil this aim, MBES surveys were performed in the Rhine river and the Meuse river between 2007 and 2010. The research shows that indeed the MBES system can be used for discriminating between the different sediments present in the river areas. In addition an important finding is that areas differing in sediment type require different classification approaches.Air Transport and OperationsAerospace Engineerin