This article provides a detailed explanation of the BBQ-Tree, a unified logic-based model that integrates both classical Decision Trees and Quantum-Logic Decision Trees into a generalized framework for classification and regression. As it combines these paradigms, the BBQ-Tree effectively addresses problems with both linear and curved decision boundaries while prioritizing interpretability. We provide a detailed description of the underlying concepts, a possible training algorithm, experimental evaluations and the incorporation of regression functionality, broadening its applicability beyond classification tasks. Strategies for efficient training and model optimization are also presented. Experimental results demonstrate that the BBQ-Tree produces compact, interpretable models capable of revealing data trends, while achieving accuracy comparable to Decision Trees. Furthermore, its new regression capabilities highlight its versatility and performance across a wider range of tasks.

The integration of multi-sensory stimuli, e.g. haptic airflow, in virtual reality (VR) has become an important topic of VR research and proved to enhance the feeling of presence. VaiR focuses on an accurate and realistic airflow simulation that goes far beyond wind. While previous works on the topic of airflow in VR are restricted to wind, while focusing on the feeling of presence, there is to the best of our knowledge no work considering the conceptual background or on the various application areas. Our pneumatic prototype emits short and long term flows with a minimum delay and is able to animate wind sources in 3D space around the user's head. To get insights on how airflow can be used in VR and how such a device should be designed, we arranged focus groups and discussed the topic. Based on the gathered knowledge, we developed a prototype which proved to increase presence, as well as enjoyment and realism, while not disturbing the VR experience.