Fachbereich Wirtschaftswissenschaften
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Green infrastructure has been widely recognized for the benefits to human health and biodiversity conservation. However, knowledge of the qualities and requirements of such spaces and structures for the effective delivery of the range of ecosystem services expected is still limited, as well as the identification of trade-offs between services. In this study, we apply the One Health approach in the context of green spaces to investigate how urban park characteristics affect human mental health and wildlife support outcomes and identify synergies and trade-offs between these dimensions. Here we show that perceived restorativeness of park users varies significantly across sites and is mainly affected by safety and naturalness perceptions. In turn, these perceptions are driven by objective indicators of quality, such as maintenance of facilities and vegetation structure, and subjective estimations of biodiversity levels. The presence of water bodies benefited both mental health and wildlife. However, high tree canopy coverage provided greater restoration potential whereas a certain level of habitat heterogeneity was important to support a wider range of bird species requirements. To reconcile human and wildlife needs in green spaces, cities should strategically implement a heterogeneous green infrastructure network that considers trade-offs and maximizes synergies between these dimensions.
In recent years, eXtended Reality (XR) technology like Augmented Reality and Virtual Reality became both technically feasible as well as affordable which lead to a drastic demand of professionally designed and developed applications. However, this demand combined with a rapid pace of innovation revealed a lack of design tool support for professional interaction designers as well as a knowledge gap regarding their approaches and needs. To address this gap, this thesis engages with the work of professional XR interaction designers in a qualitative research into XR interaction design approach. Therefore, this thesis applies two complementary lenses stemming from scientific design and social practice theory discourses to observe, describe, analyze, and understand professional XR interaction designers' challenges and approaches with a focus on application prototyping.
Improved Thermal Comfort Model Leveraging Conditional Tabular GAN Focusing on Feature Selection
(2024)
The indoor thermal comfort in both homes and workplaces significantly influences the health and productivity of inhabitants. The heating system, controlled by Artificial Intelligence (AI), can automatically calibrate the indoor thermal condition by analyzing various physiological and environmental variables. To ensure a comfortable indoor environment, smart home systems can adjust parameters related to thermal comfort based on accurate predictions of inhabitants’ preferences. Modeling personal thermal comfort preferences poses two significant challenges: the inadequacy of data and its high dimensionality. An adequate amount of data is a prerequisite for training efficient machine learning (ML) models. Additionally, high-dimensional data tends to contain multiple irrelevant and noisy features, which might hinder ML models’ performance. To address these challenges, we propose a framework for predicting personal thermal comfort preferences, combining the conditional tabular generative adversarial network (CTGAN) with multiple feature selection techniques. We first address the data inadequacy challenge by applying CTGAN to generate synthetic data samples, incorporating challenges associated with multimodal distributions and categorical features. Then, multiple feature selection techniques are employed to identify the best possible sets of features. Experimental results based on a wide range of settings on a standard dataset demonstrated state-of-the-art performance in predicting personal thermal comfort preferences. The results also indicated that ML models trained on synthetic data achieved significantly better performance than models trained on real data. Overall, our method, combining CTGAN and feature selection techniques, outperformed existing known related work in thermal comfort prediction in terms of multiple evaluation metrics, including area under the curve (AUC), Cohen’s Kappa, and accuracy. Additionally, we presented a global, model-agnostic explanation of the thermal preference prediction system, providing an avenue for thermal comfort experiment designers to consciously select the data to be collected.
The Peren Theorem
(2024)
The Peren-Clement Index
(2024)
Network Analysis Method
(2024)
Dynamic Programming
(2024)
Heuristic Methods
(2024)
Sequencing Problems
(2024)
Queueing Theory
(2024)
Linear Optimization
(2024)
The Decision Tree Procedure
(2024)
In intensively used agricultural landscapes, path margins are one of the few refuges and nurseries for wildlife. They provide e. g. food sources and overwintering opportunities for many insects, serve as migration corridors for animals, protect soil from erosion, increase its water-holding capacity, and increase soil organic carbon, contributing thus directly to biodiversity conservation and climate change mitigation. Path margins are often municipally owned but used and managed by agriculture. For a path margin to be functional, certain conditions must be fulfilled, such as the width, the botanical composition, and how it is managed through the seasons. Therefore, it must be managed under specific requirements. A multifunctional path margin can be achieved only through the commitment of all stakeholders (e.g., farmers, municipalities, conservationists, and civil society).
The art of nudging
(2023)
Do simple and subtle changes in the living and study environment improve the eating behaviour of students in an educational setting? This dissertation provides a not-so-simple answer to this simple question based on the outcomes of four studies that explore the effects and design of artwork nudges (specifically the artwork of Alberto Giacometti) on the eating behaviour of students by applying different research designs. Study 1 explores the effects of a Giacometti-like nudge (a more contemporary version of the original nudge) regarding the dietary behaviour of high school students in a controlled setting. Study 2 applies different artwork nudges within a virtual vignette setting to measure their effects on virtual meal choices made. Also, the degree to which individuals were aware of the nudge’s presence is included as an influential factor in nudge effectiveness. Study 3 assesses the susceptibility to nudges as measured with a questionnaire. Susceptibility to nudges is defined as nudgeability. Study 4 assesses the effects of the original Giacometti nudge in a real-world university cafeteria setting. Specifically, the immediate and sustained effects of the original Giacometti nudge on students’ meal purchases in the university cafeteria are considered. In addition, the role of awareness of the nudge’s presence as well as the acceptance of this specific nudge are discussed. The conclusion is drawn that the original Giacometti nudge should only be applied in an educational setting to improve healthy eating behaviour if the intended target groups and environment meet certain conditions. Artwork nudges in general should be applied only after rigorous testing of various types of different nudges and more research reflecting healthy eating in its entirety.