11 Interfakultäre Einrichtungen
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/12
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Item Open Access On the accurate estimation of information-theoretic quantities from multi-dimensional sample data(2024) Álvarez Chaves, Manuel; Gupta, Hoshin V.; Ehret, Uwe; Guthke, AnneliUsing information-theoretic quantities in practical applications with continuous data is often hindered by the fact that probability density functions need to be estimated in higher dimensions, which can become unreliable or even computationally unfeasible. To make these useful quantities more accessible, alternative approaches such as binned frequencies using histograms and k -nearest neighbors ( k -NN) have been proposed. However, a systematic comparison of the applicability of these methods has been lacking. We wish to fill this gap by comparing kernel-density-based estimation (KDE) with these two alternatives in carefully designed synthetic test cases. Specifically, we wish to estimate the information-theoretic quantities: entropy, Kullback–Leibler divergence, and mutual information, from sample data. As a reference, the results are compared to closed-form solutions or numerical integrals. We generate samples from distributions of various shapes in dimensions ranging from one to ten. We evaluate the estimators’ performance as a function of sample size, distribution characteristics, and chosen hyperparameters. We further compare the required computation time and specific implementation challenges. Notably, k -NN estimation tends to outperform other methods, considering algorithmic implementation, computational efficiency, and estimation accuracy, especially with sufficient data. This study provides valuable insights into the strengths and limitations of the different estimation methods for information-theoretic quantities. It also highlights the significance of considering the characteristics of the data, as well as the targeted information-theoretic quantity when selecting an appropriate estimation technique. These findings will assist scientists and practitioners in choosing the most suitable method, considering their specific application and available data. We have collected the compared estimation methods in a ready-to-use open-source Python 3 toolbox and, thereby, hope to promote the use of information-theoretic quantities by researchers and practitioners to evaluate the information in data and models in various disciplines.Item Open Access Willingness to pay for digital wellbeing features on social network sites : a study with Arab and European samples(2024) Alshakhsi, Sameha; Babiker, Areej; Sindermann, Cornelia; Al-Thani, Dena; Montag, Christian; Ali, RaianIn recent years, concerns over the potential negative impacts of social network sites (SNS) on users’ digital wellbeing are on the rise. These concerns have sparked a growing demand for SNS to introduce changes to their business model and offer features that prioritize users’ wellbeing, even if it means introducing fees to users. Still, it is questionable whether such a new model is welcomed by users and commercially valid. In this paper, we investigate (i) people’s willingness to pay (WTP) for digital wellbeing services designed to foster more autonomy, control, and personal growth in users and (ii) the influence of sociodemographic variables, personality, and social networks use disorder (SNUD) on WTP. Data were collected through an online survey with participants from two distinct cultural contexts, the European and Arabic. The samples comprised 262 participants from Europe (Males: 57.63%) and 251 from Arab countries (Males: 60.56%). The participants ranged in age from 18 to 66 years (MEurope = 29.16, SD = 8.42; MArab = 31.24, SD = 8.23). The results revealed that a notable proportion of participants were willing to pay for digital wellbeing services (Europe: 24%; Arab: 30%). Females in the European sample demonstrated a higher WTP for “Mental Health Issues Minimization” compared to males. In the Arab sample, males showed a higher WTP for “Safeguarding Data Privacy” than females. Multiple regression analyses revealed that SNUD and the need for cognition emerged as significant and positive predictors of WTP in both the European and Arab samples. Differences in the relations of personality traits and sociodemographic variables on WTP in each sample were noted. These insights contribute to our understanding of the factors shaping individuals’ preferences and valuation related to digital wellbeing services on SNS and highlight the importance of considering sociodemographic variables and personal factors as well as cultural contexts when planning and introducing them.Item Open Access Uncharted water conflicts ahead : mapping the scenario space for Germany in the year 2050(2024) Kosow, Hannah; Brauner, Simon; Brumme, Anja; Hauser, Wolfgang; Hölzlberger, Fabian; Moschner, Janina; Rübbelke, Dirk; Vögele, Stefan; Weimer-Jehle, WolfgangIntroduction: In recent years, conflicts surrounding the use, distribution, and governance of surface water and groundwater in Germany have gained prominence in the media, on the political agenda, and in research. Increasing effects of climate change, such as heatwaves and drought but also extreme rain events and flooding, are considered to become more prominent and pressing in the future by different societal actors. However, it remains highly uncertain if and what type of conflicts related to water quantity Germany might actually face in the future (and how they will be framed). This paper addresses one dimension of this uncertainty - namely the future context uncertainty of possible resource and water governance conflicts. Our research contributes to an improved understanding of the uncertainty concerning future climatic, natural, land use related, political, economic, and other societal contexts that could impact water conflicts. Method: We ask: What are possible coherent context scenarios for Germany in the year 2050, and how are they expected to influence future water conflicts? In an expert-based process, we apply a qualitative and systematic method of systems analysis, cross-impact balances (CIB). With CIB, we build internally consistent scenarios of possible futures and map the future scenario space. Results and discussion: Diversity mapping with a new CIB web application of the ScenarioWizard reveals that the scenario space is rather large and diverse. The identified scenario space of n = 355 internally consistent scenarios spans four most diverse scenarios “Polycrisis,” “Economy and agriculture in crisis,” “Growth through adaptation to climate change,” and “Sustainable transformation.” Depending on the development of future contexts, the risk for future water resource and governance conflicts may unfold in various ways. We conclude that our scenario analysis provides a useful base for research and practice to address the context uncertainty of water conflicts in Germany. Our results can be used for risk assessment, to define societal framework assumptions for societal-hydrological modeling, and to develop robust and adaptive strategies and policies.Item Open Access Learning soft millirobot multimodal locomotion with sim‐to‐real transfer(2024) Demir, Sinan Ozgun; Tiryaki, Mehmet Efe; Karacakol, Alp Can; Sitti, MetinWith wireless multimodal locomotion capabilities, magnetic soft millirobots have emerged as potential minimally invasive medical robotic platforms. Due to their diverse shape programming capability, they can generate various locomotion modes, and their locomotion can be adapted to different environments by controlling the external magnetic field signal. Existing adaptation methods, however, are based on hand‐tuned signals. Here, a learning‐based adaptive magnetic soft millirobot multimodal locomotion framework empowered by sim‐to‐real transfer is presented. Developing a data‐driven magnetic soft millirobot simulation environment, the periodic magnetic actuation signal is learned for a given soft millirobot in simulation. Then, the learned locomotion strategy is deployed to the real world using Bayesian optimization and Gaussian processes. Finally, automated domain recognition and locomotion adaptation for unknown environments using a Kullback‐Leibler divergence‐based probabilistic method are illustrated. This method can enable soft millirobot locomotion to quickly and continuously adapt to environmental changes and explore the actuation space for unanticipated solutions with minimum experimental cost.Item Open Access To bucket or not to bucket? : analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization(2024) Acuña Espinoza, Eduardo; Loritz, Ralf; Álvarez Chaves, Manuel; Bäuerle, Nicole; Ehret, UweHydrological hybrid models have been proposed as an option to combine the enhanced performance of deep learning methods with the interpretability of process-based models. Among the various hybrid methods available, the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks has shown high potential. We explored this method further to evaluate specifically if the flexibility given by the dynamic parameterization overwrites the physical interpretability of the process-based part. We conducted our study using a subset of the CAMELS-GB dataset. First, we show that the hybrid model can reach state-of-the-art performance, comparable with LSTM, and surpassing the performance of conceptual models in the same area. We then modified the conceptual model structure to assess if the dynamic parameterization can compensate for structural deficiencies of the model. Our results demonstrated that the deep learning method can effectively compensate for these deficiencies. A model selection technique based purely on the performance to predict streamflow, for this type of hybrid model, is hence not advisable. In a second experiment, we demonstrated that if a well-tested model architecture is combined with an LSTM, the deep learning model can learn to operate the process-based model in a consistent manner, and untrained variables can be recovered. In conclusion, for our case study, we show that hybrid models cannot surpass the performance of data-driven methods, and the remaining advantage of such models is the access to untrained variables.Item Open Access Mapping the ethics of generative AI : a comprehensive scoping review(2024) Hagendorff, ThiloThe advent of generative artificial intelligence and the widespread adoption of it in society engendered intensive debates about its ethical implications and risks. These risks often differ from those associated with traditional discriminative machine learning. To synthesize the recent discourse and map its normative concepts, we conducted a scoping review on the ethics of generative artificial intelligence, including especially large language models and text-to-image models. Our analysis provides a taxonomy of 378 normative issues in 19 topic areas and ranks them according to their prevalence in the literature. The study offers a comprehensive overview for scholars, practitioners, or policymakers, condensing the ethical debates surrounding fairness, safety, harmful content, hallucinations, privacy, interaction risks, security, alignment, societal impacts, and others. We discuss the results, evaluate imbalances in the literature, and explore unsubstantiated risk scenarios.Item Open Access Semi-explicit integration of second order for weakly coupled poroelasticity(2024) Altmann, R.; Maier, R.; Unger, B.We introduce a semi-explicit time-stepping scheme of second order for linear poroelasticity satisfying a weak coupling condition. Here, semi-explicit means that the system, which needs to be solved in each step, decouples and hence improves the computational efficiency. The construction and the convergence proof are based on the connection to a differential equation with two time delays, namely one and two times the step size. Numerical experiments confirm the theoretical results and indicate the applicability to higher-order schemes.Item Open Access Higher-order iterative decoupling for poroelasticity(2024) Altmann, Robert; Mujahid, Abdullah; Unger, BenjaminFor the iterative decoupling of elliptic–parabolic problems such as poroelasticity, we introduce time discretization schemes up to order five based on the backward differentiation formulae. Its analysis combines techniques known from fixed-point iterations with the convergence analysis of the temporal discretization. As the main result, we show that the convergence depends on the interplay between the time step size and the parameters for the contraction of the iterative scheme. Moreover, this connection is quantified explicitly, which allows for balancing the single error components. Several numerical experiments illustrate and validate the theoretical results, including a three-dimensional example from biomechanics.Item Open Access Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events(2025) Acuña Espinoza, Eduardo; Loritz, Ralf; Kratzert, Frederik; Klotz, Daniel; Gauch, Martin; Álvarez Chaves, Manuel; Ehret, UweData-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulation. Recently, hybrid models, which combine data-driven methods with process-based approaches, have been proposed to leverage the strengths of both methodologies, aiming to enhance simulation accuracy while maintaining a certain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events, comparing their performance against long short-term memory (LSTM) networks and process-based models. Our results indicate that hybrid models show performance similar to that of the LSTM network for most cases. However, hybrid models reported slightly lower errors in the most extreme cases and were able to produce higher peak discharges.Item Open Access Assessing the immediate effects of detached mindfulness on repetitive negative thinking and affect in daily life : a randomized controlled trial(2024) Bolzenkötter, Teresa; Bürkner, Paul-Christian; Zetsche, Ulrike; Schulze, LarsObjectives. Repetitive negative thinking (RNT) is a problematic thinking style that is related to multiple mental disorders. Detached mindfulness is a technique of metacognitive therapy that aims to reduce RNT. Our study set out to investigate the immediate effects of detached mindfulness in daily life. Methods. Participants with elevated trait RNT ( n = 50) were prompted to engage in detached mindfulness exercises three times a day for 5 consecutive days. Immediate effects on RNT and affect were assessed 15 and 30 min after each exercise using experience sampling methodology. We compared the effects of this exercise phase to (1) a 5-day non-exercise baseline phase and (2) a different group of participants that engaged in an active control exercise ( n = 50). Results. Results of Bayesian multilevel models showed that, across groups, improvements in RNT, negative affect, and positive affect were stronger during the exercise phase than during the non-exercise baseline phase (RNT after 15 min: b = -0.26, 95% CI = [-0.38, -0.14]). However, the two exercise groups did not differ in these improvements (RNT after 15 min: b = 0.02, 95% CI = [-0.22, 0.27]). Thus, the detached mindfulness and the active control exercises resulted in similar effects on RNT and affect in daily life. Conclusions. Results of this study imply that there was no additional benefit of having participants observe their thoughts detached and non-judgmentally, compared to excluding these assumed mechanisms of action as done for the active control group. We discuss possible reasons for the non-difference between the groups.