05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
Browse
126 results
Search Results
Item Open Access Endowing a NAO robot with practical social-touch perception(2022) Burns, Rachael Bevill; Lee, Hyosang; Seifi, Hasti; Faulkner, Robert; Kuchenbecker, Katherine J.Social touch is essential to everyday interactions, but current socially assistive robots have limited touch-perception capabilities. Rather than build entirely new robotic systems, we propose to augment existing rigid-bodied robots with an external touch-perception system. This practical approach can enable researchers and caregivers to continue to use robotic technology they have already purchased and learned about, but with a myriad of new social-touch interactions possible. This paper presents a low-cost, easy-to-build, soft tactile-perception system that we created for the NAO robot, as well as participants’ feedback on touching this system. We installed four of our fabric-and-foam-based resistive sensors on the curved surfaces of a NAO’s left arm, including its hand, lower arm, upper arm, and shoulder. Fifteen adults then performed five types of affective touch-communication gestures (hitting, poking, squeezing, stroking, and tickling) at two force intensities (gentle and energetic) on the four sensor locations; we share this dataset of four time-varying resistances, our sensor patterns, and a characterization of the sensors’ physical performance. After training, a gesture-classification algorithm based on a random forest identified the correct combined touch gesture and force intensity on windows of held-out test data with an average accuracy of 74.1%, which is more than eight times better than chance. Participants rated the sensor-equipped arm as pleasant to touch and liked the robot’s presence significantly more after touch interactions. Our promising results show that this type of tactile-perception system can detect necessary social-touch communication cues from users, can be tailored to a variety of robot body parts, and can provide HRI researchers with the tools needed to implement social touch in their own systems.Item Open Access Client aware adaptive federated learning using UCB-based reinforcement for people re-identification(2025) Waref, Dinah; Alayary, Yomna; Fathallah, Nadeen; Abd El Ghany, Mohamed A.; Salem, Mohammed A.-M.People re-identification enables locating and identifying individuals across different camera views in surveillance environments. The surveillance data contains personally identifiable information such as facial images, behavioral patterns, and location data, which can be used for malicious purposes such as identity theft, stalking, or discrimination. This raises serious ethical and privacy concerns. The communication overhead of transporting a large number of data needed to train a global model and the diverse nature of the data from different sources are serious limitations facing the development of people re-identification technologies. We address these challenges by proposing a novel three-step federated learning framework. First, we investigate the impact of data augmentation techniques on the model generalizability and explore the effectiveness of different backbone networks. Second, we use reinforcement learning-based Upper Confidence Bounds (UCB) as a client-selection strategy in the federated round that dynamically chooses devices similar to the current model state, ensuring the model is updated with relevant data and enables faster convergence. Finally, we introduce a feature-level attention mechanism focusing on discriminative features for re-identification. Extensive experiments were conducted on nine benchmark re-ID datasets. The proposed framework outperformed the federated re-ID baseline by 10% in rank-1 accuracy and achieved results comparable to the centralized approach, with a difference of 2%. This improvement over the previous state-of-the-art establishes a new benchmark for federated re-identification.Item Open Access Advances in clinical voice quality analysis with VOXplot(2023) Barsties von Latoszek, Ben; Mayer, Jörg; Watts, Christopher R.; Lehnert, BernhardBackground: The assessment of voice quality can be evaluated perceptually with standard clinical practice, also including acoustic evaluation of digital voice recordings to validate and further interpret perceptual judgments. The goal of the present study was to determine the strongest acoustic voice quality parameters for perceived hoarseness and breathiness when analyzing the sustained vowel [a:] using a new clinical acoustic tool, the VOXplot software. Methods: A total of 218 voice samples of individuals with and without voice disorders were applied to perceptual and acoustic analyses. Overall, 13 single acoustic parameters were included to determine validity aspects in relation to perceptions of hoarseness and breathiness. Results: Four single acoustic measures could be clearly associated with perceptions of hoarseness or breathiness. For hoarseness, the harmonics-to-noise ratio (HNR) and pitch perturbation quotient with a smoothing factor of five periods (PPQ5), and, for breathiness, the smoothed cepstral peak prominence (CPPS) and the glottal-to-noise excitation ratio (GNE) were shown to be highly valid, with a significant difference being demonstrated for each of the other perceptual voice quality aspects. Conclusions: Two acoustic measures, the HNR and the PPQ5, were both strongly associated with perceptions of hoarseness and were able to discriminate hoarseness from breathiness with good confidence. Two other acoustic measures, the CPPS and the GNE, were both strongly associated with perceptions of breathiness and were able to discriminate breathiness from hoarseness with good confidence.Item Open Access Subjective annotation for a frame interpolation benchmark using artefact amplification(2020) Men, Hui; Hosu, Vlad; Lin, Hanhe; Bruhn, Andrés; Saupe, DietmarCurrent benchmarks for optical flow algorithms evaluate the estimation either directly by comparing the predicted flow fields with the ground truth or indirectly by using the predicted flow fields for frame interpolation and then comparing the interpolated frames with the actual frames. In the latter case, objective quality measures such as the mean squared error are typically employed. However, it is well known that for image quality assessment, the actual quality experienced by the user cannot be fully deduced from such simple measures. Hence, we conducted a subjective quality assessment crowdscouring study for the interpolated frames provided by one of the optical flow benchmarks, the Middlebury benchmark. It contains interpolated frames from 155 methods applied to each of 8 contents. For this purpose, we collected forced-choice paired comparisons between interpolated images and corresponding ground truth. To increase the sensitivity of observers when judging minute difference in paired comparisons we introduced a new method to the field of full-reference quality assessment, called artefact amplification. From the crowdsourcing data (3720 comparisons of 20 votes each) we reconstructed absolute quality scale values according to Thurstone’s model. As a result, we obtained a re-ranking of the 155 participating algorithms w.r.t. the visual quality of the interpolated frames. This re-ranking not only shows the necessity of visual quality assessment as another evaluation metric for optical flow and frame interpolation benchmarks, the results also provide the ground truth for designing novel image quality assessment (IQA) methods dedicated to perceptual quality of interpolated images. As a first step, we proposed such a new full-reference method, called WAE-IQA, which weights the local differences between an interpolated image and its ground truth.Item Open Access On the impact of service-oriented patterns on software evolvability: a controlled experiment and metric-based analysis(2019) Bogner, Justus; Wagner, Stefan; Zimmermann, AlfredBackground: Design patterns are supposed to improve various quality attributes of software systems. However, there is controversial quantitative evidence of this impact. Especially for younger paradigms such as service- and Microservice-based systems, there is a lack of empirical studies. Objective: In this study, we focused on the effect of four service-based patterns - namely Process Abstraction, Service Façade, Decomposed Capability, and Event-Driven Messaging - on the evolvability of a system from the viewpoint of inexperienced developers. Method: We conducted a controlled experiment with Bachelor students (N = 69). Two functionally equivalent versions of a service-based web shop - one with patterns (treatment group), one without (control group) - had to be changed and extended in three tasks. We measured evolvability by the effectiveness and efficiency of the participants in these tasks. Additionally, we compared both system versions with nine structural maintainability metrics for size, granularity, complexity, cohesion, and coupling. Results: Both experiment groups were able to complete a similar number of tasks within the allowed 90 min. Median effectiveness was 1/3. Mean efficiency was 12% higher in the treatment group, but this difference was not statistically significant. Only for the third task, we found statistical support for accepting the alternative hypothesis that the pattern version led to higher efficiency. In the metric analysis, the pattern version had worse measurements for size and granularity while simultaneously having slightly better values for coupling metrics. Complexity and cohesion were not impacted. Interpretation: For the experiment, our analysis suggests that the difference in efficiency is stronger with more experienced participants and increased from task to task. With respect to the metrics, the patterns introduce additional volume in the system, but also seem to decrease coupling in some areas. Conclusions: Overall, there was no clear evidence for a decisive positive effect of using service-based patterns, neither for the student experiment nor for the metric analysis. This effect might only be visible in an experiment setting with higher initial effort to understand the system or with more experienced developers.Item Open Access Small delay fault testing with multiple voltages under variations : defect vs. fault coverage(2025) Jafarzadeh, Hanieh; Klemme, Florian; Amrouch, Hussam; Hellebrand, Sybille; Wunderlich, Hans-JoachimIt has been known and explored for many years that low voltage testing amplifies the effect of a defect, increasing the size of a Small Delay Fault (SDF) and, in the best case, turning SDFs into easily detectable stuck-at-faults. It is often overlooked that Vmintesting poses an additional challenge to the test pattern generation method under process variations. The standard deviation of gate delays under Vminis a multiple of that under nominal voltage. The increased variation will invalidate the efficiency of test patterns generated under nominal voltage and significantly reduce fault coverage. This paper presents the first algorithm for test pattern generation specifically tuned for Vmintesting which obtains higher fault coverage by smaller test sets than those generated for nominal voltage. The patterns applicable to other voltage levels can be derived from the pattern set generated under extreme variations at low supply voltage. Experimental results demonstrate that the proposed method produces test patterns that outperform N-detection test sets in terms of test set volume and fault efficiency across different voltage levels.Item Open Access Cross-lingual citations in English papers : a large-scale analysis of prevalence, usage, and impact(2021) Saier, Tarek; Färber, Michael; Tsereteli, TornikeCitation information in scholarly data is an important source of insight into the reception of publications and the scholarly discourse. Outcomes of citation analyses and the applicability of citation-based machine learning approaches heavily depend on the completeness of such data. One particular shortcoming of scholarly data nowadays is that non-English publications are often not included in data sets, or that language metadata is not available. Because of this, citations between publications of differing languages (cross-lingual citations) have only been studied to a very limited degree. In this paper, we present an analysis of cross-lingual citations based on over one million English papers, spanning three scientific disciplines and a time span of three decades. Our investigation covers differences between cited languages and disciplines, trends over time, and the usage characteristics as well as impact of cross-lingual citations. Among our findings are an increasing rate of citations to publications written in Chinese, citations being primarily to local non-English languages, and consistency in citation intent between cross- and monolingual citations. To facilitate further research, we make our collected data and source code publicly available.Item Open Access Uncertainty quantification and propagation in surrogate-based Bayesian inference(2025) Reiser, Philipp; Aguilar, Javier Enrique; Guthke, Anneli; Bürkner, Paul-ChristianSurrogate models are statistical or conceptual approximations for more complex simulation models. In this context, it is crucial to propagate the uncertainty induced by limited simulation budget and surrogate approximation error to predictions, inference, and subsequent decision-relevant quantities. However, quantifying and then propagating the uncertainty of surrogates is usually limited to special analytic cases or is otherwise computationally very expensive. In this paper, we propose a framework enabling a scalable, Bayesian approach to surrogate modeling with thorough uncertainty quantification, propagation, and validation. Specifically, we present three methods for Bayesian inference with surrogate models given measurement data. This is a task where the propagation of surrogate uncertainty is especially relevant, because failing to account for it may lead to biased and/or overconfident estimates of the parameters of interest. We showcase our approach in three detailed case studies for linear and nonlinear real-world modeling scenarios. Uncertainty propagation in surrogate models enables more reliable and safe approximation of expensive simulators and will therefore be useful in various fields of applications.Item Open Access Benchmarking the performance of portfolio optimization with QAOA(2022) Brandhofer, Sebastian; Braun, Daniel; Dehn, Vanessa; Hellstern, Gerhard; Hüls, Matthias; Ji, Yanjun; Polian, Ilia; Bhatia, Amandeep Singh; Wellens, ThomasWe present a detailed study of portfolio optimization using different versions of the quantum approximate optimization algorithm (QAOA). For a given list of assets, the portfolio optimization problem is formulated as quadratic binary optimization constrained on the number of assets contained in the portfolio. QAOA has been suggested as a possible candidate for solving this problem (and similar combinatorial optimization problems) more efficiently than classical computers in the case of a sufficiently large number of assets. However, the practical implementation of this algorithm requires a careful consideration of several technical issues, not all of which are discussed in the present literature. The present article intends to fill this gap and thereby provides the reader with a useful guide for applying QAOA to the portfolio optimization problem (and similar problems). In particular, we will discuss several possible choices of the variational form and of different classical algorithms for finding the corresponding optimized parameters. Viewing at the application of QAOA on error-prone NISQ hardware, we also analyse the influence of statistical sampling errors (due to a finite number of shots) and gate and readout errors (due to imperfect quantum hardware). Finally, we define a criterion for distinguishing between ‘easy’ and ‘hard’ instances of the portfolio optimization problem.Item Open Access Int-HRL : towards intention-based hierarchical reinforcement learning(2024) Penzkofer, Anna; Schaefer, Simon; Strohm, Florian; Bâce, Mihai; Leutenegger, Stefan; Bulling, AndreasWhile deep reinforcement learning (RL) agents outperform humans on an increasing number of tasks, training them requires data equivalent to decades of human gameplay. Recent hierarchical RL methods have increased sample efficiency by incorporating information inherent to the structure of the decision problem but at the cost of having to discover or use human-annotated sub-goals that guide the learning process. We show that intentions of human players, i.e. the precursor of goal-oriented decisions, can be robustly predicted from eye gaze even for the long-horizon sparse rewards task of Montezuma’s Revenge-one of the most challenging RL tasks in the Atari2600 game suite. We propose Int-HRL : Hierarchical RL with intention-based sub-goals that are inferred from human eye gaze. Our novel sub-goal extraction pipeline is fully automatic and replaces the need for manual sub-goal annotation by human experts. Our evaluations show that replacing hand-crafted sub-goals with automatically extracted intentions leads to an HRL agent that is significantly more sample efficient than previous methods.