05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Sharp MIR plasmonic modes in gratings made of heavily doped pulsed laser-melted Ge1-xSnx(2023) Berkmann, Fritz; Steuer, Oliver; Ganss, Fabian; Prucnal, Slawomir; Schwarz, Daniel; Fischer, Inga Anita; Schulze, JörgItem Open Access Additively manufactured transverse flux machine components with integrated slits for loss reduction(2022) Kresse, Thomas; Schurr, Julian; Lanz, Maximilian; Kunert, Torsten; Schmid, Martin; Parspour, Nejila; Schneider, Gerhard; Goll, DagmarLaser powder bed fusion (L-PBF) was used to produce stator half-shells of a transverse flux machine from pure iron (99.9% Fe). In order to reduce iron losses in the bulk components, radially extending slits with a nominal width of 150 and 300 µm, respectively, were integrated during manufacturing. The components were subjected to a suitable heat treatment. In addition to a microscopic examination of the slit quality, the iron losses were also measured using both a commercial and a self-developed measurement setup. The investigations showed the iron losses can be reduced by up to 49% due to the integrated slits and the heat treatment.Item Open Access Modeling and experimental investigation of the interaction between pressure-dependent aging and pressure development due to the aging of lithium-ion cells(2023) Avdyli, Arber; Fill, Alexander; Birke, Kai PeterIn order to meet the increasing demands of the battery in terms of range, safety and performance, it is necessary to ensure optimal operation conditions of a lithium-ion cell. In this thesis, the influence of mechanical boundary conditions on the cell is investigated theoretically and experimentally. First, fundamental equations are derived that lead to coupled models that can be parameterized based on specific cell measurements and predict the pressure evolution due to capacity aging and vice versa. The model is used to derive optimal operating points of the cell, which can be considered in the module design.Item Open Access Surface charge density and induced currents by self-charging sliding drops(2024) Bista, Pravash; Ratschow, Aaron D.; Stetten, Amy Z.; Butt, Hans-Jürgen; Weber, Stefan A. L.Spontaneous charge separation in drops sliding over a hydrophobized insulator surface is a well-known phenomenon and lots of efforts have been made to utilize this effect for energy harvesting. For maximizing the efficiency of such devices, a comprehensive understanding of the dewetted surface charge would be required to quantitatively predict the electric current signals, in particular for drop sequences. Here, we use a method based on mirror charge detection to locally measure the surface charge density after drops move over a hydrophobic surface. For this purpose, we position a metal electrode beneath the hydrophobic substrate to measure the capacitive current induced by the moving drop. Furthermore, we investigate drop-induced charging on different dielectric surfaces together with the surface neutralization processes. The surface neutralizes over a characteristic time, which is influenced by the substrate and the surrounding environment. We present an analytical model that describes the slide electrification using measurable parameters such as the surface charge density and its neutralization time. Understanding the model parameters and refining them will enable a targeted optimization of the efficiency in solid–liquid charge separation.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 Distributional measures of semantic abstraction(2022) Schulte im Walde, Sabine; Frassinelli, DiegoThis article provides an in-depth study of distributional measures for distinguishing between degrees of semantic abstraction. Abstraction is considered a “central construct in cognitive science” (Barsalou, 2003) and a “process of information reduction that allows for efficient storage and retrieval of central knowledge” (Burgoon et al., 2013). Relying on the distributional hypothesis, computational studies have successfully exploited measures of contextual co-occurrence and neighbourhood density to distinguish between conceptual semantic categorisations. So far, these studies have modeled semantic abstraction across lexical-semantic tasks such as ambiguity; diachronic meaning changes; abstractness vs. concreteness; and hypernymy. Yet, the distributional approaches target different conceptual types of semantic relatedness, and as to our knowledge not much attention has been paid to apply, compare or analyse the computational abstraction measures across conceptual tasks. The current article suggests a novel perspective that exploits variants of distributional measures to investigate semantic abstraction in English in terms of the abstract-concrete dichotomy (e.g., glory-banana) and in terms of the generality-specificity distinction (e.g., animal-fish), in order to compare the strengths and weaknesses of the measures regarding categorisations of abstraction, and to determine and investigate conceptual differences. In a series of experiments we identify reliable distributional measures for both instantiations of lexical-semantic abstraction and reach a precision higher than 0.7, but the measures clearly differ for the abstract-concrete vs. abstract-specific distinctions and for nouns vs. verbs. Overall, we identify two groups of measures, (i) frequency and word entropy when distinguishing between more and less abstract words in terms of the generality-specificity distinction, and (ii) neighbourhood density variants (especially target-context diversity) when distinguishing between more and less abstract words in terms of the abstract-concrete dichotomy. We conclude that more general words are used more often and are less surprising than more specific words, and that abstract words establish themselves empirically in semantically more diverse contexts than concrete words. Finally, our experiments once more point out that distributional models of conceptual categorisations need to take word classes and ambiguity into account: results for nouns vs. verbs differ in many respects, and ambiguity hinders fine-tuning empirical observations.Item Open Access Electrically detected magnetic resonance on a chip (EDMRoC) for analysis of thin-film silicon photovoltaics(2023) Segantini, Michele; Marcozzi, Gianluca; Djekic, Denis; Chu, Anh; Amkreutz, Daniel; Trinh, Cham Thi; Neubert, Sebastian; Stannowski, Bernd; Jacob, Kerstin; Rudolph, Ivo; McPeak, Joseph E.; Anders, Jens; Naydenov, Boris; Lips, KlausElectrically detected magnetic resonance (EDMR) is a spectroscopic technique that provides information about the physical properties of materials through the detection of variations in conductivity induced by spin-dependent processes. EDMR has been widely applied to investigate thin-film semiconductor materials in which the presence of defects can induce the current limiting processes. Conventional EDMR measurements are performed on samples with a special geometry that allows the use of a typical electron paramagnetic resonance (EPR) resonator. For such measurements, it is of utmost importance that the geometry of the sample under assessment does not influence the results of the experiment. Here, we present a single-board EPR spectrometer using a chip-integrated, voltage-controlled oscillator (VCO) array as a planar microwave source, whose geometry optimally matches that of a standard EDMR sample, and which greatly facilitates electrical interfacing to the device under assessment. The probehead combined an ultrasensitive transimpedance amplifier (TIA) with a twelve-coil array, VCO-based, single-board EPR spectrometer to permit EDMR-on-a-Chip (EDMRoC) investigations. EDMRoC measurements were performed at room temperature on a thin-film hydrogenated amorphous silicon (a-Si:H) pin solar cell under dark and forward bias conditions, and the recombination current driven by the a-Si:H dangling bonds (db) was detected. These experiments serve as a proof of concept for a new generation of small and versatile spectrometers that allow in situ and operando EDMR experiments.Item Open Access ILP-based resource optimization realized by quantum annealing for optical wide-area communication networks : a framework for solving combinatorial problems of a real-world application by quantum annealing(2024) Witt, Arthur; Kim, Jangho; Körber, Christopher; Luu, ThomasResource allocation of wide-area internet networks is inherently a combinatorial optimization problem that if solved quickly, could provide near real-time adaptive control of internet-protocol traffic ensuring increased network efficacy and robustness, while minimizing energy requirements coming from power-hungry transceivers. In recent works we demonstrated how such a problem could be cast as a quadratic unconstrained binary optimization (QUBO) problem that can be embedded onto the D-Wave Advantage™ quantum annealer system, demonstrating proof of principle. Our initial studies left open the possibility for improvement of D-Wave solutions via judicious choices of system run parameters. Here we report on our investigations for optimizing these system parameters, and how we incorporate machine learning (ML) techniques to further improve on the quality of solutions. In particular, we use the Hamming distance to investigate correlations between various system-run parameters and solution vectors. We then apply a decision tree neural network (NN) to learn these correlations, with the goal of using the neural network to provide further guesses to solution vectors. We successfully implement this NN in a simple integer linear programming (ILP) example, demonstrating how the NN can fully map out the solution space that was not captured by D-Wave. We find, however, for the 3-node network problem the NN is not able to enhance the quality of space of solutions.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 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.