Navigationen: Tech | Demo (Navigationen - Zeitschrift für Medien- und Kulturwissenschaften)
Keywords: tech demo; technology demonstration; demo or die

PSΦ: Entwicklung von Unterstützungsmaßnahmen für Theoretische Physik - Abbas, Nilab; Bauer, Anna Brigitte; Reinhold, Peter (Lernen, Lehren und Forschen in einer digital geprägten Welt)

PSФ: Entwicklung einer abgestimmten Studieneingangsphase (Physik) - Bauer, Anna Brigitte; Reinhold, Peter (Lernen, Lehren und Forschen in einer digital geprägten Welt)

Diquat Based Dyes: A New Class of Photoredox Catalysts and Their Use in Aerobic Thiocyanation - Meier, Armin; Badalov, Sabuhi; Biktagirov, Timur; Schmidt, Wolf Gero; Wilhelm, René (Chemistry – A European Journal)
A series of new organic donor–π–acceptor dyes incorporating a diquat moiety as a novel electron-acceptor unit have been synthesized and characterized. The analytical data were supported by DFT calculations. These dyes were explored in the aerobic thiocyanation of indoles and pyrroles. Here they showed a high photocatalytic activity under visible light, giving isolated yields of up to 97 %. In addition, the photocatalytic activity of standalone diquat and methyl viologen through formation of an electron donor acceptor complex is presented.
Keywords: General Chemistry; Catalysis; Organic Chemistry

Rutile, anatase, brookite and titania thin film from Hubbard corrected and hybrid DFT - Badalov, Sabuhi; Bocchini, Adriana; Wilhelm, Rene; Kozub, A. L.; Gerstmann, Uwe; Schmidt, Wolf Gero (Materials Research Express)
As a benchmark, the structural, electronic and optical properties of the three main phases of TiO$\rm{_2}$ crystals have been calculated using Hubbard U correction and hybrid functional methods in density-functional theory. These calculations are compared concerning the available experimental observations on pristine TiO$\rm{_2}$ crystals. Modified hybrid functionals, particularly the PBE0 functional with 11.4% fraction of exact exchange, are shown to provide highly accurate atomic structures and also accurate electronic structure data, including optical excitation energies. With $\rm{DFT+U}$, accurate optical spectra are also possible, but only if the Hubbard U is applied on the O $\rm2p$ electrons exclusively. Furthermore, both methods, the 11.4%-PBE0 hybrid functional and the $\rm{DFT+U_p}$ scheme have been used to study TiO$\rm{_2}$ amorphous ultra-thin films, confirming the agreement of the two methods even with respect to small details of the optical spectra. Our results show that the proposed $\rm{DFT+U_p}$ methodology is computationally efficient, but still accurate. It can be applied to well-ordered TiO$\rm{_2}$ polymorphs as well as to amorphous TiO$\rm{_2}$ and will allow for the calculations of complex titania-based structures.

Integrating Prospective LCA in the Development of Automotive Components - Grenz, Julian; Ostermann, Moritz; Käsewieter, Karoline; Cerdas, Felipe; Marten, Thorsten; Herrmann, Christoph; Tröster, Thomas (Sustainability)
The development of automotive components with reduced greenhouse gas (GHG) emissions is needed to reduce overall vehicle emissions. Life Cycle Engineering (LCE) based on Life Cycle Assessment (LCA) supports this by providing holistic information and improvement potentials regarding eco-efficient products. Key factors influencing LCAs of automotive components, such as material production, will change in the future. First approaches for integrating future scenarios for these key factors into LCE already exist, but they only consider a limited number of parameters and scenarios. This work aims to develop a method that can be practically applied in the industry for integrating prospective LCAs (pLCA) into the LCE of automotive components, considering relevant parameters and consistent scenarios. Therefore, pLCA methods are further developed to investigate the influence of future scenarios on the GHG emissions of automotive components. The practical application is demonstrated for a vehicle component with different design options. This paper shows that different development paths of the foreground and background system can shift the ecological optimum of design alternatives. Therefore, future pathways of relevant parameters must be considered comprehensively to reduce GHG emissions of future vehicles. This work contributes to the methodological and practical integration of pLCA into automotive development processes and provides quantitative results.
Keywords: prospective LCA; life cycle engineering (LCE); lightweight design; automotive components; body parts; circular economy; steel; aluminum; hybrid materials; fiber metal laminates

Memorization-Dilation: Modeling Neural Collapse Under Noise - Nguyen, Duc Anh; Levie, Ron; Lienen, Julian; Kutyniok, Gitta; Hüllermeier, Eyke (International Conference on Learning Representations, ICLR)
The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase of training a deep neural network, the feature embedding of all examples of the same class tend to collapse to a single representation, and the features of different classes tend to separate as much as possible. Neural collapse is often studied through a simplified model, called the unconstrained feature representation, in which the model is assumed to have "infinite expressivity" and can map each data point to any arbitrary representation. In this work, we propose a more realistic variant of the unconstrained feature representation that takes the limited expressivity of the network into account. Empirical evidence suggests that the memorization of noisy data points leads to a degradation (dilation) of the neural collapse. Using a model of the memorization-dilation (M-D) phenomenon, we show one mechanism by which different losses lead to different performances of the trained network on noisy data. Our proofs reveal why label smoothing, a modification of cross-entropy empirically observed to produce a regularization effect, leads to improved generalization in classification tasks.

Mitigating Label Noise through Data Ambiguation - Lienen, Julian; Hüllermeier, Eyke (arXiv:2305.13764)
Label noise poses an important challenge in machine learning, especially in deep learning, in which large models with high expressive power dominate the field. Models of that kind are prone to memorizing incorrect labels, thereby harming generalization performance. Many methods have been proposed to address this problem, including robust loss functions and more complex label correction approaches. Robust loss functions are appealing due to their simplicity, but typically lack flexibility, while label correction usually adds substantial complexity to the training setup. In this paper, we suggest to address the shortcomings of both methodologies by "ambiguating" the target information, adding additional, complementary candidate labels in case the learner is not sufficiently convinced of the observed training label. More precisely, we leverage the framework of so-called superset learning to construct set-valued targets based on a confidence threshold, which deliver imprecise yet more reliable beliefs about the ground-truth, effectively helping the learner to suppress the memorization effect. In an extensive empirical evaluation, our method demonstrates favorable learning behavior on synthetic and real-world noise, confirming the effectiveness in detecting and correcting erroneous training labels.

Neural Class Expression Synthesis - KOUAGOU, N'Dah Jean; Heindorf, Stefan; Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023))
Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis
Keywords: Neural network; Concept learning; Description logics

Mitigating Label Noise through Data Ambiguation - Lienen, Julian; Hüllermeier, Eyke (arXiv:2305.13764)
Label noise poses an important challenge in machine learning, especially in deep learning, in which large models with high expressive power dominate the field. Models of that kind are prone to memorizing incorrect labels, thereby harming generalization performance. Many methods have been proposed to address this problem, including robust loss functions and more complex label correction approaches. Robust loss functions are appealing due to their simplicity, but typically lack flexibility, while label correction usually adds substantial complexity to the training setup. In this paper, we suggest to address the shortcomings of both methodologies by "ambiguating" the target information, adding additional, complementary candidate labels in case the learner is not sufficiently convinced of the observed training label. More precisely, we leverage the framework of so-called superset learning to construct set-valued targets based on a confidence threshold, which deliver imprecise yet more reliable beliefs about the ground-truth, effectively helping the learner to suppress the memorization effect. In an extensive empirical evaluation, our method demonstrates favorable learning behavior on synthetic and real-world noise, confirming the effectiveness in detecting and correcting erroneous training labels.

Dynamic control of hybrid grafted perfect vector vortex beams - Ahmed, Hammad; Ansari, Muhammad Afnan; Li, Yan; Zentgraf, Thomas; Mehmood, Muhammad Qasim; Chen, Xianzhong (Nature Communications)
Perfect vector vortex beams (PVVBs) have attracted considerable interest due to their peculiar optical features. PVVBs are typically generated through the superposition of perfect vortex beams, which suffer from the limited number of topological charges (TCs). Furthermore, dynamic control of PVVBs is desirable and has not been reported. We propose and experimentally demonstrate hybrid grafted perfect vector vortex beams (GPVVBs) and their dynamic control. Hybrid GPVVBs are generated through the superposition of grafted perfect vortex beams with a multifunctional metasurface. The generated hybrid GPVVBs possess spatially variant rates of polarization change due to the involvement of more TCs. Each hybrid GPVVB includes different GPVVBs in the same beam, adding more design flexibility. Moreover, these beams are dynamically controlled with a rotating half waveplate. The generated dynamic GPVVBs may find applications in the fields where dynamic control is in high demand, including optical encryption, dense data communication, and multiple particle manipulation.
Keywords: General Physics and Astronomy; General Biochemistry; Genetics and Molecular Biology; General Chemistry; Multidisciplinary

Capabilities and Limitations of Local Strategies in Dynamic Networks - Götte, Thorsten; Knollmann, Till; Meyer auf der Heide, Friedhelm; Scheideler, Christian; Werthmann, Julian (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers - Karl, Holger; Maack, Marten; Meyer auf der Heide, Friedhelm; Pukrop, Simon; Redder, Adrian (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Practical Cryptograhic Techniques for Secure and Privacy-Preserving Customer Loyalty Systems - Blömer, Johannes; Bobolz, Jan; Eidens, Fabian; Jager, Tibor; Kramer, Paul (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Architectural Management of OTF Computing Markets - Gottschalk, Sebastian; Vorbohle, Christian; Kundisch, Dennis; Engels, Gregor; Wünderlich, Nacy V. (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Robustness and Security - Blömer, Johannes; Eidens, Fabian; Jager, Tibor; Niehues, David; Scheideler, Christian (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation - Bäumer, Frederik Simon; Chen, Wei-Fan; Geierhos, Michaela; Kersting, Joschka; Wachsmuth, Henning (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Configuration and Evaluation - Hanselle, Jonas Manuel; Hüllermeier, Eyke; Mohr, Felix; Ngonga Ngomo, Axel-Cyrille; Sherif, Mohamed; Tornede, Alexander; Wever, Marcel Dominik (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

The Market for Services: Incentives, Algorithms, Implementation - Haake, Claus-Jochen; Hehenkamp, Burkhard; Polevoy, Gleb (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Composition Analysis in Unknown Contexts - Wehrheim, Heike; Hüllermeier, Eyke; Becker, Steffen; Becker, Matthias; Richter, Cedric; Sharma, Arnab (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Mitigating Label Noise through Data Ambiguation - Lienen, Julian; Hüllermeier, Eyke (arXiv:2305.13764)
Label noise poses an important challenge in machine learning, especially in deep learning, in which large models with high expressive power dominate the field. Models of that kind are prone to memorizing incorrect labels, thereby harming generalization performance. Many methods have been proposed to address this problem, including robust loss functions and more complex label correction approaches. Robust loss functions are appealing due to their simplicity, but typically lack flexibility, while label correction usually adds substantial complexity to the training setup. In this paper, we suggest to address the shortcomings of both methodologies by "ambiguating" the target information, adding additional, complementary candidate labels in case the learner is not sufficiently convinced of the observed training label. More precisely, we leverage the framework of so-called superset learning to construct set-valued targets based on a confidence threshold, which deliver imprecise yet more reliable beliefs about the ground-truth, effectively helping the learner to suppress the memorization effect. In an extensive empirical evaluation, our method demonstrates favorable learning behavior on synthetic and real-world noise, confirming the effectiveness in detecting and correcting erroneous training labels.

Empirical Analysis in Markets for OTF Services - Elrich, Alina; Kaimann, Daniel; Fahr, René; Kundisch, Dennis; Mir Djawadi, Behnud; Müller, Michelle; Poniatowski, Martin; Schäfers, Sabrina; Frick, Bernd (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Anticipatory Assignment of Passengers to Meeting Points for Taxi-Ridesharing - Dieter, Peter; Stumpe, Miriam; Ulmer, Marlin Wolf; Schryen, Guido (Transportation Research Part D)

Tagungsbericht: 10/20 Jahre UNESCO-Konvention zum Erhalt des Immateriellen Kulturerbes – Auftaktveranstaltung zum Doppeljubiläum - Leineweber, Jonas

Das DigitELE Tutorial: Eine digitale Lernumgebung in der Englischdidaktik - Janzen, Thomas; Gabel, Stephan; Gampert, Martha; Matz, Frauke; Reckermann, Julia (Digitalisierung in der Hochschullehre – Perspektiven und Gestaltungsoptionen)

Multi-FPGA Designs and Scaling of HPC Challenge Benchmarks via MPI and Circuit-Switched Inter-FPGA Networks - Meyer, Marius; Kenter, Tobias; Plessl, Christian (ACM Transactions on Reconfigurable Technology and Systems)
While FPGA accelerator boards and their respective high-level design tools are maturing, there is still a lack of multi-FPGA applications, libraries, and not least, benchmarks and reference implementations towards sustained HPC usage of these devices. As in the early days of GPUs in HPC, for workloads that can reasonably be decoupled into loosely coupled working sets, multi-accelerator support can be achieved by using standard communication interfaces like MPI on the host side. However, for performance and productivity, some applications can profit from a tighter coupling of the accelerators. FPGAs offer unique opportunities here when extending the dataflow characteristics to their communication interfaces. In this work, we extend the HPCC FPGA benchmark suite by multi-FPGA support and three missing benchmarks that particularly characterize or stress inter-device communication: b_eff, PTRANS, and LINPACK. With all benchmarks implemented for current boards with Intel and Xilinx FPGAs, we established a baseline for multi-FPGA performance. Additionally, for the communication-centric benchmarks, we explored the potential of direct FPGA-to-FPGA communication with a circuit-switched inter-FPGA network that is currently only available for one of the boards. The evaluation with parallel execution on up to 26 FPGA boards makes use of one of the largest academic FPGA installations.
Keywords: General Computer Science

Clifford Embeddings – A Generalized Approach for Embedding in Normed Algebras - Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (ECML-PKDD)

Neuro-Symbolic Class Expression Learning - Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (International Joint Conference on Artificial Intelligence)

Breaking the exascale barrier for the electronic structure problem in ab-initio molecular dynamics - Schade, Robert; Kenter, Tobias; Elgabarty, Hossam; Lass, Michael; Kühne, Thomas; Plessl, Christian (The International Journal of High Performance Computing Applications)
The non-orthogonal local submatrix method applied to electronic structure–based molecular dynamics simulations is shown to exceed 1.1 EFLOP/s in FP16/FP32-mixed floating-point arithmetic when using 4400 NVIDIA A100 GPUs of the Perlmutter system. This is enabled by a modification of the original method that pushes the sustained fraction of the peak performance to about 80%. Example calculations are performed for SARS-CoV-2 spike proteins with up to 83 million atoms.
Keywords: Hardware and Architecture; Theoretical Computer Science; Software

Advanced Algorithm Selection with Machine Learning: Handling Large Algorithm Sets, Learning From Censored Data, and Simplyfing Meta Level Decisions - Tornede, Alexander

Learning discrete Lagrangians for variational PDEs from data and detection of travelling waves - Offen, Christian; Ober-Blöbaum, Sina (Geometric Science of Information)
The article shows how to learn models of dynamical systems from data which are governed by an unknown variational PDE. Rather than employing reduction techniques, we learn a discrete field theory governed by a discrete Lagrangian density $L_d$ that is modelled as a neural network. Careful regularisation of the loss function for training $L_d$ is necessary to obtain a field theory that is suitable for numerical computations: we derive a regularisation term which optimises the solvability of the discrete Euler--Lagrange equations. Secondly, we develop a method to find solutions to machine learned discrete field theories which constitute travelling waves of the underlying continuous PDE.
Keywords: System identification; discrete Lagrangians; travelling waves

Variational Learning of Euler–Lagrange Dynamics from Data - Ober-Blöbaum, Sina; Offen, Christian (Journal of Computational and Applied Mathematics)
The principle of least action is one of the most fundamental physical principle. It says that among all possible motions connecting two points in a phase space, the system will exhibit those motions which extremise an action functional. Many qualitative features of dynamical systems, such as the presence of conservation laws and energy balance equations, are related to the existence of an action functional. Incorporating variational structure into learning algorithms for dynamical systems is, therefore, crucial in order to make sure that the learned model shares important features with the exact physical system. In this paper we show how to incorporate variational principles into trajectory predictions of learned dynamical systems. The novelty of this work is that (1) our technique relies only on discrete position data of observed trajectories. Velocities or conjugate momenta do not need to be observed or approximated and no prior knowledge about the form of the variational principle is assumed. Instead, they are recovered using backward error analysis. (2) Moreover, our technique compensates discretisation errors when trajectories are computed from the learned system. This is important when moderate to large step-sizes are used and high accuracy is required. For this, we introduce and rigorously analyse the concept of inverse modified Lagrangians by developing an inverse version of variational backward error analysis. (3) Finally, we introduce a method to perform system identification from position observations only, based on variational backward error analysis.
Keywords: Lagrangian learning; variational backward error analysis; modified Lagrangian; variational integrators; physics informed learning

Backward error analysis for conjugate symplectic methods - McLachlan, Robert; Offen, Christian (Journal of Geometric Mechanics)
The numerical solution of an ordinary differential equation can be interpreted as the exact solution of a nearby modified equation. Investigating the behaviour of numerical solutions by analysing the modified equation is known as backward error analysis. If the original and modified equation share structural properties, then the exact and approximate solution share geometric features such as the existence of conserved quantities. Conjugate symplectic methods preserve a modified symplectic form and a modified Hamiltonian when applied to a Hamiltonian system. We show how a blended version of variational and symplectic techniques can be used to compute modified symplectic and Hamiltonian structures. In contrast to other approaches, our backward error analysis method does not rely on an ansatz but computes the structures systematically, provided that a variational formulation of the method is known. The technique is illustrated on the example of symmetric linear multistep methods with matrix coefficients.
Keywords: variational integrators; backward error analysis; Euler--Lagrange equations; multistep methods; conjugate symplectic methods

Hamiltonian Neural Networks with Automatic Symmetry Detection - Dierkes, Eva; Offen, Christian; Ober-Blöbaum, Sina; Flaßkamp, Kathrin (Chaos)
Recently, Hamiltonian neural networks (HNN) have been introduced to incorporate prior physical knowledge when learning the dynamical equations of Hamiltonian systems. Hereby, the symplectic system structure is preserved despite the data-driven modeling approach. However, preserving symmetries requires additional attention. In this research, we enhance the HNN with a Lie algebra framework to detect and embed symmetries in the neural network. This approach allows to simultaneously learn the symmetry group action and the total energy of the system. As illustrating examples, a pendulum on a cart and a two-body problem from astrodynamics are considered.

Testinstrumente und Testdatenanalyse zur Verarbeitung von Unsicherheiten in Logikblöcken hochintegrierter Schaltungen - Sprenger, Alexander
Ever increasing demands on the performance of microchips are leading to ever more complex semiconductor technologies with ever shrinking feature sizes. Complex applications with high demands on safety and reliability, such as autonomous driving, are simultaneously driving the requirements for test and diagnosis of VLSI circuits. Throughout the life cycle of a microchip, uncertainties occur that affect its timing behavior. For example, weak circuit structures, aging effects, or process variations can lead to a change in the timing behavior of the circuit. While these uncertainties do not necessarily lead to a change of the functional behavior, they can lead to a reliability problem. With modular and hybrid compaction two test instruments are presented in this work that can be used for X-tolerant test response compaction in the built-in Faster-than-At-Speed Test (FAST) which is used to detect uncertainties in VLSI circuits. One challenge for test response compaction during FAST is the high and varying X-rate at the outputs of the circuit under test. By dividing the circuit outputs into test groups and separately compacting these test groups using stochastic compactors, the modular compaction is able to handle these high and varying X-rates. To deal with uncertainties on logic interconnects, a method for distinguishing crosstalk and process variation is presented. In current semiconductor technologies, the number of parasitic coupling capacitances between logic interconnects is growing. These coupling capacitances can lead to crosstalk, which causes increased current flow in the logic interconnects, which in turn can lead to increased electromigration. In the presented method, delay maps describing the timing behavior of the circuit outputs at different operating points are used to train artificial neural networks which classify the tested circuits into fault-free and faulty.
Keywords: Testantwortkompaktierung; Prozessvariation; Silicon Lifecycle Management

Partial observations, coarse graining and equivariance in Koopman operator theory for large-scale dynamical systems - Peitz, Sebastian; Harder, Hans; Nüske, Feliks; Philipp, Friedrich; Schaller, Manuel; Worthmann, Karl (arXiv:2307.15325)
The Koopman operator has become an essential tool for data-driven analysis, prediction and control of complex systems, the main reason being the enormous potential of identifying linear function space representations of nonlinear dynamics from measurements. Until now, the situation where for large-scale systems, we (i) only have access to partial observations (i.e., measurements, as is very common for experimental data) or (ii) deliberately perform coarse graining (for efficiency reasons) has not been treated to its full extent. In this paper, we address the pitfall associated with this situation, that the classical EDMD algorithm does not automatically provide a Koopman operator approximation for the underlying system if we do not carefully select the number of observables. Moreover, we show that symmetries in the system dynamics can be carried over to the Koopman operator, which allows us to massively increase the model efficiency. We also briefly draw a connection to domain decomposition techniques for partial differential equations and present numerical evidence using the Kuramoto--Sivashinsky equation.

Revisiting the initial reaction rates for TMS combustion and a new evidence for metastable silica nanoparticles in the gas-phase synthesis - Karakaya, Yasin; Somnitz, H.; Hermsen, A.; Gonchikzhapov, Munko; Kasper, Tina (Applications in Energy and Combustion Science)
Keywords: Metastable particles; Nanomaterials; Quartz-crystal-microbalance; Molecular-beam mass spectrometry; Tetramethylsilane; Reaction kinetics

Finite-data error bounds for Koopman-based prediction and control - Nüske, Feliks; Peitz, Sebastian; Philipp, Friedrich; Schaller, Manuel; Worthmann, Karl (Journal of Nonlinear Science)
The Koopman operator has become an essential tool for data-driven approximation of dynamical (control) systems in recent years, e.g., via extended dynamic mode decomposition. Despite its popularity, convergence results and, in particular, error bounds are still quite scarce. In this paper, we derive probabilistic bounds for the approximation error and the prediction error depending on the number of training data points; for both ordinary and stochastic differential equations. Moreover, we extend our analysis to nonlinear control-affine systems using either ergodic trajectories or i.i.d. samples. Here, we exploit the linearity of the Koopman generator to obtain a bilinear system and, thus, circumvent the curse of dimensionality since we do not autonomize the system by augmenting the state by the control inputs. To the best of our knowledge, this is the first finite-data error analysis in the stochastic and/or control setting. Finally, we demonstrate the effectiveness of the proposed approach by comparing it with state-of-the-art techniques showing its superiority whenever state and control are coupled.

Multi-Objective Optimization for Sparse Deep Neural Network Training - Hotegni, Sedjro Salomon; Peitz, Sebastian; Berkemeier, Manuel Bastian (arXiv:2308.12243)
Different conflicting optimization criteria arise naturally in various Deep Learning scenarios. These can address different main tasks (i.e., in the setting of Multi-Task Learning), but also main and secondary tasks such as loss minimization versus sparsity. The usual approach is a simple weighting of the criteria, which formally only works in the convex setting. In this paper, we present a Multi-Objective Optimization algorithm using a modified Weighted Chebyshev scalarization for training Deep Neural Networks (DNNs) with respect to several tasks. By employing this scalarization technique, the algorithm can identify all optimal solutions of the original problem while reducing its complexity to a sequence of single-objective problems. The simplified problems are then solved using an Augmented Lagrangian method, enabling the use of popular optimization techniques such as Adam and Stochastic Gradient Descent, while efficaciously handling constraints. Our work aims to address the (economical and also ecological) sustainability issue of DNN models, with a particular focus on Deep Multi-Task models, which are typically designed with a very large number of weights to perform equally well on multiple tasks. Through experiments conducted on two Machine Learning datasets, we demonstrate the possibility of adaptively sparsifying the model during training without significantly impacting its performance, if we are willing to apply task-specific adaptations to the network weights. Code is available at https://github.com/salomonhotegni/MDMTN.

Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames - Gonchikzhapov, Munko; Kasper, Tina (Applications in Energy and Combustion Science)
Keywords: Nanoparticle synthesis; Flame spray pyrolysis; SpraySyn burner; Flame structure; Species distribution; Temperature distribution

ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids - Wallscheid, Oliver; Peitz, Sebastian; Stenner, Jan; Weber, Daniel; Boshoff, Septimus; Meyer, Marvin; Chidananda, Vikas; Schweins, Oliver (Journal of Open Source Software)
Keywords: General Earth and Planetary Sciences; General Environmental Science

Paradigmenwechsel vom klassischen zum datengetriebenen Problemlösen im Informatikunterricht - Höper, Lukas; Schulte, Carsten (MNU journal)

On the impossibility of surviving (iterated) deletion of weakly dominated strategies in rational MPC - Blömer, Johannes; Bobolz, Jan; Bröcher, Henrik

A Generic Construction of an Anonymous Reputation System and Instantiations from Lattices - Blömer, Johannes; Bobolz, Jan; Porzenheim, Laurens Alexander

Influence of the filler–matrix adhesion and the effects of conditioning on tensile properties of laser-sintered parts built with polyamide–glass bead dry blends - Kletetzka, Ivo; Kosanke, Maren; Meinderink, Dennis; Neßlinger, Vanessa; Grundmeier, Guido; Schmid, Hans-Joachim (Progress in Additive Manufacturing)
In this work, the influence of the filler–matrix adhesion on the tensile properties of laser-sintered parts built with Polyamide 613 filled with glass beads was investigated. For this purpose, dry blends of glass beads with and without organosilane coupling agents and polyamide powder were prepared and processed into tensile specimens on an EOS P396 laser sintering system. The samples were tested both in the dry state and after an accelerated conditioning in a climate chamber. Furthermore, finite element method (FEM) simulations were performed to model the extreme cases of optimum adhesion and no adhesion. By correlating the tensile tests with the simulation results and by analyzing the fracture surfaces, it was shown that the filler–matrix adhesion is sufficient in the dry state but is strongly degraded by conditioning. Even the presence of various organosilane thin films could not prevent a strong deterioration of the filler–matrix adhesion and the associated deterioration of the mechanical properties. Since a comparison with an injection-molded sample of the same polymer filler combination shows identical behavior after conditioning, it is assumed that this problem is not limited to additively manufactured parts.
Keywords: Industrial and Manufacturing Engineering

Influence of the filler matrix adhesion and the effects of conditioning on tensile properties of laser sintered parts built with polyamide glass bead dry blends - Kletetzka, Ivo; Kosanke, Maren; Meinderink, Dennis; Neßlinger, Vanessa; Grundmeier, Guido; Schmid, Hans-Joachim
Abstract In this work, the influence of the filler matrix adhesion on the tensile properties of laser-sintered parts built with Polyamide 613 filled with glass beads was investigated. For this purpose, dry blends of glass beads with and without organosilane coupling agents and polyamide powder were prepared and processed into tensile specimens on an EOS P396. The samples were tested both in the dry state and after an accelerated conditioning in a climate chamber. Furthermore, FEM simulations were performed to model the limiting cases of optimum adhesion and no adhesion. By correlating the tensile tests with the simulation results and by analyzing the fracture surfaces, it was shown that the filler matrix adhesion is sufficient in the dry state but is strongly degraded by conditioning. Even the presence of various organosilane thin films could not prevent a strong deterioration of the filler-matrix adhesion and the associated deterioration of the mechanical properties. Since a comparison with an injection molded sample of the same polymer filler combination shows identical behavior after conditioning, it is assumed that this problem is not limited to additively manufactured parts.

Influence of a prolonged shelf time on PA12 laser sintering powder and resulting part properties - Klippstein, Sven Helge; Kletetzka, Ivo; Sural, Ilknur; Schmid, Hans-Joachim (The International Journal of Advanced Manufacturing Technology)
In the laser sintering technology, the semi-crystalline polymer material is exposed to elevated temperatures during processing, which leads to serious material ageing for most materials. This has already been investigated intensively by various authors. However, the ageing of the material at ambient temperatures during shelf life has not been the focus so far. The need to analyse the shelf life can be derived from an ecological and economic point of view. This work is focusing on the shelf life of PA2200 (PA12). To reduce the potential influences of powder production fluctuations, two different powder batches stored for 5.5 years and 6.5 years are investigated and compared to a reference powder produced 0.5 years before these investigations. Multiple powder analyses and part characterisations have been performed. A significant yellowing and molecular chain length reduction can be derived from the measurement results. Whereas the influence on mechanical part performance was minor, the parts built with the stored powders are more yellowish. As it is most likely that this is due to the consumption of polyamide stabilisers, it can be assumed that these parts will be subject to significantly faster ageing. Therefore, it is still not recommended to use the stored powders for critical parts or light intense and humid environments.
Keywords: Selective laser sintering; Shelf life; Polyamide 12; powder; PA2200; material ageing

Editorial - Schönhärl, Korinna; Schotters, Frederike; Thiemeyer, Guido (Werkstatt Geschichte)
»Über Geld spricht man nicht.« Diese Benimmregel erweist sich beim Blick in die Ver- gangenheit als Illusion. Keineswegs war Geld grundsätzlich ein Tabuthema zwischen- menschlicher Kommunikation. Ganz im Gegenteil: Mit dem Reden über Geld wird dieses mit Bedeutung aufgeladen. Die Autor*innen dieses Themenheftes untersuch en Gelddis- kurse und die Zuschreibungen von Bedeutung an Geld in der internationalen Geschichte.
Keywords: Financial History; Discourse Analysis; History of Money

Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits - Wohlleben, Meike Claudia; Muth, Lars; Peitz, Sebastian; Sextro, Walter (Proceedings in Applied Mathematics and Mechanics)
Modelling of dynamic systems plays an important role in many engineering disciplines. Two different approaches are physical modelling and data‐driven modelling, both of which have their respective advantages and disadvantages. By combining these two approaches, hybrid models can be created in which the respective disadvantages are mitigated, with discrepancy models being a particular subclass. Here, the basic system behaviour is described physically, that is, in the form of differential equations. Inaccuracies resulting from insufficient modelling or numerics lead to a discrepancy between the measurements and the model, which can be compensated by a data‐driven error correction term. Since discrepancy methods still require a large amount of measurement data, this paper investigates the extent to which a single discrepancy model can be trained for a physical model with additional parameter dependencies without the need for retraining. As an example, a damped electromagnetic oscillating circuit is used. The physical model is realised by a differential equation describing the electric current, considering only inductance and capacitance; dissipation due to resistance is neglected. This creates a discrepancy between measurement and model, which is corrected by a data‐driven model. In the experiments, the inductance and the capacity are varied. It is found that the same data‐driven model can only be used if additional parametric dependencies in the data‐driven term are considered as well.
Keywords: Electrical and Electronic Engineering; Atomic and Molecular Physics; and Optics

Expert-Informed Hierarchical Diagnostics of Multiple Fault Modes of a Spacecraft Propulsion System - Aimiyekagbon, Osarenren Kennedy; Löwen, Alexander; Bender, Amelie; Muth, Lars; Sextro, Walter (Proceedings of the Asia Pacific Conference of the PHM Society 2023)
This paper presents a comprehensive study on diagnosing a spacecraft propulsion system utilizing data provided by the Prognostics and Health Management (PHM) society, specifically obtained as part of the Asia-Pacific PHM conference’s data challenge 2023. The objective of the challenge is to identify and diagnose known faults as well as unknown anomalies in the spacecraft’s propulsion system, which is critical for ensuring the spacecraft’s proper functionality and safety. To address this challenge, the proposed method follows a systematic approach of feature extraction, feature selection, and model development. The models employed in this study are kMeans clustering and decision trees combined to ensembles, enriched with expert knowledge. With the method presented, our team was capable of reaching high accuracy in identifying anomalies as well as diagnosing faults, resulting in attaining the seventh place with a score of 93.08 %.
Keywords: PHM; Fault Diagnostics; Multiple Fault Modes; Expert-Informed Diagnostics; Anomaly Detection

Contrastiveness in the context of action demonstration: an eye-tracking study on its effects on action perception and action recall - Singh, Amit; Rohlfing, Katharina J. (Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45))
The study investigates two different ways of guiding the addressee of an explanation - an explainee, through action demonstration: contrastive and non-contrastive. Their effect was tested on attention to specific action elements (goal) as well as on event memory. In an eye-tracking experiment, participants were shown different motion videos that were either contrastive or non-contrastive with respect to the segments of movement presentation. Given that everyday action demonstration is often multimodal, the stimuli were created with re- spect to their visual and verbal presentation. For visual presentation, a video combined two movements in a contrastive (e.g., Up-motion following a Down-motion) or non-contrastive way (e.g., two Up-motions following each other). For verbal presentation, each video was combined with a sequence of instruction descriptions in the form of negative (i.e., contrastive) or assertive (i.e., non-contrastive) guidance. It was found that a) attention to the event goal increased for this condition in the later time window, and b) participants’ recall of the event was facilitated when a visually contrastive motion was combined with a verbal contrast.
Keywords: Attention; negation; contrastive guidance; eye-movements; action understanding; event representation

Zur Kritik der Politischen Ökonomie des Digitalen Kapitalismus: Die Aktualität von Manfred Knoches Beitrag zur Kritik der Politischen Ökonomie der Medien und der Kommunikation - Fuchs, Christian (Eigentum, Medien, Öffentlichkeit: Verhandlungen des Netzwerks Kritische Kommunikationswissenschaft)

Dialogical Functions of You-Narration in Auto/Biography: Anne Harich’s “Wenn ich das gewußt hätte…”: Erinnerungen an Wolfgang Harich (2007) - Mildorf, Jarmila (Zagadnienia Rodzajów Literackich)

Modeling nonlinear optical interactions of focused beams in bulk crystals and thin films: A phenomenological approach - Spychala, Kai J.; Amber, Zeeshan H.; Eng, Lukas M.; Rüsing, Michael (Journal of Applied Physics)
Coherent nonlinear optical μ-spectroscopy is a frequently used tool in modern material science as it is sensitive to many different local observables, which comprise, among others, crystal symmetry and vibrational properties. The richness in information, however, may come with challenges in data interpretation, as one has to disentangle the many different effects like multiple reflections, phase jumps at interfaces, or the influence of the Guoy-phase. In order to facilitate interpretation, the work presented here proposes an easy-to-use semi-analytical modeling Ansatz, which bases upon known analytical solutions using Gaussian beams. Specifically, we apply this Ansatz to compute nonlinear optical responses of (thin film) optical materials. We try to conserve the meaning of intuitive parameters like the Gouy-phase and the nonlinear coherent interaction length. In particular, the concept of coherence length is extended, which is a must when using focal beams. The model is subsequently applied to exemplary cases of second- and third-harmonic generation. We observe a very good agreement with experimental data, and furthermore, despite the constraints and limits of the analytical Ansatz, our model performs similarly well as when using more rigorous simulations. However, it outperforms the latter in terms of computational power, requiring more than three orders less computational time and less performant computer systems.
Keywords: General Physics and Astronomy

K-12 Data Science Education: Outcomes of a National Workshop; International Perspectives; and Next Steps for the Learning Sciences - Wilkerson, Michelle; Ben-Zvi, Dani; Dvir, Michal; Matuk, Camilla; Podworny, Susanne; Stephens, Amy; Zapata-Cardona, Lucia (General Proceedings of the ISLS Annual Meeting: Building Knowledge and Sustaining our Community)

Tax Morale and the Church: How Catholic Clergies Adapted Norms of Paying Taxes to Secular Institutions (1940s–1950s) - Schönhärl, Korinna (Reassessing the Moral Economy Religion and Economic Ethics from Ancient Greece to the 20th Century)
Paying taxes is a field of economic activity that has always been highly morally charged: the question of who pays how much or can avoid or evade the prescribed payments is always closely related to debate about a fair societal distribution of burdens. In the process of moralisation, therefore, faith communities such as the Catholic Church also repeatedly seized the floor to propagate certain norms. The article examines the contributions of theologians from Spain, the USA and West Germany in the 1940s and 1950s. It concludes that the norms of taxation they propagated differed greatly depending on the institutional and economic frameworks within which they operated. The analysis proves taxation to be a field of economic action and societal dispute where economics and morality are indissolubly interconnected.
Keywords: Tax history; religious history: financial history; catholic church; history of economic thought

Review on: Christos Tsakas: Post-war Greco-German Relations, 1953-1981. Economic Development, Business Interests and European Integration, Basingstoke 2022. - Schönhärl, Korinna (Sehepunkte)

On the Integration of Sampling Rate Synchronization and Acoustic Beamforming - Gburrek, Tobias; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold (European Signal Processing Conference (EUSIPCO))

Scaffolding the human partner by contrastive guidance in an explanatory human-robot dialogue - Groß, A.; Singh, Amit; Banh, Ngoc Chi; Richter, B.; Scharlau, Ingrid; Rohlfing, Katharina J.; Wrede, B. (Frontiers in Robotics and AI)
Explanation has been identified as an important capability for AI-based systems, but research on systematic strategies for achieving understanding in interaction with such systems is still sparse. Negation is a linguistic strategy that is often used in explanations. It creates a contrast space between the affirmed and the negated item that enriches explaining processes with additional contextual information. While negation in human speech has been shown to lead to higher processing costs and worse task performance in terms of recall or action execution when used in isolation, it can decrease processing costs when used in context. So far, it has not been considered as a guiding strategy for explanations in human-robot interaction. We conducted an empirical study to investigate the use of negation as a guiding strategy in explanatory human-robot dialogue, in which a virtual robot explains tasks and possible actions to a human explainee to solve them in terms of gestures on a touchscreen. Our results show that negation vs. affirmation 1) increases processing costs measured as reaction time and 2) increases several aspects of task performance. While there was no significant effect of negation on the number of initially correctly executed gestures, we found a significantly lower number of attempts—measured as breaks in the finger movement data before the correct gesture was carried out—when being instructed through a negation. We further found that the gestures significantly resembled the presented prototype gesture more following an instruction with a negation as opposed to an affirmation. Also, the participants rated the benefit of contrastive vs. affirmative explanations significantly higher. Repeating the instructions decreased the effects of negation, yielding similar processing costs and task performance measures for negation and affirmation after several iterations. We discuss our results with respect to possible effects of negation on linguistic processing of explanations and limitations of our study.
Keywords: HRI; XAI; negation; understanding; explaining; touch interaction; gesture

When Did Europe Become Identified With Christianity? The Revolutionary Origins of an All Too Common Slogan - Süßmann, Johannes (Beyond Binaries. Religious Diversity in Europe)

Assessing the Impact of the Powder Production Method on Ceramic-filled Polyamide Composites made by Laser Sintering - Kletetzka, Ivo; Neitzel, Fabian; Schmid, Hans-Joachim (Proceedings of the 34th Annual International Solid Freeform Fabrication Symposium)
Polymer composites represent the industry standard in injection molding for the production of plastic components with increased requirements in terms of heat resistance and stiffness. In the field of laser sintering (LS), these materials are less common so far. In order to extend the available material variety for the LS process, new ceramic-filled Polyamide 613 powders are investigated within the scope of this work. Here, the resulting properties from two different powder production methods are compared. One filled powder is produced by dry blending and the other powder with the same filler and filling ratio is produced by encapsulating the filler particles inside the polymer particles within the dissolution-precipitation process. It was found that encapsulating the filler particles can provide certain benefits for the processability, for example an improved powder flowability or better filler dispersion. However, encapsulating the filler also alters the thermal properties of the precipitated powder.

Ibn Khaldûn and the Political Economy of Communication: A Reply to Graham Murdock - Fuchs, Christian (Critical Sociology)

Autonomous Golf Putting with Data-Driven and Physics-Based Methods - Junker, Annika; Fittkau, Niklas; Timmermann, Julia; Trächtler, Ansgar (2022 Sixth IEEE International Conference on Robotic Computing (IRC))

Novel Straightening-Machine Design with Integrated Force Measurement for Straightening of High-Strength Flat Wire - Bathelt, Lukas; Scurk, Maximilian; Djakow, Eugen; Henke, Christian; Trächtler, Ansgar (Sensors)
In a punch-bending machine, wire products are manufactured for a wide range of industrial sectors, such as the electronics industry. The raw material for this process is flat wire made of high-strength steel. During the manufacturing process of the flat wire, residual stresses and plastic deformations are induced into the wire. These residual stresses and deformations fluctuate over the length of the semi-finished product and have a negative effect on the final product quality. Straightening machines are used to reduce this influence to a minimum. So far, the adjustment of a straightening machine has been performed manually, which is a lengthy and complex task even for an experienced worker. This inevitably leads to the use of inefficient straightening strategies and causes high rejection rates in the entire production process. Due to a lack of sensor information from the straightening operation, application of modern feedback control methods has not been practicable. This paper presents a novel design for a straightening machine with an integrated, precise straightening force measurement. By simultaneously monitoring the position of the straightening rollers, state variables of the straightening operation can be derived. Additionally, a tension control for feeding the flat wire is introduced. This is implemented to mitigate the disturbing effects caused by irregularities in the wire-feeding process. In the results of this article, the high precision of the developed force measurement design and its possible applications are shown.

Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization - Cord-Landwehr, Tobias; Boeddeker, Christoph; Zorilă, Cătălin; Doddipatla, Rama; Haeb-Umbach, Reinhold (ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

LibriWASN: A Data Set for Meeting Separation, Diarization, and Recognition with Asynchronous Recording Devices - Schmalenstroeer, Joerg; Gburrek, Tobias; Haeb-Umbach, Reinhold (ITG Conference on Speech Communication)

A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures - Cord-Landwehr, Tobias; Boeddeker, Christoph; Zorilă, Cătălin; Doddipatla, Rama; Haeb-Umbach, Reinhold (INTERSPEECH 2023)

Rezension von: Jörg van Norden: Verlust der Vergangenheit. Historische Erkenntnis und Materialität zwischen Wiedererkennen und Befremden, Frankfurt/M.: Wochenschau-Verlag 2022 - Hartung, Olaf (sehepunkte)

Data-driven identification of disturbances using a sliding mode observer - Götte, Ricarda-Samantha; Klusmann, Jo Noel; Timmermann, Julia (Proceedings - 33. Workshop Computational Intelligence: Berlin, 23.-24. November 2023)

On Feature Importance and Interpretability of Speaker Representations - Rautenberg, Frederik; Kuhlmann, Michael; Wiechmann, Jana; Seebauer, Fritz; Wagner, Petra; Haeb-Umbach, Reinhold (ITG Conference on Speech Communication)
Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal. In this contribution, we take a closer look at the embedding vector representing the slowly varying signal components, commonly named the speaker embedding vector. We ask, which properties of a speaker's voice are captured and investigate to which extent do individual embedding vector components sign responsible for them, using the concept of Shapley values. Our findings show that certain speaker-specific acoustic-phonetic properties can be fairly well predicted from the speaker embedding, while the investigated more abstract voice quality features cannot.

Explaining voice characteristics to novice voice practitioners-How successful is it? - Wiechmann, Jana; Rautenberg, Frederik; Wagner, Petra; Haeb-Umbach, Reinhold (20th International Congress of the Phonetic Sciences (ICPhS))

Nachhaltigkeit in der Bildung fOERdern: Open Educational Resources in der Hochschullehre - Weber, Tassja (Inverted Classroom and beyond 2023: Agile Didaktik für nachhaltige Bildung)

Die Fremdheit der Tiere. Zur theologischen Konstruktion und Dekonstruktion des Anderen - Herdramm, Henrike

Die Tiervergessenheit in der Theologie - Herdramm, Henrike (Feinschwarz.net)
Keywords: Tiertheologie; Tiervergessenheit; Anthropozentrismus

Die Tiertheologie und die Schöpfungstheologie - Herdramm, Henrike

Wissenschaft und Alltagserfahrung: Überlegungen zur Wissenschaftsdidaktik der Psychologie - Scharlau, Ingrid (Wissenschaftsdidaktik II: Einzelne Disziplinen)
Keywords: Unterrichtsfach Psychologie

Vibrational Properties of the Potassium Titanyl Phosphate Crystal Family - Neufeld, Sergej; Gerstmann, Uwe; Padberg, Laura; Eigner, Christof; Berth, Gerhard; Silberhorn, Christine; Eng, Lukas M.; Schmidt, Wolf Gero; Rüsing, Michael (Crystals)
The crystal family of potassium titanyl phosphate (KTiOPO4) is a promising material group for applications in quantum and nonlinear optics. The fabrication of low-loss optical waveguides, as well as high-grade periodically poled ferroelectric domain structures, requires a profound understanding of the material properties and crystal structure. In this regard, Raman spectroscopy offers the possibility to study and visualize domain structures, strain, defects, and the local stoichiometry, which are all factors impacting device performance. However, the accurate interpretation of Raman spectra and their changes with respect to extrinsic and intrinsic defects requires a thorough assignment of the Raman modes to their respective crystal features, which to date is only partly conducted based on phenomenological modelling. To address this issue, we calculated the phonon spectra of potassium titanyl phosphate and the related compounds rubidium titanyl phosphate (RbTiOPO4) and potassium titanyl arsenate (KTiOAsO4) based on density functional theory and compared them with experimental data. Overall, this allows us to assign various spectral features to eigenmodes of lattice substructures with improved detail compared to previous assignments. Nevertheless, the analysis also shows that not all features of the spectra can unambigiously be explained yet. A possible explanation might be that defects or long range fields not included in the modeling play a crucial rule for the resulting Raman spectrum. In conclusion, this work provides an improved foundation into the vibrational properties in the KTiOPO4 material family.
Keywords: Inorganic Chemistry; Condensed Matter Physics; General Materials Science; General Chemical Engineering

Lydia Böttger (Universität Paderborn) rezensiert: Burwitz-Melzer, Eva; Riemer, Claudia; Schmelter, Lars (Hrsg.) (2022): Feedback beim Lehren und Lernen von Fremd- und Zweitsprachen. Arbeitspapiere der 42. Frühjahrs- konferenz zur Erforschung des Fremdsprachenunterrichts. [Giessener Beiträge zur Fremdsprachendidaktik]. Tübingen: Narr Francke Attempto, 245 Seiten. ISBN 978-3- 8233-8569-1 - Böttger, Lydia (www.daz-portal.de)

Practice reduces the costs of producing head fakes in basketball - Böer, Nils Tobias; Weigelt, Matthias; Schütz, Christoph; Güldenpenning, Iris (Psychological Research)
Abstract Previous research indicates that performing passes with a head fake in basketball leads to increased response initiation times and errors as compared to performing a pass without a head fake. These so-called fake production costs only occurred when not given the time to mentally prepare the deceptive movement. In the current study, we investigated if extensive practice could reduce the cognitive costs of producing a pass with head fake. Twenty-four basketball novices participated in an experiment on five consecutive days. A visual cue prompted participants to play a pass with or without a head fake either to the left or right side. The cued action had to be executed after an interstimulus interval (ISI) of either 0 ms, 400 ms, 800 ms or 1200 ms, allowing for different movement preparation times. Results indicated higher response initiation times (ITs) and error rates (ERs) for passes with head fakes for the short preparation intervals (ISI 0 ms and 400 ms) on the first day but no difference for the longer preparation intervals (ISI 800 ms and 1200 ms). After only one day of practice, participants showed reduced fake production costs (for ISI 0 ms) and were even able to eliminate these cognitive costs when given time to mentally prepare the movement (for ISI 400 ms). Accordingly, physical practice can reduce the cognitive costs associated with head-fake generation. This finding is discussed against the background of the strengthening of stimulus response associations.
Keywords: Arts and Humanities (miscellaneous); Developmental and Educational Psychology; Experimental and Cognitive Psychology; General Medicine

Accelerating the analysis of optical quantum systems using the Koopman operator - Peitz, Sebastian; Hunstig, Anna; Rose, Hendrik; Meier, Torsten
The prediction of photon echoes is an important technique for gaining an understanding of optical quantum systems. However, this requires a large number of simulations with varying parameters and/or input pulses, which renders numerical studies expensive. This article investigates how we can use data-driven surrogate models based on the Koopman operator to accelerate this process. In order to be successful, we require a model that is accurate over a large number of time steps. To this end, we employ a bilinear Koopman model using extended dynamic mode decomposition and simulate the optical Bloch equations for an ensemble of inhomogeneously broadened two-level systems. Such systems are well suited to describe the excitation of excitonic resonances in semiconductor nanostructures, for example, ensembles of semiconductor quantum dots. We perform a detailed study on the required number of system simulations such that the resulting data-driven Koopman model is sufficiently accurate for a wide range of parameter settings. We analyze the L2 error and the relative error of the photon echo peak and investigate how the control positions relate to the stabilization. After proper training, the dynamics of the quantum ensemble can be predicted accurately and numerically very efficiently by our methods.

Ibn Khaldûn and the Political Economy of Communication in the Age of Digital Capitalism - Fuchs, Christian (Critical Sociology)

ENHANCED PLL CIRCUIT - Iftekhar, Mohammed; Scheytt, J. Christoph

Rezension: Erika Thomalla: Anwälte des Autors. Zur Geschichte der Herausgeberschaft im 18. und 19. Jahrhundert, Göttingen: Wallstein 2020 und Ines Barner: Von anderer Hand. Praktiken des Schreibens zwischen Autor und Lektor, Göttingen: Wallstein 2021 - Spener, Anna Maria; Heimgartner, Stephanie (Sprache und Literatur)

Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria - von Neumann, Thilo; Kinoshita, Keisuke; Boeddeker, Christoph; Delcroix, Marc; Haeb-Umbach, Reinhold (IEEE/ACM Transactions on Audio, Speech, and Language Processing)
Continuous Speech Separation (CSS) has been proposed to address speech overlaps during the analysis of realistic meeting-like conversations by eliminating any overlaps before further processing. CSS separates a recording of arbitrarily many speakers into a small number of overlap-free output channels, where each output channel may contain speech of multiple speakers. This is often done by applying a conventional separation model trained with Utterance-level Permutation Invariant Training (uPIT), which exclusively maps a speaker to an output channel, in sliding window approach called stitching. Recently, we introduced an alternative training scheme called Graph-PIT that teaches the separation network to directly produce output streams in the required format without stitching. It can handle an arbitrary number of speakers as long as never more of them overlap at the same time than the separator has output channels. In this contribution, we further investigate the Graph-PIT training scheme. We show in extended experiments that models trained with Graph-PIT also work in challenging reverberant conditions. Models trained in this way are able to perform segment-less CSS, i.e., without stitching, and achieve comparable and often better separation quality than the conventional CSS with uPIT and stitching. We simplify the training schedule for Graph-PIT with the recently proposed Source Aggregated Signal-to-Distortion Ratio (SA-SDR) loss. It eliminates unfavorable properties of the previously used A-SDR loss and thus enables training with Graph-PIT from scratch. Graph-PIT training relaxes the constraints w.r.t. the allowed numbers of speakers and speaking patterns which allows using a larger variety of training data. Furthermore, we introduce novel signal-level evaluation metrics for meeting scenarios, namely the source-aggregated scale- and convolution-invariant Signal-to-Distortion Ratio (SA-SI-SDR and SA-CI-SDR), which are generalizations of the commonly used SDR-based metrics for the CSS case.
Keywords: Continuous Speech Separation; Source Separation; Graph-PIT; Dynamic Programming; Permutation Invariant Training

On Word Error Rate Definitions and Their Efficient Computation for Multi-Speaker Speech Recognition Systems - von Neumann, Thilo; Boeddeker, Christoph; Kinoshita, Keisuke; Delcroix, Marc; Haeb-Umbach, Reinhold (ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))
We propose a general framework to compute the word error rate (WER) of ASR systems that process recordings containing multiple speakers at their input and that produce multiple output word sequences (MIMO). Such ASR systems are typically required, e.g., for meeting transcription. We provide an efficient implementation based on a dynamic programming search in a multi-dimensional Levenshtein distance tensor under the constraint that a reference utterance must be matched consistently with one hypothesis output. This also results in an efficient implementation of the ORC WER which previously suffered from exponential complexity. We give an overview of commonly used WER definitions for multi-speaker scenarios and show that they are specializations of the above MIMO WER tuned to particular application scenarios. We conclude with a discussion of the pros and cons of the various WER definitions and a recommendation when to use which.
Keywords: Word Error Rate; Meeting Recognition; Levenshtein Distance

MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems - von Neumann, Thilo; Boeddeker, Christoph; Delcroix, Marc; Haeb-Umbach, Reinhold (Proc. CHiME 2023 Workshop on Speech Processing in Everyday Environments)
MeetEval is an open-source toolkit to evaluate all kinds of meeting transcription systems. It provides a unified interface for the computation of commonly used Word Error Rates (WERs), specifically cpWER, ORC WER and MIMO WER along other WER definitions. We extend the cpWER computation by a temporal constraint to ensure that only words are identified as correct when the temporal alignment is plausible. This leads to a better quality of the matching of the hypothesis string to the reference string that more closely resembles the actual transcription quality, and a system is penalized if it provides poor time annotations. Since word-level timing information is often not available, we present a way to approximate exact word-level timings from segment-level timings (e.g., a sentence) and show that the approximation leads to a similar WER as a matching with exact word-level annotations. At the same time, the time constraint leads to a speedup of the matching algorithm, which outweighs the additional overhead caused by processing the time stamps.
Keywords: Speech Recognition; Word Error Rate; Meeting Transcription

Schnittstelle zwischen Programmen und Forschung – Die Forschungsbegleitung InnoVET - Ertl, Hubert; Peitz, Nina-Madeleine (Datenreport zum Berufsbildungsbericht 2023. Informationen und Analysen zur Entwicklung der beruflichen Bildung)

Berufliche Fortbildung – gleichwertige Alternativen zum Hochschulabschluss. Erste Erkenntnisse aus dem Innovationswettbewerb InnoVET - Bednarz, Sigrid; Martens, Stephanie; Peitz, Nina-Madeleine (Berufsbildung in Wissenschaft und Praxis)

A Memetic NSGA-II for the Multi-Objective Flexible Job Shop Scheduling Problem with Real-time Energy Tariffs - Burmeister, Sascha Christian; Guericke, Daniela; Schryen, Guido (Flexible Services and Manufacturing Journal)

Spatial Diarization for Meeting Transcription with Ad-Hoc Acoustic Sensor Networks - Gburrek, Tobias; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold (Proc. Asilomar Conference on Signals, Systems, and Computers)
We propose a diarization system, that estimates “who spoke when” based on spatial information, to be used as a front-end of a meeting transcription system running on the signals gathered from an acoustic sensor network (ASN). Although the spatial distribution of the microphones is advantageous, exploiting the spatial diversity for diarization and signal enhancement is challenging, because the microphones’ positions are typically unknown, and the recorded signals are initially unsynchronized in general. Here, we approach these issues by first blindly synchronizing the signals and then estimating time differences of arrival (TDOAs). The TDOA information is exploited to estimate the speakers’ activity, even in the presence of multiple speakers being simultaneously active. This speaker activity information serves as a guide for a spatial mixture model, on which basis the individual speaker’s signals are extracted via beamforming. Finally, the extracted signals are forwarded to a speech recognizer. Additionally, a novel initialization scheme for spatial mixture models based on the TDOA estimates is proposed. Experiments conducted on real recordings from the LibriWASN data set have shown that our proposed system is advantageous compared to a system using a spatial mixture model, which does not make use of external diarization information.
Keywords: Diarization; time difference of arrival; ad-hoc acoustic sensor network; meeting transcription

Schulkulturbezogene Schultypen im Zeitalter der digitalen Transformation. Eine Typologie unter Berücksichtigung von Hintergrundmerkmalen der zur Schulkultur befragten Lehrkräfte - Caruso, Carina; Drossel, Kerstin; Heldt, Melanie (MedienPädagogik)
In view of technological progress, a digitalisation deficit in German schools as well as the experiences in schools as a result of the Corona pandemic, it becomes apparent that the question of a school culture conducive to learning retains its relevance in the age of digital transformation: On the one hand, it is evident that school culture changes in view of the digital transformation. On the other hand, it contributes to the successful implementation of digital media. Previous research findings in connection with the digital transformation focus on particular competencies of teachers (Meyer, Becker, and Bock 2023; Caruso, Heldt, and Drossel 2022; Vogelsang et al. 2023) and their cooperative behaviour (Drossel and Heldt 2022; Schulze, Drossel, and Eickelmann 2022). These questions whether school culture-related school types can be identified or not and how teachers perceive the school culture have been less considered so far. This article is dedicated to this question and explores if the school culture-related school types differ in terms of the background characteristics of the teachers. Based on a Latent Class Analysis, three school culture-related school types become apparent: strong in innovation and cooperation (Type I: 45.74 %), highly innovative and inhibited cooperation (Type II: 17.95 %), inhibited in terms of innovation and cooperation (Type III: 36.31 %). The types do not differ from each other regarding the background characteristics.

The connection of open science practices and the methodological approach of researchers - Steinhardt, Isabel; Bauer, Mareike; Wünsche, Hannes; Schimmler, Sonja (Quality & Quantity)
Abstract The Open Science movement is gaining tremendous popularity and tries to initiate changes in science, for example the sharing and reuse of data. The new requirements that come with Open Science poses researchers with several challenges. While most of these challenges have already been addressed in several studies, little attention has been paid so far to the underlying Open Science practices (OSP). An exploratory study was conducted focusing on the OSP relating to sharing and using data. 13 researchers from the Weizenbaum Institute were interviewed. The Weizenbaum Institute is an interdisciplinary research institute in Germany that was founded in 2017. To reconstruct OSP a grounded theory methodology (Strauss in Qualitative Analysis for Social Scientists, Cambridge University Press, Cambridge, 1987) was used and classified OSP into open production, open distribution and open consumption (Smith in Openness as social praxis. First Monday, 2017). The research shows that apart from the disciplinary background and research environment, the methodological approach and the type of research data play a major role in the context of OSP. The interviewees’ self-attributions related to the types of data they work with: qualitative, quantitative, social media and source code. With regard to the methodological approach and type of data, it was uncovered that uncertainties and missing knowledge, data protection, competitive disadvantages, vulnerability and costs are the main reasons for the lack of openness. The analyses further revealed that knowledge and established data infrastructures as well as competitive advantages act as drivers for openness. Because of the link between research data and OSP, the authors of this paper argue that in order to promote OSP, the methodological approach and the type of research data must also be considered.
Keywords: Open Science

Integrating and Synthesizing Technostress Research: A Meta-Analysis on Technostress Creators, Outcomes, and Usage Contexts - Nastjuk, I.; Trang, S.; Grummeck-Braamt, J.; Adam, M.; Tarafdar, M. (European Journal of Information Systems)

The technology-behavioral compensation effect: Unintended consequences of health technology adoption - Wolf, T.; Trang, S.; Weiger, W.; Trenz, M. (Journal of Information Technology)

A mixed-methods study of the quality of parental support during adolescents' information-related Internet use as a co-construction process - Kurock, Ricarda; Teichert, Jeannine; Meister, Dorothee M.; Gerhardts, Lara; Buhl, Heike M.; Bonanati, Sabrina (Journal of Adolescence)

Historische Textmuster im Wandel. Neue Wege zu ihrer Erschließung

Hitting the Breaks While Working from Home. Changes in Taking-Breaks Behaviours During Pandemic Lockdowns - Voicu, Bogdan; Țălnar-Naghi, Dana; Neguț, Adriana; Glăvan, Eugen; Tufă, Laura; Florea, Alexandra (Sociológia - Slovak Sociological Review)
Keywords: Sociology and Political Science

Self-Assembled Block Copolymer Thin Films and Their Applications (Polymers)

Show me the verb: Visualisierung von Wortstellungsregeln im DaF-Unterricht für die Grundstufe - Lentfort, Theresa; Mentchen, Silke (GfL)
Die charakteristische Verbzweitstellung des Deutschen und die sogenannte Satzklammer führen bei der Sprachproduktion vieler Lernender zu klassischen Fehlern und Frustration. Die Herausforderung für den fremdsprachlichen A1-/A2-Unterricht besteht darin, das Phänomen der Verbstellung didaktisch so zu reduzieren, dass der Gegenstand zwar nicht unzulässig vereinfacht wird, die DaF-Lernenden aber ein leicht handhabbares Modell für die Sprachproduktion zur Verfügung haben, das sie auch ohne umfassende linguistische Vorkenntnisse nutzen können. Im vorliegenden Beitrag werden wir zeigen, wie eine Vermittlung dieses grammatischen Inhalts durch Metaphorisierung und Visualisierung gelingen kann. Dazu untersuchen wir gängige Metaphern, die in Lehrmaterial für A1-/A2-Niveau zur Einführung der Verbzweitstellung und der Klammerstruktur verwendet werden, und geben einen Überblick über die dort eingesetzten Visualisierungen, deren didaktischen Nutzen wir anhand eines von uns erstellten Kriterienkatalogs analysieren. Hierzu fassen wir syntaktische Modelle wie das Feldermodell, die Dependenz- und die Valenztheorie im Kontext unseres Interesses zusammen. Ziel unserer Untersuchung ist es, brauchbare und ausbaufähige Modelle zu identifizieren.
Keywords: A1-/A2-Unterricht; Verbstellung; Satzklammer; Metapher; Visualisierung; Lerntheorie; Kognitive Linguistik; Lehrmaterial

Sprachlichkeit des Geschichtslernens. Fachliche Grundlagen, Sprachgebrauch und Ansätze fachintegrierter Spracharbeit - Hartung, Olaf (Beiträge zur Lehrerinnen- und Lehrerbildung)