Far-Field Automatic Speech Recognition - Haeb-Umbach, Reinhold; Heymann, Jahn; Drude, Lukas; Watanabe, Shinji; Delcroix, Marc; Nakatani, Tomohiro (Proceedings of the IEEE)
The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention in science and industry, which caused or was caused by an equally significant improvement in recognition accuracy. Meanwhile it has entered the consumer market with digital home assistants with a spoken language interface being its most prominent application. Speech recorded at a distance is affected by various acoustic distortions and, consequently, quite different processing pipelines have emerged compared to ASR for close-talk speech. A signal enhancement front-end for dereverberation, source separation and acoustic beamforming is employed to clean up the speech, and the back-end ASR engine is robustified by multi-condition training and adaptation. We will also describe the so-called end-to-end approach to ASR, which is a new promising architecture that has recently been extended to the far-field scenario. This tutorial article gives an account of the algorithms used to enable accurate speech recognition from a distance, and it will be seen that, although deep learning has a significant share in the technological breakthroughs, a clever combination with traditional signal processing can lead to surprisingly effective solutions.

A Comparison of Multi-View Learning Strategies for Satellite Image-based Real Estate Appraisal - Kucklick, Jan-Peter; Müller, Oliver (The AAAI-21 Workshop on Knowledge Discovery from Unstructured Data in Financial Services)

Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models - Berkemeier, Manuel Bastian; Peitz, Sebastian (Mathematical and Computational Applications)
We present a flexible trust region descend algorithm for unconstrained and convexly constrained multiobjective optimization problems. It is targeted at heterogeneous and expensive problems, i.e., problems that have at least one objective function that is computationally expensive. The method is derivative-free in the sense that neither need derivative information be available for the expensive objectives nor are gradients approximated using repeated function evaluations as is the case in finite-difference methods. Instead, a multiobjective trust region approach is used that works similarly to its well-known scalar pendants. Local surrogate models constructed from evaluation data of the true objective functions are employed to compute possible descent directions. In contrast to existing multiobjective trust region algorithms, these surrogates are not polynomial but carefully constructed radial basis function networks. This has the important advantage that the number of data points scales linearly with the parameter space dimension. The local models qualify as fully linear and the corresponding general scalar framework is adapted for problems with multiple objectives. Convergence to Pareto critical points is proven and numerical examples illustrate our findings.

Nonlinear Bicolor Holography Using Plasmonic Metasurfaces - Frese, Daniel; Wei, Qunshuo; Wang, Yongtian; Cinchetti, Mirko; Huang, Lingling; Zentgraf, Thomas (ACS Photonics)

Distributed Online Service Coordination Using Deep Reinforcement Learning - Schneider, Stefan Balthasar; Qarawlus, Haydar; Karl, Holger (IEEE International Conference on Distributed Computing Systems (ICDCS))
Services often consist of multiple chained components such as microservices in a service mesh, or machine learning functions in a pipeline. Providing these services requires online coordination including scaling the service, placing instance of all components in the network, scheduling traffic to these instances, and routing traffic through the network. Optimized service coordination is still a hard problem due to many influencing factors such as rapidly arriving user demands and limited node and link capacity. Existing approaches to solve the problem are often built on rigid models and assumptions, tailored to specific scenarios. If the scenario changes and the assumptions no longer hold, they easily break and require manual adjustments by experts. Novel self-learning approaches using deep reinforcement learning (DRL) are promising but still have limitations as they only address simplified versions of the problem and are typically centralized and thus do not scale to practical large-scale networks. To address these issues, we propose a distributed self-learning service coordination approach using DRL. After centralized training, we deploy a distributed DRL agent at each node in the network, making fast coordination decisions locally in parallel with the other nodes. Each agent only observes its direct neighbors and does not need global knowledge. Hence, our approach scales independently from the size of the network. In our extensive evaluation using real-world network topologies and traffic traces, we show that our proposed approach outperforms a state-of-the-art conventional heuristic as well as a centralized DRL approach (60% higher throughput on average) while requiring less time per online decision (1 ms).
Keywords: network management; service management; coordination; reinforcement learning; distributed

Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools und deren Datennutzung - Gottschalk, Sebastian; Yigitbas, Enes
Die kontinuierliche Weiterentwicklung des eigenen Geschäftsmodells ist für eine Organisation von entscheidender Bedeutung, um wettbewerbsfähig und somit nachhaltig erfolgreich zu bleiben. Während für die Entwicklung neuer Geschäftsmodelle häufig Workshops und einfache Software-Tools zur Visualisierung genutzt werden, wurden in der Forschung bereits erste Ansätze von datengetriebener Geschäftsmodellentwicklung (GME) vorgestellt. Diese Ansätze nutzen dabei Daten, Informationen oder auch Wissen aus internen und externen Unternehmensquellen, um den GME-Prozess zu unterstützen. Innerhalb dieses Beitrags zeigen wir einige Ansätze aus der aktuellen Literatur und analysieren wie ihre Datennutzung den GME-Prozess unterstützt. Weiterhin stellen wir mit dem BMDL Feature Modeler ein Tool vor, welches den GME-Prozess mit Expertenwissen unterstützt.

Distributed merchandise management system - Göllner, Thomas; Schwarz, Jan-Hendrik; Gottschalk, Sebastian; Sauer, Stefan
The invention describes a distributed merchandise management system, in which the client, retailer and the manufacturer are linked by a network. This is implemented by a cloud storage (105), the cloud storage (105) comprising a means (105 a) for storing data, a means for receiving first data from a first network node (110), the first data being associated with a physical object, a means for receiving request data from a second network node (120), a means for receiving second data from a third network node (130), the second data being associated with the first data and comprising at least one data piece adapted to change the first data depending on the received request data, a means for changing the first data based at least in part on the second data and the request data, and a means for sending a changed portion of the first data from the cloud storage (105) to the first network node (110).

Optical secret sharing with cascaded metasurface holography - Georgi, Philip; Wei, Qunshuo; Sain, Basudeb; Schlickriede, Christian; Wang, Yongtian; Huang, Lingling; Zentgraf, Thomas (Science Advances)
Secret sharing is a well-established cryptographic primitive for storing highly sensitive information like encryption keys for encoded data. It describes the problem of splitting a secret into different shares, without revealing any information to its shareholders. Here, we demonstrate an all-optical solution for secret sharing based on metasurface holography. In our concept, metasurface holograms are used as spatially separable shares that carry encrypted messages in the form of holographic images. Two of these shares can be recombined by bringing them close together. Light passing through this stack of metasurfaces accumulates the phase shift of both holograms and optically reconstructs the secret with high fidelity. In addition, the hologram generated by each single metasurface can uniquely identify its shareholder. Furthermore, we demonstrate that the inherent translational alignment sensitivity between two stacked metasurface holograms can be used for spatial multiplexing, which can be further extended to realize optical rulers.

From Label Smoothing to Label Relaxation - Lienen, Julian; Hüllermeier, Eyke (Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI)

Situation-specific Business Model Development Methods for Mobile App Developers - Gottschalk, Sebastian; Yigitbas, Enes; Nowosad, Alexander; Engels, Gregor (Enterprise, Business-Process and Information Systems Modeling)
The development of effective business models is an essential task in highly competitive markets like mobile ecosystems. Existing development methods for these business models do not specifically focus that the development process profoundly depends on the situation (e.g., market size, regulations) of the mobile app developer. Here, a mismatch between method and situation can lead to poor resource management and longer development cycles. In software engineering, situational method engineering is used for software projects to configure a development method out of a method repository based on the project situation. Analogously, we support creating situation-specific business model development methods with a method base and new user roles. Here, the method engineer obtains the knowledge of the domain expert and stores it in the method base as elements, building blocks, and patterns. The expert knowledge is derived from a grey literature review on mobile development processes. After this, the method engineer constructs the development method based on the described situation of the business developer. We provide an open-source tool and evaluate it by constructing a local event platform's business model development method.
Keywords: Business Model Development; Situational Method Engineering; Mobile App; Business Model Development Tools

Application-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML - Schubert, David; Eikerling, Hendrik; Holtmann, Jörg (Frontiers in Computer Science)
Modern and flexible application-level software platforms increase the attack surface of connected vehicles and thereby require automotive engineers to adopt additional security control techniques. These techniques encompass host-based intrusion detection systems (HIDSs) that detect suspicious activities in application contexts. Such application-aware HIDSs originate in information and communications technology systems and have a great potential to deal with the flexible nature of application-level software platforms. However, the elementary characteristics of known application-aware HIDS approaches and thereby the implications for their transfer to the automotive sector are unclear. In previous work, we presented a systematic literature review (SLR) covering the state of the art of application-aware HIDS approaches. We synthesized our findings by means of a fine-grained classification for each approach specified through a feature model and corresponding variant models. These models represent the approaches’ elementary characteristics. Furthermore, we summarized key findings and inferred implications for the transfer of application-aware HIDSs to the automotive sector. In this article, we extend the previous work by several aspects. We adjust the quality evaluation process within the SLR to be able to consider high quality conference publications, which results in an extended final pool of publications. For supporting HIDS developers on the task of configuring HIDS analysis techniques based on machine learning, we report on initial results on the applicability of AutoML. Furthermore, we present lessons learned regarding the application of the feature and variant model approach for SLRs. Finally, we more thoroughly describe the SLR study design.

What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing - Nouri, Zahra; Gadiraju, Ujwal; Engels, Gregor; Wachsmuth, Henning (Proceedings of the 32nd ACM Conference on Hypertext and Social Media)

Low Temperature Laser Sintering on a Standard System: First Attempts and Results with PA12 - Menge, Dennis; Schmid, Hans-Joachim
The laser sintering process has been a well-established AM process for many years. Disadvantages of LS are the low material variety and the thermal damage of the unprocessed material. The low temperature laser sintering attacks at this point and processes powder material at a build chamber temperature lower than the recrystallization temperature. This drastic reduction in temperature results in significantly less thermal damage to the material. This work deals with the low temperature laser sintering of Polyamide 12 (PA12) on a commercial, unmodified laser sintering system to compare it to standard laser sintered PA12 and to create the basis for low temperature laser sintering of high temperature materials on such a system. First results by changing the exposure parameters and by fixing parts on a building platform show a processing of PA12 on an EOS P396 at a build chamber temperature less than 100 °C instead of standard approx. 175 °C.
Keywords: Low Temp LS; Low Temperature Laser Sintering; Polyamid 12

Selective Etching of (111)B-Oriented AlxGa1−xAs-Layers for Epitaxial Lift-Off - Henksmeier, Tobias; Eppinger, Martin; Reineke, Bernhard; Zentgraf, Thomas; Meier, Cedrik; Reuter, Dirk (physica status solidi (a))
GaAs-(111)-nanostructures exhibiting second harmonic generation are new building blocks in nonlinear optics. Such structures can be fabricated through epitaxial lift-off using selective etching of Al-containing layers and subsequent transfer to glass substrates. Herein, the selective etching of (111)B-oriented AlxGa1−xAs sacrificial layers (10–50 nm thick) with different aluminum concentrations (x = 0.5–1.0) in 10% hydrofluoric acid is investigated and compared with standard (100)-oriented structures. The thinner the sacrificial layer and the lower the aluminum content, the lower the lateral etch rate. For both orientations, the lateral etch rates are in the same order of magnitude, but some quantitative differences exist. Furthermore, the epitaxial lift-off, the transfer, and the nanopatterning of thin (111)B-oriented GaAs membranes are demonstrated. Atomic force microscopy and high-resolution X-ray diffraction measurements reveal the high structural quality of the transferred GaAs-(111) films.
Keywords: epitaxial lift-off; GaAs/AlxGa1−xAs heterostructures; selective etching

Divide and Conquer: Hierarchical Network and Service Coordination - Schneider, Stefan Balthasar; Jürgens, Mirko; Karl, Holger (IFIP/IEEE International Symposium on Integrated Network Management (IM))
In practical, large-scale networks, services are requested by users across the globe, e.g., for video streaming. Services consist of multiple interconnected components such as microservices in a service mesh. Coordinating these services requires scaling them according to continuously changing user demand, deploying instances at the edge close to their users, and routing traffic efficiently between users and connected instances. Network and service coordination is commonly addressed through centralized approaches, where a single coordinator knows everything and coordinates the entire network globally. While such centralized approaches can reach global optima, they do not scale to large, realistic networks. In contrast, distributed approaches scale well, but sacrifice solution quality due to their limited scope of knowledge and coordination decisions. To this end, we propose a hierarchical coordination approach that combines the good solution quality of centralized approaches with the scalability of distributed approaches. In doing so, we divide the network into multiple hierarchical domains and optimize coordination in a top-down manner. We compare our hierarchical with a centralized approach in an extensive evaluation on a real-world network topology. Our results indicate that hierarchical coordination can find close-to-optimal solutions in a fraction of the runtime of centralized approaches.
Keywords: network management; service management; coordination; hierarchical; scalability; nfv

Situation-specific Development of Business Models for Services in Software Ecosystems - Gottschalk, Sebastian (Advanced Software Engineering. Doctorial Consortium)

Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models - Spliethöver, Maximilian; Wachsmuth, Henning (Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21)
Word embedding models reflect bias towards genders, ethnicities, and other social groups present in the underlying training data. Metrics such as ECT, RNSB, and WEAT quantify bias in these models based on predefined word lists representing social groups and bias-conveying concepts. How suitable these lists actually are to reveal bias - let alone the bias metrics in general - remains unclear, though. In this paper, we study how to assess the quality of bias metrics for word embedding models. In particular, we present a generic method, Bias Silhouette Analysis (BSA), that quantifies the accuracy and robustness of such a metric and of the word lists used. Given a biased and an unbiased reference embedding model, BSA applies the metric systematically for several subsets of the lists to the models. The variance and rate of convergence of the bias values of each model then entail the robustness of the word lists, whereas the distance between the models' values gives indications of the general accuracy of the metric with the word lists. We demonstrate the behavior of BSA on two standard embedding models for the three mentioned metrics with several word lists from existing research.

Generating Informative Conclusions for Argumentative Texts - Syed, Shahbaz; Al-Khatib, Khalid; Alshomary, Milad; Wachsmuth, Henning; Potthast, Martin (Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021): Findings)

Syntopical Graphs for Computational Argumentation Tasks - Barrow, Joe; Jain, Rajiv; Lipka, Nedim; Dernoncourt, Franck; Morariu, Vlad; Manjunatha, Varun; Oard, Douglas; Resnik, Philip; Wachsmuth, Henning (Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021))

Android App Analysis Benchmark Case Generation - Schott, Stefan

Nonlinear metasurface combining telecom-range intersubband transitions in GaN/AlN quantum wells with resonant plasmonic antenna arrays - Mundry, Jan; Spreyer, Florian; Jmerik, Valentin; Ivanov, Sergey; Zentgraf, Thomas; Betz, Markus (Optical Materials Express)
We realize and investigate a nonlinear metasurface taking advantage of intersubband transitions in ultranarrow GaN/AlN multi-quantum well heterostructures. Owing to huge band offsets, the structures offer resonant transitions in the telecom window around 1.55 µm. These heterostructures are functionalized with an array of plasmonic antennas featuring cross-polarized resonances at these near-infrared wavelengths and their second harmonic. This kind of nonlinear metasurface allows for substantial second-harmonic generation at normal incidence which is completely absent for an antenna array without the multi-quantum well structure underneath. While the second harmonic is originally radiated only into the plane of the quantum wells, a proper geometrical arrangement of the plasmonic elements permits the redirection of the second-harmonic light to free-space radiation, which is emitted perpendicular to the surface.

Credal Self-Supervised Learning - Lienen, Julian; Hüllermeier, Eyke (arXiv:2106.11853)
Self-training is an effective approach to semi-supervised learning. The key idea is to let the learner itself iteratively generate "pseudo-supervision" for unlabeled instances based on its current hypothesis. In combination with consistency regularization, pseudo-labeling has shown promising performance in various domains, for example in computer vision. To account for the hypothetical nature of the pseudo-labels, these are commonly provided in the form of probability distributions. Still, one may argue that even a probability distribution represents an excessive level of informedness, as it suggests that the learner precisely knows the ground-truth conditional probabilities. In our approach, we therefore allow the learner to label instances in the form of credal sets, that is, sets of (candidate) probability distributions. Thanks to this increased expressiveness, the learner is able to represent uncertainty and a lack of knowledge in a more flexible and more faithful manner. To learn from weakly labeled data of that kind, we leverage methods that have recently been proposed in the realm of so-called superset learning. In an exhaustive empirical evaluation, we compare our methodology to state-of-the-art self-supervision approaches, showing competitive to superior performance especially in low-label scenarios incorporating a high degree of uncertainty.

Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-based Deep Learning Approach - Kucklick, Jan-Peter; Müller, Jennifer; Beverungen, Daniel; Müller, Oliver (European Conference on Information Systems)

A new Device for Determination of Forming-Limit-Curves under Hot-Forming Conditions - Triebus, Marcel; Gierse, Jan; Marten, Thorsten; Tröster, Thomas (IOP Conference Series: Materials Science and Engineering)

COVID-19 reporting and willingness to pay for leisure activities - Warkulat, Sonja; Krull, Sebastian; Ortmann, Regina; Klocke, Nina; Pelster, Matthias (Covid Economics)
The containment of COVID-19 critically hinges on individuals’ behavior. We investigate how individuals react to variations in COVID-19 reporting. Using a survey, we elicit individuals' perceived infection risk given various COVID-19 metrics (e.g., confirmed cases, reproduction rate, or case-fatality ratio). We proxy individuals' risk perception with their willingness to pay for the participation in everyday life and amusements events. We find that participants react to different COVID-19 metrics with varying sensitivity. We observe a saturation of sensitivity for several measures at critical limits used in the political discussion, making our results highly relevant for policy makers in their efforts to direct individuals to adhere to hygienic etiquette and social distancing guidelines.
Keywords: COVID-19 reporting; willingness to pay; willingness to accept

Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning - Schneider, Stefan Balthasar; Khalili, Ramin; Manzoor, Adnan; Qarawlus, Haydar; Schellenberg, Rafael; Karl, Holger; Hecker, Artur (Transactions on Network and Service Management)
Modern services consist of interconnected components,e.g., microservices in a service mesh or machine learning functions in a pipeline. These services can scale and run across multiple network nodes on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities, changing demands, and Quality of Service (QoS) requirements into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge). We propose DeepCoord, a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm on how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, DeepCoord significantly improves flow throughput (up to 76%) and overall network utility (more than 2x) on realworld network topologies and traffic traces. It also supports optimizing multiple, possibly competing objectives, learns to respect QoS requirements, generalizes to scenarios with unseen, stochastic traffic, and scales to large real-world networks. For reproducibility and reuse, our code is publicly available.
Keywords: network management; service management; coordination; reinforcement learning; self-learning; self-adaptation; multi-objective

Zum Zusammenhang von Berufsethos und der Berufswahlmotivation angehender Wirtschaftspädagog*innen - Goller, Michael; Ziegler, Simone (bwp@ Spezial)
Sowohl Berufsethos als auch Berufswahlmotivation tragen zu relevanten lern-, leistungs- und laufbahnbedingenden Prozessen eines Individuums bei und prägen dessen Lebensverlauf wesentlich. Während die Berufswahlmotivation bereits verstärkt im wirtschaftspädagogischen Kontext untersucht wurde, existieren zum Berufsethos von Wirtschaftspädagog*innen nur vereinzelt empirische Studien. So ist beispielsweise wenig darüber bekannt, wie das Berufsethos von Wirtschaftspädagog*innen in der Ausbildungsphase ausgeprägt ist. Auch die Erforschung des Zusammenhangs zwischen den Konstrukten des Berufsethos und der Berufswahlmotivation blieb bisher unbeachtet. In diesem Beitrag wird entsprechend dieses Forschungsdesiderats untersucht, wie das anfänglich ausgebildete Berufsethos von Wirtschaftspädagogikstudierenden in der universitären Ausbildung ausgeprägt ist, ob sich die Ausprägung nach dem angegebenen Berufswunsch der Studierenden unterscheidet und inwiefern das anfänglich ausgeprägte Berufsethos mit der Berufswahlmotivation von Studierenden zusammenhängt. Dafür wurden im Wintersemester 2019/20 an zwölf deutschen Universitäten insgesamt 879 Wirtschaftspädagogikstudierende schriftlich befragt. Die Ergebnisse zeigen, dass das anfängliche Berufsethos der Befragten bereits in der universitären Ausbildungsphase relativ stark ausgeprägt ist. Weiterhin ist zu erkennen, dass das Berufsethos bei angehenden Wirtschaftspädagog*innen, die den Berufswunsch Lehrkraft haben, ausgeprägter ist als bei Wirtschaftspädagogikstudierenden, die eine Tätigkeit außerhalb des Schuldienstes anstreben bzw. noch unentschlossen sind. Letztlich kann aufgezeigt werden, dass grundsätzlich positive Zusammenhänge zwischen dem anfänglich ausgeprägten Berufsethos und der Berufswahlmotivation von angehenden Wirtschaftspädagog*innen bestehen.
Keywords: Berufsethos; Berufswahlmotivation; Wirtschaftspädagogik; Studierende

Spectral Properties of Effective Dynamics from Conditional Expectations - Nüske, Feliks; Koltai, Péter; Boninsegna, Lorenzo; Clementi, Cecilia (Entropy)
The reduction of high-dimensional systems to effective models on a smaller set of variables is an essential task in many areas of science. For stochastic dynamics governed by diffusion processes, a general procedure to find effective equations is the conditioning approach. In this paper, we are interested in the spectrum of the generator of the resulting effective dynamics, and how it compares to the spectrum of the full generator. We prove a new relative error bound in terms of the eigenfunction approximation error for reversible systems. We also present numerical examples indicating that, if Kramers–Moyal (KM) type approximations are used to compute the spectrum of the reduced generator, it seems largely insensitive to the time window used for the KM estimators. We analyze the implications of these observations for systems driven by underdamped Langevin dynamics, and show how meaningful effective dynamics can be defined in this setting.

Resonant evanescent excitation of guided waves with high-order optical angular momentum - Hammer, Manfred; Ebers, Lena; Förstner, Jens (Journal of the Optical Society of America B)
Gaussian-beam-like bundles of semi-guided waves propagating in a dielectric slab can excite modes with high-order optical angular momentum supported by a circular fiber. We consider a multimode step-index fiber with a high-index coating, where the waves in the slab are evanescently coupled to the modes of the fiber. Conditions for effective resonant interaction are identified. Based on a hybrid analytical–numerical coupled mode model, our simulations predict that substantial fractions of the input power can be focused into waves with specific orbital angular momentum, of excellent purity, with a clear distinction between degenerate modes with opposite vorticity.
Keywords: tet_topic_waveguides

An efficient descent method for locally Lipschitz multiobjective optimization problems - Gebken, Bennet; Peitz, Sebastian (Journal of Optimization Theory and Applications)
In this article, we present an efficient descent method for locally Lipschitz continuous multiobjective optimization problems (MOPs). The method is realized by combining a theoretical result regarding the computation of descent directions for nonsmooth MOPs with a practical method to approximate the subdifferentials of the objective functions. We show convergence to points which satisfy a necessary condition for Pareto optimality. Using a set of test problems, we compare our method to the multiobjective proximal bundle method by M\"akel\"a. The results indicate that our method is competitive while being easier to implement. While the number of objective function evaluations is larger, the overall number of subgradient evaluations is lower. Finally, we show that our method can be combined with a subdivision algorithm to compute entire Pareto sets of nonsmooth MOPs.

Inverse multiobjective optimization: Inferring decision criteria from data - Gebken, Bennet; Peitz, Sebastian (Journal of Global Optimization)
It is a challenging task to identify the objectives on which a certain decision was based, in particular if several, potentially conflicting criteria are equally important and a continuous set of optimal compromise decisions exists. This task can be understood as the inverse problem of multiobjective optimization, where the goal is to find the objective function vector of a given Pareto set. To this end, we present a method to construct the objective function vector of an unconstrained multiobjective optimization problem (MOP) such that the Pareto critical set contains a given set of data points with prescribed KKT multipliers. If such an MOP can not be found, then the method instead produces an MOP whose Pareto critical set is at least close to the data points. The key idea is to consider the objective function vector in the multiobjective KKT conditions as variable and then search for the objectives that minimize the Euclidean norm of the resulting system of equations. By expressing the objectives in a finite-dimensional basis, we transform this problem into a homogeneous, linear system of equations that can be solved efficiently. Potential applications of this approach include the identification of objectives (both from clean and noisy data) and the construction of surrogate models for expensive MOPs.

Observing 0D subwavelength-localized modes at ~100 THz protected by weak topology - Lu, Jinlong; Wirth, Konstantin G.; Gao, Wenlong; Heßler, Andreas; Sain, Basudeb; Taubner, Thomas; Zentgraf, Thomas (Science Advances)
Topological photonic crystals (TPhCs) provide robust manipulation of light with built-in immunity to fabrication tolerances and disorder. Recently, it was shown that TPhCs based on weak topology with a dislocation inherit this robustness and further host topologically protected lower-dimensional localized modes. However, TPhCs with weak topology at optical frequencies have not been demonstrated so far. Here, we use scattering-type scanning near-field optical microscopy to verify mid-bandgap zero-dimensional light localization close to 100 THz in a TPhC with nontrivial Zak phase and an edge dislocation. We show that because of the weak topology, differently extended dislocation centers induce similarly strong light localization. The experimental results are supported by full-field simulations. Along with the underlying fundamental physics, our results lay a foundation for the application of TPhCs based on weak topology in active topological nanophotonics, and nonlinear and quantum optic integrated devices because of their strong and robust light localization.

Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis - Schubert, Philipp; Hermann, Ben; Bodden, Eric (European Conference on Object-Oriented Programming (ECOOP))
Static analysis is used to automatically detect bugs and security breaches, and aids compileroptimization. Whole-program analysis (WPA) can yield high precision, however causes long analysistimes and thus does not match common software-development workflows, making it often impracticalto use for large, real-world applications.This paper thus presents the design and implementation ofModAlyzer, a novel static-analysisapproach that aims at accelerating whole-program analysis by making the analysis modular andcompositional. It shows how to computelossless, persisted summaries for callgraph, points-to anddata-flow information, and it reports under which circumstances this function-level compositionalanalysis outperforms WPA.We implementedModAlyzeras an extension to LLVM and PhASAR, and applied it to 12 real-world C and C++ applications. At analysis time,ModAlyzermodularly and losslessly summarizesthe analysis effect of the library code those applications share, hence avoiding its repeated re-analysis.The experimental results show that the reuse of these summaries can save, on average, 72% ofanalysis time over WPA. Moreover, because it is lossless, the module-wise analysis fully retainsprecision and recall. Surprisingly, as our results show, it sometimes even yields precision superior toWPA. The initial summary generation, on average, takes about 3.67 times as long as WPA.

Further development of a numerical method for analyzing the load capacity of clinched joints in versatile process chains - Bielak, Christian Roman; Böhnke, Max; Bobbert, Mathias; Meschut, Gerson

Automated Machine Learning for Multi-Label Classification - Wever, Marcel Dominik

The influence of manufacturing processes and optical measurement methods on the damage behavior of HX340LAD micro-alloyed steels - Otroshi, Mortaza; Meschut, Gerson; Nesakumar, Aathavan (Journal of Manufacturing Engineering)
This study deals with the damage behavior of metallic materials by the application of different manufacturing processes and using different optical measurement methods to identify the crack initiation in the damage specimen. The study is intended to highlight the importance of considering manufacturing processes and optical measurement methods in a numerical simulation when analyzing the damage behavior of metallic materials. To describe the damage behavior of the material in the process chain simulations, it is important to calibrate the parameters of damage model more accurately. These parameters are determined using experimental investigation of desired damage specimens. In this regard, a selected damage specimen manufactured by different cutting processes is first experimentally and then numerically investigated. It is shown that the manufacturing process and the optical measurement methods influence the stress state analyzed in the numerical simulation.
Keywords: Damage behaviour; Stress triaxiality; Manufacturing process and Optical measurement

Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning - Kirchhoff, Jonas; Burmeister, Sascha Christian; Weskamp, Christoph; Engels, Gregor (Energy Informatics and Electro Mobility ICT)
Requirements for energy distribution networks are changing fast due to the growing share of renewable energy, increasing electrification, and novel consumer and asset technologies. Since uncertainties about future developments increase planning difficulty, flexibility potentials such as synergies between the electricity, gas, heat, and transport sector often remain unused. In this paper, we therefore present a novel module-based concept for a decision support system that helps distribution network planners to identify cross-sectoral synergies and to select optimal network assets such as transformers, cables, pipes, energy storage systems or energy conversion technology. The concept enables long-term transformation plans and supports distribution network planners in designing reliable, sustainable and cost-efficient distribution networks for future demands.

Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach - Prester, Julian; Wagner, Gerit; Schryen, Guido; Hassan, Nik Rushdi (Decision Support Systems)
Ideational impact refers to the uptake of a paper's ideas and concepts by subsequent research. It is defined in stark contrast to total citation impact, a measure predominantly used in research evaluation that assumes that all citations are equal. Understanding ideational impact is critical for evaluating research impact and understanding how scientific disciplines build a cumulative tradition. Research has only recently developed automated citation classification techniques to distinguish between different types of citations and generally does not emphasize the conceptual content of the citations and its ideational impact. To address this problem, we develop Deep Content-enriched Ideational Impact Classification (Deep-CENIC) as the first automated approach for ideational impact classification to support researchers' literature search practices. We evaluate Deep-CENIC on 1,256 papers citing 24 information systems review articles from the IT business value domain. We show that Deep-CENIC significantly outperforms state-of-the-art benchmark models. We contribute to information systems research by operationalizing the concept of ideational impact, designing a recommender system for academic papers based on deep learning techniques, and empirically exploring the ideational impact of the IT business value domain.
Keywords: Ideational impact; citation classification; academic recommender systems; natural language processing; deep learning; cumulative tradition

Which Factors Affect the Scientific Impact of Review Papers in IS Research? A Scientometric Study - Wagner, Gerit; Prester, Julian; Roche, Maria; Schryen, Guido; Benlian, Alexander; Paré, Guy; Templier, Mathieu (Information & Management)
Review papers are essential for knowledge development in IS. While some are cited twice a day, others accumulate single digit citations over a decade. The magnitude of these differences prompts us to analyze what distinguishes those reviews that have proven to be integral to scientific progress from those that might be considered less impactful. Our results highlight differences between reviews aimed at describing, understanding, explaining, and theory testing. Beyond the control variables, they demonstrate the importance of methodological transparency and the development of research agendas. These insights inform all stakeholders involved in the development and publication of review papers.
Keywords: Literature review; review papers; scientometric; scientific impact; citation analysis

Study on Sensitivity of Electric Bus Systems under Simultaneous Optimization of Charging Infrastructure and Vehicle Schedules - Stumpe, Miriam; Rößler, David; Schryen, Guido; Kliewer, Natalia (EURO Journal on Transportation and Logistics)

Exploring the Scientific Impact of Information Systems Design Science Research - Wagner, Gerit; Prester, Julian; Schryen, Guido (Communications of the Association for Information Systems)

The Computation and Analysis of Invariant Sets of Infinite-Dimensional Systems - Gerlach, Raphael
Ein zentraler Aspekt bei der Untersuchung dynamischer Systeme ist die Analyse ihrer invarianten Mengen wie des globalen Attraktors und (in)stabiler Mannigfaltigkeiten. Insbesondere wenn das zugrunde liegende System von einem Parameter abhängt, ist es entscheidend, sie im Bezug auf diesen Parameter effizient zu verfolgen. Für die Berechnung invarianter Mengen stützen wir uns für ihre Approximation auf numerische Algorithmen. Typischerweise können diese Methoden jedoch nur auf endlich-dimensionale dynamische Systeme angewendet werden. In dieser Arbeit präsentieren wir daher einen numerischen Rahmen für die globale dynamische Analyse unendlich-dimensionaler Systeme. Wir werden Einbettungstechniken verwenden, um das core dynamical system (CDS) zu definieren, welches ein dynamisch äquivalentes endlich-dimensionales System ist.Das CDS wird dann verwendet, um eingebettete invariante Mengen, also eins-zu-eins Bilder, mittels Mengen-orientierten numerischen Methoden zu approximieren. Bei der Konstruktion des CDS ist es entscheidend, eine geeignete Beobachtungsabbildung auszuwählen und die geeignete inverse Abbildung zu entwerfen. Dazu werden wir geeignete numerische Implementierungen des CDS für DDEs und PDEs vorstellen. Für eine nachfolgende geometrische Analyse der eingebetteten invarianten Menge betrachten wir eine Lerntechnik namens diffusion maps, die ihre intrinsische Geometrie enthüllt sowie ihre Dimension schätzt. Schließlich wenden wir unsere entwickelten numerischen Methoden an einigen bekannten unendlich-dimensionale dynamischen Systeme an, wie die Mackey-Glass-Gleichung, die Kuramoto-Sivashinsky-Gleichung und die Navier-Stokes-Gleichung.

Einblicke in explizite und implizite Erwartungen Lehrender an Studierendentexte. Textbasierte Interviews zu Zielen und Erträgen von fachsensiblem Peer-Textfeedback - Karsten, Andrea (Schreiblehrkonzepte an Hochschulen. Fallstudien und Reflexionen zum fachspezifischen Schreibenlehren und -lernen)

Holistic change propagation and impact analysis in requirements management - Gräßler, Iris; Oleff, Christian; Preuß, Daniel
In developing complex technical systems, requirements are subject to continuous change. Systematic and holistic change impact analysis and proactive measures are required for reducing the number of requirement changes and their negative impact. There is no method to analyse the holistic impact of a requirement change in the context of developing complex technical systems. Holistic analysis requires to consider the local effects of requirement changes as well as effects from change propagation. To develop an approach for holistic change propagation and impact analysis, twelve performance goals are defined. Those are derived from a state of research analysis as well as an industry workshop. A three-step method is proposed. Firstly, requirement dependencies that cause change propagation are detected. Secondly, critical requirements are automatically identified based on a Page Rank algorithm. Thirdly, change impact of critical requirements is analysed based on a guideline. Validation proves that ten goals are fulfilled and two are partly fulfilled. The method addresses major shortcomings of preceding research and enables sound decision making for development engineers both before a change occurs and during decision process on a change request. This helps to reduce negative change impact in development projects and the risk of project failure.

Cryptimeleon: A Library for Fast Prototyping of Privacy-Preserving Cryptographic Schemes - Bobolz, Jan; Eidens, Fabian; Heitjohann, Raphael; Fell, Jeremy

Configurable lossless broadband beam splitters for semi-guided waves in integrated silicon photonics - Hammer, Manfred; Ebers, Lena; Förstner, Jens (OSA Continuum)
We show that narrow trenches in a high-contrast silicon-photonics slab can act as lossless power dividers for semi-guided waves. Reflectance and transmittance can be easily configured by selecting the trench width. At sufficiently high angles of incidence, the devices are lossless, apart from material attenuation and scattering due to surface roughness. We numerically simulate a series of devices within the full 0-to-1-range of splitting ratios, for semi-guided plane wave incidence as well as for excitation by focused Gaussian wave bundles. Straightforward cascading of the trenches leads to concepts for 1×M-power dividers and a polarization beam splitter.
Keywords: tet_topic_waveguide

DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning - Schneider, Stefan Balthasar; Karl, Holger; Khalili, Ramin; Hecker, Artur
Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice. Instead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches.
Keywords: mobility management; coordinated multipoint; CoMP; cell selection; resource management; reinforcement learning; multi agent; MARL; self-learning; self-adaptation; QoE

Mariemont – Modernismus und Erinnerung. Videographierter Vortrag für den 5. Belgientag des Belgienzentrums Paderborn ›Belgien – Pralle Kunst des Lebens‹ am 18. Mai 2021 - Süßmann, Johannes

Validation and Performance of Satellite Meteorological Dataset MERRA-2 for Solar and Wind Applications - Khatibi, Arash; Krauter, Stefan (Energies)
Fast-growing energy demand of the world makes the researchers focus on finding new energy sources or optimizing already-developed approaches. For an efficient use of solar and wind energy in an energy system, correct design and sizing of a power system is of high importance and improving or optimizing the process of data obtaining for this purpose leads to higher performance and lower cost per unit of energy. It is essential to have the most precise possible estimation of solar and wind energy potential and other local weather parameters in order to fully feed the demand and avoid extra costs. There are various methods for obtaining local data, such as local measurements, official organizational data, satellite obtained, and reanalysis data. In this paper, the Modern-Era Retrospective analysis for Research and Applications dataset version 2 (MERRA-2) dataset provided by NASA is introduced and its performance is evaluated by comparison to various locally measured datasets offered by meteorological institutions such as Meteonorm and Deutscher Wetterdienst (DWD, or Germany’s National Meteorological Service) around the world. After comparison, correlation coefficients from 0.95 to 0.99 are observed for monthly global horizontal irradiance values. In the case of air temperature, correlation coefficients of 0.99 and for wind speed from 0.81 to 0.99 are observed. High correlation with ground measurements and relatively low errors are confirmed, especially for irradiance and temperature values, that makes MERRA-2 a valuable dataset, considering its world coverage and availability.
Keywords: Solar irradiance; MERRA 2; Meteonorm; DWD

A wavelength and polarization selective photon sieve for holographic applications - Frese, Daniel; Sain, Basudeb; Zhou, Hongqiang; Wang, Yongtian; Huang, Lingling; Zentgraf, Thomas (Nanophotonics)
Optical metasurfaces are perfect candidates for the phase and amplitude modulation of light, featuring an excellent basis for holographic applications. In this work, we present a dual amplitude holographic scheme based on the photon sieve principle, which is then combined with a phase hologram by utilizing the Pancharatnam–Berry phase. We demonstrate that two types of apertures, rectangular and square shapes in a gold film filled with silicon nanoantennas are sufficient to create two amplitude holograms at two different wavelengths in the visible, multiplexed with an additional phase-only hologram. The nanoantennas are tailored to adjust the spectral transmittance of the apertures, enabling the wavelength sensitivity. The phase-only hologram is implemented by utilizing the anisotropic rectangular structure. Interestingly, such three holograms have quantitative mathematical correlations with each other. Thus, the flexibility of polarization and wavelength channels can be utilized with custom-tailored features to achieve such amplitude and phase holography simultaneously without sacrificing any space-bandwidth product. The present scheme has the potential to store different pieces of information which can be displayed separately by switching the wavelength or the polarization state of the reading light beam.

Explicit multiobjective model predictive control for nonlinear systems with symmetries - Ober-Blöbaum, Sina; Peitz, Sebastian (International Journal of Robust and Nonlinear Control)
Model predictive control is a prominent approach to construct a feedback control loop for dynamical systems. Due to real-time constraints, the major challenge in MPC is to solve model-based optimal control problems in a very short amount of time. For linear-quadratic problems, Bemporad et al. have proposed an explicit formulation where the underlying optimization problems are solved a priori in an offline phase. In this article, we present an extension of this concept in two significant ways. We consider nonlinear problems and - more importantly - problems with multiple conflicting objective functions. In the offline phase, we build a library of Pareto optimal solutions from which we then obtain a valid compromise solution in the online phase according to a decision maker's preference. Since the standard multi-parametric programming approach is no longer valid in this situation, we instead use interpolation between different entries of the library. To reduce the number of problems that have to be solved in the offline phase, we exploit symmetries in the dynamical system and the corresponding multiobjective optimal control problem. The results are verified using two different examples from autonomous driving.

Finanzielle Netze. Die bayerisch–französische Familienbank von Eichthal und ihre Investitionspläne in Griechenland in den 1830er Jahren/ Οικονομικά δίκτυα. Η βαυαρογαλλική οικογενειακή τράπεζα των Άιχταλ και τα επενδυτικά σχέδιά της στην Ελλάδα κατά τη δεκαετία του 1830 - Schönhärl, Korinna
Als Griechenland 1830 seine Unabhängigkeit erlangte, war das Land wirtschaftlich wenig entwickelt und von der Industrialisierung noch kaum berührt. Kredite für die Gründung oder den Ausbau von Unternehmen waren auf Grund des Kapitalmangels entweder unmöglich oder extrem teuer – ein für die wirtschaftliche Entwicklung ernst zu nehmendes Hemmnis. Das Land brauchte zur wirtschaftlichen Entwicklung also Investitionen aus dem Ausland. Jedoch hielten sich die europäischen Banken und Anleger mit solchen Investitionen vor den 1870er Jahren zurück. Warum diese Scheu der Kapitalanleger vor Griechenland, obwohl sie anderswo keineswegs vor risikoreichen Investitionen zurückschreckten, wenn nur entsprechend hohe Erträge lockten? Dieser Frage möchte der Beitrag anhand eines Beispiels nachgehen: der bayerisch-französischen Bankiersfamilie von Eichthal, die in den 1830er Jahren enge Geschäftsbeziehungen nach Griechenland aufbaute und zeitweilig sehr interessiert an Investitionen war – bevor das Bankhaus sich von diesen Plänen schließlich unverrichteter Dinge wieder abwandte. Das kulturelle Interesse an Griechenland überdauerte dagegen bis in die 1880er Jahre. Die Eichthals eignen sich hervorragend, um paradigmatisch zu untersuchen, auf welcher Grundlage und wie europäische Bankiers ihre Investitionsentscheidungen für oder gegen Griechenland trafen.

Design of Distributed Reconfigurable Robotics Systems with ReconROS - Lienen, Christian; Platzner, Marco (arXiv:2107.07208)
Robotics applications process large amounts of data in real-time and require compute platforms that provide high performance and energy-efficiency. FPGAs are well-suited for many of these applications, but there is a reluctance in the robotics community to use hardware acceleration due to increased design complexity and a lack of consistent programming models across the software/hardware boundary. In this paper we present ReconROS, a framework that integrates the widely-used robot operating system (ROS) with ReconOS, which features multithreaded programming of hardware and software threads for reconfigurable computers. This unique combination gives ROS2 developers the flexibility to transparently accelerate parts of their robotics applications in hardware. We elaborate on the architecture and the design flow for ReconROS and report on a set of experiments that underline the feasibility and flexibility of our approach.

Tomographie des Schallfelds von Ultraschallwandlern mittels Schlierentechnik - Hetkämper, Tim; Dreiling, Dmitrij; Claes, Leander; Henning, Bernd (Fortschritte der Akustik - DAGA 2021)

Rezension: Hendrik Kasten und Denis Vogel: Grundlagen der ebenen Geometrie – Eine zugängliche aber exakte Einführung in die ebene Geometrie - Hoffmann, Max (Mathematische Semesterberichte)

German university students’ views of nature of science in the introductory phase - Woitkowski, David; Rochell, Leonie; Bauer, Anna (Physical Review Physics Education Research)

HyOpt - Optimization-Based Development of Hybrid Materials - Triebus, Marcel; Tröster, Thomas (9th NRW Nano Conference - Innovations in Materials and Applications)

Providing Decision Makers with Tailored Decision Support Systems - Kirchhoff, Jonas (The 1st Early Career Researchers Workshop Co-Located with ECSS 2021)

The digital home learning environment and its relation to children’s ICT self-efficacy - Bonanati, Sabrina; Buhl, Heike M. (Learning Environments Research)
With the rapid progress of technological development, self-efficacy in reference to digital devices (i.e., information and computer technology [ICT] self-efficacy) is an important driver that helps students to deal with technological problems and support their lifelong learning processes. Schools, peers, and home learning environments are important sources for the development of positive self-efficacy. Expanding on previous research, we investigated the associations between different aspects of the digital home learning environment and students’ ICT self-efficacy. The moderation effects of gender were also tested. A total of 651 children answered a questionnaire about different digital home learning environment dimensions and estimated their ICT self-efficacy using an adapted scale—Schwarzer and Jerusalem’s (1999) general self-efficacy scale. Using the structural equation modeling technique, a digital home learning environment containing six different qualities of parental support was investigated. Families’ cultural capital, parents’ attitudes toward the Internet, and shared Internet activities at home contributed positively to ICT self-efficacy. We observed small gender differences, with the moderation effect being nonsignificant. The results help researchers and practitioners to understand how different dimensions of the digital home learning environment support ICT self-efficacy. We will discuss how parents can enhance the home learning environment and how teachers can integrate this knowledge into formal education.
Keywords: Digital media use; Gender; Home learning environment; ICT self-efcacy; Motivation; Parental involvement

Latent Congruence Model to Investigate Similarity and Accuracy in Family Members' Perception: The Challenge of Cross-National and Cross-Informant Measurement (Non)Invariance - Tagliabue, Semira; Zambelli, Michela; Sorgente, Angela; Sommer, Sabrina; Hoellger, Christian; Buhl, Heike M.; Lanz, Margherita (Frontiers in Psychology)
Several methods are available to answer questions regarding similarity and accuracy, each of which has specific properties and limitations. This study focuses on the Latent Congruence Model (LCM; Cheung, 2009), because of its capacity to deal with cross-informant measurement invariance issues. Until now, no cross-national applications of LCM are present in the literature, perhaps because of the difficulty to deal with both cross-national and cross-informant measurement issues implied by those models. This study presents a step-by-step procedure to apply LCM to dyadic cross-national research designs controlling for both cross-national and cross-informant measurement invariance. An illustrative example on parent–child support exchanges in Italy and Germany is provided. Findings help to show the different possible scenarios of partial invariance, and a discussion related to how to deal with those scenarios is provided. Future perspectives in the study of parent–child similarity and accuracy in cross-national research will be discussed.
Keywords: latent congruence model; measurement invariance; similarity; accuracy; cross-national; cross-informant; parent-child relationship; support exchanges

Intergenerational Value Similarity and Subjective Well-Being - Hoellger, Christian; Sommer, Sabrina; Buhl, Heike M. (Journal of Family Issues)
This investigation concentrates on the association of intergenerational value similarity and adult children’s and parents’subjective well-being, on the linkage between relationship quality and subjective well-being. Mediation effects of the relationship quality on the associations between value similarity and subjective well-being were focused. The sample consisted of 600 adult German children (53.8% women) and their parents. Dyadic correlations were constructed to determine the value similarity. In this study, the general value orientation and the family values were objects of research. We measured the subjective well-being with the Satisfaction with Life Scale and we used the Network of Relationships Inventory (NRI) to measure the relationship quality. Associations between subjective well-being and value similarity, and between subjective well-being and relationship quality, as well as mediation effects, were found. All effects depend on gender and perspective.
Keywords: adult child–parent dyads; relationship quality; life satisfaction; parent–child relationship; intergenerational stake hypothesis; mediation analyses

Augmented Reality als Experimentierhilfe bei Beobachtung und Deutung - Peeters, Hendrik; Habig, Sebastian; Fechner, Sabine (Naturwissenschaftlicher Unterricht und Lehrerbildung im Umbruch?)
Keywords: digitale Medien

Messverfahren für die akustische Absorption in reinen Fluiden zur Bestimmung der Volumenviskosität - Claes, Leander
Die vollständige Beschreibung fluiddynamischer und akustischer Vorgänge setzt voraus, dass die Eigenschaften des Fluids hinlänglich bekannt sind.Während Fluidkenngrößen, wie etwa die Schallgeschwindigkeit oder die Scherviskosität, für viele Flüssigkeiten über weite Bereiche des thermodynamischen Zustandsraums bekannt sind, existieren für die Volumenviskosität nur eine geringe Anzahl Messdaten.In dieser Arbeit wird daher ein Messverfahren zur selektiven Bestimmung der Volumenviskosität von Flüssigkeiten, basierend auf der Absorption von Ultraschallwellen, entwickelt und realisiert.Schwerpunkte bilden dabei der simulationsgestützte Entwurf von Algorithmen zur Auswertung der Messsignale sowie die Analyse und Weiterentwicklung einer Messanordnung, basierend auf dem Puls-Echo-Verfahren. Neben der Absorption im Fluid treten dabei weitere Effekte (zum Beispiel Beugung oder unvollständige Reflexion) auf, die das akustische Signal schwächen oder anderweitig beeinflussen. Die Entwicklung von Verfahren zur Trennung dieser Effekte von der akustischen Absorption bildet daher einen weiteren Schwerpunkt dieser Arbeit.Abschließend wird die Volumenviskosität aus der gemessenen akustischen Absorption für unterschiedliche Fluide in verschiedenen thermodynamischen Zuständen unter Zuhilfenahme anderer bekannter Fluidkenngrößen bestimmt sowie eine Unsicherheitsbetrachtung durchgeführt.

Spectral Asymptotics for Kinetic Brownian Motion on Surfaces of Constant Curvature - Kolb, Martin; Weich, Tobias; Wolf, Lasse (Annales Henri Poincaré)
The kinetic Brownian motion on the sphere bundle of a Riemannian manifold M is a stochastic process that models a random perturbation of the geodesic flow. If M is an orientable compact constantly curved surface, we show that in the limit of infinitely large perturbation the L2-spectrum of the infinitesimal generator of a time-rescaled version of the process converges to the Laplace spectrum of the base manifold.

Wave Front Sets of Nilpotent Lie Group Representations - Weich, Tobias; Budde, Julia (arXiv:2103.02968v1)

Have Academics’ Citation Patterns Changed in Response to the Rise of World University Rankings? A Test Using First-Citation Speeds - Lee, Soo Jeung; Schneijderberg, Christian; Kim, Yangson; Steinhardt, Isabel (Sustainability)
Academics may actively respond to the expectations of the academic status market, which have largely been shaped by the World University Rankings (WURs). This study empirically examines how academics’ citation patterns have changed in response to the rise of an “evaluation environment” in academia. We regard the WURs to be a macro-level trigger for cementing a bibliometric-based evaluation environment in academia. Our analyses of citation patterns in papers published in two higher education journals explicitly considered three distinct periods: the pre-WURs (1990–2003), the period of WURs implementation (2004–2010), and the period of adaption to WURs (2011–2017). We applied the nonparametric Kaplan–Meier method to compare first-citation speeds of papers published across the three periods. We found that not only has first-citation speed become faster, but first-citation probability has also increased following the emergence of the WURs. Applying Cox proportional hazard models to first-citation probabilities, we identified journal impact factors and third-party funding as factors influencing first-citation probability, while other author- and paper-related factors showed limited effects. We also found that the general effects of different factors on first-citation speeds have changed with the emergence of the WURs. The findings expand our understanding of the citation patterns of academics in the rise of WURs and provide practical grounds for research policy as well as higher education policy.
Keywords: world university rankings; citation; first-citation speed; Minerva; Studies in Higher Education

ASSET: A Semi-supervised Approach for Entity Typing in Knowledge Graphs - Zahera, Hamada Mohamed Abdelsamee; Heindorf, Stefan; Ngonga Ngomo, Axel-Cyrille (Proceedings of the 11th on Knowledge Capture Conference)

Drift Detection in Text Data with Document Embeddings - Feldhans, Robert; Wilke, Adrian; Heindorf, Stefan; Shaker, Mohammad Hossein; Hammer, Barbara; Ngonga Ngomo, Axel-Cyrille; Hüllermeier, Eyke (Intelligent Data Engineering and Automated Learning – IDEAL 2021)

Convolutional Hypercomplex Embeddings for Link Prediction - Demir, Caglar; Moussallem, Diego; Heindorf, Stefan; Ngonga Ngomo, Axel-Cyrille (The 13th Asian Conference on Machine Learning, ACML 2021)
Knowledge graph embedding research has mainly focused on the two smallest normed division algebras, $\mathbb{R}$ and $\mathbb{C}$. Recent results suggest that trilinear products of quaternion-valued embeddings can be a more effective means to tackle link prediction. In addition, models based on convolutions on real-valued embeddings often yield state-of-the-art results for link prediction. In this paper, we investigate a composition of convolution operations with hypercomplex multiplications. We propose the four approaches QMult, OMult, ConvQ and ConvO to tackle the link prediction problem. QMult and OMult can be considered as quaternion and octonion extensions of previous state-of-the-art approaches, including DistMult and ComplEx. ConvQ and ConvO build upon QMult and OMult by including convolution operations in a way inspired by the residual learning framework. We evaluated our approaches on seven link prediction datasets including WN18RR, FB15K-237 and YAGO3-10. Experimental results suggest that the benefits of learning hypercomplex-valued vector representations become more apparent as the size and complexity of the knowledge graph grows. ConvO outperforms state-of-the-art approaches on FB15K-237 in MRR, Hit@1 and Hit@3, while QMult, OMult, ConvQ and ConvO outperform state-of-the-approaches on YAGO3-10 in all metrics. Results also suggest that link prediction performances can be further improved via prediction averaging. To foster reproducible research, we provide an open-source implementation of approaches, including training and evaluation scripts as well as pretrained models.

Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts - Nickchen, Tobias; Heindorf, Stefan; Engels, Gregor (2021 IEEE Winter Conference on Applications of Computer Vision (WACV))

Automatically generating instructions from tutorials for search and user navigation - Heindorf, Stefan

Integrated superconducting nanowire single-photon detectors on titanium in-diffused lithium niobate waveguides - Höpker, Jan Philipp; Verma, Varun B; Protte, Maximilian; Ricken, Raimund; Quiring, Viktor; Eigner, Christof; Ebers, Lena; Hammer, Manfred; Förstner, Jens; Silberhorn, Christine; Mirin, Richard P; Woo Nam, Sae; et al. (Journal of Physics: Photonics)
We demonstrate the integration of amorphous tungsten silicide superconducting nanowire single-photon detectors on titanium in-diffused lithium niobate waveguides. We show proof-of-principle detection of evanescently coupled photons of 1550 nm wavelength using bidirectional waveguide coupling for two orthogonal polarization directions. We investigate the internal detection efficiency as well as detector absorption using coupling-independent characterization measurements. Furthermore, we describe strategies to improve the yield and efficiency of these devices.

A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions - Bender, Amelie (Machines)
While increasing digitalization enables multiple advantages for a reliable operation of technical systems, a remaining challenge in the context of condition monitoring is seen in suitable consideration of uncertainties affecting the monitored system. Therefore, a suitable prognostic approach to predict the remaining useful lifetime of complex technical systems is required. To handle different kinds of uncertainties, a novel Multi-Model-Particle Filtering-based prognostic approach is developed and evaluated by the use case of rubber-metal-elements. These elements are maintained preventively due to the strong influence of uncertainties on their behavior. In this paper, two measurement quantities are compared concerning their ability to establish a prediction of the remaining useful lifetime of the monitored elements and the influence of present uncertainties. Based on three performance indices, the results are evaluated. A comparison with predictions of a classical Particle Filter underlines the superiority of the developed Multi-Model-Particle Filter. Finally, the value of the developed method for enabling condition monitoring of technical systems related to uncertainties is given exemplary by a comparison between the preventive and the predictive maintenance strategy for the use case.
Keywords: prognostics; RUL predictions; particle filter; uncertainty consideration; Multi-Model-Particle Filter; model-based approach; rubber-metal-elements; predictive maintenance

Conventional and Machine Learning Approaches for Network and Service Coordination - Schneider, Stefan Balthasar
Network and service coordination is important to provide modern services consisting of multiple interconnected components, e.g., in 5G, network function virtualization (NFV), or cloud and edge computing. In this paper, I outline my dissertation research, which proposes six approaches to automate such network and service coordination. All approaches dynamically react to the current demand and optimize coordination for high service quality and low costs. The approaches range from centralized to distributed methods and from conventional heuristic algorithms and mixed-integer linear programs to machine learning approaches using supervised and reinforcement learning. I briefly discuss their main ideas and advantages over other state-of-the-art approaches and compare strengths and weaknesses.
Keywords: nfv; coordination; machine learning; reinforcement learning; phd; digest

Artificial Intelligence and the Sociotechnical Imaginary: On Skynet, Self-Healing Swarms and Slaughterbots - Weber, Jutta (Drone Imaginaries. The Power of Remote Vision)

From Optimizing Military Operations to Targeting Terrorist Networks: Social Network Analysis in Data-Driven Warfare - Weber, Jutta; Mayer, Katja (Explorations in Digital Cultures)

Human-Machine Learning und Digital Commons - Weber, Jutta (In digitaler Gesellschaft. Neukonfigurationen zwischen Robotern, Algorithmen und Usern)

Students in the spotlight: Using collaborative autoethnography to build a community of learning in the Corona crisis - Steinhardt, Isabel (ISA Pedagogy Series)
Due to the Corona crisis, German Higher Education Institutions had to close their campuses in March and lecturers had to teach online. To understand how the Corona crisis affected students, first this article explains the structural and social inequalities in the German higher education system, using Tinto's (1975; 1997) student engagement theory. Second, the concept of Bergman-Rosamond et al. (2020) is used to analyze the challenges that Corona has raised for students, including current surveys. We found that the closure of the social space campus (and the Corona crisis as a whole) particularly hit hard those students who had previously been affected by (intersectional) inequality. Therefore, to lessen the specific challenges associated with the ad hoc transition to digital studying, the creation of a digital community of learning can help. We demonstrate how such a community can be created by the example seminar, "Digital practices: an autoethnographic observation". During the seminar, students recorded their digital technology use in a journal, and we analyzed the diary entries using the collaborate autoethnography method. The seminar example shows that this method is well suited for the development of a community of learning as it not only places students in the spotlight but as students work together on a topic they get to know each other, and a basis of trust is created through peer-feedback. Therefore, it was important to have a digital space (in this case Mahara) where the exchange could take place. The continuous insight into the students’ "learning status" enabled the lecturer to promote the learning and provide individual assistance for the students.
Keywords: Intersectionality; inequality; gender; diversity; higher-education; crisis

Opening up and Sharing Data from Qualitative Research: A Primer - Steinhardt, Isabel; Fischer, Caroline; Heimstädt, Maximilian; Hirsbrunner, Simon David; Ikiz-Akinci, Dilek; Kressin, Lisa; Kretzer, Susanne; Möllenkamp, Andreas; Portzelt, Maike; Rahal, Rima-Maria; Schimmler, Sonja; Wilke, René; et al.
The call for free access to research data and materials is becoming louder and louder from the political and scientific communities in Germany. More and more researchers are facing demands to open up qualitative research data for scientific purposes. They often have a general interest in sharing their data, but are unsure how to proceed. This handout was developed to provide an initial introduction to opening and sharing qualitative data. It was developed at a workshop held in Berlin in January 2020, organized by the research group „Digitization of Science“ of the Weizenbaum Institute, together with its associate researcher Dr. Isabel Steinhardt from the University of Kassel. The workshop involved staff from German research data centers as well as mentees and mentors from the Fellow Program Open Science who already have experience with Open Science, qualitative research, and interdisciplinary research. The handout is addressed primarily to qualitatively researching scientists in Germany. For this reason, it was initially written in German. One year later, we have now decided to translate the handout into English as well. The reasons are twofold: first, we want to make it accessible to researchers in Germany with little knowledge of German. Second, we also want to give interested people outside Germany an insight into the German system and the German discussion about opening up and sharing qualitative data. Due to the objectives and the history of its development, the handout focuses on the German context. This includes the literature references and further sources, and the references to research data centers as well as legal issues. We have deliberately not included a contextualization of the German situation in international discussions in order to keep the handout as short as possible.

Digitale Praktiken und das Studium - Steinhardt, Isabel (Entwicklungen im Feld der Hochschule)
Anhand einer explorativen Studie in den Fächern Jura und Soziale Arbeit wird rekonstruiert welche Praktiken Studierende in Bezug auf digitale Technologien haben und ob digitale Praktiken im Studium existieren. Dazu wurden narrative Interviews mit sechs Studierenden geführt, die habitushermeneutisch ausgewertet wurden. Die Ergebnisse zeigen keine digitalen Praktiken in Bezug auf das Studium, wohingegen sich digitale Praktiken im alltäglichen Leben zeigen. Für das Studium zeigen sich unterschiedliche Praktiken in der Nutzung digitaler Technologien, die in Beziehung zu den Kapitalsorten stehen, die Studierende besitzen. Die explorativen Ergebnisse legen nahe, dass Studierende unterschiedliche Hilfestellungen in Bezug auf die Digitalisierung des Studiums benötigen, die in der Lehrplanung und -pädagogik berücksichtigt werden müssten.

Geometric and Numerical Methods in Optimal Control and Zermelo Problems on Revolution Surfaces - Applications - Wembe Moafo, Boris Edgar

Concept development of a method for identifying friction coefficients for the numerical simulation of clinching processes - Böhnke, Max; Rossel, Moritz Sebastian; Bielak, Christian Roman; Bobbert, Mathias; Meschut, Gerson (The International Journal of Advanced Manufacturing Technology)
Abstract In order to reduce fuel consumption and thus pollutant emissions, the automotive industry is increasingly developing lightweight construction concepts that are accompanied by an increasing usage of aluminum materials. Due to poor weldability of aluminum in combination with other materials, mechanical joining methods such as clinching were developed and established in series production. In order to predict the relevant characteristics of clinched joints and to ensure the reliability of the process, it is simulated numerically during product development processes. In this regard, the predictive accuracy of the simulated process highly depends on the implemented friction model. In particular, the frictional behavior between the sheet metals as well as between the sheet metal and clinching tools has a significant impact on the geometrical formation of the clinched joint. No testing methods exist that can sufficiently investigate the frictional behavior in sheet materials, especially under high interface pressures, different relative velocities, and long friction paths, while allowing a decoupled consideration of the test parameters. This paper describes the development of further testing concepts based on a proven tribo-torsion test method for determining friction coefficients between sheet metal materials for the simulation of clinching processes. For this purpose, the correlation of interface pressure and the relative velocity between aluminum and steel sheet material in clinching processes is investigated using numerical simulation. Based on these findings, the developed concepts focus on determining friction coefficients at interface pressures of the above materials, yield stress, as well as the reproduction of the occurring friction conditions between sheet metal materials and tool surfaces in clinching processes using tool substitutes. Furthermore, wear investigations between sheet metal material and tool surface were carried out in the friction tests with subsequent EDX analyses of the frictioned tool surfaces. The developed method also allows an optical deformation measurement of the sheet metal material specimen by means of digital image correlation (DIC). Based on a methodological approach, the test setups and the test systems used are explained, and the functionality of the concepts is proven by experimental tests using different sheet metal materials.

Artificial Intelligence in the Age of Technoscience - Weber, Jutta (Routledge Social Science Handbook of Artificial Intelligence)

Technological and Inclusive Education - Considering Students’ Needs Towards Technological Learning in Primary Schools - Schröer, Franz; Tenberge, Claudia (TECHNE SERIES - Forskning i slöjdpedagogik och slöjdvetenskap)
Research on technological educationininterdisciplinary scienceand socialstudies (Sachunterricht) in German primary schools emphasizes that childrenare generally interested in technology. While several STEAM initiatives point towards a growing recognition of technological literacy, the consideration of technology education ininterdisciplinaryscience and social studies is quite underrepresented in practice as well as in research and teacher training.Takinginto accountthe UN-CRPDclaims foran inclusive educational system andthus alsothe right to equally participate in a free society,participation in society through participation in technological development is a fundamental common goal of technological and inclusive education and part of widely recognized technological literacy.It is therefore not well understood how teaching and learning arrangementscan consider and satisfythe needs of all different students. The research project the present paper is part of tries to unveil the appearance of student’s basic needs in relation to technological educationfor all children. Thisinitial quantitative part of a grounded theory study examined the subjective significance of basic psychological needs in interdisciplinary science studies in primary educationto allow for a well-reasoned sample choice for subsequent interviews. Quantitative results point towards some revisions regarding the instrument used and several implications on the diversity of students ́needs in science and social studies. Future research is needed with larger samples for factor-analysis.
Keywords: Inclusion; basic needs; Technology Education; Primary Education; autonomy; competence; social relatedness

„Vom Fahr-Zeug zum Fahr-Ding. Ein Heideggerianischer Kommentar zum autonomen Automobil“ - Alpsancar, Suzana (Autonome Autos – Die Zukunft des Verkehrs und die Dispositive der Mobilität)

Simulation of Guided Waves in Cylinders Subject to Arbitrary Boundary Conditions Using the Scaled Boundary Finite Element Method - Itner, D.; Gravenkamp, H.; Dreiling, Dmitrij; Feldmann, Nadine; Henning, Bernd (14th WCCM-ECCOMAS Congress)

"Wenn sich die Mitte auflöst...", ist das kein Verlust für die Religionspädagogik - ein bilanzierender Tagungsrückblick mit Augenzwinkern - Uppenkamp, Vera; Höger, Christian (Theo-Web. Zeitschrift für Religionspädagogik)

Art. Mädchen/Frauen - Uppenkamp, Vera (Das wissenschaftlich-religionspädagogische Lexikon im Internet www.wirelex.de)

Systemtheorie von Hardware-in-the-Loop-Simulationen mit Anwendung auf einem Fahrzeugachsprüfstand mit parallelkinematischem Lastsimulator - Olma, Simon

Systematik zur Evolution technischer Anforderungen - Lankeit, Christopher

Das Audioviduum. Eine Theoriegeschichte des Menschenmotivs in audiovisuellen Medien - Eckel, Julia

The Public Service Media and Public Service Internet Utopias Survey Report - Fuchs, Christian (The Public Service Media and Public Service Internet Manifesto)

History and Class Consciousness 2.0: Georg Lukács in the Age of Digital Capitalism and Big Data - Fuchs, Christian (Information, Communication and Society)

Engels@200: Friedrich Engels and Digital Capitalism. How Relevant Are Engels’s Works 200 Years After His Birth? - Fuchs, Christian (tripleC: Communication, Capitalism & Critique)

Engels@200: Friedrich Engels in the Age of Digital Capitalism. Introduction - Fuchs, Christian (tripleC: Communication, Capitalism & Critique)

Cornel West and Marxist Humanism - Fuchs, Christian (Critical Sociology)

The Public Service Media and Public Service Internet Manifesto

The Future of Public Service Media and the Internet - Alessandro, D'Arma; Fuchs, Christian; Horowitz, Minna; Unterberger, Klaus (The Public Service Media and Public Service Internet Manifesto)

Introduction - Fuchs, Christian; Unterberger, Klaus (The Public Service Media and Public Service Internet Manifesto)

The Digital Commons and the Digital Public Sphere: How to Advance Digital Democracy Today - Fuchs, Christian (Westminster Papers in Communication and Culture)