Erweiterung des epistemologischen Verständnisses durch Konfrontation mit anomalen Daten. - Pollmeier, Pascal; Fechner, Sabine (Naturwissenschaftlicher Unterricht und Lehrerbildung im Umbruch?)

Guaranteeing Properties of Reconfigurable Hardware Circuits with Proof-Carrying Hardware - Wiersema, Tobias
Previous research in proof-carrying hardware has established the feasibility and utility of the approach, and provided a concrete solution for employing it for the certification of functional equivalence checking against a specification, but fell short in connecting it to state-of-the-art formal verification insights, methods and tools. Due to the immense complexity of modern circuits, and verification challenges such as the state explosion problem for sequential circuits, this restriction of readily-available verification solutions severely limited the applicability of the approach in wider contexts. This thesis closes the gap between the PCH approach and current advances in formal hardware verification, provides methods and tools to express and certify a wide range of circuit properties, both functional and non-functional, and presents for the first time prototypes in which circuits that are implemented on actual reconfigurable hardware are verified with PCH methods. Using these results, designers can now apply PCH to establish trust in more complex circuits, by using more diverse properties which they can express using modern, efficient property specification techniques.
Keywords: Proof-Carrying Hardware; Formal Verification; Sequential Circuits; Non-Functional Properties; Functional Properties

Examination of hazardous situations in industrial closed-loop processes using dynamic simulations - Bothe, Mike; Lutters, Nicole; Kenig, Eugeny (Chemical Engineering Transactions)

Option Implied Tax Rate Expectations - Eberbach, Jelena; Sureth-Sloane, Caren; Uhrig-Homburg, Marliese

TaintBench: Automatic real-world malware benchmarking of Android taint analyses - Luo, Linghui; Pauck, Felix; Piskachev, Goran; Benz, Manuel; Pashchenko, Ivan; Mory, Martin; Bodden, Eric; Hermann, Ben; Massacci, Fabio (Empirical Software Engineering)
Due to the lack of established real-world benchmark suites for static taint analyses of Android applications, evaluations of these analyses are often restricted and hard to compare. Even in evaluations that do use real-world apps, details about the ground truth in those apps are rarely documented, which makes it difficult to compare and reproduce the results. To push Android taint analysis research forward, this paper thus recommends criteria for constructing real-world benchmark suites for this specific domain, and presents TaintBench, the first real-world malware benchmark suite with documented taint flows. TaintBench benchmark apps include taint flows with complex structures, and addresses static challenges that are commonly agreed on by the community. Together with the TaintBench suite, we introduce the TaintBench framework, whose goal is to simplify real-world benchmarking of Android taint analyses. First, a usability test shows that the framework improves experts’ performance and perceived usability when documenting and inspecting taint flows. Second, experiments using TaintBench reveal new insights for the taint analysis tools Amandroid and FlowDroid: (i) They are less effective on real-world malware apps than on synthetic benchmark apps. (ii) Predefined lists of sources and sinks heavily impact the tools’ accuracy. (iii) Surprisingly, up-to-date versions of both tools are less accurate than their predecessors.

К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН - Lugovtsova, Yevgeniya; Zeipert, Henning; Johannesmann, Sarah; Nicolai, Marcel; Prager, Jens; Henning, Bernd (МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция)

Entwicklung von Praxiskompetenz durch Kooperationsprozesse von Lehrkräften - Bloh, Thiemo (Zeitschrift für Bildungsforschung)
Zusammenfassung Lehrkräftekooperation wird generell eine positive Bedeutung in Bezug auf Schul- und Unterrichtsentwicklung zugeschrieben. Dabei sind empirische Belege für eine positive Wirksamkeit nach wie vor kaum vorhanden, es gibt sogar Befunde zu ‚negativen‘ Konsequenzen von Lehrkräftekooperation. Um diese Widersprüchlichkeit zu klären, wurde in der vorliegenden Arbeit Kooperation nicht als Instrument bzw. als Technik betrachtet, sondern als soziale Praxis verstanden, in der eigenlogisches, kollektiv-implizites Wissen (re)produziert wird (Community of Practice). Parallel dazu wurde ein praxeologisches Kompetenzverständnis (Praxiskompetenz) eingeführt, das wesentlich auf die Praxeologie Pierre Bourdieus zurückgeht und den Zusammenhang zwischen Lehrkräftekooperation als Community of Practice und kollektiv strukturierter, individueller Kompetenz theoretisch verdeutlicht. Die empirischen Befunde, welche mittels der Dokumentarischen Methode generiert wurden, verweisen auf die Bedeutung unterschiedlicher Relationslogiken (Nicht-Passung, Entfaltung, Herausforderung) für das ‚Lernen‘ von oder innerhalb von Praxiskompetenz(en) und damit auch auf die Wichtigkeit einer grundlegend kollektiv gerahmten Perspektive auf Lehrkräftekooperation. Vor diesem Hintergrund ist ein allzu positiver Blick auf Lehrkräftekooperationsprozesse kritisch zu betrachten.

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)