@inproceedings{21637,
  author       = {{Lienen, Julian and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings of the 35th AAAI Conference on Artificial Intelligence, AAAI}},
  location     = {{Online}},
  number       = {{10}},
  pages        = {{8583--8591}},
  publisher    = {{AAAI Press}},
  title        = {{{From Label Smoothing to Label Relaxation}}},
  volume       = {{35}},
  year         = {{2021}},
}

@inproceedings{21639,
  abstract     = {{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.    }},
  author       = {{Gottschalk, Sebastian and Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}},
  booktitle    = {{Enterprise, Business-Process and Information Systems Modeling}},
  keywords     = {{Business Model Development, Situational Method Engineering, Mobile App, Business Model Development Tools}},
  publisher    = {{Springer}},
  title        = {{{Situation-specific Business Model Development Methods for Mobile App Developers}}},
  doi          = {{10.1007/978-3-030-79186-5_17}},
  year         = {{2021}},
}

@article{23526,
  abstract     = {{<jats:p>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.</jats:p>}},
  author       = {{Schubert, David and Eikerling, Hendrik and Holtmann, Jörg}},
  issn         = {{2624-9898}},
  journal      = {{Frontiers in Computer Science}},
  publisher    = {{Frontiers Media}},
  title        = {{{Application-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML}}},
  doi          = {{10.3389/fcomp.2021.567873}},
  volume       = {{3}},
  year         = {{2021}},
}

@inproceedings{23708,
  author       = {{Nouri, Zahra and Gadiraju, Ujwal and Engels, Gregor and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the 32nd ACM Conference on Hypertext and Social Media}},
  pages        = {{165--175}},
  title        = {{{What Is Unclear? Computational Assessment of Task Clarity in Crowdsourcing}}},
  year         = {{2021}},
}

@inproceedings{23760,
  abstract     = {{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.}},
  author       = {{Menge, Dennis and Schmid, Hans-Joachim}},
  keywords     = {{Low Temp LS, Low Temperature Laser Sintering, Polyamid 12}},
  location     = {{Austin, TX}},
  title        = {{{Low Temperature Laser Sintering on a Standard System: First Attempts and Results with PA12}}},
  year         = {{2021}},
}

@article{20592,
  abstract     = {{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.}},
  author       = {{Henksmeier, Tobias and Eppinger, Martin and Reineke, Bernhard and Zentgraf, Thomas and Meier, Cedrik and Reuter, Dirk}},
  journal      = {{physica status solidi (a)}},
  keywords     = {{epitaxial lift-off, GaAs/AlxGa1−xAs heterostructures, selective etching}},
  number       = {{3}},
  pages        = {{2000408}},
  title        = {{{Selective Etching of (111)B-Oriented AlxGa1−xAs-Layers for Epitaxial Lift-Off}}},
  doi          = {{https://doi.org/10.1002/pssa.202000408}},
  volume       = {{218}},
  year         = {{2021}},
}

@inproceedings{20693,
  abstract     = {{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.}},
  author       = {{Schneider, Stefan Balthasar and Jürgens, Mirko and Karl, Holger}},
  booktitle    = {{IFIP/IEEE International Symposium on Integrated Network Management (IM)}},
  keywords     = {{network management, service management, coordination, hierarchical, scalability, nfv}},
  location     = {{Bordeaux, France}},
  publisher    = {{IFIP/IEEE}},
  title        = {{{Divide and Conquer: Hierarchical Network and Service Coordination}}},
  year         = {{2021}},
}

@inproceedings{22155,
  author       = {{Gottschalk, Sebastian}},
  booktitle    = {{Advanced Software Engineering. Doctorial Consortium}},
  publisher    = {{CEUR}},
  title        = {{{Situation-specific Development of Business Models for Services in Software Ecosystems}}},
  year         = {{2021}},
}

@inproceedings{22156,
  abstract     = {{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.}},
  author       = {{Spliethöver, Maximilian and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21}},
  location     = {{Online}},
  pages        = {{552--559}},
  title        = {{{Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models}}},
  doi          = {{10.24963/ijcai.2021/77}},
  year         = {{2021}},
}

@inproceedings{22158,
  author       = {{Syed, Shahbaz and Al-Khatib, Khalid and Alshomary, Milad and Wachsmuth, Henning and Potthast, Martin}},
  booktitle    = {{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}},
  pages        = {{3482--3493}},
  title        = {{{Generating Informative Conclusions for Argumentative Texts}}},
  year         = {{2021}},
}

@inproceedings{22159,
  author       = {{Barrow, Joe and Jain, Rajiv and Lipka, Nedim and Dernoncourt, Franck and Morariu, Vlad and Manjunatha, Varun and Oard, Douglas and Resnik, Philip and Wachsmuth, Henning}},
  booktitle    = {{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)}},
  pages        = {{1583--1595}},
  title        = {{{Syntopical Graphs for Computational Argumentation Tasks}}},
  year         = {{2021}},
}

@misc{22304,
  author       = {{Schott, Stefan}},
  title        = {{{Android App Analysis Benchmark Case Generation}}},
  year         = {{2021}},
}

@article{22450,
  abstract     = {{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.}},
  author       = {{Mundry, Jan and Spreyer, Florian and Jmerik, Valentin and Ivanov, Sergey and Zentgraf, Thomas and Betz, Markus}},
  issn         = {{2159-3930}},
  journal      = {{Optical Materials Express}},
  number       = {{7}},
  publisher    = {{OSA}},
  title        = {{{Nonlinear metasurface combining telecom-range intersubband transitions in GaN/AlN quantum wells with resonant plasmonic antenna arrays}}},
  doi          = {{10.1364/ome.426236}},
  volume       = {{11}},
  year         = {{2021}},
}

@unpublished{22509,
  abstract     = {{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.}},
  author       = {{Lienen, Julian and Hüllermeier, Eyke}},
  booktitle    = {{arXiv:2106.11853}},
  title        = {{{Credal Self-Supervised Learning}}},
  year         = {{2021}},
}

@inproceedings{22514,
  author       = {{Kucklick, Jan-Peter and Müller, Jennifer and Beverungen, Daniel and Müller, Oliver}},
  booktitle    = {{European Conference on Information Systems}},
  location     = {{Virtual}},
  title        = {{{Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-based Deep Learning Approach}}},
  year         = {{2021}},
}

@article{22518,
  author       = {{Triebus, Marcel and Gierse, Jan and Marten, Thorsten and Tröster, Thomas}},
  issn         = {{1757-8981}},
  journal      = {{IOP Conference Series: Materials Science and Engineering}},
  location     = {{Virtual - Stuttgart}},
  publisher    = {{IOP Publishing Ltd}},
  title        = {{{A new Device for Determination of Forming-Limit-Curves under Hot-Forming Conditions}}},
  doi          = {{10.1088/1757-899x/1157/1/012052}},
  year         = {{2021}},
}

@article{22523,
  abstract     = {{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.}},
  author       = {{Warkulat, Sonja and Krull, Sebastian and Ortmann, Regina and Klocke, Nina and Pelster, Matthias}},
  journal      = {{Covid Economics}},
  keywords     = {{COVID-19 reporting, willingness to pay, willingness to accept}},
  number       = {{83}},
  pages        = {{183--205}},
  publisher    = {{CEPR Press}},
  title        = {{{COVID-19 reporting and willingness to pay for leisure activities}}},
  year         = {{2021}},
}

@article{21808,
  abstract     = {{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.}},
  author       = {{Schneider, Stefan Balthasar and Khalili, Ramin and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Hecker, Artur}},
  journal      = {{Transactions on Network and Service Management}},
  keywords     = {{network management, service management, coordination, reinforcement learning, self-learning, self-adaptation, multi-objective}},
  publisher    = {{IEEE}},
  title        = {{{Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning}}},
  doi          = {{10.1109/TNSM.2021.3076503}},
  year         = {{2021}},
}

@article{21815,
  abstract     = {{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.}},
  author       = {{Goller, Michael and Ziegler, Simone}},
  issn         = {{1618-8543}},
  journal      = {{bwp@ Spezial}},
  keywords     = {{Berufsethos, Berufswahlmotivation, Wirtschaftspädagogik, Studierende}},
  pages        = {{1--28}},
  title        = {{{Zum Zusammenhang von Berufsethos und der Berufswahlmotivation angehender Wirtschaftspädagog*innen}}},
  volume       = {{18}},
  year         = {{2021}},
}

@article{21820,
  abstract     = {{<jats:p>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.</jats:p>}},
  author       = {{Nüske, Feliks and Koltai, Péter and Boninsegna, Lorenzo and Clementi, Cecilia}},
  issn         = {{1099-4300}},
  journal      = {{Entropy}},
  title        = {{{Spectral Properties of Effective Dynamics from Conditional Expectations}}},
  doi          = {{10.3390/e23020134}},
  year         = {{2021}},
}