@inbook{16289,
  abstract     = {{In the development of model predictive controllers for PDE-constrained problems, the use of reduced order models is essential to enable real-time applicability. Besides local linearization approaches, proper orthogonal decomposition (POD) has been most widely used in the past in order to derive such models. Due to the huge advances concerning both theory as well as the numerical approximation, a very promising alternative based on the Koopman operator has recently emerged. In this chapter, we present two control strategies for model predictive control of nonlinear PDEs using data-efficient approximations of the Koopman operator. In the first one, the dynamic control system is replaced by a small number of autonomous systems with different yet constant inputs. The control problem is consequently transformed into a switching problem. In the second approach, a bilinear surrogate model is obtained via a convex combination of these autonomous systems. Using a recent convergence result for extended dynamic mode decomposition (EDMD), convergence of the reduced objective function can be shown. We study the properties of these two strategies with respect to solution quality, data requirements, and complexity of the resulting optimization problem using the 1-dimensional Burgers equation and the 2-dimensional Navier–Stokes equations as examples. Finally, an extension for online adaptivity is presented.}},
  author       = {{Peitz, Sebastian and Klus, Stefan}},
  booktitle    = {{Lecture Notes in Control and Information Sciences}},
  isbn         = {{9783030357122}},
  issn         = {{0170-8643}},
  pages        = {{257--282}},
  publisher    = {{Springer}},
  title        = {{{Feedback Control of Nonlinear PDEs Using Data-Efficient Reduced Order Models Based on the Koopman Operator}}},
  doi          = {{10.1007/978-3-030-35713-9_10}},
  volume       = {{484}},
  year         = {{2020}},
}

@article{16290,
  abstract     = {{The control of complex systems is of critical importance in many branches of science, engineering, and industry, many of which are governed by nonlinear partial differential equations. Controlling an unsteady fluid flow is particularly important, as flow control is a key enabler for technologies in energy (e.g., wind, tidal, and combustion), transportation (e.g., planes, trains, and automobiles), security (e.g., tracking airborne contamination), and health (e.g., artificial hearts and artificial respiration). However, the high-dimensional, nonlinear, and multi-scale dynamics make real-time feedback control infeasible. Fortunately, these high- dimensional systems exhibit dominant, low-dimensional patterns of activity that can be exploited for effective control in the sense that knowledge of the entire state of a system is not required. Advances in machine learning have the potential to revolutionize flow control given its ability to extract principled, low-rank feature spaces characterizing such complex systems.We present a novel deep learning modelpredictive control framework that exploits low-rank features of the flow in order to achieve considerable improvements to control performance. Instead of predicting the entire fluid state, we use a recurrent neural network (RNN) to accurately predict the control relevant quantities of the system, which are then embedded into an MPC framework to construct a feedback loop. In order to lower the data requirements and to improve the prediction accuracy and thus the control performance, incoming sensor data are used to update the RNN online. The results are validated using varying fluid flow examples of increasing complexity.}},
  author       = {{Bieker, Katharina and Peitz, Sebastian and Brunton, Steven L. and Kutz, J. Nathan and Dellnitz, Michael}},
  issn         = {{0935-4964}},
  journal      = {{Theoretical and Computational Fluid Dynamics}},
  pages        = {{577–591}},
  title        = {{{Deep model predictive flow control with limited sensor data and online learning}}},
  doi          = {{10.1007/s00162-020-00520-4}},
  volume       = {{34}},
  year         = {{2020}},
}

@article{16299,
  author       = {{Castenow, Jannik and Fischer, Matthias and Harbig, Jonas and Jung, Daniel and Meyer auf der Heide, Friedhelm}},
  issn         = {{0304-3975}},
  journal      = {{Theoretical Computer Science}},
  pages        = {{289--309}},
  title        = {{{Gathering Anonymous, Oblivious Robots on a Grid}}},
  doi          = {{10.1016/j.tcs.2020.02.018}},
  volume       = {{815}},
  year         = {{2020}},
}

@inproceedings{16300,
  author       = {{Wolf, Verena and Bartelheimer, Christian}},
  booktitle    = {{16th International Research Conference in Service Management}},
  location     = {{ La Londe les Maures}},
  title        = {{{Transformation of Actors’ Roles in Service Systems: A Multi-Level Analysis }}},
  year         = {{2020}},
}

@inproceedings{16307,
  author       = {{Wecker, Christian and Hoppe, Anna and Schulz, Andreas and Heine, Jens and Bart, Hans-Jörg and Kenig, Eugeny}},
  publisher    = {{Jahrestreffen der ProcessNet-Fachgruppe Wärme- und Stofftransport}},
  title        = {{{Numerische Untersuchungen des Stofftransports in Flüssig-Flüssig-Systemen unter Berücksichtigung der Marangonikonvektion}}},
  year         = {{2020}},
}

@inproceedings{16308,
  author       = {{Schulz, Andreas and Wecker, Christian and Kenig, Eugeny}},
  publisher    = {{Jahrestreffen der ProcessNet-Fachgruppe Wärme- und Stofftransport}},
  title        = {{{Ein PLIC-basierter Ansatz zur Erfassung des Stoffübergangs an bewegten Phasengrenzflächen}}},
  year         = {{2020}},
}

@article{16309,
  abstract     = {{In recent years, the success of the Koopman operator in dynamical systems
analysis has also fueled the development of Koopman operator-based control
frameworks. In order to preserve the relatively low data requirements for an
approximation via Dynamic Mode Decomposition, a quantization approach was
recently proposed in [Peitz & Klus, Automatica 106, 2019]. This way, control
of nonlinear dynamical systems can be realized by means of switched systems
techniques, using only a finite set of autonomous Koopman operator-based
reduced models. These individual systems can be approximated very efficiently
from data. The main idea is to transform a control system into a set of
autonomous systems for which the optimal switching sequence has to be computed.
In this article, we extend these results to continuous control inputs using
relaxation. This way, we combine the advantages of the data efficiency of
approximating a finite set of autonomous systems with continuous controls. We
show that when using the Koopman generator, this relaxation --- realized by
linear interpolation between two operators --- does not introduce any error for
control affine systems. This allows us to control high-dimensional nonlinear
systems using bilinear, low-dimensional surrogate models. The efficiency of the
proposed approach is demonstrated using several examples with increasing
complexity, from the Duffing oscillator to the chaotic fluidic pinball.}},
  author       = {{Peitz, Sebastian and Otto, Samuel E. and Rowley, Clarence W.}},
  journal      = {{SIAM Journal on Applied Dynamical Systems}},
  number       = {{3}},
  pages        = {{2162--2193}},
  title        = {{{Data-Driven Model Predictive Control using Interpolated Koopman  Generators}}},
  doi          = {{10.1137/20M1325678}},
  volume       = {{19}},
  year         = {{2020}},
}

@article{16334,
  abstract     = {{We analyze the actual behavior of agents in a matching mechanism, using data from a clearinghouse at the Faculty of Business Administration and Economics at a German university, where a variant of the Boston mechanism is used. We supplement this data with data generated in a survey among the students who participated in the clearinghouse. We find that under the current mechanism over 74% of students act strategically by misrepresenting at least one of their preferences. Nevertheless, not all students are able to improve their outcome by doing so. We show that this is mainly due to the incomplete information of students and naiveté. Sophisticated students actually reach significantly better outcomes than naive students. Thus, we find evidence that naive students are exploited by sophisticated students in an incomplete information setting.}},
  author       = {{Hoyer, Britta and Stroh-Maraun, Nadja}},
  journal      = {{Games and Economic Behavior}},
  pages        = {{453 -- 481}},
  title        = {{{Matching Strategies of Heterogeneous Agents under Incomplete Information in a University Clearinghouse}}},
  doi          = {{10.1016/j.geb.2020.03.006}},
  volume       = {{121}},
  year         = {{2020}},
}

@inproceedings{16346,
  author       = {{Daymude, Joshua J. and Gmyr, Robert and Hinnenthal, Kristian and Kostitsyna, Irina and Scheideler, Christian and Richa, Andréa W.}},
  booktitle    = {{Proceedings of the 21st International Conference on Distributed Computing and Networking}},
  isbn         = {{9781450377515}},
  title        = {{{Convex Hull Formation for Programmable Matter}}},
  doi          = {{10.1145/3369740.3372916}},
  year         = {{2020}},
}

@inproceedings{16363,
  author       = {{Hansmeier, Tim and Kaufmann, Paul and Platzner, Marco}},
  booktitle    = {{GECCO '20: Proceedings of the Genetic and Evolutionary Computation Conference Companion}},
  isbn         = {{978-1-4503-7127-8}},
  location     = {{Cancún, Mexico}},
  pages        = {{125--126}},
  publisher    = {{Association for Computing Machinery (ACM)}},
  title        = {{{Enabling XCSF to Cope with Dynamic Environments via an Adaptive Error Threshold}}},
  doi          = {{10.1145/3377929.3389968}},
  year         = {{2020}},
}

@inproceedings{16373,
  author       = {{Oczko, Marie-Christin H. and Stratmann, Lukas and Franke, Mario and Heinovski, Julian and Buse, Dominik S. and Klingler, Florian and Dressler, Falko}},
  booktitle    = {{2020 International Conference on Computing, Networking and Communications (ICNC)}},
  isbn         = {{9781728149059}},
  title        = {{{Integrating Haptic Signals with V2X-based Safety Systems for Vulnerable Road Users}}},
  doi          = {{10.1109/icnc47757.2020.9049723}},
  year         = {{2020}},
}

@inproceedings{16400,
  abstract     = {{Softwarization facilitates the introduction of smart
manufacturing applications in the industry. Manifold devices
such as machine computers, Industrial IoT devices, tablets,
smartphones and smart glasses are integrated into factory networks
to enable shop floor digitalization and big data analysis. To
handle the increasing number of devices and the resulting traffic,
a flexible and scalable factory network is necessary which can be
realized using softwarization technologies like Network Function
Virtualization (NFV). However, the security risks increase with
the increasing number of new devices, so that cyber security must
also be considered in NFV-based networks.

Therefore, extending our previous work, we showcase threat
detection using a cloud-native NFV-driven intrusion detection
system (IDS) that is integrated in our industrial-specific network
services. As a result of the threat detection, the affected network
service is put into quarantine via automatic network reconfiguration.
We use the 5GTANGO service platform to deploy our
developed network services on Kubernetes and to initiate the
network reconfiguration.}},
  author       = {{Müller, Marcel and Behnke, Daniel and Bök, Patrick-Benjamin and Schneider, Stefan Balthasar and Peuster, Manuel and Karl, Holger}},
  booktitle    = {{IEEE Conference on Network Softwarization (NetSoft) Demo Track}},
  location     = {{Ghent, Belgium}},
  publisher    = {{IEEE}},
  title        = {{{Cloud-Native Threat Detection and Containment for Smart Manufacturing}}},
  year         = {{2020}},
}

@inproceedings{13868,
  author       = {{Pukrop, Simon and Mäcker, Alexander and Meyer auf der Heide, Friedhelm}},
  booktitle    = {{Proceedings of the 46th International Conference on Current Trends in Theory and Practice of Computer Science (SOFSEM)}},
  title        = {{{Approximating Weighted Completion Time for Order Scheduling with Setup Times}}},
  year         = {{2020}},
}

@inbook{13108,
  abstract     = {{Diagrammatisches Schlie{\ss}en wird im Zusammenhang mit dem Lernen von Mathmematik und ihrer Symbolsprache als wesentliche Theorie der Wissenskonstruktion diskutiert. Dabei wird h{\"{a}}ufig davon ausgegangen, dass die Wissenskonstruktion im Sinne diagrammatischen Schlie{\ss}ens erfolgt. Deskriptive Rekonstruktionen diagrammatischen Schlie{\ss}ens bei Lernenden stellen jedoch ein Desiderat der mathematikdidaktischen Forschung dar. Der vorliegende Beitrag befasst sich mit der Fragestellung, wie sich diagrammatisches Schlie{\ss}en bei Lernenden rekonstruieren l{\"{a}}sst. Als m{\"{o}}gliche Werkzeuge f{\"{u}}r eine solche Rekonstruktion werden Toulmins Argumentationsschema und Vergnauds Schema-Begriff exemplarisch angewandt, um das diagrammatische Schlie{\ss}en eines Sch{\"{u}}lerpaars beim Einstieg in die Subtraktion negativer Zahlen zu rekonstruieren. Abschlie{\ss}end wird die tats{\"{a}}chliche Eignung der beiden Ans{\"{a}}tze zur Rekonstruktion diagrammatischen Schlie{\ss}ens diskutiert.}},
  author       = {{Schumacher, Jan and Rezat, Sebastian}},
  booktitle    = {{Zeichen und Sprache im Mathematikunterricht}},
  editor       = {{Kadunz, Gert}},
  publisher    = {{Springer}},
  title        = {{{Rekonstruktion diagrammatischen Schließens beim Erlernen der Subtraktion negativer Zahlen. Vergleich zweier methodischer Zugänge}}},
  doi          = {{10.1007/978-3-662-61194-4_5}},
  year         = {{2020}},
}

@article{10330,
  author       = {{Kiesel, Dora and Riehmann, Patrick and Wachsmuth, Henning and Stein, Benno and Fröhlich, Bernd}},
  journal      = {{IEEE Transactions of Visualization & Computer Graphics}},
  number       = {{2}},
  pages        = {{1139--1148}},
  title        = {{{Visual Analysis of Argumentation in Essays}}},
  volume       = {{27}},
  year         = {{2020}},
}

@inproceedings{13584,
  author       = {{Szopinski, Daniel and Schoormann, Thorsten and Kundisch, Dennis}},
  booktitle    = {{Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS)}},
  location     = {{Maui, Hawaii}},
  title        = {{{Criteria as a prelude for guiding taxonomy evaluation}}},
  year         = {{2020}},
}

@techreport{23568,
  abstract     = {{We study the structure of power networks in consideration of local protests against certain
power lines (’not-in-my-backyard’). An application of a network formation game is used to
determine whether or not such protests arise. We examine the existence of stable networks and
their characteristics, when no player wants to make an alteration. Stability within this game is
only reached if each player is sufficiently connected to a power source but is not linked to more
players than necessary. In addition we introduce an algorithm that creates a stable network.}},
  author       = {{Block, Lukas}},
  keywords     = {{Network formation, NIMBY, Power networks, Nash stability}},
  title        = {{{Network formation with NIMBY constraints}}},
  year         = {{2020}},
}

@article{24563,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Laser surface treatment of metals is one option to improve their properties for adhesive bonding. In this paper, a pulsed YVO4 Laser source with a wavelength of 1064 nm and a maximum power of 25 W was utilized to increase the surface area of the steel HCT490X in order to improve its bonding properties with a carbon fibre reinforced polymer (CFRP). Investigated was the influence of the scanning speed of the laser source on the bonding properties. For this purpose, the steel surfaces were ablated at a scanning speed between 1500 and 4500 mm/s. Afterwards the components were bonded with the adhesive HexBond™ 677. After lap shear tests were carried out on the specimen, the surfaces were inspected using scanning electron microscopy (SEM). The experiments revealed that the bonding quality can be improved with a high scanning speed, even when the surface is not completely ablated.</jats:p>}},
  author       = {{Voswinkel, D. and Kloidt, D. and Grydin, O. and Schaper, M.}},
  issn         = {{0944-6524}},
  journal      = {{Production Engineering}},
  pages        = {{263--270}},
  title        = {{{Time efficient laser modification of steel surfaces for advanced bonding in hybrid materials}}},
  doi          = {{10.1007/s11740-020-01006-2}},
  year         = {{2020}},
}

@inproceedings{27106,
  author       = {{Kummert, Chrstina and  Diekmann, Wolfgang and Tews, Karina and Schmid, Hans-Joachim}},
  booktitle    = {{29th Annual International Solid Freeform Fabrication Symposium}},
  title        = {{{Influence of Part Microstructure on Mechanical Properties of PA6X Laser Sintered Specimens}}},
  year         = {{2020}},
}

@article{21252,
  author       = {{Traue, Arne and Book, Gerrit and Kirchgässner, Wilhelm and Wallscheid, Oliver}},
  issn         = {{2162-237X}},
  journal      = {{IEEE Transactions on Neural Networks and Learning Systems}},
  pages        = {{1--10}},
  title        = {{{Toward a Reinforcement Learning Environment Toolbox for Intelligent Electric Motor Control}}},
  doi          = {{10.1109/tnnls.2020.3029573}},
  year         = {{2020}},
}