@inproceedings{22913, author = {{Hüllermeier, Eyke and Mohr, Felix and Tornede, Alexander and Wever, Marcel Dominik}}, location = {{Bilbao (Virtual)}}, title = {{{Automated Machine Learning, Bounded Rationality, and Rational Metareasoning}}}, year = {{2021}}, } @inproceedings{22914, author = {{Mohr, Felix and Wever, Marcel Dominik}}, location = {{Virtual}}, title = {{{Replacing the Ex-Def Baseline in AutoML by Naive AutoML}}}, year = {{2021}}, } @inproceedings{22927, author = {{Derrick, John and Doherty, Simon and Dongol, Brijesh and Schellhorn, Gerhard and Wehrheim, Heike}}, booktitle = {{Proceedings of the 35th International Symposium on Distributed Computing (DISC)}}, publisher = {{Schloß Dagstuhl}}, title = {{{On Strong Observational Refinement and Forward Simulation}}}, year = {{2021}}, } @inproceedings{22959, author = {{Weidmann, Nils and Engels, Gregor}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, location = {{Lille, France}}, title = {{{Concurrent model synchronisation with multiple objectives}}}, doi = {{10.1145/3449639.3459283}}, year = {{2021}}, } @inproceedings{23374, author = {{Kummita, Sriteja and Piskachev, Goran and Spath, Johannes and Bodden, Eric}}, booktitle = {{2021 International Conference on Code Quality (ICCQ)}}, title = {{{Qualitative and Quantitative Analysis of Callgraph Algorithms for Python}}}, doi = {{10.1109/iccq51190.2021.9392986}}, year = {{2021}}, } @inproceedings{21727, abstract = {{Platform-based business models underlie the success of many of today’s largest, fastest-growing, and most disruptive companies. Despite the success of prominent examples, such as Uber and Airbnb, creating a profitable platform ecosystem presents a key challenge for many companies across all industries. Although research provides knowledge about platforms’ different value drivers (e.g., network effects), companies that seek to transform their current business model into a platform-based one lack an artifact to reduce knowledge boundaries, collaborate effectively, and cope with the complexities and dynamics of platform ecosystems. We address this challenge by developing two artifacts and combining research from variability modeling, business model dependencies, and system dynamics. This paper presents a design science research approach to develop the platform ecosystem modeling language and the platform ecosystem development tool that support researcher and practitioner by visualizing and simulating platform ecosystems. }}, author = {{Vorbohle, Christian and Gottschalk, Sebastian}}, booktitle = {{Proceedings of the 29th European Conference on Information Systems (ECIS)}}, keywords = {{Platform Ecosystems, Platform Ecosystem Modeling Language, Platform Ecosystem Development Tool, Business Models, Design Science}}, location = {{Virtual Conference/Workshop}}, publisher = {{AIS}}, title = {{{Towards Visualizing and Simulating Business Models in Dynamic Platform Ecosystems }}}, 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{21820, abstract = {{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.}}, 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}}, } @article{21932, abstract = {{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.}}, author = {{Hammer, Manfred and Ebers, Lena and Förstner, Jens}}, issn = {{0740-3224}}, journal = {{Journal of the Optical Society of America B}}, keywords = {{tet_topic_waveguides}}, number = {{5}}, pages = {{1717}}, title = {{{Resonant evanescent excitation of guided waves with high-order optical angular momentum}}}, doi = {{10.1364/josab.422731}}, volume = {{38}}, year = {{2021}}, } @inproceedings{22013, author = {{Zeipert, Henning and Claes, Leander and Johannesmann, Sarah and Webersen, Manuel and Lugovtsova, Yevgeniya and Prager, Jens and Henning, Bernd}}, location = {{Nürnberg}}, pages = {{91 -- 92}}, title = {{{Measurement and Simulation of Lamb Waves in Adhesive-bonded Multilayer Systems}}}, doi = {{10.5162/SMSI2021/A8.2}}, year = {{2021}}, } @inbook{22057, abstract = {{We construct more efficient cryptosystems with provable security against adaptive attacks, based on simple and natural hardness assumptions in the standard model. Concretely, we describe: – An adaptively-secure variant of the efficient, selectively-secure LWE- based identity-based encryption (IBE) scheme of Agrawal, Boneh, and Boyen (EUROCRYPT 2010). In comparison to the previously most efficient such scheme by Yamada (CRYPTO 2017) we achieve smaller lattice parameters and shorter public keys of size O(log λ), where λ is the security parameter. – Adaptively-secure variants of two efficient selectively-secure pairing- based IBEs of Boneh and Boyen (EUROCRYPT 2004). One is based on the DBDH assumption, has the same ciphertext size as the cor- responding BB04 scheme, and achieves full adaptive security with public parameters of size only O(log λ). The other is based on a q- type assumption and has public key size O(λ), but a ciphertext is only a single group element and the security reduction is quadrat- ically tighter than the corresponding scheme by Jager and Kurek (ASIACRYPT 2018). – A very efficient adaptively-secure verifiable random function where proofs, public keys, and secret keys have size O(log λ). As a technical contribution we introduce blockwise partitioning, which leverages the assumption that a cryptographic hash function is weak near-collision resistant to prove full adaptive security of cryptosystems.}}, author = {{Jager, Tibor and Kurek, Rafael and Niehues, David}}, booktitle = {{Public-Key Cryptography – PKC 2021}}, isbn = {{9783030752446}}, issn = {{0302-9743}}, title = {{{Efficient Adaptively-Secure IB-KEMs and VRFs via Near-Collision Resistance}}}, doi = {{10.1007/978-3-030-75245-3_22}}, year = {{2021}}, } @inbook{22059, abstract = {{Verifiable random functions (VRFs), introduced by Micali, Rabin and Vadhan (FOCS’99), are the public-key equivalent of pseudo- random functions. A public verification key and proofs accompanying the output enable all parties to verify the correctness of the output. How- ever, all known standard model VRFs have a reduction loss that is much worse than what one would expect from known optimal constructions of closely related primitives like unique signatures. We show that: 1. Every security proof for a VRF that relies on a non-interactive assumption has to lose a factor of Q, where Q is the number of adver- sarial queries. To that end, we extend the meta-reduction technique of Bader et al. (EUROCRYPT’16) to also cover VRFs. 2. This raises the question: Is this bound optimal? We answer this ques- tion in the affirmative by presenting the first VRF with a reduction from the non-interactive qDBDHI assumption to the security of VRF that achieves this optimal loss. We thus paint a complete picture of the achievability of tight verifiable random functions: We show that a security loss of Q is unavoidable and present the first construction that achieves this bound.}}, author = {{Niehues, David}}, booktitle = {{Public-Key Cryptography – PKC 2021}}, isbn = {{9783030752477}}, issn = {{0302-9743}}, title = {{{Verifiable Random Functions with Optimal Tightness}}}, doi = {{10.1007/978-3-030-75248-4_3}}, year = {{2021}}, } @article{16867, abstract = {{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.}}, author = {{Gebken, Bennet and Peitz, Sebastian}}, journal = {{Journal of Optimization Theory and Applications}}, pages = {{696--723}}, title = {{{An efficient descent method for locally Lipschitz multiobjective optimization problems}}}, doi = {{10.1007/s10957-020-01803-w}}, volume = {{188}}, year = {{2021}}, } @article{16295, abstract = {{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.}}, author = {{Gebken, Bennet and Peitz, Sebastian}}, journal = {{Journal of Global Optimization}}, pages = {{3--29}}, publisher = {{Springer}}, title = {{{Inverse multiobjective optimization: Inferring decision criteria from data}}}, doi = {{10.1007/s10898-020-00983-z}}, volume = {{80}}, year = {{2021}}, } @inproceedings{22217, author = {{Krauter, Stefan and Khatibi, Arash}}, booktitle = {{Tagungsband des 36. PV-Symposium, 18.-26 Mai 2021, online, ISBN 978-3-948176-14-3, S. 301-304. }}, isbn = {{978-3-948176-14-3}}, location = {{Staffelstein / online}}, pages = {{301--304}}, publisher = {{Conexio}}, title = {{{Einfluss von Steilaufstellung, Nachführung und Einsatz bifazialer PV-Module auf den Speicherbedarf und die Kosten einer 100% EE-Versorgung Deutschlands}}}, year = {{2021}}, } @inproceedings{21953, author = {{Witschen, Linus Matthias and Wiersema, Tobias and Raeisi Nafchi, Masood and Bockhorn, Arne and Platzner, Marco}}, booktitle = {{Proceedings of International Symposium on Applied Reconfigurable Computing (ARC'21)}}, editor = {{Hannig, Frank and Derrien, Steven and Diniz, Pedro and Chillet, Daniel}}, location = {{Virtual conference}}, publisher = {{Springer Lecture Notes in Computer Science}}, title = {{{Timing Optimization for Virtual FPGA Configurations}}}, doi = {{10.1007/978-3-030-79025-7_4}}, year = {{2021}}, } @inproceedings{29235, author = {{Gottschalk, Sebastian and Aziz, Muhammad Suffyan and Yigitbas, Enes and Engels, Gregor}}, booktitle = {{Software Business - 12th International Conference, ICSOB 2021, Drammen, Norway, December 2-3, 2021, Proceedings}}, editor = {{Wang, Xiaofeng and Martini, Antonio and Nguyen-Duc, Anh and Stray, Viktoria}}, pages = {{205–220}}, publisher = {{Springer}}, title = {{{Design Principles for a Crowd-Based Prototype Validation Platform}}}, doi = {{10.1007/978-3-030-91983-2_16}}, volume = {{434}}, year = {{2021}}, } @inbook{25528, abstract = {{Developing effective business models is a complex process for a company where several tasks (e.g., conduct customer interviews) need to be accomplished, and decisions (e.g., advertisement as a revenue stream) must be made. Here, domain experts can guide the choices of tasks and decisions with their knowledge. Nevertheless, this knowledge needs to match the situation of the company (e.g., financial resources) and the application domain of the product/service (e.g., mobile app) to reduce the risk of developing ineffective business models with low market penetration. This is not covered by one-size-fits-all development methods without tailoring before the enaction. Therefore, we conduct a design science study to create a situation-specific development approach for business models. Based on situational method engineering and our previous work in storing knowledge of methods and models in distinct repositories, this paper shows the situation-specific composition and enaction of business model development methods. First, the method engineer composes the development method out of both repositories based on the situational context. Second, the business developer enacts the method and develops the business model. We implement the approach in a tool and evaluate it with a industrial case study on mobile apps.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}}, booktitle = {{Product-focused Software Process Improvement}}, keywords = {{Business Model Development, Situational Method Engineering, Lean Development, Kanban Boards, Canvas Models}}, location = {{Turin}}, publisher = {{Springer}}, title = {{{Situation- and Domain-specific Composition and Enactment of Business Model Development Methods}}}, year = {{2021}}, } @book{29876, author = {{Schröder, Dierk and Böcker, Joachim}}, isbn = {{978-3-662-62699-3}}, pages = {{1625}}, publisher = {{Springer Nature}}, title = {{{Elektrische Antriebe – Regelung von Antriebssystemen}}}, doi = {{10.1007/978-3-662-62700-6}}, year = {{2021}}, } @inproceedings{29849, abstract = {{DC-DC converters for on-board chargers (OBC) of electrical vehicles are usually galvanically isolated allowing modular single-phase PFC front-end solutions, but require transformers which are more bulky, costly and lossy than inductors of non-isolated DC-DCs. Furthermore, for vehicle-to-grid applications, bidirectional converters with transformers are generally more complex and have a higher count on semiconductor switches than transformerless solutions. However, when using non-isolated DC-DC converters within an OBC, the large common-mode (CM) capacitance comprising capacitive parasitics of the traction battery as well as explicit Y-capacitors connecting the high-voltage DC-system (HV-system) within specific HV-loads to ground has to be considered. For the PFC front-end stage, when supplied from the three-phase mains this means that generation of high-frequency and high-amplitude CM voltages, as it is common e.g. with the conventional six-switch full-bridge converter, has to be strictly avoided. For this reason, a modified topology is suggested leading to a different mode of operation and to a very low common-mode noise behaviour: The three-phase four-wire full-bridge PFC with split DC-link, whose midpoint is connected to the mains neutral provides very stable potentials at the DC-link rails and therefore it can be classified as Zero-CM-topology.For dedicated single-phase operation, as required for most OBC, an additional balancing leg may be added to the topology to reduce the required DC-link capacitance and allow non-electrolytic capacitors.The function of the bidirectional Zero-CM three-phase four-wire full-bridge PFC was verified by simulation and on an 11 kW-laboratory sample. The power factor is above 0.999 and an efficiency of 98 % is measured.}}, author = {{Strothmann, Benjamin and Schafmeister, Frank and Böcker, Joachim}}, booktitle = {{2021 IEEE Applied Power Electronics Conference and Exposition (APEC)}}, keywords = {{Three-phase four-wire, OBC, Y2G, PFC, CM, EY charger, balancing circuit}}, publisher = {{IEEE}}, title = {{{Common-Mode-Free Bidirectional Three-Phase PFC-Rectifier for Non-Isolated EV Charger}}}, doi = {{10.1109/apec42165.2021.9487462}}, year = {{2021}}, }