@unpublished{19603, abstract = {{Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas. Modern MSGs are largely driven by power electronic converters due to their high efficiency and flexibility. Nevertheless, controlling MSGs is a challenging task due to highest requirements on energy availability, safety and voltage quality within a wide range of different MSG topologies. This results in a high demand for comprehensive testing of new control concepts during their development phase and comparisons with the state of the art in order to ensure their feasibility. This applies in particular to data-driven control approaches from the field of reinforcement learning (RL), whose stability and operating behavior can hardly be evaluated a priori. Therefore, the OpenModelica Microgrid Gym (OMG) package, an open-source software toolbox for the simulation and control optimization of MSGs, is proposed. It is capable of modeling and simulating arbitrary MSG topologies and offers a Python-based interface for plug \& play controller testing. In particular, the standardized OpenAI Gym interface allows for easy RL-based controller integration. Besides the presentation of the OMG toolbox, application examples are highlighted including safe Bayesian optimization for low-level controller tuning.}}, author = {{Bode, Henrik and Heid, Stefan Helmut and Weber, Daniel and Hüllermeier, Eyke and Wallscheid, Oliver}}, booktitle = {{arXiv:2005.04869}}, title = {{{Towards a Scalable and Flexible Simulation and Testing Environment Toolbox for Intelligent Microgrid Control}}}, year = {{2020}}, } @inproceedings{19606, abstract = {{Mobile shopping apps have been using Augmented Reality (AR) in the last years to place their products in the environment of the customer. While this is possible with atomic 3D objects, there is is still a lack in the runtime configuration of 3D object compositions based on user needs and environmental constraints. For this, we previously developed an approach for model-based AR-assisted product configuration based on the concept of Dynamic Software Product Lines. In this demonstration paper, we present the corresponding tool support ProConAR in the form of a Product Modeler and a Product Configurator. While the Product Modeler is an Angular web app that splits products (e.g. table) up into atomic parts (e.g. tabletop, table legs, funnier) and saves it within a configuration model, the Product Configurator is an Android client that uses the configuration model to place different product configurations within the environment of the customer. We show technical details of our ready to use tool-chain ProConAR by describing its implementation and usage as well as pointing out future research directions.}}, author = {{Gottschalk, Sebastian and Yigitbas, Enes and Schmidt, Eugen and Engels, Gregor}}, booktitle = {{Human-Centered Software Engineering. HCSE 2020}}, editor = {{Bernhaupt, Regina and Ardito, Carmelo and Sauer, Stefan}}, keywords = {{Product Configuration, Augmented Reality, Model-based, Tool Support}}, location = {{Eindhoven}}, publisher = {{Springer}}, title = {{{ProConAR: A Tool Support for Model-based AR Product Configuration}}}, doi = {{10.1007/978-3-030-64266-2_14}}, volume = {{12481}}, year = {{2020}}, } @inproceedings{19607, abstract = {{Modern services consist of modular, interconnected components, e.g., microservices forming a service mesh. To dynamically adjust to ever-changing service demands, service components have to be instantiated on nodes across the network. Incoming flows requesting a service then need to be routed through the deployed instances while considering node and link capacities. Ultimately, the goal is to maximize the successfully served flows and Quality of Service (QoS) through online service coordination. Current approaches for service coordination are usually centralized, assuming up-to-date global knowledge and making global decisions for all nodes in the network. Such global knowledge and centralized decisions are not realistic in practical large-scale networks. To solve this problem, we propose two algorithms for fully distributed service coordination. The proposed algorithms can be executed individually at each node in parallel and require only very limited global knowledge. We compare and evaluate both algorithms with a state-of-the-art centralized approach in extensive simulations on a large-scale, real-world network topology. Our results indicate that the two algorithms can compete with centralized approaches in terms of solution quality but require less global knowledge and are magnitudes faster (more than 100x).}}, author = {{Schneider, Stefan Balthasar and Klenner, Lars Dietrich and Karl, Holger}}, booktitle = {{IEEE International Conference on Network and Service Management (CNSM)}}, keywords = {{distributed management, service coordination, network coordination, nfv, softwarization, orchestration}}, publisher = {{IEEE}}, title = {{{Every Node for Itself: Fully Distributed Service Coordination}}}, year = {{2020}}, } @inproceedings{19609, abstract = {{Modern services comprise interconnected components, e.g., microservices in a service mesh, that can scale and run on multiple nodes across the network on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities and changing demands 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 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 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, it significantly improves flow throughput and overall network utility on real-world network topologies and traffic traces. It also learns to optimize different objectives, generalizes to scenarios with unseen, stochastic traffic patterns, and scales to large real-world networks.}}, author = {{Schneider, Stefan Balthasar and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Khalili, Ramin and Hecker, Artur}}, booktitle = {{IEEE International Conference on Network and Service Management (CNSM)}}, keywords = {{self-driving networks, self-learning, network coordination, service coordination, reinforcement learning, deep learning, nfv}}, publisher = {{IEEE}}, title = {{{Self-Driving Network and Service Coordination Using Deep Reinforcement Learning}}}, year = {{2020}}, } @article{19939, author = {{Kreusser, Lisa Maria and McLachlan, Robert I and Offen, Christian}}, issn = {{0951-7715}}, journal = {{Nonlinearity}}, number = {{5}}, pages = {{2335--2363}}, title = {{{Detection of high codimensional bifurcations in variational PDEs}}}, doi = {{10.1088/1361-6544/ab7293}}, volume = {{33}}, year = {{2020}}, } @phdthesis{19947, abstract = {{Ordinary differential equations (ODEs) and partial differential equations (PDEs) arise in most scientific disciplines that make use of mathematical techniques. As exact solutions are in general not computable, numerical methods are used to obtain approximate solutions. In order to draw valid conclusions from numerical computations, it is crucial to understand which qualitative aspects numerical solutions have in common with the exact solution. Symplecticity is a subtle notion that is related to a rich family of geometric properties of Hamiltonian systems. While the effects of preserving symplecticity under discretisation on long-term behaviour of motions is classically well known, in this thesis (a) the role of symplecticity for the bifurcation behaviour of solutions to Hamiltonian boundary value problems is explained. In parameter dependent systems at a bifurcation point the solution set to a boundary value problem changes qualitatively. Bifurcation problems are systematically translated into the framework of classical catastrophe theory. It is proved that existing classification results in catastrophe theory apply to persistent bifurcations of Hamiltonian boundary value problems. Further results for symmetric settings are derived. (b) It is proved that to preserve generic bifurcations under discretisation it is necessary and sufficient to preserve the symplectic structure of the problem. (c) The catastrophe theory framework for Hamiltonian ODEs is extended to PDEs with variational structure. Recognition equations for A-series singularities for functionals on Banach spaces are derived and used in a numerical example to locate high-codimensional bifurcations. (d) The potential of symplectic integration for infinite-dimensional Lie-Poisson systems (Burgers’ equation, KdV, fluid equations, . . . ) using Clebsch variables is analysed. It is shown that the advantages of symplectic integration can outweigh the disadvantages of integrating over a larger phase space introduced by a Clebsch representation. (e) Finally, the preservation of variational structure of symmetric solutions in multisymplectic PDEs by multisymplectic integrators on the example of (phase-rotating) travelling waves in the nonlinear wave equation is discussed.}}, author = {{Offen, Christian}}, publisher = {{Massey University}}, title = {{{Analysis of Hamiltonian boundary value problems and symplectic integration}}}, year = {{2020}}, } @inproceedings{19953, abstract = {{Current GNN architectures use a vertex neighborhood aggregation scheme, which limits their discriminative power to that of the 1-dimensional Weisfeiler-Lehman (WL) graph isomorphism test. Here, we propose a novel graph convolution operator that is based on the 2-dimensional WL test. We formally show that the resulting 2-WL-GNN architecture is more discriminative than existing GNN approaches. This theoretical result is complemented by experimental studies using synthetic and real data. On multiple common graph classification benchmarks, we demonstrate that the proposed model is competitive with state-of-the-art graph kernels and GNNs.}}, author = {{Damke, Clemens and Melnikov, Vitaly and Hüllermeier, Eyke}}, booktitle = {{Proceedings of the 12th Asian Conference on Machine Learning (ACML 2020)}}, editor = {{Jialin Pan, Sinno and Sugiyama, Masashi}}, keywords = {{graph neural networks, Weisfeiler-Lehman test, cycle detection}}, location = {{Bangkok, Thailand}}, pages = {{49--64}}, publisher = {{PMLR}}, title = {{{A Novel Higher-order Weisfeiler-Lehman Graph Convolution}}}, volume = {{129}}, year = {{2020}}, } @inproceedings{20139, author = {{Spliethöver, Maximilian and Wachsmuth, Henning}}, booktitle = {{Proceedings of the 7th Workshop on Argument Mining (ArgMining 2020)}}, pages = {{76--87}}, title = {{{Argument from Old Man's View: Assessing Social Bias in Argumentation}}}, year = {{2020}}, } @article{20170, author = {{Otroshi, Mortaza and Meschut, Gerson}}, issn = {{0300-3167}}, journal = {{Umformtechnik Blech Rohre Profile}}, number = {{7/20}}, pages = {{48--50}}, title = {{{Spannungszustandsabhängige Schädigungsmodellierung zum Halbhohlstanznieten}}}, year = {{2020}}, } @inproceedings{20191, author = {{Hemsen, Paul and Hesse, Marc and Löken, Nils and Nouri, Zahra}}, booktitle = {{2nd Crowdworking Symposium}}, location = {{Paderborn}}, title = {{{Platform-independent Reputation and Qualification System for Crowdwork}}}, year = {{2020}}, } @unpublished{20211, abstract = {{In many real-world applications, the relative depth of objects in an image is crucial for scene understanding, e.g., to calculate occlusions in augmented reality scenes. Predicting depth in monocular images has recently been tackled using machine learning methods, mainly by treating the problem as a regression task. Yet, being interested in an order relation in the first place, ranking methods suggest themselves as a natural alternative to regression, and indeed, ranking approaches leveraging pairwise comparisons as training information ("object A is closer to the camera than B") have shown promising performance on this problem. In this paper, we elaborate on the use of so-called \emph{listwise} ranking as a generalization of the pairwise approach. Listwise ranking goes beyond pairwise comparisons between objects and considers rankings of arbitrary length as training information. Our approach is based on the Plackett-Luce model, a probability distribution on rankings, which we combine with a state-of-the-art neural network architecture and a sampling strategy to reduce training complexity. An empirical evaluation on benchmark data in a "zero-shot" setting demonstrates the effectiveness of our proposal compared to existing ranking and regression methods.}}, author = {{Lienen, Julian and Hüllermeier, Eyke}}, booktitle = {{arXiv:2010.13118}}, title = {{{Monocular Depth Estimation via Listwise Ranking using the Plackett-Luce model}}}, year = {{2020}}, } @article{20233, abstract = {{The challenge of designing new tunable nonlinear dielectric materials with tailored properties has attracted an increasing amount of interest recently. Herein, we study the effective nonlinear dielectric response of a stochastic paraelectric-dielectric composite consisting of equilibrium distributions of circular and partially penetrable disks (or parallel, infinitely long, identical, partially penetrable, circular cylinders) of a dielectric phase randomly dispersed in a continuous matrix of a paraelectric phase. The random microstructures were generated using the Metropolis Monte Carlo algorithm. The evaluation of the effective permittivity and tunability were carried out by employing either a Landau thermodynamic model or its Johnson’s approximation to describe the field-dependent permittivity of the paraelectric phase and solving continuum-electrostatics equations using finite element calculations. We reveal that the percolation threshold in this composite governs the critical behavior of the effective permittivity and tunability. For microstructures below the percolation threshold, our simulations demonstrate a strong nonlinear behaviour of the field-dependent effective permittivity and very high tunability that increases as a function of dielectric phase concentration. Above the percolation threshold, the effective permittivity shows the tendency to linearization and the tunability dramatically drops down. The highly reduced permittivity and extraordinarily high tunability are obtained for the composites with dielectric impenetrable disks at high concentrations, in which the triggering of the percolation transition is avoided. The reported results cast light on distinct nonlinear behaviour of 2D and 3D stochastic composites and can guide the design of novel composites with the controlled morphology and tailored permittivity and tunability.}}, author = {{Myroshnychenko, Viktor and Smirnov, Stanislav and Jose, Pious Mathews Mulavarickal and Brosseau, Christian and Förstner, Jens}}, issn = {{1359-6454}}, journal = {{Acta Materialia}}, pages = {{116432}}, title = {{{Nonlinear dielectric properties of random paraelectric-dielectric composites}}}, doi = {{10.1016/j.actamat.2020.10.051}}, volume = {{203}}, year = {{2020}}, } @article{29045, author = {{Engels, Gregor}}, issn = {{2366-6145}}, journal = {{Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO)}}, pages = {{363--370}}, title = {{{Der digitale Fußabdruck, Schatten oder Zwilling von Maschinen und Menschen}}}, doi = {{10.1007/s11612-020-00527-9}}, year = {{2020}}, } @techreport{21406, abstract = {{Previous accounting research shows that taxes affect decision making by individuals and firms. Most studies assume that agents have an accurate perception regarding their tax burden. However, there is a growing body of literature analyzing whether taxes are indeed perceived correctly. We review 127 studies on the measurement of tax misperception and its behavioral implications. The review reveals that many taxpayers have substantial tax misperceptions that lead to biased decision making. We develop a Behavioral Taxpayer Response Model on the impact of provided tax information on tax perception. Besides individual traits, characteristics of the tax information and the decision environment determine the extent of tax misperception. We discuss opportunities for future research and methodological limitations. While there is much evidence on tax misperception at the individual level, we hardly find any research at the firm level. Little is known about the real effects of managers’ tax misperception and on how tax information is strategically managed to impact stakeholders. This research gap is surprising as a large part of the accounting literature analyzes decision making and disclosure of firms. We recommend a mixed-method approach combining experiments, surveys, and archival data analyses to improve the knowledge on tax misperception and its consequences.}}, author = {{Blaufus, Kay and Chirvi, Malte and Huber, Hans-Peter and Maiterth, Ralf and Sureth-Sloane, Caren}}, title = {{{Tax Misperception and Its Effects on Decision Making - a Literature Review}}}, volume = {{No. 39}}, year = {{2020}}, } @techreport{21410, abstract = {{We analyze the impact of trust on bargaining behavior between auditor and auditee in a tax setting. We study the effect of interpersonal trust and trust in government on both taxpayer and tax auditor. In an experiment with variation in pairwise trust settings, we find evidence that both kinds of trust affect the bargaining behavior, albeit in different ways. While trust in government increases taxpayers’ tax offers, interpersonal trust may lead to more concessionary behavior of tax auditors moderated by trust in government. Our findings help tax authorities to shape programs to enhance compliance in an atmosphere of trust.}}, author = {{Eberhartinger, Eva and Speitmann, Raffael and Sureth-Sloane, Caren}}, title = {{{How Does Trust Affect Concessionary Behavior in Tax Bargaining?}}}, volume = {{No. 41}}, year = {{2020}}, } @techreport{21411, abstract = {{This study examines the visibility of the GAAP effective tax rate (ETR) in firms’ financial statements as a distinct disclosure choice. Applying a game-theory disclosure model for voluntary disclosure strategies of firms to a tax setting, we argue that firms face a trade-off in their ETR disclosure decisions. On the one hand, firms have an incentive to enhance their ETR disclosure when the ratio offers shareholders “favourable conditions”, for example in terms of higher expected after-tax cash-flows. On the other hand, the disclosure of a favourable low ETR could attract the attention of tax auditors and the public and ultimately result in disclosure costs. We empirically test disclosure behaviour by examining the relation between disclosure visibility and different ETR conditions that reflect different stakeholder specific costs and benefits. While we find that unfavourable ETR conditions are not highlighted, we observe higher disclosure visibility for favourable ETRs (smooth, close to the industry average, decreasing). Additional analyses reveal that this high visibility is characteristic of firm-years with only moderately decreasing ETRs at usual ETR levels, while extreme ETRs are not highlighted. Interestingly and in contrast to our main results, a subsample of family firms do not seem to highlight favourable ETRs.}}, author = {{Flagmeier, Vanessa and Müller, Jens and Sureth-Sloane, Caren}}, title = {{{When Do Firms Highlight Their Effective Tax Rate?}}}, volume = {{No. 37}}, year = {{2020}}, } @techreport{21414, author = {{Heile, Vanessa and Huber, Hans-Peter and Maiterth, Ralf and Sureth-Sloane, Caren}}, title = {{{Umfrage: Steuerliche Verwaltungskosten, steuerliche Corona-Soforthilfemaßnahmen und Investitionen in der Krise}}}, doi = {{10.52569/RUHF6645}}, year = {{2020}}, } @techreport{21416, abstract = {{This article comprehensively reviews Australia’s corporate income tax complexity as faced by multinational corporations (MNCs) and compares it to the average of the remaining OECD countries. Building on unique survey data, I find that the Australian tax code is considerably more complex than the OECD average, which is mainly due to overly complex anti-avoidance legislation, such as regulations on transfer pricing, general anti-avoidance or controlled foreign corporations (CFC). In contrast, Australia’s tax framework, which covers processes and features such as tax law enactment or tax audits, is close to the OECD average. A more granular analysis yields further interesting insights. For example, excessive details in the tax code and the time between the announcement of a tax law change and its enactment turn out to be serious issues in Australia relative to the remaining OECD countries.}}, author = {{Hoppe, Thomas}}, title = {{{Tax Complexity in Australia - A Survey-Based Comparison to the OECD Average}}}, volume = {{No. 14}}, year = {{2020}}, } @techreport{21417, author = {{Hoppe, Thomas and Schanz, Deborah and Schipp, Adrian and Siegel, Felix and Sturm, Susann and Sureth-Sloane, Caren}}, title = {{{2018 Global MNC Tax Complexity Survey}}}, doi = {{10.52569/RPVO1003}}, year = {{2020}}, } @techreport{21418, abstract = {{This paper introduces an index that comprehensively measures the complexity of countries’ corporate income tax systems faced by multinational corporations. It builds on surveys of highly experienced tax consultants of the largest international tax services networks. The index, called the Tax Complexity Index (TCI), is composed of a tax code subindex covering tax regulations and a tax framework subindex covering tax processes and features. For a sample of 100 countries, we find that tax complexity varies considerably across countries, and tax code and framework complexity also vary within countries. Among others, tax complexity is strongly driven by the complexity of transfer pricing regulations in the tax code and tax audits in the tax framework. When analyzing the associations with other country characteristics, we identify different patterns. For example, with regard to GDP, we find a positive association with tax code complexity and a negative association with tax framework complexity, suggesting that highly economically developed countries tend to have more complex tax codes and less complex frameworks. Overall, our tax complexity measures can serve as valuable proxies in future research and supportive tools for a variety of firm decisions and national and international tax policy discussions.}}, author = {{Hoppe, Thomas and Schanz, Deborah and Sturm, Susann and Sureth-Sloane, Caren}}, title = {{{Measuring Tax Complexity Across Countries: A Survey Study on MNCs}}}, volume = {{No. 5}}, year = {{2020}}, }