@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title = {{{Platform-independent Reputation and Qualification System for Crowdwork}}}, year = {{2020}}, } @unpublished{20211, abstract = {{In many real-world applications, the relative depth of objects in an image is crucial for scene understanding, e.g., to calculate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}}, } @techreport{21419, abstract = {{This paper analyzes the association between tax complexity and foreign direct investments (FDI) based on the newly developed Tax Complexity Index (TCI) and its components. For a sample of 15,607 new foreign subsidiaries, we find no association between total tax complexity, as proxied by the TCI, and the location probability. When we decompose the TCI into tax code complexity and tax framework complexity, we find opposing associations. Tax code complexity is positively related to the location probability, while tax framework complexity is negatively related to it. These associations are, for example, driven by the complexity of transfer pricing and loss offset regulations in the tax code and the dimensions guidance, audits, as well as filing and payments, in the tax framework. In additional analyses, we find that the associations are sensitive to certain characteristics, such as country-specific and firm-specific characteristics. For example, the positive tax code association diminishes when tax rates are high. Overall, we are the first to provide empirical evidence on potential cost-benefit tradeoffs of tax complexity for FDI and thereby enhance prior literature, which has primarily focused on the costs of tax complexity.}}, author = {{Hoppe, Thomas and Schanz, Deborah and Sturm, Susann and Sureth-Sloane, Caren and Voget, Johannes}}, title = {{{The Relation between Tax Complexity and Foreign Direct Investments: Evidence Across Countries}}}, volume = {{No. 13}}, year = {{2020}}, } @article{21422, author = {{Sureth-Sloane, Caren}}, journal = {{AWV-Informationen}}, number = {{5}}, pages = {{16--19}}, title = {{{Steuerkomplexität als Standortfaktor. So komplex ist das Steuersystem in Deutschland}}}, year = {{2020}}, } @inbook{17367, author = {{Hoppe, Julia Amelie and Johansson-Pajala, Rose-Marie and Gustafsson, Christine and Melkas, Helinä and Tusku, Outi and Pekkarinen, Satu and Hennala, Lea and Thommes, Kirsten}}, booktitle = {{Aging between Participation and Simulation - Ethical Dimensions of Socially Assistive Technologies in elderly care }}, editor = {{Haltaufderheide, Joschka and Hovemann, Johanna and Vollmann, Jochen}}, pages = {{139--156}}, publisher = {{De Gruyter}}, title = {{{Assistive robots in care: Expectations and perceptions of older people}}}, doi = {{10.1515/9783110677485-009}}, year = {{2020}}, } @article{17390, author = {{Chantakit, Teanchai and Schlickriede, Christian and Sain, Basudeb and Meyer, Fabian and Weiss, Thomas and Chattham, Nattaporn and Zentgraf, Thomas}}, issn = {{2327-9125}}, journal = {{Photonics Research}}, number = {{9}}, pages = {{1435--1440}}, publisher = {{OSA}}, title = {{{All-dielectric silicon metalens for two-dimensional particle manipulation in optical tweezers}}}, doi = {{10.1364/prj.389200}}, volume = {{8}}, year = {{2020}}, } @article{17426, abstract = {{The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.}}, author = {{Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and Stich, Volker and Hicking, Jan and Bremer, Martin and Kaminski, Lars and Beverungen, Daniel and zur Heiden, Philipp and Tornede, Tanja}}, issn = {{1424-8220}}, journal = {{Sensors}}, title = {{{Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}}}, doi = {{10.3390/s20072099}}, year = {{2020}}, } @unpublished{17605, abstract = {{Syntactic annotation of corpora in the form of part-of-speech (POS) tags is a key requirement for both linguistic research and subsequent automated natural language processing (NLP) tasks. This problem is commonly tackled using machine learning methods, i.e., by training a POS tagger on a sufficiently large corpus of labeled data. While the problem of POS tagging can essentially be considered as solved for modern languages, historical corpora turn out to be much more difficult, especially due to the lack of native speakers and sparsity of training data. Moreover, most texts have no sentences as we know them today, nor a common orthography. These irregularities render the task of automated POS tagging more difficult and error-prone. Under these circumstances, instead of forcing the POS tagger to predict and commit to a single tag, it should be enabled to express its uncertainty. In this paper, we consider POS tagging within the framework of set-valued prediction, which allows the POS tagger to express its uncertainty via predicting a set of candidate POS tags instead of guessing a single one. The goal is to guarantee a high confidence that the correct POS tag is included while keeping the number of candidates small. In our experimental study, we find that extending state-of-the-art POS taggers to set-valued prediction yields more precise and robust taggings, especially for unknown words, i.e., words not occurring in the training data.}}, author = {{Heid, Stefan Helmut and Wever, Marcel Dominik and Hüllermeier, Eyke}}, booktitle = {{Journal of Data Mining and Digital Humanities}}, publisher = {{episciences}}, title = {{{Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction}}}, year = {{2020}}, } @inproceedings{17763, author = {{Haeb-Umbach, Reinhold}}, booktitle = {{Studientexte zur Sprachkommunikation: Elektronische Sprachsignalverarbeitung 2020}}, editor = {{Böck, Ronald and Siegert, Ingo and Wendemuth, Andreas}}, isbn = {{978-3-959081-93-1}}, keywords = {{Poster}}, pages = {{227--234}}, publisher = {{TUDpress, Dresden}}, title = {{{Sprachtechnologien für Digitale Assistenten}}}, year = {{2020}}, }