@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Voltage Switchgear to Enable the Energy and Mobility Revolutions}}}, doi = {{10.3390/s20072099}}, year = {{2020}}, } @unpublished{17605, abstract = {{Syntactic annotation of corpora in the form of part-of-speech (POS) tags is a key requirement for both linguistic research and subsequent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}}, } @article{17803, abstract = {{We numerically simulate multiple light scattering in discrete disordered media represented by large clusters of irregular non-absorbing particles. The packing density of clusters is 0.5. With such conditions diffuse scattering is significantly reduced and light transport follows propagation channels that are determined by the particle size and topology of the medium. This kind of localization produces coherent backscattering intensity surge and enhanced negative polarization branch if compared to lower density samples.}}, author = {{Grynko, Yevgen and Shkuratov, Yuriy and Förstner, Jens}}, issn = {{0022-4073}}, journal = {{Journal of Quantitative Spectroscopy and Radiative Transfer}}, keywords = {{tet_topic_scattering}}, pages = {{107234}}, title = {{{Light backscattering from large clusters of densely packed irregular particles}}}, doi = {{10.1016/j.jqsrt.2020.107234}}, volume = {{255}}, year = {{2020}}, } @inproceedings{18876, author = {{Reinhold, Jannik and Frank, Maximilian and Koldewey, Christian and Dumitrescu, Roman and Buss, Eugen}}, booktitle = {{Proceedings of the ISPIM Connects Bangkok – Partnering for an Innovative Community}}, publisher = {{LUT Scientific and Expertise Publications}}, title = {{{In-depth Analysis of the Effects of Smart Services on Value Creation}}}, year = {{2020}}, } @article{19153, author = {{Eke, Norbert Otto}}, journal = {{German Life and Letters (Special Issue: Herta Müller and the Currents of European History)}}, number = {{1}}, pages = {{72--84}}, title = {{{Der ‚Eigene Kalender‘ des Erinnerns: Die Wahrheit der erfundenen Erinnerung in Herta Müllers Romanen, Erzählungen und Essays}}}, volume = {{73}}, year = {{2020}}, } @inbook{20568, author = {{Reinhold, Jannik and Koldewey, Christian and Dumitrescu, Roman}}, booktitle = {{Der Geschäftsmodell-Toolguide }}, editor = {{Buchholz, Birgit and Bürger, Matthias}}, pages = {{52--56}}, publisher = {{Campus Verlag}}, title = {{{GEMINI-Modellierungssprache für Wertschöpfungssysteme}}}, year = {{2020}}, } @inbook{20570, author = {{Koldewey, Christian and Reinhold, Jannik and Dumitrescu, Roman}}, booktitle = {{Der Geschäftsmodell-Toolguide}}, editor = {{Buchholz, Birgit and Bürger, Matthias}}, pages = {{61--66}}, publisher = {{Campus Verlag}}, title = {{{GEMINI-Geschäftsmodellmuster-Kartenset}}}, year = {{2020}}, } @inbook{20571, author = {{Koldewey, Christian and Reinhold, Jannik and Dumitrescu, Roman}}, booktitle = {{Der Geschäftsmodell-Toolguide}}, editor = {{Buchholz, Birgit and Bürger, Matthias}}, pages = {{106 -- 111}}, publisher = {{Campus Verlag}}, title = {{{Geschäftsmodellvalidierung}}}, year = {{2020}}, } @inbook{20573, author = {{Koldewey, Christian and Reinhold, Jannik and Dumitrescu, Roman}}, booktitle = {{Der Geschäftsmodell-Toolguide}}, editor = {{Buchholz, Birgit and Bürger, Matthias}}, pages = {{138 -- 143}}, publisher = {{Campus Verlag}}, title = {{{Geschäftsmodell-Roadmapping}}}, year = {{2020}}, } @inproceedings{20695, author = {{Boeddeker, Christoph and Nakatani, Tomohiro and Kinoshita, Keisuke and Haeb-Umbach, Reinhold}}, booktitle = {{ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}}, isbn = {{9781509066315}}, title = {{{Jointly Optimal Dereverberation and Beamforming}}}, doi = {{10.1109/icassp40776.2020.9054393}}, year = {{2020}}, } @inproceedings{20700, author = {{Boeddeker, Christoph and Cord-Landwehr, Tobias and Heitkaemper, Jens and Zorila, Catalin and Hayakawa, Daichi and Li, Mohan and Liu, Min and Doddipatla, Rama and Haeb-Umbach, Reinhold}}, booktitle = {{Proc. CHiME 2020 Workshop on Speech Processing in Everyday Environments}}, title = {{{Towards a speaker diarization system for the CHiME 2020 dinner party transcription}}}, year = {{2020}}, } @book{20705, editor = {{Herzig, Bardo and Klar, Tilman-Mathies and Martin, Alexander and Meister, Dorothee}}, issn = {{1424-3636}}, title = {{{Orientierungen in der digitalen Welt}}}, doi = {{10.21240/mpaed/39.x}}, year = {{2020}}, } @inproceedings{20854, author = {{Camberg, Alan Adam and Tröster, Thomas}}, location = {{Seoul, South Korea}}, title = {{{A simplified method for the evaluation of the layer compression test using one 3D digital image correlation system and considering the material anisotropy by the equibiaxial Lankford parameter}}}, doi = {{10.1088/1757-899X/967/1/012077}}, year = {{2020}}, } @inproceedings{20856, author = {{Camberg, Alan Adam and Erhart, Tobias and Tröster, Thomas}}, location = {{Seoul, South Korea}}, title = {{{Predicting fracture at non-isothermal forming conditions: A temperature dependent extension of the LS-DYNA GISSMO fracture indicator framework}}}, doi = {{10.13140/RG.2.2.23924.17288}}, year = {{2020}}, } @inproceedings{18249, abstract = {{Augmented Reality (AR) has recently found high attention in mobile shopping apps such as in domains like furniture or decoration. Here, the developers of the apps focus on the positioning of atomic 3D objects in the physical environment. With this focus, they neglect the configuration of multi-faceted 3D object composition according to the user needs and environmental constraints. To tackle these challenges, we present a model-based approach to support AR-assisted product con-figuration based on the concept of Dynamic Software Product Lines. Our approach splits products (e.g. table) into parts (e.g. tabletop, ta-ble legs, funnier) with their 3D objects and additional information (e.g. name, price). The possible products, which can be configured out of these parts, are stored in a feature model. At runtime, this feature model can be used to configure 3D object compositions out of the product parts and adapt to user needs and environmental constraints. The benefits of this approach are demonstrated by a case study of configuring modular kitchens with the help of a prototypical mobile-based implementation.}}, 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, Runtime Adaptation, Dynamic Software Product Lines}}, location = {{Eindhoven}}, publisher = {{Springer}}, title = {{{Model-based Product Configuration in Augmented Reality Applications}}}, doi = {{10.1007/978-3-030-64266-2_5}}, volume = {{12481}}, year = {{2020}}, } @misc{18637, author = {{Schürmann, Patrick}}, publisher = {{Universität Paderborn}}, title = {{{A Group Signature Scheme from Flexible Public Key Signatures and Structure-Preserving Signatures on Equivalence Classes}}}, year = {{2020}}, } @article{21819, abstract = {{Many dimensionality and model reduction techniques rely on estimating dominant eigenfunctions of associated dynamical operators from data. Important examples include the Koopman operator and its generator, but also the Schrödinger operator. We propose a kernel-based method for the approximation of differential operators in reproducing kernel Hilbert spaces and show how eigenfunctions can be estimated by solving auxiliary matrix eigenvalue problems. The resulting algorithms are applied to molecular dynamics and quantum chemistry examples. Furthermore, we exploit that, under certain conditions, the Schrödinger operator can be transformed into a Kolmogorov backward operator corresponding to a drift-diffusion process and vice versa. This allows us to apply methods developed for the analysis of high-dimensional stochastic differential equations to quantum mechanical systems.}}, author = {{Klus, Stefan and Nüske, Feliks and Hamzi, Boumediene}}, issn = {{1099-4300}}, journal = {{Entropy}}, title = {{{Kernel-Based Approximation of the Koopman Generator and Schrödinger Operator}}}, doi = {{10.3390/e22070722}}, year = {{2020}}, } @inproceedings{16487, author = {{Bobolz, Jan and Eidens, Fabian and Krenn, Stephan and Slamanig, Daniel and Striecks, Christoph}}, booktitle = {{Proceedings of the 15th ACM Asia Conference on Computer and Communications Security (ASIA CCS ’20),}}, location = {{Taiwan}}, publisher = {{ACM}}, title = {{{Privacy-Preserving Incentive Systems with Highly Efficient Point-Collection}}}, doi = {{10.1145/3320269.3384769}}, year = {{2020}}, }