TY - CHAP A1 - Burgeth, Bernhard A1 - Kleefeld, Andreas A1 - Zhang, Eugene A1 - Zhang, Yue ED - Baudrier, Étienne ED - Naegel, Benoît ED - Krähenbühl, Adrien ED - Tajine, Mohamed T1 - Towards Topological Analysis of Non-symmetric Tensor Fields via Complexification T2 - Discrete Geometry and Mathematical Morphology N2 - Fields of asymmetric tensors play an important role in many applications such as medical imaging (diffusion tensor magnetic resonance imaging), physics, and civil engineering (for example Cauchy-Green-deformation tensor, strain tensor with local rotations, etc.). However, such asymmetric tensors are usually symmetrized and then further processed. Using this procedure results in a loss of information. A new method for the processing of asymmetric tensor fields is proposed restricting our attention to tensors of second-order given by a 2x2 array or matrix with real entries. This is achieved by a transformation resulting in Hermitian matrices that have an eigendecomposition similar to symmetric matrices. With this new idea numerical results for real-world data arising from a deformation of an object by external forces are given. It is shown that the asymmetric part indeed contains valuable information. Y1 - 2022 SN - 978-3-031-19897-7 U6 - https://doi.org/10.1007/978-3-031-19897-7_5 N1 - Second International Joint Conference, DGMM 2022, Strasbourg, France, October 24–27, 2022 N1 - Corresponding author: Andreas Kleefeld SP - 48 EP - 59 PB - Springer CY - Cham ER - TY - CHAP A1 - Blanke, Tobias A1 - Schmidt, Katharina S. A1 - Göttsche, Joachim A1 - Döring, Bernd A1 - Frisch, Jérôme A1 - van Treeck, Christoph ED - Weidlich, Anke ED - Neumann, Dirk ED - Gust, Gunther ED - Staudt, Philipp ED - Schäfer, Mirko T1 - Time series aggregation for energy system design: review and extension of modelling seasonal storages T2 - Energy Informatics N2 - Using optimization to design a renewable energy system has become a computationally demanding task as the high temporal fluctuations of demand and supply arise within the considered time series. The aggregation of typical operation periods has become a popular method to reduce effort. These operation periods are modelled independently and cannot interact in most cases. Consequently, seasonal storage is not reproducible. This inability can lead to a significant error, especially for energy systems with a high share of fluctuating renewable energy. The previous paper, “Time series aggregation for energy system design: Modeling seasonal storage”, has developed a seasonal storage model to address this issue. Simultaneously, the paper “Optimal design of multi-energy systems with seasonal storage” has developed a different approach. This paper aims to review these models and extend the first model. The extension is a mathematical reformulation to decrease the number of variables and constraints. Furthermore, it aims to reduce the calculation time while achieving the same results. KW - Energy system KW - Renewable energy KW - Mixed integer linear programming (MILP) KW - Typical periods KW - Time-series aggregation Y1 - 2022 U6 - https://doi.org/10.1186/s42162-022-00208-5 SN - 2520-8942 N1 - 11th DACH+ Conference on Energy Informatics, 15-16 September 2022, Freiburg, Germany VL - 5 IS - 1, Article number: 17 PB - Springer Nature ER - TY - CHAP A1 - Blaneck, Patrick Gustav A1 - Bornheim, Tobias A1 - Grieger, Niklas A1 - Bialonski, Stephan T1 - Automatic readability assessment of german sentences with transformer ensembles T2 - Proceedings of the GermEval 2022 Workshop on Text Complexity Assessment of German Text N2 - Reliable methods for automatic readability assessment have the potential to impact a variety of fields, ranging from machine translation to self-informed learning. Recently, large language models for the German language (such as GBERT and GPT-2-Wechsel) have become available, allowing to develop Deep Learning based approaches that promise to further improve automatic readability assessment. In this contribution, we studied the ability of ensembles of fine-tuned GBERT and GPT-2-Wechsel models to reliably predict the readability of German sentences. We combined these models with linguistic features and investigated the dependence of prediction performance on ensemble size and composition. Mixed ensembles of GBERT and GPT-2-Wechsel performed better than ensembles of the same size consisting of only GBERT or GPT-2-Wechsel models. Our models were evaluated in the GermEval 2022 Shared Task on Text Complexity Assessment on data of German sentences. On out-of-sample data, our best ensemble achieved a root mean squared error of 0:435. Y1 - 2022 U6 - https://doi.org/10.48550/arXiv.2209.04299 N1 - Proceedings of the 18th Conference on Natural Language Processing / Konferenz zur Verarbeitung natürlicher Sprache (KONVENS 2022), 12-15 September, 2022, University of Potsdam, Potsdam, Germany SP - 57 EP - 62 PB - Association for Computational Linguistics CY - Potsdam ER - TY - CHAP A1 - Amir, Malik A1 - Bauckhage, Christian A1 - Chircu, Alina A1 - Czarnecki, Christian A1 - Knopf, Christian A1 - Piatkowski, Nico A1 - Sultanow, Eldar T1 - What can we expect from quantum (digital) twins? T2 - Wirtschaftsinformatik 2022 Proceedings N2 - Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better address changes in their environment and differentiate their products andservices. KW - Artificial Intelligence KW - Digital Twin Evolution KW - Machine Learning KW - Quantum Computing KW - Quantum Machine Learning Y1 - 2022 N1 - 17. Internationale Tagung Wirtschaftsinformatik, 21. – 23. Februar 2022, Nürnberg (online) SP - 1 EP - 14 PB - AIS Electronic Library (AISeL) ER - TY - CHAP A1 - Allal, D. A1 - Bannister, R. A1 - Buisman, K. A1 - Capriglione, D. A1 - Di Capua, G. A1 - García-Patrón, M. A1 - Gatzweiler, Thomas A1 - Gellersen, F. A1 - Harzheim, Thomas A1 - Heuermann, Holger A1 - Hoffmann, J. A1 - Izbrodin, A. A1 - Kuhlmann, K. A1 - Lahbacha, K. A1 - Maffucci, A. A1 - Miele, G. A1 - Mubarak, F. A1 - Salter, M. A1 - Pham, T.D. A1 - Sayegh, A. A1 - Singh, D. A1 - Stein, F. A1 - Zeier, M. T1 - RF measurements for future communication applications: an overview T2 - 2022 IEEE International Symposium on Measurements & Networking (M&N) N2 - In this paper research activities developed within the FutureCom project are presented. The project, funded by the European Metrology Programme for Innovation and Research (EMPIR), aims at evaluating and characterizing: (i) active devices, (ii) signal- and power integrity of field programmable gate array (FPGA) circuits, (iii) operational performance of electronic circuits in real-world and harsh environments (e.g. below and above ambient temperatures and at different levels of humidity), (iv) passive inter-modulation (PIM) in communication systems considering different values of temperature and humidity corresponding to the typical operating conditions that we can experience in real-world scenarios. An overview of the FutureCom project is provided here, then the research activities are described. KW - FPGA KW - signal integrity KW - power integrity KW - passive inter-modulation KW - metrological characterization Y1 - 2022 SN - 978-1-6654-8362-9 SN - 978-1-6654-8363-6 U6 - https://doi.org/10.1109/MN55117.2022.9887740 SN - 2639-5061 SN - 2639-507X N1 - 2022 IEEE International Symposium on Measurements & Networking (M&N), 18-20 July 2022, Padua, Italy. SP - 1 EP - 6 PB - IEEE ER -