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2185 Publications
2019 | Conference Paper | LibreCat-ID: 13461 | 
Kaul, T., Bender, A., & Sextro, W. (2019). Digital Twin for Reliability Analysis During Design and Operation of Mechatronic Systems. In M. Beer & E. Zio (Eds.), Proceedings of the 29th European Safety and Reliability Conference (ESREL2019) (Issue 29, pp. 2340–2347).
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2019 | Journal Article | LibreCat-ID: 47947
Rüsing, M., Weigel, P. O., Zhao, J., & Mookherjea, S. (2019). Toward 3D Integrated Photonics Including Lithium Niobate Thin Films: A Bridge Between Electronics, Radio Frequency, and Optical Technology. IEEE Nanotechnology Magazine, 13(4), 18–33. https://doi.org/10.1109/mnano.2019.2916115
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2019 | Book Chapter | LibreCat-ID: 48341
Wille, M. (2019). Prinzipien und Strategien der Textgliederung in den Zeitungen des 18. Jahrhunderts – Eine computerbasierte Korpusanalyse. In F. Simmler & G. Baeva (Eds.), Textgliederungsprinzipien. Ihre Kennzeichnungsformen und Funktionen vom 8. bis 18. Jahrhundert. Akten zum Internationalen Kongress vom 22. bis 24. Juni 2017 an der Universität St. Petersburg (Vol. 34, pp. 507–531). Weidler.
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2019 | Conference Paper | LibreCat-ID: 15237 |
Gburrek, T., Glarner, T., Ebbers, J., Haeb-Umbach, R., & Wagner, P. (2019). Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion. Proc. 10th ISCA Speech Synthesis Workshop, 81–86. https://doi.org/10.21437/SSW.2019-15
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2019 | Book Chapter | LibreCat-ID: 31142
Schuster, B.-M. (2019). Textgliederungsprinzipien und Beziehungsgestaltung im Stammbuch von 1559–1878. In F. Simmler & G. Baeva (Eds.), Textgliederungsprinzipien. Ihre Kennzeichnungsformen und Funktionen in Texten vom 8. bis 18. Jahrhundert. Akten zum Internationalen Kongress an der Staatlichen Universität St. Petersburg vom 22. bis 24. Juni 2017 (pp. 293–312). WEIDLER.
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2019 | Journal Article | LibreCat-ID: 46346
Kerschke, P., & Trautmann, H. (2019). Automated Algorithm Selection on Continuous Black-Box Problems By Combining Exploratory Landscape Analysis and Machine Learning. Evolutionary Computation (ECJ), 27(1), 99–127. https://doi.org/10.1162/evco_a_00236
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2019 | Book Chapter | LibreCat-ID: 48501
Balluff, S., Bendfeld, J., & Krauter, S. (2019). Meteorological Data Forecast using RNN. In Deep Learning and Neural Networks. IGI Global. https://doi.org/10.4018/978-1-7998-0414-7.ch050
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2019 | Journal Article | LibreCat-ID: 28992
Golombek, C., Klingsieck, K. B., & Scharlau, I. (2019). Assessing Self-Efficacy for Self-Regulation of Academic Writing: Development and validation of a scale. European Journal of Psychological Assessment, 35(5), 751–761. https://doi.org/10.1027/1015-5759/a000452
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2019 | Journal Article | LibreCat-ID: 48703
Zobe, C., Krause, D., & Blischke, K. (2019). Dissociative effects of normative feedback on motor automaticity and motor accuracy in learning an arm movement sequence. Human Movement Science, 66, 529–540. https://doi.org/10.1016/j.humov.2019.06.004
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| DOI
2019 | Journal Article | LibreCat-ID: 48702
Krause, D., Koers, T., & Maurer, L. K. (2019). Valence‐dependent brain potentials of processing augmented feedback in learning a complex arm movement sequence. Psychophysiology, 57(3). https://doi.org/10.1111/psyp.13508
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| DOI
2019 | Conference Paper | LibreCat-ID: 23720
Gräßler, I., Pottebaum, J., Taplick, P., Roesmann, D., & Preuß, D. (2019). Unterstützung des Lernens für kritische Situationen: Potenzial von Augmented Reality für die Instandsetzung auf See. In U. Lukas, K. Bauer, & T. Dolereit (Eds.), Go-3D 2019 “Mit 3D Richtung Maritim 4.0” - Tagungsband zur Konferenz Go-3D 2019 (pp. 45–57). Fraunhofer Verlag.
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2019 | Conference Paper | LibreCat-ID: 48858
Bossek, J., & Grimme, C. (2019). Solving Scalarized Subproblems within Evolutionary Algorithms for Multi-criteria Shortest Path Problems. In R. Battiti, M. Brunato, I. Kotsireas, & P. M. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 184–198). Springer International Publishing. https://doi.org/10.1007/978-3-030-05348-2_17
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2019 | Conference Paper | LibreCat-ID: 48875
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. M. Pardalos (Eds.), Learning and Intelligent Optimization (pp. 215–219). Springer International Publishing. https://doi.org/10.1007/978-3-030-05348-2_19
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| DOI
2019 | Journal Article | LibreCat-ID: 48877
Casalicchio, G., Bossek, J., Lang, M., Kirchhoff, D., Kerschke, P., Hofner, B., Seibold, H., Vanschoren, J., & Bischl, B. (2019). OpenML: An R Package to Connect to the Machine Learning Platform OpenML. Computational Statistics, 34(3), 977–991. https://doi.org/10.1007/s00180-017-0742-2
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| DOI
2019 | Conference Paper | LibreCat-ID: 45054
Knickenberg, M., Marwin Felix, L., & Frank, H. (2019). Potential influencing factors for teachers’ self-efficacy beliefs concerning inclusive education. 18th Biennial EARLI (European Association for Research on Learning and Instruction) Conference 2019, Aachen.
LibreCat
2019 | Conference Paper | LibreCat-ID: 45055
Knickenberg, M., & Chantal, H. (2019). Applicability of ESM in School: Quality of students’ social interaction. 18th Biennial EARLI (European Association for Research on Learning and Instruction) Conference 2019, Aachen.
LibreCat
2019 | Journal Article | LibreCat-ID: 46156
Wessel, L. (2019). Vocabulary in learning processes towards conceptual understanding of equivalent fractions—specifying students’ language demands on the basis of lexical trace analyses. Mathematics Education Research Journal, 32(4), 653–681. https://doi.org/10.1007/s13394-019-00284-z
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| DOI
2019 | Book (Editor) | LibreCat-ID: 48376
Klinger, M., Schüler-Meyer, A., & Wessel, L. (Eds.). (2019). Hanse-Kolloquium zur Hochschuldidaktik der Mathematik 2018 (Vol. 6). WTM-Verlag. https://doi.org/10.37626/ga9783959870986.0
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| DOI
2019 | Journal Article | LibreCat-ID: 53972
Santos-Arteaga, F. J., Torrecillas, C., & Tavana, M. (2019). Dynamic effects of learning on the innovative outputs and productivity in Spanish multinational enterprises. The Journal of Technology Transfer, 44(1), 97–131. https://doi.org/10.1007/s10961-017-9597-5
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| DOI
2019 | Conference Paper | LibreCat-ID: 46337
Bossek, J., & Trautmann, H. (2019). Multi-Objective Performance Measurement: Alternatives to PAR10 and Expected Running Time. In R. Battiti, M. Brunato, I. Kotsireas, & P. Pardalos (Eds.), Learning and Intelligent Optimization (Vol. 11353, pp. 215–219). Springer.
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