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13721 Publications


2020 | Journal Article | LibreCat-ID: 21539
R. Ortmann, M. Pelster, and S. T. Wengerek, “COVID-19 and investor behavior,” Finance Research Letters, 2020.
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2020 | Journal Article | LibreCat-ID: 16277
T. Kühne et al., “CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations,” The Journal of Chemical Physics, vol. 152, no. 19, 2020.
LibreCat | Files available | DOI | Download (ext.) | arXiv
 

2020 | Journal Article | LibreCat-ID: 17386
T. D. Kühne et al., “CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations,” The Journal of Chemical Physics, vol. 152, no. 19, p. 194103, 2020.
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2020 | Conference Paper | LibreCat-ID: 13584
D. Szopinski, T. Schoormann, and D. Kundisch, “Criteria as a prelude for guiding taxonomy evaluation,” in Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS), Maui, Hawaii, 2020.
LibreCat | Files available
 

2020 | Journal Article | LibreCat-ID: 20467
D. Lorenz and S. Domzalski, “CRITERIA-BASED RETURN TO SPRINTING PROGRESSION FOLLOWING LOWER EXTREMITY INJURY.,” Int J Sports Phys Ther, vol. 15, no. 2, pp. 326–332, 2020.
LibreCat | PubMed | Europe PMC
 

2020 | Journal Article | LibreCat-ID: 20157
F. Thiele et al., “Cryogenic electro-optic polarisation conversion in titanium in-diffused lithium niobate waveguides,” Optics Express, 2020.
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2020 | Dissertation | LibreCat-ID: 15482
N. Löken, Cryptography for the Crowd — A Study of Cryptographic Schemes with Applications to Crowd Work. 2020.
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2020 | Conference Paper | LibreCat-ID: 20516
J. Holtmann, J.-P. Steghofer, M. Rath, and D. Schmelter, “Cutting through the Jungle: Disambiguating Model-based Traceability Terminology,” in 2020 IEEE 28th International Requirements Engineering Conference (RE), 2020.
LibreCat | DOI
 

2020 | Journal Article | LibreCat-ID: 16964
R. Hochmuth, M. Liebendörfer, R. Biehler, and A. Eichler, “Das Kompetenzzentrum Hochschuldidaktik Mathematik (khdm),” Neues Handbuch Hochschullehre, vol. 95, pp. 117–138, 2020.
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2020 | Journal Article | LibreCat-ID: 20836
J. Magenheim and C. Schulte, “Data science education,” Encyclopedia of Education and Information Technologies. Cham: Springer, 2020.
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2020 | Journal Article | LibreCat-ID: 16288
S. Klus, F. Nüske, S. Peitz, J.-H. Niemann, C. Clementi, and C. Schütte, “Data-driven approximation of the Koopman generator: Model reduction, system identification, and control,” Physica D: Nonlinear Phenomena, vol. 406, 2020.
LibreCat | DOI
 

2020 | Journal Article | LibreCat-ID: 17072
Y. Feng, T. Gries, and M. Fritz, “Data-driven local polynomial for the trend and its derivatives in economic time series,” Journal of Nonparametric Statistics, pp. 510–533, 2020.
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2020 | Journal Article | LibreCat-ID: 16309
S. Peitz, S. E. Otto, and C. W. Rowley, “Data-Driven Model Predictive Control using Interpolated Koopman  Generators,” SIAM Journal on Applied Dynamical Systems, vol. 19, no. 3, pp. 2162–2193, 2020.
LibreCat | DOI | Download (ext.)
 

2020 | Journal Article | LibreCat-ID: 20448
M. Meyer, M. Frank, M. Massmann, N. Wendt, and R. Dumitrescu, “Data-Driven Product Generation and Retrofit Planning,” Procedia CIRP, no. 93, pp. 965–970, 2020.
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2020 | Journal Article | LibreCat-ID: 21558
A. Brosch, S. Hanke, O. Wallscheid, and J. Bocker, “Data-Driven Recursive Least Squares Estimation for Model Predictive Current Control of Permanent Magnet Synchronous Motors,” IEEE Transactions on Power Electronics, pp. 2179–2190, 2020.
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2020 | Journal Article | LibreCat-ID: 20449
E. Uhlmann, R. Dumitrescu, J. Polte, M. Meyer, and D. Simsek, “Datengetriebene Steigerung der Verfügbarkeit,” wt Werkstattstechnik online , vol. 110, no. 07–08, pp. 532–535, 2020.
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2020 | Journal Article | LibreCat-ID: 20883
C. Grund, C. Harbring, K. Thommes, and K. R. Tilkes, “Decisions on Extending Group Membership—Evidence from a Public Good Experiment,” Games, 2020.
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2020 | Journal Article | LibreCat-ID: 16290
K. Bieker, S. Peitz, S. L. Brunton, J. N. Kutz, and M. Dellnitz, “Deep model predictive flow control with limited sensor data and online learning,” Theoretical and Computational Fluid Dynamics, vol. 34, pp. 577–591, 2020.
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2020 | Conference Paper | LibreCat-ID: 18651
T. Gburrek, J. Schmalenstroeer, A. Brendel, W. Kellermann, and R. Haeb-Umbach, “Deep Neural Network based Distance Estimation for Geometry Calibration in Acoustic Sensor Network,” in European Signal Processing Conference (EUSIPCO), 2020.
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2020 | Conference Paper | LibreCat-ID: 20808
H. Ghasemzadeh Mohammadi et al., “DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms,” in 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), 2020.
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