Die Hochschulbibliographie der TU Dortmund dient dem Nachweis von Publikationen der Angehörigen der TU Dortmund. Dabei wird Vollständigkeit angestrebt.
Die Hochschulbibliographie (ehemals Jahrbuch der TUM) verzeichnet wissenschaftliche Veröffentlichungen von Angehörigen der Technischen Universität München seit 1970. Es wird von der Universitätsbibliothek redaktionell betreut.
Die Universitätsbibliographie ist der zentrale Publikationsnachweis der Universität Duisburg-Essen, der online die Publikationstätgkeit der Hochschulangehörigen verzeichnet.
Das Kompetenzzentrum Bibliometrie ist ein institutionenübergreifender Verbund, um auf der Basis der zur Verfügung stehenden Dateninfrastruktur einen Beitrag zur Fortentwicklung der Bibliometrie und deren Anwendbarkeit zu leisten.
In der Hochschulbibliographie werden seit 1994 erschienene und der Universitätsbibliothek gemeldete Publikationen von Angehörigen der Universität Erfurt nachgewiesen, die im Zusammenhang mit einer Tätigkeit an der Universität Erfurt entstanden sind.
D. Gläser. Software, (2024)Related to: Boon, W.M., Gläser, D., Helmig, R. et al. A mortar method for the coupled Stokes-Darcy problem using the MAC scheme for Stokes and mixed finite elements for Darcy. Comput Geosci (2024). doi: 10.1007/s10596-023-10267-6.
B. Bursik, J. Eller, and J. Groß. Dataset, (2024)Related to: B. Bursik, J. Eller, J. Gross: Predicting Solvation Free Energies from the Minnesota Solvation Database Using Classical Density Functional Theory Based on the PC-SAFT Equation of State. Journal of Physical Chemistry B, (2024). Accepted manuscript.
C. Homs Pons, and R. Lautenschlager. Software, (2024)Related to: Coupled Simulations and Parameter Inversion for Neural System and Electrophysiological Muscle Models, submitted to GAMM Mitteilungen.
F. Euchner, P. Stephan, M. Gauger, and S. Brink. Dataset, (2024)Related to: F. Euchner, M. Gauger, S. Dörner, S. ten Brink: Ä Distributed Massive MIMO Channel Sounder for "Big CSI Data"-driven Machine Learning". In: WSA 2021 : 25th International ITG Workshop on Smart Antennas. Berlin : VDE Verlag, 2021 (ITG-Fachbericht 300), S. 289-294, ISBN: 978-3-8007-5686-5.
Y. Wang. Software, (2024)Related to: Y. Wang, W. Wang, A. Abdelhafez, M. Elfares, Z. Hu, M. Bâce, A. Bulling. "SalChartQA: Question-driven Saliency on Information Visualisations", in Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems. doi: 10.1145/3613904.3642942.
P. Seifer, D. Hernández, R. Lämmel, and S. Staab. Software, (2024)Related to: Philipp Seifer, Daniel Hernández, Ralf Lämmel, and Steffen Staab. 2024. From Shapes to Shapes: Inferring SHACL Shapes for Results of SPARQL CONSTRUCT Queries. In Proceedings of the ACM Web Conference 2024 (WWW ’24). ACM. doi: 10.1145/3589334.3645550.
N. Rodrigues, F. Dennig, V. Brandt, D. Keim, and D. Weiskopf. Software, (2024)Related to: Rodrigues, N., Dennig, F. L., Brandt, V., Keim, D. A., & Weiskopf, D. (2024). Comparative Evaluation of Animated Scatter Plot Transitions. arXiv preprint. arXiv: 2401.04692.
L. Skoury, and T. Wortmann. Dataset, (2024)Related to: L. Skoury et al., “Towards data-informed co-design in digital fabrication”, Autom. Constr., vol. 158, p. 105229, Feb. 2024. doi: 10.1016/j.autcon.2023.105229.
T. Nadler, S. Wolfen, D. Häufle, and S. Schmitt. Dataset, (2024)Related to: Driess, D., Zimmermann, H., Wolfen, S., Suissa, D., Haeufle, D., Hennes, D., Toussaint, M. & Schmitt, S. (2018, May). Learning to control redundant musculoskeletal systems with neural networks and SQP: exploiting muscle properties. In 2018 IEEE International Conference on robotics and automation (ICRA) (pp. 6461-6468). IEEE. doi: 10.1109/ICRA.2018.8463160.
A. Schönle, C. Gnanasambandham, and P. Eberhard. Calm, smooth and smart : novel approaches for influencing vibrations by means of deliberately introduced dissipation, volume 102 of Lecture notes in applied and computational mechanics, Springer, (2024)
M. Alvarez Chaves, H. Gupta, U. Ehret, and A. Guthke. Software, (2024)Related to: Evaluating Density- and Nearest Neighbor-based Methods to Accurately Estimate Information-Theoretic Quantities from Multi-Dimensional Sample Data.
J. Gärtner. Software, (2024)Related to: J. W. Gärtner, A. Kronenburg, A. Rees, J. Sender, M. Oschwald, and G. Lamanna, "Numerical and Experimental Analysis of Flashing Cryogenic Nitrogen", International Journal of Multiphase Flow, vol 130, 2020. doi: 10.1016/j.ijmultiphaseflow.2020.103360.
S. Leder, L. Siriwardena, and A. Menges. Software, (2024)Related to: Groenewolt, A., Schwinn, T., Nguyen, L., & Menges, A. (2018). An interactive agent-based framework for materialization-informed architectural design. Swarm Intelligence, 12(2), 155-186. doi: 10.1007/s11721-017-0151-8.
Y. Wang, and A. Bulling. Software, (2024)Related to: Y. Wang, Q. Dai, M. Bâce, K. Klein, A. Bulling. "Saliency3D: A 3D Saliency Dataset Collected on Screen", in Proceedings of the ACM Symposium on Eye Tracking Research & Applications (ETRA '24). doi: 10.1145/3649902.3653350.
F. Bechler. Dataset, (2024)Related to: Related Publication: Bechler, F.: Enabling Holistic Vehicle Safety - Combined Knowledge and Information through a Graph-based Approach, Dissertation, University of Stuttgart, Shaker Verlag, Aachen, tbd.
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
J. Pelzer. Software, (2024)Related to: Pelzer, Julia, and Miriam Schulte. "Efficient two-stage modeling of heat plume interactions of geothermal heat pumps in shallow aquifers using convolutional neural networks." Geoenergy Science and Engineering (2024): 212788. doi: 10.1016/j.geoen.2024.212788.
R. Hedeshy, R. Menges, and S. Staab. Dataset, (2024)Related to: CNVVE: Dataset and Benchmark for Classifying Non-verbal Voice Expressions.R. Hedeshy, R. Menges, and S. Staab. Interspeech 2023, August 20-24, 2023. Dublin, Ireland, (2023). doi: 10.21437/Interspeech.2023-201.
Z. Asma, D. Hernandez, L. Galárraga, G. Flouris, I. Fundulaki, and K. Hose. Software, (2024)Related to: A. Zubaria, D. Hernández, L. Galárraga, G. Flouris, I. Fundulaki, and K. Hose. NPCS: Native Provenance Computation for SPARQL. Proceedings of the ACM Web Conference 2024 (WWW '24), May13-17, 2024, Singapore, Singapore, ACM, (May 2024). doi: 10.1145/3589334.3645557.