Jauch, C. . (2023). Grid Integration of Wind Turbines. In Wind Power Technology (S. 427–490). Cham: Springer. http://doi.org/10.1007/978-3-031-20332-9_10 (Original work published Juni 2023)
Abstract
These days, in many grids around the world power system stability relies on the functionalities of modern wind turbines.
Tausch-Nebel, L. ., & van der Sluis, H. . (2023). „Man ist mehr im Stoff drin“ – Befunde aus der Verblockung von Grundlagenkursen. Die Neue Hochschule (DNH), (3/2023), 4. (Original work published Juni 2023)
Lübben, R. ., & Rizk, A. . (2023). TAILING: Tail Distribution Forecasting of Packet Delays using Quantile Regression Neural Networks. In IEEE International Conference on Communications (ICC) (S. 7). (Original work published Mai 2023)
Minhas, N. M., Koppula, T. ., Petersen, K. ., & Börstler, J. . (2023). Using goal—question—metric to compare research and practice perspectives on regression testing. Journal of Software: Evolution and Process, 35, e2506.
Eissing, C. S., Richter, A. ., & Schlipf, D. . (2023). CPACS LTA—-Using Common Data Structures for Visualization and Optimization of Airship Designs. In D. . Shukla (Hrsg.), Lighter Than Air Systems (S. 25–36). Singapore: Springer Nature Singapore. http://doi.org/10.1007/978-981-19-6049-9_2
Süncksen, M. ., Reinhold, S. ., & Teistler, M. . (2023). Exploring Interaction Techniques for Navigating Medical Images Using a Motion-Tracked Pen. In 2023 IEEE 11th International Conference on Serious Games and Applications for Health (SeGAH) (S. 1–5). http://doi.org/10.1109/SeGAH57547.2023.10253799
Guo, F. ., Schlipf, D. ., & Cheng, P. W. (2023). Evaluation of lidar-assisted wind turbine control under various turbulence characteristics. Wind Energy Science, 8, 149–171. http://doi.org/10.5194/wes-8-149-2023
Königs, M. ., & Löhlein, B. . (2023). Lumped model eddy current analysis of influencefactors on PM segmentation effectiveness. e&I Elektrotechnik Und Informationstechnik, 140(2). http://doi.org/10.1007/s00502-023-01148-y
Prott, K.-O. ., Teegen, F. ., & Christiansen, J. . (2023). Embedding Functional Logic Programming in Haskell via a Compiler Plugin. In Practical Aspects of Declarative Languages. Boston, MA, USA: Springer. http://doi.org/10.1017/978-3-031-24841-2_3
Abstract
We present a technique to embed a functional logic language in Haskell using a GHC plugin. Our approach is based on a monadic lifting that models the functional logic semantics explicitly. Using a GHC plugin, we get many language extensions that GHC provides for free in the embedded language. As a result, we obtain a seamless embedding of a functional logic language, without having to implement a full compiler. We briefly show that our approach can be used to embed other domain-specific languages as well. Furthermore, we can use such a plugin to build a full blown compiler for our language.