Lübben, R. . (2022). Forecasting TCP s Rate to Speed up Slow Start. IEEE Open Journal of the Computer Society, 1–9. http://doi.org/10.1109/OJCS.2022.3208701
Irshad, M. ., Börstler, J. ., & Petersen, K. . (2022). Supporting refactoring of BDD specifications—An empirical study. Information and Software Technology, 141, 106717.
Neumann, T. ., Widrat, A. ., & Fichter, K. . (2022). Finanzierungs- & Förderangebote für Ecopreneure. Gründerplattform. Abgerufen von https://cdn.kettufy.io/gp.kettufy.io/documents/gruenderplattform.de/Material-3_Broschuere-FinanzierungFoerderungangebote.pdf
Freißmann, J. ., Fritz, M. ., & Tuschy, I. . (2022). Solarthermisch gestützte Nah- und Fernwärmeversorgung als Baustein der sektorgekoppelten Wärmewende in Schleswig-Holstein (SolWW-SH). Forschungsergebnisse. Abgerufen von http://www.znes-flensburg.de/sites/default/files/projects/SolWW-SH_ZNES_Forschungsergebnisse_2020531.pdf
Pornak, S. C., Griemsmann, S. ., Böhle, A. ., Lusch, A. ., Schulte, R. ., & Lehr, B. . (2022). Evaluation einer Prostatakrebsnachsorge-App aus Patientensicht: Eine qualitative Studie. Zeitschrift für Evidenz, Fortbildung Und Qualität Im Gesundheitswesen, 175, 67–75.
Labes, A. ., Koopmann, I. K., Möller, S. ., Elle, C. ., Hindersin, S. ., Kramer, A. ., & Labes, A. . (2022). Optimization of Astaxanthin Recovery in the Downstream Process of Haematococcus pluvialis. Foods. http://doi.org/10.3390/foods11091352
Blaufus, K. ., Chirvi, M. ., Huber, H.-P. ., Maiterth, R. ., & Sureth-Sloane, C. . (2022). Tax Misperception and its Effects on Decision Making – Literature Review and Behavioral Taxpayer Response Model. European Accounting Review, 31(1). http://doi.org/10.1080/09638180.2020.1852095
Abstract
Previous accounting research shows that taxes affect decision making by individuals and firms. Most studies assume that agents have an accurate perception regarding their tax burden. However, there is a growing body of literature analyzing whether taxes are indeed perceived correctly. We review 128 studies on the measurement of tax misperception and its behavioral implications. The review reveals that many taxpayers have substantial tax misperceptions that lead to biased decision making. We develop a Behavioral Taxpayer Response Model on the impact of provided tax information on tax perception. Besides individual traits, characteristics of the tax information and the decision environment determine the extent of tax misperception. We discuss opportunities for future research and methodological limitations. While there is much evidence on tax misperception at the individual level, we hardly find any research at the firm level. Little is known about the real effects of managers’ tax misperception and on how tax information is strategically managed to impact stakeholders. This research gap is surprising as a large part of the accounting literature analyzes decision making and disclosure of firms. We recommend a mixed-method approach combining experiments, surveys, and archival data analyses to improve the knowledge on tax misperception and its consequences.
Branlard, E. ., & Geisler, J. . (2022). A symbolic framework to obtain mid-fidelity models of flexible multibody systems with application to horizontal-axis wind turbines. Wind Energy Science, 7, 2351–2371. http://doi.org/10.5194/wes-7-2351-2022
Abstract
The article presents a symbolic framework (also called computer algebra program) that is used to obtain, in symbolic mathematical form, the linear and nonlinear equations of motion of a mid-fidelity multibody system including rigid and flexible bodies. Our approach is based on Kane's method and a nonlinear shape function representation for flexible bodies. The shape function approach does not represent the state of the art for flexible multibody dynamics but is an effective trade-off to obtain mid-fidelity models with few degrees of freedom, taking advantage of the separation of space and time. The method yields compact symbolic equations of motion with implicit account of the constraints. The general and automatic framework facilitates the creation and manipulation of models with various levels of complexity by adding or removing degrees of freedom. The symbolic treatment allows for analytical gradients and linearized equations of motion. The linear and nonlinear equations can be exported to Python code or dedicated software. There are multiple applications, such as time domain simulation, stability analyses, frequency domain analyses, advanced controller design, state observers, and digital twins. In this article, we describe the method we used to systematically generate the equations of motion of multibody systems and present the implementation of the framework using the Python package SymPy. We apply the framework to generate illustrative land-based and offshore wind turbine models. We compare our results with OpenFAST simulations and discuss the advantages and limitations of the method. The Python implementation is provided as an open-source project.
Chen, Y. ., Schlipf, D. ., & Cheng, P. W. (2021). Parameterization of wind evolution using lidar. Wind Energy Science, 6, 61–91. http://doi.org/10.5194/wes-6-61-2021 (Original work published 2024)
Chen, S. ., Cai, W. ., Witte, F. ., Wang, X. ., Wang, F. ., Kolditz, O. ., & Shao, H. . (2021). Long-term thermal imbalance in large borehole heat exchangers array - A numerical study based on the Leicester project. Energy and Buildings, 231, 110518. http://doi.org/10.1016/j.enbuild.2020.110518 (Original work published 2024)