@article{Gaigall2020,
  author    = {Gaigall, Daniel},
  title     = {Rothman-Woodroofe symmetry test statistic revisited},
  series = {Computational Statistics \& Data Analysis},
  volume    = {2020},
  journal   = {Computational Statistics \& Data Analysis},
  number    = {142},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0167-9473},
  doi       = {10.1016/j.csda.2019.106837},
  pages     = {Artikel 106837},
  year      = {2020},
  abstract  = {The Rothman-Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.},
  language  = {en}
}
@article{KetelhutBrueggeGoelletal.2020,
  author    = {Ketelhut, Maike and Br{\"u}gge, G. M. and G{\"o}ll, Fabian and Braunstein, Bjoern and Albracht, Kirsten and Abel, Dirk},
  title     = {Adaptive iterative learning control of an industrial robot during neuromuscular training},
  series = {IFAC PapersOnLine},
  volume    = {53},
  journal   = {IFAC PapersOnLine},
  number    = {2},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {2405-8963},
  doi       = {10.1016/j.ifacol.2020.12.741},
  pages     = {16468 -- 16475},
  year      = {2020},
  abstract  = {To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.},
  language  = {en}
}
@article{BungErpicumTullis2020,
  author    = {Bung, Daniel Bernhard and Erpicum, S{\´e}bastien and Tullis, Blanke P.},
  title     = {Advances in hydraulic structures engineering},
  series = {Journal of Hydraulic Engineering},
  volume    = {147},
  journal   = {Journal of Hydraulic Engineering},
  number    = {1},
  publisher = {ASCE},
  address   = {Reston, Va.},
  issn      = {0733-9429 (Druckausgabe)},
  doi       = {10.1061/(ASCE)HY.1943-7900.0001851},
  pages     = {1 Seite},
  year      = {2020},
  language  = {en}
}