TY - CHAP A1 - Jung, Alexander A1 - Staat, Manfred A1 - Müller, Wolfram T1 - Effect of wind on flight style optimisation in ski jumping T2 - 15th International Symposium on Computer Simulation in Biomechanics ; July 9th-11th 2015, Edinburgh, UK Y1 - 2016 SP - 53 EP - 54 PB - The University of Edinburgh ; Loughborough University CY - Edinburgh ER - TY - JOUR A1 - Gaigall, Daniel T1 - On a new approach to the multi-sample goodness-of-fit problem JF - Communications in Statistics - Simulation and Computation N2 - Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions. KW - Goodness-of-fit test KW - Multi-sample problem KW - Parametric bootstrap Y1 - 2019 U6 - https://doi.org/10.1080/03610918.2019.1618472 SN - 1532-4141 VL - 53 IS - 10 SP - 2971 EP - 2989 PB - Taylor & Francis CY - London ER - TY - INPR A1 - Grieger, Niklas A1 - Mehrkanoon, Siamak A1 - Bialonski, Stephan T1 - Preprint: Data-efficient sleep staging with synthetic time series pretraining T2 - arXiv N2 - Analyzing electroencephalographic (EEG) time series can be challenging, especially with deep neural networks, due to the large variability among human subjects and often small datasets. To address these challenges, various strategies, such as self-supervised learning, have been suggested, but they typically rely on extensive empirical datasets. Inspired by recent advances in computer vision, we propose a pretraining task termed "frequency pretraining" to pretrain a neural network for sleep staging by predicting the frequency content of randomly generated synthetic time series. Our experiments demonstrate that our method surpasses fully supervised learning in scenarios with limited data and few subjects, and matches its performance in regimes with many subjects. Furthermore, our results underline the relevance of frequency information for sleep stage scoring, while also demonstrating that deep neural networks utilize information beyond frequencies to enhance sleep staging performance, which is consistent with previous research. We anticipate that our approach will be advantageous across a broad spectrum of applications where EEG data is limited or derived from a small number of subjects, including the domain of brain-computer interfaces. Y1 - 2024 ER - TY - JOUR A1 - Laack, Walter van T1 - Our world is well ordered in measurement and number : or why natural constants are as they are JF - American Journal of Humanities and Social Sciences (AHSS) N2 - All the important natural constants can be logically explained with and derived from the first four ordinal numbers, 1, 2, 3 and 4, its addition to ten and finally the standard values for obviously maximal feasibility Ω and the optimum in our world, the Golden Section (GS), i.e. the number sequences 273 and 618. They both are the first three numbers of irrational results by an arithmetical transformation of simple geometrical relationships by creating multiplicity out of singularity. Both of them show that the infinite is inherent in finiteness and explain in a simple way the smallest deviations and fluctuations between the physical AS-IS state and the obvious spiritual ideal behind: Wherever we look in this world, and especially in important key-positions, we regularly find these sequences. All of the above mentioned numbers so seem to be key players in our world, what can be demonstrated by the derivation of natural constants. Y1 - 2013 U6 - https://doi.org/10.11634/232907811301390 SN - 2329-079X SN - 2329-0781 VL - 1 IS - 4 SP - 219 EP - 221 ER - TY - CHAP A1 - Engelmann, Ulrich M. A1 - Shasha, Carolyn A1 - Slabu, Ioana T1 - Magnetic nanoparticle relaxation in biomedical application: focus on simulating nanoparticle heating T2 - Magnetic nanoparticles in human health and medicine Y1 - 2021 SN - 978-1-119-75467-1 SP - 327 EP - 354 PB - Wiley-Blackwell CY - Hoboken, New Jeersey ER - TY - JOUR A1 - Bronder, Thomas A1 - Jessing, Max P. A1 - Poghossian, Arshak A1 - Keusgen, Michael A1 - Schöning, Michael Josef T1 - Detection of PCR-Amplified Tuberculosis DNA Fragments with Polyelectrolyte-Modified Field-Effect Sensors JF - Analytical Chemistry N2 - Field-effect-based electrolyte-insulator-semiconductor (EIS) sensors were modified with a bilayer of positively charged weak polyelectrolyte (poly(allylamine hydrochloride) (PAH)) and probe single-stranded DNA (ssDNA) and are used for the detection of complementary single-stranded target DNA (cDNA) in different test solutions. The sensing mechanism is based on the detection of the intrinsic molecular charge of target cDNA molecules after the hybridization event between cDNA and immobilized probe ssDNA. The test solutions contain synthetic cDNA oligonucleotides (with a sequence of tuberculosis mycobacteria genome) or PCR-amplified DNA (which origins from a template DNA strand that has been extracted from Mycobacterium avium paratuberculosis-spiked human sputum samples), respectively. Sensor responses up to 41 mV have been measured for the test solutions with DNA, while only small signals of ∼5 mV were detected for solutions without DNA. The lower detection limit of the EIS sensors was ∼0.3 nM, and the sensitivity was ∼7.2 mV/decade. Fluorescence experiments using SybrGreen I fluorescence dye support the electrochemical results. Y1 - 2018 U6 - https://doi.org/10.1021/acs.analchem.8b01807 SN - 0003-2700 VL - 90 IS - 12 SP - 7747 EP - 7753 PB - ACS Publications CY - Washington, DC ER - TY - GEN A1 - Burgeth, Bernhard A1 - Kleefeld, Andreas A1 - Naegel, Benoît A1 - Perret, Benjamin T1 - Editorial — Special Issue: ISMM 2019 T2 - Mathematical Morphology - Theory and Applications N2 - This editorial presents the Special Issue dedicated to the conference ISMM 2019 and summarizes the articles published in this Special Issue. Y1 - 2020 U6 - https://doi.org/10.1515/mathm-2020-0200 SN - 2353-3390 VL - 4 IS - 1 SP - 159 EP - 161 PB - De Gruyter CY - Warschau ER - TY - JOUR A1 - Ditzhaus, Marc A1 - Gaigall, Daniel T1 - A consistent goodness-of-fit test for huge dimensional and functional data JF - Journal of Nonparametric Statistics N2 - A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals. KW - Cramér-von-Mises statistic KW - separable Hilbert space KW - huge dimensional data KW - functional data Y1 - 2018 U6 - https://doi.org/10.1080/10485252.2018.1486402 SN - 1029-0311 VL - 30 IS - 4 SP - 834 EP - 859 PB - Taylor & Francis CY - Abingdon ER - TY - JOUR A1 - Gaigall, Daniel A1 - Gerstenberg, Julian A1 - Trinh, Thi Thu Ha T1 - Empirical process of concomitants for partly categorial data and applications in statistics JF - Bernoulli N2 - On the basis of independent and identically distributed bivariate random vectors, where the components are categorial and continuous variables, respectively, the related concomitants, also called induced order statistic, are considered. The main theoretical result is a functional central limit theorem for the empirical process of the concomitants in a triangular array setting. A natural application is hypothesis testing. An independence test and a two-sample test are investigated in detail. The fairly general setting enables limit results under local alternatives and bootstrap samples. For the comparison with existing tests from the literature simulation studies are conducted. The empirical results obtained confirm the theoretical findings. KW - bootstrap KW - Categorial variable KW - Concomitant KW - Empirical process KW - Independence test Y1 - 2022 U6 - https://doi.org/10.3150/21-BEJ1367 SN - 1573-9759 VL - 28 IS - 2 SP - 803 EP - 829 PB - International Statistical Institute CY - Den Haag, NL ER - TY - JOUR A1 - Artmann, Gerhard A1 - Grebe, R. A1 - Homrighausen, A. A1 - Wolff, H. A1 - Teitel, P. A1 - Schmid-Schönbein, H. T1 - Response of normal and diabetic erythrocytes to membrane deformation by chemical and mechanical forces. Artmann, Gerhard Michael; Grebe, R.; Homrighausen, A.; Wolff, H.; Teitel, P.; Schmid-Schönbein, H. JF - 12. Jahrestagung der Gesellschaft für Mikrozirkulation Y1 - 1988 SP - 196 EP - 200 PB - Karger [u.a.] CY - Basel [u.a.] ER -