Dieter Suter’s research while affiliated with TU Dortmund University and other places

... One could analyse how world records evolved over time and compare the progress made in given athletic events. 21 To take a view on long-term trends in athletic performances this is certainly a valid methodology. However, to compare the general level of performance in any given year or period looking at the prevailing world records would provide a biased view. ...

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Internationalization, competitiveness and performance in athletics (1984–2006)

... It is the study of the statistical properties of particularly large or small values within a data set. EVA is widely applied in various fields where extreme phenomena hold significant importance, such as engineering, meteorology, finance, insurance, and environmental science (Basnayake et al 2019;de Haan and Ferreira 2006;Dong 2016;Einmahl and Magnus 2008;Gembris et al. 2002;Kratz 2017;Rootzen 2017;Songchitruksa and Tarko 2006;Tippett et al. 2016;Tsuduki 2024;Wong and Collins 2020). The central concepts of EVA involve identifying the largest or smallest values in a dataset, determining whether these extremes follow distributions like the Fréchet distribution, Weibull distribution, or Gumbel distribution, and analyzing data points that exceed specific thresholds to estimate their distribution. ...

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Extreme-value analysis in nano-biological systems: Applications and Implications

... Correction for temporal correlations was not available. Cummulative correlation analysis (Gembris et al 2000) was performed for comparison. Activation maps were spatially smoothed using a 3×3 median filter. ...

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Enhancement of Temporal Resolution and BOLD Sensitivity in Real-Time fMRI using Multi-Slab Echo-Volumar Imaging

... The physical laws that govern the dynamics of this substance are expressed as a set of partial differential equations (PDEs), which are solved numerically on the diffusion tensor field to produce a metric of connectivity. Early work in this area focused on developing methods modeled on the simple diffusion of heat or water through the image volume, whose dynamics is computed by solving the first order heat equation on the diffusion tensor field [41]- [43]. These methods have the advantages of level set and probabilistic methods and are based the same physical model used to construct the diffusion tensor field. ...

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A Diffusion Tensor Imaging Tractography Algorithm Based on Navier–Stokes Fluid Mechanics

... In general, there are several characteristics, such as: The basic gradient technique is often applied to machine learning, as detailed in [22]. Creating a multidimensional plane is an effective classification method [23]. ...

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Technique for Segmentation and Selection of Biomedical Images

... Based on the fact that the concentration (or density) fluctuation of an ideal diffusive medium is governed entirely by the diffusion equation (a partial-derivative description of Fick's law [17]), a natural strategy to reveal the spatio-temporal diffusion process is to obtain the numerical solution of the diffusion equation [18]. Previous attempts to employ this strategy, however, have not been successful due to their limitations in practical implementations, such as the 2-D or partial-brain calculation domain requirements as stated in [18][19][20]. Xu et al. [21] recently employed an improved numerical method to diffusion-weighted Bloch-Torrey equation in simulating diffusion MRI measurements on biological tissues, yet not presented the macroscopic evolution of the diffusive concentration. In this paper, we present a method to map the 3-D spatio-temporal diffusion process in the entire brain based on the numerical solution of the diffusion equation, and then compare with an IOI study. ...

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Mapping Spatio-Temporal Diffusion inside the Human Brain Using a Numerical Solution of the Diffusion Equation

... Applying such methods online would imply that the incremental computation time increases on each new scan, which is clearly a serious drawback when considering real-time constraints. To overcome this problem, some techniques were proposed that compute the correlation between the signal and the model, either in an incremental fashion [2], or by restricting computations to a sliding time window [3]. ...

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Solving Incrementally the Fitting and Detection Problems in fMRI Time Series

... In competitive sports, achieving a new world record is always gratifying. However, it's not just about representing the pinnacle of a specific sports specialty, it's crucial to assess the valuable information and patterns behind the record [1]. Sports records, over time, follow a monotonic function on a time scale and spatial function [2]. ...

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Exploring the dynamics of sports records evolution through the gembris prediction model and network relevance analysis

... It is the study of the statistical properties of particularly large or small values within a data set. EVA is widely applied in various fields where extreme phenomena hold significant importance (Coles 2001;Gilleland and Katz 2016), such as disaster prevention (de Haan and Ferreira 2006;Tippett et al. 2016), finance (Kratz 2019), safety estimation (Songchitruksa and Tarko 2006), sports (Einmahl and Magnus 2008;Gembris et al. 2002), human lifespan (Dong et al. 2016;Rootzen and Zolud 2017), and the recent pandemic (Wong and Collins 2020). Recently, its applications in the biological data analysis has also become active (Basnayake et al. 2019;Tsuduki 2024). ...

Reference:

Extreme-value analysis in nano-biological systems: applications and implications