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KI-Morph – User-friendly large-scale image analysis & AI on bwHPC systems

Abstract (Expand)

Artificial Intelligence (AI) has become indispensable for analyzing large-scale datasets, particularly in the realm of 3D image volumes. However, effectively harnessing AI for such tasks often requires … advanced algorithms and high-performance computing (HPC) resources, presenting significant challenges for non-technical users. To overcome these barriers, we present KI-Morph, a novel software platform for large-scale image analysis seamlessly integrated with the bwHPC infrastructure. It offers a user-friendly interface, enabling sophisticated AI-driven analysis without requiring technical expertise in either AI or HPC. KI-Morph prioritizes data privacy and sovereignty, ensuring that users retain full control over their data. Additionally, the components developed for the platform support researchers also with science outreach by enabling the creation of interactive online visualizations, for example using the 2D, 3D and augmented reality viewers.

Authors: Vincent Heuveline, Alexander Zeilmann

Date Published: 26th Sep 2024

Publication Type: InProceedings

Generating Highly Designable Proteins with Geometric Algebra Flow Matching

Abstract

Not specified

Authors: Simon Wagner, Leif Seute, Vsevolod Viliuga, Nicolas Wolf, Frauke Gräter, Jan Stuehmer

Date Published: 25th Sep 2024

Publication Type: InProceedings

Multivariate post‐processing of probabilistic sub‐seasonal weather regime forecasts

Abstract

Not specified

Authors: Fabian Mockert, Christian M. Grams, Sebastian Lerch, Marisol Osman, Julian Quinting

Date Published: 19th Sep 2024

Publication Type: Journal

Physics-based vs. data-driven 24-hour probabilistic forecasts of precipitation for northern tropical Africa

Abstract

Not specified

Authors: Eva–Maria Walz, Peter Knippertz, Andreas H. Fink, Gregor Köhler, Tilmann Gneiting

Date Published: 1st Sep 2024

Publication Type: Journal

Testing a non-local 1-equation turbulent convection model: A solar model

Abstract (Expand)

Context: Turbulent convection models treat stellar convection more physically than standard mixing-length theory by including non-local effects. We recently successfully applied the Kuhfuss version to … convective cores in main sequence stars. Its usefulness for convective envelopes remains to be tested. Aims: The solar convective envelope constitutes a viable test bed for investigating the usefulness of the 1-equation Kuhfuss turbulent convection model. Methods: We used the one-dimensional stellar evolution code GARSTEC to calculate a standard solar model with the 1-equation Kuhfuss turbulent convection model, and compared it to helioseismic measurements and a solar model using standard mixing-length theory. Additionally, we investigated the influence of the additional free parameters of the convection model on the solar structure. Results: The 1-equation Kuhfuss model reproduces the sound-speed profile and the lower boundary of the convective region less well than the mixing-length model, because the inherent non-local effects overestimate the amount of convective penetration below the Schwarzschild boundary. We trace this back to the coupling of the temperature gradient to the convective flux in the 1-equation version of the Kuhfuss theory. Conclusions: The temperature stratification of the solar convective envelope is not well modelled by the 1-equation Kuhfuss turbulent convection model, and the more complex 3-equation version is needed to improve the modelling of convection in the envelopes of 1D stellar evolution models.

Authors: T. A. M. Braun, F. Ahlborn, A. Weiss

Date Published: 1st Sep 2024

Publication Type: Journal

Effects of Systematic Errors on Phylogenetic Inference

Abstract

Not specified

Authors: Erik Borker, Alexandros Stamatakis

Date Published: 1st Sep 2024

Publication Type: Master's Thesis

Merger seismology: Asteroseismic properties of massive merger products

Abstract

Not specified

Authors: Jan Henneco, Fabian R. N. Schneider, Saskia Hekker, Conny Aerts

Date Published: 1st Sep 2024

Publication Type: InProceedings

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