https://puma.ub.uni-stuttgart.de/user/testusersimtechPUMA RSS feed for /user/testusersimtech2026-04-24T11:28:06+02:00https://puma.ub.uni-stuttgart.de/bibtex/2d8337fef78da9afa5e09d133f3ddaadc/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN5 PN5-11 selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andrea Barth" itemprop="url" href="/person/110a468b05935bc09e64db5be6dd8b6ac/author/0"><span itemprop="name">A. Barth</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Stein" itemprop="url" href="/person/110a468b05935bc09e64db5be6dd8b6ac/author/1"><span itemprop="name">A. Stein</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Mathematics and Computers in Simulation</span>, </em> </span>(<em><span>2025<meta content="2025" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Mathematics and Computers in Simulation347-370A stochastic transport problem with Lévy noise: Fully discrete numerical approximation.2272025EXC2075 PN5 PN5-11 selected https://puma.ub.uni-stuttgart.de/bibtex/265200d7a79f2d53cbf585dc001367089/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN3 PN3-4(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Juan Carlos del Valle" itemprop="url" href="/person/145f321147ed11675b9d45a481a0cfd42/author/0"><span itemprop="name">J. del Valle</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pilar Redondo" itemprop="url" href="/person/145f321147ed11675b9d45a481a0cfd42/author/1"><span itemprop="name">P. Redondo</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Kästner" itemprop="url" href="/person/145f321147ed11675b9d45a481a0cfd42/author/2"><span itemprop="name">J. Kästner</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Germán Molpeceres" itemprop="url" href="/person/145f321147ed11675b9d45a481a0cfd42/author/3"><span itemprop="name">G. Molpeceres</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Astrophys. J.</span>, </em> </span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Astrophys. J.129Formation of the Interstellar Sugar Precursor, (Z)-1,2-Ethenediol, through Radical Reactions on Dust Grains9742024EXC2075 PN3 PN3-4(II) selected https://puma.ub.uni-stuttgart.de/bibtex/2ac370fa7743902ae86e187835955a477/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN3 PN3-4(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Patrick M. Becker" itemprop="url" href="/person/199f9d1de09f3d6401e8b8fcc1bccc0d9/author/0"><span itemprop="name">P. Becker</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Katja Heinze" itemprop="url" href="/person/199f9d1de09f3d6401e8b8fcc1bccc0d9/author/1"><span itemprop="name">K. Heinze</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Biprajit Sarkar" itemprop="url" href="/person/199f9d1de09f3d6401e8b8fcc1bccc0d9/author/2"><span itemprop="name">B. Sarkar</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johannes Kästner" itemprop="url" href="/person/199f9d1de09f3d6401e8b8fcc1bccc0d9/author/3"><span itemprop="name">J. Kästner</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">ChemElectroChem</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">11 </span></span>(<span itemprop="issueNumber">20</span>): <span itemprop="pagination">e202400301</span></em> </span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025ChemElectroChem20e202400301Redox−Acid/Base Phase Diagrams as an Entry to Computational Redox Chemistry112024EXC2075 PN3 PN3-4(II) selected https://puma.ub.uni-stuttgart.de/bibtex/21eb2bb4951a0104ba400e5f9529ce502/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN3 PN3A-8 PN5 PN5-7 PN6 PN6-1(II) misc <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="R. Herkert" itemprop="url" href="/person/1e9d1b612a6b17d90226f0f74c57a399e/author/0"><span itemprop="name">R. Herkert</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="P. Buchfink" itemprop="url" href="/person/1e9d1b612a6b17d90226f0f74c57a399e/author/1"><span itemprop="name">P. Buchfink</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="B. Haasdonk" itemprop="url" href="/person/1e9d1b612a6b17d90226f0f74c57a399e/author/2"><span itemprop="name">B. Haasdonk</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="J. Rettberg" itemprop="url" href="/person/1e9d1b612a6b17d90226f0f74c57a399e/author/3"><span itemprop="name">J. Rettberg</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="J. Fehr" itemprop="url" href="/person/1e9d1b612a6b17d90226f0f74c57a399e/author/4"><span itemprop="name">J. Fehr</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Large-Scale Scientific Computations</span>, </em></span><em>page <span itemprop="pagination">99--107</span>. </em><em>Cham, </em><em><span itemprop="publisher">Springer Nature Switzerland</span>, </em>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025ChamLarge-Scale Scientific Computations99--107Randomized Symplectic Model Order Reduction for Hamiltonian Systems2024EXC2075 PN3 PN3A-8 PN5 PN5-7 PN6 PN6-1(II) misc Simulations of large scale dynamical systems in multi-query or real-time contexts require efficient surrogate modelling techniques, as e.g. achieved via Model Order Reduction (MOR). Recently, symplectic methods like the complex singular value decomposition (cSVD) or the SVD-like decomposition have been developed for preserving Hamiltonian structure during MOR. In this contribution, we show how symplectic structure preserving basis generation can be made more efficient with randomized matrix factorizations. We present a randomized complex SVD (rcSVD) algorithm and a randomized SVD-like decomposition (rSVD-like). We demonstrate the efficiency of the approaches with numerical experiments on high dimensional systems.https://puma.ub.uni-stuttgart.de/bibtex/20d96128b61e1e64fe07a0889834cf99c/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6 PN6-5 PN6-5(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dirk Väth" itemprop="url" href="/person/123bb54fcd793f1ff09321766c81ad8c0/author/0"><span itemprop="name">D. Väth</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/123bb54fcd793f1ff09321766c81ad8c0/author/1"><span itemprop="name">P. Tilli</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/123bb54fcd793f1ff09321766c81ad8c0/author/2"><span itemprop="name">N. Vu</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations</span>, </em></span><em>page <span itemprop="pagination">114--123</span>. </em>(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations114--123Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking2021EXC2075 PN6 PN6-5 PN6-5(II) selected https://puma.ub.uni-stuttgart.de/bibtex/2baadf322b0b79fe1bc38454c418b0375/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6 PN6-2 selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Raphael Leiteritz" itemprop="url" href="/person/1a3ae90dbf6cd17e3488488dffffd0934/author/0"><span itemprop="name">R. Leiteritz</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Marcel Hurler" itemprop="url" href="/person/1a3ae90dbf6cd17e3488488dffffd0934/author/1"><span itemprop="name">M. Hurler</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dirk Pflüger" itemprop="url" href="/person/1a3ae90dbf6cd17e3488488dffffd0934/author/2"><span itemprop="name">D. Pflüger</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)</span>, </em></span><em>page <span itemprop="pagination">1664-1669</span>. </em>(<em><span>2021<meta content="2021" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 20252021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)1664-1669Learning Free-Surface Flow with Physics-Informed Neural Networks2021EXC2075 PN6 PN6-2 selected The interface between data-driven learning methods and classical simulation poses an interesting field offering a multitude of new applications. In this work, we build on the notion of physics-informed neural networks (PINNs) and employ them in the area of shallow-water equation (SWE) models. These models play an important role in modeling and simulating free-surface flow scenarios such as in flood-wave propagation or tsunami waves. Different formulations of the PINN residual are compared to each other and multiple optimizations are being evaluated to speed up the convergence rate. We test these with different 1-D and 2-D experiments and finally demonstrate that regarding a SWE scenario with varying bathymetry, the method is able to produce competitive results in comparison to the direct numerical simulation with a total relative $L_2$ error of $8.9e-3$.https://puma.ub.uni-stuttgart.de/bibtex/2cd9efcbe6c558e7c9d560a12c0abbb48/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN3-8 PN3-8(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maximilian Fleck" itemprop="url" href="/person/16d3fafd4d984eea4315ffa87b2a19661/author/0"><span itemprop="name">M. Fleck</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Samir Darouich" itemprop="url" href="/person/16d3fafd4d984eea4315ffa87b2a19661/author/1"><span itemprop="name">S. Darouich</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Niels Hansen" itemprop="url" href="/person/16d3fafd4d984eea4315ffa87b2a19661/author/2"><span itemprop="name">N. Hansen</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Joachim Gross" itemprop="url" href="/person/16d3fafd4d984eea4315ffa87b2a19661/author/3"><span itemprop="name">J. Gross</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">The Journal of Physical Chemistry B</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">128 </span></span>(<span itemprop="issueNumber">39</span>): <span itemprop="pagination">9544–9552</span></em> </span>(<em><span>September 2024<meta content="September 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025The Journal of Physical Chemistry B09399544–9552TAMie Force Field for Alkanethiols: Multifidelity Gaussian Processes for Dealing with Scarce Experimental Data1282024EXC2075 PN3-8 PN3-8(II) selected https://puma.ub.uni-stuttgart.de/bibtex/222bd48b9c5df6375654727c982125149/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN2 <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Matthew Millard" itemprop="url" href="/person/1f87d2c872f2e6f474113b724ada23083/author/0"><span itemprop="name">M. Millard</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Norman Stutzig" itemprop="url" href="/person/1f87d2c872f2e6f474113b724ada23083/author/1"><span itemprop="name">N. Stutzig</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jörg Fehr" itemprop="url" href="/person/1f87d2c872f2e6f474113b724ada23083/author/2"><span itemprop="name">J. Fehr</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Siebert" itemprop="url" href="/person/1f87d2c872f2e6f474113b724ada23083/author/3"><span itemprop="name">T. Siebert</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Journal of the Mechanical Behavior of Biomedical Materials</span>, </em> </span>(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Journal of the Mechanical Behavior of Biomedical Materials106740A benchmark of muscle models to length changes great and small1602024EXC2075 PN2 Digital human body models are used to simulate injuries that occur as a result of vehicle collisions, vibration, sports, and falls. Given enough time the body’s musculature can generate force, affect the body’s movements, and change the risk of some injuries. The finite-element code LS-DYNA is often used to simulate the movements and injuries sustained by the digital human body models as a result of an accident. In this work, we evaluate the accuracy of the three muscle models in LS-DYNA (MAT_156, EHTM, and the VEXAT) when simulating a range of experiments performed on isolated muscle: force-length-velocity experiments on maximally and sub-maximally stimulated muscle, active-lengthening experiments, and vibration experiments. The force-length-velocity experiments are included because these conditions are typical of the muscle activity that precedes an accident, while the active-lengthening and vibration experiments mimic conditions that can cause injury. The three models perform similarly during the maximally and sub-maximally activated force-length-velocity experiments, but noticeably differ in response to the active-lengthening and vibration experiments. The VEXAT model is able to generate the enhanced forces of biological muscle during active lengthening, while both the MAT_156 and EHTM produce too little force. In response to vibration, the stiffness and damping of the VEXAT model closely follows the experimental data while the MAT_156 and EHTM models differ substantially. The accuracy of the VEXAT model comes from two additional mechanical structures that are missing in the MAT_156 and EHTM models: viscoelastic cross-bridges, and an active titin filament. To help others build on our work we have made our simulation code publicly available.linked to Projekt Adireshttps://puma.ub.uni-stuttgart.de/bibtex/2c01258abd2921f28efb25a02c0940cb7/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6-5 PN6-5(II) misc <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lucas Möller" itemprop="url" href="/person/147c8ca6d1ac5ac549e6f6b7ae63abe8c/author/0"><span itemprop="name">L. Möller</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/147c8ca6d1ac5ac549e6f6b7ae63abe8c/author/1"><span itemprop="name">P. Tilli</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/147c8ca6d1ac5ac549e6f6b7ae63abe8c/author/2"><span itemprop="name">N. Vu</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Padó" itemprop="url" href="/person/147c8ca6d1ac5ac549e6f6b7ae63abe8c/author/3"><span itemprop="name">S. Padó</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Explaining Vision-Language Similarities in Dual Encoders with Feature-Pair Attributions2024EXC2075 PN6-5 PN6-5(II) misc https://puma.ub.uni-stuttgart.de/bibtex/240afd7347f9a617cb6cb2c623248edca/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN1 PN1-10 misc <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias S. Feinler" itemprop="url" href="/person/1f7082ccd8db4bd80faf045bee455eef1/author/0"><span itemprop="name">M. Feinler</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Bernadette N. Hahn" itemprop="url" href="/person/1f7082ccd8db4bd80faf045bee455eef1/author/1"><span itemprop="name">B. Hahn</span></a></span></span>. </span><span class="additional-entrytype-information">(<em><span>2024<meta content="2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Learned RESESOP for solving inverse problems with inexact forward operator2024EXC2075 PN1 PN1-10 misc https://puma.ub.uni-stuttgart.de/bibtex/25944e92567502f815dd268d2a8973b21/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6-5 PN6-5(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Esra Dönmez" itemprop="url" href="/person/1c8bde8198bf201783db70355cc494958/author/0"><span itemprop="name">E. Dönmez</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/1c8bde8198bf201783db70355cc494958/author/1"><span itemprop="name">P. Tilli</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hsiu-Yu Yang" itemprop="url" href="/person/1c8bde8198bf201783db70355cc494958/author/2"><span itemprop="name">H. Yang</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/1c8bde8198bf201783db70355cc494958/author/3"><span itemprop="name">N. Vu</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Carina Silberer" itemprop="url" href="/person/1c8bde8198bf201783db70355cc494958/author/4"><span itemprop="name">C. Silberer</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)</span>, </em></span><em>page <span itemprop="pagination">364--388</span>. </em><em>Singapore, </em><em><span itemprop="publisher">Association for Computational Linguistics</span>, </em>(<em><span>December 2023<meta content="December 2023" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025SingaporeProceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)12364--388{HNC}: Leveraging Hard Negative Captions towards Models with Fine-Grained Visual-Linguistic Comprehension Capabilities2023EXC2075 PN6-5 PN6-5(II) selected Image-Text-Matching (ITM) is one of the defacto methods of learning generalized representations from a large corpus in Vision and Language (VL). However, due to the weak association between the web-collected image{--}text pairs, models fail to show fine-grained understanding of the combined semantics of these modalities. To this end, we propose Hard Negative Captions (HNC): an automatically created dataset containing foiled hard negative captions for ITM training towards achieving fine-grained cross-modal comprehension in VL. Additionally, we provide a challenging manually-created test set for benchmarking models on a fine-grained cross-modal mismatch with varying levels of compositional complexity. Our results show the effectiveness of training on HNC by improving the models{'} zero-shot capabilities in detecting mismatches on diagnostic tasks and performing robustly under noisy visual input scenarios. Also, we demonstrate that HNC models yield a comparable or better initialization for fine-tuning. Our code and data are publicly available.https://puma.ub.uni-stuttgart.de/bibtex/2112b47e516f3b08e53d295d89027127a/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN2 PN2-8Siebert selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Corinna Coenning" itemprop="url" href="/person/17118ef30d9e0d0109338f9b611d56769/author/0"><span itemprop="name">C. Coenning</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Volker Rieg" itemprop="url" href="/person/17118ef30d9e0d0109338f9b611d56769/author/1"><span itemprop="name">V. Rieg</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Siebert" itemprop="url" href="/person/17118ef30d9e0d0109338f9b611d56769/author/2"><span itemprop="name">T. Siebert</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Veit Wank" itemprop="url" href="/person/17118ef30d9e0d0109338f9b611d56769/author/3"><span itemprop="name">V. Wank</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Scientific Reports</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">14 </span></span>(<span itemprop="issueNumber">1</span>): <span itemprop="pagination">24929</span></em> </span>(<em><span>Oct 22, 2024<meta content="Oct 22, 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Scientific Reports10124929Impact of contraction intensity and ankle joint angle on calf muscle fascicle length and pennation angle during isometric and dynamic contractions142024EXC2075 PN2 PN2-8Siebert selected 22During muscle contraction, not only are the fascicles shortening but also the pennation angle changes, which leads to a faster contraction of the muscle than of its fascicles. This phenomenon is called muscle gearing, and it has a direct influence on the force output of the muscle. There are few studies showing pennation angle changes during isometric and concentric contractions for different contraction intensities and muscle lengths. Therefore, the aim was to determine these influences over a wide range of contraction intensities and ankle joint angles for human triceps surae. Additionally, the influence of contraction intensity and ankle joint angle on muscle gearing was evaluated. Ten sport students performed concentric and isometric contractions with intensities between 0 and 90{\%} of the maximum voluntary contraction and ankle joint angles from 50{\textdegree} to 120{\textdegree}. During these contractions, the m. gastrocnemius medialis and lateralis and the m. soleus were recorded via ultrasound imaging. A nonlinear relationship between fascicle length and pennation angle was discovered, which can be described with a quadratic fit for each of the muscles during isometric contraction. A nearly identical relationship was detected during dynamic contraction. The muscle gearing increased almost linearly with contraction intensity and ankle joint angle.https://puma.ub.uni-stuttgart.de/bibtex/206617cdd3b123aca9801eb5205b09f1f/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN7 PN7-6(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jonas Kneifl" itemprop="url" href="/person/12ffaae3d8e2209369441c9740b61edf8/author/0"><span itemprop="name">J. Kneifl</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jörg Fehr" itemprop="url" href="/person/12ffaae3d8e2209369441c9740b61edf8/author/1"><span itemprop="name">J. Fehr</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steven L. Brunton" itemprop="url" href="/person/12ffaae3d8e2209369441c9740b61edf8/author/2"><span itemprop="name">S. Brunton</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="J. Nathan Kutz" itemprop="url" href="/person/12ffaae3d8e2209369441c9740b61edf8/author/3"><span itemprop="name">J. Kutz</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Computational Mechanics</span>, </em> </span>(<em><span>Oct 5, 2024<meta content="Oct 5, 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Computational Mechanics10Multi-hierarchical surrogate learning for explicit structural dynamical systems using graph convolutional neural networks2024EXC2075 PN7 PN7-6(II) selected 05Highly nonlinear dynamic finite element simulations using explicit time integration are particularly valuable tools for structural analysis in fields like automotive, aerospace, and civil engineering, or in the study of injury biomechanics. However, such state-of-the-art simulation models demand significant computational resources. Conventional data-driven surrogate modeling approaches address this by evolving the dynamics on low-dimensional embeddings, yet the majority of them operate directly on high-resolution data obtained from numerical discretizations, making them costly and unsuitable for adaptive resolutions or for handling information flow over large spatial distances. We therefore propose a multi-hierarchical framework for the structured creation of a series of surrogate models at different resolutions. Macroscale features are captured on coarse surrogates, while microscale effects are resolved on finer ones, while leveraging transfer learning to pass information between scales. The objective of this study is to develop efficient surrogates for a kart frame model in a frontal impact scenario. To achieve this, its mesh is simplified to obtain multi-resolution representations of the kart. Subsequently, a graph-convolutional neural network-based surrogate learns parameter-dependent low-dimensional latent dynamics on the coarsest representation. Following surrogates are trained on residuals using finer resolutions, allowing for multiple surrogates with varying hardware requirements and increasing accuracy.https://puma.ub.uni-stuttgart.de/bibtex/29f29154735b58797b7bdcb76a162cbcf/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN3 PN3-7 selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ángel D\&#039;ıaz Carral" itemprop="url" href="/person/16e379372559086387b40dde24215cb39/author/0"><span itemprop="name">{. Carral</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Magnus Ostertag" itemprop="url" href="/person/16e379372559086387b40dde24215cb39/author/1"><span itemprop="name">M. Ostertag</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Maria Fyta" itemprop="url" href="/person/16e379372559086387b40dde24215cb39/author/2"><span itemprop="name">M. Fyta</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">The Journal of Chemical Physics</span>, </em> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">154 </span></span>(<span itemprop="issueNumber">4</span>): <span itemprop="pagination">044111</span></em> </span>(<em><span>January 2021<meta content="January 2021" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025The Journal of Chemical Physics014044111Deep learning for nanopore ionic current blockades1542021EXC2075 PN3 PN3-7 selected https://puma.ub.uni-stuttgart.de/bibtex/274ebb87478e426fb1ca3ed8d21b1db0d/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6-5 PN6-5(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/1924c42b00a0554ad9e2adc79ed955ad7/author/0"><span itemprop="name">P. Tilli</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/1924c42b00a0554ad9e2adc79ed955ad7/author/1"><span itemprop="name">N. Vu</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</span>, </em></span><em>page <span itemprop="pagination">9204--9223</span>. </em><em>Torino, Italia, </em><em><span itemprop="publisher">ELRA and ICCL</span>, </em>(<em><span>May 2024<meta content="May 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Torino, ItaliaProceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)059204--9223Intrinsic Subgraph Generation for Interpretable Graph Based Visual Question Answering2024EXC2075 PN6-5 PN6-5(II) selected The large success of deep learning based methods in Visual Question Answering (VQA) has concurrently increased the demand for explainable methods. Most methods in Explainable Artificial Intelligence (XAI) focus on generating post-hoc explanations rather than taking an intrinsic approach, the latter characterizing an interpretable model. In this work, we introduce an interpretable approach for graph-based VQA and demonstrate competitive performance on the GQA dataset. This approach bridges the gap between interpretability and performance. Our model is designed to intrinsically produce a subgraph during the question-answering process as its explanation, providing insight into the decision making. To evaluate the quality of these generated subgraphs, we compare them against established post-hoc explainability methods for graph neural networks, and perform a human evaluation. Moreover, we present quantitative metrics that correlate with the evaluations of human assessors, acting as automatic metrics for the generated explanatory subgraphs. Our code will be made publicly available at link removed due to anonymity period.https://puma.ub.uni-stuttgart.de/bibtex/28010c05fb55b9efeb6025dc2b5dc6212/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN5 selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Teng Xu" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/0"><span itemprop="name">T. Xu</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sinan Xiao" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/1"><span itemprop="name">S. Xiao</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Reuschen" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/2"><span itemprop="name">S. Reuschen</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nils Wildt" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/3"><span itemprop="name">N. Wildt</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Harrie-Jan Hendricks Franssen" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/4"><span itemprop="name">H. Franssen</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Wolfgang Nowak" itemprop="url" href="/person/1761ff9054529b7eb6f53550c26f605e4/author/5"><span itemprop="name">W. Nowak</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Hydrology and Earth System Sciences</span>, </em> </span>(<em><span>2024 (accepted)<meta content="2024 (accepted)" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Hydrology and Earth System SciencesTowards a community-wide effort for benchmarking in subsurface hydrological inversion: benchmarking cases, high-fidelity reference solutions, procedure and a first comparison2024 (accepted)EXC2075 PN5 selected https://puma.ub.uni-stuttgart.de/bibtex/2a935bae2b08351be41efd97fae95465e/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6 PN6-5 PN6-5(II) misc <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sarina Meyer" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/0"><span itemprop="name">S. Meyer</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/1"><span itemprop="name">P. Tilli</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pavel Denisov" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/2"><span itemprop="name">P. Denisov</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Florian Lux" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/3"><span itemprop="name">F. Lux</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Julia Koch" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/4"><span itemprop="name">J. Koch</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/1ae2771c0b5955a966fc1cef34a99462e/author/5"><span itemprop="name">N. Vu</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">2022 IEEE Spoken Language Technology Workshop (SLT)</span>, </em></span><em>page <span itemprop="pagination">912--919</span>. </em><em>IEEE, </em>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 20252022 IEEE Spoken Language Technology Workshop (SLT)912--919Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy2023EXC2075 PN6 PN6-5 PN6-5(II) misc https://puma.ub.uni-stuttgart.de/bibtex/2d645e1d39e2fd40bab22b53e22a73771/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN6-5 PN6-5(II) selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Noel Schäfer" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/0"><span itemprop="name">N. Schäfer</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sebastian Künzel" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/1"><span itemprop="name">S. Künzel</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tanja Munz-Körner" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/2"><span itemprop="name">T. Munz-Körner</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Pascal Tilli" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/3"><span itemprop="name">P. Tilli</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sandeep Vidyapu" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/4"><span itemprop="name">S. Vidyapu</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ngoc Thang Vu" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/5"><span itemprop="name">N. Thang Vu</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Daniel Weiskopf" itemprop="url" href="/person/1339c20d6111bec800cfc2c8f23acfcf9/author/6"><span itemprop="name">D. Weiskopf</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 16th International Symposium on Visual Information Communication and Interaction</span>, </em></span><em>New York, NY, USA, </em><em><span itemprop="publisher">Association for Computing Machinery</span>, </em>(<em><span>2023<meta content="2023" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025New York, NY, USAProceedings of the 16th International Symposium on Visual Information Communication and InteractionVINCI '23Visual Analysis of Scene-Graph-Based Visual Question Answering2023EXC2075 PN6-5 PN6-5(II) selected Scene-graph-based Visual Question Answering (VQA) has emerged as a burgeoning field in Deep Learning research, with a growing demand for robust and interpretable VQA systems. In this paper, we present a novel visual analysis approach that addresses two critical objectives in VQA: identifying and correcting prediction issues and providing insights into model decision-making processes through visualizing internal information. Our approach builds on the GraphVQA framework, which uses graph neural networks to process scene graphs representing images and which was trained on the widely-used GQA dataset. Our analysis tool aims at users familiar with the basics of graph-based VQA. By leveraging query-based scene analysis and visualization of crucial internal states, we are able to detect and pinpoint reasons for inaccurate predictions, facilitating model refinement and dataset curation. Identifying expressive internal states is a challenge. Through rigorous computer-based evaluations and presentation of a use case, we demonstrate the effectiveness of our analysis tool and model state visualization.https://puma.ub.uni-stuttgart.de/bibtex/2c95bd672eec94118623f036030864e68/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PN2 selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Fabian Kempter" itemprop="url" href="/person/1958da81d5faeafe01668d01f4a237c19/author/0"><span itemprop="name">F. Kempter</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lorena Lantella" itemprop="url" href="/person/1958da81d5faeafe01668d01f4a237c19/author/1"><span itemprop="name">L. Lantella</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Norman Stutzig" itemprop="url" href="/person/1958da81d5faeafe01668d01f4a237c19/author/2"><span itemprop="name">N. Stutzig</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jörg Fehr" itemprop="url" href="/person/1958da81d5faeafe01668d01f4a237c19/author/3"><span itemprop="name">J. Fehr</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tobias Siebert" itemprop="url" href="/person/1958da81d5faeafe01668d01f4a237c19/author/4"><span itemprop="name">T. Siebert</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Annals of Biomedical Engineering</span>, </em> </span>(<em><span>April 2024<meta content="April 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Annals of Biomedical Engineering04771–782Role of Rotated Head Postures on Volunteer Kinematics and Muscle Activity in Braking Scenarios Performed on a Driving Simulator512024EXC2075 PN2 selected Occupants exposed to low or moderate crash events can already suffer from whiplash-associated disorders leading to severe and long-lasting symptoms. However, the underlying injury mechanisms and the role of muscle activity are not fully clear. Potential increases in injury risk of non-nominal postures, i.e., rotated head, cannot be evaluated in detail due to the lack of experimental data. Examining changes in neck muscle activity to hold and stabilize the head in a rotated position during pre-crash scenarios might provide a deeper understanding of muscle reflex contributions and injury mechanisms. In this study, the influence of two different head postures (nominal vs. rotation of the head by about 63 ± 9° to the right) on neck muscle activity and head kinematics was investigated in simulated braking experiments inside a driving simulator. The braking scenario was implemented by visualization of the virtual scene using head-mounted displays and a combined translational-rotational platform motion. Kinematics of seventeen healthy subjects was tracked using 3D motion capturing. Surface electromyography were used to quantify muscle activity of left and right sternocleidomastoideus (SCM) and trapezius (TRP) muscles. The results show clear evidence that rotated head postures affect the static as well as the dynamic behavior of muscle activity during the virtual braking event. With head turned to the right, the contralateral left muscles yielded higher base activation and delayed muscle onset times. In contrast, right muscles had much lower activations and showed no relevant changes in muscle activation between nominal and rotated head position. The observed delayed muscle onset times and increased asymmetrical muscle activation patterns in the rotated head position are assumed to affect injury mechanisms. This could explain the prevalence of rotated head postures during a crash reported by patients suffering from WAD. The results can be used for validating the active behavior of human body models in braking simulations with nominal and rotated head postures, and to gain a deeper understanding of neck injury mechanisms.linked to Adireshttps://puma.ub.uni-stuttgart.de/bibtex/2d967334e0e1673115b49cc5f64a3b7a6/testusersimtechtestusersimtech2025-01-27T13:09:00+01:00EXC2075 PNX selected <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Sibylle Hermann" itemprop="url" href="/person/1567912cd4c1492f96e17d17d42aa3dce/author/0"><span itemprop="name">S. Hermann</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jörg Fehr" itemprop="url" href="/person/1567912cd4c1492f96e17d17d42aa3dce/author/1"><span itemprop="name">J. Fehr</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Royal Society Open Science</span>, </em> </span>(<em><span>October 2024<meta content="October 2024" itemprop="datePublished"/></span></em>)</span>Mon Jan 27 13:09:00 CET 2025Royal Society Open Science1010Documenting Research in Simulation Science to Enhance Understanding for Reusability112024EXC2075 PNX selected