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Brunton","J. Nathan Kutz" ], "authors": [ {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Jörg", "last" : "Fehr"}, {"first" : "Steven L.", "last" : "Brunton"}, {"first" : "J. Nathan", "last" : "Kutz"} ], "abstract": "Highly 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.", "issn" : "1432-0924", "preprinturl" : "https://doi.org/10.48550/arXiv.2402.09234", "doi" : "10.1007/s00466-024-02553-6", "bibtexKey": "Kneifl2024" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2b1084a07104d9d1132be8af4581360ab/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Sedlmair","PN7-1.3","selected" ], "intraHash" : "b1084a07104d9d1132be8af4581360ab", "interHash" : "6c2799500d702cde816a3ccc26ef2dc5", "label" : "ChoreoVis: Planning and Assessing Formations in Dance Choreographies", "user" : "testusersimtech", "description" : "", "date" : "2024-10-07 09:24:07", "changeDate" : "2024-10-07 09:24:07", "count" : 7, "pub-type": "proceedings", "journal": "Computer Graphics Forum","publisher":"The Eurographics Association and John Wiley & Sons Ltd.", "year": "2024", "url": "https://diglib.eg.org/handle/10.1111/cgf15104", "author": [ "Samuel Beck","Nina Doerr","Kuno Kurzhals","Alexander Riedlinger","Fabian Schmierer","Michael Sedlmair","Steffen Koch" ], "authors": [ {"first" : "Samuel", "last" : "Beck"}, {"first" : "Nina", "last" : "Doerr"}, {"first" : "Kuno", "last" : "Kurzhals"}, {"first" : "Alexander", "last" : "Riedlinger"}, {"first" : "Fabian", "last" : "Schmierer"}, {"first" : "Michael", "last" : "Sedlmair"}, {"first" : "Steffen", "last" : "Koch"} ], "volume": "43","number": "3","abstract": "Sports visualization has developed into an active research field over the last decades. Many approaches focus on analyzing movement data recorded from unstructured situations, such as soccer. For the analysis of choreographed activities like formation dancing, however, the goal differs, as dancers follow specific formations in coordinated movement trajectories. To date, little work exists on how visual analytics methods can support such choreographed performances. To fill this gap, we introduce a new visual approach for planning and assessing dance choreographies. In terms of planning choreographies, we contribute a web application with interactive authoring tools and views for the dancers' positions and orientations, movement trajectories, poses, dance floor utilization, and movement distances. For assessing dancers' real-world movement trajectories, extracted by manual bounding box annotations, we developed a timeline showing aggregated trajectory deviations and a dance floor view for detailed trajectory comparison. Our approach was developed and evaluated in collaboration with dance instructors, showing that introducing visual analytics into this domain promises improvements in training efficiency for the future.", "issn" : "1467-8659", "doi" : "10.1111/cgf.15104", "bibtexKey": "10.1111:cgf.15104" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/25d2f808133b0b5ef1694fa776b46177d/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Sedlmair","PN7-1.3","selected" ], "intraHash" : "5d2f808133b0b5ef1694fa776b46177d", "interHash" : "0f4c31756eb9bd0ca1340bcb7b99756a", "label" : "Sitting Posture Recognition and Feedback: A Literature Review", "user" : "testusersimtech", "description" : "", "date" : "2024-10-07 09:24:07", "changeDate" : "2024-10-07 09:24:07", "count" : 8, "pub-type": "inproceedings", "booktitle": "CHI '24: Proceedings of the CHI Conference on Human Factors in Computing Systems","series": "CHI","publisher":"ACM","address":"NY", "year": "2024", "url": "https://github.com/ChristianKrauter/sitting-posture-review-material", "author": [ "Christian Krauter","Katrin Angerbauer","Aimée Sousa Calepso","Alexander Achberger","Sven Mayer","Michael Sedlmair" ], "authors": [ {"first" : "Christian", "last" : "Krauter"}, {"first" : "Katrin", "last" : "Angerbauer"}, {"first" : "Aimée", "last" : "Sousa Calepso"}, {"first" : "Alexander", "last" : "Achberger"}, {"first" : "Sven", "last" : "Mayer"}, {"first" : "Michael", "last" : "Sedlmair"} ], "affiliation" : "Krauter, Christian, University of Stuttgart. Angerbauer, Katrin, Visualisierungsinstitut der Universität Stuttgart. Sousa Calepso, Aimée, Visualisierungsinstitut der Universität Stuttgart. Achberger, Alexander, Visualisierungsinstitut der Universität Stuttgart. Sedlmair, Michael, Visualisierungsinstitut der Universität Stuttgart", "orcid-numbers" : "Krauter, Christian/0000-0002-9787-0816, Angerbauer, Katrin/0000-0002-1126-5288, Sedlmair, Michael/0000-0001-7048-9292", "doi" : "10.1145/3613904.3642657", "bibtexKey": "krauter:2024:sitting" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/256098df22d41a8c64c592971e155a9d5/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Becker","PN7-1.1","selected" ], "intraHash" : "56098df22d41a8c64c592971e155a9d5", "interHash" : "c457add8aa0d32d7b146f5c6f0c7661c", "label" : "Persival: Simulating Complex 3D Meshes on Resource-Constrained Mobile AR Devices Using Interpolation", "user" : "testusersimtech", "description" : "", "date" : "2024-09-16 14:37:42", "changeDate" : "2024-09-16 14:37:42", "count" : 11, "pub-type": "inproceedings", "booktitle": "Proceedings of the 2022 IEEE International Conference on Distributed Computing Systems (ICDCS)", "year": "2022", "url": "", "author": [ "Johannes Kässinger","David Rosin","Frank Dürr","Niklas Hornischer","Kurt Rothermel","Oliver Röhrle" ], "authors": [ {"first" : "Johannes", "last" : "Kässinger"}, {"first" : "David", "last" : "Rosin"}, {"first" : "Frank", "last" : "Dürr"}, {"first" : "Niklas", "last" : "Hornischer"}, {"first" : "Kurt", "last" : "Rothermel"}, {"first" : "Oliver", "last" : "Röhrle"} ], "pages": "961--971", "doi" : "10.1109/ICDCS54860.2022.00097", "bibtexKey": "kassinger2022persival" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2bbcf827c4564a053b8b371aecd1971a0/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Becker","PN7-1.1","selected" ], "intraHash" : "bbcf827c4564a053b8b371aecd1971a0", "interHash" : "1fde610dc74ce6153cb9913558539c43", "label" : "Persival: Using Delayed Remote Updates in a Distributed Mobile Simulation", "user" : "testusersimtech", "description" : "", "date" : "2024-09-16 14:37:42", "changeDate" : "2024-09-16 14:37:42", "count" : 12, "pub-type": "article", "year": "2023", "url": "", "author": [ "Johannes Kässinger","David Rosin","Frank Dürr","Benedikt Mehler","Thomas Hubatscheck","Kurt Rothermel" ], "authors": [ {"first" : "Johannes", "last" : "Kässinger"}, {"first" : "David", "last" : "Rosin"}, {"first" : "Frank", "last" : "Dürr"}, {"first" : "Benedikt", "last" : "Mehler"}, {"first" : "Thomas", "last" : "Hubatscheck"}, {"first" : "Kurt", "last" : "Rothermel"} ], "eventtitle" : "Submitted to: International Conference on Computer Communications and Networks (ICCCN 2023)", "bibtexKey": "kassinger2023persival" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/22764d6993d458c90941423f1ca2bdd92/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Becker","PN7-1.1","selected" ], "intraHash" : "2764d6993d458c90941423f1ca2bdd92", "interHash" : "6221db40abc105f036527d536102121a", "label" : "SimEdge: Towards Accelerated Real-Time Augmented Reality Simulations Using Adaptive Smart Edge Computing", "user" : "testusersimtech", "description" : "", "date" : "2024-09-16 14:37:42", "changeDate" : "2024-09-16 14:37:42", "count" : 8, "pub-type": "inproceedings", "booktitle": "Proceedings of the Int'l ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems","publisher":"Association for Computing Machinery", "year": "2023", "url": "", "author": [ "Johannes Kässinger","Heiko Trötsch","Frank Dürr","Janick Edinger" ], "authors": [ {"first" : "Johannes", "last" : "Kässinger"}, {"first" : "Heiko", "last" : "Trötsch"}, {"first" : "Frank", "last" : "Dürr"}, {"first" : "Janick", "last" : "Edinger"} ], "pages": "181-190", "venue" : "Montreal, Canada", "isbn" : "979-8-4007-0366-9", "research-areas" : "Engineering; Telecommunications", "language" : "eng", "eventdate" : "2023-10-30/2023-11-03", "eventtitle" : "26th ACM International Conference on Modelling, Analysis, and Simulation of Wireless and Mobile Systems (MSWiM)", "affiliation" : "Kässinger, J (Corresponding Author), Univ Stuttgart, IPVS, Stuttgart, Germany.\n Kaessinger, Johannes; Duerr, Frank, Univ Stuttgart, IPVS, Stuttgart, Germany.\n Troetsch, Heiko, Univ Mannheim, Mannheim, Germany.\n Edinger, Janick, Univ Hamburg, Hamburg, Germany.", "unique-id" : "WOS:001122494100023", "doi" : "10.1145/3616388.3617526", "bibtexKey": "kassinger2023simedge" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/21d6f0d36afc9fb227782a7eeae0c5e71/testusersimtech", "tags" : [ "EXC2075","PN3","PN3A-8","PN7","PN7-6(II)","misc" ], "intraHash" : "1d6f0d36afc9fb227782a7eeae0c5e71", "interHash" : "e74987dd84939f46117540d9532f55d8", "label" : "Data-driven identification of latent port-Hamiltonian systems", "user" : "testusersimtech", "description" : "", "date" : "2024-09-12 12:02:31", "changeDate" : "2024-09-12 12:02:31", "count" : 7, "pub-type": "misc", "year": "2024", "url": "https://arxiv.org/abs/2408.08185", "author": [ "Johannes Rettberg","Jonas Kneifl","Julius Herb","Patrick Buchfink","Jörg Fehr","Bernard Haasdonk" ], "authors": [ {"first" : "Johannes", "last" : "Rettberg"}, {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Julius", "last" : "Herb"}, {"first" : "Patrick", "last" : "Buchfink"}, {"first" : "Jörg", "last" : "Fehr"}, {"first" : "Bernard", "last" : "Haasdonk"} ], "note": "nur Preprint", "eprint" : "2408.08185", "archiveprefix" : "arXiv", "primaryclass" : "math.DS", "doi" : "https://doi.org/10.48550/arXiv.2408.08185", "bibtexKey": "rettberg2024datadrivenidentificationlatentporthamiltonian" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27e724b83a7eb0255a8b94e75da9bc0c3/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-1(II)Sedlmair","PN7-1.3","selected" ], "intraHash" : "7e724b83a7eb0255a8b94e75da9bc0c3", "interHash" : "1accfcc7c6674ce6c6b8c00162b5daf1", "label" : "MolecuSense: Using Force-Feedback Gloves for Creating and Interacting with Ball-and-Stick Molecules in VR", "user" : "testusersimtech", "description" : "", "date" : "2024-09-12 12:02:31", "changeDate" : "2024-09-12 12:02:31", "count" : 18, "pub-type": "inproceedings", "booktitle": "Proceedings of the 15th International Symposium on Visual Information Communication and Interaction","series": "VINCI '22","publisher":"Association for Computing Machinery","address":"New York, NY, USA", "year": "2022", "url": "https://doi.org/10.1145/3554944.3554956", "author": [ "Patrick Gebhardt","Xingyao Yu","Andreas Köhn","Michael Sedlmair" ], "authors": [ {"first" : "Patrick", "last" : "Gebhardt"}, {"first" : "Xingyao", "last" : "Yu"}, {"first" : "Andreas", "last" : "Köhn"}, {"first" : "Michael", "last" : "Sedlmair"} ], "pages": "1\u20135","abstract": "We contribute MolecuSense, a virtual version of a physical molecule construction kit, based on visualization in Virtual Reality (VR) and interaction with force-feedback gloves. Targeting at chemistry education, our goal is to make virtual molecule structures more tangible. Results of an initial user study indicate that the VR molecular construction kit was positively received. Compared to a physical construction kit, the VR molecular construction kit is on the same level in terms of natural interaction. Besides, it fosters the typical digital advantages though, such as saving, exporting, and sharing of molecules. Feedback from the study participants has also revealed potential future avenues for tangible molecule visualizations.", "isbn" : "9781450398060", "location" : "Chur, Switzerland", "doi" : "10.1145/3554944.3554956", "bibtexKey": "Gebhardt2022" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/25a0b1ed823863221c7de810797a39e5c/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)","unclear" ], "intraHash" : "5a0b1ed823863221c7de810797a39e5c", "interHash" : "d1c0cf1bf9df7eca4ce83a54d6cbc03a", "label" : "VENI-VINDy-VICI: 0.1.7", "user" : "testusersimtech", "description" : "Code", "date" : "2024-09-12 12:02:31", "changeDate" : "2024-09-12 12:02:31", "count" : 6, "pub-type": "misc", "publisher":"Zenodo", "year": "2024", "url": "https://zenodo.org/doi/10.5281/zenodo.13120249", "author": [ "Jonas Kneifl","Paolo Conti" ], "authors": [ {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Paolo", "last" : "Conti"} ], "note": "Was soll das sein?","abstract": "An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification", "copyright" : "MIT License", "doi" : "10.5281/ZENODO.13120249", "bibtexKey": "https://doi.org/10.5281/zenodo.13120249" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c170f60a0e993f10ff3a6461dff8ecee/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)","selected" ], "intraHash" : "c170f60a0e993f10ff3a6461dff8ecee", "interHash" : "d3e28796b1b2f7fab0422bbe9fbaaa51", "label" : "On using machine learning algorithms for motorcycle collision detection", "user" : "testusersimtech", "description" : "", "date" : "2024-08-09 07:49:09", "changeDate" : "2024-08-09 07:49:09", "count" : 15, "pub-type": "article", "journal": "Discover Applied Sciences", "year": "2024", "url": "https://doi.org/10.1007/s42452-024-06014-w", "author": [ "Philipp Rodegast","Steffen Maier","Jonas Kneifl","Jörg Fehr" ], "authors": [ {"first" : "Philipp", "last" : "Rodegast"}, {"first" : "Steffen", "last" : "Maier"}, {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Jörg", "last" : "Fehr"} ], "volume": "6","number": "6","pages": "326","abstract": "Globally, motorcycles attract vast and varied users. However, since the rate of severe injury and fatality in motorcycle accidents far exceeds that of passenger car accidents, efforts have been directed towards increasing passive safety systems. Impact simulations show that the risk of severe injury or death in the event of a motorcycle-to-car impact can be greatly reduced if the motorcycle is equipped with passive safety measures such as airbags and seat belts. For the passive safety systems to be activated, a collision must be detected within milliseconds for a wide variety of impact configurations, but under no circumstances may it be falsely triggered. For the challenge of reliably detecting impending collisions, this paper presents an investigation towards the applicability of machine learning algorithms. First, a series of simulations of accidents and driving operation is introduced to collect data to train machine learning classification models. Their performance is henceforth assessed and compared via multiple representative and application-oriented criteria.", "issn" : "3004-9261", "doi" : "10.1007/s42452-024-06014-w", "bibtexKey": "Rodegast2024" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2c0203b229f9524f712d15ffbe47db0b0/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6","slected" ], "intraHash" : "c0203b229f9524f712d15ffbe47db0b0", "interHash" : "d6b780508badd621361b9c0639481d09", "label" : "Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme", "user" : "testusersimtech", "description" : "", "date" : "2024-08-09 07:49:09", "changeDate" : "2024-08-09 07:49:09", "count" : 6, "pub-type": "article", "journal": "IFAC-PapersOnLine","publisher":"Elsevier BV", "year": "2022", "url": "https://doi.org/10.1016%2Fj.ifacol.2022.09.109", "author": [ "J. Kneifl","J. Hay","J. Fehr" ], "authors": [ {"first" : "J.", "last" : "Kneifl"}, {"first" : "J.", "last" : "Hay"}, {"first" : "J.", "last" : "Fehr"} ], "volume": "55","number": "20","pages": "283--288","note": "preprint: https://arxiv.org/abs/2110.13583", "doi" : "10.1016/j.ifacol.2022.09.109", "bibtexKey": "Kneifl_2022" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2357b165eefbd825089d47dde703a76f4/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-8","selected" ], "intraHash" : "357b165eefbd825089d47dde703a76f4", "interHash" : "c7f7351ae5947e5f5674777d138b1cba", "label" : "chARpack: The Chemistry Augmented Reality Package", "user" : "testusersimtech", "description" : "", "date" : "2024-07-19 15:07:18", "changeDate" : "2024-07-19 15:07:18", "count" : 7, "pub-type": "article", "journal": "J. Chem. Inf. Model.", "year": "2024", "url": "https://doi.org/10.1021/acs.jcim.4c00462", "author": [ "Tobias Rau","Michael Sedlmair","Andreas Köhn" ], "authors": [ {"first" : "Tobias", "last" : "Rau"}, {"first" : "Michael", "last" : "Sedlmair"}, {"first" : "Andreas", "last" : "Köhn"} ], "volume": "64","number": "12","pages": "4700\u20134708", "abstractnote" : "Off-loading visualization and interaction into virtual reality (VR) using head-mounted displays (HMDs) has gained considerable popularity in simulation sciences, particularly in chemical modeling. Because of its unique way of soft immersion, augmented reality (AR) HMD technology has even more potential to be integrated into the everyday workflow of computational chemists. In this work, we present our environment to explore the prospects of AR in chemistry and general molecular sciences: The chemistry in Augmented Reality package (chARpack). Besides providing an extensible framework, our software focuses on a seamless transition between a 3D stereoscopic view with true 3D interactions and the traditional desktop PC setup to provide users with the best setup for all tasks in their workflow. Using feedback from domain experts, we discuss our design requirements for this kind of hybrid working environment (AR + PC), regarding input, features, degree of immersion, and collaboration.", "issn" : "1549-9596", "doi" : "10.1021/acs.jcim.4c00462", "bibtexKey": "Rau_Sedlmair_Köhn_2024" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/23c18ff6580575dbbdc6e0f12d266cf9d/testusersimtech", "tags" : [ "EXC2075","PN7","darus" ], "intraHash" : "3c18ff6580575dbbdc6e0f12d266cf9d", "interHash" : "8255ce94bee8751857302fc0d36a7d29", "label" : "Replication Code for: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference", "user" : "testusersimtech", "description" : "", "date" : "2024-07-03 10:45:48", "changeDate" : "2024-07-03 10:45:48", "count" : 6, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Philipp Luca Reiser","Javier Enrique Aguilar","Anneli Guthke","Paul-Christian Bürkner" ], "authors": [ {"first" : "Philipp Luca", "last" : "Reiser"}, {"first" : "Javier Enrique", "last" : "Aguilar"}, {"first" : "Anneli", "last" : "Guthke"}, {"first" : "Paul-Christian", "last" : "Bürkner"} ], "note": "Related to: Reiser P., Aguilar J. E., Guthke A., & Bürkner P. C. (2023). Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. ArXiv preprint 2312.05153. arXiv: 2312.05153","abstract": "This code allows to replicate key experiments from our paper: Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference. For further details, please refer to the README.md.", "affiliation" : "Reiser, Philipp/Universität Stuttgart, Aguilar, Javier Enrique/TU Dortmund, Guthke, Anneli/Universität Stuttgart, Bürkner, Paul-Christian/TU Dortmund", "orcid-numbers" : "Reiser, Philipp/0000-0002-5553-1007, Guthke, Anneli/0000-0003-2901-1603, Bürkner, Paul-Christian/0000-0001-5765-8995", "doi" : "10.18419/darus-4093", "bibtexKey": "reiser2024replication" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2ecf8c87b4b9d1ebadb6af38afaaaef5c/testusersimtech", "tags" : [ "EXC2075","PN7","darus" ], "intraHash" : "ecf8c87b4b9d1ebadb6af38afaaaef5c", "interHash" : "f27086583ad6d368788a572f54d26155", "label" : "2023 CCN Time Window Project Code", "user" : "testusersimtech", "description" : "", "date" : "2024-07-03 10:45:48", "changeDate" : "2024-07-03 10:45:48", "count" : 4, "pub-type": "misc", "year": "2023", "url": "", "author": [ "René Sebastian Skukies" ], "authors": [ {"first" : "René Sebastian", "last" : "Skukies"} ], "note": "Related to: Skukies, R., & Ehinger, B. V. (2023). The effect of estimation time window length on overlap correction in EEG data (2023.06.05.543689). bioRxiv. doi: 10.1101/2023.06.05.543689","abstract": "Notebooks/ scripts used for the time window project done for our CCN contribution in 2023. The notebooks will simulate EEG data based on a known \"ground truth\" ERP and test whether the estimation length during ERP activity estimation will have an Influence on the results. To get a first impression why this is important please have a look at our online application: http://estimationwindow.ccn2023.s-ccs.de . Used notebooks can be found in \\PlutoNB; generally, the nb_CCN2023_unfoldEstimationWindow_exploration was used during actual project work. However, nb_CCN2023_unfoldEstimationWindow.jl is a cleaned-up version and more readable. To replicate the results simply open and run the notebook in question using Pluto.jl", "affiliation" : "Skukies, René/Universität Stuttgart", "orcid-numbers" : "Skukies, René/0000-0002-4124-4584", "doi" : "10.18419/darus-3635", "bibtexKey": "skukies2023window" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/29768defd15033d9f0dcf05136cf205e6/testusersimtech", "tags" : [ "EXC2075","PN7","darus" ], "intraHash" : "9768defd15033d9f0dcf05136cf205e6", "interHash" : "bdd0ba0fd06024e5606c28ad23efd3a9", "label" : "deepsysid: System Identification Toolkit for Multistep Prediction using Deep Learning", "user" : "testusersimtech", "description" : "", "date" : "2024-07-03 10:45:48", "changeDate" : "2024-07-03 10:45:48", "count" : 10, "pub-type": "misc", "year": "2023", "url": "", "author": [ "Alexandra Baier","Daniel Frank" ], "authors": [ {"first" : "Alexandra", "last" : "Baier"}, {"first" : "Daniel", "last" : "Frank"} ], "note": "Related to: Baier, Alexandra, Boukhers, Zeyd, & Staab, Steffen (2021). Hybrid Physics and Deep Learning Model for Interpretable Vehicle State Prediction. ArXiv, abs/2103.06727. arXiv: abs/2103.06727","abstract": "deepsysid is a system identification toolkit for multistep prediction using deep learning and hybrid methods. The toolkit is easy to use. After you follow the instructions in the README, you will be able to download a dataset, run hyperparameter optimization and identify your best-performing multistep prediction models with just three commands: deepsysid download 4dof-sim-ship, deepsysid session --enable-cuda progress.json NEW, deepsysid session --enable-cuda --reportin=progress.json progress.json TEST_BEST. The most current version of this software is available on GitHub.", "affiliation" : "Baier, Alexandra/Universität Stuttgart, Frank, Daniel/Universität Stuttgart", "orcid-numbers" : "Baier, Alexandra/0000-0001-5609-3400, Frank, Daniel/0000-0002-6730-2252", "doi" : "10.18419/darus-3455", "bibtexKey": "baier2023deepsysid" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/24b180f1c4f012df08a39d3011d211c56/testusersimtech", "tags" : [ "EXC2075","PN1","PN1-7","PN7" ], "intraHash" : "4b180f1c4f012df08a39d3011d211c56", "interHash" : "1f2f2a10f6694342f7187cbd68abbad9", "label" : "Advanced neural network architectures for continuum biomechanical simulation surrogates", "user" : "testusersimtech", "description" : "This is a student-thesis submitted within the bachelor program \"Informatik\".", "date" : "2024-06-21 15:02:15", "changeDate" : "2024-06-21 15:02:15", "count" : 5, "pub-type": "misc", "year": "2022", "url": "", "author": [ "David Lieb" ], "authors": [ {"first" : "David", "last" : "Lieb"} ], "editor": [ "David Rosin" ], "editors": [ {"first" : "David", "last" : "Rosin"} ], "abstract": "With more augmented reality (AR)/ devices around, real-time simulation on resource-\nrestricted devices has attracted considerable interest in recent years, and there is greater\ninterest in using them for things like medical visualization. There already exist simula-\ntion methods such as the Finte Element (FE) method for continuum-biomechanics, which\nis good for 3D simulation of soft tissue, but is very computationally expensive. In recent\nyears, sparse grid (SG) surrogates have been shown to allow real-time forward sim. using\ncontinuum-biomechanical data. Furthermore, a neural network (NN) surrogate has been\ntrained using data interpolated with the sparse grid for real-time vis. using such data. However, that proof-of-concept model is purely densely connected. This work aims to achieve the same or better performance with fewer parameters by a novel NN architecture. This work does so using a four-part model, consisting of densely connected, convolutional and locally connected layers, utilizing a point-cloud-to-voxel grid embedding for the convolutional neural network (CNN) to work. The main focus of this work has been on the process of finding and evaluating such a surrogate model. The use of CNN\u2019s locally connected layers helped to obtain a prescise and lightweight model. In addition, a sophisticated mapping procedure has been developed, to take advantage of a CNN\u2019s architecture into a point-cloud dataformat. The results demonstrated the effectiveness of this method. Depending on the hyperparameter configurations, the surrogate model was able to achieve frame rates of up to 2280 frames per second (fps) and a mean absolute error (mae) of 0.0082mm in the muscle surface coordinates. Furthermore, a notable reduction of trainable parameters, namely, from 43.9mio. to 104, 507 was possible, which is only 0.2% of the original value. The results also provided insight into the hyperparameter configurations that have the greatest impact on the model. In general,\nactivation functions and channel sizes exerted the most influence on model quality. High\nframe-rates also help reduce the energy consumption of mobile devices powered by batteries. Due to machine learning (ML) being a huge field, this work can\u2019t calim to have found the best solution. However, the current architecture improves upon the prove-of-concept in all desired areas. In the future, the model could be tested and executed on a mobile device or become part of a AR application with dynamic 3D objects.", "bibtexKey": "lieb2022advanced" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/2282e34503b589a170a466bb194f8bd00/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)" ], "intraHash" : "282e34503b589a170a466bb194f8bd00", "interHash" : "d3e28796b1b2f7fab0422bbe9fbaaa51", "label" : "On using Machine Learning Algorithms for Motorcycle Collision Detection", "user" : "testusersimtech", "description" : "", "date" : "2024-06-21 15:02:15", "changeDate" : "2024-06-21 15:02:15", "count" : 15, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Philipp Rodegast","Steffen Maier","Jonas Kneifl","Jörg Fehr" ], "authors": [ {"first" : "Philipp", "last" : "Rodegast"}, {"first" : "Steffen", "last" : "Maier"}, {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Jörg", "last" : "Fehr"} ], "eprint" : "2403.09491", "archiveprefix" : "arXiv", "primaryclass" : "cs.LG", "bibtexKey": "rodegast2024on" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/213c14040542fabfca71c9091d9b15464/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)","preprint","selected" ], "intraHash" : "13c14040542fabfca71c9091d9b15464", "interHash" : "a4b40872f8bc5d4e0941f5adc45e5c5a", "label" : "Multi-Hierarchical Surrogate Learning for Structural Dynamical Crash Simulations Using Graph Convolutional Neural Networks", "user" : "testusersimtech", "description" : "", "date" : "2024-06-21 15:02:15", "changeDate" : "2024-06-21 15:02:15", "count" : 5, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Jonas Kneifl","Jörg Fehr","Steven L. Brunton","J. Nathan Kutz" ], "authors": [ {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Jörg", "last" : "Fehr"}, {"first" : "Steven L.", "last" : "Brunton"}, {"first" : "J. Nathan", "last" : "Kutz"} ], "eprint" : "2402.09234", "archiveprefix" : "arXiv", "primaryclass" : "cs.LG", "bibtexKey": "kneifl2024multihierarchical" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/29e9493e187992dff40d589c09b080f39/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)","selected" ], "intraHash" : "9e9493e187992dff40d589c09b080f39", "interHash" : "b1c2b84e1cf4be479bb3b4fac22141c1", "label" : "Crash Simulations of a Racing Kart's Structural Frame Colliding against a Rigid Wall", "user" : "testusersimtech", "description" : "", "date" : "2024-06-21 15:02:15", "changeDate" : "2024-06-21 15:02:15", "count" : 9, "pub-type": "dataset", "publisher":"DaRUS", "year": "2023", "url": "https://darus.uni-stuttgart.de/citation?persistentId=doi:10.18419/darus-3789", "author": [ "Jonas Kneifl","Jörg Fehr" ], "authors": [ {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Jörg", "last" : "Fehr"} ], "doi" : "10.18419/DARUS-3789", "bibtexKey": "https://doi.org/10.18419/darus-3789" } , { "type" : "Publication", "id" : "https://puma.ub.uni-stuttgart.de/bibtex/27ef94ad9cb0a61cdbbca14f758d53c1d/testusersimtech", "tags" : [ "EXC2075","PN7","PN7-6(II)" ], "intraHash" : "7ef94ad9cb0a61cdbbca14f758d53c1d", "interHash" : "18fefd43044d37272b652a08cb13459e", "label" : "VENI, VINDy, VICI: a variational reduced-order modeling framework with uncertainty quantification", "user" : "testusersimtech", "description" : "", "date" : "2024-06-21 15:02:15", "changeDate" : "2024-06-21 15:02:15", "count" : 6, "pub-type": "misc", "year": "2024", "url": "", "author": [ "Paolo Conti","Jonas Kneifl","Andrea Manzoni","Attilio Frangi","Jörg Fehr","Steven L. Brunton","J. Nathan Kutz" ], "authors": [ {"first" : "Paolo", "last" : "Conti"}, {"first" : "Jonas", "last" : "Kneifl"}, {"first" : "Andrea", "last" : "Manzoni"}, {"first" : "Attilio", "last" : "Frangi"}, {"first" : "Jörg", "last" : "Fehr"}, {"first" : "Steven L.", "last" : "Brunton"}, {"first" : "J. Nathan", "last" : "Kutz"} ], "eprint" : "2405.20905", "archiveprefix" : "arXiv", "primaryclass" : "cs.LG", "bibtexKey": "conti2024veni" } ] }