[{"language":[{"iso":"eng"}],"article_number":"106606","doi":"10.1016/j.jaerosci.2025.106606","author":[{"first_name":"Torben N.","last_name":"Rüther","full_name":"Rüther, Torben N."},{"full_name":"Rasche, David B.","last_name":"Rasche","first_name":"David B."},{"id":"464","full_name":"Schmid, Hans-Joachim","last_name":"Schmid","first_name":"Hans-Joachim","orcid":"000-0001-8590-1921"}],"publication_identifier":{"issn":["0021-8502"]},"title":"The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data","year":"2025","intvolume":"       188","article_type":"original","date_updated":"2025-08-25T16:17:49Z","publication_status":"published","date_created":"2025-08-25T16:10:18Z","keyword":["POCS","Projection onto convex sets","Data inversion","2D distribution","CDMA","Centrifugal Differential Mobility Analyzer"],"type":"journal_article","publication":"Journal of Aerosol Science","funded_apc":"1","_id":"61013","publisher":"Elsevier BV","volume":188,"user_id":"464","status":"public","citation":{"ieee":"T. N. Rüther, D. B. Rasche, and H.-J. Schmid, “The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data,” <i>Journal of Aerosol Science</i>, vol. 188, Art. no. 106606, 2025, doi: <a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">10.1016/j.jaerosci.2025.106606</a>.","apa":"Rüther, T. N., Rasche, D. B., &#38; Schmid, H.-J. (2025). The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data. <i>Journal of Aerosol Science</i>, <i>188</i>, Article 106606. <a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">https://doi.org/10.1016/j.jaerosci.2025.106606</a>","short":"T.N. Rüther, D.B. Rasche, H.-J. Schmid, Journal of Aerosol Science 188 (2025).","chicago":"Rüther, Torben N., David B. Rasche, and Hans-Joachim Schmid. “The POCS-Algorithm—An Effective Tool for Calculating 2D Particle Property Distributions via Data Inversion of Exemplary CDMA Measurement Data.” <i>Journal of Aerosol Science</i> 188 (2025). <a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">https://doi.org/10.1016/j.jaerosci.2025.106606</a>.","mla":"Rüther, Torben N., et al. “The POCS-Algorithm—An Effective Tool for Calculating 2D Particle Property Distributions via Data Inversion of Exemplary CDMA Measurement Data.” <i>Journal of Aerosol Science</i>, vol. 188, 106606, Elsevier BV, 2025, doi:<a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">10.1016/j.jaerosci.2025.106606</a>.","bibtex":"@article{Rüther_Rasche_Schmid_2025, title={The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data}, volume={188}, DOI={<a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">10.1016/j.jaerosci.2025.106606</a>}, number={106606}, journal={Journal of Aerosol Science}, publisher={Elsevier BV}, author={Rüther, Torben N. and Rasche, David B. and Schmid, Hans-Joachim}, year={2025} }","ama":"Rüther TN, Rasche DB, Schmid H-J. The POCS-Algorithm—An effective tool for calculating 2D particle property distributions via data inversion of exemplary CDMA measurement data. <i>Journal of Aerosol Science</i>. 2025;188. doi:<a href=\"https://doi.org/10.1016/j.jaerosci.2025.106606\">10.1016/j.jaerosci.2025.106606</a>"},"quality_controlled":"1"},{"department":[{"_id":"151"}],"type":"research_data","keyword":["bushing","experimental data","rubber-metal-bushing","Dataset suspension"],"date_created":"2026-03-11T10:22:01Z","abstract":[{"lang":"eng","text":"This dataset contains experimental measurements of the radial dynamic and quasi-static characteristics of four different types of Rubber-Metal Bushings (RMBs) used in the suspension system of a passenger car under harmonic displacement excitation. For each bushing type, 2–3 individual specimens were tested.\r\n \r\nQuasi-static measurements were performed at a constant excitation frequency of 0.05 Hz with varying displacement amplitudes. Dynamic measurements were conducted with displacement amplitudes ranging from 0.04 mm to 0.3 mm and excitation frequencies of 2, 5, 10, ..., up to 100 Hz.\r\n\r\nThe data is structured by bushing type, measurement mode, amplitude, and frequency, and is provided in *.csv  and *.hrm format. It is intended to support further research in modeling rubber-metal bushings and parameter identification techniques."}],"citation":{"ama":"Schütte J. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University; 2025. doi:<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>","bibtex":"@book{Schütte_2025, title={Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation}, DOI={<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>}, publisher={LibreCat University}, author={Schütte, Jan}, year={2025} }","mla":"Schütte, Jan. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025, doi:<a href=\"https://doi.org/10.5281/ZENODO.14851317\">10.5281/ZENODO.14851317</a>.","short":"J. Schütte, Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation, LibreCat University, 2025.","chicago":"Schütte, Jan. <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025. <a href=\"https://doi.org/10.5281/ZENODO.14851317\">https://doi.org/10.5281/ZENODO.14851317</a>.","apa":"Schütte, J. (2025). <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University. <a href=\"https://doi.org/10.5281/ZENODO.14851317\">https://doi.org/10.5281/ZENODO.14851317</a>","ieee":"J. Schütte, <i>Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation</i>. LibreCat University, 2025."},"doi":"10.5281/ZENODO.14851317","user_id":"22109","_id":"64894","publisher":"LibreCat University","date_updated":"2026-03-11T10:25:23Z","author":[{"id":"22109","full_name":"Schütte, Jan","orcid":"0000-0001-9025-9742","first_name":"Jan","last_name":"Schütte"}],"title":"Experimental Dataset: Force and Displacement Measurements of Four Rubber-Metal Bushing Types from a Passenger Car under Harmonic Displacement Excitation","status":"public","year":"2025"},{"type":"conference","keyword":["extreme learning machines","partial differential equations","data-driven prediction","high-dimensional systems"],"date_created":"2024-04-30T08:43:14Z","abstract":[{"text":"We utilize extreme learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individually using a single model. Despite requiring only few data points (in some cases, our method can learn from a single full-state snapshot), it still achieves high accuracy and can predict the flow of PDEs over long time horizons. Moreover, we show how additional symmetries can be exploited to increase sample efficiency and to enforce equivariance.","lang":"eng"}],"publication":"Systems theory in data and optimization","doi":"10.1007/978-3-031-83191-1_10","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2404.18530"}],"date_updated":"2026-10-01T11:39:19Z","publication_status":"published","author":[{"first_name":"Hans","last_name":"Harder","full_name":"Harder, Hans","id":"98879"},{"id":"47427","full_name":"Peitz, Sebastian","orcid":"0000-0002-3389-793X","last_name":"Peitz","first_name":"Sebastian"}],"publication_identifier":{"isbn":["978-3-031-83191-1"]},"title":"Solving partial differential equations with equivariant extreme learning machines","year":"2025","oa":"1","place":"Cham","citation":{"ama":"Harder H, Peitz S. Solving partial differential equations with equivariant extreme learning machines. In: Berberich J, Ianelli A, Allgöwer F, eds. <i>Systems Theory in Data and Optimization</i>. Springer; 2025:153-168. doi:<a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">10.1007/978-3-031-83191-1_10</a>","bibtex":"@inproceedings{Harder_Peitz_2025, place={Cham}, title={Solving partial differential equations with equivariant extreme learning machines}, DOI={<a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">10.1007/978-3-031-83191-1_10</a>}, booktitle={Systems theory in data and optimization}, publisher={Springer}, author={Harder, Hans and Peitz, Sebastian}, editor={Berberich, J. and Ianelli, A. and Allgöwer, F.}, year={2025}, pages={153–168} }","mla":"Harder, Hans, and Sebastian Peitz. “Solving Partial Differential Equations with Equivariant Extreme Learning Machines.” <i>Systems Theory in Data and Optimization</i>, edited by J. Berberich et al., Springer, 2025, pp. 153–68, doi:<a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">10.1007/978-3-031-83191-1_10</a>.","chicago":"Harder, Hans, and Sebastian Peitz. “Solving Partial Differential Equations with Equivariant Extreme Learning Machines.” In <i>Systems Theory in Data and Optimization</i>, edited by J. Berberich, A. Ianelli, and F. Allgöwer, 153–68. Cham: Springer, 2025. <a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">https://doi.org/10.1007/978-3-031-83191-1_10</a>.","short":"H. Harder, S. Peitz, in: J. Berberich, A. Ianelli, F. Allgöwer (Eds.), Systems Theory in Data and Optimization, Springer, Cham, 2025, pp. 153–168.","apa":"Harder, H., &#38; Peitz, S. (2025). Solving partial differential equations with equivariant extreme learning machines. In J. Berberich, A. Ianelli, &#38; F. Allgöwer (Eds.), <i>Systems theory in data and optimization</i> (pp. 153–168). Springer. <a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">https://doi.org/10.1007/978-3-031-83191-1_10</a>","ieee":"H. Harder and S. Peitz, “Solving partial differential equations with equivariant extreme learning machines,” in <i>Systems theory in data and optimization</i>, 2025, pp. 153–168, doi: <a href=\"https://doi.org/10.1007/978-3-031-83191-1_10\">10.1007/978-3-031-83191-1_10</a>."},"editor":[{"full_name":"Berberich, J.","last_name":"Berberich","first_name":"J."},{"last_name":"Ianelli","first_name":"A.","full_name":"Ianelli, A."},{"first_name":"F.","last_name":"Allgöwer","full_name":"Allgöwer, F."}],"user_id":"47427","_id":"53793","publisher":"Springer","page":"153-168","status":"public"},{"year":"2024","status":"public","title":"Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment","conference":{"location":"Stockholm, Schweden","name":"2024 Prognostics and System Health Management Conference (PHM)","start_date":"2024-05-28","end_date":"2024-05-31"},"author":[{"last_name":"Bender","first_name":"Amelie","full_name":"Bender, Amelie","id":"54290"},{"id":"9557","full_name":"Aimiyekagbon, Osarenren Kennedy","first_name":"Osarenren Kennedy","last_name":"Aimiyekagbon"},{"full_name":"Sextro, Walter","first_name":"Walter","last_name":"Sextro","id":"21220"}],"publication_identifier":{"isbn":["979-8-3503-6058-5"]},"date_updated":"2024-07-22T09:29:26Z","language":[{"iso":"eng"}],"_id":"55336","publisher":"IEEE Computer Society","doi":"10.1109/PHM61473.2024.00038","user_id":"54290","publication":"Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)","citation":{"mla":"Bender, Amelie, et al. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>, IEEE Computer Society, 2024, doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","ama":"Bender A, Aimiyekagbon OK, Sextro W. Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. In: <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society; 2024. doi:<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>","bibtex":"@inproceedings{Bender_Aimiyekagbon_Sextro_2024, title={Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment}, DOI={<a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>}, booktitle={Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)}, publisher={IEEE Computer Society}, author={Bender, Amelie and Aimiyekagbon, Osarenren Kennedy and Sextro, Walter}, year={2024} }","apa":"Bender, A., Aimiyekagbon, O. K., &#38; Sextro, W. (2024). Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment. <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>","ieee":"A. Bender, O. K. Aimiyekagbon, and W. Sextro, “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment,” presented at the 2024 Prognostics and System Health Management Conference (PHM), Stockholm, Schweden, 2024, doi: <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">10.1109/PHM61473.2024.00038</a>.","chicago":"Bender, Amelie, Osarenren Kennedy Aimiyekagbon, and Walter Sextro. “Diagnostics and Prognostics for Retrofitted Systems: A Comprehensive Approach for Enhanced System Health Assessment.” In <i>Proceedings of the 2024 Prognostics and System Health Management Conference (PHM)</i>. IEEE Computer Society, 2024. <a href=\"https://doi.org/10.1109/PHM61473.2024.00038\">https://doi.org/10.1109/PHM61473.2024.00038</a>.","short":"A. Bender, O.K. Aimiyekagbon, W. Sextro, in: Proceedings of the 2024 Prognostics and System Health Management Conference (PHM), IEEE Computer Society, 2024."},"abstract":[{"lang":"eng","text":"Predicting the remaining useful life of technical \r\nsystems has gained significant attention in recent years due to \r\nincreasing demands for extending the lifespan of degrading system \r\ncomponents. Therefore, already used systems are retrofitted by \r\nintegrating sensors to monitor their performance and \r\nfunctionality, enabling accurate diagnosis of their condition and \r\nprediction of their remaining useful life. One of the main \r\nchallenges in this field is identified in the missing data from the \r\ntime where the retrofitted system has already run but without \r\nbeing monitored by sensors. In this paper, a novel approach for \r\nthe combined diagnostics and prognostics of retrofitted systems is \r\nproposed. The methodology aims to provide an accurate diagnosis \r\nof the system’s health state and estimation of the remaining useful \r\nlife by a combination of a machine learning and expert knowledge. \r\nTo evaluate the effectiveness of the proposed methodology, a case \r\nstudy involving a retrofitted system in an industrial setting is \r\nselected and applied. It is demonstrated that the approach \r\neffectively diagnose the current system’s health state and \r\naccurately predict its remaining useful life, thereby enabling \r\npredictive maintenance and decision-making. Overall, our \r\nresearch contributes to advancing the field of condition \r\nmonitoring for retrofitted systems by providing a comprehensive \r\nmethodology that addresses the challenge of missing data."}],"quality_controlled":"1","date_created":"2024-07-22T09:27:57Z","keyword":["retrofit","diagnosis","prognostics","RUL prediction","missing data","ball bearings"],"type":"conference","department":[{"_id":"151"}]},{"date_created":"2024-09-17T09:56:43Z","type":"conference","keyword":["Data Driven Design","Design Automation","Systems Engineering (SE)","Artificial Intelligence (AI)"],"publication":"DS 130: Proceedings of NordDesign 2024","related_material":{"link":[{"url":"https://www.designsociety.org/publication/47658/Towards+Automated+Design%3A+Automatically+Generating+Modeling+Elements+with+Prompt+Engineering+and+Generative+Artificial+Intelligence","relation":"confirmation"}]},"abstract":[{"text":"Developing Intelligent Technical Systems (ITS) involves a complex process encompassing planning, analysis, design, production, and maintenance. Model-Based Systems Engineering (MBSE) is a key methodology for systematic systems engineering. Designing models for ITS requires harmonious interaction of various elements, posing a challenge in MBSE. Leveraging Generative Artificial Intelligence, we generated a dataset for modeling, using prompt engineering on large language models. The generated artifacts can aid engineers in MBSE design or serve as synthetic training data for AI assistants.","lang":"eng"}],"language":[{"iso":"eng"}],"doi":"10.35199/NORDDESIGN2024.66","author":[{"full_name":"Kulkarni, Pranav Jayant","first_name":"Pranav Jayant","last_name":"Kulkarni","id":"86782"},{"id":"44458","last_name":"Tissen","first_name":"Denis","full_name":"Tissen, Denis"},{"id":"36312","full_name":"Bernijazov, Ruslan","first_name":"Ruslan","last_name":"Bernijazov"},{"id":"16190","last_name":"Dumitrescu","first_name":"Roman","full_name":"Dumitrescu, Roman"}],"publication_identifier":{"unknown":["978-1-912254-21-7"]},"year":"2024","title":"Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence","publication_status":"epub_ahead","date_updated":"2024-09-17T09:57:07Z","citation":{"ieee":"P. J. Kulkarni, D. Tissen, R. Bernijazov, and R. Dumitrescu, “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence,” in <i>DS 130: Proceedings of NordDesign 2024</i>, Reykjavik, 2024, pp. 617–625, doi: <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","apa":"Kulkarni, P. J., Tissen, D., Bernijazov, R., &#38; Dumitrescu, R. (2024). Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, &#38; O. Isaksson (Eds.), <i>DS 130: Proceedings of NordDesign 2024</i> (pp. 617–625). <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>","mla":"Kulkarni, Pranav Jayant, et al. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist et al., 2024, pp. 617–25, doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>.","bibtex":"@inproceedings{Kulkarni_Tissen_Bernijazov_Dumitrescu_2024, title={Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence}, DOI={<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>}, booktitle={DS 130: Proceedings of NordDesign 2024}, author={Kulkarni, Pranav Jayant and Tissen, Denis and Bernijazov, Ruslan and Dumitrescu, Roman}, editor={Malmqvist, J. and Candi, M. and Saemundsson, R. and Bystrom, F. and Isaksson, O.}, year={2024}, pages={617–625} }","ama":"Kulkarni PJ, Tissen D, Bernijazov R, Dumitrescu R. Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence. In: Malmqvist J, Candi M, Saemundsson R, Bystrom F, Isaksson O, eds. <i>DS 130: Proceedings of NordDesign 2024</i>. ; 2024:617-625. doi:<a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">10.35199/NORDDESIGN2024.66</a>","short":"P.J. Kulkarni, D. Tissen, R. Bernijazov, R. Dumitrescu, in: J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, O. Isaksson (Eds.), DS 130: Proceedings of NordDesign 2024, 2024, pp. 617–625.","chicago":"Kulkarni, Pranav Jayant, Denis Tissen, Ruslan Bernijazov, and Roman Dumitrescu. “Towards Automated Design: Automatically Generating Modeling Elements with Prompt Engineering and Generative Artificial Intelligence.” In <i>DS 130: Proceedings of NordDesign 2024</i>, edited by J. Malmqvist, M. Candi, R. Saemundsson, F. Bystrom, and O. Isaksson, 617–25, 2024. <a href=\"https://doi.org/10.35199/NORDDESIGN2024.66\">https://doi.org/10.35199/NORDDESIGN2024.66</a>."},"_id":"56166","page":"617-625","editor":[{"last_name":"Malmqvist","first_name":"J.","full_name":"Malmqvist, J."},{"full_name":"Candi, M.","last_name":"Candi","first_name":"M."},{"first_name":"R.","last_name":"Saemundsson","full_name":"Saemundsson, R."},{"last_name":"Bystrom","first_name":"F.","full_name":"Bystrom, F."},{"first_name":"O.","last_name":"Isaksson","full_name":"Isaksson, O."}],"user_id":"86782","conference":{"end_date":"2024-08-14","start_date":"2024-08-12","name":"NordDesign Conference 2024","location":"Reykjavik"},"status":"public"},{"citation":{"ieee":"J. Gerritzen, A. Hornig, P. Winkler, and M. Gude, “Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning,” in <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, 2024, vol. 3, pp. 1252–1259, doi: <a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>.","mla":"Gerritzen, Johannes, et al. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, vol. 3, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259, doi:<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>.","apa":"Gerritzen, J., Hornig, A., Winkler, P., &#38; Gude, M. (2024). Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, <i>3</i>, 1252–1259. <a href=\"https://doi.org/10.60691/yj56-np80\">https://doi.org/10.60691/yj56-np80</a>","bibtex":"@inproceedings{Gerritzen_Hornig_Winkler_Gude_2024, title={Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning}, volume={3}, DOI={<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>}, booktitle={ECCM21 - Proceedings of the 21st European Conference on Composite Materials}, publisher={European Society for Composite Materials (ESCM)}, author={Gerritzen, Johannes and Hornig, Andreas and Winkler, Peter and Gude, Maik}, year={2024}, pages={1252–1259} }","chicago":"Gerritzen, Johannes, Andreas Hornig, Peter Winkler, and Maik Gude. “Direct Parameter Identification for Highly Nonlinear Strain Rate Dependent Constitutive Models Using Machine Learning.” In <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>, 3:1252–1259. European Society for Composite Materials (ESCM), 2024. <a href=\"https://doi.org/10.60691/yj56-np80\">https://doi.org/10.60691/yj56-np80</a>.","short":"J. Gerritzen, A. Hornig, P. Winkler, M. Gude, in: ECCM21 - Proceedings of the 21st European Conference on Composite Materials, European Society for Composite Materials (ESCM), 2024, pp. 1252–1259.","ama":"Gerritzen J, Hornig A, Winkler P, Gude M. Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning. In: <i>ECCM21 - Proceedings of the 21st European Conference on Composite Materials</i>. Vol 3. European Society for Composite Materials (ESCM); 2024:1252–1259. doi:<a href=\"https://doi.org/10.60691/yj56-np80\">10.60691/yj56-np80</a>"},"project":[{"name":"TRR 285:  Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten","_id":"130"},{"name":"TRR 285 - Subproject A03","_id":"137"},{"_id":"131","name":"TRR 285 - Project Area A"}],"_id":"62078","publisher":"European Society for Composite Materials (ESCM)","page":"1252–1259","volume":3,"user_id":"105344","status":"public","date_created":"2025-11-04T12:47:06Z","keyword":["Direct parameter identification","Machine learning","Convolutional neural networks","Strain rate dependency","Fiber reinforced plastics","woven composites","segmentation","synthetic training data","x-ray computed tomography"],"type":"conference","publication":"ECCM21 - Proceedings of the 21st European Conference on Composite Materials","abstract":[{"lang":"eng","text":"Fiber reinforced plastics (FRP) exhibit strongly non-linear deformation behavior. To capture this in simulations, intricate models with a variety of parameters are typically used. The identification of values for such parameters is highly challenging and requires in depth understanding of the model itself. Machine learning (ML) is a promising approach for alleviating this challenge by directly predicting parameters based on experimental results. So far, this works mostly for purely artificial data. In this work, two approaches to generalize to experimental data are investigated: a sequential approach, leveraging understanding of the constitutive model and a direct, purely data driven approach. This is exemplary carried out for a highly non-linear strain rate dependent constitutive model for the shear behavior of FRP.The sequential model is found to work better on both artificial and experimental data. It is capable of extracting well suited parameters from the artificial data under realistic conditions. For the experimental data, the model performance depends on the composition of the experimental curves, varying between excellently suiting and reasonable predictions. Taking the expert knowledge into account for ML-model training led to far better results than the purely data driven approach. Robustifying the model predictions on experimental data promises further improvement. "}],"language":[{"iso":"eng"}],"doi":"10.60691/yj56-np80","author":[{"full_name":"Gerritzen, Johannes","last_name":"Gerritzen","first_name":"Johannes","orcid":"0000-0002-0169-8602","id":"105344"},{"last_name":"Hornig","first_name":"Andreas","full_name":"Hornig, Andreas"},{"first_name":"Peter","last_name":"Winkler","full_name":"Winkler, Peter"},{"full_name":"Gude, Maik","last_name":"Gude","first_name":"Maik"}],"publication_identifier":{"isbn":["978-2-912985-01-9"]},"title":"Direct parameter identification for highly nonlinear strain rate dependent constitutive models using machine learning","year":"2024","intvolume":"         3","date_updated":"2026-02-27T06:46:21Z"},{"ddc":["006"],"user_id":"88024","_id":"52235","has_accepted_license":"1","conference":{"end_date":"2024-04-15","location":"Lisbon, Portugal","name":"11th International Conference on Mobile Software Engineering and Systems 2024","start_date":"2024-04-14"},"status":"public","external_id":{"arxiv":["2402.07889"]},"citation":{"ama":"Khedkar M, Bodden E. Toward an Android Static Analysis Approach for Data Protection. In: <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i> ; 2024. doi:<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>","bibtex":"@inproceedings{Khedkar_Bodden_2024, title={Toward an Android Static Analysis Approach for Data Protection}, DOI={<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>}, booktitle={Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.}, author={Khedkar, Mugdha and Bodden, Eric}, year={2024} }","mla":"Khedkar, Mugdha, and Eric Bodden. “Toward an Android Static Analysis Approach for Data Protection.” <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2024, doi:<a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>.","chicago":"Khedkar, Mugdha, and Eric Bodden. “Toward an Android Static Analysis Approach for Data Protection.” In <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i>, 2024. <a href=\"https://doi.org/10.1145/3647632.3651389\">https://doi.org/10.1145/3647632.3651389</a>.","short":"M. Khedkar, E. Bodden, in: Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68., 2024.","apa":"Khedkar, M., &#38; Bodden, E. (2024). Toward an Android Static Analysis Approach for Data Protection. <i>Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft ’24). Association for Computing Machinery, New York, NY, USA, 65–68.</i> 11th International Conference on Mobile Software Engineering and Systems 2024, Lisbon, Portugal. <a href=\"https://doi.org/10.1145/3647632.3651389\">https://doi.org/10.1145/3647632.3651389</a>","ieee":"M. Khedkar and E. Bodden, “Toward an Android Static Analysis Approach for Data Protection,” presented at the 11th International Conference on Mobile Software Engineering and Systems 2024, Lisbon, Portugal, 2024, doi: <a href=\"https://doi.org/10.1145/3647632.3651389\">10.1145/3647632.3651389</a>."},"file_date_updated":"2024-03-03T14:39:08Z","doi":"10.1145/3647632.3651389","language":[{"iso":"eng"}],"date_updated":"2026-03-04T08:11:48Z","author":[{"id":"88024","full_name":"Khedkar, Mugdha","first_name":"Mugdha","last_name":"Khedkar"},{"id":"59256","full_name":"Bodden, Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden","first_name":"Eric"}],"year":"2024","title":"Toward an Android Static Analysis Approach for Data Protection","department":[{"_id":"76"}],"type":"conference","keyword":["static program analysis","data protection and privacy","GDPR compliance"],"date_created":"2024-03-03T14:37:53Z","file":[{"creator":"khedkarm","date_created":"2024-03-03T14:39:08Z","access_level":"closed","file_size":530812,"file_name":"2402.07889v1.pdf","date_updated":"2024-03-03T14:39:08Z","relation":"main_file","content_type":"application/pdf","success":1,"file_id":"52236"}],"abstract":[{"text":"Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). Since app developers are not legal experts, they find it difficult to write privacy-aware source code. Moreover, they have limited tool support to reason about data protection throughout their app development process.\r\nThis paper motivates the need for a static analysis approach to diagnose and explain data protection in Android apps. The analysis will recognize personal data sources in the source code, and aims to further examine the data flow originating from these sources. App developers can then address key questions about data manipulation, derived data, and the presence of technical measures. Despite challenges, we explore to what extent one can realize this analysis through static taint analysis, a common method for identifying security vulnerabilities. This is a first step towards designing a tool-based approach that aids app developers and assessors in ensuring data protection in Android apps, based on automated static program analysis. ","lang":"eng"}],"publication":"Proceedings of the IEEE/ACM 11th International Conference on Mobile Software Engineering and Systems (MOBILESoft '24). Association for Computing Machinery, New York, NY, USA, 65–68."},{"citation":{"mla":"Werning, Alexander, and Reinhold Haeb-Umbach. “Target-Specific Dataset Pruning for Compression of Audio Tagging Models.” <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>, 2024.","ama":"Werning A, Haeb-Umbach R. Target-Specific Dataset Pruning for Compression of Audio Tagging Models. In: <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>. ; 2024.","bibtex":"@inproceedings{Werning_Haeb-Umbach_2024, title={Target-Specific Dataset Pruning for Compression of Audio Tagging Models}, booktitle={32nd European Signal Processing Conference (EUSIPCO 2024)}, author={Werning, Alexander and Haeb-Umbach, Reinhold}, year={2024} }","apa":"Werning, A., &#38; Haeb-Umbach, R. (2024). Target-Specific Dataset Pruning for Compression of Audio Tagging Models. <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>. 32nd European Signal Processing Conference, Lyon.","ieee":"A. Werning and R. Haeb-Umbach, “Target-Specific Dataset Pruning for Compression of Audio Tagging Models,” presented at the 32nd European Signal Processing Conference, Lyon, 2024.","chicago":"Werning, Alexander, and Reinhold Haeb-Umbach. “Target-Specific Dataset Pruning for Compression of Audio Tagging Models.” In <i>32nd European Signal Processing Conference (EUSIPCO 2024)</i>, 2024.","short":"A. Werning, R. Haeb-Umbach, in: 32nd European Signal Processing Conference (EUSIPCO 2024), 2024."},"file_date_updated":"2024-11-18T12:10:09Z","project":[{"_id":"512","name":"WestAI - AI Service Center West"}],"quality_controlled":"1","conference":{"name":"32nd European Signal Processing Conference","location":"Lyon"},"status":"public","has_accepted_license":"1","_id":"57160","ddc":["000"],"user_id":"62152","publication":"32nd European Signal Processing Conference (EUSIPCO 2024)","abstract":[{"text":"Large audio tagging models are usually trained or pre-trained on AudioSet, a dataset that encompasses a large amount of different sound classes and acoustic environments. Knowledge distillation has emerged as a method to compress such models without compromising their effectiveness. There are many different applications for audio tagging, some of which require a specialization to a narrow domain of sounds to be classified. For these scenarios, it is beneficial to distill the large audio tagger with respect to a specific subset of sounds of interest. A method to prune a general dataset with respect to a target dataset is presented. By distilling with such a specialized pruned dataset, we obtain a compressed model with better classification accuracy in the specific target domain than with target-agnostic distillation.","lang":"eng"}],"date_created":"2024-11-18T09:29:16Z","file":[{"date_created":"2024-11-18T12:10:09Z","creator":"awerning","file_id":"57200","content_type":"application/pdf","success":1,"file_name":"Eusipco__Target_specific_Dataset_Pruning_for_Compression_of_Audio_Tagging_Models.pdf","access_level":"closed","file_size":183539,"relation":"main_file","date_updated":"2024-11-18T12:10:09Z"}],"department":[{"_id":"54"}],"keyword":["data pruning","knowledge distillation","audio tagging"],"type":"conference","author":[{"id":"62152","full_name":"Werning, Alexander","last_name":"Werning","first_name":"Alexander"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}],"year":"2024","title":"Target-Specific Dataset Pruning for Compression of Audio Tagging Models","date_updated":"2025-11-28T13:22:00Z","language":[{"iso":"eng"}]},{"author":[{"first_name":"Osarenren","last_name":"Aimiyekagbon","full_name":"Aimiyekagbon, Osarenren","id":"9557"}],"year":"2024","title":"Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions","status":"public","date_updated":"2026-09-30T08:15:51Z","publisher":"Zenodo","_id":"67245","user_id":"40298","doi":"10.5281/ZENODO.10805042","citation":{"chicago":"Aimiyekagbon, Osarenren. <i>Run-to-Failure Data Set of Ball Bearings Subjected to Time-Varying Load and Speed Conditions</i>. Zenodo, 2024. <a href=\"https://doi.org/10.5281/ZENODO.10805042\">https://doi.org/10.5281/ZENODO.10805042</a>.","short":"O. Aimiyekagbon, Run-to-Failure Data Set of Ball Bearings Subjected to Time-Varying Load and Speed Conditions, Zenodo, 2024.","apa":"Aimiyekagbon, O. (2024). <i>Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions</i>. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.10805042\">https://doi.org/10.5281/ZENODO.10805042</a>","ieee":"O. Aimiyekagbon, <i>Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions</i>. Zenodo, 2024.","ama":"Aimiyekagbon O. <i>Run-to-Failure Data Set of Ball Bearings Subjected to Time-Varying Load and Speed Conditions</i>. Zenodo; 2024. doi:<a href=\"https://doi.org/10.5281/ZENODO.10805042\">10.5281/ZENODO.10805042</a>","bibtex":"@book{Aimiyekagbon_2024, title={Run-to-failure data set of ball bearings subjected to time-varying load and speed conditions}, DOI={<a href=\"https://doi.org/10.5281/ZENODO.10805042\">10.5281/ZENODO.10805042</a>}, publisher={Zenodo}, author={Aimiyekagbon, Osarenren}, year={2024} }","mla":"Aimiyekagbon, Osarenren. <i>Run-to-Failure Data Set of Ball Bearings Subjected to Time-Varying Load and Speed Conditions</i>. Zenodo, 2024, doi:<a href=\"https://doi.org/10.5281/ZENODO.10805042\">10.5281/ZENODO.10805042</a>."},"abstract":[{"text":"This data set consist of experimental data collected during 17 run-to-failure experiments on ball bearings subjected to time-varying load and speed conditions. No defect was initiated in the bearings before the experiments. A detailed description file is enclosed.","lang":"eng"}],"date_created":"2026-09-23T11:45:02Z","department":[{"_id":"151"}],"type":"research_data","keyword":["Prognostics","Non-Stationary conditions","RUL","Run to failure data","Ball bearing","Varying conditions","Accelerated life tests","bearings"]},{"abstract":[{"lang":"eng","text":"Despite the widespread use of machine learning algorithms, their effectiveness is limited by a phenomenon known as algorithm aversion. Recent research concluded that unobserved variables can cause algorithm aversion. However, the impact of an unobserved variable on algorithm aversion remains unclear. Previous studies focused on situations where humans had more variables available than algorithms. We extend this research by conducting an online experiment with 94 participants, systematically varying the number of observable variables to the advisor and the advisor type. Surprisingly, our results did not confirm that an unobserved variable had a negative effect on advice-taking. Instead, we found a positive impact in an algorithm appreciation scenario. This study provides new insights into the paradoxical behavior in which people weigh advice more despite having fewer variables, as they correct for the advisor's errors. Practitioners should consider this behavior when designing algorithms and account for user correction behavior."}],"citation":{"mla":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” <i>Wirtschaftsinformatik Conference</i>, no. 19, 2023.","bibtex":"@inproceedings{Leffrang_2023, title={The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization}, number={19}, booktitle={Wirtschaftsinformatik Conference}, author={Leffrang, Dirk}, year={2023} }","ama":"Leffrang D. The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. In: <i>Wirtschaftsinformatik Conference</i>. ; 2023.","ieee":"D. Leffrang, “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization,” in <i>Wirtschaftsinformatik Conference</i>, Paderborn, 2023, no. 19.","apa":"Leffrang, D. (2023). The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization. <i>Wirtschaftsinformatik Conference</i>, <i>19</i>.","chicago":"Leffrang, Dirk. “The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization.” In <i>Wirtschaftsinformatik Conference</i>, 2023.","short":"D. Leffrang, in: Wirtschaftsinformatik Conference, 2023."},"issue":"19","publication":"Wirtschaftsinformatik Conference","department":[{"_id":"196"}],"keyword":["Algorithm aversion","Data","Decision-making","Advice-taking","Human-Computer Interaction"],"type":"conference","date_created":"2024-01-03T09:50:06Z","date_updated":"2024-01-10T09:53:24Z","conference":{"location":"Paderborn","name":"Wirtschaftsinformatik"},"author":[{"id":"51271","full_name":"Leffrang, Dirk","first_name":"Dirk","last_name":"Leffrang","orcid":"0000-0001-9004-2391"}],"year":"2023","status":"public","title":"The Broken Leg of Algorithm Appreciation: An Experimental Study on the Effect of Unobserved Variables on Advice Utilization","user_id":"51271","_id":"50118","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://aisel.aisnet.org/wi2023/19 "}]},{"publisher":"IEEE","_id":"52369","language":[{"iso":"eng"}],"user_id":"66731","doi":"10.1109/ictmod59086.2023.10438135","year":"2023","status":"public","title":"Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research","author":[{"id":"66731","full_name":"Fichtler, Timm","first_name":"Timm","last_name":"Fichtler","orcid":"https://orcid.org/0000-0001-6034-4399"},{"first_name":"Khoren","last_name":"Grigoryan","full_name":"Grigoryan, Khoren"},{"id":"43136","full_name":"Koldewey, Christian","first_name":"Christian","last_name":"Koldewey","orcid":"https://orcid.org/0000-0001-7992-6399"},{"full_name":"Dumitrescu, Roman","last_name":"Dumitrescu","first_name":"Roman","id":"16190"}],"conference":{"start_date":"2023-11-22","name":"IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","location":"Rabat, Morocco","end_date":"2023-11-24"},"publication_status":"published","date_updated":"2024-03-07T18:17:34Z","date_created":"2024-03-07T18:13:47Z","type":"conference","keyword":["Product Lifecyle Management (PLM)","Data Analytics","Data-driven Design","Engineering Management","Lifecycle Data"],"department":[{"_id":"563"}],"publication":"2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)","citation":{"ama":"Fichtler T, Grigoryan K, Koldewey C, Dumitrescu R. Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research. In: <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE; 2023. doi:<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>","bibtex":"@inproceedings{Fichtler_Grigoryan_Koldewey_Dumitrescu_2023, title={Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research}, DOI={<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>}, booktitle={2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}, publisher={IEEE}, author={Fichtler, Timm and Grigoryan, Khoren and Koldewey, Christian and Dumitrescu, Roman}, year={2023} }","mla":"Fichtler, Timm, et al. “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research.” <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>, IEEE, 2023, doi:<a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>.","chicago":"Fichtler, Timm, Khoren Grigoryan, Christian Koldewey, and Roman Dumitrescu. “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research.” In <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE, 2023. <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">https://doi.org/10.1109/ictmod59086.2023.10438135</a>.","short":"T. Fichtler, K. Grigoryan, C. Koldewey, R. Dumitrescu, in: 2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), IEEE, 2023.","apa":"Fichtler, T., Grigoryan, K., Koldewey, C., &#38; Dumitrescu, R. (2023). Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research. <i>2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)</i>. IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), Rabat, Morocco. <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">https://doi.org/10.1109/ictmod59086.2023.10438135</a>","ieee":"T. Fichtler, K. Grigoryan, C. Koldewey, and R. Dumitrescu, “Towards a Data-Driven Product Management – Concepts, Advantages, and Future Research,” presented at the IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), Rabat, Morocco, 2023, doi: <a href=\"https://doi.org/10.1109/ictmod59086.2023.10438135\">10.1109/ictmod59086.2023.10438135</a>."},"abstract":[{"text":"Megatrends, such as digitization or sustainability, are confronting the product management of manufacturing companies with a variety of challenges regarding the design of future products, but also the management of the actual products. To successfully position their products in the market, product managers need to gather and analyze comprehensive information about customers, developments in the products’ environment, product usage, and more. The digitization of all aspects of life is making data on these topics increasingly available – via social media, documents, or the internet of things from the products themselves. The systematic collection and analysis of these data enable the exploitation of new potentials for the adaption of existing products and the creation of the products of tomorrow. However, there are still no insights into the main concepts and cause-effect relationships in exploiting data-driven approaches for product management. Therefore, this paper aims to identify the main concepts and advantages of data-driven product management. To answer the corresponding research questions a comprehensive systematic literature review is conducted. From its results, a detailed description of the main concepts of data-driven product management is derived. Furthermore, a taxonomy for the advantages of data-driven product management is presented. The main concepts and the taxonomy allow for a deeper understanding of the topic while highlighting necessary future actions and research needs.","lang":"eng"}]},{"date_created":"2024-03-25T10:16:24Z","keyword":["synthetic training data","machine vision quality gates","deep learning","automated inspection and quality control","production control"],"type":"conference","department":[{"_id":"152"}],"publication":"Lectures","abstract":[{"text":"Manufacturing companies face the challenge of reaching required quality standards. Using\r\noptical sensors and deep learning might help. However, training deep learning algorithms\r\nrequire large amounts of visual training data. Using domain randomization to generate synthetic\r\nimage data can alleviate this bottleneck. This paper presents the application of synthetic\r\nimage training data for optical quality inspections using visual sensor technology. The results\r\nshow synthetically generated training data are appropriate for visual quality inspections.","lang":"eng"}],"language":[{"iso":"eng"}],"doi":"10.5162/smsi2023/d7.4","title":"Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing","year":"2023","author":[{"id":"47565","first_name":"Iris","orcid":"0000-0001-5765-971X","last_name":"Gräßler","full_name":"Gräßler, Iris"},{"id":"72252","first_name":"Michael","last_name":"Hieb","full_name":"Hieb, Michael"}],"publication_status":"published","date_updated":"2024-03-25T11:05:53Z","citation":{"mla":"Gräßler, Iris, and Michael Hieb. “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing.” <i>Lectures</i>, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524, doi:<a href=\"https://doi.org/10.5162/smsi2023/d7.4\">10.5162/smsi2023/d7.4</a>.","ama":"Gräßler I, Hieb M. Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. In: <i>Lectures</i>. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany; 2023:253-524. doi:<a href=\"https://doi.org/10.5162/smsi2023/d7.4\">10.5162/smsi2023/d7.4</a>","bibtex":"@inproceedings{Gräßler_Hieb_2023, title={Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing}, DOI={<a href=\"https://doi.org/10.5162/smsi2023/d7.4\">10.5162/smsi2023/d7.4</a>}, booktitle={Lectures}, publisher={AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany}, author={Gräßler, Iris and Hieb, Michael}, year={2023}, pages={253–524} }","apa":"Gräßler, I., &#38; Hieb, M. (2023). Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing. <i>Lectures</i>, 253–524. <a href=\"https://doi.org/10.5162/smsi2023/d7.4\">https://doi.org/10.5162/smsi2023/d7.4</a>","ieee":"I. Gräßler and M. Hieb, “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing,” in <i>Lectures</i>, Nuremberg, 2023, pp. 253–524, doi: <a href=\"https://doi.org/10.5162/smsi2023/d7.4\">10.5162/smsi2023/d7.4</a>.","short":"I. Gräßler, M. Hieb, in: Lectures, AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023, pp. 253–524.","chicago":"Gräßler, Iris, and Michael Hieb. “Creating Synthetic Training Datasets for Inspection in Machine Vision Quality Gates in Manufacturing.” In <i>Lectures</i>, 253–524. AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany, 2023. <a href=\"https://doi.org/10.5162/smsi2023/d7.4\">https://doi.org/10.5162/smsi2023/d7.4</a>."},"quality_controlled":"1","page":"253-524","publisher":"AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany","_id":"52816","user_id":"5905","status":"public","conference":{"end_date":"2023-05-11","start_date":"2023-05-08","name":"SMSI 2023. Sensor and Measurement Science International","location":"Nuremberg"}},{"oa":"1","department":[{"_id":"874"}],"type":"misc","keyword":["MEI","Edirom","Music Encoding Initiative","Linked Open Data","MELD"],"date_created":"2024-08-28T11:48:31Z","abstract":[{"lang":"eng","text":"This release covers the state of this prototype app at the end of the funding phase for the Paderborn University part of the Beethoven in the House project. It uses https://api.domestic-beethoven.eu/ld/BithCollection.jsonld as starting point for traversing the LOD graph, and reads data from the project pod available from https://bith.solidcommunity.net/public/bith.ttl (which has no content at the time of the release)."}],"citation":{"bibtex":"@book{Kepper_2023, title={DomesticBeethoven/bith-annotator: Release 2023-04}, DOI={<a href=\"https://doi.org/10.5281/ZENODO.7877741\">10.5281/ZENODO.7877741</a>}, publisher={Zenodo}, author={Kepper, Johannes}, year={2023} }","ama":"Kepper J. <i>DomesticBeethoven/Bith-Annotator: Release 2023-04</i>. Zenodo; 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.7877741\">10.5281/ZENODO.7877741</a>","mla":"Kepper, Johannes. <i>DomesticBeethoven/Bith-Annotator: Release 2023-04</i>. Zenodo, 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.7877741\">10.5281/ZENODO.7877741</a>.","chicago":"Kepper, Johannes. <i>DomesticBeethoven/Bith-Annotator: Release 2023-04</i>. Zenodo, 2023. <a href=\"https://doi.org/10.5281/ZENODO.7877741\">https://doi.org/10.5281/ZENODO.7877741</a>.","short":"J. Kepper, DomesticBeethoven/Bith-Annotator: Release 2023-04, Zenodo, 2023.","ieee":"J. Kepper, <i>DomesticBeethoven/bith-annotator: Release 2023-04</i>. Zenodo, 2023.","apa":"Kepper, J. (2023). <i>DomesticBeethoven/bith-annotator: Release 2023-04</i>. Zenodo. <a href=\"https://doi.org/10.5281/ZENODO.7877741\">https://doi.org/10.5281/ZENODO.7877741</a>"},"doi":"10.5281/ZENODO.7877741","user_id":"1684","_id":"55850","language":[{"iso":"eng"}],"publisher":"Zenodo","main_file_link":[{"open_access":"1","url":"https://zenodo.org/record/7877741"}],"date_updated":"2024-08-28T13:59:52Z","publication_status":"published","author":[{"full_name":"Kepper, Johannes","first_name":"Johannes","last_name":"Kepper"}],"title":"DomesticBeethoven/bith-annotator: Release 2023-04","status":"public","year":"2023"},{"status":"public","_id":"55833","page":"145–150","editor":[{"last_name":"Weigl","first_name":"David","full_name":"Weigl, David"},{"full_name":"Bain, Jennifer","first_name":"Jennifer","last_name":"Bain"},{"full_name":"Ang, Ailynn","first_name":"Ailynn","last_name":"Ang"}],"user_id":"1684","citation":{"apa":"Shibata, E., Lewis, D., Saccomano, M., Kepper, J., &#38; Page, K. (2023). A New Conceptual Model for Musical Sources and Musicological Studies. In D. Weigl, J. Bain, &#38; A. Ang (Eds.), <i>Proceedings of the Music Encoding Conference 2022</i> (pp. 145–150). <a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>","mla":"Shibata, Elisabete, et al. “A New Conceptual Model for Musical Sources and Musicological Studies.” <i>Proceedings of the Music Encoding Conference 2022</i>, edited by David Weigl et al., 2023, pp. 145–150, doi:<a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>.","ieee":"E. Shibata, D. Lewis, M. Saccomano, J. Kepper, and K. Page, “A New Conceptual Model for Musical Sources and Musicological Studies,” in <i>Proceedings of the Music Encoding Conference 2022</i>, 2023, pp. 145–150, doi: <a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>.","ama":"Shibata E, Lewis D, Saccomano M, Kepper J, Page K. A New Conceptual Model for Musical Sources and Musicological Studies. In: Weigl D, Bain J, Ang A, eds. <i>Proceedings of the Music Encoding Conference 2022</i>. ; 2023:145–150. doi:<a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>","short":"E. Shibata, D. Lewis, M. Saccomano, J. Kepper, K. Page, in: D. Weigl, J. Bain, A. Ang (Eds.), Proceedings of the Music Encoding Conference 2022, Halifax, Nova Scotia, Canada, 2023, pp. 145–150.","chicago":"Shibata, Elisabete, David Lewis, Mark Saccomano, Johannes Kepper, and Kevin Page. “A New Conceptual Model for Musical Sources and Musicological Studies.” In <i>Proceedings of the Music Encoding Conference 2022</i>, edited by David Weigl, Jennifer Bain, and Ailynn Ang, 145–150. Halifax, Nova Scotia, Canada, 2023. <a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>.","bibtex":"@inproceedings{Shibata_Lewis_Saccomano_Kepper_Page_2023, place={Halifax, Nova Scotia, Canada}, title={A New Conceptual Model for Musical Sources and Musicological Studies}, DOI={<a href=\"https://doi.org/10.17613/8p2c-1q77\">https://doi.org/10.17613/8p2c-1q77</a>}, booktitle={Proceedings of the Music Encoding Conference 2022}, author={Shibata, Elisabete and Lewis, David and Saccomano, Mark and Kepper, Johannes and Page, Kevin}, editor={Weigl, David and Bain, Jennifer and Ang, Ailynn}, year={2023}, pages={145–150} }"},"place":"Halifax, Nova Scotia, Canada","oa":"1","author":[{"first_name":"Elisabete","last_name":"Shibata","full_name":"Shibata, Elisabete"},{"first_name":"David","last_name":"Lewis","full_name":"Lewis, David"},{"last_name":"Saccomano","first_name":"Mark","full_name":"Saccomano, Mark"},{"first_name":"Johannes","orcid":"0000-0003-4891-260X","last_name":"Kepper","full_name":"Kepper, Johannes","id":"1684"},{"last_name":"Page","first_name":"Kevin","full_name":"Page, Kevin"}],"title":"A New Conceptual Model for Musical Sources and Musicological Studies","year":"2023","date_updated":"2024-08-28T14:12:33Z","publication_status":"published","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://hcommons.org/deposits/item/hc:59295/"}],"doi":"https://doi.org/10.17613/8p2c-1q77","publication":"Proceedings of the Music Encoding Conference 2022","abstract":[{"text":"We present a new multi-layered, conceptual model for associating musical source materials to musicological arguments. We describe our proposal for operationalizing these concepts through a framework for musical annotation which we have implemented using RDF. Briefly stated, this model shows how portions of digitized data in various files and formats can be identified, selected, labelled, and compared.","lang":"eng"}],"date_created":"2024-08-28T11:41:59Z","department":[{"_id":"874"}],"keyword":["BitH","Linked Data"],"type":"conference"},{"date_created":"2024-08-28T11:41:41Z","keyword":["BitH","Linked Data"],"type":"conference","department":[{"_id":"874"}],"oa":"1","citation":{"mla":"Lewis, David, et al. <i>Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection</i>. 2023, doi:<a href=\"https://doi.org/10.5281/ZENODO.10265407\">10.5281/ZENODO.10265407</a>.","bibtex":"@inproceedings{Lewis_Shibata_Hankinson_Kepper_Page_Rosendahl_Saccomano_Siegert_2023, title={Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection}, DOI={<a href=\"https://doi.org/10.5281/ZENODO.10265407\">10.5281/ZENODO.10265407</a>}, author={Lewis, David and Shibata, Elisabete and Hankinson, Andrew and Kepper, Johannes and Page, Kevin R. and Rosendahl, Lisa and Saccomano, Mark and Siegert, Christine}, year={2023} }","ama":"Lewis D, Shibata E, Hankinson A, et al. Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection. In: ; 2023. doi:<a href=\"https://doi.org/10.5281/ZENODO.10265407\">10.5281/ZENODO.10265407</a>","ieee":"D. Lewis <i>et al.</i>, “Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection,” 2023, doi: <a href=\"https://doi.org/10.5281/ZENODO.10265407\">10.5281/ZENODO.10265407</a>.","apa":"Lewis, D., Shibata, E., Hankinson, A., Kepper, J., Page, K. R., Rosendahl, L., Saccomano, M., &#38; Siegert, C. (2023). <i>Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection</i>. <a href=\"https://doi.org/10.5281/ZENODO.10265407\">https://doi.org/10.5281/ZENODO.10265407</a>","short":"D. Lewis, E. Shibata, A. Hankinson, J. Kepper, K.R. Page, L. Rosendahl, M. Saccomano, C. Siegert, in: 2023.","chicago":"Lewis, David, Elisabete Shibata, Andrew Hankinson, Johannes Kepper, Kevin R. Page, Lisa Rosendahl, Mark Saccomano, and Christine Siegert. “Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection,” 2023. <a href=\"https://doi.org/10.5281/ZENODO.10265407\">https://doi.org/10.5281/ZENODO.10265407</a>."},"abstract":[{"lang":"eng","text":"Digital musicology research often proceeds by extending and enriching its evidence base as it progresses, rather than starting with a complete corpus of data and metadata, as a consequence of an emergent research need. In this paper, we consider a research workflow which assumes an incremental approach to data gathering and annotation. We describe tooling which implements parts of this workflow, developed to support the study of nineteenth-century music arrangements, and evaluate the applicability of our approach through interviews with musicologists and music editors who have used the tools. We conclude by considering extensions of this approach and the wider implications for digital musicology and music information retrieval."}],"main_file_link":[{"url":"https://zenodo.org/records/10265407/files/000094.pdf?download=1","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"55832","user_id":"1684","doi":"10.5281/ZENODO.10265407","year":"2023","title":"Supporting Musicological Investigations With Information Retrieval Tools: An Iterative Approach to Data Collection","status":"public","author":[{"full_name":"Lewis, David","first_name":"David","last_name":"Lewis"},{"full_name":"Shibata, Elisabete","last_name":"Shibata","first_name":"Elisabete"},{"full_name":"Hankinson, Andrew","first_name":"Andrew","last_name":"Hankinson"},{"full_name":"Kepper, Johannes","orcid":"0000-0003-4891-260X","first_name":"Johannes","last_name":"Kepper","id":"1684"},{"full_name":"Page, Kevin R.","first_name":"Kevin R.","last_name":"Page"},{"full_name":"Rosendahl, Lisa","last_name":"Rosendahl","first_name":"Lisa"},{"last_name":"Saccomano","first_name":"Mark","full_name":"Saccomano, Mark"},{"full_name":"Siegert, Christine","first_name":"Christine","last_name":"Siegert"}],"publication_status":"published","date_updated":"2024-08-28T14:14:55Z"},{"title":"Geographic Information Systems in Information Systems Research - Review and Research Prospects","year":"2023","status":"public","conference":{"name":"56th Hawaii International Conference on System Sciences"},"author":[{"full_name":"Priefer, Jennifer","first_name":"Jennifer","last_name":"Priefer","id":"82872"}],"date_updated":"2023-01-19T06:32:30Z","main_file_link":[{"url":"https://hdl.handle.net/10125/103252"}],"language":[{"iso":"eng"}],"_id":"37497","user_id":"82872","editor":[{"last_name":"Bui","first_name":"T.X.","full_name":"Bui, T.X."},{"full_name":"Sprague, R.H.","first_name":"R.H.","last_name":"Sprague"}],"publication":"Proceedings of the 56th Hawaii International Conference on System Sciences","citation":{"ama":"Priefer J. Geographic Information Systems in Information Systems Research - Review and Research Prospects. In: Bui TX, Sprague RH, eds. <i>Proceedings of the 56th Hawaii International Conference on System Sciences</i>. ; 2023.","bibtex":"@inproceedings{Priefer_2023, title={Geographic Information Systems in Information Systems Research - Review and Research Prospects}, booktitle={Proceedings of the 56th Hawaii International Conference on System Sciences}, author={Priefer, Jennifer}, editor={Bui, T.X. and Sprague, R.H.}, year={2023} }","mla":"Priefer, Jennifer. “Geographic Information Systems in Information Systems Research - Review and Research Prospects.” <i>Proceedings of the 56th Hawaii International Conference on System Sciences</i>, edited by T.X. Bui and R.H. Sprague, 2023.","chicago":"Priefer, Jennifer. “Geographic Information Systems in Information Systems Research - Review and Research Prospects.” In <i>Proceedings of the 56th Hawaii International Conference on System Sciences</i>, edited by T.X. Bui and R.H. Sprague, 2023.","short":"J. Priefer, in: T.X. Bui, R.H. Sprague (Eds.), Proceedings of the 56th Hawaii International Conference on System Sciences, 2023.","apa":"Priefer, J. (2023). Geographic Information Systems in Information Systems Research - Review and Research Prospects. In T. X. Bui &#38; R. H. Sprague (Eds.), <i>Proceedings of the 56th Hawaii International Conference on System Sciences</i>.","ieee":"J. Priefer, “Geographic Information Systems in Information Systems Research - Review and Research Prospects,” in <i>Proceedings of the 56th Hawaii International Conference on System Sciences</i>, 2023."},"abstract":[{"lang":"eng","text":"Since historical times, cartographic maps have revealed spatial relations and enabled decisions and processes. Geographic Information Systems (GIS) allow for acquisition, management, analysis, and presentation of geospatial objects. With free geospatial data becoming available through open data policies and an increasing amount of digitally connected objects in the Internet of Things (IoT), GIS are becoming indispensable to Information Systems (IS) research. However, the consideration and relevance of GIS has only been investigated rarely. We examine, how and in which fields of application GIS have been studied in the IS literature and elicit the importance of GIS regarding their design and usage. A systematic literature review leads us to develop four research propositions. Our results indicate that GIS are still an undeservedly underrepresented discipline in IS and should be more theorized, put center-stage in design-oriented research, and considered for creating superior value co-creation in service systems."}],"date_created":"2023-01-19T06:32:14Z","type":"conference","keyword":["GIS","Industry 4.0","and Sustainability","geographic information systems","geospatial data","gis","information systems research","literature review"]},{"_id":"45793","language":[{"iso":"eng"}],"user_id":"66731","title":"Data-Driven Product Management: A Practitioner-Driven Research Agenda","year":"2023","status":"public","conference":{"location":"Sydney","name":"33rd CIRP Design Conference"},"author":[{"full_name":"Grigoryan, Khoren","last_name":"Grigoryan","first_name":"Khoren"},{"id":"66731","orcid":"https://orcid.org/0000-0001-6034-4399","last_name":"Fichtler","first_name":"Timm","full_name":"Fichtler, Timm"},{"full_name":"Schreiner, Nick","last_name":"Schreiner","first_name":"Nick"},{"full_name":"Rabe, Martin","last_name":"Rabe","first_name":"Martin"},{"id":"72658","first_name":"Melina","last_name":"Panzner","full_name":"Panzner, Melina"},{"full_name":"Kühn, Arno","first_name":"Arno","last_name":"Kühn"},{"full_name":"Dumitrescu, Roman","first_name":"Roman","last_name":"Dumitrescu","id":"16190"},{"id":"43136","full_name":"Koldewey, Christian","orcid":"https://orcid.org/0000-0001-7992-6399","last_name":"Koldewey","first_name":"Christian"}],"date_updated":"2023-06-27T13:57:42Z","date_created":"2023-06-27T13:46:45Z","type":"conference","keyword":["Product Management","Data Analytics","Data-Driven Design","Product-related data","Lifecycle Data","Tool-support"],"department":[{"_id":"563"},{"_id":"241"}],"publication":"Procedia CIRP 33","citation":{"bibtex":"@inproceedings{Grigoryan_Fichtler_Schreiner_Rabe_Panzner_Kühn_Dumitrescu_Koldewey_2023, title={Data-Driven Product Management: A Practitioner-Driven Research Agenda}, booktitle={Procedia CIRP 33}, author={Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}, year={2023} }","ama":"Grigoryan K, Fichtler T, Schreiner N, et al. Data-Driven Product Management: A Practitioner-Driven Research Agenda. In: <i>Procedia CIRP 33</i>. ; 2023.","short":"K. Grigoryan, T. Fichtler, N. Schreiner, M. Rabe, M. Panzner, A. Kühn, R. Dumitrescu, C. Koldewey, in: Procedia CIRP 33, 2023.","chicago":"Grigoryan, Khoren, Timm Fichtler, Nick Schreiner, Martin Rabe, Melina Panzner, Arno Kühn, Roman Dumitrescu, and Christian Koldewey. “Data-Driven Product Management: A Practitioner-Driven Research Agenda.” In <i>Procedia CIRP 33</i>, 2023.","ieee":"K. Grigoryan <i>et al.</i>, “Data-Driven Product Management: A Practitioner-Driven Research Agenda,” presented at the 33rd CIRP Design Conference, Sydney, 2023.","apa":"Grigoryan, K., Fichtler, T., Schreiner, N., Rabe, M., Panzner, M., Kühn, A., Dumitrescu, R., &#38; Koldewey, C. (2023). Data-Driven Product Management: A Practitioner-Driven Research Agenda. <i>Procedia CIRP 33</i>. 33rd CIRP Design Conference, Sydney.","mla":"Grigoryan, Khoren, et al. “Data-Driven Product Management: A Practitioner-Driven Research Agenda.” <i>Procedia CIRP 33</i>, 2023."},"abstract":[{"text":"The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.","lang":"eng"}]},{"citation":{"short":"M. Khedkar, in: 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, Pp. 197-199, n.d.","chicago":"Khedkar, Mugdha. “Static Analysis for Android GDPR Compliance Assurance.” In <i>2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, Pp. 197-199</i>, n.d. <a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">https://doi.org/10.1109/ICSE-Companion58688.2023.00054</a>.","ieee":"M. Khedkar, “Static Analysis for Android GDPR Compliance Assurance,” doi: <a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">10.1109/ICSE-Companion58688.2023.00054</a>.","apa":"Khedkar, M. (n.d.). Static Analysis for Android GDPR Compliance Assurance. <i>2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, Pp. 197-199</i>. <a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">https://doi.org/10.1109/ICSE-Companion58688.2023.00054</a>","bibtex":"@inproceedings{Khedkar, title={Static Analysis for Android GDPR Compliance Assurance}, DOI={<a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">10.1109/ICSE-Companion58688.2023.00054</a>}, booktitle={2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, pp. 197-199}, author={Khedkar, Mugdha} }","ama":"Khedkar M. Static Analysis for Android GDPR Compliance Assurance. In: <i>2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, Pp. 197-199</i>. doi:<a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">10.1109/ICSE-Companion58688.2023.00054</a>","mla":"Khedkar, Mugdha. “Static Analysis for Android GDPR Compliance Assurance.” <i>2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, Pp. 197-199</i>, doi:<a href=\"https://doi.org/10.1109/ICSE-Companion58688.2023.00054\">10.1109/ICSE-Companion58688.2023.00054</a>."},"file_date_updated":"2023-04-24T12:15:27Z","external_id":{"arxiv":["2303.09606"]},"has_accepted_license":"1","status":"public","user_id":"88024","ddc":["004"],"_id":"44146","abstract":[{"lang":"eng","text":"Many Android applications collect data from users. When they do, they must\r\nprotect this collected data according to the current legal frameworks. Such\r\ndata protection has become even more important since the European Union rolled\r\nout the General Data Protection Regulation (GDPR). App developers have limited\r\ntool support to reason about data protection throughout their app development\r\nprocess. Although many Android applications state a privacy policy, privacy\r\npolicy compliance checks are currently manual, expensive, and prone to error.\r\nOne of the major challenges in privacy audits is the significant gap between\r\nlegal privacy statements (in English text) and technical measures that Android\r\napps use to protect their user's privacy. In this thesis, we will explore to\r\nwhat extent we can use static analysis to answer important questions regarding\r\ndata protection. Our main goal is to design a tool based approach that aids app\r\ndevelopers and auditors in ensuring data protection in Android applications,\r\nbased on automated static program analysis."}],"publication":"2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, pp. 197-199","department":[{"_id":"76"}],"keyword":["static analysis","data protection and privacy","GDPR compliance"],"type":"conference","date_created":"2023-04-24T12:14:17Z","file":[{"file_name":"2023047614.pdf","file_size":85313,"access_level":"closed","relation":"main_file","date_updated":"2023-04-24T12:15:27Z","file_id":"44147","success":1,"content_type":"application/pdf","creator":"khedkarm","date_created":"2023-04-24T12:15:27Z"}],"publication_status":"accepted","date_updated":"2024-09-16T08:46:25Z","author":[{"last_name":"Khedkar","first_name":"Mugdha","full_name":"Khedkar, Mugdha","id":"88024"}],"title":"Static Analysis for Android GDPR Compliance Assurance","year":"2023","doi":"10.1109/ICSE-Companion58688.2023.00054","language":[{"iso":"eng"}]},{"doi":"https://doi.org/10.1016/j.ifacol.2023.02.015","language":[{"iso":"eng"}],"date_updated":"2024-11-13T08:43:05Z","intvolume":"        56","year":"2023","title":"Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF","author":[{"id":"43992","first_name":"Ricarda-Samantha","last_name":"Götte","full_name":"Götte, Ricarda-Samantha"},{"id":"15402","first_name":"Julia","last_name":"Timmermann","full_name":"Timmermann, Julia"}],"keyword":["joint estimation","unscented transform","Kalman filter","sparsity","data-driven","compressed sensing"],"type":"conference","department":[{"_id":"153"},{"_id":"880"}],"date_created":"2022-12-01T07:17:00Z","abstract":[{"lang":"eng","text":"State estimation when only a partial model of a considered system is available remains a major challenge in many engineering fields. This work proposes a joint, square-root unscented Kalman filter to estimate states and model uncertainties simultaneously by linear combinations of physics-motivated library functions. Using a sparsity promoting approach, a selection of those linear combinations is chosen and thus an interpretable model can be extracted. Results indicate a small estimation error compared to a traditional square-root unscented Kalman filter and exhibit the enhancement of physically meaningful models."}],"publication":"12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)","issue":"1","user_id":"43992","volume":56,"page":"85-90","_id":"34171","status":"public","conference":{"end_date":"2023-01-06","location":"Canberra, Australien","start_date":"2023-01-04","name":"12th IFAC Symposium on Nonlinear Control Systems NOLCOS 2022"},"quality_controlled":"1","citation":{"mla":"Götte, Ricarda-Samantha, and Julia Timmermann. “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF.” <i>12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)</i>, vol. 56, no. 1, 2023, pp. 85–90, doi:<a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>.","ama":"Götte R-S, Timmermann J. Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. In: <i>12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)</i>. Vol 56. ; 2023:85-90. doi:<a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>","bibtex":"@inproceedings{Götte_Timmermann_2023, title={Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF}, volume={56}, DOI={<a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>}, number={1}, booktitle={12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)}, author={Götte, Ricarda-Samantha and Timmermann, Julia}, year={2023}, pages={85–90} }","apa":"Götte, R.-S., &#38; Timmermann, J. (2023). Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF. <i>12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)</i>, <i>56</i>(1), 85–90. <a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>","ieee":"R.-S. Götte and J. Timmermann, “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF,” in <i>12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)</i>, Canberra, Australien, 2023, vol. 56, no. 1, pp. 85–90, doi: <a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>.","chicago":"Götte, Ricarda-Samantha, and Julia Timmermann. “Estimating States and Model Uncertainties Jointly by a Sparsity Promoting UKF.” In <i>12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022)</i>, 56:85–90, 2023. <a href=\"https://doi.org/10.1016/j.ifacol.2023.02.015\">https://doi.org/10.1016/j.ifacol.2023.02.015</a>.","short":"R.-S. Götte, J. Timmermann, in: 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), 2023, pp. 85–90."}},{"title":"Security Analysis of the 3MF Data Format","year":"2023","author":[{"id":"58331","orcid":"0000-0002-3182-4059","first_name":"Jost","last_name":"Rossel","full_name":"Rossel, Jost"},{"full_name":"Mladenov, Vladislav","last_name":"Mladenov","first_name":"Vladislav"},{"id":"83504","first_name":"Juraj","orcid":"0000-0002-3593-7720","last_name":"Somorovsky","full_name":"Somorovsky, Juraj"}],"publication_status":"published","date_updated":"2025-07-16T11:06:49Z","main_file_link":[{"url":"https://dl.acm.org/doi/abs/10.1145/3607199.3607216"}],"language":[{"iso":"eng"}],"doi":"10.1145/3607199.3607216","publication":"Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses","abstract":[{"text":"3D printing is a well-established technology with rapidly increasing usage scenarios both in the industry and consumer context. The growing popularity of 3D printing has also attracted security researchers, who have analyzed possibilities for weakening 3D models or stealing intellectual property from 3D models. We extend these important aspects and provide the first comprehensive security analysis of 3D printing data formats. We performed our systematic study on the example of the 3D Manufacturing Format (3MF), which offers a large variety of features that could lead to critical attacks. Based on 3MF’s features, we systematized three attack goals: Data Exfiltration (dex), Denial of Service, and UI Spoofing (uis). We achieve these goals by exploiting the complexity of 3MF, which is based on the Open Packaging Conventions (OPC) format and uses XML to define 3D models. In total, our analysis led to 352 tests. To create and run these tests automatically, we implemented an open-source tool named 3MF Analyzer (tool), which helped us evaluate 20 applications.","lang":"eng"}],"file":[{"content_type":"application/pdf","file_id":"48065","date_updated":"2024-09-05T11:14:40Z","relation":"main_file","access_level":"open_access","file_size":1054999,"file_name":"Security_Analysis_of_the_3mf_Data_Format.pdf","date_created":"2023-10-16T03:48:08Z","creator":"jrossel"}],"date_created":"2023-10-11T13:42:09Z","type":"conference","keyword":["Data Format Security","3D Manufacturing Format","3D Printing","Additive Manufacturing"],"department":[{"_id":"632"}],"status":"public","conference":{"location":"Hongkong","start_date":"2023-10-16","name":"26th International Symposium on Research in Attacks, Intrusions and Defenses","end_date":"2023-10-18"},"has_accepted_license":"1","publisher":"ACM","_id":"48012","user_id":"58331","ddc":["000"],"file_date_updated":"2024-09-05T11:14:40Z","citation":{"bibtex":"@inproceedings{Rossel_Mladenov_Somorovsky_2023, title={Security Analysis of the 3MF Data Format}, DOI={<a href=\"https://doi.org/10.1145/3607199.3607216\">10.1145/3607199.3607216</a>}, booktitle={Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses}, publisher={ACM}, author={Rossel, Jost and Mladenov, Vladislav and Somorovsky, Juraj}, year={2023} }","ama":"Rossel J, Mladenov V, Somorovsky J. Security Analysis of the 3MF Data Format. In: <i>Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses</i>. ACM; 2023. doi:<a href=\"https://doi.org/10.1145/3607199.3607216\">10.1145/3607199.3607216</a>","short":"J. Rossel, V. Mladenov, J. Somorovsky, in: Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses, ACM, 2023.","chicago":"Rossel, Jost, Vladislav Mladenov, and Juraj Somorovsky. “Security Analysis of the 3MF Data Format.” In <i>Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses</i>. ACM, 2023. <a href=\"https://doi.org/10.1145/3607199.3607216\">https://doi.org/10.1145/3607199.3607216</a>.","ieee":"J. Rossel, V. Mladenov, and J. Somorovsky, “Security Analysis of the 3MF Data Format,” presented at the 26th International Symposium on Research in Attacks, Intrusions and Defenses, Hongkong, 2023, doi: <a href=\"https://doi.org/10.1145/3607199.3607216\">10.1145/3607199.3607216</a>.","mla":"Rossel, Jost, et al. “Security Analysis of the 3MF Data Format.” <i>Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses</i>, ACM, 2023, doi:<a href=\"https://doi.org/10.1145/3607199.3607216\">10.1145/3607199.3607216</a>.","apa":"Rossel, J., Mladenov, V., &#38; Somorovsky, J. (2023). Security Analysis of the 3MF Data Format. <i>Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses</i>. 26th International Symposium on Research in Attacks, Intrusions and Defenses, Hongkong. <a href=\"https://doi.org/10.1145/3607199.3607216\">https://doi.org/10.1145/3607199.3607216</a>"},"quality_controlled":"1","oa":"1"}]