--- _id: '64916' abstract: - lang: eng text: The joining of dissimilar materials, such as steel and aluminum, entails significant challenges during thermal curing processes due to differing coefficients of thermal expansion. This study addresses the formation of “viscous fingering” instabilities in structural adhesive joints, which are induced by thermally driven relative displacements during the liquid phase of the adhesive. Using a component-like specimen “bridge specimen,” the dependency of this phenomenon on process temperature and structural stiffness (rivet distance) was characterized. Experimental results reveal that while the relative displacement scales cubically with the free buckling length, the resulting adhesive area reduction follows an exponential trend, leading to a loss of effective bond area of up to 79%, which significantly compromises the joint strength in automotive applications. To predict these process-induced defects, a thermo-chemo-viscoelastic-viscoplastic adhesive model implemented in LS-DYNA was applied. The model combines curing kinetics, viscoelastic relaxation, and pressure-dependent plasticity and features a geometric damage parameter (D) that captures the adhesive area reduction caused by viscous fingering as an exponential function of the accumulated normal strain in the liquid phase. This damage parameter, calibrated on base-specimen level, was transferred to the component geometry. The simulation demonstrated high predictive accuracy with a maximum deviation of the adhesive area reduction of 3.1% compared to experimental data. This validates the model’s capability to predict manufacturing-induced damage in complex hybrid structures solely based on thermal boundary conditions. article_type: original author: - first_name: Mohamad full_name: Al Trjman, Mohamad id: '65415' last_name: Al Trjman - first_name: Felix full_name: Beule, Felix id: '66192' last_name: Beule - first_name: Dominik full_name: Teutenberg, Dominik id: '537' last_name: Teutenberg - first_name: Gerson full_name: Meschut, Gerson id: '32056' last_name: Meschut orcid: 0000-0002-2763-1246 - first_name: Julia full_name: Riese, Julia id: '101499' last_name: Riese orcid: 0000-0002-3053-0534 citation: ama: Al Trjman M, Beule F, Teutenberg D, Meschut G, Riese J. Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixed structures. The Journal of Adhesion. Published online 2026:1-24. doi:10.1080/00218464.2026.2644394 apa: Al Trjman, M., Beule, F., Teutenberg, D., Meschut, G., & Riese, J. (2026). Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixed structures. The Journal of Adhesion, 1–24. https://doi.org/10.1080/00218464.2026.2644394 bibtex: '@article{Al Trjman_Beule_Teutenberg_Meschut_Riese_2026, title={Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixed structures}, DOI={10.1080/00218464.2026.2644394}, journal={The Journal of Adhesion}, publisher={Informa UK Limited}, author={Al Trjman, Mohamad and Beule, Felix and Teutenberg, Dominik and Meschut, Gerson and Riese, Julia}, year={2026}, pages={1–24} }' chicago: Al Trjman, Mohamad, Felix Beule, Dominik Teutenberg, Gerson Meschut, and Julia Riese. “Experimental Characterization and Numerical Analysis of the Influence of the CED Coating Process on Viscous Fingering Formation in Hybrid-Jointed Mixed Structures.” The Journal of Adhesion, 2026, 1–24. https://doi.org/10.1080/00218464.2026.2644394. ieee: 'M. Al Trjman, F. Beule, D. Teutenberg, G. Meschut, and J. Riese, “Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixed structures,” The Journal of Adhesion, pp. 1–24, 2026, doi: 10.1080/00218464.2026.2644394.' mla: Al Trjman, Mohamad, et al. “Experimental Characterization and Numerical Analysis of the Influence of the CED Coating Process on Viscous Fingering Formation in Hybrid-Jointed Mixed Structures.” The Journal of Adhesion, Informa UK Limited, 2026, pp. 1–24, doi:10.1080/00218464.2026.2644394. short: M. Al Trjman, F. Beule, D. Teutenberg, G. Meschut, J. Riese, The Journal of Adhesion (2026) 1–24. date_created: 2026-03-14T18:43:41Z date_updated: 2026-03-14T19:04:46Z ddc: - '620' - '670' - '660' department: - _id: '9' doi: 10.1080/00218464.2026.2644394 file: - access_level: closed content_type: application/pdf creator: mohamada date_created: 2026-03-14T18:50:31Z date_updated: 2026-03-14T18:50:31Z file_id: '64917' file_name: Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixe.pdf file_size: 14668789 relation: main_file success: 1 file_date_updated: 2026-03-14T18:50:31Z has_accepted_license: '1' keyword: - Adhesive area reduction - CED coating process - delta alpha problem - epoxy structural adhesive - influence of manufacture - multi-material design - numerical simulation (FEM) - relative displacements - viscous fingering (saffman-taylor-instability). language: - iso: eng main_file_link: - open_access: '1' oa: '1' page: 1-24 publication: The Journal of Adhesion publication_identifier: issn: - 0021-8464 - 1545-5823 publication_status: published publisher: Informa UK Limited status: public title: Experimental characterization and numerical analysis of the influence of the CED coating process on viscous fingering formation in hybrid-jointed mixed structures type: journal_article user_id: '65415' year: '2026' ... --- _id: '55400' abstract: - lang: eng text: "This study contributes to the evolving field of robot learning in interaction\r\nwith humans, examining the impact of diverse input modalities on learning\r\noutcomes. It introduces the concept of \"meta-modalities\" which encapsulate\r\nadditional forms of feedback beyond the traditional preference and scalar\r\nfeedback mechanisms. Unlike prior research that focused on individual\r\nmeta-modalities, this work evaluates their combined effect on learning\r\noutcomes. Through a study with human participants, we explore user preferences\r\nfor these modalities and their impact on robot learning performance. Our\r\nfindings reveal that while individual modalities are perceived differently,\r\ntheir combination significantly improves learning behavior and usability. This\r\nresearch not only provides valuable insights into the optimization of\r\nhuman-robot interactive task learning but also opens new avenues for enhancing\r\nthe interactive freedom and scaffolding capabilities provided to users in such\r\nsettings." article_type: original author: - first_name: Helen full_name: Beierling, Helen last_name: Beierling - first_name: 'Robin ' full_name: 'Beierling, Robin ' last_name: Beierling - first_name: Anna-Lisa full_name: Vollmer, Anna-Lisa last_name: Vollmer citation: ama: Beierling H, Beierling R, Vollmer A-L. The power of combined modalities in interactive robot learning. Frontiers in Robotics and AI. 2025;12. apa: Beierling, H., Beierling, R., & Vollmer, A.-L. (2025). The power of combined modalities in interactive robot learning. Frontiers in Robotics and AI, 12. bibtex: '@article{Beierling_Beierling_Vollmer_2025, title={The power of combined modalities in interactive robot learning}, volume={12}, journal={Frontiers in Robotics and AI}, publisher={Frontiers }, author={Beierling, Helen and Beierling, Robin and Vollmer, Anna-Lisa}, year={2025} }' chicago: Beierling, Helen, Robin Beierling, and Anna-Lisa Vollmer. “The Power of Combined Modalities in Interactive Robot Learning.” Frontiers in Robotics and AI 12 (2025). ieee: H. Beierling, R. Beierling, and A.-L. Vollmer, “The power of combined modalities in interactive robot learning,” Frontiers in Robotics and AI, vol. 12, 2025. mla: Beierling, Helen, et al. “The Power of Combined Modalities in Interactive Robot Learning.” Frontiers in Robotics and AI, vol. 12, Frontiers , 2025. short: H. Beierling, R. Beierling, A.-L. Vollmer, Frontiers in Robotics and AI 12 (2025). date_created: 2024-07-26T08:35:24Z date_updated: 2025-09-17T13:38:18Z ddc: - '004' extern: '1' file: - access_level: closed content_type: application/pdf creator: helebeen date_created: 2025-09-17T13:36:09Z date_updated: 2025-09-17T13:36:09Z file_id: '61331' file_name: frobt-12-1598968.pdf file_size: 36978223 relation: main_file success: 1 file_date_updated: 2025-09-17T13:36:09Z funded_apc: '1' has_accepted_license: '1' intvolume: ' 12' keyword: - human-robot interaction - human-in-the-loop learning - reinforcement learning - interactive robot learning - multi-modal feedback - learning from demonstration - preference-based learning - scaffolding in robot learning language: - iso: eng main_file_link: - open_access: '1' url: https://pmc.ncbi.nlm.nih.gov/articles/PMC12312635/ oa: '1' project: - _id: '123' name: 'TRR 318 - B5: TRR 318 - Subproject B5' publication: Frontiers in Robotics and AI publication_status: published publisher: 'Frontiers ' status: public title: The power of combined modalities in interactive robot learning type: journal_article user_id: '50995' volume: 12 year: '2025' ... --- _id: '62066' abstract: - lang: eng text: In the context of high-performance computing (HPC) for distributed workloads, individual field-programmable gate arrays (FPGAs) need efficient ways to exchange data, which requires network infrastructure and software abstractions. Dedicated multi-FPGA clusters provide inter-FPGA networks for direct device to device communication. The oneAPI high-level synthesis toolchain offers I/O pipes to allow user kernels to interact with the networking ports of the FPGA board. In this work, we evaluate using oneAPI I/O pipes for direct FPGA-to-FPGA communication by scaling a SYCL implementation of a Jacobi solver on up to 25 FPGAs in the Noctua 2 cluster. We see good results in weak and strong scaling experiments. author: - first_name: Christoph full_name: Alt, Christoph id: '100625' last_name: Alt - first_name: Christian full_name: Plessl, Christian id: '16153' last_name: Plessl orcid: 0000-0001-5728-9982 - first_name: Tobias full_name: Kenter, Tobias id: '3145' last_name: Kenter citation: ama: 'Alt C, Plessl C, Kenter T. Evaluating oneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to multiple FPGAs. In: Proceedings of the 13th International Workshop on OpenCL and SYCL. IWOCL ’25. Association for Computing Machinery; 2025. doi:10.1145/3731125.3731131' apa: Alt, C., Plessl, C., & Kenter, T. (2025). Evaluating oneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to multiple FPGAs. Proceedings of the 13th International Workshop on OpenCL and SYCL. https://doi.org/10.1145/3731125.3731131 bibtex: '@inproceedings{Alt_Plessl_Kenter_2025, place={New York, NY, USA}, series={IWOCL ’25}, title={Evaluating oneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to multiple FPGAs}, DOI={10.1145/3731125.3731131}, booktitle={Proceedings of the 13th International Workshop on OpenCL and SYCL}, publisher={Association for Computing Machinery}, author={Alt, Christoph and Plessl, Christian and Kenter, Tobias}, year={2025}, collection={IWOCL ’25} }' chicago: 'Alt, Christoph, Christian Plessl, and Tobias Kenter. “Evaluating OneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to Multiple FPGAs.” In Proceedings of the 13th International Workshop on OpenCL and SYCL. IWOCL ’25. New York, NY, USA: Association for Computing Machinery, 2025. https://doi.org/10.1145/3731125.3731131.' ieee: 'C. Alt, C. Plessl, and T. Kenter, “Evaluating oneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to multiple FPGAs,” 2025, doi: 10.1145/3731125.3731131.' mla: Alt, Christoph, et al. “Evaluating OneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to Multiple FPGAs.” Proceedings of the 13th International Workshop on OpenCL and SYCL, Association for Computing Machinery, 2025, doi:10.1145/3731125.3731131. short: 'C. Alt, C. Plessl, T. Kenter, in: Proceedings of the 13th International Workshop on OpenCL and SYCL, Association for Computing Machinery, New York, NY, USA, 2025.' date_created: 2025-11-04T09:45:23Z date_updated: 2025-11-04T09:47:26Z department: - _id: '27' - _id: '518' doi: 10.1145/3731125.3731131 keyword: - Multi-FPGA - High-level Synthesis - oneAPI - FPGA language: - iso: eng main_file_link: - open_access: '1' oa: '1' place: New York, NY, USA project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Proceedings of the 13th International Workshop on OpenCL and SYCL publication_identifier: isbn: - '9798400713606' publisher: Association for Computing Machinery quality_controlled: '1' series_title: IWOCL ’25 status: public title: Evaluating oneAPI I/O Pipes in a Case Study of Scaling a SYCL Jacobi Solver to multiple FPGAs type: conference user_id: '3145' year: '2025' ... --- _id: '63053' author: - first_name: Carlos full_name: Hernández, Carlos last_name: Hernández - first_name: Angel E. full_name: Rodriguez-Fernandez, Angel E. last_name: Rodriguez-Fernandez - first_name: Lennart full_name: Schäpermeier, Lennart last_name: Schäpermeier - first_name: Oliver full_name: Cuate, Oliver last_name: Cuate - first_name: Heike full_name: Trautmann, Heike id: '100740' last_name: Trautmann orcid: 0000-0002-9788-8282 - first_name: Oliver full_name: Schütze, Oliver last_name: Schütze citation: ama: Hernández C, Rodriguez-Fernandez AE, Schäpermeier L, Cuate O, Trautmann H, Schütze O. An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation. Published online 2025:1-1. doi:10.1109/TEVC.2025.3637276 apa: Hernández, C., Rodriguez-Fernandez, A. E., Schäpermeier, L., Cuate, O., Trautmann, H., & Schütze, O. (2025). An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2025.3637276 bibtex: '@article{Hernández_Rodriguez-Fernandez_Schäpermeier_Cuate_Trautmann_Schütze_2025, title={An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization}, DOI={10.1109/TEVC.2025.3637276}, journal={IEEE Transactions on Evolutionary Computation}, author={Hernández, Carlos and Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Cuate, Oliver and Trautmann, Heike and Schütze, Oliver}, year={2025}, pages={1–1} }' chicago: Hernández, Carlos, Angel E. Rodriguez-Fernandez, Lennart Schäpermeier, Oliver Cuate, Heike Trautmann, and Oliver Schütze. “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary Computation, 2025, 1–1. https://doi.org/10.1109/TEVC.2025.3637276. ieee: 'C. Hernández, A. E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann, and O. Schütze, “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2025, doi: 10.1109/TEVC.2025.3637276.' mla: Hernández, Carlos, et al. “An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary Computation, 2025, pp. 1–1, doi:10.1109/TEVC.2025.3637276. short: C. Hernández, A.E. Rodriguez-Fernandez, L. Schäpermeier, O. Cuate, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2025) 1–1. date_created: 2025-12-12T06:13:06Z date_updated: 2025-12-12T06:13:51Z department: - _id: '819' doi: 10.1109/TEVC.2025.3637276 keyword: - Optimization - Evolutionary computation - Hands - Proposals - Convergence - Computational efficiency - Artificial intelligence - Accuracy - Approximation algorithms - Aerospace electronics - Multi-objective optimization - evolutionary algorithms - nearly optimal solutions - multimodal optimization - archiving - continuation language: - iso: eng page: 1-1 publication: IEEE Transactions on Evolutionary Computation status: public title: An Evolutionary Approach for the Computation of ∈-Locally Optimal Solutions for Multi-Objective Multimodal Optimization type: journal_article user_id: '15504' year: '2025' ... --- _id: '56221' author: - first_name: Angel E. full_name: Rodriguez-Fernandez, Angel E. last_name: Rodriguez-Fernandez - first_name: Lennart full_name: Schäpermeier, Lennart last_name: Schäpermeier - first_name: Carlos full_name: Hernández, Carlos last_name: Hernández - first_name: Pascal full_name: Kerschke, Pascal last_name: Kerschke - first_name: Heike full_name: Trautmann, Heike id: '100740' last_name: Trautmann orcid: 0000-0002-9788-8282 - first_name: Oliver full_name: Schütze, Oliver last_name: Schütze citation: ama: Rodriguez-Fernandez AE, Schäpermeier L, Hernández C, Kerschke P, Trautmann H, Schütze O. Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation. Published online 2024:1-1. doi:10.1109/TEVC.2024.3458855 apa: Rodriguez-Fernandez, A. E., Schäpermeier, L., Hernández, C., Kerschke, P., Trautmann, H., & Schütze, O. (2024). Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization. IEEE Transactions on Evolutionary Computation, 1–1. https://doi.org/10.1109/TEVC.2024.3458855 bibtex: '@article{Rodriguez-Fernandez_Schäpermeier_Hernández_Kerschke_Trautmann_Schütze_2024, title={Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization}, DOI={10.1109/TEVC.2024.3458855}, journal={IEEE Transactions on Evolutionary Computation}, author={Rodriguez-Fernandez, Angel E. and Schäpermeier, Lennart and Hernández, Carlos and Kerschke, Pascal and Trautmann, Heike and Schütze, Oliver}, year={2024}, pages={1–1} }' chicago: Rodriguez-Fernandez, Angel E., Lennart Schäpermeier, Carlos Hernández, Pascal Kerschke, Heike Trautmann, and Oliver Schütze. “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary Computation, 2024, 1–1. https://doi.org/10.1109/TEVC.2024.3458855. ieee: 'A. E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, and O. Schütze, “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization,” IEEE Transactions on Evolutionary Computation, pp. 1–1, 2024, doi: 10.1109/TEVC.2024.3458855.' mla: Rodriguez-Fernandez, Angel E., et al. “Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization.” IEEE Transactions on Evolutionary Computation, 2024, pp. 1–1, doi:10.1109/TEVC.2024.3458855. short: A.E. Rodriguez-Fernandez, L. Schäpermeier, C. Hernández, P. Kerschke, H. Trautmann, O. Schütze, IEEE Transactions on Evolutionary Computation (2024) 1–1. date_created: 2024-09-24T08:01:14Z date_updated: 2024-09-24T08:01:47Z doi: 10.1109/TEVC.2024.3458855 keyword: - Optimization - Evolutionary computation - Approximation algorithms - Benchmark testing - Vectors - Surveys - Pareto optimization - multi-objective optimization - evolutionary computation - multimodal optimization - local solutions language: - iso: eng page: 1-1 publication: IEEE Transactions on Evolutionary Computation status: public title: Finding ϵ-Locally Optimal Solutions for Multi-Objective Multimodal Optimization type: journal_article user_id: '15504' year: '2024' ... --- _id: '56636' abstract: - lang: eng text: Abstract. Business reputation ecosystems are a widely untapped research field. In these ecosystems, agents can selectively exchange (monetary) ratings to in-form about the experienced quality in a market. We build a model for conducting a multi-agent simulation that can be used to simulate and evaluate business rep-utation ecosystems as a new system class. We explore the factual occurring vol-untary payment to create positive (pay) or negative ratings (no pay), selling rat-ings selectively to alleviate information asymmetry, and the workings of counter-ratings to prevent buyers' dishonest ratings. Thereby, we analyze, among others, agent profitability, the occurrence of dishonest ratings, and reputation bias and sensitivity. The results provide simulation-based empirical evidence that the con-cept of monetary reputation systems provides necessary incentives for participa-tion, and high-quality sellers and honest buyers benefit from such a system. The results indicate that counter-ratings prompt buyers author: - first_name: Ulvi full_name: Ibrahimli, Ulvi last_name: Ibrahimli - first_name: Simon full_name: Hemmrich, Simon last_name: Hemmrich - first_name: Simon full_name: Zauke, Simon last_name: Zauke - first_name: Axel full_name: Winkelmann, Axel last_name: Winkelmann citation: ama: 'Ibrahimli U, Hemmrich S, Zauke S, Winkelmann A. Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-agent Simulation on Monetary  Ratings. In: 19. Internationale Tagung Wirtschaftsinformatik (WI24). ; 2024.' apa: Ibrahimli, U., Hemmrich, S., Zauke, S., & Winkelmann, A. (2024). Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-agent Simulation on Monetary  Ratings. 19. Internationale Tagung Wirtschaftsinformatik (WI24). bibtex: '@inproceedings{Ibrahimli_Hemmrich_Zauke_Winkelmann_2024, title={Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-agent Simulation on Monetary  Ratings}, booktitle={19. Internationale Tagung Wirtschaftsinformatik (WI24)}, author={Ibrahimli, Ulvi and Hemmrich, Simon and Zauke, Simon and Winkelmann, Axel}, year={2024} }' chicago: Ibrahimli, Ulvi, Simon Hemmrich, Simon Zauke, and Axel Winkelmann. “Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-Agent Simulation on Monetary  Ratings.” In 19. Internationale Tagung Wirtschaftsinformatik (WI24), 2024. ieee: U. Ibrahimli, S. Hemmrich, S. Zauke, and A. Winkelmann, “Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-agent Simulation on Monetary  Ratings,” Würzburg, 2024. mla: Ibrahimli, Ulvi, et al. “Overcoming Lemon Markets with Business Reputation  Ecosystem – A Multi-Agent Simulation on Monetary  Ratings.” 19. Internationale Tagung Wirtschaftsinformatik (WI24), 2024. short: 'U. Ibrahimli, S. Hemmrich, S. Zauke, A. Winkelmann, in: 19. Internationale Tagung Wirtschaftsinformatik (WI24), 2024.' conference: location: Würzburg date_created: 2024-10-16T07:36:56Z date_updated: 2026-04-02T04:31:53Z jel: - C30 - A12 - D4 - D82 - L14 keyword: - Reputation System - Payment as Rating - Multi-Agent Simulation - Lemon Markets language: - iso: eng main_file_link: - open_access: '1' url: https://www.researchgate.net/publication/382338551_Overcoming_Lemon_Markets_with_Business_Reputation_Ecosystem_-A_Multi-agent_Simulation_on_Monetary_Ratings_Research_Paper oa: '1' publication: 19. Internationale Tagung Wirtschaftsinformatik (WI24) publication_status: published quality_controlled: '1' status: public title: Overcoming Lemon Markets with Business Reputation Ecosystem – A Multi-agent Simulation on Monetary Ratings type: conference user_id: '83557' year: '2024' ... --- _id: '45812' author: - first_name: Leon full_name: Özcan, Leon id: '45137' last_name: Özcan - first_name: Timm full_name: Fichtler, Timm id: '66731' last_name: Fichtler orcid: https://orcid.org/0000-0001-6034-4399 - first_name: Benjamin full_name: Kasten, Benjamin last_name: Kasten - first_name: Christian full_name: Koldewey, Christian id: '43136' last_name: Koldewey orcid: https://orcid.org/0000-0001-7992-6399 - first_name: Roman full_name: Dumitrescu, Roman id: '16190' last_name: Dumitrescu citation: ama: 'Özcan L, Fichtler T, Kasten B, Koldewey C, Dumitrescu R. Interview Study on Strategy Options for Platform Operation in B2B Markets. In: ; 2023.' apa: Özcan, L., Fichtler, T., Kasten, B., Koldewey, C., & Dumitrescu, R. (2023). Interview Study on Strategy Options for Platform Operation in B2B Markets. ISPIM Innovation Conference, Ljubljana. bibtex: '@inproceedings{Özcan_Fichtler_Kasten_Koldewey_Dumitrescu_2023, title={Interview Study on Strategy Options for Platform Operation in B2B Markets}, author={Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}, year={2023} }' chicago: Özcan, Leon, Timm Fichtler, Benjamin Kasten, Christian Koldewey, and Roman Dumitrescu. “Interview Study on Strategy Options for Platform Operation in B2B Markets,” 2023. ieee: L. Özcan, T. Fichtler, B. Kasten, C. Koldewey, and R. Dumitrescu, “Interview Study on Strategy Options for Platform Operation in B2B Markets,” presented at the ISPIM Innovation Conference, Ljubljana, 2023. mla: Özcan, Leon, et al. Interview Study on Strategy Options for Platform Operation in B2B Markets. 2023. short: 'L. Özcan, T. Fichtler, B. Kasten, C. Koldewey, R. Dumitrescu, in: 2023.' conference: location: Ljubljana name: ISPIM Innovation Conference date_created: 2023-06-28T11:18:12Z date_updated: 2023-06-28T11:18:31Z department: - _id: '563' keyword: - Digital Platform - Platform Strategy - Strategic Management - Platform Life Cycle - Interview Study - Business Model - Business-to-Business - Two-sided Market - Multi-sided Market language: - iso: eng status: public title: Interview Study on Strategy Options for Platform Operation in B2B Markets type: conference user_id: '66731' year: '2023' ... --- _id: '33991' abstract: - lang: eng text: In the course of digitalization, digital platforms are unleashing their full disruptive potential and are already dominating the first industries (e.g., hotel industry). As a result of this success, more and more companies want to build their own platforms and participate in the success. However, building and operating a digital platform involves multiple challenges and most of such ambitions fail. Since most digital platforms fail, strategic leadership of digital platforms must consider both success factors and reasons for platform failure. For this purpose, we conducted a systematic literature analysis and identified 24 success as well as failure factors in 9 dimensions. From a scientific perspective, the article provides a structured analysis of success and failure factors of digital platforms, which previously did not exist in literature. Practitioners can use the resulting knowledge base to successfully manage platform activities and avoid pitfalls. author: - first_name: Leon full_name: Özcan, Leon id: '45137' last_name: Özcan - first_name: Christian full_name: Koldewey, Christian last_name: Koldewey - first_name: Estelle full_name: Duparc, Estelle last_name: Duparc - first_name: Hendrik full_name: van der Valk, Hendrik last_name: van der Valk - first_name: Boris full_name: Otto, Boris last_name: Otto - first_name: Roman full_name: Dumitrescu, Roman last_name: Dumitrescu citation: ama: 'Özcan L, Koldewey C, Duparc E, van der Valk H, Otto B, Dumitrescu R. Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors. In: ; 2022.' apa: Özcan, L., Koldewey, C., Duparc, E., van der Valk, H., Otto, B., & Dumitrescu, R. (2022). Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors. 28th Americas Conference on Information Systems (AMCIS), Minneapolis. bibtex: '@inproceedings{Özcan_Koldewey_Duparc_van der Valk_Otto_Dumitrescu_2022, title={Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors}, author={Özcan, Leon and Koldewey, Christian and Duparc, Estelle and van der Valk, Hendrik and Otto, Boris and Dumitrescu, Roman}, year={2022} }' chicago: Özcan, Leon, Christian Koldewey, Estelle Duparc, Hendrik van der Valk, Boris Otto, and Roman Dumitrescu. “Why Do Digital Platforms Succeed or Fail? - A Literature Review on Success and Failure Factors,” 2022. ieee: L. Özcan, C. Koldewey, E. Duparc, H. van der Valk, B. Otto, and R. Dumitrescu, “Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors,” presented at the 28th Americas Conference on Information Systems (AMCIS), Minneapolis, 2022. mla: Özcan, Leon, et al. Why Do Digital Platforms Succeed or Fail? - A Literature Review on Success and Failure Factors. 2022. short: 'L. Özcan, C. Koldewey, E. Duparc, H. van der Valk, B. Otto, R. Dumitrescu, in: 2022.' conference: location: Minneapolis name: 28th Americas Conference on Information Systems (AMCIS) date_created: 2022-11-03T23:11:13Z date_updated: 2022-11-03T23:14:33Z ddc: - '600' department: - _id: '563' file: - access_level: closed content_type: application/pdf creator: loezcan date_created: 2022-11-03T23:07:27Z date_updated: 2022-11-03T23:07:27Z file_id: '33993' file_name: '[ÖKD+22]_Why do Digital Platforms succeed or fail - A Literature Review on Success and Failure Factors.pdf' file_size: 301409 relation: main_file success: 1 file_date_updated: 2022-11-03T23:07:27Z has_accepted_license: '1' keyword: - Digital Platform - Multi-sided Market - Two-sided Market - Success Factor - Failure Factor language: - iso: eng main_file_link: - url: https://aisel.aisnet.org/amcis2022/sig_dite/sig_dite/15/ status: public title: Why do Digital Platforms succeed or fail? - A Literature Review on Success and Failure Factors type: conference user_id: '45137' year: '2022' ... --- _id: '34209' abstract: - lang: eng text: Predicting the durability of components subjected to mechanical load under environmental conditions leading to corrosion is one of the most challenging tasks in mechanical engineering. The demand for precise predictions increases with the desire of lightweight design in transportation due to environmental protection. Corrosion with its manifold of mechanisms often occurs together with the production of hydrogen by electrochemical reactions. Hydrogen embrittlement is one of the most feared damage mechanisms for metal constructions often leading to early and unexpected failure. Until now, predictions are mostly based on costly experiments. Hence, a rational predictive model based on the fundamentals of electrochemistry and damage mechanics has to be developed in order to reduce the costs. In this work, a first model approach based on classical continuum damage mechanics is presented to couple both, the damage induced by the mechanical stress and the hydrogen embrittlement. An elaborated two-scale model based on the selfconsistent theory is applied to describe the mechanical damage due to fatigue. The electrochemical kinetics are elucidated through the Langmuir adsorption isotherm and the diffusion equation to consider the impact of hydrogen embrittlement on the fatigue. The modeling of the mechanism of hydrogen embrittlement defines the progress of damage accumulation due to the electrochemistry. The durability results like the S-N diagram show the influence of hydrogen embrittlement by varying, e.g. the fatigue frequency or the stress ratio. author: - first_name: Yuhao full_name: Shi, Yuhao last_name: Shi - first_name: Sven full_name: Harzheim, Sven last_name: Harzheim - first_name: Martin full_name: Hofmann, Martin last_name: Hofmann - first_name: Thomas full_name: Wallmersperger, Thomas last_name: Wallmersperger citation: ama: 'Shi Y, Harzheim S, Hofmann M, Wallmersperger T. A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement. In: Material Modeling and Structural Mechanics. Springer International Publishing; 2022. doi:10.1007/978-3-030-97675-0_9' apa: Shi, Y., Harzheim, S., Hofmann, M., & Wallmersperger, T. (2022). A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement. In Material Modeling and Structural Mechanics. Springer International Publishing. https://doi.org/10.1007/978-3-030-97675-0_9 bibtex: '@inbook{Shi_Harzheim_Hofmann_Wallmersperger_2022, place={Cham}, title={A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement}, DOI={10.1007/978-3-030-97675-0_9}, booktitle={Material Modeling and Structural Mechanics}, publisher={Springer International Publishing}, author={Shi, Yuhao and Harzheim, Sven and Hofmann, Martin and Wallmersperger, Thomas}, year={2022} }' chicago: 'Shi, Yuhao, Sven Harzheim, Martin Hofmann, and Thomas Wallmersperger. “A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement.” In Material Modeling and Structural Mechanics. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-030-97675-0_9.' ieee: 'Y. Shi, S. Harzheim, M. Hofmann, and T. Wallmersperger, “A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement,” in Material Modeling and Structural Mechanics, Cham: Springer International Publishing, 2022.' mla: Shi, Yuhao, et al. “A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement.” Material Modeling and Structural Mechanics, Springer International Publishing, 2022, doi:10.1007/978-3-030-97675-0_9. short: 'Y. Shi, S. Harzheim, M. Hofmann, T. Wallmersperger, in: Material Modeling and Structural Mechanics, Springer International Publishing, Cham, 2022.' date_created: 2022-12-05T20:53:13Z date_updated: 2023-01-02T11:10:26Z department: - _id: '630' doi: 10.1007/978-3-030-97675-0_9 keyword: - Hydrogen embrittlement - Fatigue - Continuum damage mechanics - Numerical simulation - Multi-field problem language: - iso: eng place: Cham project: - _id: '130' grant_number: '418701707' name: 'TRR 285: TRR 285' - _id: '132' name: 'TRR 285 - B: TRR 285 - Project Area B' - _id: '142' name: 'TRR 285 – B03: TRR 285 - Subproject B03' publication: Material Modeling and Structural Mechanics publication_identifier: isbn: - '9783030976743' - '9783030976750' issn: - 1869-8433 - 1869-8441 publication_status: published publisher: Springer International Publishing status: public title: A Damage Model for Corrosion Fatigue Due to Hydrogen Embrittlement type: book_chapter user_id: '14931' year: '2022' ... --- _id: '48882' abstract: - lang: eng text: In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV. author: - first_name: Jonathan full_name: Heins, Jonathan last_name: Heins - first_name: Jeroen full_name: Rook, Jeroen last_name: Rook - first_name: Lennart full_name: Schäpermeier, Lennart last_name: Schäpermeier - first_name: Pascal full_name: Kerschke, Pascal last_name: Kerschke - first_name: Jakob full_name: Bossek, Jakob id: '102979' last_name: Bossek orcid: 0000-0002-4121-4668 - first_name: Heike full_name: Trautmann, Heike last_name: Trautmann citation: ama: 'Heins J, Rook J, Schäpermeier L, Kerschke P, Bossek J, Trautmann H. BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In: Rudolph G, Kononova AV, Aguirre H, Kerschke P, Ochoa G, Tusar T, eds. Parallel Problem Solving from Nature (PPSN XVII). Lecture Notes in Computer Science. Springer International Publishing; 2022:192–206. doi:10.1007/978-3-031-14714-2_14' apa: 'Heins, J., Rook, J., Schäpermeier, L., Kerschke, P., Bossek, J., & Trautmann, H. (2022). BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems. In G. Rudolph, A. V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, & T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII) (pp. 192–206). Springer International Publishing. https://doi.org/10.1007/978-3-031-14714-2_14' bibtex: '@inproceedings{Heins_Rook_Schäpermeier_Kerschke_Bossek_Trautmann_2022, place={Cham}, series={Lecture Notes in Computer Science}, title={BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems}, DOI={10.1007/978-3-031-14714-2_14}, booktitle={Parallel Problem Solving from Nature (PPSN XVII)}, publisher={Springer International Publishing}, author={Heins, Jonathan and Rook, Jeroen and Schäpermeier, Lennart and Kerschke, Pascal and Bossek, Jakob and Trautmann, Heike}, editor={Rudolph, Günter and Kononova, Anna V. and Aguirre, Hernán and Kerschke, Pascal and Ochoa, Gabriela and Tusar, Tea}, year={2022}, pages={192–206}, collection={Lecture Notes in Computer Science} }' chicago: 'Heins, Jonathan, Jeroen Rook, Lennart Schäpermeier, Pascal Kerschke, Jakob Bossek, and Heike Trautmann. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” In Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph, Anna V. Kononova, Hernán Aguirre, Pascal Kerschke, Gabriela Ochoa, and Tea Tusar, 192–206. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2022. https://doi.org/10.1007/978-3-031-14714-2_14.' ieee: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, and H. Trautmann, “BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems,” in Parallel Problem Solving from Nature (PPSN XVII), 2022, pp. 192–206, doi: 10.1007/978-3-031-14714-2_14.' mla: 'Heins, Jonathan, et al. “BBE: Basin-Based Evaluation of Multimodal Multi-Objective Optimization Problems.” Parallel Problem Solving from Nature (PPSN XVII), edited by Günter Rudolph et al., Springer International Publishing, 2022, pp. 192–206, doi:10.1007/978-3-031-14714-2_14.' short: 'J. Heins, J. Rook, L. Schäpermeier, P. Kerschke, J. Bossek, H. Trautmann, in: G. Rudolph, A.V. Kononova, H. Aguirre, P. Kerschke, G. Ochoa, T. Tusar (Eds.), Parallel Problem Solving from Nature (PPSN XVII), Springer International Publishing, Cham, 2022, pp. 192–206.' date_created: 2023-11-14T15:58:58Z date_updated: 2023-12-13T10:47:50Z department: - _id: '819' doi: 10.1007/978-3-031-14714-2_14 editor: - first_name: Günter full_name: Rudolph, Günter last_name: Rudolph - first_name: Anna V. full_name: Kononova, Anna V. last_name: Kononova - first_name: Hernán full_name: Aguirre, Hernán last_name: Aguirre - first_name: Pascal full_name: Kerschke, Pascal last_name: Kerschke - first_name: Gabriela full_name: Ochoa, Gabriela last_name: Ochoa - first_name: Tea full_name: Tusar, Tea last_name: Tusar extern: '1' keyword: - Anytime behavior - Benchmarking - Continuous optimization - Multi-objective optimization - Multimodality - Performance metric language: - iso: eng page: 192–206 place: Cham publication: Parallel Problem Solving from Nature (PPSN XVII) publication_identifier: isbn: - 978-3-031-14714-2 publisher: Springer International Publishing series_title: Lecture Notes in Computer Science status: public title: 'BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems' type: conference user_id: '102979' year: '2022' ... --- _id: '48896' abstract: - lang: eng text: Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space. author: - first_name: Jeroen full_name: Rook, Jeroen last_name: Rook - first_name: Heike full_name: Trautmann, Heike last_name: Trautmann - first_name: Jakob full_name: Bossek, Jakob id: '102979' last_name: Bossek orcid: 0000-0002-4121-4668 - first_name: Christian full_name: Grimme, Christian last_name: Grimme citation: ama: 'Rook J, Trautmann H, Bossek J, Grimme C. On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO’22. Association for Computing Machinery; 2022:356–359. doi:10.1145/3520304.3528998' apa: Rook, J., Trautmann, H., Bossek, J., & Grimme, C. (2022). On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. https://doi.org/10.1145/3520304.3528998 bibtex: '@inproceedings{Rook_Trautmann_Bossek_Grimme_2022, place={New York, NY, USA}, series={GECCO’22}, title={On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}, DOI={10.1145/3520304.3528998}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference Companion}, publisher={Association for Computing Machinery}, author={Rook, Jeroen and Trautmann, Heike and Bossek, Jakob and Grimme, Christian}, year={2022}, pages={356–359}, collection={GECCO’22} }' chicago: 'Rook, Jeroen, Heike Trautmann, Jakob Bossek, and Christian Grimme. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 356–359. GECCO’22. New York, NY, USA: Association for Computing Machinery, 2022. https://doi.org/10.1145/3520304.3528998.' ieee: 'J. Rook, H. Trautmann, J. Bossek, and C. Grimme, “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems,” in Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022, pp. 356–359, doi: 10.1145/3520304.3528998.' mla: Rook, Jeroen, et al. “On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems.” Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, 2022, pp. 356–359, doi:10.1145/3520304.3528998. short: 'J. Rook, H. Trautmann, J. Bossek, C. Grimme, in: Proceedings of the Genetic and Evolutionary Computation Conference Companion, Association for Computing Machinery, New York, NY, USA, 2022, pp. 356–359.' date_created: 2023-11-14T15:59:00Z date_updated: 2023-12-13T10:50:24Z department: - _id: '819' doi: 10.1145/3520304.3528998 extern: '1' keyword: - configuration - multi-modality - multi-objective optimization language: - iso: eng page: 356–359 place: New York, NY, USA publication: Proceedings of the Genetic and Evolutionary Computation Conference Companion publication_identifier: isbn: - 978-1-4503-9268-6 publisher: Association for Computing Machinery series_title: GECCO’22 status: public title: On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems type: conference user_id: '102979' year: '2022' ... --- _id: '33997' abstract: - lang: eng text: "Digital platforms have already led to disruptions in multiple B2C markets and are becoming increasingly dominant in B2B markets. As a result, more and more companies are trying to participate in the platform economy. However, the successful development and operation of a digital platform is associated with significant challenges, which leads to 85% of all platforms failing. A core challenge is the dynamic nature of the platform economy, with varying strategic objectives at different stages in the platform lifecycle. Platform operators must continuously monitor platform progress and adjust their strategy.\r\nUtilizing action research in the real-world platform project AI Marketplace, we developed a lifecycle-oriented performance management approach for digital platforms in B2B markets. It enables platform operators to reflect on their position in the platform lifecycle, derive relevant strategic objectives, and monitor them with suitable key performance indicators. Hence, allowing them to secure the long-term success of their platform business." author: - first_name: Leon full_name: Özcan, Leon id: '45137' last_name: Özcan - first_name: Lisa Irene full_name: Kirchberg, Lisa Irene id: '63192' last_name: Kirchberg - first_name: Christian full_name: Koldewey, Christian last_name: Koldewey - first_name: Roman full_name: Dumitrescu, Roman last_name: Dumitrescu citation: ama: 'Özcan L, Kirchberg LI, Koldewey C, Dumitrescu R. Performance Management Approach for Digital Platforms in B2B Markets. In: Bitran I, Bitetti L, Conn S, et al., eds. The Role of Innovation: Past, Present, Future. ; 2022.' apa: 'Özcan, L., Kirchberg, L. I., Koldewey, C., & Dumitrescu, R. (2022). Performance Management Approach for Digital Platforms in B2B Markets. In I. Bitran, L. Bitetti, S. Conn, J. Fishburn, E. Huizingh, M. Torkkeli, & J. Yang (Eds.), The Role of Innovation: Past, Present, Future.' bibtex: '@inproceedings{Özcan_Kirchberg_Koldewey_Dumitrescu_2022, place={Athens}, title={Performance Management Approach for Digital Platforms in B2B Markets}, booktitle={The Role of Innovation: Past, Present, Future}, author={Özcan, Leon and Kirchberg, Lisa Irene and Koldewey, Christian and Dumitrescu, Roman}, editor={Bitran, Iain and Bitetti, Leandro and Conn, Steffen and Fishburn, Jessica and Huizingh, Eelko and Torkkeli, Marko and Yang, Jialei}, year={2022} }' chicago: 'Özcan, Leon, Lisa Irene Kirchberg, Christian Koldewey, and Roman Dumitrescu. “Performance Management Approach for Digital Platforms in B2B Markets.” In The Role of Innovation: Past, Present, Future, edited by Iain Bitran, Leandro Bitetti, Steffen Conn, Jessica Fishburn, Eelko Huizingh, Marko Torkkeli, and Jialei Yang. Athens, 2022.' ieee: 'L. Özcan, L. I. Kirchberg, C. Koldewey, and R. Dumitrescu, “Performance Management Approach for Digital Platforms in B2B Markets,” in The Role of Innovation: Past, Present, Future, Athens, 2022.' mla: 'Özcan, Leon, et al. “Performance Management Approach for Digital Platforms in B2B Markets.” The Role of Innovation: Past, Present, Future, edited by Iain Bitran et al., 2022.' short: 'L. Özcan, L.I. Kirchberg, C. Koldewey, R. Dumitrescu, in: I. Bitran, L. Bitetti, S. Conn, J. Fishburn, E. Huizingh, M. Torkkeli, J. Yang (Eds.), The Role of Innovation: Past, Present, Future, Athens, 2022.' conference: end_date: 2022-11-30 location: Athens name: ISPIM Connects Athens start_date: 2022-11-28 date_created: 2022-11-04T07:31:57Z date_updated: 2024-09-30T07:59:27Z ddc: - '600' department: - _id: '563' editor: - first_name: Iain full_name: Bitran, Iain last_name: Bitran - first_name: Leandro full_name: Bitetti, Leandro last_name: Bitetti - first_name: Steffen full_name: ' Conn, Steffen' last_name: ' Conn' - first_name: Jessica full_name: Fishburn, Jessica last_name: Fishburn - first_name: 'Eelko ' full_name: 'Huizingh, Eelko ' last_name: Huizingh - first_name: Marko full_name: Torkkeli, Marko last_name: Torkkeli - first_name: Jialei full_name: Yang, Jialei last_name: Yang file: - access_level: closed content_type: application/pdf creator: loezcan date_created: 2022-11-04T07:30:29Z date_updated: 2022-11-04T07:30:29Z file_id: '33998' file_name: '[ÖKK+22] Performance Management Approach for Digital Platforms in B2B Markets.pdf' file_size: 694337 relation: main_file success: 1 file_date_updated: 2022-11-04T07:30:29Z has_accepted_license: '1' keyword: - Digital Platform - Two-Sided Market - Multi-Sided Market - Platform Lifecycle - Platform Monitoring - Performance Management language: - iso: eng place: Athens publication: 'The Role of Innovation: Past, Present, Future' publication_identifier: unknown: - 978-952-65069-1-3 status: public title: Performance Management Approach for Digital Platforms in B2B Markets type: conference user_id: '1112' year: '2022' ... --- _id: '31066' abstract: - lang: eng text: 'While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model. ' author: - first_name: Oliver full_name: Schön, Oliver last_name: Schön - first_name: Ricarda-Samantha full_name: Götte, Ricarda-Samantha id: '43992' last_name: Götte - first_name: Julia full_name: Timmermann, Julia id: '15402' last_name: Timmermann citation: ama: 'Schön O, Götte R-S, Timmermann J. Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. In: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022). Vol 55. ; 2022:19-24. doi:https://doi.org/10.1016/j.ifacol.2022.07.282' apa: Schön, O., Götte, R.-S., & Timmermann, J. (2022). Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems. 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55(12), 19–24. https://doi.org/10.1016/j.ifacol.2022.07.282 bibtex: '@inproceedings{Schön_Götte_Timmermann_2022, title={Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}, volume={55}, DOI={https://doi.org/10.1016/j.ifacol.2022.07.282}, number={12}, booktitle={14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)}, author={Schön, Oliver and Götte, Ricarda-Samantha and Timmermann, Julia}, year={2022}, pages={19–24} }' chicago: Schön, Oliver, Ricarda-Samantha Götte, and Julia Timmermann. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” In 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 55:19–24, 2022. https://doi.org/10.1016/j.ifacol.2022.07.282. ieee: 'O. Schön, R.-S. Götte, and J. Timmermann, “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems,” in 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), Casablanca, Morocco, 2022, vol. 55, no. 12, pp. 19–24, doi: https://doi.org/10.1016/j.ifacol.2022.07.282.' mla: Schön, Oliver, et al. “Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems.” 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), vol. 55, no. 12, 2022, pp. 19–24, doi:https://doi.org/10.1016/j.ifacol.2022.07.282. short: 'O. Schön, R.-S. Götte, J. Timmermann, in: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022), 2022, pp. 19–24.' conference: end_date: 2022-07-01 location: Casablanca, Morocco name: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022) start_date: 2022-06-29 date_created: 2022-05-05T06:22:55Z date_updated: 2024-11-13T08:43:16Z department: - _id: '153' - _id: '880' doi: https://doi.org/10.1016/j.ifacol.2022.07.282 intvolume: ' 55' issue: '12' keyword: - neural networks - physics-guided - data-driven - multi-objective optimization - system identification - machine learning - dynamical systems language: - iso: eng page: 19-24 publication: 14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022) quality_controlled: '1' status: public title: Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems type: conference user_id: '43992' volume: 55 year: '2022' ... --- _id: '21004' abstract: - lang: eng text: 'Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers.' author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Alexander full_name: Tornede, Alexander id: '38209' last_name: Tornede - first_name: Felix full_name: Mohr, Felix last_name: Mohr - first_name: Eyke full_name: Hüllermeier, Eyke id: '48129' last_name: Hüllermeier citation: ama: 'Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence. Published online 2021:1-1. doi:10.1109/tpami.2021.3051276' apa: 'Wever, M. D., Tornede, A., Mohr, F., & Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1–1. https://doi.org/10.1109/tpami.2021.3051276' bibtex: '@article{Wever_Tornede_Mohr_Hüllermeier_2021, title={AutoML for Multi-Label Classification: Overview and Empirical Evaluation}, DOI={10.1109/tpami.2021.3051276}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}, year={2021}, pages={1–1} }' chicago: 'Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 1–1. https://doi.org/10.1109/tpami.2021.3051276.' ieee: 'M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label Classification: Overview and Empirical Evaluation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1–1, 2021, doi: 10.1109/tpami.2021.3051276.' mla: 'Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, pp. 1–1, doi:10.1109/tpami.2021.3051276.' short: M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1. date_created: 2021-01-16T14:48:13Z date_updated: 2022-01-06T06:54:42Z department: - _id: '34' - _id: '355' - _id: '26' doi: 10.1109/tpami.2021.3051276 keyword: - Automated Machine Learning - Multi Label Classification - Hierarchical Planning - Bayesian Optimization language: - iso: eng page: 1-1 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: IEEE Transactions on Pattern Analysis and Machine Intelligence publication_identifier: issn: - 0162-8828 - 2160-9292 - 1939-3539 publication_status: published status: public title: 'AutoML for Multi-Label Classification: Overview and Empirical Evaluation' type: journal_article user_id: '5786' year: '2021' ... --- _id: '21808' abstract: - lang: eng text: "Modern services consist of interconnected components,e.g., microservices in a service mesh or machine learning functions in a pipeline. These services can scale and run across multiple network nodes on demand. To process incoming traffic, service components have to be instantiated and traffic assigned to these instances, taking capacities, changing demands, and Quality of Service (QoS) requirements into account. This challenge is usually solved with custom approaches designed by experts. While this typically works well for the considered scenario, the models often rely on unrealistic assumptions or on knowledge that is not available in practice (e.g., a priori knowledge).\r\n\r\nWe propose DeepCoord, a novel deep reinforcement learning approach that learns how to best coordinate services and is geared towards realistic assumptions. It interacts with the network and relies on available, possibly delayed monitoring information. Rather than defining a complex model or an algorithm on how to achieve an objective, our model-free approach adapts to various objectives and traffic patterns. An agent is trained offline without expert knowledge and then applied online with minimal overhead. Compared to a state-of-the-art heuristic, DeepCoord significantly improves flow throughput (up to 76%) and overall network utility (more than 2x) on realworld network topologies and traffic traces. It also supports optimizing multiple, possibly competing objectives, learns to respect QoS requirements, generalizes to scenarios with unseen, stochastic traffic, and scales to large real-world networks. For reproducibility and reuse, our code is publicly available." article_type: original author: - first_name: Stefan Balthasar full_name: Schneider, Stefan Balthasar id: '35343' last_name: Schneider orcid: 0000-0001-8210-4011 - first_name: Ramin full_name: Khalili, Ramin last_name: Khalili - first_name: Adnan full_name: Manzoor, Adnan last_name: Manzoor - first_name: Haydar full_name: Qarawlus, Haydar last_name: Qarawlus - first_name: Rafael full_name: Schellenberg, Rafael last_name: Schellenberg - first_name: Holger full_name: Karl, Holger id: '126' last_name: Karl - first_name: Artur full_name: Hecker, Artur last_name: Hecker citation: ama: Schneider SB, Khalili R, Manzoor A, et al. Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. Transactions on Network and Service Management. 2021. doi:10.1109/TNSM.2021.3076503 apa: Schneider, S. B., Khalili, R., Manzoor, A., Qarawlus, H., Schellenberg, R., Karl, H., & Hecker, A. (2021). Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning. Transactions on Network and Service Management. https://doi.org/10.1109/TNSM.2021.3076503 bibtex: '@article{Schneider_Khalili_Manzoor_Qarawlus_Schellenberg_Karl_Hecker_2021, title={Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning}, DOI={10.1109/TNSM.2021.3076503}, journal={Transactions on Network and Service Management}, publisher={IEEE}, author={Schneider, Stefan Balthasar and Khalili, Ramin and Manzoor, Adnan and Qarawlus, Haydar and Schellenberg, Rafael and Karl, Holger and Hecker, Artur}, year={2021} }' chicago: Schneider, Stefan Balthasar, Ramin Khalili, Adnan Manzoor, Haydar Qarawlus, Rafael Schellenberg, Holger Karl, and Artur Hecker. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” Transactions on Network and Service Management, 2021. https://doi.org/10.1109/TNSM.2021.3076503. ieee: S. B. Schneider et al., “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning,” Transactions on Network and Service Management, 2021. mla: Schneider, Stefan Balthasar, et al. “Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning.” Transactions on Network and Service Management, IEEE, 2021, doi:10.1109/TNSM.2021.3076503. short: S.B. Schneider, R. Khalili, A. Manzoor, H. Qarawlus, R. Schellenberg, H. Karl, A. Hecker, Transactions on Network and Service Management (2021). date_created: 2021-04-27T08:04:16Z date_updated: 2022-01-06T06:55:15Z ddc: - '000' department: - _id: '75' doi: 10.1109/TNSM.2021.3076503 file: - access_level: open_access content_type: application/pdf creator: stschn date_created: 2021-04-27T08:01:26Z date_updated: 2021-04-27T08:01:26Z description: Author version of the accepted paper file_id: '21809' file_name: ris-accepted-version.pdf file_size: 4172270 relation: main_file file_date_updated: 2021-04-27T08:01:26Z has_accepted_license: '1' keyword: - network management - service management - coordination - reinforcement learning - self-learning - self-adaptation - multi-objective language: - iso: eng oa: '1' project: - _id: '1' name: SFB 901 - _id: '4' name: SFB 901 - Project Area C - _id: '16' name: SFB 901 - Subproject C4 publication: Transactions on Network and Service Management publisher: IEEE status: public title: Self-Learning Multi-Objective Service Coordination Using Deep Reinforcement Learning type: journal_article user_id: '35343' year: '2021' ... --- _id: '33854' abstract: - lang: eng text: "Macrodiversity is a key technique to increase the capacity of mobile networks. It can be realized using coordinated multipoint (CoMP), simultaneously connecting users to multiple overlapping cells. Selecting which users to serve by how many and which cells is NP-hard but needs to happen continuously in real time as users move and channel state changes. Existing approaches often require strict assumptions about or perfect knowledge of the underlying radio system, its resource allocation scheme, or user movements, none of which is readily available in practice.\r\n\r\nInstead, we propose three novel self-learning and self-adapting approaches using model-free deep reinforcement learning (DRL): DeepCoMP, DD-CoMP, and D3-CoMP. DeepCoMP leverages central observations and control of all users to select cells almost optimally. DD-CoMP and D3-CoMP use multi-agent DRL, which allows distributed, robust, and highly scalable coordination. All three approaches learn from experience and self-adapt to varying scenarios, reaching 2x higher Quality of Experience than other approaches. They have very few built-in assumptions and do not need prior system knowledge, making them more robust to change and better applicable in practice than existing approaches." author: - first_name: Stefan Balthasar full_name: Schneider, Stefan Balthasar id: '35343' last_name: Schneider orcid: 0000-0001-8210-4011 - first_name: Holger full_name: Karl, Holger id: '126' last_name: Karl - first_name: Ramin full_name: Khalili, Ramin last_name: Khalili - first_name: Artur full_name: Hecker, Artur last_name: Hecker citation: ama: 'Schneider SB, Karl H, Khalili R, Hecker A. DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning.; 2021.' apa: 'Schneider, S. B., Karl, H., Khalili, R., & Hecker, A. (2021). DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning.' bibtex: '@book{Schneider_Karl_Khalili_Hecker_2021, title={DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning}, author={Schneider, Stefan Balthasar and Karl, Holger and Khalili, Ramin and Hecker, Artur}, year={2021} }' chicago: 'Schneider, Stefan Balthasar, Holger Karl, Ramin Khalili, and Artur Hecker. DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.' ieee: 'S. B. Schneider, H. Karl, R. Khalili, and A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning. 2021.' mla: 'Schneider, Stefan Balthasar, et al. DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning. 2021.' short: 'S.B. Schneider, H. Karl, R. Khalili, A. Hecker, DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning, 2021.' date_created: 2022-10-20T16:44:19Z date_updated: 2022-11-18T09:59:27Z ddc: - '004' department: - _id: '75' file: - access_level: open_access content_type: application/pdf creator: stschn date_created: 2022-10-20T16:41:10Z date_updated: 2022-10-20T16:41:10Z file_id: '33855' file_name: preprint.pdf file_size: 2521656 relation: main_file file_date_updated: 2022-10-20T16:41:10Z has_accepted_license: '1' keyword: - mobility management - coordinated multipoint - CoMP - cell selection - resource management - reinforcement learning - multi agent - MARL - self-learning - self-adaptation - QoE language: - iso: eng oa: '1' project: - _id: '4' name: 'SFB 901 - C: SFB 901 - Project Area C' - _id: '16' name: 'SFB 901 - C4: SFB 901 - Subproject C4' - _id: '1' name: 'SFB 901: SFB 901' status: public title: 'DeepCoMP: Coordinated Multipoint Using Multi-Agent Deep Reinforcement Learning' type: working_paper user_id: '477' year: '2021' ... --- _id: '25046' abstract: - lang: eng text: While increasing digitalization enables multiple advantages for a reliable operation of technical systems, a remaining challenge in the context of condition monitoring is seen in suitable consideration of uncertainties affecting the monitored system. Therefore, a suitable prognostic approach to predict the remaining useful lifetime of complex technical systems is required. To handle different kinds of uncertainties, a novel Multi-Model-Particle Filtering-based prognostic approach is developed and evaluated by the use case of rubber-metal-elements. These elements are maintained preventively due to the strong influence of uncertainties on their behavior. In this paper, two measurement quantities are compared concerning their ability to establish a prediction of the remaining useful lifetime of the monitored elements and the influence of present uncertainties. Based on three performance indices, the results are evaluated. A comparison with predictions of a classical Particle Filter underlines the superiority of the developed Multi-Model-Particle Filter. Finally, the value of the developed method for enabling condition monitoring of technical systems related to uncertainties is given exemplary by a comparison between the preventive and the predictive maintenance strategy for the use case. article_number: '210' article_type: original author: - first_name: Amelie full_name: Bender, Amelie id: '54290' last_name: Bender citation: ama: Bender A. A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions. Machines. 2021;9(10). doi:10.3390/machines9100210 apa: Bender, A. (2021). A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions. Machines, 9(10), Article 210. https://doi.org/10.3390/machines9100210 bibtex: '@article{Bender_2021, title={A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions}, volume={9}, DOI={10.3390/machines9100210}, number={10210}, journal={Machines}, author={Bender, Amelie}, year={2021} }' chicago: Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions.” Machines 9, no. 10 (2021). https://doi.org/10.3390/machines9100210. ieee: 'A. Bender, “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions,” Machines, vol. 9, no. 10, Art. no. 210, 2021, doi: 10.3390/machines9100210.' mla: Bender, Amelie. “A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions.” Machines, vol. 9, no. 10, 210, 2021, doi:10.3390/machines9100210. short: A. Bender, Machines 9 (2021). date_created: 2021-09-27T07:07:58Z date_updated: 2022-11-03T11:42:46Z department: - _id: '151' doi: 10.3390/machines9100210 intvolume: ' 9' issue: '10' keyword: - prognostics - RUL predictions - particle filter - uncertainty consideration - Multi-Model-Particle Filter - model-based approach - rubber-metal-elements - predictive maintenance language: - iso: eng main_file_link: - open_access: '1' url: https://www.mdpi.com/2075-1702/9/10/210 oa: '1' publication: Machines publication_identifier: issn: - 2075-1702 publication_status: published quality_controlled: '1' status: public title: A Multi-Model-Particle Filtering-Based Prognostic Approach to Consider Uncertainties in RUL Predictions type: journal_article user_id: '54290' volume: 9 year: '2021' ... --- _id: '46318' abstract: - lang: eng text: 'Multi-objective (MO) optimization, i.e., the simultaneous optimization of multiple conflicting objectives, is gaining more and more attention in various research areas, such as evolutionary computation, machine learning (e.g., (hyper-)parameter optimization), or logistics (e.g., vehicle routing). Many works in this domain mention the structural problem property of multimodality as a challenge from two classical perspectives: (1) finding all globally optimal solution sets, and (2) avoiding to get trapped in local optima. Interestingly, these streams seem to transfer many traditional concepts of single-objective (SO) optimization into claims, assumptions, or even terminology regarding the MO domain, but mostly neglect the understanding of the structural properties as well as the algorithmic search behavior on a problem’s landscape. However, some recent works counteract this trend, by investigating the fundamentals and characteristics of MO problems using new visualization techniques and gaining surprising insights. Using these visual insights, this work proposes a step towards a unified terminology to capture multimodality and locality in a broader way than it is usually done. This enables us to investigate current research activities in multimodal continuous MO optimization and to highlight new implications and promising research directions for the design of benchmark suites, the discovery of MO landscape features, the development of new MO (or even SO) optimization algorithms, and performance indicators. For all these topics, we provide a review of ideas and methods but also an outlook on future challenges, research potential and perspectives that result from recent developments.' author: - first_name: Christian full_name: Grimme, Christian last_name: Grimme - first_name: Pascal full_name: Kerschke, Pascal last_name: Kerschke - first_name: Pelin full_name: Aspar, Pelin last_name: Aspar - first_name: Heike full_name: Trautmann, Heike id: '100740' last_name: Trautmann orcid: 0000-0002-9788-8282 - first_name: Mike full_name: Preuss, Mike last_name: Preuss - first_name: André H. full_name: Deutz, André H. last_name: Deutz - first_name: Hao full_name: Wang, Hao last_name: Wang - first_name: Michael full_name: Emmerich, Michael last_name: Emmerich citation: ama: 'Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research. 2021;136:105489. doi:https://doi.org/10.1016/j.cor.2021.105489' apa: 'Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., & Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. Computers & Operations Research, 136, 105489. https://doi.org/10.1016/j.cor.2021.105489' bibtex: '@article{Grimme_Kerschke_Aspar_Trautmann_Preuss_Deutz_Wang_Emmerich_2021, title={Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization}, volume={136}, DOI={https://doi.org/10.1016/j.cor.2021.105489}, journal={Computers & Operations Research}, author={Grimme, Christian and Kerschke, Pascal and Aspar, Pelin and Trautmann, Heike and Preuss, Mike and Deutz, André H. and Wang, Hao and Emmerich, Michael}, year={2021}, pages={105489} }' chicago: 'Grimme, Christian, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, and Michael Emmerich. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” Computers & Operations Research 136 (2021): 105489. https://doi.org/10.1016/j.cor.2021.105489.' ieee: 'C. Grimme et al., “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” Computers & Operations Research, vol. 136, p. 105489, 2021, doi: https://doi.org/10.1016/j.cor.2021.105489.' mla: 'Grimme, Christian, et al. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” Computers & Operations Research, vol. 136, 2021, p. 105489, doi:https://doi.org/10.1016/j.cor.2021.105489.' short: C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers & Operations Research 136 (2021) 105489. date_created: 2023-08-04T07:28:34Z date_updated: 2023-10-16T12:58:42Z department: - _id: '34' - _id: '819' doi: https://doi.org/10.1016/j.cor.2021.105489 intvolume: ' 136' keyword: - Multimodal optimization - Multi-objective continuous optimization - Landscape analysis - Visualization - Benchmarking - Theory - Algorithms language: - iso: eng page: '105489' publication: Computers & Operations Research publication_identifier: issn: - 0305-0548 status: public title: 'Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization' type: journal_article user_id: '15504' volume: 136 year: '2021' ... --- _id: '17860' abstract: - lang: eng text: "Purpose\r\nThe purpose of this paper is to identify strategic options and challenges that arise when an industrial firm moves from providing smart service toward providing a platform.\r\n\r\nDesign/methodology/approach\r\nThis conceptual study takes on a multidisciplinary research perspective that integrates concepts, theories and insights from service management and marketing, information systems and platform economics.\r\n\r\nFindings\r\nThe paper outlines three platform types – smart data platform, smart product platform and matching platform – as strategic options for firms that wish to evolve from smart service providers to platform providers.\r\n\r\nResearch limitations/implications\r\nInvestigating smart service platforms calls for launching interdisciplinary research initiatives. Promising research avenues are outlined to span boundaries that separate different research disciplines today.\r\n\r\nPractical implications\r\nManaging a successful transition from providing smart service toward providing a platform requires making significant investments in IT, platform-related capabilities and skills, as well as implement new approaches toward relationship management and brand-building.\r\n\r\nOriginality/value\r\nThe findings described in this paper are valuable to researchers in multiple disciplines seeking to develop and to justify theory related to platforms in industrial scenarios." article_type: original author: - first_name: Daniel full_name: Beverungen, Daniel id: '59677' last_name: Beverungen - first_name: Dennis full_name: Kundisch, Dennis id: '21117' last_name: Kundisch - first_name: Nancy full_name: Wünderlich, Nancy id: '36392' last_name: Wünderlich citation: ama: 'Beverungen D, Kundisch D, Wünderlich N. Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers. Journal of Service Management. 2021;32(4):507-532. doi:10.1108/JOSM-03-2020-0066' apa: 'Beverungen, D., Kundisch, D., & Wünderlich, N. (2021). Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers. Journal of Service Management, 32(4), 507–532. https://doi.org/10.1108/JOSM-03-2020-0066' bibtex: '@article{Beverungen_Kundisch_Wünderlich_2021, title={Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers}, volume={32}, DOI={10.1108/JOSM-03-2020-0066}, number={4}, journal={Journal of Service Management}, publisher={Emerald Insight}, author={Beverungen, Daniel and Kundisch, Dennis and Wünderlich, Nancy}, year={2021}, pages={507–532} }' chicago: 'Beverungen, Daniel, Dennis Kundisch, and Nancy Wünderlich. “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers.” Journal of Service Management 32, no. 4 (2021): 507–32. https://doi.org/10.1108/JOSM-03-2020-0066.' ieee: 'D. Beverungen, D. Kundisch, and N. Wünderlich, “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers,” Journal of Service Management, vol. 32, no. 4, pp. 507–532, 2021, doi: 10.1108/JOSM-03-2020-0066.' mla: 'Beverungen, Daniel, et al. “Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers.” Journal of Service Management, vol. 32, no. 4, Emerald Insight, 2021, pp. 507–32, doi:10.1108/JOSM-03-2020-0066.' short: D. Beverungen, D. Kundisch, N. Wünderlich, Journal of Service Management 32 (2021) 507–532. date_created: 2020-08-12T12:12:36Z date_updated: 2024-04-18T12:46:37Z ddc: - '380' department: - _id: '276' - _id: '181' doi: 10.1108/JOSM-03-2020-0066 intvolume: ' 32' issue: '4' keyword: - Smart service - Platform - Interdisciplinary research - Manufacturing company - Smart service provider - Platform economics - Information systems - Multi-sided markets - Business-to-business (B2B) markets language: - iso: eng page: 507-532 project: - _id: '1' grant_number: '160364472' name: SFB 901 - _id: '4' name: SFB 901 - Project Area C - _id: '17' name: SFB 901 - Subproject C5 publication: Journal of Service Management publication_identifier: issn: - 507-532 publication_status: published publisher: Emerald Insight quality_controlled: '1' status: public title: 'Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers' type: journal_article user_id: '59677' volume: 32 year: '2021' ... --- _id: '22724' abstract: - lang: eng text: "\r\nPredictive Maintenance as a desirable maintenance strategy in industrial applications relies on suitable condition monitoring solutions to reduce costs and risks of the monitored technical systems. In general, those solutions utilize model-based or data-driven methods to diagnose the current state or predict future states of monitored technical systems. However, both methods have their advantages and drawbacks. Combining both methods can improve uncertainty consideration and accuracy. Different combination approaches of those hybrid methods exist to exploit synergy effects. The choice of an appropriate approach depends on different requirements and the goal behind the selection of a hybrid approach.\r\n\r\n \r\n\r\nIn this work, the hybrid approach for estimating remaining useful lifetime takes potential uncertainties into account. Therefore, a data-driven estimation of new measurements is integrated within a model-based method. To consider uncertainties within the system, a differentiation between different system behavior is realized throughout diverse states of degradation.\r\n\r\nThe developed hybrid prediction approach bases on a particle filtering method combined with a machine learning method, to estimate the remaining useful lifetime of technical systems. Particle filtering as a Monte Carlo simulation technique is suitable to map and propagate uncertainties. Moreover, it is a state-of-the-art model-based method for predicting remaining useful lifetime of technical systems. To integrate uncertainties a multi-model particle filtering approach is employed. In general, resampling as a part of the particle filtering approach has the potential to lead to an accurate prediction. However, in the case where no future measurements are available, it may increase the uncertainty of the prediction. By estimating new measurements, those uncertainties are reduced within the data-driven part of the approach. Hence, both parts of the hybrid approach strive to account for and reduce uncertainties.\r\n\r\n \r\n\r\nRubber-metal-elements are employed as a use-case to evaluate the developed approach. Rubber-metal-elements, which are used to isolate vibrations in various systems, such as railways, trucks and wind turbines, show various uncertainties in their behavior and their degradation. Those uncertainties are caused by diverse inner and outer factors, such as manufacturing influences and operating conditions. By expert knowledge the influences are described, analyzed and if possible reduced. However, the remaining uncertainties are considered within the hybrid prediction method. Relative temperature is the selected measurand to describe the element’s degradation. In lifetime tests, it is measured as the difference between the element’s temperature and the ambient temperature. Thereby, the influence of the ambient temperature on the element’s temperature is taken into account. Those elements show three typical states of degradation that are identified within the temperature measurements. Depending on the particular state of degradation a new measurement is estimated within the hybrid approach to reduce potential uncertainties.\r\n\r\nFinally, the performance of the developed hybrid method is compared to a model-based method for estimating the remaining useful lifetime of the same elements. Suitable performance indices are implemented to underline the differences between the results." author: - first_name: Amelie full_name: Bender, Amelie id: '54290' last_name: Bender - first_name: Walter full_name: Sextro, Walter id: '21220' last_name: Sextro citation: ama: 'Bender A, Sextro W. Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In: Do P, King S, Fink Olga, eds. Proceedings of the European Conference of the PHM Society 2021. Vol 6. ; 2021. doi:https://doi.org/10.36001/phme.2021.v6i1.2843 ' apa: Bender, A., & Sextro, W. (2021). Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties. In P. Do, S. King, & Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021 (Vol. 6, Issue 1). https://doi.org/10.36001/phme.2021.v6i1.2843 bibtex: '@inproceedings{Bender_Sextro_2021, title={Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties}, volume={6}, DOI={https://doi.org/10.36001/phme.2021.v6i1.2843 }, number={1}, booktitle={Proceedings of the European Conference of the PHM Society 2021}, author={Bender, Amelie and Sextro, Walter}, editor={Do, Phuc and King, Steve and Fink, Olga}, year={2021} }' chicago: Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” In Proceedings of the European Conference of the PHM Society 2021, edited by Phuc Do, Steve King, and Olga Fink, Vol. 6, 2021. https://doi.org/10.36001/phme.2021.v6i1.2843 . ieee: 'A. Bender and W. Sextro, “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties,” in Proceedings of the European Conference of the PHM Society 2021, 2021, vol. 6, no. 1, doi: https://doi.org/10.36001/phme.2021.v6i1.2843 .' mla: Bender, Amelie, and Walter Sextro. “Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties.” Proceedings of the European Conference of the PHM Society 2021, edited by Phuc Do et al., vol. 6, no. 1, 2021, doi:https://doi.org/10.36001/phme.2021.v6i1.2843 . short: 'A. Bender, W. Sextro, in: P. Do, S. King, Olga Fink (Eds.), Proceedings of the European Conference of the PHM Society 2021, 2021.' conference: end_date: 2021-07-02 name: 6th European Conference of Prognostics and Health Management start_date: 2021-06-28 date_created: 2021-07-14T06:29:08Z date_updated: 2023-09-22T07:19:48Z department: - _id: '151' doi: 'https://doi.org/10.36001/phme.2021.v6i1.2843 ' editor: - first_name: 'Phuc ' full_name: 'Do, Phuc ' last_name: Do - first_name: Steve full_name: King, Steve last_name: King - first_name: ' Olga' full_name: Fink, Olga last_name: Fink intvolume: ' 6' issue: '1' keyword: - Hybrid prediction method - Multi-model particle filtering - Uncertainty quantification - RUL estimation language: - iso: eng main_file_link: - open_access: '1' url: https://papers.phmsociety.org/index.php/phme/article/view/2843 oa: '1' publication: Proceedings of the European Conference of the PHM Society 2021 publication_identifier: unknown: - 978-1-936263-34-9 publication_status: published quality_controlled: '1' status: public title: Hybrid Prediction Method for Remaining Useful Lifetime Estimation Considering Uncertainties type: conference user_id: '54290' volume: 6 year: '2021' ...