--- _id: '45824' abstract: - lang: eng text: As cognitive function is critical for muscle coordination, cognitive training may also improve neuromuscular control strategy and knee function following an anterior cruciate ligament reconstruction (ACLR). The purpose of this case-control study was to examine the effects of cognitive training on joint stiffness regulation in response to negative visual stimuli and knee function following ACLR. A total of 20 ACLR patients and 20 healthy controls received four weeks of online cognitive training. Executive function, joint stiffness in response to emotionally evocative visual stimuli (neutral, fearful, knee injury related), and knee function outcomes before and after the intervention were compared. Both groups improved executive function following the intervention (p = 0.005). The ACLR group had greater mid-range stiffness in response to fearful (p = 0.024) and injury-related pictures (p = 0.017) than neutral contents before the intervention, while no post-intervention stiffness differences were observed among picture types. The ACLR group showed better single-legged hop for distance after cognitive training (p = 0.047), while the healthy group demonstrated no improvement. Cognitive training enhanced executive function, which may reduce joint stiffness dysregulation in response to emotionally arousing images and improve knee function in ACLR patients, presumably by facilitating neural processing necessary for neuromuscular control. article_number: '1875' author: - first_name: Yong Woo full_name: An, Yong Woo last_name: An - first_name: Kyung-Min full_name: Kim, Kyung-Min last_name: Kim - first_name: Andrea full_name: DiTrani Lobacz, Andrea last_name: DiTrani Lobacz - first_name: Jochen full_name: Baumeister, Jochen id: '46' last_name: Baumeister orcid: 0000-0003-2683-5826 - first_name: Jill S. full_name: Higginson, Jill S. last_name: Higginson - first_name: Jeffrey full_name: Rosen, Jeffrey last_name: Rosen - first_name: Charles Buz full_name: Swanik, Charles Buz last_name: Swanik citation: ama: An YW, Kim K-M, DiTrani Lobacz A, et al. Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls. Healthcare. 2023;11(13). doi:10.3390/healthcare11131875 apa: An, Y. W., Kim, K.-M., DiTrani Lobacz, A., Baumeister, J., Higginson, J. S., Rosen, J., & Swanik, C. B. (2023). Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls. Healthcare, 11(13), Article 1875. https://doi.org/10.3390/healthcare11131875 bibtex: '@article{An_Kim_DiTrani Lobacz_Baumeister_Higginson_Rosen_Swanik_2023, title={Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls}, volume={11}, DOI={10.3390/healthcare11131875}, number={131875}, journal={Healthcare}, publisher={MDPI AG}, author={An, Yong Woo and Kim, Kyung-Min and DiTrani Lobacz, Andrea and Baumeister, Jochen and Higginson, Jill S. and Rosen, Jeffrey and Swanik, Charles Buz}, year={2023} }' chicago: An, Yong Woo, Kyung-Min Kim, Andrea DiTrani Lobacz, Jochen Baumeister, Jill S. Higginson, Jeffrey Rosen, and Charles Buz Swanik. “Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls.” Healthcare 11, no. 13 (2023). https://doi.org/10.3390/healthcare11131875. ieee: 'Y. W. An et al., “Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls,” Healthcare, vol. 11, no. 13, Art. no. 1875, 2023, doi: 10.3390/healthcare11131875.' mla: An, Yong Woo, et al. “Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls.” Healthcare, vol. 11, no. 13, 1875, MDPI AG, 2023, doi:10.3390/healthcare11131875. short: Y.W. An, K.-M. Kim, A. DiTrani Lobacz, J. Baumeister, J.S. Higginson, J. Rosen, C.B. Swanik, Healthcare 11 (2023). date_created: 2023-06-30T13:47:33Z date_updated: 2023-06-30T13:48:21Z department: - _id: '17' doi: 10.3390/healthcare11131875 intvolume: ' 11' issue: '13' keyword: - Health Information Management - Health Informatics - Health Policy - Leadership and Management language: - iso: eng publication: Healthcare publication_identifier: issn: - 2227-9032 publication_status: published publisher: MDPI AG status: public title: Cognitive Training Improves Joint Stiffness Regulation and Function in ACLR Patients Compared to Healthy Controls type: journal_article user_id: '46' volume: 11 year: '2023' ... --- _id: '33734' abstract: - lang: eng text: 'Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'''' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'''' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis' author: - first_name: N'Dah Jean full_name: KOUAGOU, N'Dah Jean id: '87189' last_name: KOUAGOU - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Caglar full_name: Demir, Caglar id: '43817' last_name: Demir - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: 'KOUAGOU NJ, Heindorf S, Demir C, Ngonga Ngomo A-C. Neural Class Expression Synthesis. In: Pesquita C, Jimenez-Ruiz E, McCusker J, et al., eds. The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023). Vol 13870. Springer International Publishing; 2023:209-226. doi:https://doi.org/10.1007/978-3-031-33455-9_13' apa: KOUAGOU, N. J., Heindorf, S., Demir, C., & Ngonga Ngomo, A.-C. (2023). Neural Class Expression Synthesis. In C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, & S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) (Vol. 13870, pp. 209–226). Springer International Publishing. https://doi.org/10.1007/978-3-031-33455-9_13 bibtex: '@inproceedings{KOUAGOU_Heindorf_Demir_Ngonga Ngomo_2023, title={Neural Class Expression Synthesis}, volume={13870}, DOI={https://doi.org/10.1007/978-3-031-33455-9_13}, booktitle={The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}, publisher={Springer International Publishing}, author={KOUAGOU, N’Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}, editor={Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}, year={2023}, pages={209–226} }' chicago: KOUAGOU, N’Dah Jean, Stefan Heindorf, Caglar Demir, and Axel-Cyrille Ngonga Ngomo. “Neural Class Expression Synthesis.” In The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita, Ernesto Jimenez-Ruiz, Jamie McCusker, Daniel Faria, Mauro Dragoni, Anastasia Dimou, Raphael Troncy, and Sven Hertling, 13870:209–26. Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-33455-9_13. ieee: 'N. J. KOUAGOU, S. Heindorf, C. Demir, and A.-C. Ngonga Ngomo, “Neural Class Expression Synthesis,” in The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Hersonissos, Crete, Greece, 2023, vol. 13870, pp. 209–226, doi: https://doi.org/10.1007/978-3-031-33455-9_13.' mla: KOUAGOU, N’Dah Jean, et al. “Neural Class Expression Synthesis.” The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), edited by Catia Pesquita et al., vol. 13870, Springer International Publishing, 2023, pp. 209–26, doi:https://doi.org/10.1007/978-3-031-33455-9_13. short: 'N.J. KOUAGOU, S. Heindorf, C. Demir, A.-C. Ngonga Ngomo, in: C. Pesquita, E. Jimenez-Ruiz, J. McCusker, D. Faria, M. Dragoni, A. Dimou, R. Troncy, S. Hertling (Eds.), The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023), Springer International Publishing, 2023, pp. 209–226.' conference: end_date: 2023-06-01 location: Hersonissos, Crete, Greece name: 20th Extended Semantic Web Conference start_date: 2023-05-28 date_created: 2022-10-15T19:20:11Z date_updated: 2023-07-02T18:10:02Z department: - _id: '574' - _id: '760' doi: https://doi.org/10.1007/978-3-031-33455-9_13 editor: - first_name: Catia full_name: Pesquita, Catia last_name: Pesquita - first_name: Ernesto full_name: Jimenez-Ruiz, Ernesto last_name: Jimenez-Ruiz - first_name: Jamie full_name: McCusker, Jamie last_name: McCusker - first_name: Daniel full_name: Faria, Daniel last_name: Faria - first_name: Mauro full_name: Dragoni, Mauro last_name: Dragoni - first_name: Anastasia full_name: Dimou, Anastasia last_name: Dimou - first_name: Raphael full_name: Troncy, Raphael last_name: Troncy - first_name: Sven full_name: Hertling, Sven last_name: Hertling external_id: unknown: - https://link.springer.com/chapter/10.1007/978-3-031-33455-9_13 intvolume: ' 13870' keyword: - Neural network - Concept learning - Description logics language: - iso: eng main_file_link: - open_access: '1' url: https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Kouagou_2023_Neural.pdf oa: '1' page: 209 - 226 project: - _id: '410' name: 'KnowGraphs: KnowGraphs: Knowledge Graphs at Scale' - _id: '407' grant_number: '101070305' name: 'ENEXA: Efficient Explainable Learning on Knowledge Graphs' - _id: '285' grant_number: NW21-059D name: 'SAIL: SAIL: SustAInable Life-cycle of Intelligent Socio-Technical Systems' publication: The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023) publication_identifier: unknown: - 978-3-031-33455-9 publication_status: published publisher: Springer International Publishing status: public title: Neural Class Expression Synthesis type: conference user_id: '11871' volume: 13870 year: '2023' ... --- _id: '37937' abstract: - lang: eng text: "Knowledge bases are widely used for information management on the web,\r\nenabling high-impact applications such as web search, question answering, and\r\nnatural language processing. They also serve as the backbone for automatic\r\ndecision systems, e.g. for medical diagnostics and credit scoring. As\r\nstakeholders affected by these decisions would like to understand their\r\nsituation and verify fair decisions, a number of explanation approaches have\r\nbeen proposed using concepts in description logics. However, the learned\r\nconcepts can become long and difficult to fathom for non-experts, even when\r\nverbalized. Moreover, long concepts do not immediately provide a clear path of\r\naction to change one's situation. Counterfactuals answering the question \"How\r\nmust feature values be changed to obtain a different classification?\" have been\r\nproposed as short, human-friendly explanations for tabular data. In this paper,\r\nwe transfer the notion of counterfactuals to description logics and propose the\r\nfirst algorithm for generating counterfactual explanations in the description\r\nlogic $\\mathcal{ELH}$. Counterfactual candidates are generated from concepts\r\nand the candidates with fewest feature changes are selected as counterfactuals.\r\nIn case of multiple counterfactuals, we rank them according to the likeliness\r\nof their feature combinations. For evaluation, we conduct a user survey to\r\ninvestigate which of the generated counterfactual candidates are preferred for\r\nexplanation by participants. In a second study, we explore possible use cases\r\nfor counterfactual explanations." author: - first_name: Leonie Nora full_name: Sieger, Leonie Nora id: '93402' last_name: Sieger - first_name: Stefan full_name: Heindorf, Stefan id: '11871' last_name: Heindorf orcid: 0000-0002-4525-6865 - first_name: Lukas full_name: Blübaum, Lukas last_name: Blübaum - first_name: Axel-Cyrille full_name: Ngonga Ngomo, Axel-Cyrille id: '65716' last_name: Ngonga Ngomo citation: ama: Sieger LN, Heindorf S, Blübaum L, Ngonga Ngomo A-C. Counterfactual Explanations for Concepts in ELH. arXiv:230105109. Published online 2023. apa: Sieger, L. N., Heindorf, S., Blübaum, L., & Ngonga Ngomo, A.-C. (2023). Counterfactual Explanations for Concepts in ELH. In arXiv:2301.05109. bibtex: '@article{Sieger_Heindorf_Blübaum_Ngonga Ngomo_2023, title={Counterfactual Explanations for Concepts in ELH}, journal={arXiv:2301.05109}, author={Sieger, Leonie Nora and Heindorf, Stefan and Blübaum, Lukas and Ngonga Ngomo, Axel-Cyrille}, year={2023} }' chicago: Sieger, Leonie Nora, Stefan Heindorf, Lukas Blübaum, and Axel-Cyrille Ngonga Ngomo. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023. ieee: L. N. Sieger, S. Heindorf, L. Blübaum, and A.-C. Ngonga Ngomo, “Counterfactual Explanations for Concepts in ELH,” arXiv:2301.05109. 2023. mla: Sieger, Leonie Nora, et al. “Counterfactual Explanations for Concepts in ELH.” ArXiv:2301.05109, 2023. short: L.N. Sieger, S. Heindorf, L. Blübaum, A.-C. Ngonga Ngomo, ArXiv:2301.05109 (2023). date_created: 2023-01-22T19:36:01Z date_updated: 2023-07-02T18:10:34Z department: - _id: '574' - _id: '760' external_id: arxiv: - '2301.05109' language: - iso: eng main_file_link: - url: https://arxiv.org/pdf/2301.05109.pdf publication: arXiv:2301.05109 status: public title: Counterfactual Explanations for Concepts in ELH type: preprint user_id: '11871' year: '2023' ... --- _id: '45244' abstract: - lang: eng text: "Label noise poses an important challenge in machine learning, especially in\r\ndeep learning, in which large models with high expressive power dominate the\r\nfield. Models of that kind are prone to memorizing incorrect labels, thereby\r\nharming generalization performance. Many methods have been proposed to address\r\nthis problem, including robust loss functions and more complex label correction\r\napproaches. Robust loss functions are appealing due to their simplicity, but\r\ntypically lack flexibility, while label correction usually adds substantial\r\ncomplexity to the training setup. In this paper, we suggest to address the\r\nshortcomings of both methodologies by \"ambiguating\" the target information,\r\nadding additional, complementary candidate labels in case the learner is not\r\nsufficiently convinced of the observed training label. More precisely, we\r\nleverage the framework of so-called superset learning to construct set-valued\r\ntargets based on a confidence threshold, which deliver imprecise yet more\r\nreliable beliefs about the ground-truth, effectively helping the learner to\r\nsuppress the memorization effect. In an extensive empirical evaluation, our\r\nmethod demonstrates favorable learning behavior on synthetic and real-world\r\nnoise, confirming the effectiveness in detecting and correcting erroneous\r\ntraining labels." author: - first_name: Julian full_name: Lienen, Julian last_name: Lienen - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: Lienen J, Hüllermeier E. Mitigating Label Noise through Data Ambiguation. arXiv:230513764. Published online 2023. apa: Lienen, J., & Hüllermeier, E. (2023). Mitigating Label Noise through Data Ambiguation. In arXiv:2305.13764. bibtex: '@article{Lienen_Hüllermeier_2023, title={Mitigating Label Noise through Data Ambiguation}, journal={arXiv:2305.13764}, author={Lienen, Julian and Hüllermeier, Eyke}, year={2023} }' chicago: Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023. ieee: J. Lienen and E. Hüllermeier, “Mitigating Label Noise through Data Ambiguation,” arXiv:2305.13764. 2023. mla: Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023. short: J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023). date_created: 2023-05-24T05:28:34Z date_updated: 2023-06-30T14:20:31Z external_id: arxiv: - '2305.13764' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/pdf/2305.13764.pdf oa: '1' publication: arXiv:2305.13764 status: public title: Mitigating Label Noise through Data Ambiguation type: preprint user_id: '44040' year: '2023' ... --- _id: '45828' abstract: - lang: eng text: This article presents the potential-dependent adsorption of two proteins, bovine serum albumin (BSA) and lysozyme (LYZ), on Ti6Al4V alloy at pH 7.4 and 37 °C. The adsorption process was studied on an electropolished alloy under cathodic and anodic overpotentials, compared to the open circuit potential (OCP). To analyze the adsorption process, various complementary interface analytical techniques were employed, including PM-IRRAS (polarization-modulation infrared reflection-absorption spectroscopy), AFM (atomic force microscopy), XPS (X-ray photoelectron spectroscopy), and E-QCM (electrochemical quartz crystal microbalance) measurements. The polarization experiments were conducted within a potential range where charging of the electric double layer dominates, and Faradaic currents can be disregarded. The findings highlight the significant influence of the interfacial charge distribution on the adsorption of BSA and LYZ onto the alloy surface. Furthermore, electrochemical analysis of the protein layers formed under applied overpotentials demonstrated improved corrosion protection properties. These studies provide valuable insights into protein adsorption on titanium alloys under physiological conditions, characterized by varying potentials of the passive alloy. author: - first_name: Belma full_name: Duderija, Belma id: '54863' last_name: Duderija - first_name: Alejandro full_name: González-Orive, Alejandro last_name: González-Orive - first_name: Christoph full_name: Ebbert, Christoph id: '7266' last_name: Ebbert - first_name: Vanessa full_name: Neßlinger, Vanessa last_name: Neßlinger - first_name: Adrian full_name: Keller, Adrian id: '48864' last_name: Keller orcid: 0000-0001-7139-3110 - first_name: Guido full_name: Grundmeier, Guido id: '194' last_name: Grundmeier citation: ama: Duderija B, González-Orive A, Ebbert C, Neßlinger V, Keller A, Grundmeier G. Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy. Molecules. 2023;28(13):5109. doi:10.3390/molecules28135109 apa: Duderija, B., González-Orive, A., Ebbert, C., Neßlinger, V., Keller, A., & Grundmeier, G. (2023). Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy. Molecules, 28(13), 5109. https://doi.org/10.3390/molecules28135109 bibtex: '@article{Duderija_González-Orive_Ebbert_Neßlinger_Keller_Grundmeier_2023, title={Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy}, volume={28}, DOI={10.3390/molecules28135109}, number={13}, journal={Molecules}, publisher={MDPI AG}, author={Duderija, Belma and González-Orive, Alejandro and Ebbert, Christoph and Neßlinger, Vanessa and Keller, Adrian and Grundmeier, Guido}, year={2023}, pages={5109} }' chicago: 'Duderija, Belma, Alejandro González-Orive, Christoph Ebbert, Vanessa Neßlinger, Adrian Keller, and Guido Grundmeier. “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy.” Molecules 28, no. 13 (2023): 5109. https://doi.org/10.3390/molecules28135109.' ieee: 'B. Duderija, A. González-Orive, C. Ebbert, V. Neßlinger, A. Keller, and G. Grundmeier, “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy,” Molecules, vol. 28, no. 13, p. 5109, 2023, doi: 10.3390/molecules28135109.' mla: Duderija, Belma, et al. “Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy.” Molecules, vol. 28, no. 13, MDPI AG, 2023, p. 5109, doi:10.3390/molecules28135109. short: B. Duderija, A. González-Orive, C. Ebbert, V. Neßlinger, A. Keller, G. Grundmeier, Molecules 28 (2023) 5109. date_created: 2023-07-03T08:06:28Z date_updated: 2023-07-03T08:07:55Z department: - _id: '302' doi: 10.3390/molecules28135109 intvolume: ' 28' issue: '13' keyword: - Chemistry (miscellaneous) - Analytical Chemistry - Organic Chemistry - Physical and Theoretical Chemistry - Molecular Medicine - Drug Discovery - Pharmaceutical Science language: - iso: eng page: '5109' publication: Molecules publication_identifier: issn: - 1420-3049 publication_status: published publisher: MDPI AG status: public title: Electrode Potential-Dependent Studies of Protein Adsorption on Ti6Al4V Alloy type: journal_article user_id: '48864' volume: 28 year: '2023' ... --- _id: '45829' author: - first_name: Adrian full_name: Keller, Adrian id: '48864' last_name: Keller orcid: 0000-0001-7139-3110 - first_name: Guido full_name: Grundmeier, Guido id: '194' last_name: Grundmeier citation: ama: 'Keller A, Grundmeier G. High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces. In: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier; 2023. doi:10.1016/b978-0-323-85669-0.00123-9' apa: Keller, A., & Grundmeier, G. (2023). High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces. In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier. https://doi.org/10.1016/b978-0-323-85669-0.00123-9 bibtex: '@inbook{Keller_Grundmeier_2023, title={High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces}, DOI={10.1016/b978-0-323-85669-0.00123-9}, booktitle={Reference Module in Chemistry, Molecular Sciences and Chemical Engineering}, publisher={Elsevier}, author={Keller, Adrian and Grundmeier, Guido}, year={2023} }' chicago: Keller, Adrian, and Guido Grundmeier. “High-Speed AFM Studies of Macromolecular Dynamics at Solid/Liquid Interfaces.” In Reference Module in Chemistry, Molecular Sciences and Chemical Engineering. Elsevier, 2023. https://doi.org/10.1016/b978-0-323-85669-0.00123-9. ieee: A. Keller and G. Grundmeier, “High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces,” in Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023. mla: Keller, Adrian, and Guido Grundmeier. “High-Speed AFM Studies of Macromolecular Dynamics at Solid/Liquid Interfaces.” Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023, doi:10.1016/b978-0-323-85669-0.00123-9. short: 'A. Keller, G. Grundmeier, in: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering, Elsevier, 2023.' date_created: 2023-07-03T08:08:29Z date_updated: 2023-07-03T08:08:44Z department: - _id: '302' doi: 10.1016/b978-0-323-85669-0.00123-9 language: - iso: eng publication: Reference Module in Chemistry, Molecular Sciences and Chemical Engineering publication_identifier: isbn: - '9780124095472' publication_status: published publisher: Elsevier status: public title: High-speed AFM studies of macromolecular dynamics at solid/liquid interfaces type: book_chapter user_id: '48864' year: '2023' ... --- _id: '45833' author: - first_name: Anastassija full_name: Kostan, Anastassija last_name: Kostan citation: ama: 'Kostan A. Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft. In: Bedeutung Und Implikationen Epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft; 2023. doi:10.5771/9783828877368-253' apa: Kostan, A. (2023). Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft. In Bedeutung und Implikationen epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft. https://doi.org/10.5771/9783828877368-253 bibtex: '@inbook{Kostan_2023, title={Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft}, DOI={10.5771/9783828877368-253}, booktitle={Bedeutung und Implikationen epistemischer Ungerechtigkeit}, publisher={Tectum – ein Verlag in der Nomos Verlagsgesellschaft}, author={Kostan, Anastassija}, year={2023} }' chicago: Kostan, Anastassija. “Die Epistemische Gewalt KI-Basierter Gesichtserkennung. Wie Ein Codierter Blick Neue Formen Der Technologisierten Subalternität Erschafft.” In Bedeutung Und Implikationen Epistemischer Ungerechtigkeit. Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023. https://doi.org/10.5771/9783828877368-253. ieee: A. Kostan, “Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft,” in Bedeutung und Implikationen epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023. mla: Kostan, Anastassija. “Die Epistemische Gewalt KI-Basierter Gesichtserkennung. Wie Ein Codierter Blick Neue Formen Der Technologisierten Subalternität Erschafft.” Bedeutung Und Implikationen Epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023, doi:10.5771/9783828877368-253. short: 'A. Kostan, in: Bedeutung Und Implikationen Epistemischer Ungerechtigkeit, Tectum – ein Verlag in der Nomos Verlagsgesellschaft, 2023.' date_created: 2023-07-03T08:30:29Z date_updated: 2023-07-03T08:38:39Z doi: 10.5771/9783828877368-253 publication: Bedeutung und Implikationen epistemischer Ungerechtigkeit publication_identifier: isbn: - '9783828877368' publication_status: published publisher: Tectum – ein Verlag in der Nomos Verlagsgesellschaft status: public title: Die epistemische Gewalt KI-basierter Gesichtserkennung. Wie ein codierter Blick neue Formen der technologisierten Subalternität erschafft type: book_chapter user_id: '99059' year: '2023' ... --- _id: '44323' abstract: - lang: eng text: "Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods.\r\nImplicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit\r\n(3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified?\r\nThe uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights.\r\nAs a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain." author: - first_name: Joschka full_name: Kersting, Joschka id: '58701' last_name: Kersting citation: ama: Kersting J. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München ; 2023. apa: Kersting, J. (2023). Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München . bibtex: '@book{Kersting_2023, place={Neubiberg}, title={Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}, publisher={Universität der Bundeswehr München }, author={Kersting, Joschka}, year={2023} }' chicago: 'Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' ieee: 'J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Neubiberg: Universität der Bundeswehr München , 2023.' mla: Kersting, Joschka. Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining. Universität der Bundeswehr München , 2023. short: J. Kersting, Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining, Universität der Bundeswehr München , Neubiberg, 2023. date_created: 2023-05-02T12:54:00Z date_updated: 2023-07-03T12:29:50Z department: - _id: '579' - _id: '7' language: - iso: ger page: '208' place: Neubiberg project: - _id: '1' grant_number: '160364472' name: 'SFB 901: SFB 901' - _id: '3' name: 'SFB 901 - B: SFB 901 - Project Area B' - _id: '9' grant_number: '160364472' name: 'SFB 901 - B1: SFB 901 - Subproject B1' publication_status: published publisher: 'Universität der Bundeswehr München ' related_material: link: - relation: supplementary_material url: https://athene-forschung.unibw.de/145003 status: public supervisor: - first_name: Michaela full_name: Geierhos, Michaela id: '42496' last_name: Geierhos orcid: 0000-0002-8180-5606 title: Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining type: dissertation user_id: '58701' year: '2023' ... --- _id: '45857' abstract: - lang: eng text: The aim of the present study is to prove the construct validity of the German versions of the Feeling Scale (FS) and the Felt Arousal Scale (FAS) for a progressive muscle relaxation (PMR) exercise. A total of 228 sport science students conducted the PMR exercise for 45 min and completed the FS, the FAS, and the Self-Assessment Manikin (SAM) in a pre-test–post-test design. A significant decrease in arousal (t(227) = 8.296, p < 0.001) and a significant increase in pleasure (t(227) = 4.748, p < 0.001) were observed. For convergent validity, the correlations between the FS and the subscale SAM-P for the valence dimension (r = 0.67, p < 0.001) and between the FAS and the subscale SAM-A for the arousal dimension (r = 0.31, p < 0.001) were significant. For discriminant validity, the correlations between different constructs (FS and SAM-A, FAS and SAM-P) were not significant, whereas the discriminant analysis between the FS and the FAS revealed a negative significant correlation (r = −0.15, p < 0.001). Together, the pattern of results confirms the use of the German versions of the FS and the FAS to measure the affective response for a PMR exercise. article_number: '523' author: - first_name: Kristin full_name: Thorenz, Kristin id: '34992' last_name: Thorenz - first_name: Andre full_name: Berwinkel, Andre last_name: Berwinkel - first_name: Matthias full_name: Weigelt, Matthias id: '36388' last_name: Weigelt citation: ama: Thorenz K, Berwinkel A, Weigelt M. A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise. Behavioral Sciences. 2023;13(7). doi:10.3390/bs13070523 apa: Thorenz, K., Berwinkel, A., & Weigelt, M. (2023). A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise. Behavioral Sciences, 13(7), Article 523. https://doi.org/10.3390/bs13070523 bibtex: '@article{Thorenz_Berwinkel_Weigelt_2023, title={A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise}, volume={13}, DOI={10.3390/bs13070523}, number={7523}, journal={Behavioral Sciences}, publisher={MDPI AG}, author={Thorenz, Kristin and Berwinkel, Andre and Weigelt, Matthias}, year={2023} }' chicago: Thorenz, Kristin, Andre Berwinkel, and Matthias Weigelt. “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise.” Behavioral Sciences 13, no. 7 (2023). https://doi.org/10.3390/bs13070523. ieee: 'K. Thorenz, A. Berwinkel, and M. Weigelt, “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise,” Behavioral Sciences, vol. 13, no. 7, Art. no. 523, 2023, doi: 10.3390/bs13070523.' mla: Thorenz, Kristin, et al. “A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise.” Behavioral Sciences, vol. 13, no. 7, 523, MDPI AG, 2023, doi:10.3390/bs13070523. short: K. Thorenz, A. Berwinkel, M. Weigelt, Behavioral Sciences 13 (2023). date_created: 2023-07-04T11:13:16Z date_updated: 2023-07-04T11:14:50Z doi: 10.3390/bs13070523 intvolume: ' 13' issue: '7' keyword: - Behavioral Neuroscience - General Psychology - Genetics - Development - Ecology - Evolution - Behavior and Systematics language: - iso: eng publication: Behavioral Sciences publication_identifier: issn: - 2076-328X publication_status: published publisher: MDPI AG status: public title: A Validation Study for the German Versions of the Feeling Scale and the Felt Arousal Scale for a Progressive Muscle Relaxation Exercise type: journal_article user_id: '34992' volume: 13 year: '2023' ... --- _id: '45856' author: - first_name: Kristin full_name: Thorenz, Kristin id: '34992' last_name: Thorenz - first_name: Andre full_name: Berwinkel, Andre last_name: Berwinkel - first_name: Matthias full_name: Weigelt, Matthias id: '36388' last_name: Weigelt citation: ama: Thorenz K, Berwinkel A, Weigelt M. A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training). Psychology. 2023;14(06):1070-1084. doi:10.4236/psych.2023.146058 apa: Thorenz, K., Berwinkel, A., & Weigelt, M. (2023). A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training). Psychology, 14(06), 1070–1084. https://doi.org/10.4236/psych.2023.146058 bibtex: '@article{Thorenz_Berwinkel_Weigelt_2023, title={A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training)}, volume={14}, DOI={10.4236/psych.2023.146058}, number={06}, journal={Psychology}, publisher={Scientific Research Publishing, Inc.}, author={Thorenz, Kristin and Berwinkel, Andre and Weigelt, Matthias}, year={2023}, pages={1070–1084} }' chicago: 'Thorenz, Kristin, Andre Berwinkel, and Matthias Weigelt. “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training).” Psychology 14, no. 06 (2023): 1070–84. https://doi.org/10.4236/psych.2023.146058.' ieee: 'K. Thorenz, A. Berwinkel, and M. Weigelt, “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training),” Psychology, vol. 14, no. 06, pp. 1070–1084, 2023, doi: 10.4236/psych.2023.146058.' mla: Thorenz, Kristin, et al. “A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training).” Psychology, vol. 14, no. 06, Scientific Research Publishing, Inc., 2023, pp. 1070–84, doi:10.4236/psych.2023.146058. short: K. Thorenz, A. Berwinkel, M. Weigelt, Psychology 14 (2023) 1070–1084. date_created: 2023-07-04T11:12:13Z date_updated: 2023-07-04T11:14:41Z doi: 10.4236/psych.2023.146058 intvolume: ' 14' issue: '06' keyword: - General Earth and Planetary Sciences - General Environmental Science language: - iso: eng page: 1070-1084 publication: Psychology publication_identifier: issn: - 2152-7180 - 2152-7199 publication_status: published publisher: Scientific Research Publishing, Inc. status: public title: A Validation Study of the German Versions of the Feeling Scale and the Felt Arousal Scale for a Passive Relaxation Technique (Autogenic Training) type: journal_article user_id: '34992' volume: 14 year: '2023' ...