---
_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'
...