---
_id: '34417'
abstract:
- lang: eng
text: Given strict emission targets and legal requirements, especially in the automotive
industry, environmentally friendly and simultaneously versatile applicable production
technologies are gaining importance. In this regard, the use of mechanical joining
processes, such as clinching, enable assembly sheet metals to achieve strength
properties similar to those of established thermal joining technologies. However,
to guarantee a high reliability of the generated joint connection, the selection
of a best-fitting joining technology as well as the meaningful description of
individual joint properties is essential. In the context of clinching, few contributions
have to date investigated the metamodel-based estimation and optimization of joint
characteristics, such as neck or interlock thickness, by applying machine learning
and genetic algorithms. Therefore, several regression models have been trained
on varying databases and amounts of input parameters. However, if product engineers
can only provide limited data for a new joining task, such as incomplete information
on applied joining tool dimensions, previously trained metamodels often reach
their limits. This often results in a significant loss of prediction quality and
leads to increasing uncertainties and inaccuracies within the metamodel-based
design of a clinch joint connection. Motivated by this, the presented contribution
investigates different machine learning algorithms regarding their ability to
achieve a satisfying estimation accuracy on limited input data applying a statistically
based feature selection method. Through this, it is possible to identify which
regression models are suitable to predict clinch joint characteristics considering
only a minimum set of required input features. Thus, in addition to the opportunity
to decrease the training effort as well as the model complexity, the subsequent
formulation of design equations can pave the way to a more versatile application
and reuse of pretrained metamodels on varying tool configurations for a given
clinch joining task.
author:
- first_name: Christoph
full_name: Zirngibl, Christoph
last_name: Zirngibl
- first_name: Benjamin
full_name: Schleich, Benjamin
last_name: Schleich
- first_name: Sandro
full_name: Wartzack, Sandro
last_name: Wartzack
citation:
ama: Zirngibl C, Schleich B, Wartzack S. Estimation of Clinch Joint Characteristics
Based on Limited Input Data Using Pre-Trained Metamodels. AI. 2022;3(4):990-1006.
doi:10.3390/ai3040059
apa: Zirngibl, C., Schleich, B., & Wartzack, S. (2022). Estimation of Clinch
Joint Characteristics Based on Limited Input Data Using Pre-Trained Metamodels.
AI, 3(4), 990–1006. https://doi.org/10.3390/ai3040059
bibtex: '@article{Zirngibl_Schleich_Wartzack_2022, title={Estimation of Clinch Joint
Characteristics Based on Limited Input Data Using Pre-Trained Metamodels}, volume={3},
DOI={10.3390/ai3040059}, number={4},
journal={AI}, publisher={MDPI AG}, author={Zirngibl, Christoph and Schleich, Benjamin
and Wartzack, Sandro}, year={2022}, pages={990–1006} }'
chicago: 'Zirngibl, Christoph, Benjamin Schleich, and Sandro Wartzack. “Estimation
of Clinch Joint Characteristics Based on Limited Input Data Using Pre-Trained
Metamodels.” AI 3, no. 4 (2022): 990–1006. https://doi.org/10.3390/ai3040059.'
ieee: 'C. Zirngibl, B. Schleich, and S. Wartzack, “Estimation of Clinch Joint Characteristics
Based on Limited Input Data Using Pre-Trained Metamodels,” AI, vol. 3,
no. 4, pp. 990–1006, 2022, doi: 10.3390/ai3040059.'
mla: Zirngibl, Christoph, et al. “Estimation of Clinch Joint Characteristics Based
on Limited Input Data Using Pre-Trained Metamodels.” AI, vol. 3, no. 4,
MDPI AG, 2022, pp. 990–1006, doi:10.3390/ai3040059.
short: C. Zirngibl, B. Schleich, S. Wartzack, AI 3 (2022) 990–1006.
date_created: 2022-12-14T12:32:29Z
date_updated: 2022-12-14T13:43:53Z
doi: 10.3390/ai3040059
intvolume: ' 3'
issue: '4'
keyword:
- Industrial and Manufacturing Engineering
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.mdpi.com/2673-2688/3/4/59
oa: '1'
page: 990-1006
project:
- _id: '130'
grant_number: '418701707'
name: 'TRR 285: TRR 285'
- _id: '132'
name: 'TRR 285 - B: TRR 285 - Project Area B'
- _id: '144'
name: 'TRR 285 – B05: TRR 285 - Subproject B05'
publication: AI
publication_identifier:
issn:
- 2673-2688
publication_status: published
publisher: MDPI AG
status: public
title: Estimation of Clinch Joint Characteristics Based on Limited Input Data Using
Pre-Trained Metamodels
type: journal_article
user_id: '7850'
volume: 3
year: '2022'
...
---
_id: '34549'
author:
- first_name: Korinna
full_name: Schönhärl, Korinna
id: '89037'
last_name: Schönhärl
orcid: 0000-0002-7967-3261
citation:
ama: 'Schönhärl K. Review on: Daniel Benedikt Stienen: Verkauftes Vaterland. Sehepunkte.
2022;22(11).'
apa: 'Schönhärl, K. (2022). Review on: Daniel Benedikt Stienen: Verkauftes Vaterland.
In Sehepunkte (Vol. 22, Issue 11).'
bibtex: '@article{Schönhärl_2022, title={Review on: Daniel Benedikt Stienen: Verkauftes
Vaterland}, volume={22}, number={11}, journal={Sehepunkte}, author={Schönhärl,
Korinna}, year={2022} }'
chicago: 'Schönhärl, Korinna. “Review on: Daniel Benedikt Stienen: Verkauftes Vaterland.”
Sehepunkte, 2022.'
ieee: 'K. Schönhärl, “Review on: Daniel Benedikt Stienen: Verkauftes Vaterland,”
Sehepunkte, vol. 22, no. 11. 2022.'
mla: 'Schönhärl, Korinna. “Review on: Daniel Benedikt Stienen: Verkauftes Vaterland.”
Sehepunkte, vol. 22, no. 11, 2022.'
short: K. Schönhärl, Sehepunkte 22 (2022).
date_created: 2022-12-19T11:01:46Z
date_updated: 2022-12-19T11:01:55Z
department:
- _id: '445'
intvolume: ' 22'
issue: '11'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://www.sehepunkte.de /2022/11/36727.html
oa: '1'
publication: Sehepunkte
publication_date: 2022-11-15
quality_controlled: '1'
status: public
title: 'Review on: Daniel Benedikt Stienen: Verkauftes Vaterland'
type: review
user_id: '89037'
volume: 22
year: '2022'
...
---
_id: '34554'
author:
- first_name: Korinna
full_name: Schönhärl, Korinna
id: '89037'
last_name: Schönhärl
orcid: 0000-0002-7967-3261
citation:
ama: 'Schönhärl K. Review on: Sven Steinmo: Willing to Pay? A Reasonable Choice
Approach . HSozKult. Published online 2022.'
apa: 'Schönhärl, K. (2022). Review on: Sven Steinmo: Willing to Pay? A Reasonable
Choice Approach . In HSozKult.'
bibtex: '@article{Schönhärl_2022, title={Review on: Sven Steinmo: Willing to Pay?
A Reasonable Choice Approach }, journal={HSozKult}, author={Schönhärl, Korinna},
year={2022} }'
chicago: 'Schönhärl, Korinna. “Review on: Sven Steinmo: Willing to Pay? A Reasonable
Choice Approach .” HSozKult, 2022.'
ieee: 'K. Schönhärl, “Review on: Sven Steinmo: Willing to Pay? A Reasonable Choice
Approach ,” HSozKult. 2022.'
mla: 'Schönhärl, Korinna. “Review on: Sven Steinmo: Willing to Pay? A Reasonable
Choice Approach .” HSozKult, 2022.'
short: K. Schönhärl, HSozKult (2022).
date_created: 2022-12-19T11:13:08Z
date_updated: 2022-12-19T11:13:13Z
department:
- _id: '445'
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
publication: HSozKult
publication_date: 2022-6-23
quality_controlled: '1'
related_material:
link:
- relation: confirmation
url: https://www.hsozkult.de/publicationreview/id/reb-115613
status: public
title: 'Review on: Sven Steinmo: Willing to Pay? A Reasonable Choice Approach '
type: review
user_id: '89037'
year: '2022'
...
---
_id: '34618'
abstract:
- lang: eng
text: "In this article, we show how second-order derivative information can be\r\nincorporated
into gradient sampling methods for nonsmooth optimization. The\r\nsecond-order
information we consider is essentially the set of coefficients of\r\nall second-order
Taylor expansions of the objective in a closed ball around a\r\ngiven point. Based
on this concept, we define a model of the objective as the\r\nmaximum of these
Taylor expansions. Iteratively minimizing this model\r\n(constrained to the closed
ball) results in a simple descent method, for which\r\nwe prove convergence to
minimal points in case the objective is convex. To\r\nobtain an implementable
method, we construct an approximation scheme for the\r\nsecond-order information
based on sampling objective values, gradients and\r\nHessian matrices at finitely
many points. Using a set of test problems, we\r\ncompare the resulting method
to five other available solvers. Considering the\r\nnumber of function evaluations,
the results suggest that the method we propose\r\nis superior to the standard
gradient sampling method, and competitive compared\r\nto other methods."
author:
- first_name: Bennet
full_name: Gebken, Bennet
id: '32643'
last_name: Gebken
citation:
ama: Gebken B. Using second-order information in gradient sampling methods for
nonsmooth optimization. arXiv:221004579. Published online 2022.
apa: Gebken, B. (2022). Using second-order information in gradient sampling methods
for nonsmooth optimization. In arXiv:2210.04579.
bibtex: '@article{Gebken_2022, title={Using second-order information in gradient
sampling methods for nonsmooth optimization}, journal={arXiv:2210.04579}, author={Gebken,
Bennet}, year={2022} }'
chicago: Gebken, Bennet. “Using Second-Order Information in Gradient Sampling Methods
for Nonsmooth Optimization.” ArXiv:2210.04579, 2022.
ieee: B. Gebken, “Using second-order information in gradient sampling methods for
nonsmooth optimization,” arXiv:2210.04579. 2022.
mla: Gebken, Bennet. “Using Second-Order Information in Gradient Sampling Methods
for Nonsmooth Optimization.” ArXiv:2210.04579, 2022.
short: B. Gebken, ArXiv:2210.04579 (2022).
date_created: 2022-12-20T15:25:17Z
date_updated: 2022-12-20T15:28:54Z
department:
- _id: '101'
external_id:
arxiv:
- '2210.04579'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/2210.04579
oa: '1'
publication: arXiv:2210.04579
status: public
title: Using second-order information in gradient sampling methods for nonsmooth
optimization
type: preprint
user_id: '32643'
year: '2022'
...
---
_id: '29220'
abstract:
- lang: eng
text: "Modern services often comprise several components, such as chained virtual
network functions, microservices, or\r\nmachine learning functions. Providing
such services requires to decide how often to instantiate each component, where
to place these instances in the network, how to chain them and route traffic through
them. \r\nTo overcome limitations of conventional, hardwired heuristics, deep
reinforcement learning (DRL) approaches for self-learning network and service
management have emerged recently. These model-free DRL approaches are more flexible
but typically learn tabula rasa, i.e., disregard existing understanding of networks,
services, and their coordination. \r\n\r\nInstead, we propose FutureCoord, a novel
model-based AI approach that leverages existing understanding of networks and
services for more efficient and effective coordination without time-intensive
training. FutureCoord combines Monte Carlo Tree Search with a stochastic traffic
model. This allows FutureCoord to estimate the impact of future incoming traffic
and effectively optimize long-term effects, taking fluctuating demand and Quality
of Service (QoS) requirements into account. Our extensive evaluation based on
real-world network topologies, services, and traffic traces indicates that FutureCoord
clearly outperforms state-of-the-art model-free and model-based approaches with
up to 51% higher flow success ratios."
author:
- first_name: Stefan
full_name: Werner, Stefan
last_name: Werner
- 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
citation:
ama: 'Werner S, Schneider SB, Karl H. Use What You Know: Network and Service Coordination
Beyond Certainty. In: IEEE/IFIP Network Operations and Management Symposium
(NOMS). IEEE; 2022.'
apa: 'Werner, S., Schneider, S. B., & Karl, H. (2022). Use What You Know: Network
and Service Coordination Beyond Certainty. IEEE/IFIP Network Operations and
Management Symposium (NOMS). IEEE/IFIP Network Operations and Management Symposium
(NOMS), Budapest.'
bibtex: '@inproceedings{Werner_Schneider_Karl_2022, title={Use What You Know: Network
and Service Coordination Beyond Certainty}, booktitle={IEEE/IFIP Network Operations
and Management Symposium (NOMS)}, publisher={IEEE}, author={Werner, Stefan and
Schneider, Stefan Balthasar and Karl, Holger}, year={2022} }'
chicago: 'Werner, Stefan, Stefan Balthasar Schneider, and Holger Karl. “Use What
You Know: Network and Service Coordination Beyond Certainty.” In IEEE/IFIP
Network Operations and Management Symposium (NOMS). IEEE, 2022.'
ieee: 'S. Werner, S. B. Schneider, and H. Karl, “Use What You Know: Network and
Service Coordination Beyond Certainty,” presented at the IEEE/IFIP Network Operations
and Management Symposium (NOMS), Budapest, 2022.'
mla: 'Werner, Stefan, et al. “Use What You Know: Network and Service Coordination
Beyond Certainty.” IEEE/IFIP Network Operations and Management Symposium (NOMS),
IEEE, 2022.'
short: 'S. Werner, S.B. Schneider, H. Karl, in: IEEE/IFIP Network Operations and
Management Symposium (NOMS), IEEE, 2022.'
conference:
end_date: 2022-04-29
location: Budapest
name: IEEE/IFIP Network Operations and Management Symposium (NOMS)
start_date: 2022-04-25
date_created: 2022-01-11T08:43:26Z
date_updated: 2022-01-11T08:44:04Z
ddc:
- '004'
department:
- _id: '75'
file:
- access_level: open_access
content_type: application/pdf
creator: stschn
date_created: 2022-01-11T08:39:57Z
date_updated: 2022-01-11T08:39:57Z
file_id: '29222'
file_name: author_version.pdf
file_size: 528653
relation: main_file
file_date_updated: 2022-01-11T08:39:57Z
has_accepted_license: '1'
keyword:
- network management
- service management
- AI
- Monte Carlo Tree Search
- model-based
- QoS
language:
- iso: eng
oa: '1'
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
- _id: '16'
name: 'SFB 901 - C4: SFB 901 - Subproject C4'
publication: IEEE/IFIP Network Operations and Management Symposium (NOMS)
publisher: IEEE
quality_controlled: '1'
status: public
title: 'Use What You Know: Network and Service Coordination Beyond Certainty'
type: conference
user_id: '35343'
year: '2022'
...
---
_id: '23415'
author:
- first_name: Martina
full_name: Sperling, Martina
id: '76460'
last_name: Sperling
- first_name: Guido
full_name: Schryen, Guido
id: '72850'
last_name: Schryen
citation:
ama: 'Sperling M, Schryen G. Decision Support for Disaster Relief: Coordinating
Spontaneous Volunteers. European Journal of Operational Research (EJOR).
2022;299(2):690-705.'
apa: 'Sperling, M., & Schryen, G. (2022). Decision Support for Disaster Relief:
Coordinating Spontaneous Volunteers. European Journal of Operational Research
(EJOR), 299(2), 690–705.'
bibtex: '@article{Sperling_Schryen_2022, title={Decision Support for Disaster Relief:
Coordinating Spontaneous Volunteers}, volume={299}, number={2}, journal={European
Journal of Operational Research (EJOR)}, author={Sperling, Martina and Schryen,
Guido}, year={2022}, pages={690–705} }'
chicago: 'Sperling, Martina, and Guido Schryen. “Decision Support for Disaster Relief:
Coordinating Spontaneous Volunteers.” European Journal of Operational Research
(EJOR) 299, no. 2 (2022): 690–705.'
ieee: 'M. Sperling and G. Schryen, “Decision Support for Disaster Relief: Coordinating
Spontaneous Volunteers,” European Journal of Operational Research (EJOR),
vol. 299, no. 2, pp. 690–705, 2022.'
mla: 'Sperling, Martina, and Guido Schryen. “Decision Support for Disaster Relief:
Coordinating Spontaneous Volunteers.” European Journal of Operational Research
(EJOR), vol. 299, no. 2, 2022, pp. 690–705.'
short: M. Sperling, G. Schryen, European Journal of Operational Research (EJOR)
299 (2022) 690–705.
date_created: 2021-08-16T13:47:12Z
date_updated: 2022-01-19T14:55:21Z
ddc:
- '000'
department:
- _id: '277'
file:
- access_level: open_access
content_type: application/pdf
creator: hsiemes
date_created: 2021-08-16T13:46:57Z
date_updated: 2021-08-16T13:46:57Z
file_id: '23416'
file_name: CoordinatingSpontaneousVolunteers.pdf
file_size: 1275918
relation: main_file
file_date_updated: 2021-08-16T13:46:57Z
has_accepted_license: '1'
intvolume: ' 299'
issue: '2'
language:
- iso: eng
oa: '1'
page: 690 - 705
publication: European Journal of Operational Research (EJOR)
status: public
title: 'Decision Support for Disaster Relief: Coordinating Spontaneous Volunteers'
type: journal_article
user_id: '61579'
volume: 299
year: '2022'
...
---
_id: '29539'
abstract:
- lang: eng
text: Explainable Artificial Intelligence (XAI) is currently an important topic
for the application of Machine Learning (ML) in high-stakes decision scenarios.
Related research focuses on evaluating ML algorithms in terms of interpretability.
However, providing a human understandable explanation of an intelligent system
does not only relate to the used ML algorithm. The data and features used also
have a considerable impact on interpretability. In this paper, we develop a taxonomy
for describing XAI systems based on aspects about the algorithm and data. The
proposed taxonomy gives researchers and practitioners opportunities to describe
and evaluate current XAI systems with respect to interpretability and guides the
future development of this class of systems.
author:
- first_name: Jan-Peter
full_name: Kucklick, Jan-Peter
id: '77066'
last_name: Kucklick
citation:
ama: 'Kucklick J-P. Towards a model- and data-focused taxonomy of XAI systems. In:
Wirtschaftsinformatik 2022 Proceedings. ; 2022.'
apa: Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems.
Wirtschaftsinformatik 2022 Proceedings. Wirtschaftsinformatik 2022 (WI22),
Nürnberg (online).
bibtex: '@inproceedings{Kucklick_2022, title={Towards a model- and data-focused
taxonomy of XAI systems}, booktitle={Wirtschaftsinformatik 2022 Proceedings},
author={Kucklick, Jan-Peter}, year={2022} }'
chicago: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI
Systems.” In Wirtschaftsinformatik 2022 Proceedings, 2022.
ieee: J.-P. Kucklick, “Towards a model- and data-focused taxonomy of XAI systems,”
presented at the Wirtschaftsinformatik 2022 (WI22), Nürnberg (online), 2022.
mla: Kucklick, Jan-Peter. “Towards a Model- and Data-Focused Taxonomy of XAI Systems.”
Wirtschaftsinformatik 2022 Proceedings, 2022.
short: 'J.-P. Kucklick, in: Wirtschaftsinformatik 2022 Proceedings, 2022.'
conference:
end_date: 2022-02-23
location: Nürnberg (online)
name: Wirtschaftsinformatik 2022 (WI22)
start_date: 2022-02-21
date_created: 2022-01-26T08:22:03Z
date_updated: 2022-01-26T08:24:30Z
department:
- _id: '195'
- _id: '196'
keyword:
- Explainable Artificial Intelligence
- XAI
- Interpretability
- Decision Support Systems
- Taxonomy
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1056&context=wi2022
oa: '1'
publication: Wirtschaftsinformatik 2022 Proceedings
status: public
title: Towards a model- and data-focused taxonomy of XAI systems
type: conference
user_id: '77066'
year: '2022'
...
---
_id: '29763'
abstract:
- lang: eng
text: "Modern-day communication has become more and more digital. While this comes
with many advantages such as a more efficient economy, it has also created more
and more opportunities for various adversaries to manipulate communication or
eavesdrop on it. The Snowden revelations in 2013 further highlighted the seriousness
of these threats. To protect the communication of people, companies, and states
from such threats, we require cryptography with strong security guarantees.\r\nDifferent
applications may require different security properties from cryptographic schemes.
For most applications, however, so-called adaptive security is considered a reasonable
minimal requirement of security. Cryptographic schemes with adaptive security
remain secure in the presence of an adversary that can corrupt communication partners
to respond to messages of the adversaries choice, while the adversary may choose
the messages based on previously observed interactions.\r\nWhile cryptography
is associated the most with encryption, this is only one of many primitives that
are essential for the security of digital interactions. This thesis presents novel
identity-based encryption (IBE) schemes and verifiable random functions (VRFs)
that achieve adaptive security as outlined above. Moreover, the cryptographic
schemes presented in this thesis are proven secure in the standard model. That
is without making use of idealized models like the random oracle model."
author:
- first_name: David
full_name: Niehues, David
id: '36113'
last_name: Niehues
citation:
ama: Niehues D. More Efficient Techniques for Adaptively-Secure Cryptography.;
2022. doi:10.25926/rdtq-jw45
apa: Niehues, D. (2022). More Efficient Techniques for Adaptively-Secure Cryptography.
https://doi.org/10.25926/rdtq-jw45
bibtex: '@book{Niehues_2022, title={More Efficient Techniques for Adaptively-Secure
Cryptography}, DOI={10.25926/rdtq-jw45},
author={Niehues, David}, year={2022} }'
chicago: Niehues, David. More Efficient Techniques for Adaptively-Secure Cryptography,
2022. https://doi.org/10.25926/rdtq-jw45.
ieee: D. Niehues, More Efficient Techniques for Adaptively-Secure Cryptography.
2022.
mla: Niehues, David. More Efficient Techniques for Adaptively-Secure Cryptography.
2022, doi:10.25926/rdtq-jw45.
short: D. Niehues, More Efficient Techniques for Adaptively-Secure Cryptography,
2022.
date_created: 2022-02-07T13:29:07Z
date_updated: 2022-02-07T13:32:28Z
ddc:
- '000'
department:
- _id: '558'
doi: 10.25926/rdtq-jw45
file:
- access_level: closed
content_type: application/pdf
creator: davnie
date_created: 2022-02-07T13:26:05Z
date_updated: 2022-02-07T13:26:05Z
file_id: '29764'
file_name: de2107.pdf
file_size: 1542089
relation: main_file
success: 1
file_date_updated: 2022-02-07T13:26:05Z
has_accepted_license: '1'
keyword:
- public-key cryptography
- lattices
- pairings
- verifiable random functions
- identity-based encryption
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nd/4.0/
main_file_link:
- open_access: '1'
url: https://elpub.bib.uni-wuppertal.de/servlets/DerivateServlet/Derivate-14686/de2107.pdf
oa: '1'
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '4'
name: 'SFB 901 - C: SFB 901 - Project Area C'
- _id: '13'
name: 'SFB 901 - C1: SFB 901 - Subproject C1'
publication_status: published
status: public
supervisor:
- first_name: Tibor
full_name: Jager, Tibor
id: '64669'
last_name: Jager
- first_name: Anja
full_name: Lehmann, Anja
last_name: Lehmann
title: More Efficient Techniques for Adaptively-Secure Cryptography
type: dissertation
user_id: '36113'
year: '2022'
...
---
_id: '31545'
abstract:
- lang: eng
text: Knowledge graph embedding research has mainly focused on learning continuous
representations of entities and relations tailored towards the link prediction
problem. Recent results indicate an ever increasing predictive ability of current
approaches on benchmark datasets. However, this effectiveness often comes with
the cost of over-parameterization and increased computationally complexity. The
former induces extensive hyperparameter optimization to mitigate malicious overfitting.
The latter magnifies the importance of winning the hardware lottery. Here, we
investigate a remedy for the first problem. We propose a technique based on Kronecker
decomposition to reduce the number of parameters in a knowledge graph embedding
model, while retaining its expressiveness. Through Kronecker decomposition, large
embedding matrices are split into smaller embedding matrices during the training
process. Hence, embeddings of knowledge graphs are not plainly retrieved but reconstructed
on the fly. The decomposition ensures that elementwise interactions between three
embedding vectors are extended with interactions within each embedding vector.
This implicitly reduces redundancy in embedding vectors and encourages feature
reuse. To quantify the impact of applying Kronecker decomposition on embedding
matrices, we conduct a series of experiments on benchmark datasets. Our experiments
suggest that applying Kronecker decomposition on embedding matrices leads to an
improved parameter efficiency on all benchmark datasets. Moreover, empirical evidence
suggests that reconstructed embeddings entail robustness against noise in the
input knowledge graph. To foster reproducible research, we provide an open-source
implementation of our approach, including training and evaluation scripts as well
as pre-trained models in our knowledge graph embedding framework.
author:
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Julian
full_name: Lienen, Julian
id: '44040'
last_name: Lienen
- first_name: Axel-Cyrille
full_name: Ngonga Ngomo, Axel-Cyrille
id: '65716'
last_name: Ngonga Ngomo
citation:
ama: Demir C, Lienen J, Ngonga Ngomo A-C. Kronecker Decomposition for Knowledge
Graph Embeddings. arXiv:220506560. Published online 2022.
apa: Demir, C., Lienen, J., & Ngonga Ngomo, A.-C. (2022). Kronecker Decomposition
for Knowledge Graph Embeddings. In arXiv:2205.06560.
bibtex: '@article{Demir_Lienen_Ngonga Ngomo_2022, title={Kronecker Decomposition
for Knowledge Graph Embeddings}, journal={arXiv:2205.06560}, author={Demir, Caglar
and Lienen, Julian and Ngonga Ngomo, Axel-Cyrille}, year={2022} }'
chicago: Demir, Caglar, Julian Lienen, and Axel-Cyrille Ngonga Ngomo. “Kronecker
Decomposition for Knowledge Graph Embeddings.” ArXiv:2205.06560, 2022.
ieee: C. Demir, J. Lienen, and A.-C. Ngonga Ngomo, “Kronecker Decomposition for
Knowledge Graph Embeddings,” arXiv:2205.06560. 2022.
mla: Demir, Caglar, et al. “Kronecker Decomposition for Knowledge Graph Embeddings.”
ArXiv:2205.06560, 2022.
short: C. Demir, J. Lienen, A.-C. Ngonga Ngomo, ArXiv:2205.06560 (2022).
date_created: 2022-05-31T07:04:36Z
date_updated: 2022-05-31T07:05:50Z
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2205.06560
oa: '1'
publication: arXiv:2205.06560
status: public
title: Kronecker Decomposition for Knowledge Graph Embeddings
type: preprint
user_id: '44040'
year: '2022'
...
---
_id: '31546'
abstract:
- lang: eng
text: In semi-supervised learning, the paradigm of self-training refers to the idea
of learning from pseudo-labels suggested by the learner itself. Across various
domains, corresponding methods have proven effective and achieve state-of-the-art
performance. However, pseudo-labels typically stem from ad-hoc heuristics, relying
on the quality of the predictions though without guaranteeing their validity.
One such method, so-called credal self-supervised learning, maintains pseudo-supervision
in the form of sets of (instead of single) probability distributions over labels,
thereby allowing for a flexible yet uncertainty-aware labeling. Again, however,
there is no justification beyond empirical effectiveness. To address this deficiency,
we make use of conformal prediction, an approach that comes with guarantees on
the validity of set-valued predictions. As a result, the construction of credal
sets of labels is supported by a rigorous theoretical foundation, leading to better
calibrated and less error-prone supervision for unlabeled data. Along with this,
we present effective algorithms for learning from credal self-supervision. An
empirical study demonstrates excellent calibration properties of the pseudo-supervision,
as well as the competitiveness of our method on several benchmark datasets.
author:
- first_name: Julian
full_name: Lienen, Julian
id: '44040'
last_name: Lienen
- first_name: Caglar
full_name: Demir, Caglar
id: '43817'
last_name: Demir
- first_name: Eyke
full_name: Hüllermeier, Eyke
id: '48129'
last_name: Hüllermeier
citation:
ama: Lienen J, Demir C, Hüllermeier E. Conformal Credal Self-Supervised Learning.
arXiv:220515239. Published online 2022.
apa: Lienen, J., Demir, C., & Hüllermeier, E. (2022). Conformal Credal Self-Supervised
Learning. In arXiv:2205.15239.
bibtex: '@article{Lienen_Demir_Hüllermeier_2022, title={Conformal Credal Self-Supervised
Learning}, journal={arXiv:2205.15239}, author={Lienen, Julian and Demir, Caglar
and Hüllermeier, Eyke}, year={2022} }'
chicago: Lienen, Julian, Caglar Demir, and Eyke Hüllermeier. “Conformal Credal Self-Supervised
Learning.” ArXiv:2205.15239, 2022.
ieee: J. Lienen, C. Demir, and E. Hüllermeier, “Conformal Credal Self-Supervised
Learning,” arXiv:2205.15239. 2022.
mla: Lienen, Julian, et al. “Conformal Credal Self-Supervised Learning.” ArXiv:2205.15239,
2022.
short: J. Lienen, C. Demir, E. Hüllermeier, ArXiv:2205.15239 (2022).
date_created: 2022-05-31T07:05:36Z
date_updated: 2022-05-31T07:05:54Z
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2205.15239
oa: '1'
publication: arXiv:2205.15239
status: public
title: Conformal Credal Self-Supervised Learning
type: preprint
user_id: '44040'
year: '2022'
...
---
_id: '31556'
abstract:
- lang: ger
text: Mehrzieloptimierung behandelt Probleme, bei denen mehrere skalare Zielfunktionen
simultan optimiert werden sollen. Ein Punkt ist in diesem Fall optimal, wenn es
keinen anderen Punkt gibt, der mindestens genauso gut ist in allen Zielfunktionen
und besser in mindestens einer Zielfunktion. Ein notwendiges Optimalitätskriterium
lässt sich über Ableitungsinformationen erster Ordnung der Zielfunktionen herleiten.
Die Menge der Punkte, die dieses notwendige Kriterium erfüllen, wird als Pareto-kritische
Menge bezeichnet. Diese Arbeit enthält neue Resultate über Pareto-kritische Mengen
für glatte und nicht-glatte Mehrzieloptimierungsprobleme, sowohl was deren Berechnung
betrifft als auch deren Struktur. Im glatten Fall erfolgt die Berechnung über
ein Fortsetzungsverfahren, im nichtglatten Fall über ein Abstiegsverfahren. Anschließend
wird die Struktur des Randes der Pareto-kritischen Menge analysiert, welcher aus
Pareto-kritischen Mengen kleinerer Subprobleme besteht. Schlussendlich werden
inverse Probleme betrachtet, bei denen zu einer gegebenen Datenmenge ein Zielfunktionsvektor
gefunden werden soll, für den die Datenpunkte kritisch sind.
- lang: eng
text: Multiobjective optimization is concerned with the simultaneous optimization
of multiple scalar-valued functions. In this case, a point is optimal if there
is no other point that is at least as good in all objectives and better in at
least one objective. A necessary condition for optimality can be derived based
on first-order information of the objectives. The set of points that satisfy this
necessary condition is called the Pareto critical set. This thesis presents new
results about Pareto critical sets for smooth and nonsmooth multiobjective optimization
problems, both in terms of their efficient computation and structural properties.
In the smooth case they are computed via a continuation method and in the nonsmooth
case via a descent method. Afterwards, the structure of the boundary of the Pareto
critical set is analyzed, which consists of Pareto critical sets of smaller subproblems.
Finally, inverse problems are considered, where a data set is given and an objective
vector is sought for which the data points are critical.
author:
- first_name: Bennet
full_name: Gebken, Bennet
id: '32643'
last_name: Gebken
citation:
ama: Gebken B. Computation and Analysis of Pareto Critical Sets in Smooth and
Nonsmooth Multiobjective Optimization.; 2022. doi:10.17619/UNIPB/1-1327
apa: Gebken, B. (2022). Computation and analysis of Pareto critical sets in smooth
and nonsmooth multiobjective optimization. https://doi.org/10.17619/UNIPB/1-1327
bibtex: '@book{Gebken_2022, title={Computation and analysis of Pareto critical sets
in smooth and nonsmooth multiobjective optimization}, DOI={10.17619/UNIPB/1-1327},
author={Gebken, Bennet}, year={2022} }'
chicago: Gebken, Bennet. Computation and Analysis of Pareto Critical Sets in
Smooth and Nonsmooth Multiobjective Optimization, 2022. https://doi.org/10.17619/UNIPB/1-1327.
ieee: B. Gebken, Computation and analysis of Pareto critical sets in smooth and
nonsmooth multiobjective optimization. 2022.
mla: Gebken, Bennet. Computation and Analysis of Pareto Critical Sets in Smooth
and Nonsmooth Multiobjective Optimization. 2022, doi:10.17619/UNIPB/1-1327.
short: B. Gebken, Computation and Analysis of Pareto Critical Sets in Smooth and
Nonsmooth Multiobjective Optimization, 2022.
date_created: 2022-06-01T06:48:08Z
date_updated: 2022-06-01T07:13:09Z
department:
- _id: '101'
doi: 10.17619/UNIPB/1-1327
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://digital.ub.uni-paderborn.de/hs/download/pdf/6531779
oa: '1'
status: public
supervisor:
- first_name: Michael
full_name: Dellnitz, Michael
last_name: Dellnitz
title: Computation and analysis of Pareto critical sets in smooth and nonsmooth multiobjective
optimization
type: dissertation
user_id: '32643'
year: '2022'
...
---
_id: '31574'
abstract:
- lang: eng
text: We model negative polarization, which is observed for planetary regoliths
at backscattering, solving a full wave problem of light scattering with a numerically
exact Discontinuous Galerkin Time Domain (DGTD) method. Pieces of layers with
the bulk packing density of particles close to 0.5 are used. The model particles
are highly absorbing and have irregular shapes and sizes larger than the wavelength
of light. This represents a realistic analog of low-albedo planetary regoliths.
Our simulations confirm coherent backscattering mechanism of the origin of negative
polarization. We show that angular profiles of polarization are stabilized if
the number of particles in a layer piece becomes larger than ten. This allows
application of our approach to the negative polarization modeling for planetary
regoliths.
author:
- first_name: Yevgen
full_name: Grynko, Yevgen
id: '26059'
last_name: Grynko
- first_name: Yuriy
full_name: Shkuratov, Yuriy
last_name: Shkuratov
- first_name: Samer
full_name: Alhaddad, Samer
id: '42456'
last_name: Alhaddad
- first_name: Jens
full_name: Förstner, Jens
id: '158'
last_name: Förstner
orcid: 0000-0001-7059-9862
citation:
ama: Grynko Y, Shkuratov Y, Alhaddad S, Förstner J. Negative polarization of light
at backscattering from a numerical analog of planetary regoliths. Icarus.
2022;384:115099. doi:10.1016/j.icarus.2022.115099
apa: Grynko, Y., Shkuratov, Y., Alhaddad, S., & Förstner, J. (2022). Negative
polarization of light at backscattering from a numerical analog of planetary regoliths.
Icarus, 384, 115099. https://doi.org/10.1016/j.icarus.2022.115099
bibtex: '@article{Grynko_Shkuratov_Alhaddad_Förstner_2022, title={Negative polarization
of light at backscattering from a numerical analog of planetary regoliths}, volume={384},
DOI={10.1016/j.icarus.2022.115099},
journal={Icarus}, publisher={Elsevier BV}, author={Grynko, Yevgen and Shkuratov,
Yuriy and Alhaddad, Samer and Förstner, Jens}, year={2022}, pages={115099} }'
chicago: 'Grynko, Yevgen, Yuriy Shkuratov, Samer Alhaddad, and Jens Förstner. “Negative
Polarization of Light at Backscattering from a Numerical Analog of Planetary Regoliths.”
Icarus 384 (2022): 115099. https://doi.org/10.1016/j.icarus.2022.115099.'
ieee: 'Y. Grynko, Y. Shkuratov, S. Alhaddad, and J. Förstner, “Negative polarization
of light at backscattering from a numerical analog of planetary regoliths,” Icarus,
vol. 384, p. 115099, 2022, doi: 10.1016/j.icarus.2022.115099.'
mla: Grynko, Yevgen, et al. “Negative Polarization of Light at Backscattering from
a Numerical Analog of Planetary Regoliths.” Icarus, vol. 384, Elsevier
BV, 2022, p. 115099, doi:10.1016/j.icarus.2022.115099.
short: Y. Grynko, Y. Shkuratov, S. Alhaddad, J. Förstner, Icarus 384 (2022) 115099.
date_created: 2022-06-01T18:53:35Z
date_updated: 2022-06-01T18:57:51Z
ddc:
- '530'
department:
- _id: '61'
doi: 10.1016/j.icarus.2022.115099
file:
- access_level: open_access
content_type: application/pdf
creator: fossie
date_created: 2022-06-01T18:56:44Z
date_updated: 2022-06-01T18:56:44Z
file_id: '31575'
file_name: 2022-06 Grynko - Icarus - Negative polarization of light at backscattering
from a numerical analog of planetary regoliths.pdf
file_size: 1419286
relation: main_file
file_date_updated: 2022-06-01T18:56:44Z
has_accepted_license: '1'
intvolume: ' 384'
keyword:
- tet_topic_scattering
language:
- iso: eng
oa: '1'
page: '115099'
project:
- _id: '52'
name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing'
publication: Icarus
publication_identifier:
issn:
- 0019-1035
publication_status: published
publisher: Elsevier BV
status: public
title: Negative polarization of light at backscattering from a numerical analog of
planetary regoliths
type: journal_article
user_id: '158'
volume: 384
year: '2022'
...
---
_id: '32864'
abstract:
- lang: eng
text: The further development of in-mold-assembly (IMA) technologies for structural
hybrid components is of great importance for increasing the economic efficiency
and thus the application potential. This paper presents an innovative IMA process
concept for the manufacturing of bending loaded hybrid components consisting of
two outer metal belts and an inner core structure made of glass mat reinforced
thermoplastic (GMT). In this process, the core structure, which is provided with
stiffening ribs and functional elements, is formed and joined to two metal belts
in one single step. For experimental validation of the concept, the development
of a prototypic molding tool and the manufacturing of hybrid beams including process
parameters are described. Three-point bending tests and optical measurement technologies
are used to characterize the failure behavior and mechanical properties of the
produced hybrid beams. It was found that the innovative IMA process enables the
manufacturing of hybrid components with high energy absorption and low weight
in one step. The mass-specific energy absorption is increased by 693 % compared
to pure GMT beams.
author:
- first_name: Tim
full_name: Stallmeister, Tim
last_name: Stallmeister
- first_name: Thomas
full_name: Tröster, Thomas
last_name: Tröster
citation:
ama: Stallmeister T, Tröster T. In-Mold-Assembly of Hybrid Bending Structures by
Compression Molding. Key Engineering Materials. 2022;926:1457-1467. doi:10.4028/p-5fxp53
apa: Stallmeister, T., & Tröster, T. (2022). In-Mold-Assembly of Hybrid Bending
Structures by Compression Molding. Key Engineering Materials, 926,
1457–1467. https://doi.org/10.4028/p-5fxp53
bibtex: '@article{Stallmeister_Tröster_2022, title={In-Mold-Assembly of Hybrid Bending
Structures by Compression Molding}, volume={926}, DOI={10.4028/p-5fxp53},
journal={Key Engineering Materials}, publisher={Trans Tech Publications, Ltd.},
author={Stallmeister, Tim and Tröster, Thomas}, year={2022}, pages={1457–1467}
}'
chicago: 'Stallmeister, Tim, and Thomas Tröster. “In-Mold-Assembly of Hybrid Bending
Structures by Compression Molding.” Key Engineering Materials 926 (2022):
1457–67. https://doi.org/10.4028/p-5fxp53.'
ieee: 'T. Stallmeister and T. Tröster, “In-Mold-Assembly of Hybrid Bending Structures
by Compression Molding,” Key Engineering Materials, vol. 926, pp. 1457–1467,
2022, doi: 10.4028/p-5fxp53.'
mla: Stallmeister, Tim, and Thomas Tröster. “In-Mold-Assembly of Hybrid Bending
Structures by Compression Molding.” Key Engineering Materials, vol. 926,
Trans Tech Publications, Ltd., 2022, pp. 1457–67, doi:10.4028/p-5fxp53.
short: T. Stallmeister, T. Tröster, Key Engineering Materials 926 (2022) 1457–1467.
date_created: 2022-08-17T05:59:05Z
date_updated: 2022-08-17T06:02:07Z
doi: 10.4028/p-5fxp53
intvolume: ' 926'
keyword:
- Mechanical Engineering
- Mechanics of Materials
- General Materials Science
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.scientific.net/KEM.926.1457
oa: '1'
page: 1457-1467
publication: Key Engineering Materials
publication_identifier:
issn:
- 1662-9795
publication_status: published
publisher: Trans Tech Publications, Ltd.
status: public
title: In-Mold-Assembly of Hybrid Bending Structures by Compression Molding
type: journal_article
user_id: '45538'
volume: 926
year: '2022'
...
---
_id: '33033'
author:
- first_name: Lukas
full_name: Fehring, Lukas
id: '75695'
last_name: Fehring
citation:
ama: Fehring L. Combined Ranking and Regression Trees for Algorithm Selection.;
2022.
apa: Fehring, L. (2022). Combined Ranking and Regression Trees for Algorithm
Selection.
bibtex: '@book{Fehring_2022, place={Paderborn}, title={Combined Ranking and Regression
Trees for Algorithm Selection}, author={Fehring, Lukas}, year={2022} }'
chicago: Fehring, Lukas. Combined Ranking and Regression Trees for Algorithm
Selection. Paderborn, 2022.
ieee: L. Fehring, Combined Ranking and Regression Trees for Algorithm Selection.
Paderborn, 2022.
mla: Fehring, Lukas. Combined Ranking and Regression Trees for Algorithm Selection.
2022.
short: L. Fehring, Combined Ranking and Regression Trees for Algorithm Selection,
Paderborn, 2022.
date_created: 2022-08-19T09:41:14Z
date_updated: 2022-08-20T07:02:04Z
ddc:
- '006'
department:
- _id: '34'
- _id: '7'
- _id: '26'
file:
- access_level: open_access
content_type: application/pdf
creator: ahetzer
date_created: 2022-08-19T09:39:57Z
date_updated: 2022-08-19T09:39:57Z
file_id: '33034'
file_name: Final Bachelor Thesis.pdf
file_size: 24830795
relation: main_file
file_date_updated: 2022-08-19T09:39:57Z
has_accepted_license: '1'
language:
- iso: eng
oa: '1'
place: Paderborn
project:
- _id: '1'
name: 'SFB 901: SFB 901'
- _id: '3'
name: 'SFB 901 - B: SFB 901 - Project Area B'
- _id: '10'
name: 'SFB 901 - B2: SFB 901 - Subproject B2'
status: public
title: Combined Ranking and Regression Trees for Algorithm Selection
type: bachelorsthesis
user_id: '38209'
year: '2022'
...
---
_id: '33150'
abstract:
- lang: eng
text: In this article, we build on previous work to present an optimization algorithm
for nonlinearly constrained multi-objective optimization problems. The algorithm
combines a surrogate-assisted derivative-free trust-region approach with the filter
method known from single-objective optimization. Instead of the true objective
and constraint functions, so-called fully linear models are employed and we show
how to deal with the gradient inexactness in the composite step setting, adapted
from single-objective optimization as well. Under standard assumptions, we prove
convergence of a subset of iterates to a quasi-stationary point and if constraint
qualifications hold, then the limit point is also a KKT-point of the multi-objective
problem.
author:
- first_name: Manuel Bastian
full_name: Berkemeier, Manuel Bastian
id: '51701'
last_name: Berkemeier
- first_name: Sebastian
full_name: Peitz, Sebastian
id: '47427'
last_name: Peitz
orcid: 0000-0002-3389-793X
citation:
ama: Berkemeier MB, Peitz S. Multi-Objective Trust-Region Filter Method for Nonlinear
Constraints using Inexact Gradients. arXiv:220812094. Published online
2022.
apa: Berkemeier, M. B., & Peitz, S. (2022). Multi-Objective Trust-Region Filter
Method for Nonlinear Constraints using Inexact Gradients. In arXiv:2208.12094.
bibtex: '@article{Berkemeier_Peitz_2022, title={Multi-Objective Trust-Region Filter
Method for Nonlinear Constraints using Inexact Gradients}, journal={arXiv:2208.12094},
author={Berkemeier, Manuel Bastian and Peitz, Sebastian}, year={2022} }'
chicago: Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region
Filter Method for Nonlinear Constraints Using Inexact Gradients.” ArXiv:2208.12094,
2022.
ieee: M. B. Berkemeier and S. Peitz, “Multi-Objective Trust-Region Filter Method
for Nonlinear Constraints using Inexact Gradients,” arXiv:2208.12094. 2022.
mla: Berkemeier, Manuel Bastian, and Sebastian Peitz. “Multi-Objective Trust-Region
Filter Method for Nonlinear Constraints Using Inexact Gradients.” ArXiv:2208.12094,
2022.
short: M.B. Berkemeier, S. Peitz, ArXiv:2208.12094 (2022).
date_created: 2022-08-26T06:08:06Z
date_updated: 2022-08-26T06:12:10Z
department:
- _id: '101'
- _id: '655'
external_id:
arxiv:
- '2208.12094'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/pdf/2208.12094
oa: '1'
publication: arXiv:2208.12094
status: public
title: Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using
Inexact Gradients
type: preprint
user_id: '47427'
year: '2022'
...
---
_id: '33306'
author:
- first_name: Amanda Sophie
full_name: Fiege, Amanda Sophie
last_name: Fiege
- first_name: Stefan
full_name: Pape, Stefan
id: '29061'
last_name: Pape
citation:
ama: 'Fiege AS, Pape S. Moodle in der Hochschullehre: Struktur durch HTML-Code.
In: Krähwinkel T, ed. #MoodleKannMehr – nicht nur im Distanzunterricht! .
1st ed. Visual Ink Publishing; 2022:76-78.'
apa: 'Fiege, A. S., & Pape, S. (2022). Moodle in der Hochschullehre: Struktur
durch HTML-Code. In T. Krähwinkel (Ed.), #MoodleKannMehr – nicht nur im Distanzunterricht!
(1st ed., pp. 76–78). Visual Ink Publishing.'
bibtex: '@inbook{Fiege_Pape_2022, edition={1}, title={Moodle in der Hochschullehre:
Struktur durch HTML-Code}, booktitle={#MoodleKannMehr – nicht nur im Distanzunterricht!
}, publisher={Visual Ink Publishing}, author={Fiege, Amanda Sophie and Pape, Stefan},
editor={Krähwinkel, Tanja}, year={2022}, pages={76–78} }'
chicago: 'Fiege, Amanda Sophie, and Stefan Pape. “Moodle in der Hochschullehre:
Struktur durch HTML-Code.” In #MoodleKannMehr – nicht nur im Distanzunterricht!
, edited by Tanja Krähwinkel, 1st ed., 76–78. Visual Ink Publishing, 2022.'
ieee: 'A. S. Fiege and S. Pape, “Moodle in der Hochschullehre: Struktur durch HTML-Code,”
in #MoodleKannMehr – nicht nur im Distanzunterricht! , 1st ed., T. Krähwinkel,
Ed. Visual Ink Publishing, 2022, pp. 76–78.'
mla: 'Fiege, Amanda Sophie, and Stefan Pape. “Moodle in der Hochschullehre: Struktur
durch HTML-Code.” #MoodleKannMehr – nicht nur im Distanzunterricht! , edited
by Tanja Krähwinkel, 1st ed., Visual Ink Publishing, 2022, pp. 76–78.'
short: 'A.S. Fiege, S. Pape, in: T. Krähwinkel (Ed.), #MoodleKannMehr – nicht nur
im Distanzunterricht! , 1st ed., Visual Ink Publishing, 2022, pp. 76–78.'
date_created: 2022-09-08T11:38:01Z
date_updated: 2022-09-08T11:41:27Z
department:
- _id: '1'
edition: '1'
editor:
- first_name: Tanja
full_name: Krähwinkel, Tanja
last_name: Krähwinkel
language:
- iso: ger
license: https://creativecommons.org/licenses/by-sa/4.0/
main_file_link:
- open_access: '1'
url: https://visual-books.com/download/3103/
oa: '1'
page: 76 - 78
publication: '#MoodleKannMehr – nicht nur im Distanzunterricht! '
publication_identifier:
isbn:
- 978-3-96784-19-3
publication_status: published
publisher: Visual Ink Publishing
status: public
title: 'Moodle in der Hochschullehre: Struktur durch HTML-Code'
type: book_chapter
user_id: '29061'
year: '2022'
...
---
_id: '33307'
author:
- first_name: Stefan
full_name: Pape, Stefan
id: '29061'
last_name: Pape
- first_name: Amanda Sophie
full_name: Fiege, Amanda Sophie
last_name: Fiege
- first_name: Ilka
full_name: Mindt, Ilka
id: '32079'
last_name: Mindt
citation:
ama: 'Pape S, Fiege AS, Mindt I. Authentic Englishes.nrw – Developing and Using
Interactive Teaching and Learning Materials on Varieties of English. In: Wawra
D, Rose J, eds. Selected Papers from the 2021 Conference of the German Association
for the Study of English. Vol 33.2. Anglistik. Universitätsverlag Winter;
:15-27. doi:10.33675/ANGL/2022/2/6'
apa: 'Pape, S., Fiege, A. S., & Mindt, I. (n.d.). Authentic Englishes.nrw –
Developing and Using Interactive Teaching and Learning Materials on Varieties
of English. In D. Wawra & J. Rose (Eds.), Selected Papers from the 2021
Conference of the German Association for the Study of English: Vol. 33.2 (pp.
15–27). Universitätsverlag Winter. https://doi.org/10.33675/ANGL/2022/2/6'
bibtex: '@inbook{Pape_Fiege_Mindt, place={Heidelberg}, series={Anglistik}, title={Authentic
Englishes.nrw – Developing and Using Interactive Teaching and Learning Materials
on Varieties of English}, volume={33.2}, DOI={10.33675/ANGL/2022/2/6},
booktitle={Selected Papers from the 2021 Conference of the German Association
for the Study of English}, publisher={Universitätsverlag Winter}, author={Pape,
Stefan and Fiege, Amanda Sophie and Mindt, Ilka}, editor={Wawra, Daniela and Rose,
Jonathan}, pages={15–27}, collection={Anglistik} }'
chicago: 'Pape, Stefan, Amanda Sophie Fiege, and Ilka Mindt. “Authentic Englishes.Nrw
– Developing and Using Interactive Teaching and Learning Materials on Varieties
of English.” In Selected Papers from the 2021 Conference of the German Association
for the Study of English, edited by Daniela Wawra and Jonathan Rose, 33.2:15–27.
Anglistik. Heidelberg: Universitätsverlag Winter, n.d. https://doi.org/10.33675/ANGL/2022/2/6.'
ieee: 'S. Pape, A. S. Fiege, and I. Mindt, “Authentic Englishes.nrw – Developing
and Using Interactive Teaching and Learning Materials on Varieties of English,”
in Selected Papers from the 2021 Conference of the German Association for the
Study of English, vol. 33.2, D. Wawra and J. Rose, Eds. Heidelberg: Universitätsverlag
Winter, pp. 15–27.'
mla: Pape, Stefan, et al. “Authentic Englishes.Nrw – Developing and Using Interactive
Teaching and Learning Materials on Varieties of English.” Selected Papers from
the 2021 Conference of the German Association for the Study of English, edited
by Daniela Wawra and Jonathan Rose, vol. 33.2, Universitätsverlag Winter, pp.
15–27, doi:10.33675/ANGL/2022/2/6.
short: 'S. Pape, A.S. Fiege, I. Mindt, in: D. Wawra, J. Rose (Eds.), Selected Papers
from the 2021 Conference of the German Association for the Study of English, Universitätsverlag
Winter, Heidelberg, n.d., pp. 15–27.'
date_created: 2022-09-08T11:52:14Z
date_updated: 2022-09-14T13:28:23Z
department:
- _id: '1'
doi: 10.33675/ANGL/2022/2/6
editor:
- first_name: Daniela
full_name: Wawra, Daniela
last_name: Wawra
- first_name: Jonathan
full_name: Rose, Jonathan
last_name: Rose
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://angl.winter-verlag.de/article/ANGL/2022/2/6
oa: '1'
page: 15 - 27
place: Heidelberg
publication: Selected Papers from the 2021 Conference of the German Association for
the Study of English
publication_identifier:
eissn:
- 2625-2147
publication_status: inpress
publisher: Universitätsverlag Winter
series_title: Anglistik
status: public
title: Authentic Englishes.nrw – Developing and Using Interactive Teaching and Learning
Materials on Varieties of English
type: book_chapter
user_id: '29061'
volume: '33.2'
year: '2022'
...
---
_id: '33371'
article_type: original
author:
- first_name: Isabel
full_name: Steinhardt, Isabel
id: '90339'
last_name: Steinhardt
orcid: https://orcid.org/0000-0002-2590-6189
citation:
ama: Steinhardt I. Kollaborative Autoethnographien digitaler Praktiken. Eine konzeptionelle,
methodische und theoretische Einführung zu einem Lehr-Forschungsprojekt im ersten
Corona-Semester. DNGPS Working Paper. 2022;8(si):1-11. doi:10.3224/dngps.v8si.01
apa: Steinhardt, I. (2022). Kollaborative Autoethnographien digitaler Praktiken.
Eine konzeptionelle, methodische und theoretische Einführung zu einem Lehr-Forschungsprojekt
im ersten Corona-Semester. DNGPS Working Paper, 8(si), 1–11. https://doi.org/10.3224/dngps.v8si.01
bibtex: '@article{Steinhardt_2022, title={Kollaborative Autoethnographien digitaler
Praktiken. Eine konzeptionelle, methodische und theoretische Einführung zu einem
Lehr-Forschungsprojekt im ersten Corona-Semester}, volume={8}, DOI={10.3224/dngps.v8si.01},
number={si}, journal={DNGPS Working Paper}, publisher={Verlag Barbara Budrich
GmbH}, author={Steinhardt, Isabel}, year={2022}, pages={1–11} }'
chicago: 'Steinhardt, Isabel. “Kollaborative Autoethnographien digitaler Praktiken.
Eine konzeptionelle, methodische und theoretische Einführung zu einem Lehr-Forschungsprojekt
im ersten Corona-Semester.” DNGPS Working Paper 8, no. si (2022): 1–11.
https://doi.org/10.3224/dngps.v8si.01.'
ieee: 'I. Steinhardt, “Kollaborative Autoethnographien digitaler Praktiken. Eine
konzeptionelle, methodische und theoretische Einführung zu einem Lehr-Forschungsprojekt
im ersten Corona-Semester,” DNGPS Working Paper, vol. 8, no. si, pp. 1–11,
2022, doi: 10.3224/dngps.v8si.01.'
mla: Steinhardt, Isabel. “Kollaborative Autoethnographien digitaler Praktiken. Eine
konzeptionelle, methodische und theoretische Einführung zu einem Lehr-Forschungsprojekt
im ersten Corona-Semester.” DNGPS Working Paper, vol. 8, no. si, Verlag
Barbara Budrich GmbH, 2022, pp. 1–11, doi:10.3224/dngps.v8si.01.
short: I. Steinhardt, DNGPS Working Paper 8 (2022) 1–11.
date_created: 2022-09-15T08:03:19Z
date_updated: 2022-09-15T08:34:45Z
ddc:
- '300'
department:
- _id: '121'
doi: 10.3224/dngps.v8si.01
file:
- access_level: closed
content_type: application/pdf
creator: isste
date_created: 2022-09-15T08:33:30Z
date_updated: 2022-09-15T08:33:30Z
file_id: '33374'
file_name: 2022 Steinhardt Kollaborative Autoethnographie DNGPS.pdf
file_size: 177005
relation: main_file
success: 1
file_date_updated: 2022-09-15T08:33:30Z
has_accepted_license: '1'
intvolume: ' 8'
issue: si
keyword:
- Open Science
- kollaborative Autoethnographie
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://www.budrich-journals.de/index.php/dngps/article/view/39212/33438
oa: '1'
page: 1-11
publication: DNGPS Working Paper
publication_identifier:
issn:
- 2365-3329
publication_status: published
publisher: Verlag Barbara Budrich GmbH
status: public
title: Kollaborative Autoethnographien digitaler Praktiken. Eine konzeptionelle, methodische
und theoretische Einführung zu einem Lehr-Forschungsprojekt im ersten Corona-Semester
type: journal_article
user_id: '90339'
volume: 8
year: '2022'
...
---
_id: '33370'
abstract:
- lang: eng
text: Research that investigates respective researchers’ engagement in Open
Science varies widely in the topics addressed, methods employed, and disciplines
investigated, which makes it difficult to integrate and compare its results. To
investigate current outcomes of Open Science research, and to get a better understanding
on well-researched topics and research gaps, we aimed at providing an openly accessible
overview of empirical studies that focus on different aspects of Open Science
in different scientific disciplines, academic groups and geographical regions.
In this paper, we describe a data set of studies about Open Science practices
retrieved following a PRISMA approach to compile a literature review. We included
studies from the Scopus and Web of Science databases with keywords relating to
Open Science between the years 2000 and 2020, as well as a snowball search for
relevant articles. Studies that did not investigate any aspect of Open Science,
or weren’t peer-reviewed were excluded, resulting in a total of 695 remaining
studies. The data set was collaboratively annotated to
ensure intercoder reliability of the coded data.
article_number: '535'
article_type: original
author:
- first_name: Jana
full_name: Lasser, Jana
last_name: Lasser
- first_name: Jürgen
full_name: Schneider, Jürgen
last_name: Schneider
- first_name: Thomas
full_name: Lösch, Thomas
last_name: Lösch
- first_name: Ronny
full_name: Röwert, Ronny
last_name: Röwert
- first_name: Tamara
full_name: Heck, Tamara
last_name: Heck
- first_name: Clemens
full_name: Bluemel, Clemens
last_name: Bluemel
- first_name: Maike
full_name: Neufend, Maike
last_name: Neufend
- first_name: Isabel
full_name: Steinhardt, Isabel
id: '90339'
last_name: Steinhardt
orcid: https://orcid.org/0000-0002-2590-6189
- first_name: Stefan
full_name: Skupien, Stefan
last_name: Skupien
citation:
ama: Lasser J, Schneider J, Lösch T, et al. MapOSR - A mapping review dataset of
empirical studies on Open Science. F1000Research. 2022;11. doi:10.12688/f1000research.121665.1
apa: Lasser, J., Schneider, J., Lösch, T., Röwert, R., Heck, T., Bluemel, C., Neufend,
M., Steinhardt, I., & Skupien, S. (2022). MapOSR - A mapping review dataset
of empirical studies on Open Science. F1000Research, 11, Article
535. https://doi.org/10.12688/f1000research.121665.1
bibtex: '@article{Lasser_Schneider_Lösch_Röwert_Heck_Bluemel_Neufend_Steinhardt_Skupien_2022,
title={MapOSR - A mapping review dataset of empirical studies on Open Science},
volume={11}, DOI={10.12688/f1000research.121665.1},
number={535}, journal={F1000Research}, publisher={F1000 Research Ltd}, author={Lasser,
Jana and Schneider, Jürgen and Lösch, Thomas and Röwert, Ronny and Heck, Tamara
and Bluemel, Clemens and Neufend, Maike and Steinhardt, Isabel and Skupien, Stefan},
year={2022} }'
chicago: Lasser, Jana, Jürgen Schneider, Thomas Lösch, Ronny Röwert, Tamara Heck,
Clemens Bluemel, Maike Neufend, Isabel Steinhardt, and Stefan Skupien. “MapOSR
- A Mapping Review Dataset of Empirical Studies on Open Science.” F1000Research
11 (2022). https://doi.org/10.12688/f1000research.121665.1.
ieee: 'J. Lasser et al., “MapOSR - A mapping review dataset of empirical
studies on Open Science,” F1000Research, vol. 11, Art. no. 535, 2022, doi:
10.12688/f1000research.121665.1.'
mla: Lasser, Jana, et al. “MapOSR - A Mapping Review Dataset of Empirical Studies
on Open Science.” F1000Research, vol. 11, 535, F1000 Research Ltd, 2022,
doi:10.12688/f1000research.121665.1.
short: J. Lasser, J. Schneider, T. Lösch, R. Röwert, T. Heck, C. Bluemel, M. Neufend,
I. Steinhardt, S. Skupien, F1000Research 11 (2022).
date_created: 2022-09-15T08:00:49Z
date_updated: 2022-09-15T08:31:55Z
doi: 10.12688/f1000research.121665.1
intvolume: ' 11'
keyword:
- Open Science
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://f1000research.com/articles/11-535
oa: '1'
publication: F1000Research
publication_identifier:
issn:
- 2046-1402
publication_status: published
publisher: F1000 Research Ltd
quality_controlled: '1'
status: public
title: MapOSR - A mapping review dataset of empirical studies on Open Science
type: journal_article
user_id: '90339'
volume: 11
year: '2022'
...
---
_id: '33377'
abstract:
- lang: ger
text: 'Zur Inhaltsanalyse gibt es bereits diverse Methodenbücher. Warum sollten
Sie also genau das vorliegende Methodenbuch „Qualitative und quantitative Inhaltsanalyse:
digital und automatisiert “lesen? Erstens schließt dieses Buch eine Lücke, der
wir in der Lehre und bei Methodenworkshops immer wieder begegnet sind. Diese Lücke
besteht darin, dass selten eine Übersicht über und Gegenüberstellung verschiedener
Methoden der qualitativen und quantitativen Inhaltsanalyse gegeben wird. Zudem
haben bisherige Lehr-und Methodenbücher in den Sozialwissenschaften teil-und vollautomatisierte
Verfahren der Textanalyse noch nicht aufgegriffen und diese mit bereits etablierten
Verfahren qualitativer und quantitativer Inhaltsanalyse verknüpft. Zweitens bietet
dieses Buch im ersten Teil eine systematische und anwendungsorientierte Einführung
zu den Grundlagen inhaltsanalytischer empirischer Sozialforschung. Im zweiten
Teil werden detaillierte Anleitungen von digital unterstützten qualitativen inhaltsanalytischen
Auswertungstechniken gegeben. Den teil-und vollautomatisierten quantitativen inhaltsanalytischen
Auswertungstechniken widmet sich der dritte Teil des Buches. Bei digital unterstützten
Verfahren werden Sie durch Software bei Ihrer Analyse unterstützt, beispielsweise
bei der digitalen Organisation Ihrer Daten und bei der digitalen Durchführung
der Auswertung. Bei teilautomatisierten Verfahren der Inhaltsanalyse nehmen Ihnen
Software und Tools Teile der Datenanalyse ab, wohingegen bei vollautomatisierten
Verfahren der gesamte Auswertungsprozess und oftmals auch die Datenbeschaffung
durch Programme und Tools durchgeführt wird.'
author:
- first_name: Christian
full_name: Schneijderberg, Christian
last_name: Schneijderberg
- first_name: Oliver
full_name: Wieczorek, Oliver
last_name: Wieczorek
- first_name: Isabel
full_name: Steinhardt, Isabel
id: '90339'
last_name: Steinhardt
orcid: https://orcid.org/0000-0002-2590-6189
citation:
ama: 'Schneijderberg C, Wieczorek O, Steinhardt I. Qualitative und quantitative
Inhaltsanalyse: digital und automatisiert. Eine anwendungsorientierte Einführung
mit empirischen Beispielen und Softwareanwendungen. Beltz Juventa; 2022.'
apa: 'Schneijderberg, C., Wieczorek, O., & Steinhardt, I. (2022). Qualitative
und quantitative Inhaltsanalyse: digital und automatisiert. Eine anwendungsorientierte
Einführung mit empirischen Beispielen und Softwareanwendungen. Beltz Juventa.'
bibtex: '@book{Schneijderberg_Wieczorek_Steinhardt_2022, place={Weinheim, Basel},
series={Standards standardisierter und nichtstandardisierter Sozialforschung},
title={Qualitative und quantitative Inhaltsanalyse: digital und automatisiert.
Eine anwendungsorientierte Einführung mit empirischen Beispielen und Softwareanwendungen},
publisher={Beltz Juventa}, author={Schneijderberg, Christian and Wieczorek, Oliver
and Steinhardt, Isabel}, year={2022}, collection={Standards standardisierter und
nichtstandardisierter Sozialforschung} }'
chicago: 'Schneijderberg, Christian, Oliver Wieczorek, and Isabel Steinhardt. Qualitative
und quantitative Inhaltsanalyse: digital und automatisiert. Eine anwendungsorientierte
Einführung mit empirischen Beispielen und Softwareanwendungen. Standards standardisierter
und nichtstandardisierter Sozialforschung. Weinheim, Basel: Beltz Juventa, 2022.'
ieee: 'C. Schneijderberg, O. Wieczorek, and I. Steinhardt, Qualitative und quantitative
Inhaltsanalyse: digital und automatisiert. Eine anwendungsorientierte Einführung
mit empirischen Beispielen und Softwareanwendungen. Weinheim, Basel: Beltz
Juventa, 2022.'
mla: 'Schneijderberg, Christian, et al. Qualitative und quantitative Inhaltsanalyse:
digital und automatisiert. Eine anwendungsorientierte Einführung mit empirischen
Beispielen und Softwareanwendungen. Beltz Juventa, 2022.'
short: 'C. Schneijderberg, O. Wieczorek, I. Steinhardt, Qualitative und quantitative
Inhaltsanalyse: digital und automatisiert. Eine anwendungsorientierte Einführung
mit empirischen Beispielen und Softwareanwendungen, Beltz Juventa, Weinheim, Basel,
2022.'
date_created: 2022-09-15T08:46:45Z
date_updated: 2022-09-15T08:46:51Z
ddc:
- '300'
file:
- access_level: closed
content_type: application/pdf
creator: isste
date_created: 2022-09-15T08:44:04Z
date_updated: 2022-09-15T08:44:04Z
file_id: '33378'
file_name: 2022 Schneijderberg_ua_quali-quanti Inhaltsanalyse.pdf
file_size: 11413008
relation: main_file
success: 1
file_date_updated: 2022-09-15T08:44:04Z
has_accepted_license: '1'
keyword:
- qualitative Inhaltsanalyse
- quantitative Inhaltsanalyse
language:
- iso: ger
main_file_link:
- open_access: '1'
url: https://www.beltz.de/fachmedien/erziehungswissenschaft/produkte/details/48826-qualitative-und-quantitative-inhaltsanalyse-digital-und-automatisiert.html
oa: '1'
place: Weinheim, Basel
publication_identifier:
eisbn:
- 978-3-7799-7037-8 E
publication_status: published
publisher: Beltz Juventa
series_title: Standards standardisierter und nichtstandardisierter Sozialforschung
status: public
title: 'Qualitative und quantitative Inhaltsanalyse: digital und automatisiert. Eine
anwendungsorientierte Einführung mit empirischen Beispielen und Softwareanwendungen'
type: book
user_id: '90339'
year: '2022'
...