@misc{56339,
  author       = {{Kokew, Stephan Matthias}},
  booktitle    = {{Der Islam}},
  issn         = {{1613-0928}},
  number       = {{1}},
  pages        = {{242--246}},
  title        = {{{Review of Antonia Bosanquet, Minding their Place. Space and Religious Hierarchy in Ibn al-Qayyim’s Aḥkām ahl al-dhimma}}},
  doi          = {{10.1515/islam-2022-0010}},
  volume       = {{99}},
  year         = {{2022}},
}

@article{34640,
  author       = {{Schloots, Franziska Margarete}},
  issn         = {{2192-5445}},
  journal      = {{Rabbit Eye - Zeitschrift für Filmforschung}},
  keywords     = {{Wearable, selft-tracking, Selbstvermessung, Animation, Tamagotchi, Anschaulichkeit}},
  pages        = {{65--77}},
  title        = {{{Die Tamagotchisierung des Selbst. Zur Anschaulichkeit von animierten Körperdaten}}},
  volume       = {{12}},
  year         = {{2022}},
}

@inproceedings{52920,
  author       = {{Baader, Franz and Koopmann, Patrick and Michel, Friedrich and Turhan, Anni-Yasmin and Zarrieß, Benjamin}},
  booktitle    = {{Proceedings of the 35th International Workshop on Description Logics (DL 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022}},
  editor       = {{Arieli, Ofer and Homola, Martin and Jung, Jean Christoph and Mugnier, Marie-Laure}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{Efficient TBox Reasoning with Value Restrictions Using the FL0wer Reasoner (Extended Abstract)}}},
  volume       = {{3263}},
  year         = {{2022}},
}

@inproceedings{52921,
  author       = {{Tirtarasa, Satyadharma and Turhan, Anni-Yasmin}},
  booktitle    = {{Proceedings of the 35th International Workshop on Description Logics (DL 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022}},
  editor       = {{Arieli, Ofer and Homola, Martin and Jung, Jean Christoph and Mugnier, Marie-Laure}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{A New Dimension to Generalization: Computing Temporal EL Concepts from Positive Examples (Extended Abstract)}}},
  volume       = {{3263}},
  year         = {{2022}},
}

@inproceedings{52922,
  author       = {{Peñaloza, Rafael and Turhan, Anni-Yasmin}},
  booktitle    = {{Proceedings of the 8th Workshop on Formal and Cognitive Reasoning co-located with the 45th German Conference on Artificial Intelligence (KI 2022), Virtual Event, Trier, Germany, September 19, 2022}},
  editor       = {{Beierle, Christoph and Ragni, Marco and Stolzenburg, Frieder and Sauerwald, Kai and Thimm, Matthias}},
  pages        = {{90–101}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{User-aware Explications of Ontology Consequences: Levelling Technicality}}},
  volume       = {{3242}},
  year         = {{2022}},
}

@article{47961,
  abstract     = {{<jats:p>Due to failures or even the absence of an electricity grid, microgrid systems are becoming popular solutions for electrifying African rural communities. However, they are heavily stressed and complex to control due to their intermittency and demand growth. Demand side management (DSM) serves as an option to increase the level of flexibility on the demand side by scheduling users’ consumption patterns profiles in response to supply. This paper proposes a demand-side management strategy based on load shifting and peak clipping. The proposed approach was modelled in a MATLAB/Simulink R2021a environment and was optimized using the artificial neural network (ANN) algorithm. Simulations were carried out to test the model’s efficacy in a stand-alone PV-battery microgrid in East Africa. The proposed algorithm reduces the peak demand, smoothing the load profile to the desired level, and improves the system’s peak to average ratio (PAR). The presence of deferrable loads has been considered to bring more flexible demand-side management. Results promise decreases in peak demand and peak to average ratio of about 31.2% and 7.5% through peak clipping. In addition, load shifting promises more flexibility to customers.</jats:p>}},
  author       = {{Philipo, Godiana Hagile and Kakande, Josephine Nakato and Krauter, Stefan}},
  issn         = {{1996-1073}},
  journal      = {{Energies}},
  keywords     = {{Energy (miscellaneous), Energy Engineering and Power Technology, Renewable Energy, Sustainability and the Environment, Electrical and Electronic Engineering, Control and Optimization, Engineering (miscellaneous), Building and Construction}},
  number       = {{14}},
  publisher    = {{MDPI AG}},
  title        = {{{Neural Network-Based Demand-Side Management in a Stand-Alone Solar PV-Battery Microgrid Using Load-Shifting and Peak-Clipping}}},
  doi          = {{10.3390/en15145215}},
  volume       = {{15}},
  year         = {{2022}},
}

@misc{54978,
  booktitle    = {{Der fremdsprachliche Unterricht Spanisch}},
  editor       = {{del Valle, Victoria}},
  issn         = {{1611-6510}},
  publisher    = {{Friedrich Verlag}},
  title        = {{{Minificciones}}},
  year         = {{2022}},
}

@book{54904,
  editor       = {{del Valle, Victoria}},
  publisher    = {{Universität Paderborn}},
  title        = {{{"Antigone" de Jean Anouilh: Projects de théâtre pour une pédagogie performative}}},
  doi          = {{10.17619/UNIPB/1-1602}},
  year         = {{2022}},
}

@inproceedings{51343,
  abstract     = {{This paper presents preliminary work on the formalization of three prominent cognitive biases in the diagnostic reasoning process over epileptic seizures, psychogenic seizures and syncopes. Diagnostic reasoning is understood as iterative exploration of medical evidence. This exploration is represented as a partially observable Markov decision process where the state (i.e., the correct diagnosis) is uncertain. Observation likelihoods and belief updates are computed using a Bayesian network which defines the interrelation between medical risk factors, diagnoses and potential findings. The decision problem is solved via partially observable upper confidence bounds for trees in Monte-Carlo planning. We compute a biased diagnostic exploration policy by altering the generated state transition, observation and reward during look ahead simulations. The resulting diagnostic policies reproduce reasoning errors which have only been described informally in the medical literature. We plan to use this formal representation in the future to inversely detect and classify biased reasoning in actual diagnostic trajectories obtained from physicians.}},
  author       = {{Battefeld, Dominik and Kopp, Stefan}},
  booktitle    = {{Proceedings of the 8th Workshop on Formal and Cognitive Reasoning}},
  keywords     = {{Diagnostic reasoning, Cognitive bias, Cognitive model, POMDP, Bayesian network, Epilepsy, CDSS}},
  location     = {{Trier}},
  title        = {{{Formalizing cognitive biases in medical diagnostic reasoning}}},
  year         = {{2022}},
}

@book{56470,
  author       = {{Teubert, Hilke and Zobe, Christina}},
  publisher    = {{Zugriff am DATUM unter https://wimasu.de/kleine-spiele-im-sportunterricht-planen-spielen-auswerten/}},
  title        = {{{Kleine Spiele planen, spielen und auswerten. Beitrag zur Spielesammlung für den Sportunterricht by Teubert & Friends}}},
  year         = {{2022}},
}

@book{56446,
  author       = {{Teubert, Hilke}},
  publisher    = {{Zugriff unter https://wimasu.de/8-schoene-kennenlern-und-kooperationsspiele-fuer-den-sportunterricht/}},
  title        = {{{8 schöne Kennenlern- und Kooperationsspiele für den Sportunterricht}}},
  year         = {{2022}},
}

@inbook{56447,
  author       = {{Teubert, Hilke}},
  booktitle    = {{Kompetenzorientierung und Bewegungsexpertise im Turnen. 11. Jahrestagung der dvs-Kommission Gerätturnen vom 01.-03.09.2020}},
  editor       = {{Menze-Sonneck, Andrea and Vinken, Pia Maria}},
  pages        = {{111--119}},
  publisher    = {{Feldhaus Verlag}},
  title        = {{{Einblicke in die Online-Lehre der Fachausbildung Bewegen an Geräten im „Corona-Sommersemester 2020“ an der Universität Paderborn}}},
  year         = {{2022}},
}

@inbook{56886,
  author       = {{Prietzel, Malte}},
  booktitle    = {{Die Habsburger im Mittelalter. Aufstieg einer Dynastie, hg. von Alexander Schubert}},
  pages        = {{104--111}},
  title        = {{{Der König im Krieg. Die Schlachten von Dürnkrut und Göllheim}}},
  year         = {{2022}},
}

@book{56469,
  author       = {{Teubert, Hilke}},
  publisher    = {{Eingeschränkter Zugriff am DATUM unter https://wimasu.de/shop/kleine-spiele-kennenlernen-kooperieren/}},
  title        = {{{Kennenlernen und Kooperieren. Die Große Spielesammlung für den Sportunterricht.}}},
  year         = {{2022}},
}

@inproceedings{50288,
  author       = {{Daniel-Söltenfuß, Desiree and Breuing, Friederike}},
  location     = {{Universität Paderborn}},
  title        = {{{Innovation and transfer processes in the German VET-system. Insights into the meta-research project 'ITiB'}}},
  year         = {{2022}},
}

@misc{43002,
  author       = {{Schott, Alicia and Neukötter, Moritz}},
  title        = {{{Entwicklung einer Anlage zur Pulverabscheidung im Filament Extension Atomization Prozess}}},
  year         = {{2022}},
}

@article{30735,
  abstract     = {{While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.}},
  author       = {{Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}},
  issn         = {{1019-6781}},
  journal      = {{Electronic Markets}},
  keywords     = {{Management of Technology and Innovation, Marketing, Computer Science Applications, Economics and Econometrics, Business and International Management}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Systematizing the lexicon of platforms in information systems: a data-driven study}}},
  doi          = {{10.1007/s12525-022-00530-6}},
  year         = {{2022}},
}

@inproceedings{56251,
  abstract     = {{<jats:p>Statistical reasoning and the confrontation with first ideas of uncertainty can already be enhanced in primary school. A challenge is how to relate theoretical-combinatorial aspects to empirical frequency aspects, given that fraction concepts are usually not available at primary school. In the frame of a Design Based Research approach we have designed and realized a teaching sequence consisting of seven lessons to develop statistical reasoning about uncertainty of grade 4 students (age 10-11). To supervise their learning processes we collected data on different levels: (a) written pre/post-tests, (b) working notes after each lesson and (c) interviews after the teaching unit. In this paper we will mainly present the design of teaching unit and first results from the analysis of pre- and posttests.</jats:p>}},
  author       = {{Frischemeier, Daniel and Biehler, Rolf}},
  booktitle    = {{Decision Making Based on Data Proceedings IASE 2019 Satellite Conference}},
  publisher    = {{International Association for Statistical Education}},
  title        = {{{Design of a teaching unit to develop primary school students ́ reasoning about uncertainty in multi-step chance experiments}}},
  doi          = {{10.52041/srap.19304}},
  year         = {{2022}},
}

@inproceedings{26539,
  abstract     = {{In control design most control strategies are model-based and require accurate models to be applied successfully. Due to simplifications and the model-reality-gap physics-derived models frequently exhibit deviations from real-world-systems. Likewise, purely data-driven methods often do not generalise well enough and may violate physical laws. Recently Physics-Guided Neural Networks (PGNN) and physics-inspired loss functions separately have shown promising results to conquer these drawbacks. In this contribution we extend existing methods towards the identification of non-autonomous systems and propose a combined approach PGNN-L, which uses a PGNN and a physics-inspired loss term (-L) to successfully identify the system's dynamics, while maintaining the consistency with physical laws. The proposed method is demonstrated on two real-world nonlinear systems and outperforms existing techniques regarding complexity and reliability.}},
  author       = {{Götte, Ricarda-Samantha and Timmermann, Julia}},
  booktitle    = {{2022 3rd International Conference on Artificial Intelligence, Robotics and Control (AIRC)}},
  keywords     = {{data-driven, physics-based, physics-informed, neural networks, system identification, hybrid modelling}},
  location     = {{Cairo, Egypt}},
  pages        = {{67--76}},
  title        = {{{Composed Physics- and Data-driven System Identification for Non-autonomous Systems in Control Engineering}}},
  doi          = {{10.1109/AIRC56195.2022.9836982}},
  year         = {{2022}},
}

@inproceedings{31066,
  abstract     = {{While trade-offs between modeling effort and model accuracy remain a major concern with system identification, resorting to data-driven methods often leads to a complete disregard for physical plausibility. To address this issue, we propose a physics-guided hybrid approach for modeling non-autonomous systems under control. Starting from a traditional physics-based model, this is extended by a recurrent neural network and trained using a sophisticated multi-objective strategy yielding physically plausible models. While purely data-driven methods fail to produce satisfying results, experiments conducted on real data reveal substantial accuracy improvements by our approach compared to a physics-based model. }},
  author       = {{Schön, Oliver and Götte, Ricarda-Samantha and Timmermann, Julia}},
  booktitle    = {{14th IFAC Workshop on Adaptive and Learning Control Systems (ALCOS 2022)}},
  keywords     = {{neural networks, physics-guided, data-driven, multi-objective optimization, system identification, machine learning, dynamical systems}},
  location     = {{Casablanca, Morocco}},
  number       = {{12}},
  pages        = {{19--24}},
  title        = {{{Multi-Objective Physics-Guided Recurrent Neural Networks for Identifying Non-Autonomous Dynamical Systems}}},
  doi          = {{https://doi.org/10.1016/j.ifacol.2022.07.282}},
  volume       = {{55}},
  year         = {{2022}},
}