@book{44719,
  abstract     = {{„Lerne deinen Körper besser kennen“, „Das Beste für deine Gesundheit“ und „Ihre Transformation beginnt jetzt“ - mit Versprechen wie diesen vermitteln die Produkttexte von Wearables wie Fitnesstracker und Smartwatches ein ganz bestimmtes Bild ihrer vorgesehenen Nutzer*innen und deren Nutzung. Verbunden mit den kleinen, am Handgelenk getragenen Geräten sind Fragen nach Erkenntnisgewinn und Kontrollverlust, Selbstoptimierung und Quantifizierungslogiken, Eigenverantwortung und Fremdsteuerung. Die vorliegende Arbeit widmet sich diesem komplexen Spannungsfeld und verfolgt dabei einen multiperspektivischen Ansatz: im Rahmen einer Dispositivanalyse werden die einzelnen Elemente des Wearable-Dispositivs als eigenständige, empirisch zu untersuchende Analysegegenstände betrachtet, um so das Zusammenwirken und die komplexe Beziehung von Diskursen, Gegenständen, Nutzung, Subjekten und Gesellschaft zu erforschen. Ein besonderes Erkenntnisinteresse liegt dabei auf dem Wissen, was sich über Wearables etabliert hat und sich in den Alltagspraktiken der Nutzer*innen widerspiegelt sowie bei der Frage nach den möglichen Funktionen und Auswirkungen des Wearable-Dispositivs. }},
  author       = {{Schloots, Franziska Margarete}},
  isbn         = {{9783658409012}},
  issn         = {{2512-112X}},
  keywords     = {{Selbstvermessung, Dispositivanalyse, Gesundheitsdiskurs, Quantifizierungsgesellschaft, Wearables, Selbstoptimierung}},
  publisher    = {{Springer Fachmedien Wiesbaden}},
  title        = {{{Mit dem Leben Schritt halten - Eine Analyse des Wearable-Dispositivs}}},
  doi          = {{10.1007/978-3-658-40902-9}},
  year         = {{2023}},
}

@article{46784,
  author       = {{Wallscheid, Oliver and Peitz, Sebastian and Stenner, Jan and Weber, Daniel and Boshoff, Septimus and Meyer, Marvin and Chidananda, Vikas and Schweins, Oliver}},
  issn         = {{2475-9066}},
  journal      = {{Journal of Open Source Software}},
  keywords     = {{General Earth and Planetary Sciences, General Environmental Science}},
  number       = {{89}},
  publisher    = {{The Open Journal}},
  title        = {{{ElectricGrid.jl - A Julia-based modeling and simulationtool for power electronics-driven electric energy grids}}},
  doi          = {{10.21105/joss.05616}},
  volume       = {{8}},
  year         = {{2023}},
}

@article{46186,
  author       = {{Höper, Lukas and Schulte, Carsten}},
  issn         = {{0025-5866}},
  journal      = {{MNU journal}},
  number       = {{4}},
  pages        = {{314--320}},
  publisher    = {{Verlag Klaus Seeberger}},
  title        = {{{Paradigmenwechsel vom klassischen zum datengetriebenen Problemlösen im Informatikunterricht}}},
  volume       = {{76}},
  year         = {{2023}},
}

@inproceedings{35014,
  author       = {{Blömer, Johannes and Bobolz, Jan and Bröcher, Henrik}},
  location     = {{Taipeh, Taiwan}},
  title        = {{{On the impossibility of surviving (iterated) deletion of weakly dominated strategies in rational MPC}}},
  year         = {{2023}},
}

@inproceedings{43458,
  author       = {{Blömer, Johannes and Bobolz, Jan and Porzenheim, Laurens Alexander}},
  location     = {{Guangzhou, China}},
  title        = {{{A Generic Construction of an Anonymous Reputation System and Instantiations from Lattices}}},
  year         = {{2023}},
}

@inproceedings{47050,
  author       = {{Wecker, Daniel  and Yigitbas, Enes}},
  booktitle    = {{Proceedings of the ACM Symposium on Spatial User Interaction (SUI 2023)}},
  publisher    = {{ACM}},
  title        = {{{Minimizing Eye Movements and Distractions in Head-Mounted Augmented Reality through Eye-Gaze Adaptiveness}}},
  year         = {{2023}},
}

@article{47051,
  author       = {{Yigitbas, Enes and Schmidt, Maximilian and Bucchiarone, Antonio and Gottschalk, Sebastian and Engels, Gregor}},
  journal      = {{Science of Computer Programming}},
  publisher    = {{Elsevier}},
  title        = {{{GaMoVR: Gamification-Based UML Learning Environment in Virtual Reality}}},
  year         = {{2023}},
}

@inproceedings{47057,
  author       = {{Schmidt, Leonard and Yigitbas, Enes}},
  booktitle    = {{Proceedings of the 27th International Workshop on Personalization and Recommendation}},
  publisher    = {{GI DL}},
  title        = {{{Transitional Cross Reality Interfaces for Spatially Demanding Search and Collect Tasks }}},
  year         = {{2023}},
}

@inproceedings{47055,
  author       = {{Neumayr, Thomas and Yigitbas, Enes and Augstein, Mirjam and Herder, Eelco}},
  booktitle    = {{Proceedings of the Mensch & Computer (2023)}},
  title        = {{{ABIS 2023 – 27th International Workshop on Personalization and Recommendation}}},
  year         = {{2023}},
}

@misc{47134,
  author       = {{Deppe, Volker}},
  title        = {{{Routing in Hypergraphs}}},
  year         = {{2023}},
}

@inproceedings{47150,
  author       = {{Yigitbas, Enes and Witalinski, Iwo and Gottschalk, Sebastian and Engels, Gregor}},
  booktitle    = {{Proceedings of the 24th International Conference on Product-Focused Software Process Improvement (PROFES 2023)}},
  publisher    = {{Springer}},
  title        = {{{Virtual Reality Collaboration Platform for Agile Software Development}}},
  year         = {{2023}},
}

@inproceedings{46813,
  abstract     = {{Modelling of dynamic systems plays an important role in many engineering disciplines. Two different approaches are physical modelling and data‐driven modelling, both of which have their respective advantages and disadvantages. By combining these two approaches, hybrid models can be created in which the respective disadvantages are mitigated, with discrepancy models being a particular subclass. Here, the basic system behaviour is described physically, that is, in the form of differential equations. Inaccuracies resulting from insufficient modelling or numerics lead to a discrepancy between the measurements and the model, which can be compensated by a data‐driven error correction term. Since discrepancy methods still require a large amount of measurement data, this paper investigates the extent to which a single discrepancy model can be trained for a physical model with additional parameter dependencies without the need for retraining. As an example, a damped electromagnetic oscillating circuit is used. The physical model is realised by a differential equation describing the electric current, considering only inductance and capacitance; dissipation due to resistance is neglected. This creates a discrepancy between measurement and model, which is corrected by a data‐driven model. In the experiments, the inductance and the capacity are varied. It is found that the same data‐driven model can only be used if additional parametric dependencies in the data‐driven term are considered as well.}},
  author       = {{Wohlleben, Meike Claudia and Muth, Lars and Peitz, Sebastian and Sextro, Walter}},
  booktitle    = {{Proceedings in Applied Mathematics and Mechanics}},
  issn         = {{1617-7061}},
  keywords     = {{Electrical and Electronic Engineering, Atomic and Molecular Physics, and Optics}},
  publisher    = {{Wiley}},
  title        = {{{Transferability of a discrepancy model for the dynamics of electromagnetic oscillating circuits}}},
  doi          = {{10.1002/pamm.202300039}},
  year         = {{2023}},
}

@article{47420,
  author       = {{Kürpick, Christian and Rasor, Anja and Scholtysik, Michel and Kühn, Arno and Koldewey, Christian and Dumitrescu, Roman}},
  issn         = {{2212-8271}},
  journal      = {{Procedia CIRP}},
  keywords     = {{General Medicine}},
  pages        = {{614--619}},
  publisher    = {{Elsevier BV}},
  title        = {{{An Integrative View of the Transformations towards Sustainability and Digitalization: The Case for a Dual Transformation}}},
  doi          = {{10.1016/j.procir.2023.02.155}},
  volume       = {{119}},
  year         = {{2023}},
}

@inproceedings{44146,
  abstract     = {{Many Android applications collect data from users. When they do, they must
protect this collected data according to the current legal frameworks. Such
data protection has become even more important since the European Union rolled
out the General Data Protection Regulation (GDPR). App developers have limited
tool support to reason about data protection throughout their app development
process. Although many Android applications state a privacy policy, privacy
policy compliance checks are currently manual, expensive, and prone to error.
One of the major challenges in privacy audits is the significant gap between
legal privacy statements (in English text) and technical measures that Android
apps use to protect their user's privacy. In this thesis, we will explore to
what extent we can use static analysis to answer important questions regarding
data protection. Our main goal is to design a tool based approach that aids app
developers and auditors in ensuring data protection in Android applications,
based on automated static program analysis.}},
  author       = {{Khedkar, Mugdha}},
  booktitle    = {{2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), Melbourne, Australia, 2023, pp. 197-199}},
  keywords     = {{static analysis, data protection and privacy, GDPR compliance}},
  title        = {{{Static Analysis for Android GDPR Compliance Assurance}}},
  doi          = {{10.1109/ICSE-Companion58688.2023.00054}},
  year         = {{2023}},
}

@inproceedings{56096,
  author       = {{Gil, Oliver Fernández and Patrizi, Fabio and Perelli, Giuseppe and Turhan, Anni-Yasmin}},
  booktitle    = {{ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023)}},
  editor       = {{Gal, Kobi and Nowé, Ann and Nalepa, Grzegorz J. and Fairstein, Roy and Radulescu, Roxana}},
  pages        = {{708–715}},
  publisher    = {{IOS Press}},
  title        = {{{Optimal Alignment of Temporal Knowledge Bases}}},
  doi          = {{10.3233/FAIA230335}},
  volume       = {{372}},
  year         = {{2023}},
}

@misc{48430,
  abstract     = {{Bei dem betrachteten Speicherproblem werden Daten mit verschiedenen
Zugriffswahrscheinlichkeiten auf Speicher mit verschiedenen Bandbreiten
und Kapazitäten aufgeteilt, dabei sind Replikate erlaubt.
Es wird die nach Zugriffswahrscheinlichkeit gewichtete kleinste Bandbreite der Daten maximiert.
Wir zeigen, dass sowohl das diskrete Speicherproblem, bei dem die Bandbreite der Speicher jeweils
gleichmäßig auf die dort abgelegten Daten aufgeteilt wird, als auch das kontinuierliche
Speicherproblem, bei dem die Bandbreite der Speicher beliebig auf abgelegte Daten verteilt werden
darf, NP-schwer ist.
Es können also, wenn P ̸ = NP, keine effizienten Algorithmen für eine optimale Lösung existieren.
Stattdessen zeigen wir jeweils einen 1/2-Approximationsalgorithmus.}},
  author       = {{Decking, Leo}},
  title        = {{{Zuweisung verteilter Speicher unter Maximierung der minimalen gewichteten Bandbreite}}},
  year         = {{2023}},
}

@inproceedings{59412,
  author       = {{Karakaya, Kadiray and Bodden, Eric}},
  booktitle    = {{2023 IEEE Conference on Software Testing, Verification and Validation (ICST)}},
  publisher    = {{IEEE}},
  title        = {{{Two Sparsification Strategies for Accelerating Demand-Driven Pointer Analysis}}},
  doi          = {{10.1109/icst57152.2023.00036}},
  year         = {{2023}},
}

@inproceedings{41812,
  author       = {{Luo, Linghui and Piskachev, Goran and Krishnamurthy, Ranjith and Dolby, Julian and Schäf, Martin and Bodden, Eric}},
  booktitle    = {{IEEE International Conference on Software Testing, Verification and Validation (ICST)}},
  title        = {{{Model Generation For Java Frameworks}}},
  year         = {{2023}},
}

@book{48666,
  abstract     = {{Unter dem Einfluss der Digitalisierung wandeln sich mechatronische Produkte zunehmend in cyber-physische Systeme (CPS). Diese sind in der Lage, umfangreiche Daten während ihres Betriebs zu sammeln und über digitale Netzinfrastrukturen zur Verfügung zu stellen. Gemeinsam mit weiteren Daten aus der Betriebsphase versprechen sie wertvolle Erkenntnisse über das Produkt und dessen Nutzer, welche für die Hersteller der CPS insbesondere für die Planung zukünftiger Produktgenerationenrelevant sind. Die zielgerichtete Nutzung von Betriebsdaten in der strategischen Produktplanung stellt produzierende Unternehmen jedoch noch vor zahlreiche Herausforderungen, z. B. hinsichtlich der Identifizierung Erfolg versprechender Use Cases. Das vorliegende Buch greift diese Herausforderungen auf und stellt ein Instrumentarium vor, das produzierende Unternehmen zur datengestützten Produktplanung befähigt. Neben der Vorstellung praxiserprobter Methoden und Werkzeuge werden Einblicke in vier Pilotprojekte gegeben. Das Instrumentarium entstand im Forschungsprojekt „DizRuPt“, das vom Bundesministerium für Bildung und Forschung (BMBF) gefördert wurde.}},
  editor       = {{Dumitrescu, Roman and Koldewey, Christian}},
  publisher    = {{Heinz Nixdorf Institut}},
  title        = {{{Datengestützte Produktplanung}}},
  doi          = {{10.17619/UNIPB/1-1667}},
  volume       = {{408}},
  year         = {{2023}},
}

@inproceedings{64114,
  author       = {{Ahmed, Qazi Arbab and Awais, Muhammad and Platzner, Marco}},
  booktitle    = {{2023 24th International Symposium on Quality Electronic Design (ISQED)}},
  publisher    = {{IEEE}},
  title        = {{{MAAS: Hiding Trojans in Approximate Circuits}}},
  doi          = {{10.1109/isqed57927.2023.10129286}},
  year         = {{2023}},
}