@inproceedings{64095,
author = {{Scheideler, Christian and Augustine , John and Werthmann, Julian}},
title = {{{Supervised Distributed Computing. }}},
year = {{2025}},
}
@inproceedings{64112,
author = {{Jalil, Farjana and Awais, Muhammad and Ahmed, Qazi Arbab and Mohammadi, Hassan Ghasemzadeh and Jungeblut, Thorsten and Platzner, Marco}},
booktitle = {{2025 55th Annual IEEE/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W)}},
publisher = {{IEEE}},
title = {{{Deep&Wide: Achieving Area Efficiency in Scalable Approximate Accelerators}}},
doi = {{10.1109/dsn-w65791.2025.00048}},
year = {{2025}},
}
@inproceedings{64113,
author = {{Hadipour, Amir Hossein and Jafari, Atousa and Awais, Muhammad and Platzner, Marco}},
booktitle = {{2025 IEEE 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS)}},
publisher = {{IEEE}},
title = {{{A Two-Stage Approximation Methodology for Efficient DNN Hardware Implementation}}},
doi = {{10.1109/ddecs63720.2025.11006769}},
year = {{2025}},
}
@inproceedings{64219,
author = {{Graunke, Jannis and Bita, Isaac Mpidi and Hermelingmeier, Dominik and Humpert, Lynn and Schierbaum, Anja and Dumitrescu, Roman}},
booktitle = {{2025 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE)}},
publisher = {{IEEE}},
title = {{{Evolving Modularity: Rethinking Architecture in Product and Organizational Systems}}},
doi = {{10.1109/rasse64831.2025.11315315}},
year = {{2025}},
}
@inproceedings{64220,
author = {{Disselkamp, Jan-Philipp and Seidenberg, Tobias and Lick, Jonas and Dumitrescu, Roman}},
booktitle = {{2025 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE)}},
publisher = {{IEEE}},
title = {{{24 Reasons for the Failure of Integrative and Integrated Product and Production System Development Methods}}},
doi = {{10.1109/rasse64831.2025.11315397}},
year = {{2025}},
}
@article{64222,
author = {{Ködding, Patrick and Koldewey, Christian and Dumitrescu, Roman}},
issn = {{0360-8581}},
journal = {{IEEE Engineering Management Review}},
pages = {{1--9}},
publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
title = {{{Tailoring scenario projects with method and tool building blocks}}},
doi = {{10.1109/emr.2025.3646110}},
year = {{2025}},
}
@inproceedings{64229,
abstract = {{ABSTRACT:This paper presents the MBSE-Graph-RAG framework to address key challenges in Model-Based Systems Engineering (MBSE). Traditional MBSE tools suffer from usability barriers, limited accessibility, and integration challenges. By combining knowledge graphs with Retrieval-Augmented Generation (RAG), the proposed framework enables AI-Augmented engineering through natural language interactions and automated system architecture generation. A systematic literature review establishes a solid research foundation, identifying gaps in AI-assisted MBSE. Key contributions include a structured MBSE-Graph interface, improved usability via Large Language Models (LLMs), and automated graph construction aligned with SysML. A proof-of-concept demonstrates the potential of this approach to enhance MBSE by reducing complexity, improving data accessibility, and supporting engineering collaboration.}},
author = {{Hanke, Fabian and Mpidi Bita, Isaac and von Heißen, Oliver and Weller, Julian and Hovemann, Aschot and Dumitrescu, Roman}},
booktitle = {{Proceedings of the Design Society}},
issn = {{2732-527X}},
pages = {{439--448}},
publisher = {{Cambridge University Press (CUP)}},
title = {{{AI-augmented systems engineering: conceptual application of retrieval-augmented generation for model-based systems engineering graph}}},
doi = {{10.1017/pds.2025.10058}},
volume = {{5}},
year = {{2025}},
}
@article{64253,
abstract = {{This paper presents a comprehensive design framework for Enterprise Architecture aimed at facilitating decision-driven analytics in smart factories. The motivation behind this research lies in challenges faced by manufacturing companies, such as skilled labor shortages and increasing global competition, alongside the imperative for sustainable production. This journal provides a novel approach for designing and documenting prescriptive analytics use cases in manufacturing environments. The framework addresses the need for effective integration of advanced data analytics and prescriptive analytics solutions within existing production environments, thereby enhancing operational efficiency and decision-making processes. A Design Science Research approach is used to iteratively derive a framework based on stakeholder needs and activities along the prescriptive analytics use case development cycle. The resulting framework is demonstrated and evaluated in an IoT Factory setup in a research facility. From a practical perspective, the framework supports manufacturing companies in systematically designing prescriptive analytics use cases. From a research perspective, it contributes to the body of knowledge on Enterprise Architecture Management (EAM) by operationalizing the design of prescriptive analytics use cases in manufacturing contexts. The main contributions of this study include the development of a framework that supports the planning, design, and integration of prescriptive analytics use cases. This framework fosters interdisciplinary collaboration and aids in managing the complexity of data-driven projects.}},
author = {{Weller, Julian and Dumitrescu, Roman}},
issn = {{2079-9292}},
journal = {{Electronics}},
number = {{21}},
publisher = {{MDPI AG}},
title = {{{Decision-Driven Analytics in Smart Factories: Enterprise Architecture Framework for Use Case Specification and Engineering (FUSE)}}},
doi = {{10.3390/electronics14214271}},
volume = {{14}},
year = {{2025}},
}
@inproceedings{64252,
abstract = {{ABSTRACT:The increasing complexity of modern product and production system development, driven by dynamic market demands, supply chain disruptions and economic pressures, poses significant challenges for companies. Existing methodologies often fall short due to their domain-specific focus, inconsistent terminology and lack of integration. To address these challenges, this paper presents a taxonomy for integrative product and production system development. The taxonomy systematically structures key elements, dependencies and processes to improve collaboration, decision-making and communication within organisations. Developed iteratively the taxonomy identifies ten core artefacts. It enables organisations to better plan improvements, synchronise development processes, and select appropriate methods and tools.}},
author = {{Disselkamp, Jan-Philipp and Seidenberg, Tobias and Westphal, Svenja and Lick, Jonas and Ptock, Lukas and Wyrwich, Fabian and Hovemann, Aschot and Dumitrescu, Roman}},
booktitle = {{Proceedings of the Design Society}},
issn = {{2732-527X}},
pages = {{2121--2130}},
publisher = {{Cambridge University Press (CUP)}},
title = {{{Integrative and Integrated product and production system development: a taxonomy for managing dependencies and processes}}},
doi = {{10.1017/pds.2025.10226}},
volume = {{5}},
year = {{2025}},
}
@inproceedings{59517,
author = {{Lick, Jonas and Kattenstroth, Fiona and Trienens, Malte and Disselkamp, Jan-Philipp and Kühn, Arno and Dumitrescu, Roman}},
booktitle = {{2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}},
publisher = {{IEEE}},
title = {{{Guidance on a Digital Factory Twin: Proposal for a Reference Architecture}}},
doi = {{10.1109/ictmod63116.2024.10878221}},
year = {{2025}},
}
@inbook{64254,
author = {{Dumitrescu, Roman and Riedel, Oliver and Henke, Michael and Metternich, Joachim and Ihlenfeldt, Steffen and Koldewey, Christian}},
booktitle = {{Gaia-X in industriellen Wertschöpfungsnetzwerken – Erkenntnisse aus der Förderlinie InGAIA-X}},
isbn = {{9783186204165}},
publisher = {{VDI Verlag}},
title = {{{Gaia-X in industriellen Wertschöpfungsnetzwerken – Erkenntnisse aus der Förderlinie InGAIA-X}}},
doi = {{10.51202/9783186204165-i}},
year = {{2025}},
}
@article{64256,
author = {{Rasor, Anja and Koldewey, Christian and Dumitrescu, Roman}},
issn = {{2662-7493}},
journal = {{Nachhaltige Industrie}},
number = {{2}},
pages = {{40--43}},
publisher = {{Springer Science and Business Media LLC}},
title = {{{Mit digitalen Hebeln zur Kreislaufwirtschaft}}},
doi = {{10.1007/s43462-025-1406-x}},
volume = {{6}},
year = {{2025}},
}
@proceedings{64257,
editor = {{Dumitrescu, Roman and Hölzle, Katharina}},
publisher = {{Verlagsschriftenreihe des Heinz Nixdorf Instituts}},
title = {{{Vorausschau und Technologieplanung - 19. Symposium für Vorausschau und Technologieplanung}}},
doi = {{10.17619/UNIPB/1-2467}},
year = {{2025}},
}
@inproceedings{59910,
abstract = {{The connection between inconsistent databases and Dung’s abstract argumentation framework has recently drawn growing interest. Specifically, an inconsistent database, involving certain types of integrity constraints such as functional and inclusion dependencies, can be viewed as an argumentation framework in Dung’s setting. Nevertheless, no prior work has explored the exact expressive power of Dung’s theory of argumentation when compared to inconsistent databases and integrity constraints. In this paper, we close this gap by arguing that an argumentation framework can also be viewed as an inconsistent database. We first establish a connection between subset-repairs for databases and extensions for AFs considering conflict-free, naive, admissible, and preferred semantics. Further, we define a new family of attribute-based repairs based on the principle of maximal content preservation. The effectiveness of these repairs is then highlighted by connecting them to stable, semi-stable, and stage semantics. Our main contributions include translating an argumentation framework into a database together with integrity constraints. Moreover, this translation can be achieved in polynomial time, which is essential in transferring complexity results between the two formalisms.}},
author = {{Mahmood, Yasir and Hecher, Markus and Ngonga Ngomo, Axel-Cyrille}},
booktitle = {{Proceedings of the AAAI Conference on Artificial Intelligence}},
issn = {{2374-3468}},
number = {{14}},
pages = {{15058--15066}},
publisher = {{Association for the Advancement of Artificial Intelligence (AAAI)}},
title = {{{Dung’s Argumentation Framework: Unveiling the Expressive Power with Inconsistent Databases}}},
doi = {{10.1609/aaai.v39i14.33651}},
volume = {{39}},
year = {{2025}},
}
@inproceedings{61918,
author = {{Rook, Jeroen and Renau, Quentin and Trautmann, Heike and Hart, Emma}},
booktitle = {{Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2025, Leiden, The Netherlands, August 27-29, 2025}},
pages = {{262–272}},
publisher = {{ACM}},
title = {{{Efficient Online Automated Algorithm Selection in the Face of Data-Drift in Optimisation Problem Instances}}},
doi = {{10.1145/3729878.3746615}},
year = {{2025}},
}
@inproceedings{61202,
abstract = {{The number of datasets on the web of data increases continuously. However, the knowledge contained therein cannot be fully utilized without finding links between the entities contained in these datasets. Equivalent entities can not be identified solely by checking the equivalence of IRIs because of the different origins and naming schemes of different data providers. Yet, such equivalences can be discovered by computing the similarity of their attributes. In this paper we propose GLIDE, an approach that links entities from two different datasets by embedding a joint model of these datasets enriched by additional relations describing the similarity of literals. The joint model is embedded into a latent vector space while paying attention to juxtaposing similar literals. We evaluate our approach against state-of-the-art algorithms using real-world datasets commonly used in link discovery literature. The results show that GLIDE outperforms all baselines on 5 of 7 datasets with perfect or near-perfect accuracy. Our approach achieves its best performance on datasets that feature several literals with similarities. Our experiments indicate that researchers should not only pay attention to equal literals in knowledge graph embedding but should also be aware of the distance between similar literals.}},
author = {{Becker, Alexander and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed }},
booktitle = {{The Semantic Web – ISWC 2025}},
keywords = {{becker sherif enexa sailproject dice simba ngonga whale}},
title = {{{GLIDE: Knowledge Graph Linking using Distance-Aware Embeddings}}},
year = {{2025}},
}
@article{61134,
author = {{Manzoor, Ali and Speck, René and Zahera, Hamada Mohamed Abdelsamee and Saleem, Muhammad and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}},
issn = {{2169-3536}},
journal = {{IEEE Access}},
pages = {{1--1}},
publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}},
title = {{{Multilingual Relation Extraction - A Survey}}},
doi = {{10.1109/access.2025.3604258}},
year = {{2025}},
}
@inbook{61222,
author = {{Lenke, Michael and Klowait, Nils and Biere, Lea and Schulte, Carsten}},
booktitle = {{Lecture Notes in Computer Science}},
isbn = {{9783032012210}},
issn = {{0302-9743}},
publisher = {{Springer Nature Switzerland}},
title = {{{Assessing AI Literacy: A Systematic Review of Questionnaires with Emphasis on Affective, Behavioral, Cognitive, and Ethical Aspects}}},
doi = {{10.1007/978-3-032-01222-7_8}},
year = {{2025}},
}
@article{61445,
abstract = {{ABSTRACT In recent years, there has been an increasing awareness of the importance of incorporating diversity into research projects, focusing on both how they are conducted and their content. Funding organizations have started to require that research applicants pay attention to inclusion and diversity by considering gender dimensions and other diversity factors in their project plans and ensuring gender equality during execution. Based on an extensive literature research and expert discussions on how to develop and implement diversity strategies in large collaborative research projects, we argue that there is a lack of practical advice in existing literature. Drawing from our own experiences in conceptualizing and implementing a Diversity Program across four universities in Germany, we propose a framework for effectively integrating diversity into collaborative research initiatives across various academic fields.}},
author = {{Lorke, Mariya and Amelung, Rena and Kuchling, Peter and Paaßen, Benjamin and Pein-Hackelbusch, Miriam and Schloots, Franziska Margarete and Schulz, Klara and Nauerth, Annette}},
journal = {{Diversity & Inclusion Research}},
keywords = {{collaborative research projects, diversity strategy, gender equality}},
number = {{4}},
pages = {{e70040}},
title = {{{Development and Implementation of Diversity Programs in Large Collaborative Research Projects: An Example From Germany}}},
doi = {{https://doi.org/10.1002/dvr2.70040}},
volume = {{2}},
year = {{2025}},
}
@inproceedings{60970,
author = {{Hebrok, Sven Niclas and Storm, Tim Leonhard and Cramer, Felix Matthias and Radoy, Maximilian Manfred and Somorovsky, Juraj}},
booktitle = {{34th USENIX Security Symposium}},
title = {{{STEK Sharing is Not Caring: Bypassing TLS Authentication in Web Servers using Session Tickets}}},
year = {{2025}},
}