@inproceedings{62285,
abstract = {{The sliding square model is a widely used abstraction for studying self-reconfigurable robotic systems, where modules are square-shaped robots that move by sliding or rotating over one another. In this paper, we propose a novel distributed algorithm that enables a group of modules to reconfigure into a rhombus shape, starting from an arbitrary side-connected configuration. It is connectivity-preserving and operates under minimal assumptions: one leader module, common chirality, constant memory per module, and visibility and communication restricted to immediate neighbors. Unlike prior work, which relaxes the original sliding square move-set, our approach uses the unmodified move-set, addressing the additional challenge of handling locked configurations. Our algorithm is sequential in nature and operates with a worst-case time complexity of O(n^2) rounds, which is optimal for sequential algorithms. To improve runtime, we introduce two parallel variants of the algorithm. Both rely on a spanning tree data structure, allowing modules to make decisions based on local connectivity. Our experimental results show a significant speedup for the first variant, and a linear average runtime for the second variant, which is worst-case optimal for parallel algorithms.}},
author = {{Kostitsyna, Irina and Liedtke, David Jan and Scheideler, Christian}},
booktitle = {{Stabilization, Safety, and Security of Distributed Systems}},
editor = {{Bonomi, Silvia and Mandal, Partha Sarathi and Robinson, Peter and Sharma, Gokarna and Tixeuil, Sebastien}},
isbn = {{9783032111265}},
issn = {{0302-9743}},
location = {{Kathmandu}},
pages = {{325--342}},
publisher = {{Springer Nature Switzerland}},
title = {{{Invited Paper: Distributed Rhombus Formation of Sliding Squares}}},
doi = {{10.1007/978-3-032-11127-2_26}},
year = {{2025}},
}
@article{64098,
author = {{Scheideler, Christian and Padalkin, Andreas and Kumar, Manish}},
journal = {{Reconfiguration and locomotion with joint movements in the amoebot model. Auton. Robots 49(3): 22 (2025)}},
title = {{{Reconfiguration and locomotion with joint movements in the amoebot model. Auton. Robots 49(3): 22 (2025)}}},
year = {{2025}},
}
@inproceedings{64094,
author = {{Scheideler, Christian and Artmann, Matthias and Maurer, Tobias and Padalkin, Andreas and Warner, Daniel}},
title = {{{AmoebotSim 2.0: A Visual Simulation Environment for the Amoebot Model with Reconfigurable Circuits and Joint Movements (Media Exposition). }}},
year = {{2025}},
}
@book{64099,
editor = {{Scheideler, Christian and Meeks, Kitty}},
title = {{{4th Symposium on Algorithmic Foundations of Dynamic Networks.}}},
year = {{2025}},
}
@inproceedings{64097,
author = {{Scheideler, Christian and Artmann, Matthias and Padalkin, Andreas}},
title = {{{On the Shape Containment Problem Within the Amoebot Model with Reconfigurable Circuits. }}},
year = {{2025}},
}
@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{64145,
author = {{Newberry, Melissa and Jonas-Ahrend, Gabriela and Rizvi, Meher and van der Want, Anna}},
location = {{Glasgow}},
title = {{{The Dynamics of Geographic Space when working with International Teacher Educators in Collaborative Research}}},
year = {{2025}},
}
@inproceedings{64143,
author = {{Guberman, Ainat and Jonas-Ahrend, Gabriela and Arvif-Elyashiv, Rinat and Ben-Yehduah, Gal and Cyprus, Dominik}},
location = {{Belgrad}},
title = {{{Career Changing STEM Teachers` Motivation over Time: Lessons from Israel and Germany}}},
year = {{2025}},
}
@inproceedings{64142,
author = {{Ratnam, Tara and Jonas-Ahrend, Gabriela and Newberry, Melissa}},
location = {{Denver/CO, USA}},
title = {{{The presence of an Invisible College in the knowledge network of ISATT}}},
year = {{2025}},
}
@inbook{62188,
author = {{Vernholz, Mats and Jonas-Ahrend, Gabriela and Temmen, Katrin}},
booktitle = {{Zukünfte technischer Bildung}},
editor = {{Wiemer, Tobias and Binder, Martin and Penning, Isabelle}},
location = {{Halle/Saale}},
title = {{{„Und ich sag mal, Theorie und Praxis ist zweierlei“. Wie können Praxisphasen Lehramtsstudierende auf zukünftige Anforderungen vorbereiten? }}},
doi = {{https://doi.org/10.25932/publishup-67926}},
volume = {{26}},
year = {{2025}},
}
@article{55459,
author = {{Bullerjahn, Nils and Kovács, Balázs}},
journal = {{IMA Journal of Numerical Analysis}},
title = {{{Error estimates for full discretization of Cahn--Hilliard equation with dynamic boundary conditions}}},
doi = {{10.1093/imanum/draf009}},
year = {{2025}},
}
@article{53141,
author = {{Edelmann, Dominik and Kovács, Balázs and Lubich, Christian}},
journal = {{IMA Journal of Numerical Analysis}},
number = {{5}},
pages = {{2581----2627}},
title = {{{Numerical analysis of an evolving bulk--surface model of tumour growth}}},
doi = {{10.1093/imanum/drae077}},
volume = {{45}},
year = {{2025}},
}
@article{55781,
abstract = {{In this paper, we prove that spatially semi-discrete evolving finite element
method for parabolic equations on a given evolving hypersurface of arbitrary
dimensions preserves the maximal $L^p$-regularity at the discrete level. We
first establish the results on a stationary surface and then extend them, via a
perturbation argument, to the case where the underlying surface is evolving
under a prescribed velocity field. The proof combines techniques in evolving
finite element method, properties of Green's functions on (discretised) closed
surfaces, and local energy estimates for finite element methods}},
author = {{Bai, Genming and Kovács, Balázs and Li, Buyang}},
journal = {{IMA Journal of Numerical Analysis}},
title = {{{Maximal regularity of evolving FEMs for parabolic equations on an evolving surface}}},
doi = {{10.1093/imanum/draf082.}},
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}},
}