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Jami J. Shah, Satchit Ramnath, Stefan Menzel, Thiago de Jesus de Araujo Rios, Fatma Kocer, Eamon Whalen, Joseph Pajot, Alex Adrian, Prakash Kumar , "Principles and Metrics for Curating Large Engineering Simulation Data Sets for ML", ASME Journal of Computing and Information Science in Engineering (JCISE), 2025.
AbstractIt is time to talk about data in its own right, not just its usage! Machine Learning applications are using a wide variety of data sources, some real, such as data collected by sensors and cameras in driving, and some artificial, such as data generated through numerical simulations. The latter mode has been gaining rapid popularity for engineering design and analysis. Early work in this arena seemed to center on the data being generated by develo...
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Archit Naik , "Leveraging 2D part segmentation for improved 6D object pose estimation", Technical Faculty at FAU Erlangen-Nürnberg, 2025.
AbstractEstimating the 6D pose of known objects from RGB-D data works well when the registration is properly initialized, but classical ICP often fails under large misalignments, object symmetries, or cluttered scenes. This thesis introduces SegmentICP, a training-free, CAD-based approach that leverages part information from 2D vision to make 3D registration more robust. SegmentICP uses a two- stage pipeline: (i) a part-aware initializer that aligns...
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Christian Internó, Andrea Castellani, Sebastian Schmitt, Barbara Hammer , "Industrial Energy Disaggregation with Digital Twin-generated Dataset and Efficient Data Augmentation", Arxiv Preprint, 2025.
AbstractIndustrial Non-Intrusive Load Monitoring (NILM) is limited by the scarcity of high-quality datasets and the complex variability of industrial energy consumption patterns. To address data scarcity and privacy issues, we introduce the Synthetic Industrial Dataset for Energy Disaggregation (SIDED), an opensource dataset generated using Digital Twin simulations. SIDED includes three types of industrial facilities across three different geographic loc...
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Melvin Wong, Jiao Liu, Thiago de Jesus de Araujo Rios, Stefan Menzel, Yew Soon Ong , "LLM2TEA: An Agentic AI Designer for Discovery with Generative Evolutionary Multitasking", IEEE Computational Intelligence Magazine, 2025.
AbstractThis paper presents LLM2TEA, a Large Language Model (LLM) driven MultiTask Evolutionary Algorithm, representing the first agentic AI designer of its kind operating with generative evolutionary multitasking (GEM). LLM2TEA enables the crossbreeding of solutions from multiple domains, fostering novel solutions that transcend disciplinary boundaries. Of particular interest is the ability to discover designs that are both novel for and conforming to r...
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David Rother, Joni Pajarinen, Jan Peters, Thomas H Weisswange , "Open-Ended Coordination for Multi-Agent Systems Using Modular Open Policies", Autonomous Agents and Multi-Agent Systems, vol. 39, 2025.
AbstractSignificant advances addressing the challenge of learning policies for acting in multi-agent systems have been made through approaches for ad hoc teamwork, a paradigm where a team of agents must cooperate effectively without prior coordination or communication. Many existing approaches, however, struggle to perform well in open environments where the setting can change significantly during deployment. This paper presents a new reinforcement lear...
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Atikkhan Faridkhan Nilgar, Kristof Van Laerhoven, Ayub Kinoti , "SRWToolkit: An Open Source Wizard of Oz Toolkit to Create Social Robotic Avatars", 17th International Conference on Social Robotics + AI (ICSR 2025), 2025.
AbstractWe present an open-source social robot Wizard of Oz toolkit designed to facilitate the development and evaluation of interactive social robotic avatars powered by local large language models. The web- based system supports multimodal interaction via text, button-activated speech, and wake-word commands and allows real-time customization of robot behavior, language, and voice through a control panel. Un- like prior toolkits dependent on cloud-ba...
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Petros Georgiadis, Martina Hasenjäger, Dimitris Voudouris, Christiane Wiebel , "On the temporal dynamics of head and eye movements for real-world walking behavior", Acta Psychologica, vol. 260, pp. 105680, 2025.
AbstractMost human actions are planned and performed based on visual information. Indeed, when interacting with the environment, humans typically direct their gaze to where relevant information for the task at hand can be found. While walking, humans shift their gaze by using both eye and head movements, and the relative contribution of the head is more pronounced when the navigated surface’s complexity increases. However, most work has examined average ...
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Sebastian Brulin, Tamon Toyooka, Lydia Fischer, Florian Kreuchauff, Tobias Rodemann , "Comparative Assessment of Swappable Battery Stations (SBEV) and Stationary Charging Stations (BEV) in Urban Electric Vehicle Networks: An Activity-Based Simulation Approach", EVTeC 2025, 2025.
AbstractThis paper investigates the comparative performance of swappable battery stations (SBEV) and stationary charging stations (BEV) in urban electric vehicle networks using large-scale activity-based MATSim simulations to assess user behavior across various scenarios. Focusing on user and operator perspectives, we investigate the hypotheses that SBEVs offer shorter charging times for users, while operators benefit from lower infrastructure costs eith...
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Linus Ekstrom, Takafumi Hosogi, Xavier Bonet-Monroig, Sebastian Schmitt, Hao Wang, Thomas Bäck , "Improving Quantum Multi-Objective Optimization with Archiving and Substitution", Machine Learning, Optimization, and Data Science, vol. 16467-16468, no. 16467 and 16468, issue Soft cover, 2025.
AbstractFinding optimal solutions of conflicting objectives is a daily matter in many industrial applications, with multi-objective optimization trying to find the best solutions to them. The advent of quantum computing has led to researchers wondering if the promised exponential advantage can be obtained for these problems by variational quantum multi-objective optimization (QMOO) algorithm. Here, we improve it by introducing a Pareto Archiving and do...
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Muhammad Ashfaq, Ahmed Sadik, Tommi Mikkonen, Niko Mäkitalo , "Runtime Composition in Dynamic System of Systems: A Systematic Review of Challenges, Solutions, Tools, and Evaluation Methods", arXiv, 2025.
AbstractContext: Modern Systems of Systems (SoSs) increasingly operate in dynamic environments (e.g., smart cities, autonomous vehicles) where runtime composition—the on-the-fly discovery, integration, and coordination of constituent systems (CSs)—is crucial for adaptability. Despite growing interest, the literature lacks a cohesive synthesis of runtime composition in dynamic SoSs. Objective: This study synthesizes research on runtime composition in d...
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