Publikationen

2025

• GPU Virtualization and Remoting Service for AI Acceleration at the Edge

  Gaikwad, N., Lübben, R., & Kosta, S. (2025). GPU Virtualization and Remoting Service for AI Acceleration at the Edge. In Summer School on Cyber-Physical Systems and Internet-of-Things. (Original work published Juli 2025)

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  • Forschungsprojekt

    • KI-Anwendungszentrum (KIAZ)

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 4: Wirtschaft

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  • 2025
  • Conference Paper
  • • Nikhil Gaikwad
    • Ralf Lübben
    • Sokol Kosta

• An Experimental Wind Farm Emulator with a Dual Variable-Speed Drive Configuration

  Gruman, N., Moses, P., & Jauch, C. (2025). An Experimental Wind Farm Emulator with a Dual Variable-Speed Drive Configuration. In 2025 Intermountain Engineering, Technology and Computing (IETC) (S. 6). Orem, UT, USA: IEEE. http://doi.org/10.1109/IETC64455.2025.11039473 (Original work published Juni 2025)

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  The rise of wind power in bulk electric systems creates a growing need to model, understand, and characterize responses to various sources of disruption. Despite the numerous advantages of computer models, physical emulators have enormous benefits in characterizing dynamic magnetic electromechanical phenomena which are unexpected or difficult for models to process accurately. The development of an experimental apparatus for physical wind farm emulation is described. The control and operation of an induction motor-generator setup for mimicking wind generator dynamics are demonstrated. Recommendations for further application of this emulator are also given.

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  • Personenseiten

    • Jauch, Clemens

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Forschungsfeld

    • Wind
    • Netzintegration

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2025
  • Conference Paper
  • • Noah Gruman
    • Paul Moses
    • Prof. Dr. Clemens Jauch
  • • Emulator
    • grid connection
    • induction machine
    • inverter, renewables
    • wind energy

• State estimation using LSTMs trained on synthetic data and validated with real measurements

  Geisler, J. (2025). State estimation using LSTMs trained on synthetic data and validated with real measurements. Namtes: WESC 2025. http://doi.org/10.5281/zenodo.15830516 (Original work published Juni 2025)

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  This study represents a novel contribution by demonstrating that LSTM-based estimators can replace traditional state estimation pipelines in wind turbine applications. By eliminating the need for detailed modeling and manual tuning, this approach opens up new opportunities for data-driven estimation in renewable energy systems.

  Unlike conventional estimators based on linear or nonlinear physical models, the proposed method trains LSTM networks to learn the mapping from inputs and outputs to internal state estimates using only simulation data. Such data can be generated in large volumes with complete access to all internal states, leveraging high-fidelity turbine simulation tools. The trained LSTM functions as a complete estimator, replacing both the predictor and corrector stages typically found in Kalman filter structures.

  The approach is evaluated across a variety of estimation tasks, from rotor effective wind speed (REWS) to more complex quantities such as blade deflections and wind shear coefficients. Results demonstrate that LSTMs trained entirely on simulation data can generalize well to real-world measurements, achieving estimation quality comparable to that of EKFs. Moreover, the method proves flexible and scalable to different input-output combinations without extensive manual modeling.

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    • Geisler, Jens

  • Forschungsprojekt

    • Adaptive Betriebsstrategien für bestehende Windenergieanlagen

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Forschungsfeld

    • Wind

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2025
  • Miscellaneous
  • • Jens Geisler
  • • state estimation
    • observer
    • kalman filter
    • neural network
    • LSTM
    • high fidelity model
    • real measurements

• Minimum CO2 Saving Requirement for the Hydraulic-Pneumatic Flywheel System in the Rotor of a Wind Turbine

  Goga, A., Jauch, C., Alhrshy, L., Gagel, A., & Kloft, P. (2025). Minimum CO2 Saving Requirement for the Hydraulic-Pneumatic Flywheel System in the Rotor of a Wind Turbine. In NEIS Conference 2024 (S. 184–191). Hamburg: VDE Verlag GmbH. http://doi.org/10.30420/566464025 (Original work published März 2025)

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  Researchers in the wind sector continuously aim to lower mechanical and structural loads on wind turbines to reduce the amount of material used in their components. One such innovative concept that is being investigated here is the integration of a flywheel system into rotor blades. In contrast to its intended aim of reducing the material usage and thereby CO2 emissions, the flywheel system in its implementation requires additional materials, which increases the carbon footprint considerably. Hence, to achieve a net CO2 saving, the CO2 expenditure of the additional components needs to be saved by the system as a minimum. The purpose of this work is to quantify the rise in CO2 emissions, caused by the installation of the flywheel system, relative to the original design. Thereby, the flywheel system’s minimal performance requirement for an exemplary wind turbine is defined.

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    • Goga, Abhinay
    • Jauch, Clemens
    • Alhrshy, Laurence

  • Forschungsprojekt

    • Ressourceneffizienz in der Windenergie

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Forschungsfeld

    • Wind

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2025
  • Conference Paper
  • • Abhinay Goga
    • Prof. Dr. Clemens Jauch
    • Laurence Alhrshy
    • Andreas Gagel
    • Peter Kloft
  • • Wind Turbine
    • Variable inertia flywheel
    • Increase In CO2 Emissions
    • Construction Materials

• On the road to interactive LLM-based systematic mapping studies

  Petersen, K., & Gerken, J. M. (2025). On the road to interactive LLM-based systematic mapping studies. Information and Software Technology, 178. (Original work published Februar 2025)

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    • Petersen, Kai
    • Gerken, Jan Michael

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Fachbereich

    • Fachbereich 4: Wirtschaft

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  • 2025
  • Journal Article
  • • Kai Petersen
    • Jan Gerken
  • • Large language models
    • Systematic mapping studies
    • GPT

• Joint Frequency Stabilisation in Future 100% Renewable Electric Power Systems

  Reese, L., Rettig, A., Jauch, C., Domin, R. J., & Karshüning, T. (2025). Joint Frequency Stabilisation in Future 100% Renewable Electric Power Systems. Energies, 18, 17. http://doi.org/10.3390/en18020418 (Original work published Januar 2025)

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  Due to the energy transition, the future electric power system will face further challenges that affect the functionality of the electricity grid and therefore the security of supply. For this reason, this article examines the future frequency stabilisation in a 100% renewable electric power system. A focus is set on the provision of inertia and frequency containment reserve. Today, the frequency stabilisation in most power systems is based on synchronous generators. By using grid-forming frequency converters, a large potential of alternative frequency stabilisation reserves can be tapped. Consequently, frequency stabilisation is not a problem of existing capacities but whether and how these are utilised. Therefore, in this paper, a collaborative approach to realise frequency stabilisation is proposed. By distributing the required inertia and frequency containment reserve across all technologies that are able to provide it, the relative contribution of each individual provider is low. To cover the need for frequency containment reserve, each capable technology would have to provide less than 1% of its rated power. The inertia demand can be covered by the available capacities at a coverage ratio of 171% (excluding wind power) to 217% (all capacities). As a result, it is proposed that provision of frequency stabilisation is made mandatory for all capable technologies. The joint provision distributes the burden of frequency stabilisation across many participants and hence increases redundancy. It ensures the stability of future electricity grids, and at the same time, it reduces the technological and economic effort. The findings are presented for the example of the German electricity grid.

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  • Personenseiten

    • Jauch, Clemens

  • Forschungsprojekt

    • Inno!Nord: Innovationslabor: Speicher zur Nutzung erneuerbarer Energien im echten Norden

  • Abteilung/Einrichtung

    • Wind Energy Technology Institute

  • Profilbereich

    • Erneuerbare Energien und nachhaltige Entwicklung

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2025
  • Journal Article
  • • Lisanne Reese
    • Arne Rettig
    • Prof. Dr. Clemens Jauch
    • Richard Domin
    • Tom Karshüning
  • • electric power system
    • energy transition
    • frequency containment reserve
    • frequency stabilisation
    • inertia
    • renewable energy
    • synchronous stability

• Relatedness Technologies: An Online Compendium and Systematic Review

  Wenhart, C., Ringfort-Felner, R., Wallbaum, T., Amidi, M., Albers, R., & Hassenzahl, M. (2025). Relatedness Technologies: An Online Compendium and Systematic Review. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery. http://doi.org/10.1145/3706598.3714260

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  Over the past decades, numerous concepts and prototypes for fostering emotional connections across distance (relatedness technologies) have been proposed. This has made it challenging for researchers and designers in Human-Computer Interaction (HCI) to maintain a comprehensive overview and effectively build on previous work. To address this, we conducted a systematic literature search (PRISMA) and collected 241 concepts and prototypes (2010-2024). We organized this corpus according to key aspects: (1) target population, (2) theoretical grounding, (3) design, (4) evaluation, and (5) ethics. Based on this, we developed the “COmpendium of RElatedness Technologies” (CORE), an open-access, searchable online database that provides researchers and practitioners with a reliable repository to inform future work. In addition, we present a systematic review of the corpus, revealing that despite its long tradition work on relatedness technologies remains characterized by limited theoretical grounding, lack of robust empirical evidence of effects, and insufficient attention to ethical considerations.

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    • Wallbaum, Torben
    • Amidi, Maryam

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  • 2025
  • Conference Paper
  • • Christiane Wenhart
    • Ronda Ringfort-Felner
    • Torben Wallbaum
    • Maryam Amidi
    • Ruben Albers
    • Marc Hassenzahl
  • • Connectedness
    • Database
    • Experience Design
    • Relatedness
    • Relatedness Technology
    • Systematic Review

• Reduction of torque ripple in electric drives with concentrated windings through unconventional stator slot numbers

  Königs, M., & Löhlein, B. (2025). Reduction of torque ripple in electric drives with concentrated windings through unconventional stator slot numbers. e+i Elektrotechnik und Informationstechnik.

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  • 2025
  • Journal Article
  • • Mike Königs
    • Bernd Löhlein

• Effortless Vision-Language Model Specialization in Histopathology without Annotation

  Qiu, J., Jain, N., Ammeling, J., Aubreville, M., & Breininger, K. (2025). Effortless Vision-Language Model Specialization in Histopathology without Annotation. In MICCAI Workshop on Computational Pathology with Multimodal Data (COMPAYL). Abgerufen von https://openreview.net/forum?id=pQDzXVeBja

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  • Personenseiten

    • Aubreville, Marc

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Profilbereich

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2025
  • Conference Paper
  • • Jingna Qiu
    • Nishanth Jain
    • Jonas Ammeling
    • Marc Aubreville
    • Katharina Breininger

• Histologic Dataset of Normal and Atypical Mitotic Figures on Human Breast Cancer (AMi-Br)

  Bertram, C. A. ", Weiss, V., Donovan, T. A., Banerjee, S., Conrad, T., Ammeling, J., … Aubreville, M. (2025). Histologic Dataset of Normal and Atypical Mitotic Figures on Human Breast Cancer (AMi-Br). In "Bildverarbeitung für die Medizin 2025" (S. 113–118). "Wiesbaden": "Springer Fachmedien Wiesbaden".

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  "Assessment of the density of mitotic figures (MFs) in histologic tumor sections is an important prognostic marker for many tumor types, including breast cancer. Recently, it has been reported in multiple works that the quantity of MFs with an atypical morphology (atypical MFs, AMFs) might be an independent prognostic criterion for breast cancer. AMFs are an indicator of mutations in the genes regulating the cell cycle and can lead to aberrant chromosome constitution (aneuploidy) of the tumor cells. To facilitate further research on this topic using pattern recognition, we present the first ever publicly available dataset of atypical and normal MFs (AMi-Br). For this, we utilized two of the most popular MF datasets (MIDOG 2021 and TUPAC) and subclassified all MFs using a three expert majority vote. Our final dataset consists of 3,720 MFs, split into 832 AMFs (22.4\%) and 2,888 normal MFs (77.6\%) across all 223 tumor cases in the combined set. We provide baseline classification experiments to investigate the consistency of the dataset, using a Monte Carlo cross-validation and different strategies to combat class imbalance.We found an averaged balanced accuracy of up to 0.806 when using a patch-level data set split, and up to 0.713 when using a patient-level split."

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  • Personenseiten

    • Banerjee, Sweta
    • Aubreville, Marc

  • Forschungsprojekt

    • Robust and Accurate Multi-Tumor, Multi-Species, Multi-Laboratory and Multi-Scanner Mitosis Detection with Large-Scale Datasets and Artificial Intelligence

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research
    • CIVU – Center for Interaction, Visualization and Usability

  • Profilbereich

    • Gesundheit und Life Sciences

  • Forschungsfeld

    • Digitale Transformation
    • Human-Computer-Interaction
    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2025
  • Conference Paper
  • • Christof Bertram
    • Viktoria Weiss
    • Taryn Donovan
    • Sweta Banerjee
    • Thomas Conrad
    • Jonas Ammeling
    • Robert Klopfleisch
    • Christopher Kaltenecker
    • Marc Aubreville