Publikationen

2024

• Dominance hierarchy does not influence distances travelled and area utilization in a large group of ponies

  Weidling, G., Krieter, J., Lübben, R., & Czycholl, I. (2024). Dominance hierarchy does not influence distances travelled and area utilization in a large group of ponies. Applied Animal Behaviour Science, 271. http://doi.org/https://doi.org/10.1016/j.applanim.2024.106178 (Original work published Februar 2024)

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  In order to improve existing horse husbandry practices by providing social contact and exercise opportunities, it is necessary to fully understand the behaviour of horses in relation to group housing. Therefore, this study investigated the influence of dominance hierarchy on the locomotor behaviour and area utilization in a large group of horses in a pasture-based housing system in Northern Germany. The movements of 40 ponies with established group affiliations were observed over approximately one month from late August to early October 2022 using GPS technology. Their dominance hierarchy was determined by testing each possible combination in separate pair-feeding tests. For the determination of area utilization, the available space was divided into a total of 8889 quadrants with 3x3 m each. Analysis of daily distances travelled by the horses revealed an average of 5.4 ± 1.2 km/day, with no significant effect of social rank. However, age had a significant effect, with older horses walking shorter distances. Quadrants used per hour, as measure of area utilization, averaged 37.9 ± 6.4, with no effect of social rank but a significant effect of age observed. Heat maps showed full pasture utilization, with lower ranked horses having less access to resources around the watering trough and a greater use of less attractive grazing areas. The study suggests that in this specific setting, social rank did not significantly affect locomotor behaviour or area use. Although the study did not find a correlation between dominance rank and locomotor behaviour or area use, it highlighted the need for further research in different group sizes and housing systems to optimise group housing practices for horses, especially in settings with limited space and resources.

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    • Lübben, Ralf

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 4: Wirtschaft

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  • 2024
  • Journal Article
  • • Gesa Weidling
    • Joachim Krieter
    • Ralf Lübben
    • Irena Czycholl
  • • Horse
    • Dominance hierarchy
    • GPS
    • Distance
    • Area utilization
    • Group housing

• Hydraulic variable inertia flywheel

  Jauch, C., Jost, R., & Kloft, P. (2024). Hydraulic variable inertia flywheel. Applied Energy, 360, 16. http://doi.org/https://doi.org/10.1016/j.apenergy.2024.122830 (Original work published Februar 2024)

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  A novel variable inertia flywheel that uses the mass of a rotating hydraulic fluid is proposed in this paper. In contrast to variable inertia flywheels that use solid masses, this flywheel stands out for its simplicity. In contrast to many other common energy storages, it does not require any environmentally harmful, rare or expensive materials. The basic working principle and the equations that cover the hydraulic behaviour, the pneumatic behaviour and the energy from angular momentum are introduced. These equations are applied to the geometry of the proposed flywheel concept, which allows quantifying the pressures that act on the different mechanical flywheel components. These pressures, together with the centrifugal acceleration from rotation, lead to the loads that have to be withstood by the mechanical components. A simple method for quantifying these loads, and for dimensioning the mechanical components, allows deriving the stationary masses and inertias. A parameter study is conducted, in which different parameters of the flywheel are varied in order to find the maxima in energy density and specific energy. The results of this parameter study reveal that the proposed hydraulic variable inertia flywheel is a very simple and safe energy storage that could provide AC power systems with inertia and control power to support their frequency.

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    • 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

  • Forschungsfeld

    • Innovation und Wachstum, Nachhaltigkeit
    • Wind
    • Netzintegration

  • Fachbereich

    • Fachbereich 2: Energy and Life Science

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  • 2024
  • Journal Article
  • • Prof. Dr. Clemens Jauch
    • Rebecca Jost
    • Peter Kloft
  • • Energy storage
    • Fluid
    • Flywheel
    • Kinetic energy
    • Variable moment of inertia
    • Variable inertia flywheel

• Breast cancer survival prediction using an automated mitosis detection pipeline

  Stathonikos, N., Aubreville, M., de Vries, S., Wilm, F., Bertram, C. A., Veta, M., & van Diest, P. J. (2024). Breast cancer survival prediction using an automated mitosis detection pipeline. The Journal of Pathology: Clinical Research, 10, e70008. http://doi.org/https://doi.org/10.1002/2056-4538.70008

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  Abstract Mitotic count (MC) is the most common measure to assess tumor proliferation in breast cancer patients and is highly predictive of patient outcomes. It is, however, subject to inter- and intraobserver variation and reproducibility challenges that may hamper its clinical utility. In past studies, artificial intelligence (AI)-supported MC has been shown to correlate well with traditional MC on glass slides. Considering the potential of AI to improve reproducibility of MC between pathologists, we undertook the next validation step by evaluating the prognostic value of a fully automatic method to detect and count mitoses on whole slide images using a deep learning model. The model was developed in the context of the Mitosis Domain Generalization Challenge 2021 (MIDOG21) grand challenge and was expanded by a novel automatic area selector method to find the optimal mitotic hotspot and calculate the MC per 2 mm2. We employed this method on a breast cancer cohort with long-term follow-up from the University Medical Centre Utrecht (N = 912) and compared predictive values for overall survival of AI-based MC and light-microscopic MC, previously assessed during routine diagnostics. The MIDOG21 model was prognostically comparable to the original MC from the pathology report in uni- and multivariate survival analysis. In conclusion, a fully automated MC AI algorithm was validated in a large cohort of breast cancer with regard to retained prognostic value compared with traditional light-microscopic MC.

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    • 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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  • 2024
  • Journal Article
  • • Nikolas Stathonikos
    • Marc Aubreville
    • Sjoerd de Vries
    • Frauke Wilm
    • Christof Bertram
    • Mitko Veta
    • Paul van Diest
  • • artificial intelligence
    • machine learning
    • histopathology
    • prognosis
    • mitosis
    • outcome
    • deep learning

• TorqTwin—An open-source reference multibody modeling framework for wind turbine structural dynamics

  Guo, F., Gao, Z., & Schlipf, D. (2024). TorqTwin—An open-source reference multibody modeling framework for wind turbine structural dynamics. Renewable Energy, 235, 121268. http://doi.org/10.1016/j.renene.2024.121268

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    • Schlipf, David

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  • 2024
  • Journal Article
  • • Feng Guo
    • Zhen Gao
    • David Schlipf

• Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis

  Ganz, J., Marzahl, C., Ammeling, J., Rosbach, E., Richter, B., Puget, C., … Aubreville, M. (2024). Information mismatch in PHH3-assisted mitosis annotation leads to interpretation shifts in H&E slide analysis. Scientific Reports, 14, 26273. http://doi.org/10.1038/s41598-024-77244-6

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  Abstract The count of mitotic figures (MFs) observed in hematoxylin and eosin (H&E)-stained slides is an important prognostic marker, as it is a measure for tumor cell proliferation. However, the identification of MFs has a known low inter-rater agreement. In a computer-aided setting, deep learning algorithms can help to mitigate this, but they require large amounts of annotated data for training and validation. Furthermore, label noise introduced during the annotation process may impede the algorithms’ performance. Unlike H&E, where identification of MFs is based mainly on morphological features, the mitosis-specific antibody phospho-histone H3 (PHH3) specifically highlights MFs. Counting MFs on slides stained against PHH3 leads to higher agreement among raters and has therefore recently been used as a ground truth for the annotation of MFs in H&E. However, as PHH3 facilitates the recognition of cells indistinguishable from H&E staining alone, the use of this ground truth could potentially introduce an interpretation shift and even label noise into the H&E-related dataset, impacting model performance. This study analyzes the impact of PHH3-assisted MF annotation on inter-rater reliability and object level agreement through an extensive multi-rater experiment. Subsequently, MF detectors, including a novel dual-stain detector, were evaluated on the resulting datasets to investigate the influence of PHH3-assisted labeling on the models’ performance. We found that the annotators’ object-level agreement significantly increased when using PHH3-assisted labeling (F1: 0.53 to 0.74). However, this enhancement in label consistency did not translate to improved performance for H&E-based detectors, neither during the training phase nor the evaluation phase. Conversely, the dual-stain detector was able to benefit from the higher consistency. This reveals an information mismatch between the H&E and PHH3-stained images as the cause of this effect, which renders PHH3-assisted annotations not well-aligned for use with H&E-based detectors. Based on our findings, we propose an improved PHH3-assisted labeling procedure.

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    • 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

    • Informatik und Gestaltung

  • Forschungsfeld

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

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Jonathan Ganz
    • Christian Marzahl
    • Jonas Ammeling
    • Emely Rosbach
    • Barbara Richter
    • Chloé Puget
    • Daniela Denk
    • Elena Demeter
    • Flaviu Tăbăran
    • Gabriel Wasinger
    • Karoline Lipnik
    • Marco Tecilla
    • Matthew Valentine
    • Michael Dark
    • Niklas Abele
    • Pompei Bolfa
    • Ramona Erber
    • Robert Klopfleisch
    • Sophie Merz
    • Taryn Donovan
    • Samir Jabari
    • Christof Bertram
    • Katharina Breininger
    • Marc Aubreville

• Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry

  Haghofer, A., Parlak, E., Bartel, A., Donovan, T., Assenmacher, C.-A., Bolfa, P., … Bertram, C. (2024). Nuclear pleomorphism in canine cutaneous mast cell tumors: Comparison of reproducibility and prognostic relevance between estimates, manual morphometry, and algorithmic morphometry. Veterinary Pathology, 03009858241295399. http://doi.org/10.1177/03009858241295399

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  Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics can improve reproducibility, but current manual methods are time-consuming. The aim of this study was to explore the limitations of estimates and develop alternative morphometric solutions for canine cutaneous mast cell tumors (ccMCTs). We assessed the following nuclear evaluation methods for accuracy, reproducibility, and prognostic utility: (1) anisokaryosis estimates by 11 pathologists; (2) gold standard manual morphometry of at least 100 nuclei; (3) practicable manual morphometry with stratified sampling of 12 nuclei by 9 pathologists; and (4) automated morphometry using deep learning–based segmentation. The study included 96 ccMCTs with available outcome information. Inter-rater reproducibility of anisokaryosis estimates was low (k = 0.226), whereas it was good (intraclass correlation = 0.654) for practicable morphometry of the standard deviation (SD) of nuclear size. As compared with gold standard manual morphometry (area under the ROC curve [AUC] = 0.839, 95% confidence interval [CI] = 0.701–0.977), the prognostic value (tumor-specific survival) of SDs of nuclear area for practicable manual morphometry and automated morphometry were high with an AUC of 0.868 (95% CI = 0.737–0.991) and 0.943 (95% CI = 0.889–0.996), respectively. This study supports the use of manual morphometry with stratified sampling of 12 nuclei and algorithmic morphometry to overcome the poor reproducibility of estimates. Further studies are needed to validate our findings, determine inter-algorithmic reproducibility and algorithmic robustness, and explore tumor heterogeneity of nuclear features in entire tumor sections.

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    • 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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  • 2024
  • Journal Article
  • • Andreas Haghofer
    • Eda Parlak
    • Alexander Bartel
    • Taryn Donovan
    • Charles-Antoine Assenmacher
    • Pompei Bolfa
    • Michael Dark
    • Andrea Fuchs-Baumgartinger
    • Andrea Klang
    • Kathrin Jäger
    • Robert Klopfleisch
    • Sophie Merz
    • Barbara Richter
    • Yvonne Schulman
    • Hannah Janout
    • Jonathan Ganz
    • Josef Scharinger
    • Marc Aubreville
    • Stephan Winkler
    • Matti Kiupel
    • Christof Bertram

• A federated learning approach to QoS forecasting in cellular vehicular communications: Approaches and empirical evidence

  Baganal-Krishna, N., Lübben, R., Liotou, E., Katsaros, K. V., & Rizk, A. (2024). A federated learning approach to QoS forecasting in cellular vehicular communications: Approaches and empirical evidence. Computer Networks, 242, 110239. http://doi.org/https://doi.org/10.1016/j.comnet.2024.110239

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  QoS forecasting for cellular vehicular communications allows cooperative, connected and automated mobility applications to tailor their behavior to the expected communication conditions on the road. In a nutshell, vehicles may, for example, execute cooperative maneuvers if the communication quality of service is only above a certain quantitative level whereas if not they revert to the individual autonomous mode. In this paper, we propose and show empirical methods for estimating packet-based QoS metrics obtained from 5G network measurements with a direct application to vehicular applications. As many distributed vehicular applications possess strict QoS requirements, we focus here on bounding packet-based statistical QoS quantiles, specifically for latency and loss. Our approach is based on training regression neural networks in a federated learning fashion and show that it can obtain predictions on par with centralized training without the vehicles needing to transmit raw measurement data. In contrast to QoS prediction using physical layer information, we briefly discuss the embedding of such much simpler application-level service within the 5G architecture. We also validate our approach through recovering classical closed-form delay quantiles that are obtained from analytical models of simple queueing systems. We show that our approach goes beyond these simple models in that it provides quantile estimates for the complex scenario of cellular vehicle communications and under different application traffic patterns including empirical data traffic traces as well as 5G testbed measurements.

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    • Lübben, Ralf

  • Abteilung/Einrichtung

    • FLAIR - Flensburg Artificial Intelligence Research

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 4: Wirtschaft

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  • 2024
  • Journal Article
  • • Nehal Baganal-Krishna
    • Ralf Lübben
    • Eirini Liotou
    • Konstantinos Katsaros
    • Amr Rizk
  • • Predictive QoS
    • Vehicular communications
    • Federated learning
    • 5G measurements

• An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine

  Ammeling, J., Aubreville, M., Fritz, A., Kießig, A., Krügel, S., & Uhl, M. (2024). An Interdisciplinary Perspective on AI-Supported Decision Making in Medicine. Technology in Society, 102791.

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    • 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

    • Informatik und Gestaltung

  • Forschungsfeld

    • Data Science und Künstliche Intelligenz

  • Fachbereich

    • Fachbereich 3: Information und Kommunikation

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  • 2024
  • Journal Article
  • • Jonas Ammeling
    • Marc Aubreville
    • Alexis Fritz
    • Angelika Kießig
    • Sebastian Krügel
    • Matthias Uhl

• Investigation of asymmetric SVM switching patterns with minor flux loops in inverter fed induction motors

  Königs, M., & Löhlein, B. (2024). Investigation of asymmetric SVM switching patterns with minor flux loops in inverter fed induction motors. Research gate, open access. http://doi.org/http://dx.doi.org/10.13140/RG.2.2.21923.26407

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  • 2024
  • Journal Article
  • • Mike Königs
    • Bernd Löhlein

• Why state-of-the-art analytical models for eddy current losses in PM of PMSM are insufficient for variable speed motors

  Königs, M., & Löhlein, B. (2024). Why state-of-the-art analytical models for eddy current losses in PM of PMSM are insufficient for variable speed motors. e+i Elektrotechnik und Informationstechnik, 141. http://doi.org/10.1007/s00502-024-01207-y

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  • 2024
  • Journal Article
  • • Mike Königs
    • Bernd Löhlein