@article{DefosseKleinschmidtSchmutzetal.2022,
  author    = {Defosse, Jerome and Kleinschmidt, Joris and Schmutz, Axel and Loop, Torsten and Staat, Manfred and Gatzweiler, Karl-Heinz and Wappler, Frank and Schieren, Mark},
  title     = {Dental strain on maxillary incisors during tracheal intubation with double-lumen tubes and different laryngoscopy techniques - a blinded manikin study},
  series = {Journal of Cardiothoracic and Vascular Anesthesia},
  volume    = {36},
  journal   = {Journal of Cardiothoracic and Vascular Anesthesia},
  number    = {8, Part B},
  publisher = {Elsevier},
  address   = {New York, NY},
  issn      = {1053-0770},
  doi       = {10.1053/j.jvca.2022.02.017},
  pages     = {3021 -- 3027},
  year      = {2022},
  language  = {en}
}
@article{IkenBronderGoretzkietal.2019,
  author    = {Iken, Heiko and Bronder, Thomas and Goretzki, Alexander and Kriesel, Jana and Ahlborn, Kristina and Gerlach, Frank and Vonau, Winfried and Zander, Willi and Schubert, J{\"u}rgen and Sch{\"o}ning, Michael Josef},
  title     = {Development of a Combined pH- and Redox-Sensitive Bi-Electrode Glass Thin-Film Sensor},
  series = {physica status solidi a : applications and materials sciences},
  volume    = {216},
  journal   = {physica status solidi a : applications and materials sciences},
  number    = {12},
  publisher = {Wiley},
  address   = {Weinheim},
  issn      = {1862-6319},
  doi       = {10.1002/pssa.201900114},
  pages     = {1 -- 8},
  year      = {2019},
  language  = {en}
}
@inproceedings{PuetzBaierBrauneretal.2022,
  author    = {P{\"u}tz, Sebastian and Baier, Ralph and Brauner, Philipp and Brillowski, Florian and Dammers, Hannah and Liehner, Luca and Mertens, Alexander and Rodemann, Niklas and Schneider, Sebastian and Schollemann, Alexander and Steuer-Dankert, Linda and Vervier, Luisa and Gries, Thomas and Leicht-Scholten, Carmen and Nagel, Saskia K. and Piller, Frank T. and Schuh, G{\"u}nther and Ziefle, Martina and Nitsch, Verena},
  title     = {An interdisciplinary view on humane interfaces for digital shadows in the internet of production},
  series = {2022 15th International Conference on Human System Interaction (HSI)},
  booktitle = {2022 15th International Conference on Human System Interaction (HSI)},
  publisher = {IEEE},
  isbn      = {978-1-6654-6823-7 (Print)},
  issn      = {2158-2246 (Print)},
  doi       = {10.1109/HSI55341.2022.9869467},
  pages     = {8 Seiten},
  year      = {2022},
  abstract  = {Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers' capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization.},
  language  = {en}
}
@inproceedings{DyllaFerreinLakemeyer2003,
  author    = {Dylla, Frank and Ferrein, Alexander and Lakemeyer, Gerhard},
  title     = {AllemaniACs 2003 team description},
  series = {RoboCup 2003 : Robot Soccer World Cup VII},
  booktitle = {RoboCup 2003 : Robot Soccer World Cup VII},
  pages     = {1 -- 3},
  year      = {2003},
  language  = {en}
}
@inproceedings{MertensBraunerBaieretal.2022,
  author    = {Mertens, Alexander and Brauner, Philipp and Baier, Ralph and Brillowski, Florian and Dammers, Hannah and van Dyck, Marc and Kong, Iris and K{\"o}nigs, Peter and Kordtomeikel, Frauke and Liehner, Gian Luca and P{\"u}tz, Sebastian and Rodermann, Niklas and Schaar, Anne Kathrin and Steuer-Dankert, Linda and Vervier, Luisa and Wlecke, Shari and Gries, Thomas and Leicht-Scholten, Carmen and Nagel, Saskia K. and Piller, Frank T. and Schuh, G{\"u}nther and Ziefle, Martina and Nitsch, Verena},
  title     = {Modelling Human Factors in Cyber Physical Production Systems by the Integration of Human Digital Shadows},
  series = {Modellierung 2022 Satellite Events},
  booktitle = {Modellierung 2022 Satellite Events},
  editor    = {Michael, Judith and Pfeiffer, J{\´e}r{\^o}me and Wortmann, Andreas},
  publisher = {GI Gesellschaft f{\"u}r Informatik},
  address   = {Bonn},
  doi       = {10.18420/modellierung2022ws-018},
  pages     = {147 -- 149},
  year      = {2022},
  abstract  = {The future of industrial manufacturing and production will increasingly manifest in the form of cyber-physical production systems. Here, Digital Shadows will act as mediators between the physical and digital world to model and operationalize the interactions and relationships between different entities in production systems. Until now, the associated concepts have been primarily pursued and implemented from a technocentric perspective, in which human actors play a subordinate role, if they are considered at all. This paper outlines an anthropocentric approach that explicitly considers the characteristics, behavior, and traits and states of human actors in socio-technical production systems. For this purpose, we discuss the potentials and the expected challenges and threats of creating and using Human Digital Shadows in production.},
  language  = {en}
}
@article{SlabuRoethEngelmannetal.2019,
  author    = {Slabu, Ioana and Roeth, Anjali A. and Engelmann, Ulrich M. and Wiekhorst, Frank and Buhl, Eva M. and Neumann, Ulf P. and Schmitz-Rode, Thomas},
  title     = {Modeling of magnetoliposome uptake in human pancreatic tumor cells in vitro},
  series = {Nanotechnology},
  volume    = {30},
  journal   = {Nanotechnology},
  number    = {18},
  issn      = {1361-6528},
  doi       = {10.1088/1361-6528/ab033e},
  pages     = {184004},
  year      = {2019},
  language  = {en}
}
@article{EngelmannBuhlDraacketal.2018,
  author    = {Engelmann, Ulrich M. and Buhl, Eva Miriam and Draack, Sebastian and Viereck, Thilo and Frank, and Schmitz-Rode, Thomas and Slabu, Ioana},
  title     = {Magnetic relaxation of agglomerated and immobilized iron oxide nanoparticles for hyperthermia and imaging applications},
  series = {IEEE Magnetic Letters},
  volume    = {9},
  journal   = {IEEE Magnetic Letters},
  number    = {Article number 8519617},
  publisher = {IEEE},
  address   = {New York, NY},
  issn      = {1949-307X},
  doi       = {10.1109/LMAG.2018.2879034},
  year      = {2018},
  abstract  = {Magnetic nanoparticles (MNPs) are used as therapeutic and diagnostic agents for local delivery of heat and image contrast enhancement in diseased tissue. Besides magnetization, the most important parameter that determines their performance for these applications is their magnetic relaxation, which can be affected when MNPs immobilize and agglomerate inside tissues. In this letter, we investigate different MNP agglomeration states for their magnetic relaxation properties under excitation in alternating fields and relate this to their heating efficiency and imaging properties. With focus on magnetic fluid hyperthermia, two different trends in MNP heating efficiency are measured: an increase by up to 23\% for agglomerated MNP in suspension and a decrease by up to 28\% for mixed states of agglomerated and immobilized MNP, which indicates that immobilization is the dominant effect. The same comparatively moderate effects are obtained for the signal amplitude in magnetic particle spectroscopy.},
  language  = {en}
}
@inproceedings{NeuJanserKhatibietal.2016,
  author    = {Neu, Eugen and Janser, Frank and Khatibi, Akbar A. and Orifici, Adrian C.},
  title     = {In-flight vibration-based structural health monitoring of aircraft wings},
  series = {30th Congress of the internatonal council of the aeronautical sciences : 25.-30. September 2016, Daejeon, Korea},
  booktitle = {30th Congress of the internatonal council of the aeronautical sciences : 25.-30. September 2016, Daejeon, Korea},
  pages     = {10 Seiten},
  year      = {2016},
  abstract  = {This work presents a methodology for automated damage-sensitive feature extraction and anomaly detection under multivariate operational variability for in-flight assessment of wings. The method uses a passive excitation approach, i. e. without the need for artificial actuation. The modal system properties (natural frequencies and damping ratios) are used as damage-sensitive features. Special emphasis is placed on the use of Fiber Bragg Grating (FBG) sensing technology and the consideration of Operational and Environmental Variability (OEV). Measurements from a wind tunnel investigation with a composite cantilever equipped with FBG and piezoelectric sensors are used to successfully detect an impact damage. In addition, the feasibility of damage localisation and severity estimation is evaluated based on the coupling found between damageand OEV-induced feature changes.},
  language  = {en}
}
@inproceedings{KleineKallweitMichauxetal.2016,
  author    = {Kleine, Harald and Kallweit, Stephan and Michaux, Frank and Havermann, Marc and Olivier, Herbert},
  title     = {PIV Measurement of Shock Wave Diffraction},
  series = {18th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2016, Lissabon},
  booktitle = {18th International Symposium on Applications of Laser Techniques to Fluid Mechanics, 2016, Lissabon},
  pages     = {1 -- 14},
  year      = {2016},
  language  = {en}
}
@inproceedings{DinghoferHartung2020,
  author    = {Dinghofer, Kai and Hartung, Frank},
  title     = {Analysis of Criteria for the Selection of Machine Learning Frameworks},
  series = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1109/ICNC47757.2020.9049650},
  pages     = {373 -- 377},
  year      = {2020},
  abstract  = {With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.},
  language  = {en}
}