Forschung

Die Koordination unserer Bewegungen in Abstimmung mit unseren Mitmenschen gelingt relativ reibungslos. Damit die Interaktionen in hybriden Gesellschaften effektiv sind und ähnlich reibungslos ablaufen, müssen menschliche Fähigkeiten und das technologisch Machbare analysiert und in neuartiger Weise aufeinander abgestimmt werden. Die Erforschung hybrider Gesellschaften trägt also dazu bei, den Einsatz verkörperter digitaler Technologien in öffentlichen Räumen nach menschlichen Bedürfnissen und Fertigkeiten auszurichten und die dazu nötigen technologischen Innovationen voranzubringen.

Forschungsprojekte

Um die bisher ungelösten Herausforderungen anzugehen und das Miteinander von Menschen und Maschinen in öffentlichen Räumen zu gestalten, ist es notwendig, dass eine Vielzahl an Disziplinen, von Psychologie und Ingenieurwissenschaften über Mathematik und Informatik bis zu den Sozial- und Geisteswissenschaften ihre Stärken zusammenführen. Am Sonderforschungsbereich Hybrid Societies arbeiten Forschende aller acht Fakultäten an der TU Chemnitz zusammen. (Wenn Sie auf die Disziplin in der Grafik klicken, gelangen Sie zu den beteiligten Teilprojekten).

Forschungsbereiche

Sensomotorik
Künstliche Körper
Geteilte Umwelten
Intentionalität
Übergreifende Projekte

Sensomotorik

In diesem Forschungsfeld sind alle Projekte versammelt, die das Wahrnehmen, Vorhersagen und die Bewegungsausführung im Koordinieren und Interagieren mit verkörperten digitalen Technologien erforschen.

Künstliche Körper

Dieses Forschungsfeld umfasst alle Vorhaben, die sich damit beschäftigen, welche Fähigkeiten den verkörperten digitalen Technologien aufgrund ihrer Erscheinung und ihres Verhaltens zugeschrieben werden. Hier geht es darum, inwiefern Prothesen oder virtuelle Agenten als Ersatz oder als Erweiterung des eigenen Körpers erfahren werden.

Geteilte Umwelten

Hier kommen alle Projekte zusammen, die sich für die gemeinsame Aufmerksamkeitsausrichtung, die räumliche Orientierung und das koordinierte Verhalten von Menschen und intelligenten Maschinen interessieren.

Intentionalität

Das Forschungsfeld vereint die Vorhaben, welche die Zuschreibung und die Kommunikation von situationsspezifischen Absichten zwischen Menschen und verkörperten digitalen Technologien untersuchen.

Übergreifende Projekte

Übergreifende Projekte beschäftigen sich sowohl mit Forschungsfragen als auch mit organisatorischen Aufgaben, die alle Forschungsbereiche des Verbunds gleichermaßen betreffen..

Forschungsdisziplinen

Publikationen

Alle Ergebnisse unserer Forschung zur Interaktion von Menschen mit verkörperten digitalen Technologien in hybriden Gesellschaften finden Sie in unseren Publikationen. Sie können diese filtern nach Erscheinungsjahr, Disziplin, Teilprojekt und Publikationsform, damit Sie genau das finden, was Sie suchen.

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    A: Verkörperte Sensor- und Motorleistungen
    B: Künstliche Körper
    C: Geteilte Umgebungen
    D: Intentionalität in hybriden Gesellschaften
    E: Übergreifende Projekte
    Research Projects
    Öffentlichkeitsarbeit Hybrid Societies
    Informations-Infrastruktur-Umgebung Hybrid Societies
    Verantwortung in Hybriden Gesellschaften
    Informationsgewinnung aus hochdimensionalen Daten
    Displays sozialer Zurechenbarkeit
    Glaubwürdige pädagogische Konversationsagenten
    Implizite Fahrsignale
    Menschenähnliche Bewegungsabläufe
    Räumliche Orientierung
    Blickinteraktion
    Stereotypisierung bionischer Körperrestauration
    Avatare: Haltungen und Gangarten
    (De-)Anthropomorphisierung
    En-passant-Evaluation der Systemlatenz
    Am Körper getragene Sensornetzwerke
    Das Erlernen flexibler motorischer Kontrolle
    Handlungswahrnehmung in gemeinsamen Handlungen
    Zentrales Verwaltungsprojekt
    Graduiertenkolleg
    Intentionalität in multimodaler Interaktion
    Telemanipulation
    Research Disciplines
    Bewegungswissenschaften
    Elektrotechnik
    Informatik
    Ingenieurpsychologie
    Kognitive Psychologie
    Künstliche Intelligenz
    Maschinenbau
    Mathematik
    Medien und Kommunikation
    Medienpsychologie
    Persönlichkeitspsychologie
    Physik
    Rechtswissenschaften
    Robotik
    Semiotik und Linguistik
    Sozialpsychologie
    Soziologie
    Werkstoffwissenschaften
Attig, C., & Franke, T. (2022). Why do people abandon activity trackers? The role of user diversity in discontinued use. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2022.2067935
Bautista-Quijano, Roberto, J., Ghrairi, K., Ben Atitallah, B., & Kanoun, O. (2022). Investigation and Implementation of Elastomer Filament Strain Sensors for Monitoring of Hand Gestures. 2021 International Workshop on Impedance Spectroscopy, 97-98. https://doi.org/10.1109/IWIS54661.2021.9711913
Ben Atitallah, B., Hu, Z., Bouchaala, D., Hussain, M. A., Ismail, A., Derbel, N., & Kanoun, O. (2022). Hand Sign Recognition System Based on EIT Imaging and Robust CNN Classification. IEEE Sensors Journal, 22(22), 1729-1737. https://doi.org/10.1109/JSEN.2021.3130982
Breitkreutz, C., Brade, J., Winkler, S., Bendixen, A., Klimant, P., & Jahn, G. (2022). Spatial Updating in Virtual Reality - Auditory and Visual Cues in a Cave Automatic Virtual Environment. 2022 IEEE Conference on Virtual Reality and 3D User Interfaces, 719-727. https://doi.org/10.1109/VR51125.2022.00093
Chiossi, F., Welsch, R., Villa, S., Chuang, L., & Mayer, S. (2022). Virtual Reality Adaptation using Electrodermal Activity to Support User Experience. Big Data and Cognitive Computing, 6(2), 55. https://doi.org/10.3390/bdcc6020055
Göring, F., Hofmann, T., & Streicher, M. (2022). Uniformly connected graphs. Journal of Graph Theory. https://doi.org/10.1002/jgt.22820
Hafsa, M., Atitallah, B. B., Ben Salah, T., Essoukri Ben Amara, N., & Kanoun, O. (2022). Hand Gesture Recognition based on Electrical Impedance Tomography Measurements using Genetic Algorithms. 2021 International Workshop on Impedance Spectroscopy, 123-125. https://doi.org/10.1109/IWIS54661.2021.9711814
Hafsa, M., Ben Atitallah, B., Ben Salah, T., Essoukri Ben Amara, N., & Kanoun, O. (2022). A Genetic Algorithm for Image Reconstruction in Electrical Impedance Tomography for Gesture Recognition. Technisches Messen, 89(5), 310-327. https://doi.org/10.1515/teme-2021-0126
Hensch, A.-C., Beggiato, M., Mandl, S., Strobel, A., & Krems, J. F. (2022). The interplay of personality traits with drivers’ gap acceptance. Advances in Transportation, 60, 329-337. https://doi.org/10.54941/ahfe1002464
Hensch, A.-C., Kreißig, I., Beggiato, M., & Krems, J. F. (2022). The Effect of eHMI Malfunctions on Younger and Elderly Pedestrians’ Trust and Acceptance of Automated Vehicle Communication Signals. Frontiers in Psychology, 13, 866475. https://doi.org/10.3389/fpsyg.2022.866475
Hofmann, T., & Schwerdtfeger, U. (2022). Edge-connectivity matrices and their spectra. Linear Algebra and Its Applications, 640, 34-47. https://doi.org/10.1016/j.laa.2022.01.012
Kretzschmar, F., Pichler, A., & Beggiato, M. (2022). Detection of Discomfort in Autonomous Driving via Stochastic Approximation. Advances in Transportation, 60, 87-92. https://doi.org/10.54941/ahfe1002437
Krumm, D., Buder, J., & Odenwald, S. (2022). Body-attached sensors for automatic detection of skating stroke events in speed skating. Engineering of Sport 14 Conference Proceedings. https://docs.lib.purdue.edu/resec-isea/2022/session06/4/
Krumm, D., Zenner, A., Sanseverino, G., & Odenwald, S. (2022). Recognition of Basic Gesture Components using Body-Attached Bending Sensors. In A. Spink, J. Barski, A.-M. Brouwer, G. Riedel, & A. Sil (Eds.), Volume 2 of the Proceedings of the joint 12th International Conference on Methods and Techniques in Behavioral Research and the 6th Seminar on Behavioral Methods (pp. 77-82). https://www.measuringbehavior.org/files/Draft-Proceedings-MB2022-Vol_2.pdf
Kutz, D. F., Fröhlich, S., Rudisch, J., Müller, K., & Voelcker-Rehage, C. (2022). Finger Tapping as a Biomarker to Classify Cognitive Status in 80+-Year-Olds. Journal of Personalized Medicine, 12(2), 286. https://doi.org/10.3390/jpm12020286
Mandl, S., Bretschneider, M., Meyer, S., Gesmann-Nuissl, D., Asbrock, F., Meyer, B., & Strobel, A. (2022). Embodied Digital Technologies: First Insights in the Social and Legal Perception of Robots and Users of Prostheses. Frontiers in Robotics and AI, 9, 787970. https://doi.org/10.3389/frobt.2022.787970
Meyer, S., Mandl, S., Gesmann-Nuissl, D., & Strobel, A. (2022). Responsibility in Hybrid Societies: Concepts and Terms. AI and Ethics. https://doi.org/10.1007/s43681-022-00184-2
Munjal, R., Arif, S., Wendler, F., & Kanoun, O. (2022). Comparative Study of Machine-Learning Frameworks for the Elaboration of Feed-Forward Neural Networks by Varying the Complexity of Impedimetric Datasets Synthesized Using Eddy Current Sensors for the Characterization of Bi-Metallic Coins. Sensors, 4(22), 1312. https://doi.org/10.3390/s22041312
Potts, D., & Schmischke, M. (2022). Learning multivariate functions with low-dimensional structures using polynomial bases. Journal of Computational and Applied Mathematics, 403, 113821. https://doi.org/10.1016/j.cam.2021.113821
Potts, D., & Schmischke, M. (2022). Interpretable Transformed ANOVA Approximation on the Example of the Prevention of Forest Fires. Frontiers in Applied Mathematics and Statistics, 8, 795250. https://doi.org/10.3389/fams.2022.795250
Sanseverino, G., Krumm, D., & Odenwald, S. (2022). A Framework for Virtual Evaluation of Body-Attached Sensor Networks. In C. Rizzi, F. Campana, M. Bici, F. Gherardini, T. Ingrassia, & P. Cicconi (Eds.), Design Tools and Methods in Industrial Engineering II. ADM 2021. Lecture Notes in Mechanical Engineering. (pp. 557-568). Cham: Springer. https://doi.org/10.1007/978-3-030-91234-5_56
Schuler, K., Quante, L., Schießl, C., Beggiato, M., & Jahn, G. (2022). Communication between drivers in a road bottleneck scenario. Advances in Transportation, 60, 306-312. https://doi.org/10.54941/ahfe1002461 
Todorovikj, S., Kettner, F., Brand, D., Beggiato, M., & Ragni, M. (2022). Predicting Individual Discomfort in Autonomous Driving. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society (pp. 3103-3109). https://escholarship.org/uc/item/71n4f4cr
Vecchiato, G., Ahlström, C., & Chuang, L. L. (2022). Editorial: Cognitive Mechanisms for Safe Road Traffic Systems. Frontiers in Neuroergonomics, 37, 897659. https://doi.org/10.3389/fnrgo.2022.897659
Al-Hammouri, S., Barioul, R., Lweesy, K., Ibbini, M., & Kanoun, O. (2021). Six Sensors Bracelet for Force Myography based American Sign Language Recognition. 2021 18th International Multi-Conference on Systems, Signals & Devices, 835-839. https://doi.org/10.1109/SSD52085.2021.9429399
Albrecht, S. (2021). Current research on the linguistic features of Chinese English. World Englishes. https://doi.org/10.1111/weng.12572
Atitallah, B. B., Rajendran, D., Hu, Z., Ramalingame, R., Bautista Quijano, J. R., da Veiga Torres, R., Bouchaala, D., Derbel, N., & Kanoun, O. (2021). Piezo-Resistive Pressure and Strain Sensors for Biomedical and Tele-Manipulation Applications. In O. Kanoun & N. Derbel (Eds.), Advanced Sensors for Biomedical Applications. Smart Sensors, Measurement and Instrumentation (Vols. 38, pp. 47-65). Cham: Springer. https://doi.org/10.1007/978-3-030-71225-9_3
Atitallah, B. B., Rajendran, D., Ramalingame, R., Bautista Quijano, J. R., & Kanoun, O. (2021). Ultra Thin Nanocomposite In-Sole Pressure Sensor Matrix for Gait Analysis. Smart Sensors, Measurement and Instrumentation, 33-45. https://doi.org/10.3390/s21186082
Bandi, C., & Thomas, U. (2021). Skeleton-based Action Recognition for Human-Robot Interaction using Self-Attention Mechanism. 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition. https://doi.org/10.1109/FG52635.2021.9666948
Dettmann, A., Hartwich, F., Roßner, P., Beggiato, M., Felbel, K., Krems, J. F., & Bullinger, A. C. (2021). Comfort or Not? Automated Driving Style and User Characteristics Causing Human Discomfort in Automated Driving. International Journal of Human–Computer Interaction, 37(4), 331-339. https://doi.org/10.1080/10447318.2020.1860518
Dommel, P., Pichler, A., & Beggiato, M. (2021). Comparison of a Logistic and SVM Model to Detect Discomfort in Automated Driving. In D. Russo, T. Ahram, W. Karwowski, G. Di Bucchianico, & R. Taiar (Eds.), Intelligent Human Systems Integration 2021. IHSI 2021. Advances in Intelligent Systems and Computing (Vols. 1322, pp. 44-49). Cham: Springer. https://doi.org/10.1007/978-3-030-68017-6_7
Drewes, J., Feder, S., & Einhäuser, W. (2021). Gaze During Locomotion in Virtual Reality and the Real World. Frontiers in Neuroscience, 15, 656913. https://doi.org/10.3389/fnins.2021.656913
Felbel, K., Dettmann, A., & Bullinger, A. C. (2021). Communication of intentions in automated driving – the importance of implicit cues and contextual information on freeway situations. In H. Krömker (Ed.), HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science (Vols. 12791). Cham: Springer. https://doi.org/10.1007/978-3-030-78358-7_17
Goelz, C., Mora, K., Rudisch, J., Gaidai, R., Reuter, E., Godde, B., Reinsberger, C., Voelcker-Rehage, C., & Vieluf, S. (2021). Classification of visuomotor tasks based on electroencephalographic data depends on age-related differences in brain activity patterns. Neural Networks, 142, 363-374. https://doi.org/10.1016/j.neunet.2021.04.029
Gäbert, C., Kaden, S., & Thomas, U. (2021). Generation of Human-like Arm Motions using Sampling-based Motion Planning. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2534-2541. https://doi.org/10.1109/IROS51168.2021.9636068
Heil, S., Bakaev, M., & Gaedke, M. (2021). Web User Interface as a Message: Power Law for Fraud Detection in Crowdsourced Labeling. In M. Brambilla, R. Chbeir, F. Frasincar, & I. Manolescu (Eds.), Web Engineering. Lecture Notes in Computer Science (Vols. 12706). Cham: Springer. https://doi.org/10.1007/978-3-030-74296-6_7
Hellara, H., Barioul, R., Sahnoun, S., Ahmed, F., & Kanoun, O. (2021). Comparative of Swarm Intelligence based Wrappers for sEMG Signals Feature Selection. 2021 18th IEEE SSD International Multi-Conference on Systems, Signals and Devices, 829-834. https://doi.org/10.1109/SSD52085.2021.9429511
Hensch, A.-C., Beggiato, M., & Krems, J. F. (2021). Drive safely and comfortably – Gap Acceptance as a Basis for a user-centred Design of Driving Styles in Automated Vehicles. Proceedings of the 7th Humanist Conference. https://www.humanist-vce.eu/fileadmin/contributeurs/humanist/Rhodes2021/Hensch.pdf
Hensch, A.-C., Beggiato, M., & Krems, J. F. (2021). Predicting Lane Changes by Identifying Sequence Patterns of Implicit Communication Cues. In N. Stanton (Ed.), Advances in Human Aspects of Transportation. Lecture Notes in Networks and Systems (Vols. 270). Cham: Springer. https://doi.org/10.1007/978-3-030-80012-3_1
Hensch, A.-C., Beggiato, M., & Krems, J. F. (2021). The Effects of eHMI Failures on Elderly Participants’ Assessment of Automated Vehicle Communication Signals. In T. Ahram & R. Taiar (Eds.), Human Interaction, Emerging Technologies and Future Systems V (pp. 355-363). Cham: Springer. https://doi.org/10.1007/978-3-030-85540-6_45
Hensch, A.-C., Beggiato, M., Schömann, M. X., & Krems, J. F. (2021). Different Types, Different Speeds – The Effect of Interaction Partners and Encountering Speeds at Intersections on Drivers’ Gap Acceptance as an Implicit Communication Signal in Automated Driving. In H. Krömker (Ed.), HCI in Mobility, Transport, and Automotive Systems. HCII 2021. Lecture Notes in Computer Science (Vols. 12791). Cham: Springer. https://doi.org/10.1007/978-3-030-78358-7_36
Hielscher, R., & Lippert, L. (2021). Isometric Embeddings of Quotients of the Rotation Group Modulo Finite Symmetries. Journal of Multivariate Analysis, 185, 104764. https://doi.org/10.48550/arXiv.2007.09664
Krabbes, P., Queck, M., Scherf, A., Ohler, P., & Rehren, O. (2021). To err makes human - The influence of errors and speech parameters on perceived humanness of robots. https://doi.org/10.18154/RWTH-CONV-245978
Krumm, D., Kuske, N., Neubert, M., Buder, J., Hamker, F., & Odenwald, S. (2021). Determining push-off forces in speed skating imitation drills. Sports Engineering Volume, 24, 25. https://doi.org/10.1007/s12283-021-00362-1
König, L. M., Attig, C., Franke, T., & Renner, B. (2021). Barriers to and facilitators for using nutrition apps: a systematic review and conceptual framework. JMIR MHealth and UHealth, 9(6), e20037. https://doi.org/10.2196/20037
Langer, A., Göpfert, C., & Gaedke, M. (2021). CARDINAL: Contextualized Adaptive Research Data Description INterface Applying LinkedData. In M. Brambilla, R. Chbeir, F. Frasincar, & I. Manolescu (Eds.), Web Engineering. Lecture Notes in Computer Science (Vols. 12706). Cham: Springer. https://doi.org/10.1007/978-3-030-74296-6_2
Larisch, R., Gönner, L., Teichmann, M., & Hamker, F. (2021). Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity. PLoS Computational Biology, 17(11), e1009566. https://doi.org/10.1371/journal.pcbi.1009566
Maith, O., Schwarz, A., & Hamker, F. (2021). Optimal attention tuning in a neuro-computational model of the visual cortex–basal ganglia–prefrontal cortex loop. Neural Networks, 142, 534-547. https://doi.org/10.1016/j.neunet.2021.07.008
Noura, M., Wang, Y., Heil, S., & Gaedke, M. (2021). OntoSpect: IoT Ontology Inspection by Concept Extraction and Natural Language Generation. In M. Brambilla, R. Chbeir, F. Frasincar, & I. Manolescu (Eds.), Web Engineering. Lecture Notes in Computer Science (Vols. 12706). Cham: Springer. https://doi.org/10.1007/978-3-030-74296-6_4
Novinac, S., Fallaha, A., Rashidib, S., Beuth, F., & Hamker, F. (2021). A neuro-computational model of visual attention with multiple attentional control sets. Vision Research, 189, 104-118. https://doi.org/10.1016/j.visres.2021.08.009
Potts, D., & Schmischke, M. (2021). Approximation of high-dimensional periodic functions with Fourier-based methods. SIAM Journal on Numerical Analysis, 59, 9. https://doi.org/10.1137/20M1354921
Potts, D., & Schmischke, M. (2021). Interpretable Approximation of High-Dimensional Data. SIAM Journal on Mathematics of Data Science, 3(4), 1301-1323. https://doi.org/10.1137/21M1407707
Potts, D., & Tasche, M. (2021). Uniform error estimates for nonequispaced fast Fourier transforms. Sampling Theory, Signal Processing, and Data Analysis, 19, 17. https://doi.org/10.1007/s43670-021-00017-z
Potts, D., & Tasche, M. (2021). Continuous window functions for NFFT. Advances in Computational Mathematics, 47, 53. https://doi.org/10.1007/s10444-021-09873-8
Rajendran, D., Ben Atitallah, B., Ramalingame, R., Quijano Jose, R., & Kanoun, O. (2021). Ultra Thin Nanocomposite In-Sole Pressure Sensor Matrix for Gait Analysis. In O. Kanoun & N. Derbel (Eds.), Advanced Sensors for Biomedical Applications. Smart Sensors, Measurement and Instrumentation (Vols. 38, pp. 33-45). Cham: Springer. https://www.springerprofessional.de/ultra-thin-nanocomposite-in-sole-pressure-sensor-matrix-for-gait/19252490
Rajendran, D., Ramalingame, R., Palaniyappan, S., Wagner, G., & Kanoun, O. (2021). Flexible Ultra-Thin Nanocomposite Based Piezoresistive Pressure Sensors for Foot Pressure Distribution Measurement. Sensors, 21(18), 6082. https://doi.org/10.3390/s21186082
Ramalingame, R., Barioul, R., Li, X., Sanseverino, G., Krumm, D., Odenwald, S., & Kanoun, O. (2021). Wearable Smart Band for American Sign Language Recognition with Polymer Carbon Nanocomposite based Pressure Sensors. IEEE Sensors Letters, 5(6), 6001204. https://doi.org/10.1109/LSENS.2021.3081689
Siegert, V., & Gaedke, M. (2021). WTA: Towards a Web-based Testbed Architecture. In M. Brambilla, R. Chbeir, F. Frasincar, & I. Manolescu (Eds.), Web Engineering. Lecture Notes in Computer Science (Vols. 12706). Cham: Springer. https://doi.org/10.1007/978-3-030-74296-6_9
Teichmann, M., Larisch, R., & Hamker, F. (2021). Performance of biologically grounded models of the early visual system on standard object recognition tasks. Neural Networks, 144, 210-228. https://doi.org/10.1016/j.neunet.2021.08.009
Atitallah, B. B., Abbasi, M. B., Barioul, R., Bouchaala, D., Derbel, N., & Kanoun, O. (2020). Simultaneous Pressure Sensors Monitoring System for Hand Gestures Recognition. 2020 IEEE Sensors. https://doi.org/10.1109/SENSORS47125.2020.9278884
Dommel, P., & Pichler, A. (2020). Convex Risk Measures based on Divergence. In Pure and Applied Functional Analysis. https://doi.org/10.48550/arXiv.2003.07648
Jahn, K., & Nissen, A. (2020). Towards Dual Processing of Social Robots: Differences in the Automatic and Reflective System. ICIS 2020 Proceedings. https://aisel.aisnet.org/icis2020/hci_artintel/hci_artintel/4
Langer, A., Göpfert, C., & Gaedke, M. (2020). Querying the Semantic Web for Concept Identifiers to Annotate Research Datasets. In T. vor der Brück (Ed.), Proceedings of the Fourteenth International Conference on Advances in Semantic Processing (pp. 49-55). ThinkMind. https://www.thinkmind.org/index.php?view=article&articleid=semapro_2020_2_50_30022
Langer, A., Vu, D. N. H., & Gaedke, M. (2020). SolidRDP: Applying Solid Data Containers for Research Data Publishing. In M. Bielikova, T. Mikkonen, & C. Pautasso (Eds.), Web Engineering. ICWE 2020. Lecture Notes in Computer Science, (Vols. 12128, pp. 399-415). Cham: Springer. https://doi.org/10.1007/978-3-030-50578-3_27
Pentzold, C., Kaun, A., & Lohmeier, C. (2020). Imagining and instituting future media: Introduction to the special issue. Convergence: The International Journal of Research into New Media Technologies, 26(4), 705-715. https://doi.org/10.1177/1354856520938584