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2024
Litschka, M., Paganini, C., & Rademacher, L. (Eds.). (2024). Digitalisierte Massenkommunikation und Verantwortung. Politik, Ökonomik und Ethik von Plattformen (Vol. 22). Nomos.
2023
Altendorfer, K., & Felberbauer, T. (2023). Forecast and production order accuracy for stochastic forecast updates with demand shifting and forecast bias correction. Simulation Modelling Practice and Theory, 125, 102740. https://doi.org/10.1016/j.simpat.2023.102740
Belinskaya, Y. (2023). How the internet is being tamed in Russia: Chronicle of state securitization measures. Journalism Research, 6(1), 71–92. https://doi.org/10.1453/2569-152x-12023-13030-en
Belinskaya, Y. (2023). ‘Insider news’ on Russian Telegram: Resembling truth, proximity and objectivity. Journal of Applied Journalism & Media Studies. https://doi.org/10.1386/ajms_00108_1
de Jesus Oliveira, V. A., Slijepčević, D., Dumphart, B., Ferstl, S., Reis, J., Raberger, A.-M., Heller, M., Horsak, B., & Iber, M. (2023). Auditory feedback in tele-rehabilitation based on automated gait classification. Personal and Ubiquitous Computing. https://doi.org/10.1007/s00779-023-01723-2
Dumphart, B., Slijepcevic, D., Kranz, A., Zeppelzauer, M., & Horsak, B. (2023). Is it time to re-think the appropriateness of autocorrelation for gait event detection? Preliminary results of an ongoing study. Gait & Posture, 106, S50–S51. https://doi.org/10.1016/j.gaitpost.2023.07.064
Dumphart, B., Slijepcevic, D., Zeppelzauer, M., Kranzl, A., Unglaube, F., Baca, A., & Horsak, B. (2023). Robust deep learning-based gait event detection across various pathologies. PLOS ONE, 18(8), e0288555. https://doi.org/10.1371/journal.pone.0288555
Horst, F., Slijepcevic, D., Simak, M., Horsak, B., Schöllhorn, W. I., & Zeppelzauer, M. (2023). Modeling biological individuality using machine learning: A study on human gait. Computational and Structural Biotechnology Journal, 21, 3414–3423. https://doi.org/10.1016/j.csbj.2023.06.009
Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Explainable Machine Learning in Human Gait Analysis: A Study on Children With Cerebral Palsy. IEEE Access, 11, 65906–65923. https://doi.org/10.1109/ACCESS.2023.3289986
Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., Breiteneder, C., & Horsak, B. (2023). Towards more transparency: The utility of Grad-CAM in tracing back deep learning based classification decisions in children with cerebral palsy. Gait & Posture, 100, 32–33. https://doi.org/10.1016/j.gaitpost.2022.11.045
Slijepcevic, D., Horst, F., Simak, M., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2023). Towards personalized gait rehabilitation: How robustly can we identify personal gait signatures with machine learning? Gait & Posture, 106, S192–S193. https://doi.org/10.1016/j.gaitpost.2023.07.232
Vulpe-Grigorasi, A. (2023). Multimodal machine learning for cognitive load based on eye tracking and biosensors. 2023 Symposium on Eye Tracking Research and Applications, 1–3. https://doi.org/10.1145/3588015.3589534
2022
Kovarova-Simecek, M., & Pellegrini, T. (2022). Instrumente der Analyse in der Investor Relations und Finanzkommunikation. In C. P. Hoffmann, D. Schiereck, & A. Zerfaß (Eds.), Handbuch Investor Relations und Finanzkommunikation (pp. 1–21). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-23389-1_14-1
Horsak, B., Simonlehner, M., Schöffer, L., Dumphart, B., Jalaeefar, A., Husinsky, M., & Siragy, T. (2022). Walking overground in a room-scale Virtual Reality Environment: a motor control perspective. 9th World Congress of Biomechanics, Taipei, Taiwan.
Litschka, M. (2022). Classical Political Economy. In Handbook of Media and Communication Economics. Springer. https://doi.org/10.1007/978-3-658-34048-3_2-2
Luh, R., Eresheim, S., Größbacher, S., Petelin, T., Mayr, F., Tavolato, P., & Schrittwieser, S. (2022). PenQuest Reloaded: A Digital Cyber Defense Game for Technical Education. 2022 IEEE Global Engineering Education Conference (EDUCON), 906–914. https://doi.org/10.1109/EDUCON52537.2022.9766700
Nurgazina, J., Felberbauer, T., Asprion, B., & Pinnamaraju, P. (2022). Visualization and clustering for rolling forecast quality verification: A case study in the automotive industry. Procedia Computer Science, 200, 1048–1057. https://doi.org/https://doi.org/10.1016/j.procs.2022.01.304
Rind, A., Slijepcevic, D., Zeppelzauer, M., Unglaube, F., Kranzl, A., & Horsak, B. (2022). Trustworthy Visual Analytics in Clinical Gait Analysis: A Case Study for Patients with Cerebral Palsy. Proc. 2022 IEEE Workshop on TRust and EXpertise in Visual Analytics (TREX), 7–15. https://doi.org/10.1109/TREX57753.2022.00006
Slijepcevic, D., Horst, F., Lapuschkin, S., Horsak, B., Raberger, A.-M., Kranzl, A., Samek, W., Breitender, C., Schöllhorn, W., & Zeppelzauer, M. (2022). Explaining Machine Learning Models for Clinical Gait Analysis. ACM Transactions on Computing for Healthcare, 3(2), 14:1-14:27. https://doi.org/10.1145/3474121
Slijepcevic, D., Horst, F., Simak, M., Lapuschkin, S., Raberger, A. M., Samek, W., Breiteneder, C., Schöllhorn, W. I., Zeppelzauer, M., & Horsak, B. (2022). Explaining machine learning models for age classification in human gait analysis. Gait & Posture, 97, S252–S253. https://doi.org/10.1016/j.gaitpost.2022.07.153