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BayWISS-Kolleg Digitalisierung www.baywiss.de

Forschung im Verbundkolleg Digitalisierung Wie gestalten wir die digitale Welt?

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Der digitale Wandel hat in nur wenigen Jahren unsere Gesellschaft verändert, in Echtzeit erleben wir einen evolutionären Sprung. Wie nie zuvor vernetzt sich die physische Welt mit der virtuellen. Das Digitalzeitalter wird im 21. Jahrhundert global gelebte Selbstverständlichkeit. Wir kommunizieren und konsumieren, arbeiten und lernen online. Wir bekämpfen Herausforderungen wie die Corona-Pandemie mit Big Data und der Analyse von Daten.

Nicht nur in der Krise zeigt sich, dass Digitalisierung weit mehr bedeutet als die Verwirklichung technischer Megatrends. Ob in der Gesundheitsforschung oder in der Logistik, in der Telekommunikation oder in der Energieversorgung, in Produktion und Dienstleistung: Digitale Innovationen haben das Potential, unser Leben zu schützen und nachhaltig zu verbessern.

Fortschritt Bit für Bit

Die Möglichkeiten sind grenzenlos: Digital vernetzte intelligente Dinge und Maschinen erleichtern nicht nur die Bewegung und Produktion von Gütern, sondern optimieren zugleich deren Nutzung, Wartung, Reparatur und das Recyling. Mit Smart Homes, Smart Cities und durch Autonomes Fahren werden auch Infrastruktur und Verkehr zu intelligent verbundenen und miteinander agierenden Systemen. Künstliche Intelligenz erkennt dabei in Sekundenschnelle Muster in unvorstellbaren Massen an Daten, Texten und Bildern – mit Vorteilen auch für Medizin, Landwirtschaft, Logistik sowie viele andere Lebensbereiche und Branchen.

In dem Maße, wie sich die Welt Bit für Bit weiter vernetzt, wird sie auch verwundbar. Die Sicherheit von Hardware, Software und Datenströmen ist bei allem Fortschritt so wichtig wie unsere Entscheidung, wie und in welchem Kontext wir die technischen Möglichkeiten – auch auf Grundlage gesellschaftlicher und ökonomischer Aspekte – einsetzen wollen.

BayWISS an der Schnittstelle zur Zukunft

Die Forschungsprojekte der BayWISS-Doktoranden tragen dazu bei, dass die Welt 4.0 nutzbringende Wirklichkeit wird: Wie kann eine App Ärzten helfen, Patienten zu betreuen? Wie können Menschen mit Hilfe von Augmented-Reality-Brillen mit Maschinen kommunizieren? Wie können Roboter in Katastrophengebieten Verletzte aufspüren? Wie helfen Drohnen, Ernteerträge umweltverträglich zu steigern? Wie gelingt es, dass autonomes zugleich sicheres Fahren bedeutet – auch unter Berücksichtigung von Haftungsfragen? Wie steuern wir intelligente Stromnetze, um die Energiewende und mehr Klimaschutz voranzubringen?

Das BayWISS-Verbundkolleg „Digitalisierung“ verbindet an der Schnittstelle von Technik-, Kommunikations- und Gesellschaftswissenschaften über alle Hochschularten hinweg starke Partner mit ihren Ideen, Ergebnissen und Erfahrungen. In ihrer Vernetzung bergen Forschungsfelder wie Big Data und Data Analytics, Robotik und Telematik, Mensch-Computer-Medien und Informationstechnik das Potential, einen Modernisierungsschub zu entfachen – zum Wohl des einzelnen Menschen, seiner Umwelt und unserer globalen Gesellschaft.

Unsere aktuellen Themen­schwerpunkte:

  • Big Data/ Data Analytics
  • Digitalisierung in industrieller Produktion und Dienstleistung
  • Intelligente Netze
  • Informationstechnik im Gesundheitssystem und in der Gesundheitsforschung
  • Mensch-Computer-Medien
  • Robotik und Telematik
  • Sicherheit von Hardware, Software und Daten
  • Ökonomische und gesellschaftliche Aspekte von Informatiksystemen im Anwendungskontext

Unsere Promotionsprojekte

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Publikationen

2021

  • 1.
    Weigl, S., Wittmann, E., Rück, T., Bierl, R., Matysik, F.-M.: Effects of ambient parameters and cross-sensitivities from O2, CO2 and H2O on the photoacoustic detection of acetone in the UV region. Sensors and Actuators B: Chemical. 328, (2021).

2020

  • 1.
    Schlör, D., Ring, M., Krause, A., Hotho, A.: Financial Fraud Detection with Improved Neural Arithmetic Logic Units. Springer (2020).
  • 2.
    Fertig, T., Schütz, A.: About the Measuring of Information Security Awareness: A Systematic Literature Review. 53rd Hawaii International Conference on System Sciences (2020).
  • 3.
    Brost, J., Egger, C., Lai, R.W.F., Schmid, F., Schröder, D., Zoppelt, M.: Threshold Password-Hardened Encryption Services. In: Ligatti, J., Ou, X., Katz, J., en Vigna, G. (reds.) ACM Conference on Computer and Communications Security. bll. 409–424. ACM (2020).
  • 4.
    Schmidtner, M., Timinger, H., Blust, M., Döring, C., Hilpoltsteiner, D.: Towards an adaptive reference model for agile and hybrid frameworks in automotive development. ICE/ITMC. bll. 1–10. IEEE (2020).
  • 5.
    Doering, C., Schmidtner, M., Maerz, J., Mueller, V., Timinger, H.: Agile working during COVID-19 pandemic. Research Notes on Data and Process Science. issue 1, (2020).
  • 6.
    Schmidtner, M., Timinger, H.: HyValue – a Hybrid Reference Model for the Automotive Product Development Process. IEEE TEMS Technology & Engineering Management Society (2020).
  • 7.
    Kriegl, B., Woratschek, H., Raab, A.: Physicians and Institutional Work: Unpacking the Black Box of Institutionalization at the Front Lines of Healthcare. Proceedings of the European Markting Academy (2020).
  • 8.
    Fertig, T., Schütz, A.E., Weber, K.: Current Issues Of Metrics For Information Security Awareness. In: Rowe, F., Amrani, R.E., Limayem, M., Newell, S., Pouloudi, N., van Heck, E., en Quammah, A.E. (reds.) ECIS (2020).
  • 9.
    Schulz, T., Böhm, M., Gewald, H., Krcmar, H.: Smart mobility – an analysis of potential customers’ preference structures Electronic Markets. Electronic Markets. Springer (2020).
  • 10.
    Schulz, T., Böhm, M., Gewald, H.: Information Technology Choice in Mobility Service Ecosystems: A Qualitative Comparative Analysis. International Conference on Information Systems, ICIS 2020 Proceedings (2020).
  • 11.
    Fertig, T., Schütz, A.E., Weber, K., Müller, N.H.: Towards an Information Security Awareness Maturity Model. In: Zaphiris, P. en Ioannou, A. (reds.) HCI (26). bll. 587–599. Springer (2020).
  • 12.
    Ulsamer, P., Fertig, T., Pfeffel, K., Müller, N.H.: Motor Imagery to Control Mobile Applications - An fNIRS Study. In: Vogel, D., Shen, K.N., Ling, P.S., Hsu, C., Thong, J.Y.L., Marco, M.D., Limayem, M., en Xu, S.X. (reds.) PACIS. bl. 56 (2020).
  • 13.
    Auernhammer, K., Freiling, F., Tavakoli Kolagari, R.: Efficient Black-Box Search for Adversarial Examples using Relevance Masks. In DYnamic and Novel Advances in Machine Learning and Intelligent Cyber Security (DYNAMICS) Workshop (2020).
  • 14.
    Ciba, M., Bestel, R., Nick, C., de Arruda, G.F., Peron, T.K.D.M., Comin, C.H., da Fontoura Costa, L., Rodrigues, F.A., Thielemann, C.: Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity. Neural Comput. 32, 887–911 (2020).
  • 15.
    Herl, G., Hiller, J., Maier, A.: Scanning trajectory optimisation using a quantitative Tuybased local quality estimation for robot-based X-ray computed tomography. Nondestructive Testing and Evaluation. 35, 287–303 (2020).
  • 16.
    Böhm, S.-A.: AI Approaches to Optimize Human-Machine Collaboration in Manufacturing Facilities with IoT-Ready Machinery. In: Davidsson, P., Langheinrich, M., Linde, P., Mayer, S., Casado-Mansilla, D., Spikol, D., Kraemer, F.A., en Russo, N.L. (reds.) IOT Companion. bll. 23:1–23:5. ACM (2020).
  • 17.
    Liang, H., Sauer, T., Faber, C.: Using wavelet transform to evaluate single-shot phase measuring deflectometry data. SPIE Proceedings. SPIE The international society for optics and photonics (2020).
  • 18.
    Weiss, N., Renner, S., Mottok, J., Matousek, V.: Transport Layer Scanning for Attack Surface Detection in Vehicular Networks. Transport Layer Scanning for Attack Surface Detection in Vehicular Networks. bll. 1–8. ACM Computer Science in Cars Symposium (2020).
  • 19.
    Renner, S., Pozzobon, E., Mottok, J.: A Hardware in the Loop Benchmark Suite to Evaluate NIST LWC Ciphers on Microcontrollers. ICICS. bll. 495–509. Springer (2020).
  • 20.
    Wunderlich, S., Ring, M., Landes, D., Hotho, A.: Comparison of System Call Representations for Intrusion Detection. Logic Journal of the IGPL. jzaa058, (2020).
  • 21.
    Wolf, M., Ring, M., Landes, D.: Impact of Generative Adversarial Networks on NetFlow-Based Traffic Classification. In: Herrero, Álvaro, Cambra, C., Urda, D., Sedano, J., Quintián, H., en Corchado, E. (reds.) CISIS. bll. 393–404. Springer (2020).
  • 22.
    Schlör, D., Ring, M., Krause, A., Hotho, A.: Financial Fraud Detection with Improved Neural Arithmetic Logic Units. Presented at the (2020).
  • 23.
    Tritscher, J., Ring, M., Schlör, D., Hettinger, L., Hotho, A.: Evaluation of Post-hoc XAI Approaches Through Synthetic Tabular Data. In: Helic, D., Leitner, G., Stettinger, M., Felfernig, A., en Ras, Z.W. (reds.) ISMIS. bll. 422–430. Springer (2020).
  • 24.
    Schlör, D., Ring, M., Hotho, A.: iNALU: Improved Neural Arithmetic Logic Unit. Frontiers in Artificial Intelligence. 3, 71 (2020).
  • 25.
    Schulz, T., Gewald, H., Böhm, M., Krcmar, H.: Smart Mobility: Contradictions in Value Co-Creation. Information Systems Frontiers. 22, (2020).
  • 26.
    Fischer, F., Niedermaier, M., Hanka, T., Knauer, P., Merli, D.: Analysis of Industrial Device Architectures for Real-Time Operations under Denial of Service Attacks. CoRR. abs/2007.08885, (2020).
  • 27.
    Schütz, A., Fertig, T., Weber, K.: Analyze Before You Sensitize: Preparation of a Targeted ISA Training. 53rd Hawaii International Conference on System Sciences (2020).
  • 28.
    Müller-Wuttke, M., Schütz, A.E., Franz, F., Müller, N.H.: Proactive Smart City Interactions. In: Zaphiris, P. en Ioannou, A. (reds.) HCI (26). bll. 615–624. Springer (2020).
  • 29.
    Hilpoltsteiner, D., Schmidtner, M.: ADAMO - Echtzeit Kollaboration mit adaptiven Prozessmodellen (ADAMO - Real-Time Collaboration with Adaptive Process Models). In: Michael, J., Bork, D., Fill, H.-G., Fettke, P., Karagiannis, D., Köpke, J., Koschmider, A., Mayr, H.C., Rehse, J.-R., Reimer, U., Striewe, M., Tropmann-Frick, M., en Ullrich, M. (reds.) Modellierung (Companion). bll. 193–197. CEUR-WS.org (2020).

2019

  • 1.
    Schütz, A.E., Fertig, T., Weber, K., Müller, N.H.: How E-Learning Can Facilitate Information Security Awareness. In: Zaphiris, P. en Ioannou, A. (reds.) HCI (25). bll. 390–401. Springer (2019).
  • 2.
    Niedermaier, M., Striegel, M., Sauer, F., Merli, D., Sigl, G.: Efficient Intrusion Detection on Low-Performance Industrial IoT Edge Node Devices. Computing Research Repository CoRR. abs/1908.03964, (2019).
  • 3.
    Zoppelt, M., Kolagari, R.T.: What Today’s Serious Cyber Attacks on Cars Tell Us: Consequences for Automotive Security and Dependability. In: Papadopoulos, Y., Aslansefat, K., Katsaros, P., en Bozzano, M. (reds.) IMBSA. bll. 270–285. Springer (2019).
  • 4.
    Zoppelt, M., Tavakoli Kolagari, R.: UnCle SAM : Modeling Cloud Attacks with the Automotive Security Abstraction Model. In CLOUD COMPUTING 2019. CLOUD COMPUTING 2019, The Tenth International Conference on Cloud Computing, GRIDs, and Virtualization, At Venice, Italy (2019).
  • 5.
    Ring, M., Wunderlich, S., Scheuring, D., Landes, D., Hotho, A.: A survey of network-based intrusion detection data sets. In Computers and Security 86, 2019, 147-167, DOI:. Computers and Security. bll. 147–167 (2019).
  • 6.
    von Rymon Lipinski, B., Seibt, S., Roth, J., Abé, D.: Level Graph - Incremental Procedural Generation of Indoor Levels using Minimum Spanning Trees. CoG. bll. 1–7. IEEE (2019).
  • 7.
    Weber, K., Saueressig, G., Schütz, A.: Informationssicherheit und Datenschutz an Hochschulen organisieren. Angewandte Forschung in der Wirtschaftsinformatik. (2019).
  • 8.
    Franz, F., Fertig, T., Schütz, A.E., Vu, H.: Towards Human-readable Smart Contracts. IEEE ICBC. bll. 38–42. IEEE (2019).
  • 9.
    Kerscher, S., Ludwig, B., Müller, N.: Investigating the Added Value of Combining Regression Results from Different Window Lengths. AIKE. bll. 128–135. IEEE (2019).
  • 10.
    Koch, P., May, S., Engelhardt, H., Ziegler, J., Nüchter, A.: Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention. SSRR. bll. 1–2. IEEE (2019).
  • 11.
    Niedermaier, M., Hanka, T., Plaga, S., von Bodisco, A., Merli, D.: Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation. Computing Research Repository CoRR. abs/1904.04271, (2019).
  • 12.
    Fertig, T., Schütz, A.E., Weber, K., Müller, N.H.: Measuring the Impact of E-Learning Platforms on Information Security Awareness. In: Zaphiris, P. en Ioannou, A. (reds.) HCI (25). bll. 26–37. Springer (2019).
  • 13.
    Sauer, F., Niedermaier, M., Kießling, S., Merli, D.: LICSTER - A Low-cost ICS Security Testbed for Education and Research. Computing Research Repository CoRR. abs/1910.00303, (2019).
  • 14.
    Niedermaier, M., Fischer, F., Merli, D., Sigl, G.: Network Scanning and Mapping for IIoT Edge Node Device Security. Computing Research Repository CoRR. abs/1910.07622, (2019).
  • 15.
    Reinker, F., Wagner, R., Hasselmann, K., aus der Wiesche, S., Fritsche, M., Epple, P., Rußwurm, H.J.: Testing, modeling and simulation of fans working with organic vapors. Proceedings of 13th European Conference on Turbomachinery Fluid dynamics & Thermodynamics (2019).
  • 16.
    Liang, H., Zimmermann, A., Reiner, K., Christian, F.: A new method for solving the height problem in deflectometry. Proceedings Applied Optical Metrology III (2019).
  • 17.
    Liang, H., Zimmermann, A., Kickingereder, R., Faber, C.: Eine neue Methode zur Lösung des Höhenproblems in der Deflektometrie. Deutsche Gesellschaft für angewandte Optik e.V (2019).
  • 18.
    Herl, G., Hiller, J., Kasperl, S., Maier, A.: Reduktion von Metallartefakten durch multipositionale Datenfusion in der industriellen Röntgen-Computertomographie. de Gruyter, tm-Technisches Messen. (2019).
  • 19.
    Epple, P., Steppert, M., Malcherek, A., Fritsche, M.: Theoretical and Numerical Analysis of the Pressure Distribution and Discharge Velocity in Flows Under Inclined Sluice Gates. ASME-JSME_KSME 2019 8th Joint Fluids Engineering Conference. (2019).
  • 20.
    Fritsche, M., Epple, P., Hasselmann, K., Reinker, F., Wagner, R., aus der Wiesche, S., Russwurm, H.: CFD-Simulation of Centrifugal Fan Performance Characteristics Using Ideal and Real Gas Models for Air and Organic Fluids. ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference (2019).
  • 21.
    Auernhammer, K., Tavakoli Kolagari, R., Zoppelt, M.: Attacks on Machine Learning: Lurking Danger for Accountability. Proceedings of the Association for the Advancement of Artificial Intelligence AAAI Workshop on Artificial Intelligence Safety 2019 (2019).
  • 22.
    aus der Wiesche, S., Reinker, F., Wagner, R., Epple, P., Fritsche, M., Russwurm, H.J.: An Accurate Thermal Measurement Approach for Determining Fan Efficiencies Based on System Identification. ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference (2019).
  • 23.
    Herl, G., Hiller, J., Sauer, T.: Artifact reduction in X-ray computed tomography by multipositional data fusion using local image quality measures. Proceedings of the 9th Conference on Industrial Computed Tomography, Padova, Italy (iCT 2019) (2019).
  • 24.
    Koch, P., May, S., Engelhardt, H., Ziegler, J., Nüchter, A.: Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’19). bl. 1–2 (2019).
  • 25.
    Niedermaier, M., Merli, D., Georg, S.: A Secure Dual-MCU Architecture for Robust Communication of IIoT Devices. Mediterranean Conference on Embedded Computing (MECO); IEEE. (2019).
  • 26.
    Schütz, A., Tobias, F., Kristin, W., Nicholas, M.: How E-Learning can Faciliate Information Security Awareness. Learning and Collaboration Technologies. (2019).

2018

  • 1.
    Kasperl, S., Hanke, R., Oeckl, S., Schmitt, P., Uhlmann, N., Heinz, D., Herl, G., Hiller, J., Kämmler, A., Miller, T., Stock, A., Sauer, T.: Digitalisierung, Verarbeitung und Analyse kultureller und industrieller Objekte: Wertschöpfung aus großen Datenmengen. Jahrestagung für zerstörungsfreie Prüfung (2018), Deutsche Gesellschaft DGZfP (2018).
  • 2.
    Ring, M., Schlör, D., Landes, D., Hotho, A.: Flow-based Network Traffic Generation using Generative Adversarial Networks. Computing Research Repository CoRR. abs/1810.07795, (2018).
  • 3.
    Schütz, A.E., Fertig, T., Weber, K., Vu, H., Hirth, M., Tran-Gia, T.: Vertrauen ist gut, Blockchain ist besser - Einsatzmöglichkeiten von Blockchain für Vertrauensprobleme im Crowdsourcing. HMD Prax. der Wirtschaftsinformatik. 55, 1155–1166 (2018).
  • 4.
    Pfitzner, C., May, S., Nüchter, A.: Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data. Sensors. 18, (2018).
  • 5.
    Stock, M., Herl, G., Sauer, T., Hiller, J.: Edge Preserving Compression of CT Scans using Wavelets. Proceedings of the Structural Health Monitoring, International Symposium Nondestructive Testing 4-5 October 2018, Saarbruecken, Germany (2018).
  • 6.
    Schulz, T., Überle, M.: How Institutional Arrangements impede Realization of Smart Ecosystems: the Case of Door-to-Door Mobility integrators. In: Bednar, P.M., Frank, U., en Kautz, K. (reds.) Proceedings of the European Conference on Information Systems (ECIS 2018), Portsmouth, UK, 2018. bl. 135 (2018).
  • 7.
    Kasperl, S., Hanke, R., Oeckl, S., Schmitt, P., Uhlmann, N., Heinz, D., Herl, G., Hiller, J., Kämmler, A., Miller, T., Stock, A.M., Sauer, T.: Digitization, Data Processing and Analysis of Industrial and Cultural Objects: Creating Additional Value from Big Data. Proceedings of the 12th, European Conference on Non-Destructive Testing (ECNDT) 2018, Gothenburg-Sweden (2018).
  • 8.
    Herl, G., Rettenberger, S., Hiller, J., Sauer, T.: Metal artifact reduction by fusion of CT scans from different positions using the unfiltered backprojection. Proceedings of the 8th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2018) (2018).
  • 9.
    Ring, M., Landes, D., Hotho, A.: Detection of slow port scans in flow-based network traffic. PLOS ONE. 13, 1–18 (2018).
  • 10.
    Schütz, A., Fertig, T., Weber, K., Vu, H., Hirth, M., Tran-Gia, T.: Vertrauen ist gut, Blockchain ist besser - Einsatzmöglichkeiten von Blockchain für Vertrauensprobleme im Crowdsourcing. HMD Praxis der Wirtschaftsinformatik. (2018).
  • 11.
    Stieler, M., Kriegl, B.: How do consumers experience the emotional rollercoaster? A smartphone app to measure emotions continously, transfer. Werbeforschung & Praxis. 64, 43–53 (2018).
  • 12.
    Niedermaier, M., Malchow, J.-O., Fischer, F., Marzin, D., Merli, D., Roth, V., von Bodisco, A.: You Snooze, You Lose: Measuring PLC Cycle Times under Attacks. In: Rossow, C. en Younan, Y. (reds.) WOOT @ USENIX Security Symposium. USENIX Association (2018).

2017

  • 1.
    Koch, R., May, S., Nüchter, A.: Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements. Proceedings of the 7th International Society for Photogrammetry and Remote Sensing, ISPRS International Workshop 3D-ARCH 2017: "3D Virtual Reconstruction and Visualization of Complex Architectures". bl. 377–384. , Nafplio, Greece (2017).
  • 2.
    Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: Creation of Flow-Based Data Sets for Intrusion Detection. Journal of Information Warfare. 16, 41–54 (2017).
  • 3.
    Ring, M., Landes, D., Dallmann, A., Hotho, A.: IP2Vec: Learning Similarities Between IP Addresses. 2017 IEEE International Conference on Data Mining Workshops (ICDMW). bll. 657–666 (2017).
  • 4.
    Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: A Toolset for Intrusion and Insider Threat Detection. In: Palomares Carrascosa, I., Kalutarage, H.K., en Huang, Y. (reds.) Data Analytics and Decision Support for Cybersecurity: Trends, Methodologies and Applications. bl. 3–31. Springer International Publishing, Cham (2017).
  • 5.
    Ring, M., Wunderlich, S., Grüdl, D., Landes, D., Hotho, A.: Flow-based benchmark data sets for intrusion detection. Proceedings of the 16th European Conference on Cyber Warfare and Security (ECCWS). bl. 361–369. ACPI (2017).

2019

  • Auernhammer K, Kolagari RT, Zoppelt M

    . Attacks on Machine Learning: Lurking Danger for Accountability. In: Espinoza H, hÉigeartaigh SÓ, Huang X, Hernández-Orallo J, Castillo-Effen M, editors. Proceedings of the Association for the Advancement of Artificial Intelligence AAAI Workshop on Artificial Intelligence Safety [online]. CEUR-WS.org; 2019. Accessed at: ceur-ws.org/Vol-2301/paper_2.pdf.

  • aus der Wiesche S, Reinker F, Wagner R, Epple P, Fritsche M, Russwurm HJ. An Accurate Thermal Measurement Approach for Determining Fan Efficiencies Based on System Identification. ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference [online]. 2019.

  • Dietrich MP, Winterfeldt G, von Mammen S. Towards EEG-Based Eye-Tracking for Interaction Design in Head-Mounted Devices. Proceedings of the 7th International Conference on Consumer Electronics Berlin (ICCE-Berlin), 2017 IEEE. 2017.

  • Epple P, Steppert M, Malcherek A, Fritsche M. Theoretical and Numerical Analysis of the Pressure Distribution and Discharge Velocity in Flows Under Inclined Sluice Gates. ASME-JSME_KSME 2019 8th Joint Fluids Engineering Conference [online serial]. Epub 2019.

  • Fertig T, Schütz A. About the Measuring of Information Security Awareness: A Systematic Literature Review. 53rd Hawaii International Conference on System Sciences [online]. 2020.

  • Fertig T, Schütz AE, Weber K, Müller NH. Measuring the Impact of E-Learning Platforms on Information Security Awareness. In: Zaphiris P, Ioannou A, editors. HCI (25) [online]. Springer; 2019. p. 26–37.

  • Franz F, Fertig T, Schütz AE, Vu H. Towards Human-readable Smart Contracts. IEEE ICBC [online]. IEEE; 2019. p. 38–42.

  • Weber K, Saueressig G, Schütz A. Informationssicherheit und Datenschutz an Hochschulen organisieren. Angewandte Forschung in der Wirtschaftsinformatik [online serial]. Epub 2019.

  • Fritsche M, Epple P, Hasselmann K, et al. CFD-Simulation of Centrifugal Fan Performance Characteristics Using Ideal and Real Gas Models for Air and Organic Fluids. ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference [online]. 2019.

  • Herl G, Hiller J, Kasperl S, Maier A. Reduktion von Metallartefakten durch multipositionale Datenfusion in der industriellen Röntgen-Computertomographie. de Gruyter, tm-Technisches Messen [online serial]. Epub 2019.

  • Herl G, Hiller J, Sauer T. Artifact reduction in X-ray computed tomography by multipositional data fusion using local image quality measures. Proceedings of the 9th Conference on Industrial Computed Tomography, Padova, Italy (iCT 2019). 2019.

  • Herl G, Rettenberger S, Hiller J, Sauer T. Metal artifact reduction by fusion of CT scans from different positions using the unfiltered backprojection. Proceedings of the 8th Conference on Industrial Computed Tomography, Wels, Austria (iCT 2018). 2018.

  • Kasperl S, Hanke R, Oeckl S, Schmitt P, Uhlmann N, Heinz D, Herl G, et al. Digitalisierung, Verarbeitung und Analyse kultureller und industrieller Objekte: Wertschöpfung aus großen Datenmengen. Jahrestagung für zerstörungsfreie Prüfung (2018), Deutsche Gesellschaft DGZfP. 2018.

  • Kasperl S, Hanke R, Oeckl S, Schmitt P, Uhlmann N, Heinz D, Herl G, et al. Digitization, Data Processing and Analysis of Industrial and Cultural Objects: Creating Additional Value from Big Data. Proceedings of the 12th, European Conference on Non-Destructive Testing (ECNDT) 2018, Gothenburg-Sweden. 2018.

  • Kerscher S, Ludwig B, Müller N. Investigating the Added Value of Combining Regression Results from Different Window Lengths. AIKE [online]. IEEE; 2019. p. 128–135.

  • Koch P, May S, Engelhardt H, Ziegler J, Nüchter A. Signed Distance Based Reconstruction for Exploration and Change Detection in Underground Mining Disaster Prevention. IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR ’19) [online]. 2019. p. 1-2.

  • Koch R, Böttcher L, Jahrsdörfer M, et al. Out of lab calibration of a rotating 2D scanner for 3D mapping. Proceedings of the International Society for Optics and Photonics SPIE optical metrology, Videometrics, Range Imaging, and Applications [online]. Munich, Germany; 2017. p. 10332-10332–10338.

  • Koch R, May S, Nüchter A. Detection and Purging of Specular Reflective and Transparent Object Influences in 3D Range Measurements. Proceedings of the 7th International Society for Photogrammetry and Remote Sensing, ISPRS International Workshop 3D-ARCH 2017: “3D Virtual Reconstruction and Visualization of Complex Architectures” [online]. Nafplio, Greece; 2017. p. 377--384.

  • Koch R, May S, Nüchter A. Effective Distinction Of Transparent And Specular Reflective Objects In Point Clouds Of A Multi-Echo Laser Scanner. Proceedings of the 18th IEEE International Conference on Advanced Robotics (ICAR ’17) [online]. Hong Kong, China; 2017. p. 566--571.

  • Liang H, Zimmermann A, Kickingereder R, Faber C. Eine neue Methode zur Lösung des Höhenproblems in der Deflektometrie. Deutsche Gesellschaft für angewandte Optik eV [online]. 2019.

  • Liang H, Zimmermann A, Reiner K, Christian F. A new method for solving the height problem in deflectometry. Proceedings Applied Optical Metrology III [online]. 2019.

  • Niedermaier M, Fischer F, Merli D, Sigl G. Network Scanning and Mapping for IIoT Edge Node Device Security. Computing Research Repository CoRR [online serial]. 2019;abs/1910.07622.

  • Niedermaier M, Hanka T, Plaga S, von Bodisco A, Merli D. Efficient Passive ICS Device Discovery and Identification by MAC Address Correlation. Computing Research Repository CoRR [online serial]. 2019;abs/1904.04271.

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  • Niedermaier M, Merli D, Georg S. A Secure Dual-MCU Architecture for Robust Communication of IIoT Devices. Mediterranean Conference on Embedded Computing (MECO); IEEE. Epub 2019.

  • Niedermaier M, Striegel M, Sauer F, Merli D, Sigl G. Efficient Intrusion Detection on Low-Performance Industrial IoT Edge Node Devices. Computing Research Repository CoRR [online serial]. 2019;abs/1908.03964. 

  • Pfitzner C, May S, Nüchter A. Body Weight Estimation for Dose-Finding and Health Monitoring of Lying, Standing and Walking Patients Based on RGB-D Data. Sensors [online serial]. 2018;18.

  • Pfitzner C, May S, Nüchter A. Evaluation of Features from RGB-D Data for Human Body Weight Estimation. International Federation of Automatic Control [online]. Toulouse, France; 2017.

  • Reinker F, Wagner R, Hasselmann K, aus der Wiesche S, Fritsche M, et al. Testing, modeling and simulation of fans working with organic vapors. Proceedings of 13th European Conference on Turbomachinery Fluid dynamics & Thermodynamics [online]. 2019.

  • Ring M, Landes D, Dallmann A, Hotho A. IP2Vec: Learning Similarities Between IP Addresses. 2017 IEEE International Conference on Data Mining Workshops (ICDMW). 2017. p. 657–666.

  • Ring M, Landes D, Hotho A. Detection of slow port scans in flow-based network traffic. PLOS ONE [online serial]. Public Library of Science; 2018;13:1–18.

  • Ring M, Schlör D, Landes D, Hotho A. Flow-based Network Traffic Generation using Generative Adversarial Networks. Computing Research Repository CoRR [online serial]. 2018;abs/1810.07795.

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  • Zoppelt M, Kolagari RT. What Today’s Serious Cyber Attacks on Cars Tell Us: Consequences for Automotive Security and Dependability. In: Papadopoulos Y, Aslansefat K, Katsaros P, Bozzano M, editors. IMBSA [online]. Springer; 2019. p. 270–285.

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2018

Koordination

Treten Sie mit uns in Kontakt. Wir freuen uns auf Ihre Fragen und Anregungen zum Verbundkolleg Digitalisierung.

Dr. Karin Streker

Dr. Karin Streker

Koordinatorin BayWISS-Verbundkolleg Digitalisierung

Julius-Maximilians-Universität Würzburg
Graduate Schools of Science and Technology
Beatrice-Edgell-Weg 21
97074 Würzburg

Telefon: +49 931 3189695
digitalisierung.vk@baywiss.de