Institut für Wirtschaftsinformatik

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  • Publikation
    Peer instruction as teaching method in cybersecurity and data privacy
    (International School for Social and Business Studies, 2023) Schneider, Bettina; Asprion, Petra [in: International Journal of Management, Knowledge and Learning]
    Cybersecurity and data privacy are important fields today. Basic education in these two interconnected areas should already be offered in schools, as practically everyone today can encounter the dangers and risks of the Internet in terms of data theft, data manipulation or the like. However, the topics of cybersecurity and data privacy are generally abstract, and many people are not interested in such rather technical topics. To arouse interest and provide a certain basic education, we used ‘peer instruction’ combined with storytelling as a promising method. Within the framework of an EU project called GEIGER and with the support of students who have learned data privacy by means of the presented method, the method has been further developed, applied, tested, reflected, and iteratively improved. In summary, the method presented is useful for the topics of cybersecurity and data privacy, but the recommendations compiled must be considered in particular with regard to careful preparation and testing.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    Innovating the digital product development toolchain with digital twins at Helbling Technik AG
    (SAGE, 2023) Bettega, Kateryna; Düggelin, Wilhelm; Ehrenthal, Joachim; Ulrich, Philipp [in: Journal of Information Technology Teaching Cases]
    This teaching case examines how engineering consultants Helbling Technik AG overcame challenges in implementing a digital twin approach to mechatronics product development, saving costs, and reducing time to market. It challenges students to understand digital twins in mechatronic system development and their implications for processes, use cases, and service models. This real-world example is relevant for students and educators interested in the challenges and opportunities of digital twin implementation.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    Comparison of the behavior of swarm robots with their computer simulations applying target-searching algorithms
    (Engineering and Technology, 2018) Zhong, Jia; Dornberger, Rolf; Hanne, Thomas [in: International Journal of Mechanical Engineering and Robotics Research]
    This paper investigates the functionality and quality of the implementation of a search and target surrounding swarm robotic algorithm using physical swarm robots named Kilobots. The implementation was developed and tested in the simulator V-REP, then transferred onto the actually running Kilobots: Ten Kilobots were used for the experiment, where one Kilobot acts as the target and nine Kilobots act as the searchers. The algorithm allows the searchers to swarm out to find the target while avoiding collisions with other searchers, to orbit around other searchers, which are closer to the target, and finally to surround the target once it is found. The results of the implementation using the physical Kilobots are compared with the results of two adjusted computer simulations. Differences between the simulations and the real robot implementation are investigated: Discrepancies regarding the locomotion and the communication capabilities are identified and discussed.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    A comparative study of pattern recognition algorithms for predicting the inpatient mortality risk using routine laboratory measurements
    (Springer, 2018) Schütz, Narayan; Leichtle, Alexander Benedikt; Riesen, Kaspar [in: Artificial Intelligence Review]
    Laboratory tests are a common and relatively cheap way to assess the general health status of patients. Various publications showed the potential of laboratory measurements for predicting inpatient mortality using statistical methodologies. However, these efforts are basically limited to the use of logistic regression models. In the present paper we use anonymized data from about 40,000 inpatient admissions to the Inselspital in Bern (Switzerland) to evaluate the potential of powerful pattern recognition algorithms employed for this particular risk prediction. In addition to the age and sex of the inpatients, a set of 33 laboratory measurements, frequently available at the Inselspital, are used as basic variables. In a large empirical evaluation we demonstrate that recent pattern recognition algorithms (such as random forests, gradient boosted trees or neural networks) outperform the more traditional approaches based on logistic regression. Moreover, we show how the predictions of the pattern recognition algorithms, which cannot be directly interpreted in general, can be calibrated to output a meaningful probabilistic risk score.
    01A - Beitrag in wissenschaftlicher Zeitschrift
  • Publikation
    Off-line signature verification using elementary combinations of directional codes from boundary pixels
    (Springer, 2021) Ajij, Md; Pratihar, Sanjoy; Nayak, Soumya Ranjan; Hanne, Thomas; Roy, Diptendu Sinha [in: Neural Computing and Applications]
    01A - Beitrag in wissenschaftlicher Zeitschrift