Hafner, Alina; Hammerschmidt, Teresa; Stolz, Katharina
Analyzing The Use of Ethical Theories Within AI Ethics Research: A Systematic Scoping Review
Wirtschaftsinformatik 2024
Würzburg, Deutschland
2024

Hafner, Alina;Oliver, Thomas M.;Paßberger, Benjamin B.;Gloor, Peter A.
Prototyping a mobile app which detects dogs’ emotions based on their body posture: a design science approach
Handbook of Social Computing
Edward Elgar Publishing
2024

Bhave, Aarya;Hafner, Alina;Bhave, Anushka;Gloor, Peter A.
Unsupervised Canine Emotion Recognition Using Momentum Contrast
Sensors
2024
24
22
7324

Sebastian Schmidt, Ludwig Stumpp, Diego Valverde, Stephan Günnemann
Deep Sensor Fusion with Constraint Safety Bounds for High Precision Localization
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
2024

Chen, Wen-Chun;Berrezueta-Guzman, Santiago;Wagner, Stefan
Task-Based Role-Playing VR Game for Supporting Intellectual Disability Therapies
2024

Xianrui Yin
Positive Tensor Network Simulations of the Driven-Dissipative Bose-Hubbard Model
Masterarbeit
2024

Berrezueta-Guzman, Jonnathan;Malache-Silva, Laura;Krusche, Stephan
ChatGPT-4 as a Tool for Reviewing Academic Books in Spanish
2023

Berrezueta-Guzman, Santiago;Bassner, Patrick;Wagner, Stefan;Krusche, Stephan
Code Collaborate: Dissecting Team Dynamics in First-Semester Programming Students
2024

Hanqi Huo
Transformations between fully connected and convolutional neural networks
Masterarbeit
2024

Benzin, Janik-Vasily;Rinderle-Ma, Stefanie
Collaboration Miner: Discovering Collaboration Petri Nets (Extended Version)
Most existing process discovery techniques aim to mine models of process orchestrations that represent behavior of cases within one business process. Collaboration process discovery techniques mine models of collaboration processes that represent behavior of collaborating cases within multiple process orchestrations that interact via collaboration concepts such as organizations, agents, and services. While workflow nets are mostly mined for process orchestrations, a standard model for collaboration processes is missing. Hence, in this work, we rely on the newly proposed collaboration Petri nets and show that in combination with the newly proposed Collaboration Miner (CM), the resulting representational bias is lower than for existing models. Moreover, CM can discover heterogeneous collaboration concepts and types such as resource sharing and message exchange, resulting in fitting and precise collaboration Petri nets. The evaluation shows that CM achieves its design goals: no assumptions on concepts and types as well as fitting and precise models, based on 26 artificial and real-world event logs from literature.
2024