Publication

Buschmeier, H., et al. (2024). Multimodal Co-Construction of Explanations with XAI Workshop.

Title Buschmeier, H., Hassan, T., & Kopp, S. (2024, November). Multimodal Co-Construction of Explanations with XAI Workshop. In Proceedings of the 26th International Conference on Multimodal Interaction (pp. 698-699). Abstract The ICMI 2024 workshop on “Multimodal Co-Construction of Explanations with XAI” bridges the fields of Explainable Artificial Intelligence (XAI) and Multimodal Interaction, focusing on the recent perspective that effective AI explanations should be dynamically co-constructed through interactive, social processes involving both the explainer and the explainee.

Yavuz, S., et al. (2024). Development of a 2-4 double arbiter PUF design on FPGA with enhanced performance.

Title Yavuz, S. (2024). Development of a 2-4 double arbiter PUF design on FPGA with enhanced performance. Abstract Implementation of delay-based Physical Unclonable Functions (PUFs) on FPGAs poses significant challenges due to high requirements, such as the generation of unique and reliable keys. These requirements must be fulfilled, especially when using PUFs in security applications, otherwise security cannot be guaranteed. In addition, it must be ensured that physical disturbances such as fluctuations in the ambient temperature do not have a major impact on the performance of the PUF and therefore on security.

Yavuz, S., et al. (2024). Vulnerabilities and challenges in the development of PUF-based authentication protocols on FPGAs: A brief review.

Title Yavuz, S., Daniel, K., & Naroska, E. (2024). Vulnerabilities and challenges in the development of PUF-based authentication protocols on FPGAs: A brief review. Abstract The security of IoT (Internet of Things) devices and the protection of sensitive information processed by these devices such as personal data, sensor values, process-related information is an important and difficult challenge. A major task in IoT communication is secure identification of devices. Unfortunately, traditional cryptographic methods are often not suitable for IoT devices due to their limited hardware resources.

Stolarz, M., et al. (2024), Deep Learning-Based Adaptation of Robot Behaviour for Assistive Robotics.

Title Stolarz, M., Romeo, M., Mitrevski, A., & Plöger, P. G. (2024, August). Deep Learning-Based Adaptation of Robot Behaviour for Assistive Robotics. In 2024 33rd IEEE International Conference on Robot and Human Interactive Communication (ROMAN) (pp. 110-117). IEEE. Abstract Robot behaviour models in socially assistive robotics are typically trained using high-level features, such as a user’s engagement, such that inaccuracies in the feature extraction can have a significant effect on a robot’s subsequent performance.

Gjoreski, M., et al. (2024). XAI for U: Explainable AI for Ubiquitous, Pervasive and Wearable Computing.

Title Gjoreski, M., Hassan, T., Vered, M., Houben, S., & Kopp, S. (2024, October). XAI for U: Explainable AI for Ubiquitous, Pervasive and Wearable Computing. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 992-995). Abstract The workshop XAI for U aims to address the critical need for transparency in Artificial Intelligence (AI) systems that integrate into our daily lives through mobile systems, wearables, and smart environments.

Schneider, J., et al. (2024). Time for an Explanation: A Mini-Review of Explainable Physio-Behavioural Time-Series Classification.

Title Schneider, J., Cheruvalath, S. S., & Hassan, T. (2024, October). Time for an Explanation: A Mini-Review of Explainable Physio-Behavioural Time-Series Classification. In Companion of the 2024 on ACM International Joint Conference on Pervasive and Ubiquitous Computing (pp. 885-889). Abstract Time-series classification is seeing growing importance as device proliferation has lead to the collection of an abundance of sensor data. Although black-box models, whose internal workings are difficult to understand, are a common choice for this task, their use in safety-critical domains has raised calls for greater transparency.

Krause, A. F., Essig, K., Wild-Wall, N., Ressel, C. (2024), A proposal for the concept of Pro-adaptive Cognitive Assistive Technology. (Abstract HFES).

Title Krause, A. F., Essig, K., Wild-Wall, N., Ressel, C. (2024), A proposal for the concept of Pro-adaptive Cognitive Assistive Technology. Abstract, accepted at Human Factors and Ergonomics Societey Europe (HFES). Abstract Assistive Technology is becoming an integral part of our daily live, supporting people in different areas, for example while driving a car or cognitive demanding tasks at work or home. Yet, existing Assistive Technology often only considers the current situational context and capabilities of a user.

Wild-Wall et al., (2024), Strukturen zur Berücksichtigung ethischer Aspekte in der Entwicklung von digitalen assistiven Technologien für vulnerable Gruppen.

Title Nele Wild-Wall, Christian Ressel, Kyra Kannen, André Frank Krause, Sarah Büscher, Birgit Mosler und Barbara Arntz (2024), Strukturen zur Berücksichtigung ethischer Aspekte in der Entwicklung von digitalen assistiven Technologien für vulnerable Gruppen. (under review)

Ferger, A., et al. Workflows and Methods for Creating Structured Corpora of Multimodal Interaction. 14–15 September 2023, University of Mannheim, Germany, 73.

Title Ferger, A., Krause, A. F., & Pitsch, K. Workflows and Methods for Creating Structured Corpora of Multimodal Interaction. 14–15 September 2023, University of Mannheim, Germany, 73. Abstract Corpus analysis of computer mediated and/or multimodal interaction can draw on methods of written and spoken corpora, while also providing further information like gaze or walk annotations or sensor-based data like kinect or motion capture or robot log files. We propose a workflow leveraging the developments of both worlds while simultaneously focussing on standard formats and a sustainable way of research data management.