Running Theses
As universities strive to enhance the effectiveness of their lecture exercises, there arises a need for diverse and realistic test user scenarios to evaluate the understandability and usefulness of educational materials. However, in creating such scenarios a number of challenges arise: Real world students can rarely be used for testing, they are likely inexperienced or ...
Fine-tuning pre-trained large language models (LLMs) enhances biomedical text mining. This thesis introduces a tool capable of performing tasks such as Named Entity Recognition (NER), Normalization (NEN), and Knowledge Graph Construction (KGC). A key research question explores how LLMs can address the challenges of named entity recognition, normalization, and relation extraction in biomedical contexts.
Developing a Flexible Interface for Agent-Behaviors inMulti-Agent-System Simulations of Electrical Power Systems
Synopsis operators for a distributed on-the-edge streaming architecture
Detect Flames in industrial Video data using edge devices.
Validating the Reference Architecture Model of International Data Spaces Regarding Vocabulary Sharing Requirements From Life-Science Industry in the Context of Persistent Identifier Systems
