Completed Theses
Thesis Type
Master
Student: Sebastian Miller
Status
In Progress
Background
Supervisory control and data acquisition (SCADA) systems are increasingly connected through information and communication technologies, exposing smart grids to cyberattacks and operational disruptions. Conventional signature-based intrusion detection systems (IDSs) reliably identify known attacks but cannot detect previously unseen patterns, while statistical and machine-learning-based IDSs may achieve high detection rates but often ...
Federated Machine Learning Architecture for an MDF Production Industry Use Case
Data-driven quality assurance in grinding manufacturing technology
While recent advancements in natural language processing have been largely driven by increasingly powerful large language models (LLMs), the role of data quality in fine-tuning these models remains underexplored. This thesis addresses the often-overlooked but critical aspect of data-centric AI by investigating how different types and levels of data degradation affect the performance of fine-tuned ...
Technical support is an essential aspect of various industries, e.g., to provide help with maintaining machinery and IT systems. However, diagnosing error messages and faults in complex technologies can be a time-consuming and challenging task. The maintainer has to search through the long documentation booklets for the technology in order to find a solution or ...
The innovative integration of Mixed Reality and Large Language Models can lead to highly interactive instructional MR agents. Utilized as automated instructors, these MR agents have the potential to significantly enhance traditional instruction manuals by providing visual guidance. For instance, they can illustrate the next required actions in practical tasks such as tightening screws in ...
The goal of this thesis is to design, implement, and evaluate a sensor-based maintenance bot that uses Large Language Models (LLMs) to support predictive maintenance and decision-making. The bot should be capable of retrieving, analyzing, and reasoning over time series sensor data as well as unstructured maintenance-related documentation (e.g., technical manuals, incident reports). The result ...
The goal of this thesis is to investigate and define stakeholder engagement and involvement within the lifecycle of sensor-based MLOps. While MLOps principles streamline the deployment and maintenance of machine learning (ML) models, ensuring proper stakeholder involvement remains a challenge. Different stakeholders must collaborate effectively across various lifecycle stages to ensure model reliability, fairness, and ...
The proliferation of misinformation and fake news on social media platforms poses a significant challenge in today’s digital age. Traditional automated fake news detection systems often struggle with the complexity of the task, lacking the ability to provide detailed explanations and interpret nuanced contextual information.
This thesis explores the enhancement of fake news detection using Multi-Agent ...
Das Ziel dieser Bachelorarbeit “OGRETA – Ontologie-gestützter Rahmen für das Entwicklungstracking von Arbeitskompetenzen” ist die Überführung des GRETA-Kompetenzmodells in eine Ontologie, die als Grundlage für ein Empfehlungssystem dienen kann. Das GRETA-Modell definiert die beruflichen Kompetenzen von Lehrkräften in der Erwachsenenbildung unabhängig von Fachgebiet, Erfahrung oder Beschäftigungsart. Durch die Strukturierung dieses Modells als Ontologie soll die ...
Sensor data is often unstructured and while available datasets show some clear use cases, for example calculating energy consumption over time, relationships between measurements can often go unnoticed without a thorough examination of the data. While exploratory data analysis can reveal connections, without a clear analytical direction the results may be limited to general information, ...
The aim of this thesis is to design, implement, and evaluate a machine learning-based system for detecting chatter in thin-walled workpieces during machining processes. By leveraging MLOps principles, the system will automate the data pipeline from sensor data acquisition to model deployment, ensuring a scalable and efficient workflow. Additionally, the integration of the system within ...
Researching the potential for custom query functions for SPARQL with WebAssembly.
The aim of this bachelor thesis is to design, implement, and evaluate a blockchain-based escrow mechanism to support secure and transparent payment handling for data challenges in the Blockchain4DataMarketPlace. The proposed system will automate fund management, support dispute resolution processes, and provide transparent documentation of transactions, ensuring fairness and trust between Data Owners and Data ...
Development of a hybrid Intrusion Detection System for EV Charging Stations
Conveying information in a tour traditionally either requires a real human or an audio recording. However, the human guide might not always be available and the quality in the tours varies. With audio recordings, extra care has to be taken to convey to the user which element is currently being talked about since there are ...
Learning content by heart can be facilitated by the method of Loci. In this mnemonic technique, the learner converts pieces of information into mental imagery. The imagined representations are then anchored in a location. If the learner then traverses a path through this location, the information can be remembered by recalling the mental imagery. However, ...
The emergence of large language models (LLMs), along with recent advances in mixed reality (MR) and virtual reality (VR), enable new opportunities for applying virtual agents in education. These simulated humans can imitate real-life situations and interactions with native speakers, which leads to an immersive and engaging learning experience. Especially in VR, interactions can be ...
Large Language Models (LLM) can be applied to transform a natural language (NL)-based text input query into a NL-based text answer. A common use case are personal assistants, e.g., for learning activities. In such teaching contexts they can process knowledge recorded in plain text documents, create summarizations, or teach knowledge according to a curriculum. However, ...
The aim of this thesis is to evaluate and extend a developing ontology of explainable data principles, an ongoing work aimed at establishing a structured framework for Data Explainability in AI systems. The current version of this ontology is in its early stages, primarily focused on defining key principles of Data Explainability and exploring their ...
The aim of this thesis is to extend the existing latency analysis of a psychomotor feedback engine within our existing MLOps pipeline . Building upon preliminary latency estimations, this thesis will focus on systematically evaluating each processing step in the pipeline, assessing both theoretical and practical contributions to the overall latency and throughput. By ...
This master’s thesis builds on the Psychomotor Feedback Engine (PFE) and the IMPECT framework , aiming to improve the graphical user interface that teachers use to implement rules and feedback elements in psychomotor learning.
This thesis aims to address those usability issues by redesigning the teacher interface and integrating the IMPECT framework to ...
Leveraging LLMs for Mathematical Optimization on the Example of Supply Chains
