Ostwestfalen-Lippe University of Applied Sciences and Arts
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Personalisierung von Radio On-Demand: Potentiale, Nutzerakzeptanz und die Zukunft des Radios im Vergleich zum linearen Rundfunk
No full textAutomatic Creation of Assembly Instructions by Using Retrieval Augmented Generation
No full textThe application of Large Language Models (LLMs) for the automated generation of assembly instructions shows significant potential for improving work preparation in production processes. However, challenges remain regarding the overall information quality and precision of the generated instructions. In light of these challenges, this study explores how the information quality of automatically generated assembly instructions can be enhanced through the targeted provision of structured input data, such as Assembly and Quantity BOMs (Bills of Materials), as well as the use of optimized prompt chaining techniques. The methodology employs ChatGPT-4o in combination with Retrieval Augmented Generation (RAG) within the Microsoft Azure environment. The results demonstrate that structured data inputs, particularly the use of Assembly BOMs with defined Tool-to-Component relations, significantly improve the precision and relevance of the generated instructions. Despite these advancements, achieving consistent information quality remains a barrier to broader practical implementation. Therefore, feedback loops should be integrated into the assembly instruction generation process to ensure continuous refinement and reliability. Future research should investigate the use of RAG or similar frameworks, focusing on optimizing data structures and implementing feedback mechanisms to enhance the automated generation of assembly instructions
User-Centered Gamification in Manufacturing: A Systematic Literature Review
No full textProduction environments are characterized by an increasingly diverse workforce caused by demographic change, globalization, and the rising demand for inclusion and equality. To ensure employee satisfaction for such a diverse workforce, gamification is a promising method. However, one-size-fits-all approaches are not sufficient, and more user-adaptive and inclusive gamified systems are needed. Therefore, this systematic literature review aims to answer the question of which user-adaptive gamified systems exist for manufacturing and how they provide inclusivity for individuals in their everyday work. Following PRISMA guidelines, a search of five electronic databases retrieved 22 relevant articles. Analysis of the literature revealed a lack of user-centered and inclusive gamified systems. Further, limited empirical evaluations in real production environments, limited application scenarios, and the need for more diverse research were identified. Based on the results, this study identifies key research gaps and provides recommendations for future research
Anomaly detection and removal strategies for in-line permittivity sensor signal used in bioprocesses
No full textIntroduction: In-line sensors, which are crucial for real-time (bio-) process monitoring, can suffer from anomalies. These signal spikes and shifts compromise process control. Due to the dynamic and non-stationary nature of bioprocess signals, addressing these issues requires specialized preprocessing. However, existing anomaly detection methods often fail for real-time applications.
Methods: This study addresses a common yet critical issue: developing a robust and easy-to-implement algorithm for real-time anomaly detection and removal for in-line permittivity sensor measurement. Recombinant Pichia pastoris cultivations served as a case study. Trivial approaches, such as moving average filtering, do not adequately capture the complexity of the problem. However, our method provides a structured solution through three consecutive steps: 1) Signal preprocessing to reduce noise and eliminate context dependency; 2) Anomaly detection using threshold-based identification; 3) Validation and removal of identified anomalies.
Results and discussion: We demonstrate that our approach effectively detects and removes anomalies by compensating signal shift value, while remaining computationally efficient and practical for real-time use. It achieves an F1-score of 0.79 with a static threshold of 1.06 pF/cm and a double rolling aggregate transformer using window sizes w1 = 1 and w2 = 15. This flexible and scalable algorithm has the potential to bridge a crucial gap in process real-time analytics and control
Bild. Botschaft. Beziehung. Die Wirkung authentischer Brandfotografie in der Markenkommunikation.
No full textTanz – ein Film über die Quarterlife Crisis und Herausforderungen der Identitätssuche von Frauen mit Migrationshintergrund
No full textDer Film basiert auf Interviews mit zwei jungen Frauen mit Migrationshintergrund, die über ihre Erfahrungen in ihren Mittzwanzigern sprechen. Diese realen Stimmen bilden die Grundlage für die narrative und visuelle Umsetzung. Dabei wird untersucht, wie die Quarterlife Crisis speziell in dieser Gruppe wahrgenommen und erlebt wird, welche Rolle kulturelle und familiäre Erwartungen spielen und welche Strategien zur Bewältigung gefunden werden
Funktionalität von Proteinen in der Verarbeitung und Anwendung in Lebensmitteln – Besonderheiten von Hanfproteinen
No full textHuman Factors in Hypertext (HUMAN’25)
No full textHUMAN 2025 is the 8th workshop of a series for the ACM Hypertext conferences. The HUMAN workshop has a strong focus on the user and brings together user‑centered hypertext with artificial intelligence to build intelligent hypertext systems.
The user-centric view on hypertext not only includes user interfaces and interaction, but also discussions about hypertext application domains as well as human-centered AI. Furthermore, the workshop raises the question of how original hypertext ideas (e.g., Doug Engelbart’s “augmenting human intellect” [7] or Jeff Conklin’s “hypertext as a computer-based medium for thinking and communication” [6]) can improve today’s hypertext systems