@misc{13120, abstract = {{This paper introduces an approach that leverages large language models (LLMs) to convert detailed descriptions of an Operational Design Domain (ODD) into realistic, executable simulation scenarios for testing autonomous vehicles. The method combines model-based and data-driven techniques to decompose ODDs into three key components: environmental, scenery, and dynamic elements. It then applies prompt engineering to generate ScenarioRunner scripts compatible with CARLA. The model-based component guides the LLM using structured prompts and a “Tree of Thoughts” strategy to outline the scenario, while a data-driven refinement process, drawing inspiration from red teaming, enhances the accuracy and robustness of the generated scripts over time. Experimental results show that while static components, such as weather and road layouts, are well captured, dynamic elements like vehicle and pedestrian behavior require further refinement. Overall, this approach not only reduces the manual effort involved in creating simulation scenarios but also identifies key challenges and opportunities for advancing safer and more adaptive autonomous driving systems.}}, author = {{Danso, Aaron Agyapong and Büker, Ulrich}}, booktitle = {{Electronics}}, issn = {{2079-9292 }}, keywords = {{large language models, generation, Operational Design Domain, autonomous vehicles, simulation, CARLA, ScenarioRunner, prompt-engineering, fine-tuning}}, number = {{16}}, pages = {{3177}}, publisher = {{MDPI}}, title = {{{Automated Generation of Test Scenarios for Autonomous Driving Using LLMs}}}, doi = {{10.3390/electronics14163177}}, volume = {{14}}, year = {{2025}}, } @misc{13291, abstract = {{The 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.}}, author = {{Herbort, Robin and Green, Dominik and Hinrichsen, Sven}}, booktitle = {{Intelligent Human Systems Integration (IHSI 2025): Integrating People and Intelligent Systems}}, editor = {{Ahram, Tareq and Karwowski, Waldemar and Martino, Carlo and Di Bucchianico, Giuseppe and Maselli, Vincenzo }}, isbn = {{978-1-964867-36-6}}, issn = {{2771-0718}}, keywords = {{Assembly Instruction, Retrieval Augmented Generation (RAG), Large Language Model (LLM)}}, location = {{Rome, Italy}}, pages = {{765--775}}, publisher = {{AHFE }}, title = {{{Automatic Creation of Assembly Instructions by Using Retrieval Augmented Generation}}}, doi = {{10.54941/ahfe1005883}}, volume = {{160}}, year = {{2025}}, } @misc{13292, abstract = {{The 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.}}, author = {{Herbort, Robin and Green, Dominik and Hinrichsen, Sven}}, booktitle = {{Intelligent Human Systems Integration (IHSI 2025): Integrating People and Intelligent Systems}}, editor = {{Ahram, Tareq and Karwowski, Waldemar and Martino, Carlo and Di Bucchianico, Giuseppe and Maselli, Vincenzo}}, isbn = {{978-1-964867-36-6}}, issn = {{2771-0718}}, keywords = {{Retrieval Augmented Generation, Large Language Model, Assembly Instructions}}, location = {{Rome}}, publisher = {{AHFE}}, title = {{{Automatic Creation of Assembly Instructions by Using Retrieval Augmented Generation}}}, doi = {{10.54941/ahfe1005883}}, volume = {{160}}, year = {{2025}}, } @misc{13293, abstract = {{The performance of large language models (LLMs) has improved significantly in recent years, with the result that they are now used in many companies in various industries. However, the design of a company-specific information system involving an LLM is associated with a large number of decisions. This leads to a high level of complexity in the design task. Against this background, companies need a structured approach that methodically supports the planning, development, implementation and long-term maintenance of LLM-based information systems so that domain- and company-specific requirements are taken into account as a result. This article therefore describes a method that supports the design, introduction and maintenance process of an LLM-based information system. The method consists of a process model and a list of design principles, which are also referred to as success factors. The process model developed is based on the proven six-stage REFA planning system. To identify and describe success factors, a systematic literature search was carried out. Based on an analysis of the contents of individual literature sources, success factors for the design of LLM-based information systems were identified. These success factors relate, for example, to the quality of the data provided, data security, user-centered system design and feedback mechanisms for improving information output.}}, author = {{Hinrichsen, Sven and Herbort, Robin and Green, Dominik and Adrian, Benjamin}}, booktitle = {{Human Interaction and Emerging Technologies (IHIET 2025)}}, editor = {{Ahram, Tareq and Motschnig, Renate }}, isbn = {{978-1-964867-73-1}}, issn = {{2771-0718}}, keywords = {{Large language model, Information system, Retrieval augmented generation}}, location = {{Vienna}}, publisher = {{AHFE}}, title = {{{How to Design an Operation-Specific LLM-Based Information System}}}, doi = {{10.54941/ahfe1006709}}, volume = {{197}}, year = {{2025}}, } @misc{13294, abstract = {{Die Leistungsfähigkeit von Large Language Models konnte in den letzten Jahren deutlich verbessert werden, so dass viele Unternehmen solche Modelle bereits einsetzen oder ihren Einsatz planen. Die Gestaltung eines betriebsspezifischen Informationssystems unter Einbeziehung eines Large Language Model (LLM) ist allerdings mit einer Vielzahl an Entscheidungen verbunden. Vor diesem Hintergrund wird in diesem Beitrag eine Methode beschrieben, die bei der Gestaltung und Einführung eines LLM-basierten Informationssystems unterstützen kann, um im Ergebnis eine möglichst anforderungsgerechte Lösung zu entwickeln. Diese Methode besteht dabei aus einem Vorgehensmodell und einer Liste mit Gestaltungsprinzipien, die auch als Erfolgsfaktoren bezeichnet werden.}}, author = {{Hinrichsen, Sven and Herbort, Robin and Green, Dominik and Adrian, Benjamin}}, booktitle = {{Arbeit 5.0: Menschzentrierte Innovationen für die Zukunft der Arbeit}}, isbn = {{978-3-936804-36-2}}, keywords = {{Large Language Model, Informationssystem, Methode}}, location = {{Aachen}}, pages = {{642--647}}, publisher = {{GfA-Press}}, title = {{{Vorgehensmodell zur Entwicklung und Implementierung von LLM-basierten Informationssystemen}}}, year = {{2025}}, } @misc{13529, abstract = {{The proliferation of misinformation is one of the most pressing challenges in today’s digital landscape, due to its far-reaching implications for public health, economic stability, trust in governmental institutions, and societal cohesion. Despite efforts to regulate online platforms and limit the spread of misinformation, many individuals are left behind because of their low digital literacy, level of education, and other contributing factors. In this context, we explore the use of Large Language Models (LLMs) to identify misinformation and we evaluate the capabilities of GPT-4.1-mini, as a representative example of these models. We then discuss how LLMs can help empower users to critically create and share information, thereby fostering more resilient online communities. We also present a set of possible interaction patterns for content creation and moderation.}}, author = {{Franco, Mirko and Grimm, Valentin and Herder, Eelco}}, booktitle = {{Proceedings of the 2025 International Conference on Information Technology for Social Good}}, editor = {{Marquez-Barja, Johann and Bujari, Armir and Slamnik-Kriještorac, Nina and Sabbioni, Andrea}}, isbn = {{979-8-4007-2089-5}}, keywords = {{misinformation, fake news, large language models, online social networks}}, location = {{Antwerp, Belgium}}, pages = {{244 -- 252}}, publisher = {{ACM}}, title = {{{Preventing Accidental Sharing of Misinformation Using Large Language Models}}}, doi = {{10.1145/3748699.3749798}}, year = {{2025}}, } @misc{11330, abstract = {{With the increasing complexity in manual assembly and a demographic decline in skilled workforce, the importance of well-documented processes through assembly instructions has grown. Creating these instructions is a time-consuming and knowledge-intensive task that typically relies on experienced employees. Although various automation solutions have been proposed to assist in generating assembly instructions, they often fall short in providing detailed textual guidance. With the rise of generative artificial intelligence (AI), new potentials arise in this domain. Therefore, this paper explores these potentials by employing various large language models (LLMs), prompting techniques and input data in an experimental setup for generating detailed assembly instructions, including the planning of assembly sequences as well as textual guidance on tools, assembly activities, and quality assurance measures. The findings reveal promising opportunities in leveraging LLMs but also substantial challenges, particularly in assembly sequence planning. To improve the reliability of generating assembly instructions, we propose a multi-agent concept that decomposes the complex task into simpler subtasks, each managed by specialized agents.}}, author = {{Meyer, Frederic and Freitag, Lennart and Hinrichsen, Sven and Niggemann, Oliver}}, booktitle = {{2024 IEEE 29th International Conference on Emerging Technologies and Factory Automation (ETFA)}}, isbn = {{979-8-3503-6123-0}}, keywords = {{assembly instruction, GPT, large language model, LLM, prompt}}, location = {{Padova, Italy}}, publisher = {{IEEE}}, title = {{{Potentials of Large Language Models for Generating Assembly Instructions}}}, doi = {{https://doi.org/10.1109/ETFA61755.2024.10710806}}, volume = {{78}}, year = {{2024}}, } @misc{11607, abstract = {{Pasteurization of bottles and cans is an important technique for biological stabilization of beer as well as mixed beer drinks, malt beer and non-alcoholic beers. Despite recuperation, the heat requirement is very high and can be significantly reduced by lowering the maximum temperature in the pasteurizer. The current practice of calculating the lethal heat effect is based on the so-called beer formula using a globalized z-value for the temperature dependence of the inactivation. The premise experiments here is that for products containing sugar, such as malt beer, yeast cells pose the greatest danger. Therefore, the D values at various temperatures and the z values of three of the Krombacher Brewery's own yeasts (bottom-fermenting and top-fermenting) were determined in the laboratory using the capillary method. In a challenge test in the brewery, bottles with different products were inoculated with these yeasts and samples were taken from the industrial pasteurizer every two minutes and examined for viable cell counts. Accordingly, using specific D/z values, precise pasteurization can be achieved, the treatment temperature can be reduced to 55° C and 20-25% of energy can be saved.}}, author = {{Nolte, Jannik and Hense, Ludger and Weishaupt, Imke and Schneider, Jan}}, keywords = {{pasteurization, D value, z-value, heat energy savings, large scale trials, biological stability, yeast}}, location = {{Lille}}, title = {{{How do you turn a shotgun into a precision rifle - significant heat savings through the use of kinetic laboratory data (D/z values) in large-scale pasteurization}}}, year = {{2024}}, } @misc{12025, author = {{Liphardt, Daniel and Al Krad, Majed and Wilhelm, Patrick and Schwarzer, Knut and Müller, Ulrich}}, keywords = {{essential oil, scale up, steam distillation, oil losses}}, location = {{Lemgo}}, title = {{{Scale up-Probleme bei der schnellen Wasserdampfdestillation zur Gewinnung ätherischer Öle}}}, year = {{2024}}, } @misc{12026, author = {{Dehghanzadeh, Yasin and Liphardt, Daniel and Schwarzer, Knut and Wilhelm, Patrick and Müller, Ulrich}}, keywords = {{essential oil, scale up, steam distillation, yield, mint plants}}, location = {{Lemgo}}, title = {{{Prozessoptimierung der schnellen Wasserdampfdestillation zur Gewinnung ätherischer Öle}}}, year = {{2024}}, } @misc{12048, abstract = {{Interactive stories can be an effective approach for teaching purposes. One shortcoming is the effort necessary to author and create these stories, especially complex storylines with choices for the readers. Based on recent advances in Natural Language Processing (NLP), new opportunities arise for assistance systems in the context of interactive stories. In our work, we present an authoring approach and prototypical tool for the creation of visual comic-strip like interactive stories, a type of hypercomics, that integrate an Artificial Intelligence (AI) assistance. Such comics are already used in our Gekonnt hanDeln web platform. The AI assistance provides suggestions for the overall story outline as well as how to design and write individual story frames. We provide a detailed description about the approach and its prototypical implementation. Furthermore, we present a study evaluating the prototype with student groups and how the prototype evolved in an iterative style based on the students’ feedback.}}, author = {{Grimm, Valentin and Rubart, Jessica}}, booktitle = {{HT '24: Proceedings of the 35th ACM Conference on Hypertext and Social Media}}, isbn = {{979-8-4007-0595-3 }}, keywords = {{Storytelling, Authoring, GPT, Hypercomics, Large Language Models}}, location = {{Poznan, Poland}}, pages = {{88--97}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{Authoring Educational Hypercomics assisted by Large Language Models}}}, doi = {{10.1145/3648188.3675124}}, year = {{2024}}, } @inproceedings{585, abstract = {{Many low-cost 3D printers have been brought to market over the last couple of years. Most of them apply a Fused Layer Manufacturing (FLM) process, and have made 3D printing a great success amongst hobbyists, the maker community and students. One drawback of such inexpensive equipment is a limited build envelope, which prevents this from becoming a significant contributor to industrial production. To overcome these limits, it is not sufficient to simply upscale dimensions, but the overall concept of such machines must be completely re-thought, as well as the concepts behind several building blocks, components and the process software system. Problems such as shrinkage of build material, support material and machine parts in combination with long printer head travels, temperature distribution and moisture effects all have to be solved. In addition, larger parts need longer process times. Therefore, reduction of process times and an increase in productivity are necessary in order to enable economic production. Some of these problems can be solved by using more than one printer head for production, by using new materials and inventing new nozzle systems as distinct solutions for big printers. Nevertheless, to solve all these problems, the development of special machines for large parts is necessary: not component-wise but as a whole system. Large parts could then be successfully produced in several industries, using large, inexpensive FLMmachines. }}, author = {{Villmer, Franz-Josef and Witte, Lars}}, booktitle = {{Production Engineering and Management}}, editor = {{Padoano, Elio and Villmer, Franz-Josef}}, isbn = {{978-3-941645-11-0}}, keywords = {{3D printing, FLM, build envelope, large-scale, thermoplastic polymers}}, location = {{Trieste, Italy}}, number = {{1}}, pages = {{111--122}}, title = {{{Large Scale 3D-Printers: The Challenge of Outgrowing Do-It-Yourself}}}, year = {{2015}}, } @inbook{4388, abstract = {{Research in the field of smart home environments is still very much technology driven. While technical aspects like system reliability, performance or data security are undeniable important design factors, potential end users desire more than pure technical functionality favoring systems with high social and hedonic value. So far, the integration of digital information layers into the architectural environment and their consequences for human perception are still largely unexplored. In this paper we present three examples of interactive architecture for increased quality of life in domestic spaces: myGreenSpace, meetingMyEating and ubiGUI.}}, author = {{Röcker, Carsten and Kasugai, Kai}}, booktitle = {{Constructing Ambient Intelligence }}, editor = {{Wichert, Reiner and Van Laerhoven, Kristof and Gelissen, Jean}}, isbn = {{978-3-642-31478-0}}, keywords = {{Ambient Intelligence, Large Domestic Screens, Smart Spaces, Aesthetics, Design, Architecture}}, location = {{Amsterdam, Netherlands}}, pages = {{12--18}}, publisher = {{Springer}}, title = {{{Interactive Architecture in Domestic Spaces}}}, doi = {{10.1007/978-3-642-31479-7_3}}, volume = {{277}}, year = {{2012}}, } @inproceedings{4395, abstract = {{This paper presents the evaluation of a mixed reality communication system for the home domain, called roomXT. The system uses a wall-sized display that is seamlessly integrated into a living lab, to create a 'life-like' video communication experience. In order to demonstrate the potential of this approach, we conducted a living lab study comparing the developed prototype with a desktop-based system. A special video communication application, which enables spatially separated users to have a joint dinner experience, served as a common basis for the different test conditions. Results of the study show that the overall concept of roomXT was well eceived by users of a wide age range and that the developed prototype system seems to be preferred to commercially available video communication solutions with respect to the tested quality dimensions.}}, author = {{Kasugai, Kai and Heidrich, Felix and Röcker, Carsten and Russell, Peter and Ziefle, Martina}}, booktitle = {{Proceedings of the 2012 International Symposium on Pervasive Displays}}, editor = {{José, Rui}}, isbn = {{978-145-031-414-5 }}, keywords = {{human-computer interaction, mixed-reality, large displays, co-dining, interactive media, family communication, co-presence, architecture}}, location = {{Porto, Portugal }}, pages = {{1--6}}, publisher = {{ACM}}, title = {{{Perspective Views in Video Communication Systems: An Analysis of Fundamental User Requirements}}}, doi = {{10.1145/2307798.2307811}}, year = {{2012}}, } @inproceedings{4767, abstract = {{This paper presents a novel concept for personalized privacy support on large public displays. In a first step, a formative evaluation was conducted in order to analyze the requirements of potential users regarding the protection of private information on large public displays. The insights gained in this evaluation were used to design a system, which automatically adapts the information visible on public displays according to the current social situation and the individual privacy preferences of the user working on the display. The developed system was evaluated regarding its appropriateness for daily usage and its usefulness to protect privacy.}}, author = {{Röcker, Carsten and Hinske, Steve and Magerkurth, Carsten}}, booktitle = {{Universal Access in Human-Computer Interaction : Ambient Interaction}}, editor = {{Stephanidis, Constantine}}, isbn = {{978-3-540-73280-8}}, keywords = {{Large Public Displays, Intelligent Privacy Support, Smart Environments, Privacy-Enhancing Technologies, Context-Adapted Information Representation, Evaluation}}, pages = {{198--207}}, publisher = {{Springer}}, title = {{{Intelligent Privacy Support for Large Public Displays}}}, doi = {{10.1007/978-3-540-73281-5_21}}, volume = {{4555}}, year = {{2007}}, } @inproceedings{4818, abstract = {{In this paper we present a system that provides personalized privacy support for large public displays based on the current social situation and individual privacy profiles. We first present the results of a user study that was conducted to derive the requirements for the design of the system. In the second part of the paper, we describe the developed system consisting of a program for privacy-enhancing information management and a small personal artefact for an easy adaptation of the privacy settings to the local context. }}, author = {{Röcker, Carsten}}, booktitle = {{Privacy, Security, Trust 2005 : proceedings of Third Annual Conference on Privacy, Security and Trust}}, editor = {{Ghorbani, Ali A. and Marsh, Stephen }}, keywords = {{Large Public Displays, Active User Support, Privacy Enhancing information Managemen}}, location = {{St. Andrews, New Brunswick, Canada}}, pages = {{217--220}}, publisher = {{Privacy, Security and Trust}}, title = {{{Providing Personalized Privacy Support in Public Places}}}, year = {{2005}}, }