@inproceedings{Meister2018, author = {Meister, Vera G.}, title = {Competency Acquisition in Applied Knowledge Engineering An Approach based on Learning from Errors}, series = {Proceedings of the 2018 International Conference on Education Science and Social Development (ESSD 2018), Shanghai, China, in July 21-22, 2018}, booktitle = {Proceedings of the 2018 International Conference on Education Science and Social Development (ESSD 2018), Shanghai, China, in July 21-22, 2018}, publisher = {Atlantis Press}, isbn = {978-94-6252-556-6}, doi = {10.2991/essd-18.2018.53}, year = {2018}, language = {en} } @inproceedings{MoellmannRegehlyVollmer2019, author = {M{\"o}llmann, Klaus-Peter and Regehly, Martin and Vollmer, Michael}, title = {Studying the transition from light emitting diodes to semiconductor lasers in applied physics laboratories}, series = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019 21-24 May 2019}, booktitle = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019 21-24 May 2019}, address = {Quebec City, Quebec, Canada}, doi = {10.1117/12.2523387}, pages = {1114312-1 -- 1114312-9}, year = {2019}, language = {en} } @inproceedings{VollmerShaw2019, author = {Vollmer, Michael and Shaw, Joseph A.}, title = {Near infrared photography of atmospheric optical phenomena}, series = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019}, booktitle = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019}, address = {Quebec City, Quebec, Canada}, doi = {10.1117/12.2523165}, pages = {111431P-1 -- 111431P-6}, year = {2019}, language = {en} } @inproceedings{VollmerShaw2019, author = {Vollmer, Michael and Shaw, Joseph A.}, title = {Extended visual range: an observation during a total solar eclipse}, series = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019}, booktitle = {Fifteenth Conference on Education and Training in Optics and Photonics: ETOP 2019}, address = {Quebec City, Quebec, Canada}, doi = {10.1117/12.2523167}, pages = {111431Q-1 -- 111431Q-6}, year = {2019}, language = {en} } @inproceedings{CreutzburgMcCallumKimetal.2018, author = {Creutzburg, Reiner and McCallum, Simon and Kim, Stefan and van R{\"u}schen, Raoul}, title = {Volumetric Terrain Rendering with WebGL}, series = {Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications, 28. Januar bis 1. Februar 2018, Burlingame, Kalifornien, USA}, booktitle = {Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications, 28. Januar bis 1. Februar 2018, Burlingame, Kalifornien, USA}, publisher = {Society for Imaging Science and Technology}, address = {Kilworth Lane / Springfield, Virginia, USA}, issn = {2470-1173}, doi = {10.2352/issn.2470-1173.2018.06.mobmu-136}, pages = {136-1 -- 136-14}, year = {2018}, language = {en} } @inproceedings{TetzlaffPurohitSpalleketal.2023, author = {Tetzlaff, Laura and Purohit, Anne-Maria and Spallek, Jacob and Holmberg, Christine and Schrader, Thomas}, title = {Evaluating Interoperability in German Critical Incident Reporting Systems}, series = {German Medical Data Sciences 2023 - Science. Close to People. Proceedings of the 68th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2023, Heilbronn, Germany}, booktitle = {German Medical Data Sciences 2023 - Science. Close to People. Proceedings of the 68th Annual Meeting of the German Association of Medical Informatics, Biometry, and Epidemiology e.V. (gmds) 2023, Heilbronn, Germany}, publisher = {IOS Press}, doi = {10.3233/SHTI230722}, pages = {249 -- 257}, year = {2023}, abstract = {In industrialised countries, one in ten patients suffers harm during hospitalization. Critical Incident Reporting Systems (CIRS) aim to minimize this by learning from errors and identifying potential risks. However, a lack of interoperability among the 16 CIRS in Germany hampers their effectiveness.}, language = {en} } @inproceedings{PepeBuchholzLasenby2024, author = {Pepe, Alberto and Buchholz, Sven and Lasenby, Joan}, title = {Clifford Group Equivariant Neural Network Layers for Protein Structure Prediction}, series = {Northern Lights Deep Learning Conference, VOL 233, 09-11 Januar 2024, Tromso, Norwegen}, booktitle = {Northern Lights Deep Learning Conference, VOL 233, 09-11 Januar 2024, Tromso, Norwegen}, publisher = {PMLR}, pages = {1 -- 7}, year = {2024}, abstract = {We employ Clifford Group Equivariant Neural Network (CGENN) layers to predict protein coordinates in a Protein Structure Prediction (PSP) pipeline. PSP is the estimation of the 3D structure of a protein, generally through deep learning architectures. Information about the geometry of the protein chain has been proven to be crucial for accurate predictions of 3D structures. However, this information is usually flattened as machine learning features that are not representative of the geometric nature of the problem. Leveraging recent advances in geometric deep learning, we redesign the 3D projector part of a PSP architecture with the addition of CGENN layers . CGENNs can achieve better generalization and robustness when dealing with data that show rotational or translational invariance such as protein coordinates, which are independent of the chosen reference frame. CGENNs inputs, outputs, weights and biases are objects in the Geometric Algebra of 3D Euclidean space, i.e. G3,0,0, and hence are interpretable from a geometrical perspective. We test 6 approaches to PSP and show that CGENN layers increase the accuracy in term of GDT scores by up to 2.1\\%, with fewer trainable parameters compared to linear layers and give a clear geometric interpretation of their outputs.}, language = {en} } @inproceedings{MarkgrafDietrichMuelleretal.2023, author = {Markgraf, Klaus and Dietrich, Benjamin and M{\"u}ller, Katja and Flassig, Robert and Flassig, Peter}, title = {FINEconcepts - Wissenstransfer und Energiesystemoptimierung mithilfe des digitalen Zwillings}, series = {NWK, HS Harz, 2023}, booktitle = {NWK, HS Harz, 2023}, publisher = {HS Harz}, pages = {428 -- 435}, year = {2023}, abstract = {Climate change, but also geopolitical circumstances, are moving topics such as energy efficiency and renewable energies more and more into the focus of the population, economy , and politics. As a result, the will to optimize new and existing energy systems extends from private individuals to companies and even entire communities. This work describes the development and usage of a new software called FINEconcepts which creates a digital twin of an energy system. This virtual model can then be used to optimize the energy system based on annual costs, CO2 emissions or other relevant criteria such as self-sufficiency. Because all system components, which include renewable technologies as well, can be added as a building block with chosen but changeable parameters, the software allows the user to explore and awaken interest and understanding of technologies that were previously considered too costly, irrelevant, or unrealistic. Implemented projects in small and large companies as well as in residential areas did prove, that the usage of FINEconcepts leads not only to more efficient energy systems by increasing the use of renewable energy, but also increased knowledge and understanding in terms of energy. Besides economics, ecology and security, understanding is an equally important factor in achieving a sustainable energy supply.}, language = {en} } @inproceedings{OrlowskiKnauffMarquardt2025, author = {Orlowski, Maximilian and Knauff, Emilia and Marquardt, Florian}, title = {Towards Personal Assistants for Energy Processes Based on Locally Deployed LLMs}, series = {Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) , 2025, Porto, Portugal}, booktitle = {Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) , 2025, Porto, Portugal}, publisher = {SCITEPRESS}, doi = {10.5220/0013175600003890}, pages = {695 -- 706}, year = {2025}, abstract = {This paper presents a coaching assistant for network operator processes based on a Retrieval-Augmented Gen- eration (RAG) system leveraging open-source Large Language Models (LLMs) as well as Embedding Models. The system addresses challenges in employee onboarding and training, particularly in the context of increased customer contact due to more complex and extensive processes. Our approach incorporates domain-specific knowledge bases to generate precise, context-aware recommendations while mitigating LLM hallucination. We introduce our systems architecture to run all components on-premise in an our own datacenter, ensuring data security and process knowledge control. We also describe requirements for underlying knowledge doc- uments and their impact on assistant answer quality. Our system aims to improve onboarding accuracy and speed while reducing senior employee workload. The results of our study show that realizing a coaching assistant for German network operators is reasonable, when addressing performance, correctness, integration and locality. However current results regarding accu- racy do not yet meet the requirements for productive use.}, language = {en} } @inproceedings{HildebrandtLamshoeftDittmannetal.2020, author = {Hildebrandt, Mario and Lamsh{\"o}ft, Kevin and Dittmann, Jana and Neubert, Tom and Vielhauer, Claus}, title = {Information Hiding in Industrial Control Systems: An OPC UA based Supply Chain Attack and its Detection}, series = {Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security (IH\&MMSec'20), June 22-24, 2020, Denver, CO, USA}, booktitle = {Proceedings of the 2020 ACM Workshop on Information Hiding and Multimedia Security (IH\&MMSec'20), June 22-24, 2020, Denver, CO, USA}, publisher = {The Association for Computing Machinery}, address = {New York}, doi = {10.1145/3369412}, pages = {115 -- 120}, year = {2020}, language = {en} } @inproceedings{KantJohannsen2022, author = {Kant, Daniel and Johannsen, Andreas}, title = {Evaluation of AI-based use cases for enhancing the cyber secu- rity defense of small and medium-sized companies (SMEs)}, series = {Proc. IS \& T International Symposium on Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications}, booktitle = {Proc. IS \& T International Symposium on Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications}, address = {Springfield, VA}, doi = {10.2352/EI.2022.34.3.MOBMU-387}, pages = {387-1 -- 387-8}, year = {2022}, language = {en} } @inproceedings{WagnerKitzelmannBoersch2025, author = {Wagner, Robin and Kitzelmann, Emanuel and Boersch, Ingo}, title = {Mitigating Hallucination by Integrating Knowledge Graphs into LLM Inference - a Systematic Literature Review}, series = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)}, booktitle = {Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)}, publisher = {Association for Computational Linguistics}, address = {Vienna}, doi = {10.18653/v1/2025.acl-srw.53}, pages = {795 -- 805}, year = {2025}, abstract = {Large Language Models (LLMs) demonstrate strong performance on different language tasks, but tend to hallucinate - generate plausible but factually incorrect outputs. Recently, several approaches to integrate Knowledge Graphs (KGs) into LLM inference were published to reduce hallucinations. This paper presents a systematic literature review (SLR) of such approaches. Following established SLR methodology, we identified relevant work by systematically search in different academic online libraries and applying a selection process. Nine publications were chosen for indepth analysis. Our synthesis reveals differences and similarities of how the KG is accessed, traversed, and how the context is finally assembled. KG integration can significantly improve LLM performance on benchmark datasets and additionally to mitigate hallucination enhance reasoning capabilities, explainability, and access to domain-specific knowledge. We also point out current limitations and outline directions for future work.}, language = {en} } @inproceedings{CraigFitzMiller2025, author = {Craig, Kevin and Fitz, Lukas R. G. and Miller, Kasey}, title = {IT Identity fostering User Innovation on Digital Platforms: The Role of Self-Esteem}, series = {AMCIS 2025, 31st Americas Conference on Information Systems, Montr{\´e}al, Canada, 2025}, booktitle = {AMCIS 2025, 31st Americas Conference on Information Systems, Montr{\´e}al, Canada, 2025}, publisher = {Association for Information Systems}, pages = {1 -- 9}, year = {2025}, abstract = {Digital platforms can grow by motivating users to explore new ways to use a wider range of affiliated products and services. This work explores the power of IT Identity to motivate such innovative use, through identity's ability to intrinsically motivate behavior. Data from 209 Amazon.com users indicates that IT Identity may cause Trying to Innovate with an IT, mediated by Self-Esteem.}, language = {en} } @inproceedings{VielhauerLoewePilgermann2025, author = {Vielhauer, Claus and Loewe, Fabian and Pilgermann, Michael}, title = {Towards Modeling Hidden \& Steganographic Malware Communication based on Images}, series = {IH\&MMSEC '25: ACM Workshop on Information Hiding and Multimedia Security, San Jose, CA, USA, 2025}, booktitle = {IH\&MMSEC '25: ACM Workshop on Information Hiding and Multimedia Security, San Jose, CA, USA, 2025}, doi = {10.1145/3733102.3733152}, pages = {52 -- 63}, year = {2025}, abstract = {Recently, an increasing number of IT security incidents involving malware, which makes use of hidden and steganographic channels for malicious communication (a.k.a. as "stegomalware"), can be observed in the wild. Especially the use of images to hide malicious code is rising. In consideration of this shift, a new model is proposed in this paper, which aims to help security professionals to identify and analyze incidents revolving around steganographic malware in the future. The model focuses on practical aspects of steganalysis of communication data to elaborate linking properties to previous code analysis knowledge. The model features two distinct roles that interact with a knowledge base which stores malware features and helps building a context for the incident. For evaluation, two image steganography malware types are chosen from popular databases (malpedia and MITRE ATT\&CK®), which are analyzed in multiple steps including steganalysis and code analysis. It is conceptually shown, how the extracted features can be stored in a knowledge base for later use to identify stegomalware from communication data without the need of a thorough code analysis. This allows to uncover previously hidden meta-information about the examined malicious programs, enrich the incident's forensic context traces and thus allows for thorough forensic insights, including attribution and improved preventive security measures in the future.}, language = {en} } @inproceedings{PepeLasenbyBuchholz2024, author = {Pepe, Alberto and Lasenby, Joan and Buchholz, Sven}, title = {CGAPoseNet+GCAN: A Geometric Clifford Algebra Network for Geometry-aware Camera Pose Regression}, series = {Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, US, 2024}, booktitle = {Winter Conference on Applications of Computer Vision, Waikoloa, Hawaii, US, 2024}, publisher = {IEEE}, doi = {10.1109/WACV57701.2024.00646}, pages = {6593 -- 6603}, year = {2024}, abstract = {We introduce CGAPoseNet+ GCAN, which enhances CGAPoseNet, an architecture for camera pose regression, with a Geometric Clifford Algebra Network (GCAN). With the addition of the GCAN we obtain a geometry-aware pipeline for camera pose regression from RGB images only. CGAPoseNet employs Clifford Geometric Algebra to unify quaternions and translation vectors into a single mathematical object, the motor, which can be used to uniquely describe camera poses. CGAPoseNet solves the issue of balancing rotation and translation components in the loss function, and can obtain comparable results to other approaches without the need of expensive tuning of the loss function or additional information about the scene, such as 3D point clouds, which might not always be available. CGAPoseNet, however, like several approaches in the literature, only learns to predict motor coefficients, and it is unaware of the mathematical space in which predictions sit in and of their geometrical meaning. By leveraging recent advances in Geometric Deep Learning, we modify CGAPoseNet with a GCAN: proposals of possible motor coefficients associated with a camera frame are obtained from the InceptionV3 backbone, and the GCAN downsamples them to a single motor through a sequence of layers that work in G_ 4, 0. The network is hence geometry-aware, has multivector-valued inputs, weights and biases and preserves the grade of the objects that it receives in input. CGAPoseNet+ GCAN has almost 4 million fewer trainable parameters, it reduces the average rotation error by 41\% and the average translation error by 8.8\% compared to CGAPoseNet. Similarly, it reduces rotation and translation errors by 32.6\% and 19.9\%, respectively, compared to the best performing PoseNet strategy. CGAPoseNet+ GCAN reaches the state-of-the-art results on 13 commonly employed datasets. To the best of our knowledge, it is the first experiment in GCANs applied to the problem of camera pose regression.}, language = {en} } @inproceedings{PepeLasenbyBuchholz2024, author = {Pepe, Alberto and Lasenby, Joan and Buchholz, Sven}, title = {GA-ReLU: an activation function for Geometric Algebra Networks applied to 2D Navier-Stokes PDEs}, series = {ICLR 2024 Workshop on AI4DifferentialEquations In Science, Wien, {\"O}sterreich}, booktitle = {ICLR 2024 Workshop on AI4DifferentialEquations In Science, Wien, {\"O}sterreich}, pages = {1 -- 6}, year = {2024}, abstract = {Many differential equations describing physical phenomena are intrinsically geometric in nature. It has been demonstrated how this geometric structure of data can be captured effectively through networks sitting in Geometric Algebra (GA) that work with multivectors, making them suitable candidates to solve differential equations. GA networks however, are still mostly uncharted territory. In this paper we focus on non-linearities, since applying them to multivectors is not a trivial task: they are generally applied in a point-wise fashion over each real-valued component of a multivector. This approach discards interactions between different elements of the multivector input and compromises the geometric nature of GA networks. To bridge this gap, we propose GA-ReLU, a GA approach to the rectified linear unit (ReLU), and show how it can improve the solution of Navier-Stokes PDEs.}, language = {en} } @inproceedings{TranconyWidemannLepper2024, author = {Tranc{\´o}n y Widemann, Baltasar and Lepper, Markus}, title = {Imagine There's No Source Code: Replay Diagnostic Location Information in Dynamic EDSL Meta-programming}, series = {MPLR 2024: Proceedings of the 21st ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes}, booktitle = {MPLR 2024: Proceedings of the 21st ACM SIGPLAN International Conference on Managed Programming Languages and Runtimes}, editor = {Ertl, M. Anton and Kirsch, Christoph M.}, publisher = {ACM}, address = {New York}, doi = {10.1145/3679007.3685061}, pages = {1 -- 11}, year = {2024}, abstract = {Programs in embedded domain-specific languages are realized as graphs of objects of the host language rather than as static input texts. This property enables dynamic meta-programming, but also makes it harder to attach location information to diagnostic messages that arise at a later stage, after the program graph construction. Thus, EDSL-generating expressions and algorithms can be difficult to debug. Here, we present a technique for transparently capturing and replaying location information about the origin of EDSL program objects. It has been implemented in the context of the LLJava-live EDSL-to-bytecode compiler framework on the JVM. The basic idea can be generalized to other contexts, and to any managed runtime environment with reified stack traces}, language = {en} } @inproceedings{DoudkinKindsmueller2024, author = {Doudkin, Alexander and Kindsm{\"u}ller, Martin Christof}, title = {Do not touch! - An artistic climate data visualization using motion capturing and 3D computer graphics}, series = {Mensch und Computer 2024 - Workshopband, Gesellschaft f{\"u}r Informatik e.V., 01.-04. September 2024, Karlsruhe, German}, booktitle = {Mensch und Computer 2024 - Workshopband, Gesellschaft f{\"u}r Informatik e.V., 01.-04. September 2024, Karlsruhe, German}, publisher = {Gesellschaft f{\"u}r Informatik e.V.}, address = {Karlsruhe}, doi = {10.18420/muc2024-mci-demo-319}, pages = {1 -- 3}, year = {2024}, abstract = {This demo explores an innovative artistic installation that creatively visualizes global temperature data using graphical visualization and motion capture technologies. By combining video-based posture capturing of nearby individuals with a dynamically rendered 3D model of the planet Earth, this installation offers an interactive and immersive experience. The goal is to transform climate change data into an engaging visual format, making it more accessible and impactful for a wide range of audiences.}, language = {en} } @inproceedings{RichterWrobel2023, author = {Richter, Nancy and Wrobel, Martin}, title = {The Impact of prototyping on the survival chances of digital early-stage startups: Findings and insights from explorative expert interviews}, series = {Proceedings of the 18th European Conference on Innovation and Entrepreneurship, ECIE 2023}, volume = {18}, booktitle = {Proceedings of the 18th European Conference on Innovation and Entrepreneurship, ECIE 2023}, number = {2}, publisher = {Academic Conferences International Limited}, doi = {10.34190/ecie.18.2.1714}, pages = {772 -- 779}, year = {2023}, abstract = {The products of digital entrepreneurs are highly innovative, and their business models contribute to the prosperity and further development of the economy and society. However, studies indicate that most of all startups fail, particularly during the early stages of their business journey Prototyping as part of Lean Startup or Business Model Testing approaches, can assist digital early-stage startups in navigating uncertainty and achieving successful product launches. However, these methods are applied very individually and there is little empirical research on best practices. We therefore conducted 65 explorative expert interviews and asked successful startups about their prototyping practices. Our results include learnings on the prototyping process and the testing format, the role of the founding team during prototyping practices, the customer focus and the role of networks. Our study adds important details to theory and practice of the innovation and prototyping processes of digital early-stage startups. Our results offer actionable advice and guidance to any current and potential entrepreneur, but especially to first-time founders and less experienced executives in early stage-startups. Additionally, our contribution enhances the theoretical understanding of the Lean Startup approach and prototyping practices.}, language = {en} } @inproceedings{FroschLindauerWinkel2025, author = {Frosch, Katharina and Lindauer, Friederike and Winkel, Carmen}, title = {Is Learning with an AI-Powered Chatbot for Everyone? A First Look at How Learning Preferences May Influence Learning Outcomes}, series = {Ubiquity Proceedings}, volume = {6}, booktitle = {Ubiquity Proceedings}, number = {1}, publisher = {ubiquity press}, doi = {10.5334/uproc.207}, pages = {1 -- 10}, year = {2025}, abstract = {In an era where AI-powered chatbots are increasingly being integrated into education and corporate learning, it is critical to determine whether these approaches benefit all learners or primarily cater to those with specific preferences. This study explores the interplay between learning preferences and learning outcomes in communication training using an AI-powered chatbot. In a field experiment with 17 participants, systematic thinkers and intrinsically motivated learners reported higher satisfaction and greater skill improvement, while those who preferred model learning and direct feedback benefited less. These findings suggest that AI-powered chatbots should be carefully designed to accommodate diverse learners and mitigate potential negative effects.}, language = {en} }