TY - JOUR A1 - Schleif, Frank-Michael T1 - Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik JF - Künstliche Intelligenz Y1 - 2007 UR - https://www.techfak.uni-bielefeld.de/~fschleif/pdf/ki_2007.pdf VL - 21 IS - 4 SP - 65 EP - 67 ER - TY - JOUR A1 - Schleif, Frank-Michael A1 - Hammer, Barbara A1 - Villmann, Thomas T1 - Margin-based active learning for LVQ networks JF - Neurocomputing Y1 - 2007 U6 - https://doi.org/10.1016/j.neucom.2006.10.149 VL - 70 IS - 7-9 SP - 1215 EP - 1224 ER - TY - JOUR A1 - Hillebrecht, Steffen A1 - Braun, Ellen T1 - Klotzen oder kapitulieren - erfolgreiches Personalmarketing im Web JF - Personal - Zeitschrift für Human Resource Management Y1 - 2011 SN - 2365-8614 VL - 63 IS - 6 SP - 34 EP - 35 PB - Verl.-Gruppe Handelsblatt CY - Düsseldorf ER - TY - JOUR A1 - Hillebrecht, Steffen A1 - Braun, Ellen T1 - Betriebliche Wahrnehmung des Burnouts JF - Der Betriebswirt Y1 - 2013 SN - 0172-6196 VL - 54 IS - 3 SP - 16 EP - 22 PB - Deutscher Betriebswirte Verlag CY - Gernsbach ER - TY - CHAP A1 - Fetzer, Toni A1 - Bullmann, Markus A1 - Ebner, Markus A1 - Kastner, Steffen A1 - Deinzer, Frank A1 - Grzegorzek, Marcin T1 - Interacting Multiple Model Particle Filter for Indoor Positioning Applications T2 - Proceedings of the 2023 International Technical Meeting of The Institute of Navigation Y1 - 2023 UR - https://www.researchgate.net/profile/Toni-Fetzer/publication/368485764_Interacting_Multiple_Model_Particle_Filter_for_Indoor_Positioning_Applications/links/63fa3e960d98a97717b975ae/Interacting-Multiple-Model-Particle-Filter-for-Indoor-Positioning-Applications.pdf ER - TY - JOUR A1 - Meißner, Pascal A1 - Dillmann, Rüdiger T1 - Implicit Shape Model Trees - Recognition of 3-D Indoor Scenes and Prediction of Object Poses for Mobile Robots JF - robotics N2 - This article describes an approach for mobile robots to identify scenes in configurations of objects spread across dense environments. This identification is enabled by intertwining the robotic object search and the scene recognition on already detected objects. We proposed “Implicit Shape Model (ISM) trees” as a scene model to solve these two tasks together. This article presents novel algorithms for ISM trees to recognize scenes and predict object poses. For us, scenes are sets of objects, some of which are interrelated by 3D spatial relations. Yet, many false positives may occur when using single ISMs to recognize scenes. We developed ISM trees, which is a hierarchical model of multiple interconnected ISMs, to remedy this. In this article, we contribute a recognition algorithm that allows the use of these trees for recognizing scenes. ISM trees should be generated from human demonstrations of object configurations. Since a suitable algorithm was unavailable, we created an algorithm for generating ISM trees. In previous work, we integrated the object search and scene recognition into an active vision approach that we called “Active Scene Recognition”. An efficient algorithm was unavailable to make their integration using predicted object poses effective. Physical experiments in this article show that the new algorithm we have contributed overcomes this problem. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-53649 VL - 12 IS - 158 PB - MDPI ER - TY - CHAP A1 - Brückner, Marcel A1 - Deinzer, Frank A1 - Denzler, Joachim ED - Yang, Guang-Zhong ED - Hawkes, David ED - Rueckert, Daniel ED - Noble, Alison ED - Taylor, Chris T1 - Temporal Estimation of the 3d Guide-Wire Position Using 2d X-ray Images T2 - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009 Y1 - 2009 UR - https://www.academia.edu/download/42129005/Temporal_estimation_of_the_3d_guide-wire20160205-19144-1xamzsr.pdf SN - 978-3-642-04267-6 VL - 5761 SP - 386 EP - 393 ER - TY - CHAP A1 - Wacker, Matthias A1 - Deinzer, Frank ED - Yang, Guang-Zhong ED - Hawkes, David ED - Rueckert, Daniel ED - Noble, Alison ED - Taylor, Chris T1 - Automatic Robust Medical Image Registration Using a New Democratic Vector Optimization Approach with Multiple Measures T2 - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009 Y1 - 2009 SN - 978-3-642-04267-6 VL - 5761 SP - 590 EP - 597 ER - TY - CHAP A1 - Köping, Lukas A1 - Mühsam, Thomas A1 - Ofenberg, Christian A1 - Czech, Bernhard A1 - Bernard, Michael A1 - Schmer, Jens A1 - Deinzer, Frank T1 - Indoor Navigation Using Particle Filter and Sensor Fusion T2 - Proceedings of the European Navigation Conference 2012 Y1 - 2012 ER - TY - CHAP A1 - Köping, L. A1 - Grzegorzek, M. A1 - Deinzer, Frank T1 - Probabilistic Step and Turn Detection in Indoor Localisation T2 - 10th IET Data Fusion Target Tracking Conference (DF TT 2014): Algorithms and Applications Y1 - 2014 UR - https://www.researchgate.net/profile/Marcin-Grzegorzek/publication/264040695_Probabilistic_Step_and_Turn_Detection_in_Indoor_Localisation/links/0046353c9a4b9b1d53000000/Probabilistic-Step-and-Turn-Detection-in-Indoor-Localisation.pdf SP - 1 EP - 7 ER - TY - JOUR A1 - Serón, Francisco A1 - de Carvalho, Carlos Vaz A1 - Saul, Melanie A1 - Deinzer, Frank A1 - Guerrero, Roberto A1 - Parra, Juan Carlos A1 - Costa, Cristiano A1 - Rigo, Sandro T1 - Realidades Virtuales/Aumentadas para el Desarrollo Social: Experiencias Entre Europa y Latinoamerica Y1 - 2014 SN - 978-950-757-046-9 ER - TY - JOUR A1 - Köping, Lukas A1 - Mühsam, Thomas A1 - Ofenberg, Christian A1 - Czech, Bernhard A1 - Bernard, Michael A1 - Schmer, Jens A1 - Deinzer, Frank T1 - Indoor Navigation Using Particle Filter and Sensor Fusion JF - Annual of Navigation Y1 - 2012 UR - https://bibliotekanauki.pl/articles/320422.pdf VL - 19 IS - 2 SP - 31 EP - 40 ER - TY - JOUR A1 - Köping, Lukas A1 - Deinzer, Frank T1 - Realidades Virtuales/Aumentadas para el Desarrollo Social: Experiencias Entre Europa y Latinoamerica Y1 - 2014 SN - 978-950-757-046-9 ER - TY - RPRT A1 - Benkert, Marius A1 - Schmidt, Jochen A1 - Rose, Lennard T1 - Question-Answering System for Coffee Machines N2 - Our study presents a comprehensive Question Answering (QA) system for coffee machine related questions. The system covers a wide range of topics such as maintenance, usage, and troubleshooting of coffee machines, offering quick and accurate answers to the users through its intuitive interface and natural language processing capabilities. The system provides a seamless experience for coffee machine owners and users to access the information they need, ensuring smooth operation of their machines and allowing them to enjoy their favorite beverages with ease. To evaluate the performance of these models, we fine-tuned a range of BERT-based Transformers on a manually created dataset of 653 question-answer pairs. In conclusion, our findings demonstrate the feasibility of using NLP Question Answering models to deliver technical answers about coffee machines, and highlight the importance of fine-tuning these models on task-specific data. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-43657 ER - TY - THES A1 - Bea, Michelle T1 - Automatisiert und rechtskonform - Best-Practice-Strategien von KMU zur Umsetzung des EU-AI-Acts im Online-Marketing N2 - In den vergangenen Jahren hat Künstliche Intelligenz (KI) das Online-Marketing grundlegend verändert. Inhalte werden zunehmend automatisiert erstellt, Kampagnen datenbasiert gesteuert und Kundeninteraktionen durch lernende Systeme personalisiert. Was lange als Innovationsvorteil galt, wird durch den EU-AI-Act nun auch zu einer rechtlichen Herausforderung: Unternehmen müssen sicherstellen, dass der Einsatz von KI-Systemen nicht nur effizient, sondern auch regelkonform erfolgt. Besonders kleine und mittlere Unternehmen (KMU) stehen vor der Aufgabe, komplexe rechtliche Anforderungen mit ihren begrenzten Ressourcen in Einklang zu bringen. Die vorliegende Masterarbeit untersucht, wie KMU im Online-Marketing die Anforderungen des EU-AI-Acts umsetzen können, um rechtliche Konformität sicherzustellen und zugleich die Leistungsfähigkeit ihrer digitalen Prozesse zu erhalten. KI-Systeme sind bereits fester Bestandteil von Marketingprozessen, doch bislang fehlen strukturierte Ansätze, um die rechtlichen Vorgaben praxisnah umzusetzen. Zur Beantwortung der Forschungsfrage wurde ein Design-Science-Research-Ansatz (DSR) nach Kuechler & Vaishnavi (2015) gewählt, der Forschung und Gestaltung in einem iterativen Fünf-Phasen-Prozess verbindet. Auf dieser Grundlage wurde die Logik des EU-AI-Acts systematisch analysiert, ein praxisorientiertes Artefakt entwickelt und dessen Anwendung und Umsetzbarkeit im Rahmen von sieben Experteninterviews aus Recht, Wissenschaft und unternehmerischer Praxis evaluiert. Als zentrales Ergebnis entstand eine Broschüre als Artefakt, die den Umsetzungsprozess des EU-AI-Acts in einem 6-Schritte-Prozess abbildet. Sie umfasst ein KI-Inventar, eine Prüfung, ob es sich um ein KI-System handelt, eine Rollenbestimmung, eine Risikoklassifizierung anhand einer Evidenz-Matrix sowie daraus abgeleitete Handlungsempfehlungen und Hinweise für den Umgang mit Hochrisiko-Systemen. Die Broschüre unterstützt KMU bei der strukturierten Selbstbewertung und bietet einen kompakten, prüffähigen Rahmen für AI-Compliance im Online-Marketing (Anhang H). Die Ergebnisse zeigen, dass KMU den EU-AI-Act als grundsätzlich realisierbar einstufen, in der Umsetzung jedoch klare Regeln und Strukturen benötigen. Frühzeitige Befassung mit der Regulierung, interdisziplinäre Zusammenarbeit und die Nutzung offizieller Leitfäden fördern eine nachhaltige Compliance-Kultur. Der EU-AI-Act erweist sich insgesamt als transformatorisches Steuerungsinstrument, das rechtliche, strategische und ethische Dimensionen verbindet. Zukünftige Arbeiten sollten die Wirksamkeit der Broschüre empirisch prüfen, sie an entstehende Normen anpassen, digitale Tool-Unterstützungen entwickeln und ihre Übertragbarkeit auf andere Unternehmensbereiche untersuchen. N2 - Artificial intelligence (AI) is transforming online marketing by automating content creation, personalizing customer interactions and optimizing campaign strategies. While these innovations drive efficiency, they also raise new legal challenges under the European Union’s Artificial Intelligence Act (EU-AI-Act). Especially small and medium-sized enterprises (SMEs) must find ways to comply with these requirements without compromising their digital competitiveness. This master’s thesis explores how SMEs in online marketing can implement the requirements of the EU-AI-Act to ensure legal compliance while maintaining the efficiency of their digital operations. Although AI systems are already integrated into marketing activities, such as in content creation, person-alization and campaign management, companies often lack structured approaches to translate the Act’s obligations into practice. Following the Design-Science-Research (DSR) approach by Kuechler & Vaishnavi (2015), the study combines theoretical analysis, artifact development and evaluation in an iterative five-phase process. The logic of the EU-AI-Act was systematically examined, a practical artifact was developed and its applicability was evaluated through seven qualitative expert interviews with professionals from law, academia and industry. The thesis presents a practical brochure as its main artifact, consolidating the findings into a 6-step pathway that guides SMEs through the implementation process. The brochure includes an AI inventory to determine whether a tool falls under the scope of the Act, a role identification module and a risk classification framework based on an evidence matrix. It further provides derived action recommendations and practical guidance for handling high-risk AI applications. The recommendations offer SMEs an auditable framework for AI compliance in online marketing contexts. The study concludes that the EU-AI-Act functions as a transformative governance framework, integrating legal, strategic and ethical dimensions. Future research should empirically test the brochure’s effectiveness, align it with emerging European standards, develop digital tool support for automation and assess its transferability to adjacent business domains. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-63905 N1 - Beiwerk zur Masterarbeit verfügbar unter: https://doi.org/10.5281/zenodo.18019609 ER - TY - CHAP A1 - Holomjova, Valerija A1 - Starkey, Andrew J. A1 - Meißner, Pascal T1 - GSMR-CNN: An End-to-End Trainable Architecture for Grasping Target Objects from Multi-Object Scenes T2 - Proceedings of IEEE International Conference on Robotics and Automation (ICRA) N2 - We present an end-to-end trainable multi-task model that locates and retrieves target objects from multi-object scenes. The model is an extension of the Siamese Mask R-CNN, which combines the components of Siamese Neural Networks (SNNs) and Mask R-CNN for performing one-shot instance segmentation. The proposed network, called Grasping Siamese Mask R-CNN (GSMR-CNN), extends Siamese Mask R-CNN by adding an additional branch for grasp detection in parallel to the previous object detection head branches. This allows our model to identify a target object with a suitable grasp simultaneously, as opposed to other approaches that require the training of separate models to achieve the same task. The inherent SNN properties enable the proposed model to generalize and recognize new object categories that were not present during training, which is beyond the capabilities of standard object detectors. Moreover, an end-to-end solution uses shared features entailing less model parameters. The model achieves grasp accuracy scores of 92.1 % and 90.4% on the OCID grasp dataset on image-wise and object-wise splits. Physical experiments show that the model achieves a grasp success rate of 76.4 % when correctly identifying the object. Code and models are available at https://github.com/valerijah/grasping_siamese_mask_rcnn Y1 - 2023 U6 - https://doi.org/10.1109/ICRA48891.2023.10161009 ER - TY - CHAP A1 - Tilly, Julian A1 - Neeb, Christopher A1 - Bhairapu, Chandu A1 - Mohamed, Fatima A1 - Kachana, Indrasena Reddy A1 - Saravanan, Mahesh A1 - Nguyen Pham, Phuoc T1 - Navigating the Future: an approach of autonomous indoor vehicles N2 - In this project, we explored the ability of Reinforcement learning (RL) in driving an indoor car autonomously. RL has proven its good performance in solving challenging decision-making problems. Therefore, RL can be a promising solution for autonomous car to deal with complex driving scenarios. As hardware a model car eqipped with sensors and powerful computational unit has been used. We also utilized SLAM for environment mapping and a combination of lidar data and Wi-Fi technology for localization. The experiment showed that the model can perform very well in simulation. Although the model lacks the ability to drive the car as smoothly along a route, the car is still able to avoid obstacles and walls in an unknown real-world environment. KW - Autonomous vehicles KW - SLAM KW - Indoor localization KW - Reinforcement learning Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-43401 ER - TY - THES A1 - Kumar, Dibyanshu T1 - A Comparative Analysis of Loss Formulations in Diffusion Models N2 - Diffusion models have established themselves as highly effective generative frameworks, inspiring significant research into their underlying mechanisms. An important aspect of these models lies in the choice of loss functions, which directly influences their training and performance. Over recent years, multiple formulations have been proposed [20, 56, 27, 49], each with distinct characteristics and theoretical foundations. This thesis provides a comprehensive exploration of these loss functions, systematically analyzing their theoretical relationships and unifying them under the framework of the variational lower bound objective. We complement this analysis with empirical studies that examine the conditions under which different objectives yield varying performance and provide insights into the factors driving these discrepancies. Additionally, we assess the impact of loss function selection on the model’s ability to achieve specific objectives, such as producing high-quality samples or precisely estimating data likelihoods. By presenting a unified perspective, this study advances the understanding of loss functions in diffusion models, contributing to more efficient and goal-oriented model designs in future research. N2 - Diffusionsmodelle haben sich als hochwirksame generative Frameworks etabliert und zu bedeutender Forschung zu ihren zugrunde liegenden Mechanismen geführt. Ein wichtiger Aspekt dieser Modelle liegt in der Wahl der Verlustfunktionen, die ihr Training und ihre Leistung direkt beeinflussen. In den letzten Jahren wurden verschiedene Formulierungen vorgeschlagen [20, 56, 27, 49], jede mit unterschiedlichen Merkmalen und theoretischen Grundlagen. Diese Arbeit bietet eine umfassende Untersuchung dieser Verlustfunktionen, analysiert systematisch ihre theoretischen Zusammenhänge und vereinheitlicht sie im Rahmen des Ziels der variationellen Untergrenze. Wir ergänzen diese Analyse durch empirische Studien, die die Bedingungen untersuchen, unter denen unterschiedliche Ziele zu unterschiedlichen Leistungen führen, und Einblicke in die Faktoren geben, die diese Diskrepanzen verursachen. Darüber hinaus bewerten wir den Einfluss der Wahl der Verlustfunktion auf die Fähigkeit des Modells, bestimmte Ziele zu erreichen, wie z. B. die Erstellung qualitativ hochwertiger Stichproben oder die präzise Schätzung von Datenwahrscheinlichkeiten. Durch die Darstellung einer einheitlichen Perspektive fördert diese Studie das Verständnis von Verlustfunktionen in Diffusionsmodellen und trägt zu effizienteren und zielorientierteren Modelldesigns in der zukünftigen Forschung bei. Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-62929 ER - TY - THES A1 - Sprenger, Axel Bernhard Martin T1 - Automation Bias bei Kl-gestützten Führungsentscheidungen in der IT Branche N2 - In vielen Organisationen werden Führungsentscheidungen zunehmend durch KI-Systeme vorbereitet oder getroffen. Diese Studie untersucht, ob und wie sich die Akzeptanz von Führungsentscheidungen verändert, wenn sie einer KI statt einer menschlichen Führungskraft zugeschrieben werden. Auf Basis des Forschungsstands zu Automation Bias, kognitiver Belastung und organisationaler Fairness wurden zunächst qualitative Interviews mit IT-Führungskräften durchgeführt, um realistische Entscheidungsszenarien (z. B. Bewerberauswahl, Ressourcenpriorisierung) zu identifizieren. Diese Szenarien dienten als Stimuli für ein onlinebasiertes Umfrage-Experiment mit IT-Beschäftigten (N = 69; 328 szenariobasierte Bewertungen), in dem die Zuschreibung der Entscheidung („KI“ vs. „Mensch“) experimentell variiert wurde. Die Ergebnisse zeigen, dass das KI-Label zwar zu einer höheren Wahrnehmung von Neutralität führt, zugleich aber die Identifikation mit der entscheidenden Instanz verringert. Ein direkter Automation Bias im Sinne einer pauschal höheren Akzeptanz von KI-Entscheidungen ließ sich nicht nachweisen. Stattdessen wird Akzeptanz überwiegend durch wahrgenommene Fairness, Zufriedenheit und Identifikation erklärt, auf die wiederum Kompetenz, Erklärbarkeit und Neutralität einwirken. Damit rücken die Qualität und Transparenz des Entscheidungsprozesses stärker in den Vordergrund als die bloße Etikettierung als KI-Entscheidung. Praktisch folgt daraus, dass KI in Führungskontexten nur als unterstützendes, erklärbares und jederzeit vom Menschen übersteuerbares Instrument eingesetzt werden sollte, um sowohl Objektivität als auch soziale Anschlussfähigkeit zu sichern. KW - Artificial Intelligence KW - AI KW - Leadership Communication KW - Decision Acceptance KW - Trust in AI KW - Human-AI Interaction KW - Künstliche Intelligenz KW - Automation Bias KW - Führungsentscheidungen KW - Akzeptanz KW - IT-Branche Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:863-opus-63941 ER - TY - JOUR A1 - Yamshchikov, Ivan A1 - Koltun, Vladyslav T1 - Pump It - Twitter Sentiment Analysis for Cryptocurrency Price Prediction JF - Risks Y1 - 2023 U6 - https://doi.org/10.3390/risks11090159 VL - 11 IS - 159 PB - MDPI ER - TY - CHAP A1 - John, Isabel A1 - Silva, Adeline T1 - Evaluating variability instantiation strategies for product lines T2 - VaMoS '11: Proceedings of the 5th International Workshop on Variability Modeling of Software-Intensive Systems N2 - Explicit variability management is essential for large product lines and requires explicit strategies for instantiating the managed variabilities during application engineering. An instantiation strategy proposes a certain order for the resolution of variabilities during application engineering or for testing. If an alphabetical strategy is used, for instance, the variabilities are resolved in alphabetical order, from A to Z. In this paper, we motivate the necessity of strategies for large variability models, which help to identify starting points and guide the resolution of variability models. We sketch the application of the strategies in a tool and give the results of an experiment performed to compare the strategies in different situations. The experiment showed that the efficiency of instantiation differs by more than 35% between different strategies. Additionally, the meaningfulness of the instantiation was perceived differently for the various strategies and the strategies were all perceived as being easy to resolve. With the experiment, we managed to demonstrate that the effectiveness of instantiation strategies differs, which motivates the need for different variability instantiation strategies in different situations. Y1 - 2011 U6 - https://doi.org/10.1145/1944892.19449 SP - 105 EP - 113 ER - TY - CHAP A1 - Callea, Viviana A1 - John, Isabel A1 - Matrisciano, Apollonia A1 - Ursache, Mihai T1 - Coaching and Engineering Synergy for Effective Vocational Tools: The COACH_ING Model T2 - 2025 IEEE Global Engineering Education Conference (EDUCON) N2 - Today, more than ever, in a market oriented towards sustainability, inclusion, and new technologies, it is necessary to integrate educational and guidance systems with tools that enable future professionals to choose their career path and later contribute to the collective good. To foster good career choices for engineers we have developed the COACH_ING model presented in earlier papers. In this paper we want to present a project and an experiment, conducted at an engineering faculty of a European university as part of a country wide Guidance and Tutoring Project. In our COACH_ING model, used by the faculty and professional associations for over seven years, new tools have been implemented for conscious career choice guidance and the enhancement of one's professional potential, via future-oriented educational concepts. The activities took place in structured workshops during which, assessments and questionnaires were systematically administered to gather useful research data and monitor the development of reference skills drawn from coaching and engineering. Specifically, the tool DIRECTING, presented at the EFEA2021, now called DIRECTINGVer2, has been enriched, as a questionnaire, with new elements based on empirical validations performed in the meantime. The collected data provided new insights into the level of learning of specific reference parameters related to the COACH_ING model intersecting Dublin Descriptors as a broadly known framework for qualification in degree programs. In the individual interventions, classroom techniques specific to new guidance models were respected, with the aim of developing an open mindset in students, through conditions initially defined based on the mastery of 16 skills and 8 MCs (Macro Capabilities) of the COACH_ING model. During our not-traditional lab, data emerged regarding eight MCs and four clusters of the questionnaire. Participants were involved in group work to bring out their knowledge and potential (as presented at ICL2024). Through focus groups and 1-to-1 sessions, we verified the actual level of confidence and acquisition of knowledge related to both the MCs and the dimensions identified in the Clusters: communication, teamwork, goal and project, relationship. The model finds its foundations in coaching process engineering, building a life project and choosing one's personalized future path. There emerges a strong need to focus on the advancement of engineering education and the concepts to be conveyed to future engineers so that they can act for their own benefit and that of the surrounding world, making conscious choices. KW - Engineering profession KW - Conferences KW - Buildings KW - Europe KW - Data models KW - Teamwork KW - Engineering education KW - Sustainable development KW - Monitoring KW - Qualifications KW - Confidence Level KW - Focus Group KW - Working Group KW - Career Path KW - Future Technologies KW - Empirical Validation KW - Faculty Of Engineering KW - Reference Parameters KW - Level Of Acquisition KW - Decision-making Process KW - Critical Thinking KW - Labour Market KW - Communication Skills KW - Completed Questionnaires KW - Personal Development KW - Technical Skills KW - Multiple-choice Questions KW - Proficiency Levels KW - PhD Students KW - Level Of Mastery KW - Engineering Students KW - Professional Profile KW - Soft Skills KW - Subject Of Work KW - Model Skill KW - Potential Tensions KW - Analytical Skills KW - Individual Answers KW - Market Requirements KW - personalized educational concepts KW - nontraditional lab concepts KW - engineering education KW - future engineers Y1 - 2025 SN - 979-8-3315-3949-8 SN - 979-8-3315-3950-4 U6 - https://doi.org/10.1109/EDUCON62633.2025.11016626 SN - 2165-9567 SN - 2165-9559 PB - IEEE ER - TY - CHAP A1 - Keller, Lisa A1 - John, Isabel T1 - How can computer science faculties increase the proportion of women in computer science by using robots? T2 - 2019 IEEE Global Engineering Education Conference (EDUCON) N2 - As women belong to a minority in computer science, this work aims to provide possible K-12 STEM education initiatives how computer science faculties can contribute to increasing the proportion of women in computer science by using robots. Through applying these initiatives, faculties can help to reduce the gender imbalance, increase diversity and the amount of computer science specialists, who are requested immensely. Based on the results of conducted requirements elicitation a concept for programming an application with the NAO robot which trains vocabularies, as well as a concept with the Cozmo robot which piles up cubes, were developed. First tests were performed with female and male high school students. Either concept consists of an introduction of possible robotics application fields, a presentation explaining the Python program code of the concept as well as corresponding exercises with the robot and Python. Evaluation of the workshop concepts through questionnaires showed that both concepts have the potential to increase the proportion of women and to motivate female as well as male students for computer science. Moreover, recommendations for further robotics projects with respect to motivating young women for STEM can be made based on the insights of the requirements elicitation and the evaluation of the concepts. Nevertheless, further refinement and validation has to be undertaken. Long-term as well as short-term initiatives are feasible with the developed concepts. All participating schools showed high interest in both types of initiatives and further cooperation. Y1 - 2019 SN - 978-1-5386-9506-7 SN - 978-1-5386-9507-4 U6 - https://doi.org/10.1109/EDUCON.2019.8725212 SN - 2165-9567 SN - 2165-9559 SP - 206 EP - 210 PB - IEEE ER - TY - CHAP A1 - Keller, Lisa A1 - John, Isabel T1 - Motivating female students for computer science by means of robot workshops T2 - International Journal of Engineering Pedagogy N2 - As women belong to a minority in computer science, this work aims to provide possible STEM education initiatives for middle to high school students. These initiatives are designed for institutions to contribute to increasing the proportion of women in computer science by using robots. Through applying these initiatives, institutions such as computer science faculties can help to reduce the gender imbalance, increase diversity and the amount of computer science specialists, who are requested immensely. Based on the results of conducted requirements elicitation a concept for programming an application with the NAO robot which trains vocabularies, as well as a concept with the Cozmo robot which piles up cubes, were developed. First tests were performed with female and male high school students. Either concept consists of an introduction of possible robotics application fields, a presentation explaining the Python program code of the concept as well as corresponding exercises with the robot and Python. Evaluation of the workshop concepts through questionnaires showed that both concepts have the potential to increase the proportion of women and to motivate female as well as male students for computer science. Moreover, recommendations for further robotics projects with respect to motivating young women for STEM can be made based on the insights of the requirements elicitation and the evaluation of the concepts. Nevertheless, further refinement and validation has to be undertaken. Long-term as well as short-term initiatives are feasible with the developed concepts. All participating schools showed high interest in both types of initiatives and further cooperation. KW - women in computer science KW - proportion of women in STEM KW - diversity KW - robotics in education Y1 - 2020 U6 - https://doi.org/10.3991/ijep.v10i1.11661 VL - 10 IS - 1 SP - 94 EP - 108 ER - TY - CHAP ED - Villmann, Thomas ED - Kaden, Marika ED - Geweniger, Tina ED - Schleif, Frank-Michael T1 - Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond - Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10-12, 2024 Y1 - 2025 SN - 978-3-031-67158-6 U6 - https://doi.org/10.1007/978-3-031-67159-3 VL - 1087 ER - TY - RPRT A1 - John, Isabel T1 - Gamification in der Software Engineering Lehre - ein Erfahrungsbericht N2 - In diesem Paper beschreiben wir die Evolution eines blended learning Kurses in Software Engineering und agilem Projekt Management. Wir verwendeten in aufeinanderfolgenden Semestern mehrere Gamification Ansätze in diesem Kurs, u.A. Punkte-basierte Gamification und Story-basierte, narrative Gamification. Der gamifizierte Kurs wurde mit dem Lern Management System Moodle realisiert. Wir beschreiben unsere Erfahrungen mit den verschiedenen Gamification Ansätzen und skizzieren weitere Ansätze für die Zukunft des Kurses. N2 - In this paper we describe the evolution of a blended learning course in software engineering. The course covers an introduction to Software Engineering also dealing with agile project management and scrum. We used different gamification approaches in this course over the years, including point based gamification and story based gamification. The gamified e-learning course was realized with the learning management system Moodle. We describe our experiences with the different gamification approaches and outline possible approaches for the future. KW - gamification KW - e-learning KW - motivation KW - agile KW - scrum Y1 - 2020 UR - https://ceur-ws.org/Vol-2531/paper09.pdf ER - TY - BOOK A1 - Liebstückel, Karl T1 - Plant Maintenance with SAP S/4HANA: Business User Guide Y1 - 2020 UR - https://www.rheinwerk-verlag.de/plant-maintenance-with-sap-s4hana-business-user-guide/ SN - 978-1-4932-2020-5 PB - SAPPRESS CY - Bonn, Boston ET - 5. Auflage ER - TY - BOOK A1 - Liebstückel, Karl T1 - Configuring Plant Maintenance in SAP S/4HANA Y1 - 2024 UR - https://www.rheinwerk-verlag.de/configuring-plant-maintenance-in-sap-s4hana/ SN - 978-1-4932-2604-7 PB - SAPPRESS CY - Bonn, Boston ET - 2. Auflage ER - TY - BOOK A1 - Liebstückel, Karl T1 - Instandhaltung mit SAP S/4HANA - Das Praxishandbuch Y1 - 2023 UR - https://www.rheinwerk-verlag.de/instandhaltung-mit-sap-das-praxishandbuch/ SN - 978-3-8362-9013-5 PB - SAPPRESS CY - Bonn, Boston ET - 6. Auflage ER - TY - CHAP A1 - Keckl, Matthias A1 - Müller, Patrick A1 - Braun, Peter T1 - Model-driven Software Development as the Key to RESTful Web Interfaces and Digitization T2 - 6th International Conference on Applied Informatics Imagination, Creativity, Design, Development (ICDD) 2022 Y1 - 2022 SP - 70 EP - 82 ER - TY - CHAP ED - Villmann, Thomas ED - Schleif, Frank-Michael ED - Kaden, Marika ED - Lange, Mandy T1 - Advances in Self-Organizing Maps and Learning Vector Quantization T2 - Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany, July, 2-4, 2014 Y1 - 2014 SN - 978-3-319-07694-2 U6 - https://doi.org/10.1007/978-3-319-07695-9 VL - 295 ER - TY - CHAP T1 - 21st International Conference on Information Fusion, FUSION 2018, Cambridge, UK, July 10-13, 2018 Y1 - 2018 SN - 978-0-9964527-6-2 ER - TY - BOOK A1 - Huang, Xinyu ED - Deinzer, Frank ED - Grzegorzek, Marcin T1 - Sensor-Based Sleep Stage Classification Using Deep Learning Y1 - 2023 SN - 978-3-8325-5617-4 VL - 4 ER - TY - BOOK A1 - Li, Frédéric T1 - Deep Learning for Time-series Classification Enhanced by Transfer Learning Based on Sensor Modality Discrimination Y1 - 2021 SN - 978-3-8325-5396-8 VL - 2 ER - TY - CHAP A1 - Klingenberg, Christiana A1 - Weber, Kristin T1 - Data Governance: Der Leitfaden für die Praxis T2 - Daten- und Informationsqualität Y1 - 2025 SN - 9783446481022 U6 - https://doi.org/10.1007/978-3-658-47317-4_16 PB - Springer Vieweg ER - TY - JOUR A1 - Holomjova, Valerija A1 - Starkey, Andrew J A1 - Yun, Bruno A1 - Meißner, Pascal T1 - One-shot learning for task-oriented grasping JF - IEEE Robotics and Automation Letters Y1 - 2023 U6 - https://doi.org/10.1109/LRA.2023.3326001 VL - 8 IS - 12 SP - 8232 EP - 8238 ER - TY - CHAP A1 - Paval, Sandro A1 - Yamshchikov, Ivan P A1 - Meißner, Pascal T1 - ComicScene154: A Scene Dataset for Comic Analysis T2 - Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing Y1 - 2025 SP - 31562 EP - 31568 ER -