@inproceedings{PreissWestner, author = {Preiß, Niklas and Westner, Markus}, title = {From Agents to Copilots: a Systematic Review of Digital Assistant Technology Adoption in Proprietary Productivity Software}, series = {Annals of Computer Science and Information Systems}, volume = {43}, booktitle = {Annals of Computer Science and Information Systems}, publisher = {Polish Information Processing Society}, issn = {2300-5963}, doi = {10.15439/2025F3271}, pages = {565 -- 576}, abstract = {This study provides a systematic review of how the impact and adaptation of digital assistant technologies (DATs) are defined, operationalized, and studied, synthesizing key domains where DATs generate or are expected to generate value. Based on an analysis of 61 articles published since 2013, it identifies five main areas of impact: productivity and efficiency, business development, resource optimization, quality enhancement, and the promotion of learning and creativity. The review highlights DAT adoption across various disciplines and industries, while revealing limited longitudinal research on benefits and adaptation. Key gaps remain in understanding strategic use and sustained impact. Future research should explore longitudinal comparisons of recently introduced generative AI-driven DATs and their organizational implications. This review contributes to information systems research by structuring current knowledge on DAT adoption and outcomes, and by proposing a research agenda to support deeper exploration of their value and long-term integration.}, language = {en} } @inproceedings{KoehlerHarlWestneretal., author = {K{\"o}hler, Jessica and Harl, Maximilian Victor and Westner, Markus and Strahringer, Susanne}, title = {Can AI be a Scholar? A Systematic Review on the Role of Generative AI in Systematic Literature Reviews}, series = {2025 27th International Conference on Business Informatics (CBI), 09-12. September 2025, Lisbon, Portugal}, booktitle = {2025 27th International Conference on Business Informatics (CBI), 09-12. September 2025, Lisbon, Portugal}, publisher = {IEEE}, doi = {10.1109/CBI68102.2025.00012}, pages = {11}, abstract = {Systematic literature reviews (SLRs) are foundational for research but resource-intensive to conduct. With the rise of large language models (LLMs) such as ChatGPT, generative AI (GenAI) tools are being increasingly explored for their potential to support and transform the SLR process. This study presents a systematic review of peerreviewed articles that examine how LLM-based GenAI tools are used in different SLR phases. Following the PRISMA 2020 guidelines, we screened 1,846 publications published since January 2021 until April 2025 and selected 54 for in-depth analysis. Each study was coded by review phase, prompting approach, automation level, validation type and challenges. Our findings show that GenAI is most often used to support in the screening, search, and writing phases, typically through Basic Prompting and under human oversight. While many studies report efficiency gains, concerns remain regarding validity, transparency, and methodological rigor. Moreover, GenAI is frequently applied to isolated tasks but is rarely embedded in a structured, methodologically guided review processhighlighting the need for clearer phase-specific guidance and standards. We offer a structured, phase-specific synthesis that highlights both the promise and the current limitations of GenAI in literature reviews and thereby offer practical recommendations for the responsible use of GenAI in literature reviews.}, language = {en} } @inproceedings{DuennweberLorenzBraeuetal., author = {D{\"u}nnweber, Jan and Lorenz, Marcel and Br{\"a}u, Fabian and Saito, Hiroshi and Melzer, Matthias}, title = {Driving out the Bears from the Suburbs by Means of Location Theory and Intelligent Agents}, series = {Proceedings of the ACM 12th International Conference on Animal-Computer Interaction, ACI 2025: The International Conference on Animal-Computer Interaction ; Indiana USA ; 01-04.12.2025}, booktitle = {Proceedings of the ACM 12th International Conference on Animal-Computer Interaction, ACI 2025: The International Conference on Animal-Computer Interaction ; Indiana USA ; 01-04.12.2025}, publisher = {ACM}, address = {New York, NY, USA}, isbn = {9798400721236}, doi = {10.1145/3768539.3768546}, pages = {9}, abstract = {Due to the recent surge in bear attacks, affected municipalities have taken various measures to drive out the intruders. Political considerations include, in many places, the expansion of shooting permits. More and more regional governmental authorities invest in technologies for efficient bear hunting, such as IP cameras and computer vision. From an ecological perspective, such procedures, which are all solely aimed at decreasing the bear population, are questionable, since ecosystems can benefit from a peaceful coexistence of bears with humans: Bears remove animal carcasses and thus return vital nutrients to the soil and prevent the spread of diseases. Moreover, the bears keep the deer population in check, which is advantageous for the forest vegetation. Conflicts start, once the bears intrude populated areas, which are often rural villages and suburbs with a low population density. Naturally, bears do not see humans as prey and respect their size. When the animal attacks, this happens rather for territorial or protective reasons, e. g., after an unexpected encounter with humans unsettled it. In this work, we analyze means to eradicate the danger: We dynamically apply Weiszfeld's algorithm for finding the shifting geometric median between time-windowed black bear sightings and use the results for implementing an early warning system. In addition, we weigh the spotted locations and predict the expected migration behavior between bear habitats using a simulation with intelligent agents. As a case study, we apply our software to data from Romania and Fukushima and identify the positions where bear repelling facilities should be placed most effectively.}, language = {en} } @inproceedings{LehmannHerrmannSchaefferetal., author = {Lehmann, Lukas and Herrmann, David and Schaeffer, Leon and Albaik, Mohammed and M{\"u}ller, Emily and Rizzello, Gianluca and B{\"o}hm, Valter}, title = {Biomimetic Auxetic Compliant Tensegrity Metamaterial with Tunable Poisson's Ratio for the Application as a Soft Robotic Skin}, series = {2025 IEEE International Conference on Cyborg and Bionic Systems (CBS), Beijing, China ;10/17/2025 - 10/19/2025}, booktitle = {2025 IEEE International Conference on Cyborg and Bionic Systems (CBS), Beijing, China ;10/17/2025 - 10/19/2025}, publisher = {IEEE}, isbn = {979-8-3315-9742-9}, doi = {10.1109/CBS65871.2025.11267590}, pages = {188 -- 193}, abstract = {The use of compliant tensegrity grids offers significant potential for adaptive and lightweight systems for applications in soft robotics. This paper presents foundational investigations into a new class of auxetic tensegrity metamaterials. This work demonstrates that the auxetic behavior of a tensegrity grid can be realized and tuned solely through the mechanical properties of tensioned members, without altering the equilibrium geometry, offering a key advantage over conventional auxetic structures with fixed topologies. To validate the concept, 3D-printed demonstrators are manufactured, tested and a possible application as a cylindrically shaped soft robotic skin is shown.}, language = {en} } @inproceedings{NadimpalliMaierStauferetal., author = {Nadimpalli, Vamsi Krishna and Maier, Robert and Staufer, Susanne and R{\"o}hrl, Simon and Ezer, Timur and Grabinger, Lisa and Hauser, Florian and Mottok, J{\"u}rgen}, title = {EXPERT SURVEYS TO REAL TIME ADAPTATION OF LEARNING PATHS}, series = {ICERI2025 Proceedings}, booktitle = {ICERI2025 Proceedings}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2025.1571}, pages = {5677 -- 5687}, abstract = {Learning management systems rely on adaptive algorithms that use learner preferences to personalize the instructional content in form of learning paths. However, these preferences are uncertain in nature, and change over time. The present solutions are either static or purely data-driven missing the dynamic adaption to changes in the preferences and infusion of pedagogical nuances respectively. This paper introduces an extended variant of Nestor, our Bayesian network engine that models personality traits, learning styles, and learning strategies. This extension overlays a lightweight rule-based mechanism whose "secret recipe'' lies in the infusion of expert-derived weights adapting learning paths dynamically whenever a learner selects new material in Moodle. To parameterise these rules, we conducted a structured survey with 12 hand-picked professors and researchers in educational science. Each expert responded to 4 demographic items and 12 item that are distributed across algorithm-overview, scenario-based, and example-based categories, thereby supplying the nuanced weightings that result the personalised recommendations. This hybrid system (Nestor plus the expert-infused rule layer) operated during the winter term of 2025. 18 students completed an end-of-term questionnaire. Although their learning gains were not recorded, the majority of respondents reported positive or neutral experiences with the dynamically adapted learning paths. The {Future work} will compare three engines: (i) the present dynamic, expert-infused rule layer on top of the static Bayesian network, (ii) purely data-driven machine-learning models that neglect expert weighting, and (iii) the original static-adaptation Bayesian network without rules. Analyses of log files, intermediate satisfaction surveys, and pre/post term surveys will clarify whether this on-the-fly adaptation and pedagogical nuance lead to measurable learning benefits.}, language = {en} } @inproceedings{SchafferEzerRoehrletal., author = {Schaffer, Josefa and Ezer, Timur and R{\"o}hrl, Simon and Hauser, Florian and Staufer, Susanne and Nadimpalli, Vamsi Krishna and Grabinger, Lisa and Antoni, Erika and Mottok, J{\"u}rgen}, title = {EYE TRACKING GLASSES IN EDUCATIONAL SETTINGS: GUIDELINES ON DATA QUALITY}, series = {ICERI2025 Proceedings}, booktitle = {ICERI2025 Proceedings}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2025.1419}, pages = {5027 -- 5038}, abstract = {Eye movement modeling examples, so-called EMME videos, are a valuable tool in education, helping learners better understand instructional content. Like conventional educational videos, EMME videos combine text, images, and voiceovers. However, they also display the instructor's or teacher's gaze, guiding learners attention to key elements. Although various approaches exist for creating EMME videos, there is currently no standardised guideline for ensuring gaze data quality. Eye tracking technology is essential to capture gaze behaviour, and in educational settings without a fixed computer monitor - such as when using blackboards or conducting live experiments - the usage of mobile eye tracking glasses is beneficial. An accuracy study is conducted using mobile eye tracking glasses to provide empirical guidance for the development of high-quality educational EMME videos and ensure that the instructor's or teacher's gaze is captured with high precision. The study uses the Tobii Pro Glasses 3 and involves a static and a dynamic setup with 34 participants. To gain insight into the effects of visual impairments on accuracy, we also include participants who wear contact lenses. In the static setup, participants are seated at a desk with a headrest and focus on a poster with nine fixation points. In the dynamic setup, participants are walking in a controlled half-circle around the poster while maintaining focus on its centre. Each setup is performed multiple times under varying lighting levels (300 lux, 700 lux) and distances between participant and poster (80 cm, 120 cm, 180 cm). This enables the simulation of diverse educational environments, including the possibility of a teacher's or instructor's movement. The study results will be evaluated regarding lighting conditions, the distance between the person wearing eye tracking glasses and the object, and possible influences of contact lenses. Based on these findings, favourable conditions for creating EMME videos in educational settings are collected, especially when working without a fixed computer monitor. The results address the outlined research gap by providing instructors and teachers with guidelines enabling them to produce high-quality educational EMME videos.}, language = {en} } @inproceedings{AlhulaibiFrauenschlaegerMottok, author = {Alhulaibi, Ayham and Frauenschl{\"a}ger, Tobias and Mottok, J{\"u}rgen}, title = {Towards Post-Quantum-Ready Automated Certificate Lifecycle Management in Operational Technology}, series = {SECURWARE 2025, The Nineteenth International Conference on Emerging Security Information, Systems and Technologies, 26.-30.10.2025, Barcelona}, booktitle = {SECURWARE 2025, The Nineteenth International Conference on Emerging Security Information, Systems and Technologies, 26.-30.10.2025, Barcelona}, publisher = {IARIA}, isbn = {978-1-68558-306-4}, pages = {112 -- 116}, abstract = {Operational Technology (OT) systems increasingly depend on robust and automated certificate lifecycle management to maintain secure operations across long device lifespans and constrained environments. As quantum-capable adversaries emerge, these systems must also support cryptographic agility and prepare for a seamless transition to Post-Quantum Cryptography (PQC). This work presents a crypto-agile, post-quantum-ready testbed architecture that extends existing standards, such as Enrollment over Secure Transport (EST) and Bootstrapping Remote Secure Key Infrastructure (BRSKI), to support hybrid certificates, hardware-based key storage, and protocol flexibility for device bootstrapping and certificate management. A work-in-progress prototype implementation demonstrates support for both traditional and PQC algorithms across device types. Planned evaluations target performance on constrained devices, PQC readiness, and compatibility with alternative protocols. The system lays a foundation for secure and standards-compliant certificate management in future-proof OT deployments.}, language = {en} } @inproceedings{SchoenbergerTrummerMauerer, author = {Sch{\"o}nberger, Manuel and Trummer, Immanuel and Mauerer, Wolfgang}, title = {Large-Scale Multiple Query Optimisation with Incremental Quantum(-Inspired) Annealing}, series = {Proceedings of the ACM on Management of Data}, volume = {3}, booktitle = {Proceedings of the ACM on Management of Data}, number = {4}, publisher = {ACM}, doi = {10.1145/3749171}, pages = {25}, abstract = {Multiple-query optimization (MQO) seeks to reduce redundant work across query batches. While MQO offers opportunities for dramatic performance improvements, the problem is NP-hard, limiting the sizes of problems that can be solved on generic hardware. We propose to leverage specialized hardware solvers for optimization, such as Fujitsu's Digital Annealer (DA), to scale up MQO to problem sizes formerly out of reach. We present a novel incremental processing approach that combines classical computation with DA acceleration. By efficiently partitioning MQO problems into sets of partial problems, and by applying a dynamic search steering strategy that reapplies initially discarded information to incrementally process individual problems, our method overcomes capacity limitations, and scales to extremely large MQO instances (up to νm1000 queries). A thorough and comprehensive empirical evaluation finds our method substantially outperforms existing approaches. Our generalisable framework lays the ground for other database use-cases on quantum-inspired hardware, and bridges towards future quantum accelerators.}, language = {en} } @inproceedings{SchamelAchhammerSchummetal., author = {Schamel, Marco and Achhammer, Anton and Schumm, Leon and Sterner, Michael}, title = {Harvesting Sustainability: Cost-competitiveness of Green Fertilizer Value Chains in Western Africa}, series = {Proceedings of the 2025 IEEE PES/IAS PowerAfrica Conference (PAC 2025): pioneering sustainable energy solutions for Africa's Future, 28.09-02.10 2025, Cairo, Egypt}, booktitle = {Proceedings of the 2025 IEEE PES/IAS PowerAfrica Conference (PAC 2025): pioneering sustainable energy solutions for Africa's Future, 28.09-02.10 2025, Cairo, Egypt}, publisher = {IEEE}, isbn = {979-8-3315-9850-1}, doi = {10.1109/PowerAfrica65840.2025.11289137}, pages = {6}, abstract = {The use of nitrogen fertilizers in Sub-Saharan Africa is low compared to other regions of the world, leading to inadequate crop yields. Furthermore, conventional production from fossil fuel-based ammonia is highly emissions-intensive, making decarbonization urgent. Local production using green hydrogen, sourced solely from solar energy, water, and air, could address both agricultural and climate challenges. This study focuses on Ghana, where nitrogen inputs are among the lowest globally. Using an open-source framework, we evaluate high-resolution production costs for sustainable ammonia and examine two decarbonized pathways: aqueous ammonia and urea. It is found that cost estimates with current assumptions mostly exceed historical prices. However, given their resilience to global market disruptions and expected future cost decreases of the technologies used, these sustainable approaches represent a promising pathway for development in Sub-Saharan Africa.}, language = {en} } @inproceedings{SadequeAhmmedHossainetal., author = {Sadeque, Md. Golam and Ahmmed, Tanvir and Hossain, Md. Aowal and Rahman, Md. Naimur and Sarker, Md Tanjil and Ramasamy, Gobbi}, title = {A Novel CWT-CNN Framework for Driver Fatigue Detection from EEG Signals}, series = {2025 Multimedia University Engineering Conference (MECON), 21-23 July 2025, Cyberjaya, Malaysia}, booktitle = {2025 Multimedia University Engineering Conference (MECON), 21-23 July 2025, Cyberjaya, Malaysia}, publisher = {IEEE}, isbn = {979-8-3315-5549-8}, doi = {10.1109/MECON67253.2025.11277149}, pages = {6}, abstract = {Fatigued driving has been a significant contributor to traffic accidents globally, posing serious threats to both human life and economic stability. Machine learning techniques based on electroencephalography (EEG) are showing promise for detecting driver fatigue, excelling other physiological modalities in this regard. However, it requires a lot of exertion, demands domain knowledge, and may not generalize effectively across different datasets to manually extract features from EEG signals. Therefore, investigating innovative deep-learning architectures that can effectively extract discriminative characteristics from unprocessed EEG data is necessary. This paper proposes a novel framework for driver fatigue detection from EEG signals using Continuous Wavelet Transform (CWT) and Convolutional Neural Networks (CNN). Rather than depending on hand-crafted feature extraction, we use CWT to convert EEG data into time-frequency spectrum pictures. After concatenating these spectral images from every channel, a CNN is fed to learn discriminative features for driver normal and fatigued states automatically. An average classification accuracy of 98.3\% is obtained by evaluating the proposed CWT-CNN system on a publicly available EEG dataset comprising recordings from twelve subjects. The results obtained indicate that the CWT-CNN framework has enormous potential to create strong driver fatigue detection systems, thereby enhancing road safety.}, language = {en} } @inproceedings{GalkaMeissner, author = {Galka, Stefan and Meißner, Sebastian}, title = {Simulation-Based Digital Twins for Internal Transport Systems}, series = {Procedia Computer Science}, volume = {274}, booktitle = {Procedia Computer Science}, publisher = {Elsevier}, doi = {10.1016/j.procs.2025.12.016}, pages = {161 -- 170}, abstract = {The increasing complexity of internal transport systems in industrial applications poses significant challenges for operational decision-making. This paper presents a simulation-based Digital Twin framework developed within the research project TwinTraSys to support the control of such systems. The framework is specifically tailored to the constraints of real-world IT infrastructures, requiring minimal transaction data, while enabling predictive analysis and dynamic scenario evaluation. It consists of a modular architecture divided into four core components: data provision, data preparation, simulation, and decision support. A dedicated simulation framework enables the automated generation of structural models and the integration of real-world operational control systems. The proposed approach has been validated in industrial settings and has demonstrated its ability to support resource planning and transport resource allocation through simulation-based experimentation and multi-criteria evaluation. This paper contributes to the practical advancement of Digital Twin applications in intralogistics by bridging the gap between theoretical models and real-world constraints.}, language = {en} } @inproceedings{HopfenspergerVanselowHopkinsetal., author = {Hopfensperger, Bernhard and Vanselow, Marcel and Hopkins, Andrew and Hahn, Ingo}, title = {Investigation of the Effect of Magnetic Coupling on the Capacitor Current of Dual Three-Phase Permanent Magnet Synchronous Machine Drives}, series = {2025 Energy Conversion Congress \& Expo Europe (ECCE Europe); Birmingham, United Kingdom ; 9/1/2025 - 9/4/2025}, booktitle = {2025 Energy Conversion Congress \& Expo Europe (ECCE Europe); Birmingham, United Kingdom ; 9/1/2025 - 9/4/2025}, publisher = {IEEE}, isbn = {979-8-3315-6752-1}, doi = {10.1109/ECCE-Europe62795.2025.11238664}, pages = {6}, abstract = {The drive towards electrification of vehicles and transport systems has led to research into multiphase drive topologies beyond the conventional three. Dual three-phase machine drives are attractive due to reduced torque and DC-link harmonic content in addition to fault tolerance. Further DC-link rms-current reductions can be realised by applying appropriate modulation schemes and shifting/interleaving PWM patterns. However, the magnetic cross coupling between the two three-phase systems impacts the output current harmonics and subsequently the torque ripple which is further exacerbated by interleaving of their respective carriers. The impact of magnetic coupling on the DC-link and output current ripples is investigated.}, language = {en} } @inproceedings{HauserStauferRoehrletal., author = {Hauser, Florian and Staufer, Susanne and R{\"o}hrl, Simon and Nadimpalli, Vamsi Krishna and Ezer, Timur and Grabinger, Lisa and Mottok, J{\"u}rgen and Falter, Thomas}, title = {LEVERAGING FIVE QUESTIONNAIRES TO ANALYZE STUDENT LEARNING STRATEGIES AND GENERATE AI-POWERED INDIVIDUALIZED LEARNING PATHS}, series = {ICERI2025 Proceedings}, booktitle = {ICERI2025 Proceedings}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2025.0658}, pages = {1775 -- 1784}, abstract = {Background: The COVID-19 pandemic has significantly accelerated the shift toward online and blended learning in higher education, placing renewed emphasis on the individualization of learning content to meet diverse student needs. Even high-quality learning materials may fail to engage learners if they do not align with students' personal preferences and learning styles. Identifying these learner preferences, therefore, emerges as a critical challenge. Objectives: This paper presents ongoing work within a larger research project aimed at employing artificial intelligence to recommend optimal learning path for students in specific courses. Beyond mere optimization, the goal is to ensure the best possible fit between learning materials and individual learners. Sample \& Methods: A total of 27 students from technical degree programs took part in this survey. All participation was voluntary, and data were handled in full compliance with GDPR regulations. Although our broader project integrates fine-grained learning analytics from Moodle, the present abstract focuses exclusively on the self-report questionnaire results. Participants completed five instruments: 1. Index of Learning Styles (ILS) 2. LIST-K (Learning and Study Strategies Inventory - Short version) 3. BFI-10 (Big Five Inventory - 10 items) 4. Custom Preferences Instrument, capturing preferences for specific learning elements (e.g. instructional videos, lecture notes, summaries) and basic demographic data 5. Motivational Value Systems Questionnaire (MVSQ), piloted last semester to assess value orientations and motivational drivers Results: Preliminary analyses of the questionnaire data reveal: - Learning Styles (ILS): The majority lean toward the visual learning type (M = 5.740, SD = 3.430). - Learning Strategies (LIST-K): High scores on metacognitive strategies (M = 3.000; SD = 0.520) and collaboration with peers (M = 3.190; SD = 0.540). - Preferred Learning Elements: Summaries, overviews, and self-checks are most favored. - Value Orientations (MVSQ): Students are primarily driven by the pursuit of personal achievement (M = 4.400; SD = 11.140). Conclusion \& Significance: By integrating these five standardized questionnaires, we gain valuable insights into student learning preferences—insights that complement our Moodle analytics in the broader project. Observed trends suggest that learning materials should be concise and designed to facilitate peer interaction and knowledge deepening. These findings will guide the refinement of our AI-driven recommendation engine, enhancing its ability to deliver personalized learning paths that boost both engagement and effectiveness.}, language = {en} } @inproceedings{EzerRoehrlMottok, author = {Ezer, Timur and R{\"o}hrl, Simon and Mottok, J{\"u}rgen}, title = {Towards accurate eye tracking: quantifying error in linear pixel-to-degree conversion}, series = {ICERI2025 Proceedings}, booktitle = {ICERI2025 Proceedings}, editor = {G{\´o}mez Chova, Luis and Gonz{\´a}lez Mart{\´i}nez, Chelo and Lees, Joanna}, publisher = {IATED}, doi = {10.21125/iceri.2025.1841}, pages = {6709 -- 6717}, abstract = {Eye tracking has become a powerful tool for analyzing cognitive processes in educational research. Educators and researchers can utilize eye tracking to model learners by determining their gaze patterns. In addition, eye tracking can be used directly for teaching by extracting experts' gaze behavior in certain areas and learning from it. However, eye tracking data is captured in a variety of coordinate systems, which can differ across individual studies. Consequently, algorithms, such as eye movement classifiers, must frequently convert gaze data between different coordinate systems. In particular, the conversion from screen pixels into visual degrees is typically approximated by a linear conversion in current literature and standard practice. However, this approximation introduces inaccuracies, thus potentially obscuring eye movements relevant to educational research. This paper provides a detailed geometric and analytical examination of the commonly applied linear approximation, quantifying its error in comparison to the exact coordinate conversion from screen pixels to angular degrees. For this purpose, the exact conversion formulas are mathematically derived from geometric optics, enabling researchers and educators to use them in their work. Utilizing these derived transformations can improve the robustness of analyses, for example, when detecting subtle eye movements. The present work supports educational research using eye tracking to achieve more insightful findings that may have previously been obscured by measurement inaccuracies. Thereby, we provide an important contribution toward more reliable and valid research and educational practices in eye tracking.}, language = {en} } @inproceedings{BuglSchneiderSehr, author = {Bugl, Benedikt and Schneider, Viola I. and Sehr, Armin}, title = {Vertical Sound Localization: Precision and Robustness to Reverberation in a Large-Scale Study}, series = {Proceedings of the 11th Convention of the European Acoustics Association Forum Acusticum / EuroNoise 2025 // M{\´a}laga, Spain ; 23-26. June 2025}, booktitle = {Proceedings of the 11th Convention of the European Acoustics Association Forum Acusticum / EuroNoise 2025 // M{\´a}laga, Spain ; 23-26. June 2025}, publisher = {European Acoustics Association}, isbn = {978-84-87985-35-5}, doi = {10.61782/fa.2025.0953}, pages = {3431 -- 3434}, abstract = {Vertical sound localization, the ability to perceive the elevation of a sound source, is a fundamental aspect of human auditory perception, yet it remains far less understood than horizontal localization. Existing studies rely on small sample sizes, limiting the generalizability of findings. The presented study bridges that gap by examining vertical sound localization and precision in a cohort exceeding 150 participants, making it the largest investigation of its kind to date.Participants were exposed to broadband noise stimuli from various elevations under controlled anechoic conditions. The elevation localization error was measured by comparing perceived sound source elevations to actual positions of speakers of a curved array. Azimuth angles of arrival were altered between 0°, 45° and 90°. For a small group the experiment was repeated in echoic conditions, to gain insight in reverberation and reflection robustness of vertical sound localization.This large-scale study establishes benchmarks for vertical sound localization precision and robustness, advancing our understanding of human auditory spatial perception. These findings have implications for audio technology development, such as spatial audio rendering and hearing aid design, and lay the groundwork for further exploration into the neural and anatomical underpinnings of vertical localization.}, language = {en} } @inproceedings{StadlerSeitz, author = {Stadler, Sebastian and Seitz, Marie Sophie}, title = {When algorithms design: a comparative study pits an AI-generated application against a manual application in a competition of user experience and user-friendliness}, series = {Proceedings of 2025 11th international HCI and UX conference in Indonesia, 5 + 6. December 2025, Bali (CHIuXiD)}, booktitle = {Proceedings of 2025 11th international HCI and UX conference in Indonesia, 5 + 6. December 2025, Bali (CHIuXiD)}, publisher = {IEEE}, doi = {10.1109/CHIuXiD68326.2025.11323819}, pages = {55 -- 60}, abstract = {The rapid growth of artificial intelligence has enabled automated website creation, including design, content, and SEO. This study compares an AI-generated application with a manually designed one in terms of usability and user experience. Forty-two participants evaluated efficiency, effectiveness, satisfaction, emotional responses, and behavioural patterns. The manual application outperformed the AI-generated one in most datasets, particularly in clarity, supportiveness, and comprehensibility, while speed, learnability, activation, creativity, and security showed no significant differences. Users reported more positive emotions and confident interactions with the manual application, whereas the AI application elicited uncertainty and frustration. These behavioural differences were also reflected in processing times and task completion rates, suggesting that AI-generated solutions currently struggle to meet established UX standards. Nevertheless, the AI builder demonstrated potential for rapid prototyping and low-effort website creation, offering advantages for users with limited technical skills or resources. The findings highlight both the opportunities and limitations of current AI-based web design tools and underline the importance of human-centered design expertise in achieving high-quality user experiences. Despite existing shortcomings, AI-supported tools may become increasingly viable as technology advances.}, language = {en} } @inproceedings{StauferEzerRoehrletal., author = {Staufer, Susanne and Ezer, Timur and R{\"o}hrl, Simon and Grabinger, Lisa and Hauser, Florian and Nadimpalli, Vamsi Krishna and Antoni, Erika and Mottok, J{\"u}rgen and Schaffer, Josefa}, title = {TYCHE ALGORITHM 2.0: Learning Paths from Questionnaire Responses and Learning Analytics}, series = {ICERI2025 Proceedings}, booktitle = {ICERI2025 Proceedings}, publisher = {IATED}, isbn = {978-84-09-78706-7}, doi = {10.21125/iceri.2025.0831}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:898-opus4-87846}, pages = {2562 -- 2572}, abstract = {The digitalization of learning processes has increased the need for adaptive learning paths tailored individually to learners. A novel algorithm for learning path generation is presented in this paper, namely Tyche 2.0. It extends the original Tyche approach after Staufer et al. - a Markov model for generating learning paths - by integrating additional learner data beyond learning styles (Index of Learning Styles (ILS)), including learning strategies (LIST-K questionnaire), personality traits (BFI-10 questionnaire), and learning analytics captured through screen recordings. In order to be able to use the screen recordings, a heuristic evaluates them. Furthermore, this enhanced algorithm employs Markov models to dynamically generate personalized learning paths. These are based on both questionnaire responses and real-time engagement data, the weights of which undergo dynamic adjustment over time. We made a small evaluation of Tyche 2.0 without the learning analytics influence, which shows that there is room for further improvements. Future research will focus on evaluating whole Tyche 2.0 in another university setting to further improve personalization and user engagement.}, language = {en} } @inproceedings{BuchmannSchwaegerl, author = {Buchmann, Thomas and Schw{\"a}gerl, Felix}, title = {Using Meta-code Generation to Realize Higher-order Model Transformations}, series = {Proceedings of the 8th International Joint Conference on Software Technologies, July 29-31, 2013, in Reykjav{\´i}k, Iceland, Vol. 1}, booktitle = {Proceedings of the 8th International Joint Conference on Software Technologies, July 29-31, 2013, in Reykjav{\´i}k, Iceland, Vol. 1}, publisher = {SciTePress - Science and and Technology Publications}, isbn = {978-989-8565-68-6}, doi = {https://doi.org/10.5220/0004522305360541}, pages = {536 -- 541}, abstract = {Model-driven engineering is a wide-spread paradigm in modern software engineering. During the last couple of years, many tools and languages have been developed, which are especially designed for model transformations — a discipline which is needed in many model-driven engineering approaches. While most of the existing model-to-model tools and languages are tailored towards batch transformations for specific model instances, they lack support for generic transformation problems, where the metamodel is unknown beforehand. In this paper we present a two-step meta-code generation approach that derives a metamodel-specific modelto- model transformation from a model-to-text transformation. The approach has been successfully applied to the problem of product derivation in model-driven software product lines.}, language = {en} } @inproceedings{SchwaegerlUhrig, author = {Schw{\"a}gerl, Felix and Uhrig, Sabrina}, title = {Tool Support for the Evaluation of Matching Algorithms in the Eclipse Modeling Framework}, series = {Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development, February 19-21, 2013, in Barcelona, Spain, Vol. 1}, booktitle = {Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development, February 19-21, 2013, in Barcelona, Spain, Vol. 1}, publisher = {SciTePress - Science and and Technology Publications}, isbn = {978-989-8565-42-6}, issn = {2184-4348}, doi = {10.5220/0004310801010110}, pages = {101 -- 110}, abstract = {In the field of model-driven development, sophisticated support for comparing model versions is urgently needed. Unfortunately, algorithms for model matching have been rarely evaluated so far. This paper deals with two extensions to the Eclipse Modeling Framework (EMF) that facilitate the evaluation of matching algorithms for EMF models, with the goal to combine user involvement and automated testing in the evaluation process. First a tree editor is presented that allows for the manual and semi-automated creation of match models which formalize the intended matching result. Second a benchmarking procedure is implemented which - given the intended match and the actual results of matching algorithms - automatically derives the number of a and b errors in a target-performance comparison. These results are valuable for drawing conclusions about the specific qualities of matching algorithms or for finding an adequate set of parameters for a configurable algorithm.}, language = {en} } @inproceedings{BauerVitzthumeckerBierletal., author = {Bauer, Lukas and Vitzthumecker, Thomas and Bierl, Rudolf and Ehrnsperger, Matthias}, title = {Machine-learning-based detection and severity estimation of drought stress in plants using hyperspectral imaging data}, series = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, booktitle = {Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVII}, publisher = {SPIE}, doi = {10.1117/12.3072011}, pages = {7}, abstract = {Growing food demand due to population growth, coupled with increasingly frequent and severe droughts caused by climate change make water increasingly scarce. To address this, accurate assessment of plant water demand is essential for precise drought treatment and water conservation. Hyperspectral imaging (HSI) captures hypercubes, a combination of spectral and spatial data and offers promising capabilities for detection of plant stresses. However, most reported approaches only use selected spectral bands or indices, neglecting the full hypercube information. This is assumed to limit the detection accuracy. To overcome these limitations, we aim to develop a measurement pipeline to generate a comprehensive dataset comprising hypercubes of plants under varying drought stress levels along with selected physiological, environmental, and illumination data. This dataset will be used to train suitable data-driven models that enable improved drought stress detection as well as the non-invasive determination of physiological parameters based on HSI data.}, language = {en} }