@inproceedings{KarpenahalliRamakrishnaMohanZeinalyetal.2025, author = {Karpenahalli Ramakrishna, Chidvilas and Mohan, Adithya and Zeinaly, Zahra and Belzner, Lenz}, title = {The Evolution of Criticality in Deep Reinforcement Learning}, booktitle = {Proceedings of the 17th International Conference on Agents and Artificial Intelligence (ICAART 2025) - Volume 3}, editor = {Rocha, Ana Paula and Steels, Luc and van den Herik, Jaap}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-737-5}, doi = {https://doi.org/10.5220/0013114200003890}, pages = {217 -- 224}, year = {2025}, abstract = {In Reinforcement Learning (RL), certain states demand special attention due to their significant influence on outcomes; these are identified as critical states. The concept of criticality is essential for the development of effective and robust policies and to improve overall trust in RL agents in real-world applications like autonomous driving. The current paper takes a deep dive into criticality and studies the evolution of criticality throughout training. The experiments are conducted on a new, simple yet intuitive continuous cliff maze environment and the Highway-env autonomous driving environment. Here, a novel finding is reported that criticality is not only learnt by the agent but can also be unlearned. We hypothesize that diversity in experiences is necessary for effective criticality quantification which is majorly driven by the chosen exploration strategy. This close relationship between exploration and criticality is studied utilizing two different strategies namely the ex ponential ε-decay and the adaptive ε-decay. The study supports the idea that effective exploration plays a crucial role in accurately identifying and understanding critical states.}, language = {en} } @inproceedings{WildgrubeEhrettTrojahnetal.2025, author = {Wildgrube, Fabian and Ehrett, Pete and Trojahn, Paul and Membarth, Richard and Beckmann, Bradford and Baumeister, Dominik and Chajdas, Matth{\"a}us}, title = {GPUs All Grown-Up: Fully Device-Driven SpMV Using GPU Work Graphs}, booktitle = {ISCA ´25: Proceedings of the 52nd Annual International Symposium on Computer Architecture}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1261-6}, doi = {https://doi.org/10.1145/3695053.3731060}, pages = {1777 -- 1791}, year = {2025}, abstract = {Sparse matrix-vector multiplication (SpMV) is a key operation across high-performance computing, graph analytics, and many more applications. In these applications, the matrix characteristics, notably non-zero elements per row, can vary widely and impact which algorithm performs best. Thus, Graphics Processing Unit (GPU) SpMV algorithms often rely on costly preprocessing to determine what per-row algorithm to select to achieve high performance. In this work we combine SpMV preprocessing and the subsequent per-row processing on the GPU by leveraging the novel "Work Graphs" GPU programming model—initially designed for graphics applications—for dynamic on-device self-scheduling. Work Graphs allow for fine-grain dataflow execution of individual workgroups using emerging hardware and firmware support. As soon as preprocessing has generated sufficient work, workgroups of individual processing kernels are self-scheduled and executed, interleaved with those of other kernels. This improves cache locality and eliminates host interaction altogether. Across a suite of 59 sparse matrices, the best of various novel Work Graphs SpMV implementations outperforms state-of-the-art rocSPARSE "LRB" for a single SpMV by up to 7.19 × (mean: 3.35 ×, SD: 1.89). Furthermore, it achieves much more stable performance across various sparsity patterns than the rocSPARSE CSR-General algorithm, and even beats the advanced rocSPARSE CSR-Adaptive algorithm for up to 92 consecutive SpMV calculations. In addition, compared to rocSPARSE LRB, it reduces code complexity by 75\%. Its memory footprint for supporting data structures is a fixed ∼ 25 MiB independent of matrix size, compared to rocSPARSE LRB's data structures that scale with matrix size to hundreds of megabytes. Overall, this work showcases the performance potential of emerging dynamic on-device scheduling techniques for GPU compute applications.}, language = {en} } @article{AxmannPujar2025, author = {Axmann, Bernhard and Pujar, Sanket}, title = {Artificial Intelligence in Knowledge Management: Overview and Selection of Software for Automotive Reporting}, volume = {19}, journal = {Tehnički glasnik}, number = {si1}, publisher = {University North}, address = {Koprivnica}, issn = {1848-5588}, doi = {https://doi.org/10.31803/tg-20250313154901}, pages = {130 -- 135}, year = {2025}, abstract = {Knowledge Management is essential for modern organizations, enabling the systematic capture, organization, and sharing of knowledge to enhance decision-making and innovation. Traditional Knowledge Management tools, focused on document storage and retrieval, struggle with unstructured data and collaboration, necessitating advanced technological solutions, particularly those incorporating Artificial Intelligence. - Artificial Intelligence-driven Knowledge Management systems revolutionize data handling through automation, and real-time insights. This is particularly valuable in data-intensive industries like automotive, finance, and healthcare. In the automotive sector, annual reports provide critical insights but are complex and time-consuming to analyze and are a complex example and therefore a good test case. Annual reports of 5 major automotive companies BMW, Volkswagen group, Toyota Motors, General Motors and Tesla were selected as the testing dataset. Artificial Intelligence tools, using natural language processing and machine learning, streamline data extraction. - Despite their benefits, organizations face challenges in selecting the right Artificial Intelligence-driven Knowledge Management software due to a lack of standardized evaluation frameworks. This research applies a systematic methodology for assessing such software, considering usability, adaptability, cost-effectiveness, and data privacy compliance, specifically tailored to automotive reporting and gives recommendation for software tools.}, language = {en} } @inproceedings{DevillersKurtenackerMembarthetal.2025, author = {Devillers, Hugo and Kurtenacker, Matthias and Membarth, Richard and Lemme, Stefan and Kenzel, Michael and Yazici, {\"O}mercan and Slusallek, Philipp}, title = {No More Shading Languages: Compiling C++ to Vulkan Shaders}, booktitle = {High-Performance Graphics - Symposium Papers}, editor = {Knoll, Aaron and Peters, Christoph}, publisher = {The Eurographics Association}, address = {Goslar}, isbn = {978-3-03868-291-2}, url = {https://diglib.eg.org/handle/10.2312/hpg20251167}, doi = {https://doi.org/10.2312/hpg.20251167}, year = {2025}, abstract = {Graphics APIs have traditionally relied on shading languages, however, these languages have a number of fundamental defects and limitations. By contrast, GPU compute platforms offer powerful, feature-rich languages suitable for heterogeneous compute. We propose reframing shading languages as embedded domain-specific languages, layered on top of a more general language like C++, doing away with traditional limitations on pointers, functions, and recursion, to the benefit of programmability. This represents a significant compilation challenge because the limitations of shaders are reflected in their lower-level representations. We present the Vcc compiler, which allows conventional C and C++ code to run as Vulkan shaders. Our compiler is complemented by a simple shading library and exposes GPU particulars as intrinsics and annotations. We evaluate the performance of our compiler using a selection of benchmarks, including a real-time path tracer, achieving competitive performance compared to their native CUDA counterparts.}, language = {en} } @unpublished{EndtEngelNaldietal.2023, author = {Endt, Sebastian and Engel, Maria and Naldi, Emanuele and Assereto, Rodolfo and Molendowska, Malwina and Mueller, Lars and Verdun, Claudio Mayrink and Pirkl, Carolin and Palombo, Marco and Jones, Derek K. and Menzel, Marion Irene}, title = {In-vivo myelin water quantification using diffusion-relaxation correlation MRI: a comparison of 1D and 2D methods}, titleParent = {Research Square}, publisher = {Research Square}, address = {Durham}, doi = {https://doi.org/10.21203/rs.3.rs-3069146/v1}, year = {2023}, abstract = {Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion-recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. While 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.}, language = {en} } @article{EndtEngelNaldietal.2023, author = {Endt, Sebastian and Engel, Maria and Naldi, Emanuele and Assereto, Rodolfo and Molendowska, Malwina and Mueller, Lars and Verdun, Claudio Mayrink and Pirkl, Carolin and Palombo, Marco and Jones, Derek K. and Menzel, Marion Irene}, title = {In Vivo Myelin Water Quantification Using Diffusion-Relaxation Correlation MRI: A Comparison of 1D and 2D Methods}, volume = {54}, journal = {Applied Magnetic Resonance}, number = {11-12}, publisher = {Springer}, address = {Wien}, issn = {0937-9347}, doi = {https://doi.org/10.1007/s00723-023-01584-1}, pages = {1571 -- 1588}, year = {2023}, abstract = {Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion-relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion.}, language = {en} } @article{VergnanoPelizzariGiorgiannietal.2025, author = {Vergnano, Alberto and Pelizzari, Alessandro and Giorgianni, Claudio and Kovanda, Jan and Zimmer, Alessandro and Lopes da Silva, Joed and Rezvanpour, Hamed and Leali, Francesco}, title = {Monitoring Occupant Posture Using a Standardized Sensor Interface with a Vehicle Seat}, volume = {9}, pages = {52}, journal = {Designs}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2411-9660}, doi = {https://doi.org/10.3390/designs9020052}, year = {2025}, abstract = {Car safety can be enhanced by enabling the Airbag Control Unit (ACU) to adaptively deploy different charges based on the occupant's position once the crash occurs. In this context, monitoring the occupant's position using a sensorized seat integrated with an Inertial Measurement Unit (IMU) offers a practical and cost-effective solution. However, certain challenges still need to be addressed. The adoption of sensorized seats in research and vehicle set-up is still under consideration. This study investigates an interface device that can be reconfigured to suit almost any seat model. This reconfigurability makes it easily adaptable to new vehicles under development and applicable to any passenger seat in the vehicle. This paper details the device's design, including its programming using calibration and monitoring features, which significantly improves its reliability compared to earlier prototypes. Extensive testing through real driving experiments with multiple participants demonstrated an accuracy range of 45-100\%. The testing involved both drivers and passengers, showcasing the device's ability to effectively monitor various in-car scenarios.}, language = {en} } @inproceedings{RadtkeBock2022, author = {Radtke, Maximilian-Peter and Bock, J{\"u}rgen}, title = {Combining Knowledge and Deep Learning for Prognostics and Health Management}, booktitle = {Proceedings of the European Conference of the PHM Society 2022}, editor = {Do, Phuc and Michau, Gabriel and Ezhilarasu, Cordelia}, publisher = {PHM Society}, address = {Rochester}, isbn = {978-1-936263-36-3}, doi = {https://doi.org/10.36001/phme.2022.v7i1.3302}, pages = {594 -- 597}, year = {2022}, abstract = {In the recent past deep learning approaches have achieved remarkable results in the area of Prognostics and Health Management (PHM). These algorithms rely on large amounts of data, which is often not available, and produce outputs, which are hard to interpret. Before the broad success of deep learning machine faults were often classified using domain expert knowledge based on experience and physical models. In comparison, these approaches only require small amounts of data and produce highly interpretable results. On the downside, however, they struggle to predict unexpected patterns hidden in data. This research aims to combine knowledge and deep learning to increase accuracy, robustness and interpretability of current models.}, language = {en} } @article{SalamatElsbacher2022, author = {Salamat, Babak and Elsbacher, Gerhard}, title = {Centralized Control in Networks of Underactuated Nonidentical Euler-Lagrange Systems Using a Generalised Multicoordinates Transformation}, volume = {10}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2022.3178606}, pages = {58311 -- 58319}, year = {2022}, abstract = {Controlling the network of underactuated Euler-Lagrange (EL) systems is challenging because of their coupled inertia matrices and time-variant control input matrices. We present generalized multi-coordinates transformation that renders the network of underactuated Euler-Lagrange dynamics in particular forms, whose mechanical properties should be preserved. The network of N nonidentical Euler-Lagrange EL-systems is modeled as a weighted interconnection graph where each EL-system is a node, and the control action at each node is a function of its state and the states of its neighbors. Second, we propose an online optimally centralized control mechanism with the prime objective of energy efficiency. The result is applied to the network of underactuated vertical takeoff and landing aircraft with strong input coupling, including the effect of the weight of the rotors into the dynamical system models. In this regard, we obtain very simple and powerful state-feedback solutions.}, language = {en} } @article{HartlBock2024, author = {Hartl, Jakob Joseph Lorenz and Bock, J{\"u}rgen}, title = {A Maturity Model to Determine the Degree of Utilization of Machine Learning in Production Planning and Control Processes}, volume = {18}, journal = {Tehnički glasnik}, number = {3}, publisher = {University North}, address = {Koprivnica}, issn = {1848-5588}, doi = {https://doi.org/10.31803/tg-20240513233046}, pages = {437 -- 444}, year = {2024}, abstract = {The presented work introduces a maturity model for evaluating Machine Learning implementations, with a primary focus on Production Planning and Control processes, as well as broader organizational and technical aspects in companies. This model emerges as a response to the research gap identified in the analysis of 14 existing maturity models, which served as foundational bases for the development of this novel approach. By examining success factors and obstacles at different maturity levels, categorized according to defined dimensions and overarching design fields, this model can serve as a catalyst for bridging the research gap between models demanded in practice and the scholary exploration of topics related to Machine Learning in corporate processes. Notably, the structured design of this maturity model ensures accessibility for small and medium sized enterprises (SMEs).}, language = {en} } @article{KovalKnollmeyerMathiasetal.2024, author = {Koval, Leonid and Knollmeyer, Simon and Mathias, Selvine George and Asif, Saara and Akmal, Muhammad Uzair and Großmann, Daniel and Bregulla, Markus}, title = {Unlocking the Potential of Information Modeling for Root Cause Analysis in a Production Environment: A Comprehensive State-of-the-Art Review Using the Kitchenham Methodology}, volume = {12}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2024.3406020}, pages = {80266 -- 80282}, year = {2024}, abstract = {Data from production environments is now available in unprecedented volumes, making the problem-solving of incidents through root cause analysis straightforward. However, the root cause analysis process remains time-consuming. This study employs the Kitchenham standard systematic literature review methodology to explore how information models and deep learning can streamline this process. By conducting a comprehensive search across four major databases, we evaluate the current technological advancements and their application in root cause analysis. The aim of this study is to assesses the impact of information models for root cause analysis in a production environment. Our findings reveal that integrating knowledge graphs, association rule mining, and deep learning algorithms significantly improves the speed and depth of root cause analysis compared to traditional methods. Specifically, the use of neural networks in recent literature shows substantial advancements in analyzing complex datasets, facilitating large-scale data integration, and enabling automated learning capabilities. Comparing our findings with other recent studies highlights the advantages of using information modeling and deep learning technologies in root cause analysis. This comparison underscores the superior accuracy and efficiency of these advanced methodologies over traditional manual interpretation methods. The effective implementation of these technologies requires a robust foundation of clean, standardized data, giving rise to the concept of "Production IT." Furthermore, it is crucial for this data to be openly available to facilitate academic research, thereby enabling the development of new methods for more efficient and effective root cause analysis.}, language = {en} } @article{KruegelUhl2023, author = {Kr{\"u}gel, Sebastian and Uhl, Matthias}, title = {The behavioral economics of dynamically inconsistent behavior: a critical assessment}, volume = {61}, journal = {Social Choice and Welfare}, number = {4}, publisher = {Springer Nature}, address = {Berlin}, issn = {0176-1714}, doi = {https://doi.org/10.1007/s00355-023-01471-5}, pages = {817 -- 833}, year = {2023}, abstract = {Preferences often change—even in short time intervals—due to either the mere passage of time (present-biased preferences) or changes in visceral or environmental conditions (state-dependent preferences). On the basis of empirical findings concerning state-dependent preferences, we critically discuss the "Aristotelian" view of unitary decision makers in economics. We illustrate that the conceptualization of preferences as "present-biased" as opposed to "state-dependent" has very different normative implications for which preferences should be considered "rational." Empirically, however, the two concepts are very difficult to distinguish. The economist can justify any paternalistic intervention if she can conceptualize changing preferences so flexibly, and she can easily become a benevolent despot. We therefore urge for a more careful "Heraclitean" view of decision-making that accepts that a person may consist of multiple selves.}, language = {en} } @article{KruegelUhl2024, author = {Kr{\"u}gel, Sebastian and Uhl, Matthias}, title = {The risk ethics of autonomous vehicles: an empirical approach}, volume = {14}, pages = {960}, journal = {Scientific Reports}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {https://doi.org/10.1038/s41598-024-51313-2}, year = {2024}, abstract = {How would people distribute risks of autonomous vehicles (AVs) in everyday road traffic? The rich literature on the ethics of autonomous vehicles (AVs) revolves around moral judgments in unavoidable collision scenarios. We argue for extending the debate to driving behaviors in everyday road traffic where ubiquitous ethical questions arise due to the permanent redistribution of risk among road users. This distribution of risks raises ethically relevant questions that cannot be evaded by simple heuristics such as "hitting the brakes." Using an interactive, graphical representation of different traffic situations, we measured participants' preferences on driving maneuvers of AVs in a representative survey in Germany. Our participants' preferences deviated significantly from mere collision avoidance. Interestingly, our participants were willing to take risks themselves for the benefit of other road users, suggesting that the social dilemma of AVs may be mitigated in risky environments. Our research might build a bridge between engineers and philosophers to discuss the ethics of AVs more constructively.}, language = {en} } @unpublished{PetrovskaErjiageKugele2025, author = {Petrovska, Ana and Erjiage, Guan and Kugele, Stefan}, title = {Defining Self-adaptive Systems: A Systematic Literature Review}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2505.17798}, year = {2025}, abstract = {In the last two decades, the popularity of self-adaptive systems in the field of software and systems engineering has drastically increased. However, despite the extensive work on self-adaptive systems, the literature still lacks a common agreement on the definition of these systems. To this day, the notion of self-adaptive systems is mainly used intuitively without a precise understanding of the terminology. Using terminology only by intuition does not suffice, especially in engineering and science, where a more rigorous definition is necessary. In this paper, we investigate the existing formal definitions of self-adaptive systems and how these systems are characterised across the literature. Additionally, we analyse and summarise the limitations of the existing formal definitions in order to understand why none of the existing formal definitions is used more broadly by the community. To achieve this, we have conducted a systematic literature review in which we have analysed over 1400 papers related to self-adaptive systems. Concretely, from an initial pool of 1493 papers, we have selected 314 relevant papers, which resulted in nine primary studies whose primary objective was to define self-adaptive systems formally. Our systematic review reveals that although there has been an increasing interest in self-adaptive systems over the years, there is a scarcity of efforts to define these systems formally. Finally, as part of this paper, based on the analysed primary studies, we also elicit requirements and set a foundation for a potential (formal) definition in the future that is accepted by the community on a broader range.}, language = {en} } @unpublished{RamicKugele2025, author = {Ramic, Amra and Kugele, Stefan}, title = {A Systematic Mapping Study on Software Architecture for AI-based Mobility Systems}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2506.01595}, year = {2025}, abstract = {Background: Due to their diversity, complexity, and above all importance, safety-critical and dependable systems must be developed with special diligence. Criticality increases as these systems likely contain artificial intelligence (AI) components known for their uncertainty. As software and reference architectures form the backbone of any successful system, including safety-critical dependable systems with learning-enabled components, choosing the suitable architecture that guarantees safety despite uncertainties is of great eminence. Aim: We aim to provide the missing overview of all existing architectures, their contribution to safety, and their level of maturity in AI-based safety-critical systems. Method: To achieve this aim, we report a systematic mapping study. From a set of 1,639 primary studies, we selected 38 relevant studies dealing with safety assurance through software architecture in AI-based safety-critical systems. The selected studies were then examined using various criteria to answer the research questions and identify gaps in this area of research. Results: Our findings showed which architectures have been proposed and to what extent they have been implemented. Furthermore, we identified gaps in different application areas of those systems and explained these gaps with various arguments. Conclusion: As the AI trend continues to grow, the system complexity will inevitably increase, too. To ensure the lasting safety of the systems, we provide an overview of the state of the art, intending to identify best practices and research gaps and direct future research more focused.}, language = {en} } @article{BodenschatzWalkowitz2024, author = {Bodenschatz, Anja and Walkowitz, Gari}, title = {Slipping on stereotypes - Interactive gender effects in the erosion of ethical behavior}, volume = {2025}, pages = {102785}, journal = {Journal of Economic Psychology}, number = {106}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0167-4870}, doi = {https://doi.org/10.1016/j.joep.2024.102785}, year = {2024}, abstract = {We investigate how gender affects ethical outcomes in repeated same- or mixed-gender interactions. In our first study (N = 681), we use an experimental slippery-slope audit setting (Gino and Bazerman, 2009), in which an "auditor" makes an approval decision about the emerging unethical behavior of an "estimator" whose gender has been made salient. Based on previous evidence, unethical behavior is more likely to be accepted when it emerges gradually compared to a situation where it occurs abruptly. While we do not find a general slippery-slope effect across the whole sample, a significant slippery-slope effect is detected when the estimator is male (d = 0.36) or when the auditor is female (d = 0.27). We observe no slippery-slope effects in same-gender estimator-auditor constellations. However, in mixed-gender constellations, we find opposite effects: when male estimators are audited by females, we observe a significant slippery-slope effect (d = 0.53), driven by a high approval rate in the slippery-slope treatment. Conversely, when female estimators are audited by males, the approval rate increases in the abrupt treatment (d = 0.33). To better understand the drivers of these findings, we asked a different sample of participants (N = 90) to indicate the level of competence or honesty they attribute to male and female estimators in the estimation task. Responses suggest that the detected slippery-slope effects may be driven by auditors (especially females), attributing more competence to male estimators (d = 0.62), which is particularly relevant in the slippery-slope treatment where unethical behavior is difficult to detect. Moreover, our finding that male auditors are particularly inclined to approve overvaluations by females in the abrupt treatment, where unethical behavior becomes salient, may be driven by a more ethical assessment of female estimators (d = 0.90).}, language = {en} } @article{Bednarz2025, author = {Bednarz, Martin}, title = {Die Casting or Sheet Metal Forming: A Comparison of Car Body Manufacturing in Times of the "Giga Press"}, volume = {19}, journal = {Tehnički glasnik}, number = {1}, publisher = {University North}, address = {Koprivnica}, issn = {1848-5588}, doi = {https://doi.org/10.31803/tg-20240510165209}, pages = {58 -- 61}, year = {2025}, abstract = {Die casting as an alternative for sheet metal structures in car body design has been around for a few years. While the application of die cast body components by legacy automakers is rather limited, especially for mass market products, Tesla bases their mass-produced cars on a few extremely big die cast structure parts. The impact of this strategy makes it necessary to rethink car body manufacturing. In this study, published information and expert interviews are used to evaluate the strengths and weaknesses of the competing philosophies of car body manufacturing.}, language = {en} } @article{Richter2024, author = {Richter, Florian}, title = {From human-system interaction to human-system co-action and back: ethical assessment of generative AI and mutual theory of mind}, volume = {5}, journal = {AI and Ethics}, number = {1}, publisher = {Springer}, address = {Cham}, issn = {2730-5961}, doi = {https://doi.org/10.1007/s43681-024-00626-z}, pages = {19 -- 28}, year = {2024}, abstract = {Human-machine ethics has emerged as a rapidly growing research field in recent years. However, it seems that Generative Artificial Intelligence (AI) leads to a paradigm shift from human-machine interaction to co-action. The ethical assessment of such relationships is still in the making and needs further scrutiny. First, studies about the influence of technology in human-system interactions and manipulation are reviewed. Second, the "mutual theory of mind" approach is critically examined to identify its shortcomings. Third, creating user models is reconstruced to demonstrate the strategies of systems. Finally, use cases are discussed and assessed to outline ethical implications.}, language = {en} } @inproceedings{SchrageSchudererFranke2025, author = {Schrage, Tobias and Schuderer, Peter and Franke, J{\"o}rg}, title = {Process- and Material-Specific Modeling to Use in Simulation-Based and Resource-Oriented Decision Support Systems Using the Example of Calcium Silicate Brick Production Planning}, booktitle = {Sustainable Manufacturing as a Driver for Growth: Proceedings of the 19th Global Conference on Sustainable Manufacturing, December 4-6, 2023, Buenos Aires, Argentina}, editor = {Kohl, Holger and Seliger, G{\"u}nther and Dietrich, Franz and Mur, Sebasti{\´a}n}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-77429-4}, doi = {https://doi.org/10.1007/978-3-031-77429-4_62}, pages = {562 -- 568}, year = {2025}, abstract = {As part of the fourth industrial revolution, data analysis and artificial intelligence are being integrated into production processes. In addition, energy consumption and CO2 costs are becoming decisive factors in the resource-oriented management of companies. For energy intensive and hybrid production processes a simulation-based decision support system (DSS) for production planning is validated and further developed for the sand lime brick industry to support the production planning process. The integration of empirical knowledge in the energy-intensive control of steam processes, in which quality-critical product parameters are set via thermodynamically complex relationships, is still part of current research approaches. In this paper, an approach for the mapping of an energetic system behavior in the energy-intensive and hybrid production processes will be discussed using the example of calcium silicate brick (CSB) production. Possibilities for using Discrete event simulation (DES) to increase the energy efficiency of steam processes are summarized and linked to formalized empirical knowledge in artificial Intelligence (AI) approaches.}, language = {en} } @inproceedings{HenssKugele2025, author = {Henß, J{\"o}rg and Kugele, Stefan}, title = {22nd Workshop on Automotive Software Engineering}, booktitle = {Software Engineering 2025 - Companion Proceedings}, editor = {Feichtinger, Kevin and Sonnleithner, Lisa and Hajiabadi, Hamideh}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, issn = {2944-7682}, doi = {https://doi.org/10.18420/se2025-ws-02}, pages = {23 -- 24}, year = {2025}, abstract = {Software-driven systems are becoming pivotal, underpinning the majority of innovations in contemporary automobiles. This workshop is poised to explore a plethora of topics pertinent to automotive software development. Attendees will engage in discourse on the most apt methodologies, techniques, and tools essential for navigating the foremost challenges faced by researchers and practitioners in the field.}, language = {en} } @article{BodenschatzUhlWalkowitz2021, author = {Bodenschatz, Anja and Uhl, Matthias and Walkowitz, Gari}, title = {Autonomous systems in ethical dilemmas}, volume = {2021}, pages = {100145}, journal = {Computers in human behavior reports}, subtitle = {attitudes toward randomization}, number = {4}, publisher = {Amsterdam}, address = {Elsevier}, issn = {2451-9588}, doi = {https://doi.org/10.1016/j.chbr.2021.100145}, year = {2021}, abstract = {It is ethically debatable whether autonomous systems should be programmed to actively impose harm on some to avoid greater harm for others. Surveys on ethical dilemmas in self-driving cars' programming have shown that people favor imposing harm on some people to save others from suffering and are consequently willing to sacrifice smaller groups to save larger ones in unavoidable accident situations. This is, if people are forced to directly impose harm. Contrary to humans, autonomous systems feature a salient deontological alternative for immediate decisions: the ability to randomize decisions over dilemmatic outcomes. To be applicable in democracies, randomization must correspond to people's moral intuition. In three studies (N = 935), we present empirical evidence that many people prefer to randomize between dilemmatic outcomes due to moral considerations. We find these preferences in hypothetical and incentivized decision-making situations. We also find that preferences are robust in different contexts and persist across Germany, with its Kantian cultural tradition, and the US, with its utilitarian cultural tradition.}, language = {en} } @article{GrundherrJauernigUhl2021, author = {Grundherr, Michael von and Jauernig, Johanna and Uhl, Matthias}, title = {To condemn is not to punish}, volume = {12}, pages = {38}, journal = {Games}, subtitle = {an experiment on hypocrisy}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2073-4336}, doi = {https://doi.org/10.3390/g12020038}, year = {2021}, abstract = {Hypocrisy is the act of claiming moral standards to which one's own behavior does not conform. Instances of hypocrisy, such as the supposedly green furnishing group IKEA's selling of furniture made from illegally felled wood, are frequently reported in the media. In a controlled and incentivized experiment, we investigate how observers rate different types of hypocritical behavior and if this judgment also translates into punishment. Results show that observers do, indeed, condemn hypocritical behavior strongly. The aversion to deceptive behavior is, in fact, so strong that even purely self-deceptive behavior is regarded as blameworthy. Observers who score high in the moral identity test have particularly strong reactions to acts of hypocrisy. The moral condemnation of hypocritical behavior, however, fails to produce a proportional amount of punishment. Punishment seems to be driven more by the violation of the norm of fair distribution than by moral pretense. From the viewpoint of positive retributivism, it is problematic if neither formal nor informal punishment follows moral condemnation.}, language = {en} } @article{NanDelSerWalshetal.2022, author = {Nan, Yang and Del Ser, Javier and Walsh, Simon and Sch{\"o}nlieb, Carola and Roberts, Michael and Selby, Ian and Howard, Kit and Owen, John and Neville, Jon and Guiot, Julien and Ernst, Benoit and Pastor, Ana and Alberich-Bayarri, Angel and Menzel, Marion Irene and Walsh, Sean and Vos, Wim and Flerin, Nina and Charbonnier, Jean-Paul and Rikxoort, Eva van and Chatterjee, Avishek and Woodruff, Henry and Lambin, Philippe and Cerd{\´a}-Alberich, Leonor and Mart{\´i}-Bonmat{\´i}, Luis and Herrera, Francisco and Yang, Guang}, title = {Data harmonisation for information fusion in digital healthcare: A state-of-the-art systematic review, meta-analysis and future research directions}, volume = {2022}, journal = {Information Fusion}, number = {82}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1566-2535}, doi = {https://doi.org/10.1016/j.inffus.2022.01.001}, pages = {99 -- 122}, year = {2022}, abstract = {Removing the bias and variance of multicentre data has always been a challenge in large scale digital healthcare studies, which requires the ability to integrate clinical features extracted from data acquired by different scanners and protocols to improve stability and robustness. Previous studies have described various computational approaches to fuse single modality multicentre datasets. However, these surveys rarely focused on evaluation metrics and lacked a checklist for computational data harmonisation studies. In this systematic review, we summarise the computational data harmonisation approaches for multi-modality data in the digital healthcare field, including harmonisation strategies and evaluation metrics based on different theories. In addition, a comprehensive checklist that summarises common practices for data harmonisation studies is proposed to guide researchers to report their research findings more effectively. Last but not least, flowcharts presenting possible ways for methodology and metric selection are proposed and the limitations of different methods have been surveyed for future research}, language = {en} }