TY - INPR A1 - Fidelis, Eduardo A1 - Reway, Fabio A1 - Ribeiro, Herick Y. S. A1 - Campos, Pietro A1 - Huber, Werner A1 - Icking, Christian A1 - Faria, Lester A1 - Schön, Torsten T1 - Generation of Realistic Synthetic Raw Radar Data for Automated Driving Applications using Generative Adversarial Networks N2 - The main approaches for simulating FMCW radar are based on ray tracing, which is usually computationally intensive and do not account for background noise. This work proposes a faster method for FMCW radar simulation capable of generating synthetic raw radar data using generative adversarial networks (GAN). The code and pre-trained weights are open-source and available on GitHub. This method generates 16 simultaneous chirps, which allows the generated data to be used for the further development of algorithms for processing radar data (filtering and clustering). This can increase the potential for data augmentation, e.g., by generating data in non-existent or safety-critical scenarios that are not reproducible in real life. In this work, the GAN was trained with radar measurements of a motorcycle and used to generate synthetic raw radar data of a motorcycle traveling in a straight line. For generating this data, the distance of the motorcycle and Gaussian noise are used as input to the neural network. The synthetic generated radar chirps were evaluated using the Frechet Inception Distance (FID). Then, the Range-Azimuth (RA) map is calculated twice: first, based on synthetic data using this GAN and, second, based on real data. Based on these RA maps, an algorithm with adaptive threshold and edge detection is used for object detection. The results have shown that the data is realistic in terms of coherent radar reflections of the motorcycle and background noise based on the comparison of chirps, the RA maps and the object detection results. Thus, the proposed method in this work has shown to minimize the simulation-to-reality gap for the generation of radar data. UR - https://doi.org/10.48550/arXiv.2308.02632 Y1 - 2023 UR - https://doi.org/10.48550/arXiv.2308.02632 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59872 PB - arXiv CY - Ithaca ER - TY - INPR A1 - Han, Longfei A1 - Kefferpütz, Klaus A1 - Beyerer, Jürgen T1 - Decentralized Fusion of 3D Extended Object Tracking based on a B-Spline Shape Model N2 - Extended Object Tracking (EOT) exploits the high resolution of modern sensors for detailed environmental perception. Combined with decentralized fusion, it contributes to a more scalable and robust perception system. This paper investigates the decentralized fusion of 3D EOT using a B-spline curve based model. The spline curve is used to represent the side-view profile, which is then extruded with a width to form a 3D shape. We use covariance intersection (CI) for the decentralized fusion and discuss the challenge of applying it to EOT. We further evaluate the tracking result of the decentralized fusion with simulated and real datasets of traffic scenarios. We show that the CI-based fusion can significantly improve the tracking performance for sensors with unfavorable perspective. UR - https://doi.org/10.48550/arXiv.2504.18708 Y1 - 2025 UR - https://doi.org/10.48550/arXiv.2504.18708 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59648 PB - arXiv CY - Ithaca ER - TY - JOUR A1 - Hahn, Christoph A1 - Bednarz, Martin T1 - Economics of Polymer Electrolyte Membrane Fuel Cells JF - Tehnički glasnik N2 - Hydrogen is considered a key component of the renewable energy transition for the 21st century, with potential applications using fuel cells in the transportation sector, decentralized heating systems, and energy storage. However, the conversion from fossil fuels to hydrogen implies comprehensive research to address technological and socio economic challenges, enabling its widespread adoption. This paper discusses the economics of fuel cells. A cost analysis of the polymer electrolyte membrane fuel cells (PEMFC) is performed, and current market data and developments are presented. UR - https://doi.org/10.31803/tg-20250303145130 Y1 - 2025 UR - https://doi.org/10.31803/tg-20250303145130 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-59496 SN - 1848-5588 VL - 19 IS - si1 SP - 124 EP - 129 PB - University North CY - Koprivnica ER - TY - CHAP A1 - Knollmeyer, Simon A1 - Caymazer, Oğuz A1 - Koval, Leonid A1 - Akmal, Muhammad Uzair A1 - Asif, Saara A1 - Mathias, Selvine George A1 - Großmann, Daniel ED - Gruenwald, Le ED - Masciari, Elio ED - Bernardino, Jorge T1 - Benchmarking of Retrieval Augmented Generation: A Comprehensive Systematic Literature Review on Evaluation Dimensions, Evaluation Metrics and Datasets T2 - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2024) - Volume 3 N2 - Despite the rapid advancements in the field of Large Language Models (LLM), traditional benchmarks have proven to be inadequate for assessing the performance of Retrieval Augmented Generation (RAG) systems. Therefore, this paper presents a comprehensive systematic literature review of evaluation dimensions, metrics, and datasets for RAG systems. This review identifies key evaluation dimensions such as context relevance, faithfulness, answer relevance, correctness, and citation quality. For each evaluation dimension, several metrics and evaluators are proposed on how to assess them. This paper synthesizes the findings from 12 relevant papers and presents a concept matrix that categorizes each evaluation approach. The results provide a foundation for the development of robust evaluation frameworks and suitable datasets that are essential for the effective implementation and deployment of RAG systems in real-world applications. UR - https://doi.org/10.5220/0013065700003838 Y1 - 2024 UR - https://doi.org/10.5220/0013065700003838 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58342 SN - 978-989-758-716-0 SP - 137 EP - 148 PB - SciTePress CY - Setúbal ER - TY - CHAP A1 - Fadl, Islam A1 - Schön, Torsten A1 - Behret, Valentino A1 - Brandmeier, Thomas A1 - Palme, Frank A1 - Helmer, Thomas ED - Bashford-Rogers, Thomas ED - Meneveaux, Daniel ED - Ammi, Mehdi ED - Ziat, Mounia ED - Jänicke, Stefan ED - Purchase, Helen ED - Radeva, Petia ED - Furnari, Antonino ED - Bouatouch, Kadi ED - Sousa, A. Augusto T1 - Environment Setup and Model Benchmark of the MuFoRa Dataset T2 - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - (Volume 3) N2 - Adverse meteorological conditions, particularly fog and rain, present significant challenges to computer vision algorithms and autonomous systems. This work presents MuFoRa a novel, controllable, and measured multimodal dataset recorded at CARISSMA’s indoor test facility, specifically designed to assess perceptual difficulties in foggy and rainy environments. The dataset bridges research gap in the public benchmarking datasets, where quantifiable weather parameters are lacking. The proposed dataset comprises synchronized data from two sensor modalities: RGB stereo cameras and LiDAR sensors, captured under varying intensities of fog and rain. The dataset incorporates synchronized meteorological annotations, such as visibility through fog and precipitation levels of rain, and the study contributes a detailed explanation of the diverse weather effects observed during data collection in the methods section. The dataset’s utility is demonstrated through a baseline evaluation example, asse ssing the performance degradation of state-of-the-art YOLO11 and DETR 2D object detection algorithms under controlled and quantifiable adverse weather conditions. The public release of the dataset (https://doi.org/10.5281/zenodo.14175611) facilitates various benchmarking and quantitative assessments of advanced multimodal computer vision and deep learning models under the challenging conditions of fog and rain. UR - https://doi.org/10.5220/0013307900003912 Y1 - 2025 UR - https://doi.org/10.5220/0013307900003912 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58070 SN - 978-989-758-728-3 SP - 729 EP - 737 PB - SciTePress CY - Setúbal ER - TY - JOUR A1 - Jauernig, Johanna A1 - Uhl, Matthias A1 - Walkowitz, Gari T1 - People prefer moral discretion to algorithms BT - algorithm aversion beyond intransparency JF - Philosophy & Technology N2 - We explore aversion to the use of algorithms in moral decision-making. So far, this aversion has been explained mainly by the fear of opaque decisions that are potentially biased. Using incentivized experiments, we study which role the desire for human discretion in moral decision-making plays. This seems justified in light of evidence suggesting that people might not doubt the quality of algorithmic decisions, but still reject them. In our first study, we found that people prefer humans with decision-making discretion to algorithms that rigidly apply exogenously given human-created fairness principles to specific cases. In the second study, we found that people do not prefer humans to algorithms because they appreciate flesh-and-blood decision-makers per se, but because they appreciate humans’ freedom to transcend fairness principles at will. Our results contribute to a deeper understanding of algorithm aversion. They indicate that emphasizing the transparency of algorithms that clearly follow fairness principles might not be the only element for fostering societal algorithm acceptance and suggest reconsidering certain features of the decision-making process. UR - https://doi.org/10.1007/s13347-021-00495-y KW - algorithm aversion KW - artificial intelligence KW - moral discretion KW - behavioral ethics Y1 - 2022 UR - https://doi.org/10.1007/s13347-021-00495-y UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-23207 SN - 2210-5441 SN - 2210-5433 VL - 35 IS - 1 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Feier, Till A1 - Gogoll, Jan A1 - Uhl, Matthias T1 - Hiding Behind Machines: Artificial Agents May Help to Evade Punishment JF - Science and Engineering Ethics N2 - The transfer of tasks with sometimes far-reaching implications to autonomous systems raises a number of ethical questions. In addition to fundamental questions about the moral agency of these systems, behavioral issues arise. We investigate the empirically accessible question of whether the imposition of harm by an agent is systematically judged differently when the agent is artificial and not human. The results of a laboratory experiment suggest that decision-makers can actually avoid punishment more easily by delegating to machines than by delegating to other people. Our results imply that the availability of artificial agents could provide stronger incentives for decision-makers to delegate sensitive decisions. UR - https://doi.org/10.1007/s11948-022-00372-7 KW - automation KW - ethics KW - experiment KW - responsibility KW - algorithm Y1 - 2022 UR - https://doi.org/10.1007/s11948-022-00372-7 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-23155 SN - 1471-5546 SN - 1353-3452 VL - 28 IS - 2 PB - Springer Nature CY - Cham ER - TY - JOUR A1 - Jauernig, Johanna A1 - Uhl, Matthias A1 - Waldhof, Gabi T1 - Genetically Engineered Foods and Moral Absolutism: A Representative Study from Germany JF - Science and Engineering Ethics N2 - There is an ongoing debate about genetic engineering (GE) in food production. Supporters argue that it makes crops more resilient to stresses, such as drought or pests, and should be considered by researchers as a technology to address issues of global food security, whereas opponents put forward that GE crops serve only the economic interests of transnational agrifood-firms and have not yet delivered on their promises to address food shortage and nutrient supply. To address discourse failure regarding the GE debate, research needs to understand better what drives the divergent positions and which moral attitudes fuel the mental models of GE supporters and opponents. Hence, this study investigates moral attitudes regarding GE opposition and support in Germany. Results show that GE opponents are significantly more absolutist than supporters and significantly less likely to hold outcome-based views. Furthermore, GE opponents are more willing to donate for preventing GE admission than supporters are willing to donate for promoting GE admission. Our results shed light on why the divide between opponents and supporters in the German GE debate could remain stark and stable for so long. UR - https://doi.org/10.1007/s11948-023-00454-0 KW - Genetic engineering (GE) KW - Moral absolutism KW - Technology aversion KW - Moral convictions KW - GE debate KW - Consumer skepticism Y1 - 2023 UR - https://doi.org/10.1007/s11948-023-00454-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-39681 SN - 1471-5546 SN - 1353-3452 VL - 29 IS - 5 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Schönmann, Manuela A1 - Bodenschatz, Anja A1 - Uhl, Matthias A1 - Walkowitz, Gari T1 - The Care-Dependent are Less Averse to Care Robots: An Empirical Comparison of Attitudes JF - International Journal of Social Robotics N2 - A growing gap is emerging between the supply of and demand for professional caregivers, not least because of the ever-increasing average age of the world’s population. One strategy to address this growing gap in many regions is the use of care robots. Although there have been numerous ethical debates about the use of robots in nursing and elderly care, an important question remains unexamined: how do the potential recipients of such care perceive situations with care robots compared to situations with human caregivers? Using a large-scale experimental vignette study, we investigated people’s affective attitudes toward care robots. Specifically, we studied the influence of the caregiver’s nature on participants’ perceived comfort levels when confronted with different care scenarios in nursing homes. Our results show that the care-robot-related views of actual care recipients (i.e., people who are already affected by care dependency) differ substantially from the views of people who are not affected by care dependency. Those who do not (yet) rely on care placed care robots’ value far below that of human caregivers, especially in a service-oriented care scenario. This devaluation was not found among care recipients, whose perceived level of comfort was not influenced by the caregiver’s nature. These findings also proved robust when controlled for people’s gender, age, and general attitudes toward robots. UR - https://doi.org/10.1007/s12369-023-01003-2 KW - Care robots KW - Nursing care KW - Robot aversion KW - Affective attitudes KW - Vignette experiment Y1 - 2023 UR - https://doi.org/10.1007/s12369-023-01003-2 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-38099 SN - 1875-4805 VL - 15 IS - 6 SP - 1007 EP - 1024 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Krügel, Sebastian A1 - Uhl, Matthias T1 - Internal whistleblowing systems without proper sanctions may backfire JF - Journal of Business Economics N2 - Internal whistleblowing systems are supposed to fight misconduct within organizations. Because it is difficult to study their efficacy in the field, scientific evidence on their performance is rare. This is problematic, because these systems bind substantial resources and might generate the erroneous impression of compliance in a company in which misconduct is prevalent. We therefore suggest a versatilely extendable experimental workhorse that allows the systematic study of internal whistleblowing systems in the lab. As a first step, we tested the efficacy of whistleblowing systems if internal punishment for misconduct is mild and hesitant which is usually the case in practice, as several fraud surveys confirm. Our results show that under these conditions almost nobody blew the whistle, and misconduct occurred even more frequently with than without a whistleblowing system. The institutionalization of whistleblowing seemed to crowd out the intrinsic motivation to act compliantly. Moreover, when a whistleblowing system was either unavailable or not used, misconduct was highly contagious and spread quickly. Yet, when we implemented severe and ensured punishment for misconduct, whistleblowing systems could deter wrongdoing. In such a setting, people were willing to blow the whistle and the prevalence of misconduct dropped substantially. Altogether, our results highlight the interaction between institutions and preferences and can support the design of compliance measures within organizations. For compliance managers a key takeaway is that if companies preach a zero-tolerance policy, they should practice it as well. Otherwise, they might even worsen the situation. UR - https://doi.org/10.1007/s11573-023-01144-w KW - Misconduct KW - Whistleblowing KW - Punishment KW - Crowding out Y1 - 2023 UR - https://doi.org/10.1007/s11573-023-01144-w UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-32074 SN - 1861-8928 SN - 0044-2372 VL - 93 IS - 8 SP - 1355 EP - 1383 PB - Springer CY - Wiesbaden ER -