@article{WickHarteltPuppe2019,
  author    = {Wick, Christoph and Hartelt, Alexander and Puppe, Frank},
  title     = {Staff, symbol and melody detection of Medieval manuscripts written in square notation using deep Fully Convolutional Networks},
  series = {Applied Sciences},
  volume    = {9},
  journal   = {Applied Sciences},
  number    = {13},
  issn      = {2076-3417},
  doi       = {10.3390/app9132646},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-197248},
  year      = {2019},
  abstract  = {Even today, the automatic digitisation of scanned documents in general, but especially the automatic optical music recognition (OMR) of historical manuscripts, still remains an enormous challenge, since both handwritten musical symbols and text have to be identified. This paper focuses on the Medieval so-called square notation developed in the 11th-12th century, which is already composed of staff lines, staves, clefs, accidentals, and neumes that are roughly spoken connected single notes. The aim is to develop an algorithm that captures both the neumes, and in particular its melody, which can be used to reconstruct the original writing. Our pipeline is similar to the standard OMR approach and comprises a novel staff line and symbol detection algorithm based on deep Fully Convolutional Networks (FCN), which perform pixel-based predictions for either staff lines or symbols and their respective types. Then, the staff line detection combines the extracted lines to staves and yields an F\(_1\) -score of over 99\% for both detecting lines and complete staves. For the music symbol detection, we choose a novel approach that skips the step to identify neumes and instead directly predicts note components (NCs) and their respective affiliation to a neume. Furthermore, the algorithm detects clefs and accidentals. Our algorithm predicts the symbol sequence of a staff with a diplomatic symbol accuracy rate (dSAR) of about 87\%, which includes symbol type and location. If only the NCs without their respective connection to a neume, all clefs and accidentals are of interest, the algorithm reaches an harmonic symbol accuracy rate (hSAR) of approximately 90\%. In general, the algorithm recognises a symbol in the manuscript with an F\(_1\) -score of over 96\%.},
  language  = {en}
}
@article{WamserSeufertHalletal.2021,
  author    = {Wamser, Florian and Seufert, Anika and Hall, Andrew and Wunderer, Stefan and Hoßfeld, Tobias},
  title     = {Valid statements by the crowd: statistical measures for precision in crowdsourced mobile measurements},
  series = {Network},
  volume    = {1},
  journal   = {Network},
  number    = {2},
  issn      = {2673-8732},
  doi       = {10.3390/network1020013},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284154},
  pages     = {215 -- 232},
  year      = {2021},
  abstract  = {Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user's perspective on a large scale. Here, network measurements are performed directly on the end-users' devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider.},
  language  = {en}
}
@article{UnruhLandeckOberdoerferetal.2021,
  author    = {Unruh, Fabian and Landeck, Maximilian and Oberd{\"o}rfer, Sebastian and Lugrin, Jean-Luc and Latoschik, Marc Erich},
  title     = {The Influence of Avatar Embodiment on Time Perception - Towards VR for Time-Based Therapy},
  series = {Frontiers in Virtual Reality},
  volume    = {2},
  journal   = {Frontiers in Virtual Reality},
  doi       = {10.3389/frvir.2021.658509},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-259076},
  pages     = {658509},
  year      = {2021},
  abstract  = {Psycho-pathological conditions, such as depression or schizophrenia, are often accompanied by a distorted perception of time. People suffering from this conditions often report that the passage of time slows down considerably and that they are "stuck in time." Virtual Reality (VR) could potentially help to diagnose and maybe treat such mental conditions. However, the conditions in which a VR simulation could correctly diagnose a time perception deviation are still unknown. In this paper, we present an experiment investigating the difference in time experience with and without a virtual body in VR, also known as avatar. The process of substituting a person's body with a virtual body is called avatar embodiment. Numerous studies demonstrated interesting perceptual, emotional, behavioral, and psychological effects caused by avatar embodiment. However, the relations between time perception and avatar embodiment are still unclear. Whether or not the presence or absence of an avatar is already influencing time perception is still open to question. Therefore, we conducted a between-subjects design with and without avatar embodiment as well as a real condition (avatar vs. no-avatar vs. real). A group of 105 healthy subjects had to wait for seven and a half minutes in a room without any distractors (e.g., no window, magazine, people, decoration) or time indicators (e.g., clocks, sunlight). The virtual environment replicates the real physical environment. Participants were unaware that they will be asked to estimate their waiting time duration as well as describing their experience of the passage of time at a later stage. Our main finding shows that the presence of an avatar is leading to a significantly faster perceived passage of time. It seems to be promising to integrate avatar embodiment in future VR time-based therapy applications as they potentially could modulate a user's perception of the passage of time. We also found no significant difference in time perception between the real and the VR conditions (avatar, no-avatar), but further research is needed to better understand this outcome.},
  language  = {en}
}
@article{TsouliasJoerissenNuechter2022,
  author    = {Tsoulias, Nikos and J{\"o}rissen, Sven and N{\"u}chter, Andreas},
  title     = {An approach for monitoring temperature on fruit surface by means of thermal point cloud},
  series = {MethodsX},
  volume    = {9},
  journal   = {MethodsX},
  issn      = {2215-0161},
  doi       = {10.1016/j.mex.2022.101712},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300270},
  year      = {2022},
  abstract  = {Heat and excessive solar radiation can produce abiotic stresses during apple maturation, resulting fruit quality. Therefore, the monitoring of temperature on fruit surface (FST) over the growing period can allow to identify thresholds, above of which several physiological disorders such as sunburn may occur in apple. The current approaches neglect spatial variation of FST and have reduced repeatability, resulting in unreliable predictions. In this study, LiDAR laser scanning and thermal imaging were employed to detect the temperature on fruit surface by means of 3D point cloud. A process for calibrating the two sensors based on an active board target and producing a 3D thermal point cloud was suggested. After calibration, the sensor system was utilised to scan the fruit trees, while temperature values assigned in the corresponding 3D point cloud were based on the extrinsic calibration. Whereas a fruit detection algorithm was performed to segment the FST from each apple. • The approach allows the calibration of LiDAR laser scanner with thermal camera in order to produce a 3D thermal point cloud. • The method can be applied in apple trees for segmenting FST in 3D. Whereas the approach can be utilised to predict several physiological disorders including sunburn on fruit surface.},
  language  = {en}
}
@article{ToepferCorovicFetteetal.2015,
  author    = {Toepfer, Martin and Corovic, Hamo and Fette, Georg and Kl{\"u}gl, Peter and St{\"o}rk, Stefan and Puppe, Frank},
  title     = {Fine-grained information extraction from German transthoracic echocardiography reports},
  series = {BMC Medical Informatics and Decision Making},
  volume    = {15},
  journal   = {BMC Medical Informatics and Decision Making},
  number    = {91},
  doi       = {doi:10.1186/s12911-015-0215-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-125509},
  year      = {2015},
  abstract  = {Background Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of W{\"u}rzburg. Methods A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts. Results The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 \% of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout. Conclusions The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of W{\"u}rzburg. Extracted results populate a clinical data warehouse which supports clinical research.},
  language  = {en}
}
@article{SirbuBeckerCaminitietal.2015,
  author    = {S{\^i}rbu, Alina and Becker, Martin and Caminiti, Saverio and De Baets, Bernard and Elen, Bart and Francis, Louise and Gravino, Pietro and Hotho, Andreas and Ingarra, Stefano and Loreto, Vittorio and Molino, Andrea and Mueller, Juergen and Peters, Jan and Ricchiuti, Ferdinando and Saracino, Fabio and Servedio, Vito D.P. and Stumme, Gerd and Theunis, Jan and Tria, Francesca and Van den Bossche, Joris},
  title     = {Participatory Patterns in an International Air Quality Monitoring Initiative},
  series = {PLoS ONE},
  volume    = {10},
  journal   = {PLoS ONE},
  number    = {8},
  doi       = {10.1371/journal. pone.0136763},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-151379},
  pages     = {e0136763},
  year      = {2015},
  abstract  = {The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.},
  language  = {en}
}
@article{SteiningerKobsDavidsonetal.2021,
  author    = {Steininger, Michael and Kobs, Konstantin and Davidson, Padraig and Krause, Anna and Hotho, Andreas},
  title     = {Density-based weighting for imbalanced regression},
  series = {Machine Learning},
  volume    = {110},
  journal   = {Machine Learning},
  number    = {8},
  issn      = {1573-0565},
  doi       = {10.1007/s10994-021-06023-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-269177},
  pages     = {2187-2211},
  year      = {2021},
  abstract  = {In many real world settings, imbalanced data impedes model performance of learning algorithms, like neural networks, mostly for rare cases. This is especially problematic for tasks focusing on these rare occurrences. For example, when estimating precipitation, extreme rainfall events are scarce but important considering their potential consequences. While there are numerous well studied solutions for classification settings, most of them cannot be applied to regression easily. Of the few solutions for regression tasks, barely any have explored cost-sensitive learning which is known to have advantages compared to sampling-based methods in classification tasks. In this work, we propose a sample weighting approach for imbalanced regression datasets called DenseWeight and a cost-sensitive learning approach for neural network regression with imbalanced data called DenseLoss based on our weighting scheme. DenseWeight weights data points according to their target value rarities through kernel density estimation (KDE). DenseLoss adjusts each data point's influence on the loss according to DenseWeight, giving rare data points more influence on model training compared to common data points. We show on multiple differently distributed datasets that DenseLoss significantly improves model performance for rare data points through its density-based weighting scheme. Additionally, we compare DenseLoss to the state-of-the-art method SMOGN, finding that our method mostly yields better performance. Our approach provides more control over model training as it enables us to actively decide on the trade-off between focusing on common or rare cases through a single hyperparameter, allowing the training of better models for rare data points.},
  language  = {en}
}
@article{SteiningerAbelZiegleretal.2023,
  author    = {Steininger, Michael and Abel, Daniel and Ziegler, Katrin and Krause, Anna and Paeth, Heiko and Hotho, Andreas},
  title     = {ConvMOS: climate model output statistics with deep learning},
  series = {Data Mining and Knowledge Discovery},
  volume    = {37},
  journal   = {Data Mining and Knowledge Discovery},
  number    = {1},
  issn      = {1384-5810},
  doi       = {10.1007/s10618-022-00877-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324213},
  pages     = {136-166},
  year      = {2023},
  abstract  = {Climate models are the tool of choice for scientists researching climate change. Like all models they suffer from errors, particularly systematic and location-specific representation errors. One way to reduce these errors is model output statistics (MOS) where the model output is fitted to observational data with machine learning. In this work, we assess the use of convolutional Deep Learning climate MOS approaches and present the ConvMOS architecture which is specifically designed based on the observation that there are systematic and location-specific errors in the precipitation estimates of climate models. We apply ConvMOS models to the simulated precipitation of the regional climate model REMO, showing that a combination of per-location model parameters for reducing location-specific errors and global model parameters for reducing systematic errors is indeed beneficial for MOS performance. We find that ConvMOS models can reduce errors considerably and perform significantly better than three commonly used MOS approaches and plain ResNet and U-Net models in most cases. Our results show that non-linear MOS models underestimate the number of extreme precipitation events, which we alleviate by training models specialized towards extreme precipitation events with the imbalanced regression method DenseLoss. While we consider climate MOS, we argue that aspects of ConvMOS may also be beneficial in other domains with geospatial data, such as air pollution modeling or weather forecasts.},
  subject      = {Klima},
  language  = {en}
}
@article{SteinhaeusserOberdoerfervonMammenetal.2022,
  author    = {Steinhaeusser, Sophia C. and Oberd{\"o}rfer, Sebastian and von Mammen, Sebastian and Latoschik, Marc Erich and Lugrin, Birgit},
  title     = {Joyful adventures and frightening places - designing emotion-inducing virtual environments},
  series = {Frontiers in Virtual Reality},
  volume    = {3},
  journal   = {Frontiers in Virtual Reality},
  issn      = {2673-4192},
  doi       = {10.3389/frvir.2022.919163},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284831},
  year      = {2022},
  abstract  = {Virtual environments (VEs) can evoke and support emotions, as experienced when playing emotionally arousing games. We theoretically approach the design of fear and joy evoking VEs based on a literature review of empirical studies on virtual and real environments as well as video games' reviews and content analyses. We define the design space and identify central design elements that evoke specific positive and negative emotions. Based on that, we derive and present guidelines for emotion-inducing VE design with respect to design themes, colors and textures, and lighting configurations. To validate our guidelines in two user studies, we 1) expose participants to 360° videos of VEs designed following the individual guidelines and 2) immerse them in a neutral, positive and negative emotion-inducing VEs combining all respective guidelines in Virtual Reality. The results support our theoretically derived guidelines by revealing significant differences in terms of fear and joy induction.},
  language  = {en}
}
@article{SeufertSchroederSeufert2021,
  author    = {Seufert, Anika and Schr{\"o}der, Svenja and Seufert, Michael},
  title     = {Delivering User Experience over Networks: Towards a Quality of Experience Centered Design Cycle for Improved Design of Networked Applications},
  series = {SN Computer Science},
  volume    = {2},
  journal   = {SN Computer Science},
  number    = {6},
  issn      = {2661-8907},
  doi       = {10.1007/s42979-021-00851-x},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-271762},
  year      = {2021},
  abstract  = {To deliver the best user experience (UX), the human-centered design cycle (HCDC) serves as a well-established guideline to application developers. However, it does not yet cover network-specific requirements, which become increasingly crucial, as most applications deliver experience over the Internet. The missing network-centric view is provided by Quality of Experience (QoE), which could team up with UX towards an improved overall experience. By considering QoE aspects during the development process, it can be achieved that applications become network-aware by design. In this paper, the Quality of Experience Centered Design Cycle (QoE-CDC) is proposed, which provides guidelines on how to design applications with respect to network-specific requirements and QoE. Its practical value is showcased for popular application types and validated by outlining the design of a new smartphone application. We show that combining HCDC and QoE-CDC will result in an application design, which reaches a high UX and avoids QoE degradation.},
  language  = {en}
}
@article{SeufertPoigneeSeufertetal.2023,
  author    = {Seufert, Anika and Poign{\´e}e, Fabian and Seufert, Michael and Hoßfeld, Tobias},
  title     = {Share and multiply: modeling communication and generated traffic in private WhatsApp groups},
  series = {IEEE Access},
  volume    = {11},
  journal   = {IEEE Access},
  doi       = {10.1109/ACCESS.2023.3254913},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-349430},
  pages     = {25401-25414},
  year      = {2023},
  abstract  = {Group-based communication is a highly popular communication paradigm, which is especially prominent in mobile instant messaging (MIM) applications, such as WhatsApp. Chat groups in MIM applications facilitate the sharing of various types of messages (e.g., text, voice, image, video) among a large number of participants. As each message has to be transmitted to every other member of the group, which multiplies the traffic, this has a massive impact on the underlying communication networks. However, most chat groups are private and network operators cannot obtain deep insights into MIM communication via network measurements due to end-to-end encryption. Thus, the generation of traffic is not well understood, given that it depends on sizes of communication groups, speed of communication, and exchanged message types. In this work, we provide a huge data set of 5,956 private WhatsApp chat histories, which contains over 76 million messages from more than 117,000 users. We describe and model the properties of chat groups and users, and the communication within these chat groups, which gives unprecedented insights into private MIM communication. In addition, we conduct exemplary measurements for the most popular message types, which empower the provided models to estimate the traffic over time in a chat group.},
  language  = {en}
}
@article{SeufertPoigneeHossfeldetal.2022,
  author    = {Seufert, Anika and Poign{\´e}e, Fabian and Hoßfeld, Tobias and Seufert, Michael},
  title     = {Pandemic in the digital age: analyzing WhatsApp communication behavior before, during, and after the COVID-19 lockdown},
  series = {Humanities and Social Sciences Communications},
  volume    = {9},
  journal   = {Humanities and Social Sciences Communications},
  doi       = {10.1057/s41599-022-01161-0},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300261},
  year      = {2022},
  abstract  = {The strict restrictions introduced by the COVID-19 lockdowns, which started from March 2020, changed people's daily lives and habits on many different levels. In this work, we investigate the impact of the lockdown on the communication behavior in the mobile instant messaging application WhatsApp. Our evaluations are based on a large dataset of 2577 private chat histories with 25,378,093 messages from 51,973 users. The analysis of the one-to-one and group conversations confirms that the lockdown severely altered the communication in WhatsApp chats compared to pre-pandemic time ranges. In particular, we observe short-term effects, which caused an increased message frequency in the first lockdown months and a shifted communication activity during the day in March and April 2020. Moreover, we also see long-term effects of the ongoing pandemic situation until February 2021, which indicate a change of communication behavior towards more regular messaging, as well as a persisting change in activity during the day. The results of our work show that even anonymized chat histories can tell us a lot about people's behavior and especially behavioral changes during the COVID-19 pandemic and thus are of great relevance for behavioral researchers. Furthermore, looking at the pandemic from an Internet provider perspective, these insights can be used during the next pandemic, or if the current COVID-19 situation worsens, to adapt communication networks to the changed usage behavior early on and thus avoid network congestion.},
  language  = {en}
}
@article{SchloerRingHotho2020,
  author    = {Schl{\"o}r, Daniel and Ring, Markus and Hotho, Andreas},
  title     = {iNALU: Improved Neural Arithmetic Logic Unit},
  series = {Frontiers in Artificial Intelligence},
  volume    = {3},
  journal   = {Frontiers in Artificial Intelligence},
  issn      = {2624-8212},
  doi       = {10.3389/frai.2020.00071},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-212301},
  year      = {2020},
  abstract  = {Neural networks have to capture mathematical relationships in order to learn various tasks. They approximate these relations implicitly and therefore often do not generalize well. The recently proposed Neural Arithmetic Logic Unit (NALU) is a novel neural architecture which is able to explicitly represent the mathematical relationships by the units of the network to learn operations such as summation, subtraction or multiplication. Although NALUs have been shown to perform well on various downstream tasks, an in-depth analysis reveals practical shortcomings by design, such as the inability to multiply or divide negative input values or training stability issues for deeper networks. We address these issues and propose an improved model architecture. We evaluate our model empirically in various settings from learning basic arithmetic operations to more complex functions. Our experiments indicate that our model solves stability issues and outperforms the original NALU model in means of arithmetic precision and convergence.},
  language  = {en}
}
@article{RiedmannSchaperLugrin2022,
  author    = {Riedmann, Anna and Schaper, Philipp and Lugrin, Birgit},
  title     = {Integration of a social robot and gamification in adult learning and effects on motivation, engagement and performance},
  series = {AI \& Society},
  journal   = {AI \& Society},
  issn      = {0951-5666},
  doi       = {10.1007/s00146-022-01514-y},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324208},
  year      = {2022},
  abstract  = {Learning is a central component of human life and essential for personal development. Therefore, utilizing new technologies in the learning context and exploring their combined potential are considered essential to support self-directed learning in a digital age. A learning environment can be expanded by various technical and content-related aspects. Gamification in the form of elements from video games offers a potential concept to support the learning process. This can be supplemented by technology-supported learning. While the use of tablets is already widespread in the learning context, the integration of a social robot can provide new perspectives on the learning process. However, simply adding new technologies such as social robots or gamification to existing systems may not automatically result in a better learning environment. In the present study, game elements as well as a social robot were integrated separately and conjointly into a learning environment for basic Spanish skills, with a follow-up on retained knowledge. This allowed us to investigate the respective and combined effects of both expansions on motivation, engagement and learning effect. This approach should provide insights into the integration of both additions in an adult learning context. We found that the additions of game elements and the robot did not significantly improve learning, engagement or motivation. Based on these results and a literature review, we outline relevant factors for meaningful integration of gamification and social robots in learning environments in adult learning.},
  language  = {en}
}
@article{Puppe2022,
  author    = {Puppe, Frank},
  title     = {Gesellschaftliche Perspektiven einer fachspezifischen KI f{\"u}r automatisierte Entscheidungen},
  series = {Informatik Spektrum},
  volume    = {45},
  journal   = {Informatik Spektrum},
  number    = {2},
  issn      = {0170-6012},
  doi       = {10.1007/s00287-022-01443-6},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-324197},
  pages     = {88-95},
  year      = {2022},
  abstract  = {Die k{\"u}nstliche Intelligenz (KI) entwickelt sich rasant und hat bereits eindrucksvolle Erfolge zu verzeichnen, darunter {\"u}bermenschliche Kompetenz in den meisten Spielen und vielen Quizshows, intelligente Suchmaschinen, individualisierte Werbung, Spracherkennung, -ausgabe und -{\"u}bersetzung auf sehr hohem Niveau und hervorragende Leistungen bei der Bildverarbeitung, u. a. in der Medizin, der optischen Zeichenerkennung, beim autonomen Fahren, aber auch beim Erkennen von Menschen auf Bildern und Videos oder bei Deep Fakes f{\"u}r Fotos und Videos. Es ist zu erwarten, dass die KI auch in der Entscheidungsfindung Menschen {\"u}bertreffen wird; ein alter Traum der Expertensysteme, der durch Lernverfahren, Big Data und Zugang zu dem gesammelten Wissen im Web in greifbare N{\"a}he r{\"u}ckt. Gegenstand dieses Beitrags sind aber weniger die technischen Entwicklungen, sondern m{\"o}gliche gesellschaftliche Auswirkungen einer spezialisierten, kompetenten KI f{\"u}r verschiedene Bereiche der autonomen, d. h. nicht nur unterst{\"u}tzenden Entscheidungsfindung: als Fußballschiedsrichter, in der Medizin, f{\"u}r richterliche Entscheidungen und sehr spekulativ auch im politischen Bereich. Dabei werden Vor- und Nachteile dieser Szenarien aus gesellschaftlicher Sicht diskutiert.},
  subject      = {K{\"u}nstliche Intelligenz},
  language  = {de}
}
@article{PrantlZeckBaueretal.2022,
  author    = {Prantl, Thomas and Zeck, Timo and Bauer, Andre and Ten, Peter and Prantl, Dominik and Yahya, Ala Eddine Ben and Ifflaender, Lukas and Dmitrienko, Alexandra and Krupitzer, Christian and Kounev, Samuel},
  title     = {A Survey on Secure Group Communication Schemes With Focus on IoT Communication},
  series = {IEEE Access},
  volume    = {10},
  journal   = {IEEE Access},
  doi       = {10.1109/ACCESS.2022.3206451},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300257},
  pages     = {99944 -- 99962},
  year      = {2022},
  abstract  = {A key feature for Internet of Things (IoT) is to control what content is available to each user. To handle this access management, encryption schemes can be used. Due to the diverse usage of encryption schemes, there are various realizations of 1-to-1, 1-to-n, and n-to-n schemes in the literature. This multitude of encryption methods with a wide variety of properties presents developers with the challenge of selecting the optimal method for a particular use case, which is further complicated by the fact that there is no overview of existing encryption schemes. To fill this gap, we envision a cryptography encyclopedia providing such an overview of existing encryption schemes. In this survey paper, we take a first step towards such an encyclopedia by creating a sub-encyclopedia for secure group communication (SGC) schemes, which belong to the n-to-n category. We extensively surveyed the state-of-the-art and classified 47 different schemes. More precisely, we provide (i) a comprehensive overview of the relevant security features, (ii) a set of relevant performance metrics, (iii) a classification for secure group communication schemes, and (iv) workflow descriptions of the 47 schemes. Moreover, we perform a detailed performance and security evaluation of the 47 secure group communication schemes. Based on this evaluation, we create a guideline for the selection of secure group communication schemes.},
  language  = {en}
}
@article{PfitznerMayNuechter2018,
  author    = {Pfitzner, Christian and May, Stefan and N{\"u}chter, Andreas},
  title     = {Body weight estimation for dose-finding and health monitoring of lying, standing and walking patients based on RGB-D data},
  series = {Sensors},
  volume    = {18},
  journal   = {Sensors},
  number    = {5},
  doi       = {10.3390/s18051311},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176642},
  pages     = {1311},
  year      = {2018},
  abstract  = {This paper describes the estimation of the body weight of a person in front of an RGB-D camera. A survey of different methods for body weight estimation based on depth sensors is given. First, an estimation of people standing in front of a camera is presented. Second, an approach based on a stream of depth images is used to obtain the body weight of a person walking towards a sensor. The algorithm first extracts features from a point cloud and forwards them to an artificial neural network (ANN) to obtain an estimation of body weight. Besides the algorithm for the estimation, this paper further presents an open-access dataset based on measurements from a trauma room in a hospital as well as data from visitors of a public event. In total, the dataset contains 439 measurements. The article illustrates the efficiency of the approach with experiments with persons lying down in a hospital, standing persons, and walking persons. Applicable scenarios for the presented algorithm are body weight-related dosing of emergency patients.},
  language  = {en}
}
@article{ObremskiLugrinSchaperetal.2021,
  author    = {Obremski, David and Lugrin, Jean-Luc and Schaper, Philipp and Lugrin, Birgit},
  title     = {Non-native speaker perception of Intelligent Virtual Agents in two languages: the impact of amount and type of grammatical mistakes},
  series = {Journal on Multimodal User Interfaces},
  volume    = {15},
  journal   = {Journal on Multimodal User Interfaces},
  number    = {2},
  issn      = {1783-8738},
  doi       = {10.1007/s12193-021-00369-9},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-269984},
  pages     = {229-238},
  year      = {2021},
  abstract  = {Having a mixed-cultural membership becomes increasingly common in our modern society. It is thus beneficial in several ways to create Intelligent Virtual Agents (IVAs) that reflect a mixed-cultural background as well, e.g., for educational settings. For research with such IVAs, it is essential that they are classified as non-native by members of a target culture. In this paper, we focus on variations of IVAs' speech to create the impression of non-native speakers that are identified as such by speakers of two different mother tongues. In particular, we investigate grammatical mistakes and identify thresholds beyond which the agents is clearly categorised as a non-native speaker. Therefore, we conducted two experiments: one for native speakers of German, and one for native speakers of English. Results of the German study indicate that beyond 10\% of word order mistakes and 25\% of infinitive mistakes German-speaking IVAs are perceived as non-native speakers. Results of the English study indicate that beyond 50\% of omission mistakes and 50\% of infinitive mistakes English-speaking IVAs are perceived as non-native speakers. We believe these thresholds constitute helpful guidelines for computational approaches of non-native speaker generation, simplifying research with IVAs in mixed-cultural settings.},
  language  = {en}
}
@article{ObremskiFriedrichHaaketal.2022,
  author    = {Obremski, David and Friedrich, Paula and Haak, Nora and Schaper, Philipp and Lugrin, Birgit},
  title     = {The impact of mixed-cultural speech on the stereotypical perception of a virtual robot},
  series = {Frontiers in Robotics and AI},
  volume    = {9},
  journal   = {Frontiers in Robotics and AI},
  issn      = {2296-9144},
  doi       = {10.3389/frobt.2022.983955},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-293531},
  year      = {2022},
  abstract  = {Despite the fact that mixed-cultural backgrounds become of increasing importance in our daily life, the representation of multiple cultural backgrounds in one entity is still rare in socially interactive agents (SIAs). This paper's contribution is twofold. First, it provides a survey of research on mixed-cultured SIAs. Second, it presents a study investigating how mixed-cultural speech (in this case, non-native accent) influences how a virtual robot is perceived in terms of personality, warmth, competence and credibility. Participants with English or German respectively as their first language watched a video of a virtual robot speaking in either standard English or German-accented English. It was expected that the German-accented speech would be rated more positively by native German participants as well as elicit the German stereotypes credibility and conscientiousness for both German and English participants. Contrary to the expectations, German participants rated the virtual robot lower in terms of competence and credibility when it spoke with a German accent, whereas English participants perceived the virtual robot with a German accent as more credible compared to the version without an accent. Both the native English and native German listeners classified the virtual robot with a German accent as significantly more neurotic than the virtual robot speaking standard English. This work shows that by solely implementing a non-native accent in a virtual robot, stereotypes are partly transferred. It also shows that the implementation of a non-native accent leads to differences in the perception of the virtual robot.},
  language  = {en}
}
@article{OberdoerferLatoschik2019,
  author    = {Oberd{\"o}rfer, Sebastian and Latoschik, Marc Erich},
  title     = {Knowledge encoding in game mechanics: transfer-oriented knowledge learning in desktop-3D and VR},
  series = {International Journal of Computer Games Technology},
  volume    = {2019},
  journal   = {International Journal of Computer Games Technology},
  doi       = {10.1155/2019/7626349},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-201159},
  pages     = {7626349},
  year      = {2019},
  abstract  = {Affine Transformations (ATs) are a complex and abstract learning content. Encoding the AT knowledge in Game Mechanics (GMs) achieves a repetitive knowledge application and audiovisual demonstration. Playing a serious game providing these GMs leads to motivating and effective knowledge learning. Using immersive Virtual Reality (VR) has the potential to even further increase the serious game's learning outcome and learning quality. This paper compares the effectiveness and efficiency of desktop-3D and VR in respect to the achieved learning outcome. Also, the present study analyzes the effectiveness of an enhanced audiovisual knowledge encoding and the provision of a debriefing system. The results validate the effectiveness of the knowledge encoding in GMs to achieve knowledge learning. The study also indicates that VR is beneficial for the overall learning quality and that an enhanced audiovisual encoding has only a limited effect on the learning outcome.},
  language  = {en}
}