@techreport{SavvidisRothTutsch2022, type = {Working Paper}, author = {Savvidis, Dimitrios and Roth, Robert and Tutsch, Dietmar}, title = {Static Evaluation of a Wheel-Topology for an SDN-based Network Usecase}, series = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)}, journal = {W{\"u}rzburg Workshop on Next-Generation Communication Networks (WueWoWas'22)}, doi = {10.25972/OPUS-28071}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280715}, pages = {3}, year = {2022}, abstract = {The increased occurrence of Software-Defined-Networking (SDN) not only improves the dynamics and maintenance of network architectures, but also opens up new use cases and application possibilities. Based on these observations, we propose a new network topology consisting of a star and a ring topology. This hybrid topology will be called wheel topology in this paper. We have considered the static characteristics of the wheel topology and compare them with known other topologies.}, subject = {Datennetz}, language = {en} } @article{LohWamserPoigneeetal.2022, author = {Loh, Frank and Wamser, Florian and Poign{\´e}e, Fabian and Geißler, Stefan and Hoßfeld, Tobias}, title = {YouTube Dataset on Mobile Streaming for Internet Traffic Modeling and Streaming Analysis}, series = {Scientific Data}, volume = {9}, journal = {Scientific Data}, number = {1}, doi = {10.1038/s41597-022-01418-y}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300240}, year = {2022}, abstract = {Around 4.9 billion Internet users worldwide watch billions of hours of online video every day. As a result, streaming is by far the predominant type of traffic in communication networks. According to Google statistics, three out of five video views come from mobile devices. Thus, in view of the continuous technological advances in end devices and increasing mobile use, datasets for mobile streaming are indispensable in research but only sparsely dealt with in literature so far. With this public dataset, we provide 1,081 hours of time-synchronous video measurements at network, transport, and application layer with the native YouTube streaming client on mobile devices. The dataset includes 80 network scenarios with 171 different individual bandwidth settings measured in 5,181 runs with limited bandwidth, 1,939 runs with emulated 3 G/4 G traces, and 4,022 runs with pre-defined bandwidth changes. This corresponds to 332 GB video payload. We present the most relevant quality indicators for scientific use, i.e., initial playback delay, streaming video quality, adaptive video quality changes, video rebuffering events, and streaming phases.}, 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{LatoschikWienrich2022, author = {Latoschik, Marc Erich and Wienrich, Carolin}, title = {Congruence and plausibility, not presence: pivotal conditions for XR experiences and effects, a novel approach}, series = {Frontiers in Virtual Reality}, volume = {3}, journal = {Frontiers in Virtual Reality}, issn = {2673-4192}, doi = {10.3389/frvir.2022.694433}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-284787}, year = {2022}, abstract = {Presence is often considered the most important quale describing the subjective feeling of being in a computer-generated and/or computer-mediated virtual environment. The identification and separation of orthogonal presence components, i.e., the place illusion and the plausibility illusion, has been an accepted theoretical model describing Virtual Reality (VR) experiences for some time. This perspective article challenges this presence-oriented VR theory. First, we argue that a place illusion cannot be the major construct to describe the much wider scope of virtual, augmented, and mixed reality (VR, AR, MR: or XR for short). Second, we argue that there is no plausibility illusion but merely plausibility, and we derive the place illusion caused by the congruent and plausible generation of spatial cues and similarly for all the current model's so-defined illusions. Finally, we propose congruence and plausibility to become the central essential conditions in a novel theoretical model describing XR experiences and effects.}, language = {en} } @article{LandeckAlvarezIgarzabalUnruhetal.2022, author = {Landeck, Maximilian and Alvarez Igarz{\´a}bal, Federico and Unruh, Fabian and Habenicht, Hannah and Khoshnoud, Shiva and Wittmann, Marc and Lugrin, Jean-Luc and Latoschik, Marc Erich}, title = {Journey through a virtual tunnel: Simulated motion and its effects on the experience of time}, series = {Frontiers in Virtual Reality}, volume = {3}, journal = {Frontiers in Virtual Reality}, issn = {2673-4192}, doi = {10.3389/frvir.2022.1059971}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-301519}, year = {2022}, abstract = {This paper examines the relationship between time and motion perception in virtual environments. Previous work has shown that the perception of motion can affect the perception of time. We developed a virtual environment that simulates motion in a tunnel and measured its effects on the estimation of the duration of time, the speed at which perceived time passes, and the illusion of self-motion, also known as vection. When large areas of the visual field move in the same direction, vection can occur; observers often perceive this as self-motion rather than motion of the environment. To generate different levels of vection and investigate its effects on time perception, we developed an abstract procedural tunnel generator. The generator can simulate different speeds and densities of tunnel sections (visibly distinguishable sections that form the virtual tunnel), as well as the degree of embodiment of the user avatar (with or without virtual hands). We exposed participants to various tunnel simulations with different durations, speeds, and densities in a remote desktop and a virtual reality (VR) laboratory study. Time passed subjectively faster under high-speed and high-density conditions in both studies. The experience of self-motion was also stronger under high-speed and high-density conditions. Both studies revealed a significant correlation between the perceived passage of time and perceived self-motion. Subjects in the virtual reality study reported a stronger self-motion experience, a faster perceived passage of time, and shorter time estimates than subjects in the desktop study. Our results suggest that a virtual tunnel simulation can manipulate time perception in virtual reality. We will explore these results for the development of virtual reality applications for therapeutic approaches in our future work. This could be particularly useful in treating disorders like depression, autism, and schizophrenia, which are known to be associated with distortions in time perception. For example, the tunnel could be therapeutically applied by resetting patients' time perceptions by exposing them to the tunnel under different conditions, such as increasing or decreasing perceived time.}, 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{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{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{HentschelKobsHotho2022, author = {Hentschel, Simon and Kobs, Konstantin and Hotho, Andreas}, title = {CLIP knows image aesthetics}, series = {Frontiers in Artificial Intelligence}, volume = {5}, journal = {Frontiers in Artificial Intelligence}, issn = {2624-8212}, doi = {10.3389/frai.2022.976235}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-297150}, year = {2022}, abstract = {Most Image Aesthetic Assessment (IAA) methods use a pretrained ImageNet classification model as a base to fine-tune. We hypothesize that content classification is not an optimal pretraining task for IAA, since the task discourages the extraction of features that are useful for IAA, e.g., composition, lighting, or style. On the other hand, we argue that the Contrastive Language-Image Pretraining (CLIP) model is a better base for IAA models, since it has been trained using natural language supervision. Due to the rich nature of language, CLIP needs to learn a broad range of image features that correlate with sentences describing the image content, composition, environments, and even subjective feelings about the image. While it has been shown that CLIP extracts features useful for content classification tasks, its suitability for tasks that require the extraction of style-based features like IAA has not yet been shown. We test our hypothesis by conducting a three-step study, investigating the usefulness of features extracted by CLIP compared to features obtained from the last layer of a comparable ImageNet classification model. In each step, we get more computationally expensive. First, we engineer natural language prompts that let CLIP assess an image's aesthetic without adjusting any weights in the model. To overcome the challenge that CLIP's prompting only is applicable to classification tasks, we propose a simple but effective strategy to convert multiple prompts to a continuous scalar as required when predicting an image's mean aesthetic score. Second, we train a linear regression on the AVA dataset using image features obtained by CLIP's image encoder. The resulting model outperforms a linear regression trained on features from an ImageNet classification model. It also shows competitive performance with fully fine-tuned networks based on ImageNet, while only training a single layer. Finally, by fine-tuning CLIP's image encoder on the AVA dataset, we show that CLIP only needs a fraction of training epochs to converge, while also performing better than a fine-tuned ImageNet model. Overall, our experiments suggest that CLIP is better suited as a base model for IAA methods than ImageNet pretrained networks.}, language = {en} } @phdthesis{Bleier2023, author = {Bleier, Michael}, title = {Underwater Laser Scanning - Refractive Calibration, Self-calibration and Mapping for 3D Reconstruction}, isbn = {978-3-945459-45-4}, doi = {10.25972/OPUS-32269}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-322693}, school = {Universit{\"a}t W{\"u}rzburg}, year = {2023}, abstract = {There is great interest in affordable, precise and reliable metrology underwater: Archaeologists want to document artifacts in situ with high detail. In marine research, biologists require the tools to monitor coral growth and geologists need recordings to model sediment transport. Furthermore, for offshore construction projects, maintenance and inspection millimeter-accurate measurements of defects and offshore structures are essential. While the process of digitizing individual objects and complete sites on land is well understood and standard methods, such as Structure from Motion or terrestrial laser scanning, are regularly applied, precise underwater surveying with high resolution is still a complex and difficult task. Applying optical scanning techniques in water is challenging due to reduced visibility caused by turbidity and light absorption. However, optical underwater scanners provide significant advantages in terms of achievable resolution and accuracy compared to acoustic systems. This thesis proposes an underwater laser scanning system and the algorithms for creating dense and accurate 3D scans in water. It is based on laser triangulation and the main optical components are an underwater camera and a cross-line laser projector. The prototype is configured with a motorized yaw axis for capturing scans from a tripod. Alternatively, it is mounted to a moving platform for mobile mapping. The main focus lies on the refractive calibration of the underwater camera and laser projector, the image processing and 3D reconstruction. For highest accuracy, the refraction at the individual media interfaces must be taken into account. This is addressed by an optimization-based calibration framework using a physical-geometric camera model derived from an analytical formulation of a ray-tracing projection model. In addition to scanning underwater structures, this work presents the 3D acquisition of semi-submerged structures and the correction of refraction effects. As in-situ calibration in water is complex and time-consuming, the challenge of transferring an in-air scanner calibration to water without re-calibration is investigated, as well as self-calibration techniques for structured light. The system was successfully deployed in various configurations for both static scanning and mobile mapping. An evaluation of the calibration and 3D reconstruction using reference objects and a comparison of free-form surfaces in clear water demonstrate the high accuracy potential in the range of one millimeter to less than one centimeter, depending on the measurement distance. Mobile underwater mapping and motion compensation based on visual-inertial odometry is demonstrated using a new optical underwater scanner based on fringe projection. Continuous registration of individual scans allows the acquisition of 3D models from an underwater vehicle. RGB images captured in parallel are used to create 3D point clouds of underwater scenes in full color. 3D maps are useful to the operator during the remote control of underwater vehicles and provide the building blocks to enable offshore inspection and surveying tasks. The advancing automation of the measurement technology will allow non-experts to use it, significantly reduce acquisition time and increase accuracy, making underwater metrology more cost-effective.}, subject = {Selbstkalibrierung}, language = {en} }