@techreport{VomhoffGeisslerHossfeld2022, type = {Working Paper}, author = {Vomhoff, Viktoria and Geißler, Stefan and Hoßfeld, Tobias}, title = {Identification of Signaling Patterns in Mobile IoT Signaling Traffic}, 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-28081}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280819}, pages = {4}, year = {2022}, abstract = {We attempt to identify sequences of signaling dialogs, to strengthen our understanding of the signaling behavior of IoT devices by examining a dataset containing over 270.000 distinct IoT devices whose signaling traffic has been observed over a 31-day period in a 2G network [4]. We propose a set of rules that allows the assembly of signaling dialogs into so-called sessions in order to identify common patterns and lay the foundation for future research in the areas of traffic modeling and anomaly detection.}, subject = {Datennetz}, 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{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{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} } @techreport{SertbasBuelbuelErgencFischer2022, type = {Working Paper}, author = {Sertbas B{\"u}lb{\"u}l, Nurefsan and Ergenc, Doganalp and Fischer, Mathias}, title = {Evaluating Dynamic Path Reconfiguration for Time Sensitive Networks}, 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-28074}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-280743}, pages = {5}, year = {2022}, abstract = {In time-sensitive networks (TSN) based on 802.1Qbv, i.e., the time-aware Shaper (TAS) protocol, precise transmission schedules and, paths are used to ensure end-to-end deterministic communication. Such resource reservations for data flows are usually established at the startup time of an application and remain untouched until the flow ends. There is no way to migrate existing flows easily to alternative paths without inducing additional delay or wasting resources. Therefore, some of the new flows cannot be embedded due to capacity limitations on certain links which leads to sub-optimal flow assignment. As future networks will need to support a large number of lowlatency flows, accommodating new flows at runtime and adapting existing flows accordingly becomes a challenging problem. In this extended abstract we summarize a previously published paper of us [1]. We combine software-defined networking (SDN), which provides better control of network flows, with TSN to be able to seamlessly migrate time-sensitive flows. For that, we formulate an optimization problem and propose different dynamic path configuration strategies under deterministic communication requirements. Our simulation results indicate that regularly reconfiguring the flow assignments can improve the latency of time-sensitive flows and can increase the number of flows embedded in the network around 4\% in worst-case scenarios while still satisfying individual flow deadlines.}, subject = {Datennetz}, language = {en} } @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} } @techreport{RieglerWernerKayal2022, type = {Working Paper}, author = {Riegler, Clemens and Werner, Lennart and Kayal, Hakan}, title = {MAPLE: Marsian Autorotation Probe Lander Experiment}, doi = {10.25972/OPUS-28239}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-282390}, pages = {7}, year = {2022}, abstract = {The first step towards aerial planetary exploration has been made. Ingenuity shows extremely promising results, and new missions are already underway. Rotorcraft are capable of flight. This capability could be utilized to support the last stages of Entry, Descent, and Landing. Thus, mass and complexity could be scaled down. Autorotation is one method of descent. It describes unpowered descent and landing, typically performed by helicopters in case of an engine failure. MAPLE is suggested to test these procedures and understand autorotation on other planets. In this series of experiments, the Ingenuity helicopter is utilized. Ingenuity would autorotate a "mid-air-landing" before continuing with normal flight. Ultimately, the collected data shall help to understand autorotation on Mars and its utilization for interplanetary exploration.}, language = {en} } @techreport{RieglerKayal2022, type = {Working Paper}, author = {Riegler, Clemens and Kayal, Hakan}, title = {VELEX: Venus Lightning Experiment}, doi = {10.25972/OPUS-28248}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-282481}, pages = {6}, year = {2022}, abstract = {Lightning has fascinated humanity since the beginning of our existence. Different types of lightning like sprites and blue jets were discovered, and many more are theorized. However, it is very likely that these phenomena are not exclusive to our home planet. Venus's dense and active atmosphere is a place where lightning is to be expected. Missions like Venera, Pioneer, and Galileo have carried instruments to measure electromagnetic activity. These measurements have indeed delivered results. However, these results are not clear. They could be explained by other effects like cosmic rays, plasma noise, or spacecraft noise. Furthermore, these lightning seem different from those we know from our home planet. In order to tackle these issues, a different approach to measurement is proposed. When multiple devices in different spacecraft or locations can measure the same atmospheric discharge, most other explanations become increasingly less likely. Thus, the suggested instrument and method of VELEX incorporates multiple spacecraft. With this approach, the question about the existence of lightning on Venus could be settled.}, 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{ReinhardHelmerichBorasetal.2022, author = {Reinhard, Sebastian and Helmerich, Dominic A. and Boras, Dominik and Sauer, Markus and Kollmannsberger, Philip}, title = {ReCSAI: recursive compressed sensing artificial intelligence for confocal lifetime localization microscopy}, series = {BMC Bioinformatics}, volume = {23}, journal = {BMC Bioinformatics}, number = {1}, doi = {10.1186/s12859-022-05071-5}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-299768}, year = {2022}, abstract = {Background Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method. Results Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality. Conclusions Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.}, language = {en} }