@misc{27072, author = {{Adsul, Vaibhav}}, title = {{{Peer-to-Peer Matching for Distributed Systems}}}, year = {{2021}}, } @misc{21084, author = {{Werthmann, Julian}}, title = {{{Derandomization and Local Graph Problems in the Node-Capacitated Clique}}}, year = {{2021}}, } @misc{21197, author = {{Mengshi, Ma}}, title = {{{Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter}}}, year = {{2021}}, } @article{21264, abstract = {{Abstract Background Hand amputation can have a truly debilitating impact on the life of the affected person. A multifunctional myoelectric prosthesis controlled using pattern classification can be used to restore some of the lost motor abilities. However, learning to control an advanced prosthesis can be a challenging task, but virtual and augmented reality (AR) provide means to create an engaging and motivating training. Methods In this study, we present a novel training framework that integrates virtual elements within a real scene (AR) while allowing the view from the first-person perspective. The framework was evaluated in 13 able-bodied subjects and a limb-deficient person divided into intervention (IG) and control (CG) groups. The IG received training by performing simulated clothespin task and both groups conducted a pre- and posttest with a real prosthesis. When training with the AR, the subjects received visual feedback on the generated grasping force. The main outcome measure was the number of pins that were successfully transferred within 20 min (task duration), while the number of dropped and broken pins were also registered. The participants were asked to score the difficulty of the real task (posttest), fun-factor and motivation, as well as the utility of the feedback. Results The performance (median/interquartile range) consistently increased during the training sessions (4/3 to 22/4). While the results were similar for the two groups in the pretest, the performance improved in the posttest only in IG. In addition, the subjects in IG transferred significantly more pins (28/10.5 versus 14.5/11), and dropped (1/2.5 versus 3.5/2) and broke (5/3.8 versus 14.5/9) significantly fewer pins in the posttest compared to CG. The participants in IG assigned (mean ± std) significantly lower scores to the difficulty compared to CG (5.2 ± 1.9 versus 7.1 ± 0.9), and they highly rated the fun factor (8.7 ± 1.3) and usefulness of feedback (8.5 ± 1.7). Conclusion The results demonstrated that the proposed AR system allows for the transfer of skills from the simulated to the real task while providing a positive user experience. The present study demonstrates the effectiveness and flexibility of the proposed AR framework. Importantly, the developed system is open source and available for download and further development. }}, author = {{Boschmann, Alexander and Neuhaus, Dorothee and Vogt, Sarah and Kaltschmidt, Christian and Platzner, Marco and Dosen, Strahinja}}, issn = {{1743-0003}}, journal = {{Journal of NeuroEngineering and Rehabilitation}}, title = {{{Immersive augmented reality system for the training of pattern classification control with a myoelectric prosthesis}}}, doi = {{10.1186/s12984-021-00822-6}}, year = {{2021}}, } @phdthesis{21628, abstract = {{This thesis considers the realization of distributed data structures and the construction of distributed protocols for self-stabilizing overlay networks. In the first part of this thesis, we provide distributed protocols for queues, stacks and priority queues that serve the insertion and deletion of elements within a logarithmic amount of rounds. Our protocols respect semantic constraints such as sequential consistency or serializability and the individual semantic constraints given by the type (queue, stack, priority queue) of the data structure. We furthermore provide a protocol that handles joining and leaving nodes. As an important side product, we present a novel protocol solving the distributed $k$-selection problem in a logarithmic amount of rounds, that is, to find the $k$-smallest elements among a polynomial number of elements spread among $n$ nodes. The second part of this thesis is devoted to the construction of protocols for self-stabilizing overlay networks, i.e., distributed protocols that transform an overlay network from any initial (potentially illegitimate) state into a legitimate state in finite time. We present protocols for self-stabilizing generalized De Bruijn graphs, self-stabilizing quadtrees and self-stabilizing supervised skip rings. Each of those protocols comes with unique properties that makes it interesting for certain distributed applications. Generalized De Bruijn networks provide routing within a constant amount of hops, thus serving the interest in networks that require a low latency for requests. The protocol for the quadtree guarantees monotonic searchability as well as a geometric variant of monotonic searchability, making it interesting for wireless networks or applications needed in the area of computational geometry. The supervised skip ring can be used to construct a self-stabilizing publish-subscribe system. }}, author = {{Feldmann, Michael}}, title = {{{Algorithms for Distributed Data Structures and Self-Stabilizing Overlay Networks}}}, doi = {{10.17619/UNIPB/1-1113}}, year = {{2021}}, } @inbook{17905, abstract = {{This chapter concentrates on aspect-based sentiment analysis, a form of opinion mining where algorithms detect sentiments expressed about features of products, services, etc. We especially focus on novel approaches for aspect phrase extraction and classification trained on feature-rich datasets. Here, we present two new datasets, which we gathered from the linguistically rich domain of physician reviews, as other investigations have mainly concentrated on commercial reviews and social media reviews so far. To give readers a better understanding of the underlying datasets, we describe the annotation process and inter-annotator agreement in detail. In our research, we automatically assess implicit mentions or indications of specific aspects. To do this, we propose and utilize neural network models that perform the here-defined aspect phrase extraction and classification task, achieving F1-score values of about 80% and accuracy values of more than 90%. As we apply our models to a comparatively complex domain, we obtain promising results. }}, author = {{Kersting, Joschka and Geierhos, Michaela}}, booktitle = {{Natural Language Processing in Artificial Intelligence -- NLPinAI 2020}}, editor = {{Loukanova, Roussanka}}, pages = {{163----189 }}, publisher = {{Springer}}, title = {{{Towards Aspect Extraction and Classification for Opinion Mining with Deep Sequence Networks}}}, doi = {{10.1007/978-3-030-63787-3_6}}, volume = {{939}}, year = {{2021}}, } @article{23524, abstract = {{We experimentally consider a dynamic multi-period Cournot duopoly with a simultaneous option to manage financial risk and a real option to delay supply. The first option allows players to manage risk before uncertainty is realized, while the second allows managing risk after realization. In our setting, firms face a strategic dilemma: They must weigh the advantages of dealing with risk exposure against the disadvantages of higher competition. In theory, firms make strategic use of the hedging component, enhancing competition. Our experimental results support this theory, suggesting that hedging increases competition and negates duopoly profits even in a simultaneous setting.}}, author = {{Cox, Caleb and Karam, Arzé and Pelster, Matthias}}, journal = {{Review of Industrial Organization}}, title = {{{Two-period duopolies with forward markets}}}, doi = {{10.1007/s11151-021-09839-6}}, year = {{2021}}, } @article{23609, author = {{Guzelturk, Burak and Winkler, Thomas and Van de Goor, Tim W. J. and Smith, Matthew D. and Bourelle, Sean A. and Feldmann, Sascha and Trigo, Mariano and Teitelbaum, Samuel W. and Steinrück, Hans-Georg and de la Pena, Gilberto A. and Alonso-Mori, Roberto and Zhu, Diling and Sato, Takahiro and Karunadasa, Hemamala I. and Toney, Michael F. and Deschler, Felix and Lindenberg, Aaron M.}}, issn = {{1476-1122}}, journal = {{Nature Materials}}, pages = {{618--623}}, title = {{{Visualization of dynamic polaronic strain fields in hybrid lead halide perovskites}}}, doi = {{10.1038/s41563-020-00865-5}}, volume = {{20}}, year = {{2021}}, } @article{23674, abstract = {{The diagnosis of diseases is decisive for planning proper treatment and ensuring the well-being of patients. Human error hinders accurate diagnostics, as interpreting medical information is a complex and cognitively challenging task. The application of artificial intelligence (AI) can improve the level of diagnostic accuracy and efficiency. While the current literature has examined various approaches to diagnosing various diseases, an overview of fields in which AI has been applied, including their performance aiming to identify emergent digitalized healthcare services, has not yet been adequately realized in extant research. By conducting a critical review, we portray the AI landscape in diagnostics and provide a snapshot to guide future research. This paper extends academia by proposing a research agenda. Practitioners understand the extent to which AI improves diagnostics and how healthcare benefits from it. However, several issues need to be addressed before successful application of AI in disease diagnostics can be achieved.}}, author = {{Mirbabaie, Milad and Stieglitz, Stefan and Frick, Nicholas R. J.}}, issn = {{2190-7188}}, journal = {{Health and Technology}}, pages = {{693--731}}, title = {{{Artificial intelligence in disease diagnostics: A critical review and classification on the current state of research guiding future direction}}}, doi = {{10.1007/s12553-021-00555-5}}, year = {{2021}}, } @inbook{23734, author = {{Lammers, Stefan and Kruse, Anne and Gierse, Jan and Tominski, Johannes and Lindemann, Christian-Friedrich}}, booktitle = {{Mehrzieloptimierte und durchgängig automatisierte Bauteilentwicklung für Additive Fertigungsverfahren im Produktentstehungsprozess}}, editor = {{Koch, Rainer and Zimmer, Detmar and Tröster, Thomas and Gräßler, Iris}}, isbn = {{978-3-8440-7932-6}}, title = {{{Konstruktionsrichtlinien in der Produktentwicklung}}}, year = {{2021}}, } @inproceedings{20641, author = {{Aßmuth, Verena and Teutenberg, Dominik and Meschut, Gerson}}, booktitle = {{10. Doktorandenseminar Klebtechnik}}, isbn = {{978-3-96144-139-6}}, location = {{Kassel}}, publisher = {{DVS Media GmbH}}, title = {{{Analyse rezepturabhängiger und alterungsbedingter Enthaftungserscheinungen geklebter SMC-Bauteile}}}, volume = {{369}}, year = {{2021}}, } @article{20683, author = {{Feldkord, Björn and Knollmann, Till and Malatyali, Manuel and Meyer auf der Heide, Friedhelm}}, journal = {{Theory of Computing Systems}}, pages = {{943–984}}, title = {{{Managing Multiple Mobile Resources}}}, doi = {{10.1007/s00224-020-10023-8}}, volume = {{65}}, year = {{2021}}, } @inproceedings{20817, author = {{Bienkowski, Marcin and Feldkord, Björn and Schmidt, Pawel}}, booktitle = {{Proceedings of the 38th Symposium on Theoretical Aspects of Computer Science (STACS)}}, pages = {{14:1 -- 14:17}}, title = {{{A Nearly Optimal Deterministic Online Algorithm for Non-Metric Facility Location}}}, doi = {{10.4230/LIPIcs.STACS.2021.14}}, year = {{2021}}, } @proceedings{22230, editor = {{Sousa Santos, Beatriz and Domik, Gitta}}, isbn = {{ISBN 978-3-03868-132-8 }}, location = {{Vienna}}, publisher = {{Eurographics Association }}, title = {{{EUROGRAPHICS 2021: Education Papers Frontmatter}}}, doi = {{10.2312/EGED.20212000}}, year = {{2021}}, } @inproceedings{22283, abstract = {{ We show how to construct an overlay network of constant degree and diameter $O(\log n)$ in time $O(\log n)$ starting from an arbitrary weakly connected graph. We assume a synchronous communication network in which nodes can send messages to nodes they know the identifier of and establish new connections by sending node identifiers. If the initial network's graph is weakly connected and has constant degree, then our algorithm constructs the desired topology with each node sending and receiving only $O(\log n)$ messages in each round in time $O(\log n)$, w.h.p., which beats the currently best $O(\log^{3/2} n)$ time algorithm of [Götte et al., SIROCCO'19]. Since the problem cannot be solved faster than by using pointer jumping for $O(\log n)$ rounds (which would even require each node to communicate $\Omega(n)$ bits), our algorithm is asymptotically optimal. We achieve this speedup by using short random walks to repeatedly establish random connections between the nodes that quickly reduce the conductance of the graph using an observation of [Kwok and Lau, APPROX'14]. Additionally, we show how our algorithm can be used to efficiently solve graph problems in \emph{hybrid networks} [Augustine et al., SODA'20]. Motivated by the idea that nodes possess two different modes of communication, we assume that communication of the \emph{initial} edges is unrestricted. In contrast, only polylogarithmically many messages can be communicated over edges that have been established throughout an algorithm's execution. For an (undirected) graph $G$ with arbitrary degree, we show how to compute connected components, a spanning tree, and biconnected components in time $O(\log n)$, w.h.p. Furthermore, we show how to compute an MIS in time $O(\log d + \log \log n)$, w.h.p., where $d$ is the initial degree of $G$.}}, author = {{Götte, Thorsten and Hinnenthal, Kristian and Scheideler, Christian and Werthmann, Julian}}, booktitle = {{Proc. of the 40th ACM Symposium on Principles of Distributed Computing (PODC '21)}}, editor = {{Censor-Hillel, Keren}}, location = {{Virtual}}, publisher = {{ACM}}, title = {{{Time-Optimal Construction of Overlays}}}, doi = {{10.1145/3465084.3467932}}, year = {{2021}}, } @inproceedings{22217, author = {{Krauter, Stefan and Khatibi, Arash}}, booktitle = {{Tagungsband des 36. PV-Symposium, 18.-26 Mai 2021, online, ISBN 978-3-948176-14-3, S. 301-304. }}, isbn = {{978-3-948176-14-3}}, location = {{Staffelstein / online}}, pages = {{301--304}}, publisher = {{Conexio}}, title = {{{Einfluss von Steilaufstellung, Nachführung und Einsatz bifazialer PV-Module auf den Speicherbedarf und die Kosten einer 100% EE-Versorgung Deutschlands}}}, year = {{2021}}, } @book{29876, author = {{Schröder, Dierk and Böcker, Joachim}}, isbn = {{978-3-662-62699-3}}, pages = {{1625}}, publisher = {{Springer Nature}}, title = {{{Elektrische Antriebe – Regelung von Antriebssystemen}}}, doi = {{10.1007/978-3-662-62700-6}}, year = {{2021}}, } @article{30645, abstract = {{As a new and innovative processing method for fabrication for fiber-reinforced thermoplastic composites (CFRTs), the feasibility of ultrasonic welding technology was proven in several studies. This method offers potential for the direct manufacturing of CFRT–metal structures via embedded pin structures. Despite the previous studies, a deeper understanding of the process of energy input and whether fibers work as energy directors and consequently can, in combination with chosen processing parameters, influence the consolidation quality of the CFRTs, is still unknown. Consequently, the aim of this work is to establish a deeper process understanding of the ultrasonic direct impregnation of fiber-reinforced thermoplastics with an emphasis on the fiber’s function as energy directors. Based on the generated insights, a better assessment of the feasibility of direct, hybrid part manufacturing is possible. The produced samples were primarily evaluated by optical and mechanical test methods. It is demonstrated that with higher welding time and amplitude, a better consolidation quality can be achieved and that independent of the process parameters chosen in this study, no significant fiber breakage occurs. This is interpreted as a sign of a gentle impregnation process. Furthermore, based on the examination of single roving and 5-layer set-ups, it is shown that the glass fibers function as energy directors and can influence the transformation of sonic energy into thermal energy. In comparison to industrially available CFRT material, the mechanical properties are weaker, but materials and processes offer potential for significant improvement. Based on these findings, proposals for a direct impregnation and joining process are made.}}, author = {{Popp, J. and Wolf, M. and Mattner, T. and Drummer, D.}}, journal = {{Journal of Composites Science}}, pages = {{239}}, title = {{{Energy direction in ultrasonic impregnation of continuous fiber-reinforced thermoplastics}}}, doi = {{10.3390/jcs5090239}}, volume = {{5}}, year = {{2021}}, } @misc{17751, author = {{Peckhaus, Volker}}, booktitle = {{Staatslexikon. Recht, Wirtschaft, Gesellschaft, Bd. 5: Schule - Virtuelle Realität}}, pages = {{983--991 (Spalten)}}, publisher = {{Herder Verlag}}, title = {{{Technikphilosophie}}}, year = {{2021}}, } @inproceedings{27381, abstract = {{Graph neural networks (GNNs) have been successfully applied in many structured data domains, with applications ranging from molecular property prediction to the analysis of social networks. Motivated by the broad applicability of GNNs, we propose the family of so-called RankGNNs, a combination of neural Learning to Rank (LtR) methods and GNNs. RankGNNs are trained with a set of pair-wise preferences between graphs, suggesting that one of them is preferred over the other. One practical application of this problem is drug screening, where an expert wants to find the most promising molecules in a large collection of drug candidates. We empirically demonstrate that our proposed pair-wise RankGNN approach either significantly outperforms or at least matches the ranking performance of the naive point-wise baseline approach, in which the LtR problem is solved via GNN-based graph regression.}}, author = {{Damke, Clemens and Hüllermeier, Eyke}}, booktitle = {{Proceedings of The 24th International Conference on Discovery Science (DS 2021)}}, editor = {{Soares, Carlos and Torgo, Luis}}, isbn = {{9783030889418}}, issn = {{0302-9743}}, keywords = {{Graph-structured data, Graph neural networks, Preference learning, Learning to rank}}, location = {{Halifax, Canada}}, pages = {{166--180}}, publisher = {{Springer}}, title = {{{Ranking Structured Objects with Graph Neural Networks}}}, doi = {{10.1007/978-3-030-88942-5}}, volume = {{12986}}, year = {{2021}}, }