TY - CONF AB - The famous $k$-Server Problem covers plenty of resource allocation scenarios, and several variations have been studied extensively for decades. However, to the best of our knowledge, no research has considered the problem if the servers are not identical and requests can express which specific servers should serve them. Therefore, we present a new model generalizing the $k$-Server Problem by *preferences* of the requests and proceed to study it in a uniform metric space for deterministic online algorithms (the special case of paging). In our model, requests can either demand to be answered by any server (*general requests*) or by a specific one (*specific requests*). If only general requests appear, the instance is one of the original $k$-Server Problem, and a lower bound for the competitive ratio of $k$ applies. If only specific requests appear, a solution with a competitive ratio of $1$ becomes trivial since there is no freedom regarding the servers' movements. Perhaps counter-intuitively, we show that if both kinds of requests appear, the lower bound raises to $2k-1$. We study deterministic online algorithms in uniform metrics and present two algorithms. The first one has an adaptive competitive ratio dependent on the frequency of specific requests. It achieves a worst-case competitive ratio of $3k-2$ while it is optimal when only general or only specific requests appear (competitive ratio of $k$ and $1$, respectively). The second has a fixed close-to-optimal worst-case competitive ratio of $2k+14$. For the first algorithm, we show a lower bound of $3k-2$, while the second algorithm has a lower bound of $2k-1$ when only general requests appear. The two algorithms differ in only one behavioral rule for each server that significantly influences the competitive ratio. Each server acting according to the rule allows approaching the worst-case lower bound, while it implies an increased lower bound for $k$-Server instances. In other words, there is a trade-off between performing well against instances of the $k$-Server Problem and instances containing specific requests. We also show that no deterministic online algorithm can be optimal for both kinds of instances simultaneously. AU - Castenow, Jannik AU - Feldkord, Björn AU - Knollmann, Till AU - Malatyali, Manuel AU - Meyer auf der Heide, Friedhelm ID - 31847 KW - K-Server Problem KW - Heterogeneity KW - Online Caching SN - 9781450391467 T2 - Proceedings of the 34th ACM Symposium on Parallelism in Algorithms and Architectures TI - The k-Server with Preferences Problem ER - TY - CHAP AU - Mindt, Ilka ED - Mah, Dana-Kristin ED - Cordula, Torner ID - 32473 T2 - Künstliche Intelligenz mit offenen Lernangeboten an Hochschulen lehren. Erfahrungen und Erkenntnisse aus dem Fellowship-Programm des KI-Campus. TI - Künstliche Intelligenz fachfremd mittels Open Educational Resources unterrichten. Wie das Flipped-Classroom-Format bei der Einbettung in die Lehre der Anglistik hilft. ER - TY - CONF AU - Mayer, Peter AU - Poddebniak, Damian AU - Fischer, Konstantin AU - Brinkmann, Marcus AU - Somorovsky, Juraj AU - Sasse, Angela AU - Schinzel, Sebastian AU - Volkamer, Melanie ID - 32572 SN - 978-1-939133-30-4 T2 - Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022) TI - "I don' know why I check this..." - Investigating Expert Users' Strategies to Detect Email Signature Spoofing Attacks ER - TY - GEN AB - BloKK-Beitrag für das ZeKK, 04.02.2022 AU - Lebock, Sarah ID - 30194 TI - Blogpost "Nahtoderfahrungen und ihre Deutungen" ER - TY - JOUR AU - Yang, Yu AU - Huang, Jingyuan AU - Dornbusch, Daniel AU - Grundmeier, Guido AU - Fahmy, Karim AU - Keller, Adrian AU - Cheung, David L. ID - 32432 JF - Langmuir KW - Electrochemistry KW - Spectroscopy KW - Surfaces and Interfaces KW - Condensed Matter Physics KW - General Materials Science SN - 0743-7463 TI - Effect of Surface Hydrophobicity on the Adsorption of a Pilus-Derived Adhesin-like Peptide VL - 38 ER - TY - JOUR AB - Guanidinium (Gdm) undergoes interactions with both hydrophilic and hydrophobic groups and, thus, is a highly potent denaturant of biomolecular structure. However, our molecular understanding of the interaction of Gdm with proteins and DNA is still rather limited. Here, we investigated the denaturation of DNA origami nanostructures by three Gdm salts, i.e., guanidinium chloride (GdmCl), guanidinium sulfate (Gdm2SO4), and guanidinium thiocyanate (GdmSCN), at different temperatures and in dependence of incubation time. Using DNA origami nanostructures as sensors that translate small molecular transitions into nanostructural changes, the denaturing effects of the Gdm salts were directly visualized by atomic force microscopy. GdmSCN was the most potent DNA denaturant, which caused complete DNA origami denaturation at 50 °C already at a concentration of 2 M. Under such harsh conditions, denaturation occurred within the first 15 min of Gdm exposure, whereas much slower kinetics were observed for the more weakly denaturing salt Gdm2SO4 at 25 °C. Lastly, we observed a novel non-monotonous temperature dependence of DNA origami denaturation in Gdm2SO4 with the fraction of intact nanostructures having an intermediate minimum at about 40 °C. Our results, thus, provide further insights into the highly complex Gdm–DNA interaction and underscore the importance of the counteranion species. AU - Hanke, Marcel AU - Hansen, Niklas AU - Tomm, Emilia AU - Grundmeier, Guido AU - Keller, Adrian ID - 32589 IS - 15 JF - International Journal of Molecular Sciences KW - Inorganic Chemistry KW - Organic Chemistry KW - Physical and Theoretical Chemistry KW - Computer Science Applications KW - Spectroscopy KW - Molecular Biology KW - General Medicine KW - Catalysis SN - 1422-0067 TI - Time-Dependent DNA Origami Denaturation by Guanidinium Chloride, Guanidinium Sulfate, and Guanidinium Thiocyanate VL - 23 ER - TY - JOUR AB - Background: Medical professionals working in an elite sport environment have the challenging task to balance the athlete’s readiness to return to the playing field after severe injury with other stakeholders’ (coaches, sponsors, teammates) opinions and objectives.Objectives: Our study aimed to evaluate differences in the physical profiles of elite rugby players at return to play (RTP) after a severe knee injury, compared with their pre-injury profiles and matched controls.Method: Before the injury, participants performed four performance tests during their preseason screening. These tests were repeated and compared to baseline once a player was declared fit to play.Results: Significant differences (p ≤ 0.05) were found in the injured players’ group who were slower over 10 m speed, in their decision-making time and the total time of the reactive agility tests at RTP, whilst controls were significantly faster over 10 m and 30 m speed tests. The countermovement jump outcomes showed significant improvement in the uninjured participants (p ≤ 0.05).Conclusion: Our study highlights that injured players’ running speeds and decision-making times are slower after injury. The uninjured players have a positive outcome to training and match stimulus by improving their running speed and lower body explosive power during the season.Clinical implications: Our study provides insight into the RTP profile of elite rugby players, and a novel finding was the decision-making time deficit. This highlights the importance of cognitive training during injury rehabilitation as athletes make numerous decisions in a pressured and uncontrolled environment during a match. Speed training development is recommended as the athletes were slower after severe knee injury. AU - Robyn, Aneurin D. AU - Louw, Quinette A. AU - Baumeister, Jochen ID - 34022 IS - 1 JF - South African Journal of Physiotherapy KW - Physical Therapy KW - Sports Therapy and Rehabilitation SN - 2410-8219 TI - Return to play in elite rugby players after severe knee injuries VL - 78 ER - TY - CHAP AB - Decision makers increasingly rely on decision support systems for optimal decision making. Recently, special attention has been paid to process-driven decision support systems (PD-DSS) in which a process model prescribes the invocation sequence of software-based decision support services and the data exchange between them. Thus, it is possible to quickly combine available decision support services as needed for optimally supporting the decision making process of an individual decision maker. However, process modelers may accidentally create a process model which is technically well-formed and executable, but contains functional and behavioral flaws such as redundant or missing services. These flaws may result in inefficient computations or invalid decision recommendations when the corresponding PD-DSS is utilized by a decision maker. In this paper, we therefore propose an approach to validate functionality and behavior of a process model representing a PD-DSS. Our approach is based on expressing flaws as anti-patterns for which the process model can be automatically checked via graph matching. We prototypically implemented our approach and demonstrate its applicability in the context of decision making for energy network planning. AU - Kirchhoff, Jonas AU - Engels, Gregor ID - 34023 SN - 1865-1348 T2 - Software Business TI - Anti-pattern Detection in Process-Driven Decision Support Systems VL - 463 ER - TY - JOUR AU - Robyn, A.D. AU - Louw, Q.A. AU - Baumeister, Jochen ID - 34021 IS - 3 JF - African Journal for Physical Activity and Health Sciences (AJPHES) KW - General Medicine SN - 2411-6939 TI - Psychological readiness of elite rugby players at return to play after severe knee injury VL - 28 ER - TY - GEN AU - Haase, Michael AU - Tasche, Frederik AU - Bieber, Maximilian AU - Zibart, Alexander ID - 34020 TI - Innovative Leichtbau- und Kühlungskonzepte für elektrische Maschinen durch additive Fertigung (ILuKadd3D) VL - Heft 1526 ER - TY - GEN AB - Controversial topics like abortion or capital punishment inherently lack of correct answers or the right way to deal with. Thus, in order to find what is true, what is good, or what should be done, the involved parties need to debate. For the purpose of forming an opinion on a controversial topic someone needs to take in a lot of arguments on that topic to gather information which can be a time-consuming process. To increase efficiency, someone can use an argument search engine to quicken the retrieval of relevant arguments. Although the usage of such a service reduces the time to find arguments, there is still a lot of textual data that needs to be read. To this end, computational summarization approaches for arguments can limit the necessary time for information review by generating short snippets capturing the main gist of each argument. Yet, we suggest that approaches that consider one argument at a time show potential for further improvement in terms of efficiency during information review. In fact, arguments on the same topic, like those retrieved by a search engine for a certain query, partially cover the same content, e. g. arguments regarding the death penalty probably use deterrence as a point in favor of it. However, if the same aspect is central in multiple arguments, their snippets reflect this, which leads to redundancy among the snippets. Consequently, someone interested in gathering information on a controversial topic does not necessarily find new information in each snippet he or she reads. We introduce the task of Contrastive Argument Summarization (CAS) which addresses the aforementioned problem regarding existing argument summarization. An approach that addresses CAS aims to produce contrastive snippets for each argument in a set of topic-related arguments. A contrastive snippet should represent the main gist of its argument, it should account for the argumentative nature of the text, and it should be dissimilar to the other topic-related arguments in order to reduce redundancy among the snippets. We propose two approaches addressing CAS, namely an extended version of the LexRank derivation by Alshomary et al. (2020), and an advancement of the work by Bista et al. (2020). Additionally, we develop two automatic measures to assess to which extent the snippets of one set are opposed. For evaluation, we compile a corpus using the args.me search engine Wachsmuth et al. (2017b) to come close to the suggested area of application. Moreover, we conduct a manual annotation study to assess approaches’ effectiveness. We find that the graph-based approach is superior when it comes to contrastiveness (i. e. snippets being dissimilar to topic-related arguments), and that the second approach outperforms the previous one and the unmodified version of Alshomary et al. (2020) when it comes to representativeness (i. e. snippets capturing the main gist of an argument). AU - Rieskamp, Jonas ID - 34025 TI - Contrastive Argument Summarization Using Supervised and Unsupervised Machine Learning ER - TY - CONF AB - Consider the practical goal of making a desired action profile played, when the planner can only change the payoffs, bound by stringent constraints. Applications include motivating people to choose the closest school, the closest subway station, or to coordinate on a communication protocol or an investment strategy. Employing subsidies and tolls, we adjust the game so that choosing this predefined action profile becomes strictly dominant. Inspired mainly by the work of Monderer and Tennenholtz, where the promised subsidies do not materialise in the not played profiles, we provide a fair and individually rational game adjustment, such that the total outside investments sum up to zero at any profile, thereby facilitating easy and frequent usage of our adjustment without bearing costs, even if some players behave unexpectedly. The resultant action profile itself needs no adjustment. Importantly, we also prove that our adjustment minimises the general transfer among all such adjustments, counting the total subsidising and taxation. AU - Polevoy, Gleb AU - Dziubiński, Marcin ED - De Raedt, Luc ID - 34040 KW - adjustment KW - strictly dominant KW - fairness KW - individually rational KW - transfer KW - tax KW - subsidy T2 - Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence TI - Fair, Individually Rational and Cheap Adjustment ER - TY - JOUR AB - Zusammenfassung: Der Beitrag befasst sich mit der professionellen pädagogischen Beziehung zwischen Referendar*innen und ihren Seminarlehrkräften, deren Beitrag für die Beanspruchung der Referendar*innen bisher noch nicht eingängig untersucht wurde. Das Ziel der Studie ist es, anhand einer Querschnittserhebung von 2583 Referendar*innen und ausgebildeten Lehrkräften, kompensatorische sowie verstärkende Effekte der Beziehungsdimensionen Transparenz, Fairness, Vertrauen und Ambivalenz auf die wahrgenommene Beanspruchung im Referendariat zu untersuchen. Die Analyse erfolgt mittels eines latent moderierten Strukturgleichungsansatzes. Die Ergebnisse zeigen, dass Belastungen durch die Kerntätigkeiten im Referendariat sowie Belastungen durch den Umgang mit Kolleg*innen im Lehrer*innenkollegium in signifikant positivem Zusammenhang mit resultierenden Beanspruchungsreaktionen stehen. Je transparenter, fairer und vertrauensvoller und je weniger ambivalent die Beziehung zur Seminarlehrkraft erlebt wird, desto geringer fallen die Beanspruchungsreaktionen aus. Die Ergebnisse werden hinsichtlich ihrer Relevanz für die Beziehungsarbeit im Referendariat als zentralem Ausbildungsbestandteil der zweiten Phase der Lehrer*innenausbildung diskutiert. AU - Kärner, Tobias AU - Goller, Michael AU - Bonnes, Caroline AU - Maué, Elisabeth ID - 30105 JF - Zeitschrift für Erziehungswissenschaft KW - Education SN - 1434-663X TI - Die professionelle pädagogische Beziehung zwischen Referendar*innen und ihren Seminarlehrkräften: Belastungsfaktor oder Ressource? VL - 25 ER - TY - CONF AU - Epstein, Leah AU - Lassota, Alexandra AU - Levin, Asaf AU - Maack, Marten AU - Rohwedder, Lars ED - Berenbrink, Petra ED - Monmege, Benjamin ID - 33085 T2 - 39th International Symposium on Theoretical Aspects of Computer Science, STACS 2022, March 15-18, 2022, Marseille, France (Virtual Conference) TI - Cardinality Constrained Scheduling in Online Models VL - 219 ER - TY - JOUR AU - Hoffmann, Christin AU - Thommes, Kirsten ID - 34044 JF - Journal of Cleaner Production KW - Industrial and Manufacturing Engineering KW - Strategy and Management KW - General Environmental Science KW - Renewable Energy KW - Sustainability and the Environment KW - Building and Construction SN - 0959-6526 TI - Clear Roads and Dirty Air? Indirect effects of reduced private traffic congestion on emissions from heavy traffic ER - TY - JOUR AU - Hoffmann, Christin AU - Thommes, Kirsten ID - 34045 JF - Journal of Cleaner Production KW - Industrial and Manufacturing Engineering KW - Strategy and Management KW - General Environmental Science KW - Renewable Energy KW - Sustainability and the Environment KW - Building and Construction SN - 0959-6526 TI - Clear Roads and Dirty Air? Indirect effects of reduced private traffic congestion on emissions from heavy traffic ER - TY - CONF AU - Alshomary, Milad AU - El Baff, Roxanne AU - Gurcke, Timon AU - Wachsmuth, Henning ID - 30840 T2 - Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics TI - The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments ER - TY - CONF AU - Wachsmuth, Henning AU - Alshomary, Milad ID - 33004 T2 - Proceedings of the 29th International Conference on Computational Linguistics TI - "Mama Always Had a Way of Explaining Things So I Could Understand": A Dialogue Corpus for Learning How to Explain ER - TY - JOUR AU - Lauscher, Anne AU - Wachsmuth, Henning AU - Gurevych, Iryna AU - Glavaš, Goran ID - 34049 JF - Transactions of the Association for Computational Linguistics TI - On the Role of Knowledge in Computational Argumentation ER - TY - CONF AU - Kiesel, Johannes AU - Alshomary, Milad AU - Handke, Nicolas AU - Cai, Xiaoni AU - Wachsmuth, Henning AU - Stein, Benno ID - 22157 T2 - Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics TI - Identifying the Human Values behind Arguments ER -