@inproceedings{23779,
  abstract     = {{Produktentstehung (PE) bezieht sich auf den Prozess der Planung und Entwicklung eines Produkts sowie der damit verbundenen Dienstleistungen von der ersten Idee bis zur Herstellung und zum Vertrieb. Während dieses Prozesses gibt es zahlreiche Aufgaben, die von menschlichem Fachwissen abhängen und typischerweise von erfahrenen Experten übernommen werden. Da sich das Feld der Künstlichen Intelligenz (KI) immer weiterentwickelt und seinen Weg in den Fertigungssektor findet, gibt es viele Möglichkeiten für eine Anwendung von KI, um bei der Lösung der oben genannten Aufgaben zu helfen. In diesem Paper geben wir einen umfassenden Überblick über den aktuellen Stand der Technik des Einsatzes von KI in der PE. 
Im Detail analysieren wir 40 bestehende Surveys zu KI in der PE und 94 Case Studies, um herauszufinden, welche Bereiche der PE von der aktuellen Forschung in diesem Bereich vorrangig adressiert werden, wie ausgereift die diskutierten KI-Methoden sind und inwieweit datenzentrierte Ansätze in der aktuellen Forschung genutzt werden.}},
  author       = {{Bernijazov, Ruslan and Dicks, Alexander and Dumitrescu, Roman and Foullois, Marc and Hanselle, Jonas Manuel and Hüllermeier, Eyke and Karakaya, Gökce and Ködding, Patrick and Lohweg, Volker and Malatyali, Manuel and Meyer auf der Heide, Friedhelm and Panzner, Melina and Soltenborn, Christian}},
  booktitle    = {{Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-21)}},
  keywords     = {{Artificial Intelligence Product Creation Literature Review}},
  location     = {{Montreal, Kanada}},
  title        = {{{A Meta-Review on Artificial Intelligence in Product Creation}}},
  year         = {{2021}},
}

@article{23791,
  author       = {{Johannesmann, Sarah and Claes, Leander and Henning, Bernd}},
  journal      = {{tm - Technisches Messen}},
  number       = {{s1}},
  pages        = {{s28--s33}},
  publisher    = {{Walter de Gruyter {GmbH}}},
  title        = {{{Lamb wave based approach to the determination of elastic and viscoelastic material parameters}}},
  doi          = {{10.1515/teme-2021-0070}},
  volume       = {{88}},
  year         = {{2021}},
}

@inproceedings{20540,
  author       = {{Jovanovikj, Ivan and Thottam, Anu Tony and Joseph Vincent, Vishal and Yigitbas, Enes and Sauer, Stefan and Engels, Gregor}},
  booktitle    = {{Proceedings of the 9th International Conference on Model-Driven Engineering and Software Development }},
  location     = {{Vienna}},
  pages        = {{232--239}},
  publisher    = {{SCITEPRESS}},
  title        = {{{A Modeling Workbench for the Development of Situation-specific Test Co-Migration Methods }}},
  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{20693,
  abstract     = {{In practical, large-scale networks, services are requested
by users across the globe, e.g., for video streaming.
Services consist of multiple interconnected components such as
microservices in a service mesh. Coordinating these services
requires scaling them according to continuously changing user
demand, deploying instances at the edge close to their users,
and routing traffic efficiently between users and connected instances.
Network and service coordination is commonly addressed
through centralized approaches, where a single coordinator
knows everything and coordinates the entire network globally.
While such centralized approaches can reach global optima, they
do not scale to large, realistic networks. In contrast, distributed
approaches scale well, but sacrifice solution quality due to their
limited scope of knowledge and coordination decisions.

To this end, we propose a hierarchical coordination approach
that combines the good solution quality of centralized approaches
with the scalability of distributed approaches. In doing so, we divide
the network into multiple hierarchical domains and optimize
coordination in a top-down manner. We compare our hierarchical
with a centralized approach in an extensive evaluation on a real-world
network topology. Our results indicate that hierarchical
coordination can find close-to-optimal solutions in a fraction of
the runtime of centralized approaches.}},
  author       = {{Schneider, Stefan Balthasar and Jürgens, Mirko and Karl, Holger}},
  booktitle    = {{IFIP/IEEE International Symposium on Integrated Network Management (IM)}},
  keywords     = {{network management, service management, coordination, hierarchical, scalability, nfv}},
  location     = {{Bordeaux, France}},
  publisher    = {{IFIP/IEEE}},
  title        = {{{Divide and Conquer: Hierarchical Network and Service Coordination}}},
  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}},
}

@inproceedings{20886,
  author       = {{Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor}},
  booktitle    = {{Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision}},
  location     = {{Hawaii}},
  pages        = {{1994--2002}},
  title        = {{{Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts}}},
  year         = {{2021}},
}

@inproceedings{22155,
  author       = {{Gottschalk, Sebastian}},
  booktitle    = {{Advanced Software Engineering. Doctorial Consortium}},
  publisher    = {{CEUR}},
  title        = {{{Situation-specific Development of Business Models for Services in Software Ecosystems}}},
  year         = {{2021}},
}

@inproceedings{22156,
  abstract     = {{Word embedding models reflect bias towards genders, ethnicities, and other social groups present in the underlying training data. Metrics such as ECT, RNSB, and WEAT quantify bias in these models based on predefined word lists representing social groups and bias-conveying concepts. How suitable these lists actually are to reveal bias - let alone the bias metrics in general - remains unclear, though. In this paper, we study how to assess the quality of bias metrics for word embedding models. In particular, we present a generic method, Bias Silhouette Analysis (BSA), that quantifies the accuracy and robustness of such a metric and of the word lists used. Given a biased and an unbiased reference embedding model, BSA applies the metric systematically for several subsets of the lists to the models. The variance and rate of convergence of the bias values of each model then entail the robustness of the word lists, whereas the distance between the models' values gives indications of the general accuracy of the metric with the word lists. We demonstrate the behavior of BSA on two standard embedding models for the three mentioned metrics with several word lists from existing research.}},
  author       = {{Spliethöver, Maximilian and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21}},
  location     = {{Online}},
  pages        = {{552--559}},
  title        = {{{Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models}}},
  doi          = {{10.24963/ijcai.2021/77}},
  year         = {{2021}},
}

@inproceedings{22158,
  author       = {{Syed, Shahbaz and Al-Khatib, Khalid and Alshomary, Milad and Wachsmuth, Henning and Potthast, Martin}},
  booktitle    = {{Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021): Findings}},
  pages        = {{3482--3493}},
  title        = {{{Generating Informative Conclusions for Argumentative Texts}}},
  year         = {{2021}},
}

@inproceedings{22159,
  author       = {{Barrow, Joe and Jain, Rajiv and Lipka, Nedim and Dernoncourt, Franck and Morariu, Vlad and Manjunatha, Varun and Oard, Douglas and Resnik, Philip and Wachsmuth, Henning}},
  booktitle    = {{Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)}},
  pages        = {{1583--1595}},
  title        = {{{Syntopical Graphs for Computational Argumentation Tasks}}},
  year         = {{2021}},
}

@inproceedings{22160,
  author       = {{Al-Khatib, Khalid and Trautner, Lukas and Wachsmuth, Henning and Hou, Yufang and Stein, Benno}},
  booktitle    = {{Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)}},
  pages        = {{4744--4754}},
  title        = {{{Employing Argumentation Knowledge Graphs for Neural Argument Generation}}},
  year         = {{2021}},
}

@misc{22216,
  author       = {{Rehnen, Jakob Werner}},
  title        = {{{Decomposition of Arithmetic Components for the Approximate Circuit Synthesis with EvoApproxLib}}},
  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}},
}

@misc{22304,
  author       = {{Schott, Stefan}},
  title        = {{{Android App Analysis Benchmark Case Generation}}},
  year         = {{2021}},
}

@inbook{22306,
  author       = {{Koldewey, Christian and Gausemeier, Jürgen and Dumitrescu, Roman and Evers, Hans-Heinrich and Frank, Maximilian and Reinhold, Jannik}},
  booktitle    = {{Digitalization}},
  editor       = {{Schallmo, Daniel R. and Tidd, Joseph}},
  pages        = {{205--237}},
  publisher    = {{Springer Nature}},
  title        = {{{Development Process for Smart Service Strategies: Grasping the Potentials of Digitalization for Servitization}}},
  doi          = {{https://doi.org/10.1007/978-3-030-69380-0_12#DOI}},
  year         = {{2021}},
}

@inproceedings{22307,
  author       = {{Eckertz, Daniel and Möller, Marus and Anacker, Harald and Dumitrescu, Roman}},
  booktitle    = {{ Proceedings of the International Conference on Information and Computer Technologies}},
  location     = {{Kahului, Hawaii, United States of America}},
  title        = {{{Digital Knowledge Base for Industrial Augmented Reality Systems Based on Semantic Technologies}}},
  year         = {{2021}},
}

@inproceedings{22309,
  abstract     = {{Approximate computing (AC) has acquired significant maturity in recent years as a promising approach to obtain energy and area-efficient hardware. Automated approximate accelerator synthesis involves a great deal of complexity on the size of design space which exponentially grows with the number of possible approximations. Design space exploration of approximate accelerator synthesis is usually targeted via heuristic-based search methods. The majority of existing frameworks prune a large part of the design space using a greedy-based approach to keep the problem tractable. Therefore, they result in inferior solutions since many potential solutions are neglected in the pruning process without the possibility of backtracking of removed approximate instances. In this paper, we address the aforementioned issue by adopting Monte Carlo Tree Search (MCTS), as an efficient stochastic learning-based search algorithm, in the context of automated synthesis of approximate accelerators. This enables the synthesis frameworks to deeply subsamples the design space of approximate accelerator synthesis toward most promising approximate instances based on the required performance goals, i.e., power consumption, area, or/and delay. We investigated the challenges of providing an efficient open-source framework that benefits analytical and search-based approximation techniques simultaneously to both speed up the synthesis runtime and improve the quality of obtained results. Besides, we studied the utilization of machine learning algorithms to improve the performance of several critical steps, i.e., accelerator quality testing, in the synthesis framework. The proposed framework can help the community to rapidly generate efficient approximate accelerators in a reasonable runtime.}},
  author       = {{Awais, Muhammad and Platzner, Marco}},
  booktitle    = {{Proceedings of IEEE Computer Society Annual Symposium on VLSI}},
  keywords     = {{Approximate computing, Design space exploration, Accelerator synthesis}},
  location     = {{Tampa, Florida USA (Virtual)}},
  pages        = {{384--389}},
  publisher    = {{IEEE}},
  title        = {{{MCTS-Based Synthesis Towards Efficient Approximate Accelerators}}},
  year         = {{2021}},
}

@inproceedings{22448,
  author       = {{Kiesel, Johannes and Spina, Damiano and Wachsmuth, Henning and Stein, Benno}},
  booktitle    = {{Proceedings of the 2021 Conversational User Interfaces Conference}},
  pages        = {{1--5}},
  title        = {{{The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases}}},
  year         = {{2021}},
}