@inproceedings{64260, author = {{Mager, Thomas and Jürgenhake, Christoph and Dumitrescu, Roman}}, booktitle = {{Proceedings of the German Microwave Conference (GeMiC)}}, location = {{Ulm}}, pages = {{224--227}}, title = {{{Efficient method for determining substrate parameters of additive manufactured spatial circuit carriers}}}, year = {{2022}}, } @inproceedings{46305, abstract = {{Hardness of Multi-Objective (MO) continuous optimization problems results from an interplay of various problem characteristics, e. g. the degree of multi-modality. We present a benchmark study of classical and diversity focused optimizers on multi-modal MO problems based on automated algorithm configuration. We show the large effect of the latter and investigate the trade-off between convergence in objective space and diversity in decision space.}}, author = {{Rook, J and Trautmann, Heike and Bossek, Jakob and Grimme, C}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference Companion}}, editor = {{Fieldsend, J and Wagner, M.}}, isbn = {{9781450392686}}, pages = {{356–359}}, publisher = {{Association for Computing Machinery}}, title = {{{On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems}}}, doi = {{10.1145/3520304.3528998}}, year = {{2022}}, } @article{64264, abstract = {{Abstract Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.}}, author = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}}, issn = {{2511-0896}}, journal = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}}, number = {{6}}, pages = {{427--431}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Künstliche Intelligenz im Engineering}}}, doi = {{10.1515/zwf-2022-1074}}, volume = {{117}}, year = {{2022}}, } @article{64263, abstract = {{Abstract Künstliche Intelligenz bietet großes Potenzial im Engineering. Der Einsatz gestattet insbesondere für Wissensarbeiter eine effiziente Arbeitsteilung, in der beispielsweise fehleranfällige und repetitive Aktivitäten unterstützt werden. Eine erfolgreiche Einführung bedarf einer vorangehenden Analyse von nutzenstiftenden Einsatzpotenzialen, bei der alle Anwendenden frühzeitig einbezogen werden. Der folgende Beitrag verdeutlicht dieses Vorgehen anhand eines realen Beispiels im Sondermaschinenbau.}}, author = {{Kharatyan, Aschot and Humpert, Lynn and Anacker, Harald and Dumitrescu, Roman and Wäschle, Moritz and Albers, Albert and Horstmeyer, Sarah}}, issn = {{2511-0896}}, journal = {{Zeitschrift für wirtschaftlichen Fabrikbetrieb}}, number = {{6}}, pages = {{427--431}}, publisher = {{Walter de Gruyter GmbH}}, title = {{{Künstliche Intelligenz im Engineering}}}, doi = {{10.1515/zwf-2022-1074}}, volume = {{117}}, year = {{2022}}, } @article{34614, abstract = {{Mit steigenden Optimierungsanforderungen an das Individuum wächst auch das indivi- duelle Bedürfnis nach Kontrolle. Dieses kann u. a. durch self tracking-Technologien erfüllt werden. Anhand von drei Fallbeispielen – der Personenwaage, dem Wearable und dem habit tracker – zeigt dieser Aufsatz, wie sich medienbasierte Selbsttechnologien im historischen Verlauf intensiviert und stärker in den Alltag integriert haben. Ein besonderer Fokus liegt dabei auf der Ambivalenz dieser Medien: Ermöglichen sie auf der einen Seite zwar eine Selbstkontrolle und stellen so potenziell sta- bilisierende Ressourcen für das Individuum dar, schaffen sie auf der anderen Seite auch neue Anforderungen, die es zu erfüllen gilt.}}, author = {{Schloots, Franziska Margarete}}, journal = {{ffk Journal}}, keywords = {{self-tracking, Selbsttechnologien, Wearable, Bullet Journal, Personenwaage, Selbstvermessung}}, number = {{7}}, pages = {{74--91}}, title = {{{‚Understand what’s happening within‘. Selbstkontrolle mit Personenwaage, Wearable und habit tracker}}}, doi = {{10.25969/MEDIAREP/18238}}, volume = {{6}}, year = {{2022}}, } @inproceedings{32247, author = {{Alshomary, Milad and Rieskamp, Jonas and Wachsmuth, Henning}}, booktitle = {{Proceedings of the 9th International Conference on Computational Models of Argument}}, pages = {{21 -- 31}}, title = {{{Generating Contrastive Snippets for Argument Search}}}, doi = {{http://dx.doi.org/10.3233/FAIA220138}}, year = {{2022}}, } @inproceedings{30840, author = {{Alshomary, Milad and El Baff, Roxanne and Gurcke, Timon and Wachsmuth, Henning}}, booktitle = {{Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics}}, pages = {{8782 -- 8797}}, title = {{{The Moral Debater: A Study on the Computational Generation of Morally Framed Arguments}}}, year = {{2022}}, } @article{60369, abstract = {{AbstractNon‐linear optimization is essential to many areas of geometry processing research. However, when experimenting with different problem formulations or when prototyping new algorithms, a major practical obstacle is the need to figure out derivatives of objective functions, especially when second‐order derivatives are required. Deriving and manually implementing gradients and Hessians is both time‐consuming and error‐prone. Automatic differentiation techniques address this problem, but can introduce a diverse set of obstacles themselves, e.g. limiting the set of supported language features, imposing restrictions on a program's control flow, incurring a significant run time overhead, or making it hard to exploit sparsity patterns common in geometry processing. We show that for many geometric problems, in particular on meshes, the simplest form of forward‐mode automatic differentiation is not only the most flexible, but also actually the most efficient choice. We introduce TinyAD: a lightweight C++ library that automatically computes gradients and Hessians, in particular of sparse problems, by differentiating small (tiny) sub‐problems. Its simplicity enables easy integration; no restrictions on, e.g., looping and branching are imposed. TinyAD provides the basic ingredients to quickly implement first and second order Newton‐style solvers, allowing for flexible adjustment of both problem formulations and solver details. By showcasing compact implementations of methods from parametrization, deformation, and direction field design, we demonstrate how TinyAD lowers the barrier to exploring non‐linear optimization techniques. This enables not only fast prototyping of new research ideas, but also improves replicability of existing algorithms in geometry processing. TinyAD is available to the community as an open source library.}}, author = {{Schmidt, Patrick and Born, Janis and Bommes, David and Campen, Marcel and Kobbelt, Leif}}, issn = {{0167-7055}}, journal = {{Computer Graphics Forum}}, number = {{5}}, pages = {{113--124}}, publisher = {{Wiley}}, title = {{{TinyAD: Automatic Differentiation in Geometry Processing Made Simple}}}, doi = {{10.1111/cgf.14607}}, volume = {{41}}, year = {{2022}}, } @article{60371, abstract = {{We describe a method for the generation of seamless surface parametrizations with guaranteed local injectivity and full control over holonomy. Previous methods guarantee only one of the two. Local injectivity is required to enable these parametrizations' use in applications such as surface quadrangulation and spline construction. Holonomy control is crucial to enable guidance or prescription of the parametrization's isocurves based on directional information, in particular from cross-fields or feature curves, and more generally to constrain the parametrization topologically. To this end we investigate the relation between cross-field topology and seamless parametrization topology. Leveraging previous results on locally injective parametrization and combining them with insights on this relation in terms of holonomy, we propose an algorithm that meets these requirements. A key component relies on the insight that arbitrary surface cut graphs, as required for global parametrization, can be homeomorphically modified to assume almost any set of turning numbers with respect to a given target cross-field.}}, author = {{Shen, Hanxiao and Zhu, Leyi and Capouellez, Ryan and Panozzo, Daniele and Campen, Marcel and Zorin, Denis}}, issn = {{0730-0301}}, journal = {{ACM Transactions on Graphics}}, number = {{4}}, pages = {{1--12}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{Which cross fields can be quadrangulated?}}}, doi = {{10.1145/3528223.3530187}}, volume = {{41}}, year = {{2022}}, } @article{60366, abstract = {{AbstractThe so‐called motorcycle graph has been employed in recent years for various purposes in the context of structured and aligned block decomposition of 2D shapes and 2‐manifold surfaces. Applications are in the fields of surface parametrization, spline space construction, semi‐structured quad mesh generation, or geometry data compression. We describe a generalization of this motorcycle graph concept to the three‐dimensional volumetric setting. Through careful extensions aware of topological intricacies of this higher‐dimensional setting, we are able to guarantee important block decomposition properties also in this case. We describe algorithms for the construction of this 3D motorcycle complex on the basis of either hexahedral meshes or seamless volumetric parametrizations. Its utility is illustrated on examples in hexahedral mesh generation and volumetric T‐spline construction.}}, author = {{Brückler, Hendrik and Gupta, Ojaswi and Mandad, Manish and Campen, Marcel}}, issn = {{0167-7055}}, journal = {{Computer Graphics Forum}}, number = {{2}}, pages = {{221--235}}, publisher = {{Wiley}}, title = {{{The 3D Motorcycle Complex for Structured Volume Decomposition}}}, doi = {{10.1111/cgf.14470}}, volume = {{41}}, year = {{2022}}, } @article{60368, abstract = {{AbstractWe present a reliable method to generate planar meshes of nonlinear rational triangular elements. The elements are guaranteed to be valid, i.e. defined by injective rational functions. The mesh is guaranteed to conform exactly, without geometric error, to arbitrary rational domain boundary and feature curves. The method generalizes the recent Bézier Guarding technique, which is applicable only to polynomial curves and elements. This generalization enables the accurate handling of practically important cases involving, for instance, circular or elliptic arcs and NURBS curves, which cannot be matched by polynomial elements. Furthermore, although many practical scenarios are concerned with rational functions of quadratic and cubic degree only, our method is fully general and supports arbitrary degree. We demonstrate the method on a variety of test cases.}}, author = {{Khanteimouri, Payam and Mandad, Manish and Campen, Marcel}}, issn = {{0167-7055}}, journal = {{Computer Graphics Forum}}, number = {{5}}, pages = {{89--99}}, publisher = {{Wiley}}, title = {{{Rational Bézier Guarding}}}, doi = {{10.1111/cgf.14605}}, volume = {{41}}, year = {{2022}}, } @article{60363, author = {{Mandad, Manish and Chen, Ruizhi and Bommes, David and Campen, Marcel}}, issn = {{0167-8396}}, journal = {{Computer Aided Geometric Design}}, publisher = {{Elsevier BV}}, title = {{{Intrinsic mixed-integer polycubes for hexahedral meshing}}}, doi = {{10.1016/j.cagd.2022.102078}}, volume = {{94}}, year = {{2022}}, } @article{60365, author = {{Hinderink, Steffen and Mandad, Manish and Campen, Marcel}}, issn = {{0167-8396}}, journal = {{Computer Aided Geometric Design}}, publisher = {{Elsevier BV}}, title = {{{Angle-bounded 2D mesh simplification}}}, doi = {{10.1016/j.cagd.2022.102085}}, volume = {{95}}, year = {{2022}}, } @article{60372, abstract = {{Developments in the field of parametrization-based quad mesh generation on surfaces have been impactful over the past decade. In this context, an important advance has been the replacement of error-prone rounding in the generation of integer-grid maps, by robust quantization methods. In parallel, parametrization-based hex mesh generation for volumes has been advanced. In this volumetric context, however, the state-of-the-art still relies on fragile rounding, not rarely producing defective meshes, especially when targeting a coarse mesh resolution. We present a method to robustly quantize volume parametrizations, i.e., to determine guaranteed valid choices of integers for 3D integer-grid maps. Inspired by the 2D case, we base our construction on a non-conforming cell decomposition of the volume, a 3D analogue of a T-mesh. In particular, we leverage the motorcycle complex, a recent generalization of the motorcycle graph, for this purpose. Integer values are expressed in a differential manner on the edges of this complex, enabling the efficient formulation of the conditions required to strictly prevent forcing the map into degeneration. Applying our method in the context of hexahedral meshing, we demonstrate that hexahedral meshes can be generated with significantly improved flexibility.}}, author = {{Brückler, Hendrik and Bommes, David and Campen, Marcel}}, issn = {{0730-0301}}, journal = {{ACM Transactions on Graphics}}, number = {{4}}, pages = {{1--19}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{Volume parametrization quantization for hexahedral meshing}}}, doi = {{10.1145/3528223.3530123}}, volume = {{41}}, year = {{2022}}, } @article{60334, abstract = {{In this article, we provide a detailed survey of techniques for hexahedral mesh generation. We cover the whole spectrum of alternative approaches to mesh generation, as well as post-processing algorithms for connectivity editing and mesh optimization. For each technique, we highlight capabilities and limitations, also pointing out the associated unsolved challenges. Recent relaxed approaches, aiming to generate not pure-hex but hex-dominant meshes, are also discussed. The required background, pertaining to geometrical as well as combinatorial aspects, is introduced along the way.}}, author = {{Pietroni, Nico and Campen, Marcel and Sheffer, Alla and Cherchi, Gianmarco and Bommes, David and Gao, Xifeng and Scateni, Riccardo and Ledoux, Franck and Remacle, Jean and Livesu, Marco}}, issn = {{0730-0301}}, journal = {{ACM Transactions on Graphics}}, number = {{2}}, pages = {{1--44}}, publisher = {{Association for Computing Machinery (ACM)}}, title = {{{Hex-Mesh Generation and Processing: A Survey}}}, doi = {{10.1145/3554920}}, volume = {{42}}, year = {{2022}}, } @article{30511, abstract = {{AbstractMany critical codebases are written in C, and most of them use preprocessor directives to encode variability, effectively encoding software product lines. These preprocessor directives, however, challenge any static code analysis. SPLlift, a previously presented approach for analyzing software product lines, is limited to Java programs that use a rather simple feature encoding and to analysis problems with a finite and ideally small domain. Other approaches that allow the analysis of real-world C software product lines use special-purpose analyses, preventing the reuse of existing analysis infrastructures and ignoring the progress made by the static analysis community. This work presents VarAlyzer, a novel static analysis approach for software product lines. VarAlyzer first transforms preprocessor constructs to plain C while preserving their variability and semantics. It then solves any given distributive analysis problem on transformed product lines in a variability-aware manner. VarAlyzer ’s analysis results are annotated with feature constraints that encode in which configurations each result holds. Our experiments with 95 compilation units of OpenSSL show that applying VarAlyzer enables one to conduct inter-procedural, flow-, field- and context-sensitive data-flow analyses on entire product lines for the first time, outperforming the product-based approach for highly-configurable systems.}}, author = {{Schubert, Philipp and Gazzillo, Paul and Patterson, Zach and Braha, Julian and Schiebel, Fabian Benedikt and Hermann, Ben and Wei, Shiyi and Bodden, Eric}}, issn = {{0928-8910}}, journal = {{Automated Software Engineering}}, keywords = {{inter-procedural static analysis, software product lines, preprocessor, LLVM, C/C++}}, number = {{1}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Static data-flow analysis for software product lines in C}}}, doi = {{10.1007/s10515-022-00333-1}}, volume = {{29}}, year = {{2022}}, } @article{24721, author = {{Fathi Ahmed, Abdullah and Ahmed Sherif, Mohamed and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}}, journal = {{Data Knowl. Eng.}}, pages = {{101874}}, title = {{{Multilingual Verbalization and Summarization for Explainable Link Discovery}}}, doi = {{10.1016/j.datak.2021.101874}}, volume = {{133}}, year = {{2021}}, } @inproceedings{24722, author = {{Röder, Michael and Frerk, Philip and Conrads, Felix and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web - 18th International Conference, {ESWC} 2021, Virtual Event, June 6-10, 2021, Proceedings}}, editor = {{Verborgh, Ruben and Hose, Katja and Paulheim, Heiko and Champin, Pierre-Antoine and Maleshkova, Maria and Corcho, Oscar and Ristoski, Petar and Alam, Mehwish}}, pages = {{93--108}}, publisher = {{Springer}}, title = {{{Applying Grammar-Based Compression to RDF}}}, doi = {{10.1007/978-3-030-77385-4\_6}}, volume = {{12731}}, year = {{2021}}, } @inproceedings{24723, author = {{Ali, Manzoor and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web: {ESWC} 2021 Satellite Events - Virtual Event, June 6-10, 2021, Revised Selected Papers}}, editor = {{Verborgh, Ruben and Dimou, Anastasia and Hogan, Aidan and d'Amato, Claudia and Tiddi, Ilaria and Br{\"{o}}ring, Arne and Maier, Simon and Ongenae, Femke and Tommasini, Riccardo and Alam, Mehwish}}, pages = {{136--140}}, publisher = {{Springer}}, title = {{{Unsupervised Relation Extraction Using Sentence Encoding}}}, doi = {{10.1007/978-3-030-80418-3\_25}}, volume = {{12739}}, year = {{2021}}, } @inproceedings{24724, author = {{Ali, Manzoor and Saleem, Muhammad and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web: {ESWC} 2021 Satellite Events - Virtual Event, June 6-10, 2021, Revised Selected Papers}}, editor = {{Verborgh, Ruben and Dimou, Anastasia and Hogan, Aidan and d'Amato, Claudia and Tiddi, Ilaria and Br{\"{o}}ring, Arne and Maier, Simon and Ongenae, Femke and Tommasini, Riccardo and Alam, Mehwish}}, pages = {{136--140}}, publisher = {{Springer}}, title = {{{Unsupervised Relation Extraction Using Sentence Encoding}}}, doi = {{10.1007/978-3-030-80418-3\_25}}, volume = {{12739}}, year = {{2021}}, }