@article{27123,
  author       = {{Poddubnyi, Vladimir I. and Trächtler, Ansgar and Warkentin, Andreas and Henke, Christian}},
  journal      = {{Russian Engineering Research}},
  number       = {{3}},
  pages        = {{198--201}},
  publisher    = {{Springer}},
  title        = {{{Model of a Triangular Caterpillar Drive and Analysis of Vertical Vehicle Dynamics}}},
  volume       = {{41}},
  year         = {{2021}},
}

@inproceedings{27365,
  author       = {{Meyer, Marius}},
  booktitle    = {{Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies}},
  title        = {{{Towards Performance Characterization of FPGAs in Context of HPC using OpenCL Benchmarks}}},
  doi          = {{10.1145/3468044.3468058}},
  year         = {{2021}},
}

@misc{27366,
  author       = {{Moritzer, Elmar and Hecker, Felix}},
  booktitle    = {{Jahresmagazin Kunststofftechnik}},
  pages        = {{70--75}},
  title        = {{{Untersuchung der mechanischen Eigenschaften, Hintergründe und weitere Entwicklungen im Kunststoff Freiformen}}},
  year         = {{2021}},
}

@inproceedings{27418,
  author       = {{Weidmann, Nils and Anjorin, Anthony}},
  booktitle    = {{{STAF} 2021 Workshop Proceedings: 9th International Workshop on Bidirectional Transformations, Joint Workshop on Foundations and Practice of Visual Modeling and Data for Model-Driven Engineering, International workshop on {MDE} for Smart IoT Systems, 4th International Workshop on (Meta)Modeling for Healthcare Systems, and 20th International Workshop on {OCL} and Textual Modeling co-located with Software Technologies: Applications and Foundations, Federation of Conferences {(STAF} 2021), Virtual Event / Bergen, Norway, June 21-25, 2021}},
  editor       = {{Iovino, Ludovico and Michael Kristensen, Lars}},
  pages        = {{54--64}},
  publisher    = {{CEUR-WS.org}},
  title        = {{{eMoflon: : Neo - Consistency and Model Management with Graph Databases}}},
  volume       = {{2999}},
  year         = {{2021}},
}

@inproceedings{27479,
  author       = {{Richts-Matthaei, Kristina and Albrecht-Hohmaier, Martin and Röwenstrunk, Daniel and Münzmay, Andreas}},
  location     = {{Alicante, Spain}},
  title        = {{{MEI Meets NFDI4Culture}}},
  year         = {{2021}},
}

@article{27528,
  abstract     = {{<p>Inhalt Additive Fertigungsverfahren bieten große Vorteile in der Bauteilgestaltung, können aufgrund ihrer Verfahrenseigenschaften aber auch zu einer Erhöhung der Bauteilfunktionalität beitragen. Mit dem Laser-Strahlschmelzen lassen sich Partikeldämpfer direkt im Fertigungsprozess in die Bauteile integrieren und an die vorliegenden Randbedingungen anpassen. Hierzu wird eine experimentelle Methode basierend auf der komplexen mechanischen Leistung vorgestellt. Aus Kennfeldern werden für unterschiedliche geometrische Einflüsse erste Konstruktionsregeln abgeleitet, die in der Anwendung im Konstruktionsprozess als eine Hilfestellung zur Erhöhung der Bauteildämpfung zur Reduzierung unerwünschter Schwingungen dienen.</p>}},
  author       = {{Künneke, Thomas and Zimmer, Detmar}},
  issn         = {{0720-5953}},
  journal      = {{Konstruktion}},
  pages        = {{72--78}},
  title        = {{{Konstruktionsregeln für additiv gefertigte Partikeldämpfer/Design rules for additive manufactured particle dampers}}},
  doi          = {{10.37544/0720-5953-2021-11-12-72}},
  year         = {{2021}},
}

@article{21004,
  abstract     = {{Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers.}},
  author       = {{Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}},
  issn         = {{0162-8828}},
  journal      = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
  keywords     = {{Automated Machine Learning, Multi Label Classification, Hierarchical Planning, Bayesian Optimization}},
  pages        = {{1--1}},
  title        = {{{AutoML for Multi-Label Classification: Overview and Empirical Evaluation}}},
  doi          = {{10.1109/tpami.2021.3051276}},
  year         = {{2021}},
}

@article{21092,
  abstract     = {{Automated Machine Learning (AutoML) seeks to automatically find so-called machine learning pipelines that maximize the prediction performance when being used to train a model on a given dataset. One of the main and yet open challenges in AutoML is an effective use of computational resources: An AutoML process involves the evaluation of many candidate pipelines, which   are costly but often ineffective because they are canceled due to a timeout.
In this paper, we present an approach to predict the runtime of two-step machine learning pipelines with up to one pre-processor, which can be used to anticipate whether or not a pipeline will time out. Separate runtime models are trained offline for each algorithm that may be used in a pipeline, and an overall prediction is derived from these models. We empirically show that the approach increases successful evaluations made by an AutoML tool while preserving or even improving on the previously best solutions.}},
  author       = {{Mohr, Felix and Wever, Marcel Dominik and Tornede, Alexander and Hüllermeier, Eyke}},
  journal      = {{IEEE Transactions on Pattern Analysis and Machine Intelligence}},
  publisher    = {{IEEE}},
  title        = {{{Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning}}},
  year         = {{2021}},
}

@article{21125,
  author       = {{Kismann, Michael and Riedl, Dr. Thomas and Lindner, Prof. Dr. Jörg KN}},
  journal      = {{Materials Science in Semiconductor Processing}},
  title        = {{{Ordered arrays of Si nanopillars with alternating diameters fabricated by nanosphere lithography and metal-assisted chemical etching}}},
  year         = {{2021}},
}

@inproceedings{21326,
  author       = {{Holtmann, Jörg and Steghöfer, Jan-Phillipp and Rath, Michael and Schmelter, David}},
  booktitle    = {{Software Engineering 2021}},
  editor       = {{Koziolek, Anne and Schaefer, Ina and Seidl, Christoph}},
  location     = {{Remote / Braunschweig, Germany }},
  pages        = {{59--60}},
  title        = {{{Cutting through the Jungle: Disambiguating Model-based Traceability Terminology (Extended Abstract)}}},
  doi          = {{10.18420/SE2021_18}},
  volume       = {{P-310}},
  year         = {{2021}},
}

@article{21374,
  abstract     = {{<jats:p>A dark-field scanning transmission ion microscopy detector was designed for the helium ion microscope. The detection principle is based on a secondary electron conversion holder with an exchangeable aperture strip allowing its acceptance angle to be tuned from 3 to 98 mrad. The contrast mechanism and performance were investigated using freestanding nanometer-thin carbon membranes. The results demonstrate that the detector can be optimized either for most efficient signal collection or for maximum image contrast. The designed setup allows for the imaging of thin low-density materials that otherwise provide little signal or contrast and for a clear end-point detection in the fabrication of nanopores. In addition, the detector is able to determine the thickness of membranes with sub-nanometer precision by quantitatively evaluating the image signal and comparing the results with Monte Carlo simulations. The thickness determined by the dark-field transmission detector is compared to X-ray photoelectron spectroscopy and energy-filtered transmission electron microscopy measurements.</jats:p>}},
  author       = {{Emmrich, Daniel and Wolff, Annalena and Meyerbröker, Nikolaus and Lindner, Jörg and Beyer, André and Gölzhäuser, Armin}},
  issn         = {{2190-4286}},
  journal      = {{Beilstein Journal of Nanotechnology}},
  pages        = {{222--231}},
  title        = {{{Scanning transmission helium ion microscopy on carbon nanomembranes}}},
  doi          = {{10.3762/bjnano.12.18}},
  year         = {{2021}},
}

@inproceedings{21442,
  author       = {{Tinkloh, Steffen Rainer and Wu, Tao and Tröster, Thomas and Niendorf, Thomas}},
  keywords     = {{Micromechanics, Fast Fourier Transform (FFT), Reduced Order Modelling, Homogenization}},
  title        = {{{Development of a submodel technique for FFT-based solvers in micromechanical analysis}}},
  year         = {{2021}},
}

@techreport{21569,
  abstract     = {{Die kontinuierliche Weiterentwicklung des eigenen Geschäftsmodells ist für eine Organisation von entscheidender Bedeutung, um wettbewerbsfähig und somit nachhaltig erfolgreich zu bleiben. Während für die Entwicklung neuer Geschäftsmodelle häufig Workshops und einfache Software-Tools zur Visualisierung genutzt werden, wurden in der Forschung bereits erste Ansätze von datengetriebener Geschäftsmodellentwicklung (GME) vorgestellt. Diese Ansätze nutzen dabei Daten, Informationen oder auch Wissen aus internen und externen Unternehmensquellen, um den GME-Prozess zu unterstützen. Innerhalb dieses Beitrags zeigen wir einige Ansätze aus der aktuellen Literatur und analysieren wie ihre Datennutzung den GME-Prozess unterstützt. Weiterhin stellen wir mit dem BMDL Feature Modeler ein Tool vor, welches den GME-Prozess mit Expertenwissen unterstützt.}},
  author       = {{Gottschalk, Sebastian and Yigitbas, Enes}},
  publisher    = {{Gesellschaft für Informatik}},
  title        = {{{Von datenbasierter zu datengetriebener Geschäftsmodellentwicklung: Ein Überblick über Software-Tools  und deren Datennutzung}}},
  volume       = {{1}},
  year         = {{2021}},
}

@inproceedings{21570,
  author       = {{Tornede, Tanja and Tornede, Alexander and Wever, Marcel Dominik and Hüllermeier, Eyke}},
  booktitle    = {{Proceedings of the Genetic and Evolutionary Computation Conference}},
  title        = {{{Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance}}},
  year         = {{2021}},
}

@article{21631,
  abstract     = {{<jats:p>Secret sharing is a well-established cryptographic primitive for storing highly sensitive information like encryption keys for encoded data. It describes the problem of splitting a secret into different shares, without revealing any information to its shareholders. Here, we demonstrate an all-optical solution for secret sharing based on metasurface holography. In our concept, metasurface holograms are used as spatially separable shares that carry encrypted messages in the form of holographic images. Two of these shares can be recombined by bringing them close together. Light passing through this stack of metasurfaces accumulates the phase shift of both holograms and optically reconstructs the secret with high fidelity. In addition, the hologram generated by each single metasurface can uniquely identify its shareholder. Furthermore, we demonstrate that the inherent translational alignment sensitivity between two stacked metasurface holograms can be used for spatial multiplexing, which can be further extended to realize optical rulers.</jats:p>}},
  author       = {{Georgi, Philip and Wei, Qunshuo and Sain, Basudeb and Schlickriede, Christian and Wang, Yongtian and Huang, Lingling and Zentgraf, Thomas}},
  issn         = {{2375-2548}},
  journal      = {{Science Advances}},
  number       = {{16}},
  title        = {{{Optical secret sharing with cascaded metasurface holography}}},
  doi          = {{10.1126/sciadv.abf9718}},
  volume       = {{7}},
  year         = {{2021}},
}

@inproceedings{21639,
  abstract     = {{The development of effective business models is an essential task in highly competitive markets like mobile ecosystems. Existing development methods for these business models do not specifically focus that the development process profoundly depends on the situation (e.g., market size, regulations) of the mobile app developer. Here, a mismatch between method and situation can lead to poor resource management and longer development cycles. In software engineering, situational method engineering is used for software projects to configure a development method out of a method repository based on the project situation. Analogously, we support creating situation-specific business model development methods with a method base and new user roles. Here, the method engineer obtains the knowledge of the domain expert and stores it in the method base as elements, building blocks, and patterns. The expert knowledge is derived from a grey literature review on mobile development processes. After this, the method engineer constructs the development method based on the described situation of the business developer. We provide an open-source tool and evaluate it by constructing a local event platform's business model development method.    }},
  author       = {{Gottschalk, Sebastian and Yigitbas, Enes and Nowosad, Alexander and Engels, Gregor}},
  booktitle    = {{Enterprise, Business-Process and Information Systems Modeling}},
  keywords     = {{Business Model Development, Situational Method Engineering, Mobile App, Business Model Development Tools}},
  publisher    = {{Springer}},
  title        = {{{Situation-specific Business Model Development Methods for Mobile App Developers}}},
  doi          = {{10.1007/978-3-030-79186-5_17}},
  year         = {{2021}},
}

@book{23458,
  author       = {{Dumitrescu, Roman and Albers, Albert and Gausemeier, Jürgen and Riedel, Oliver and Stark, Rainer}},
  publisher    = {{Fraunhofer-Institut für Entwurfstechnik Mechatronik IEM, Paderborn}},
  title        = {{{Engineering in Deutschland – Status quo in Wirtschaft und Wissenschaft. Ein Beitrag zum Advanced Systems Engineering}}},
  year         = {{2021}},
}

@article{23525,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>In the field of Model-Driven Engineering, Triple Graph Grammars
(TGGs) play an important role as a rule-based means of implementing
consistency management. From a declarative specification of a
consistency relation, several operations including forward and
backward transformations, (concurrent) synchronisation, and
consistency checks can be automatically derived. For TGGs to be
applicable in realistic application scenarios, expressiveness in
terms of supported language features is very important. A TGG tool
is schema compliant if it can take domain constraints, such as
multiplicity constraints in a meta-model, into account when
performing consistency management tasks. To guarantee schema
compliance, most TGG tools allow application conditions to be
attached as necessary to relevant rules. This strategy is
problematic for at least two reasons: First, ensuring compliance to
a sufficiently expressive schema for all previously mentioned
derived operations is still an open challenge; to the best of our
knowledge, all existing TGG tools only support a very restricted
subset of application conditions. Second, it is conceptually
demanding for the user to indirectly specify domain constraints as
application conditions, especially because this has to be completely
revisited every time the TGG or domain constraint is changed. While
domain constraints can in theory be automatically transformed to
obtain the required set of application conditions, this has only
been successfully transferred to TGGs for a very limited subset of
domain constraints. To address these limitations, this paper
proposes a search-based strategy for achieving schema compliance. We
show that all correctness and completeness properties, previously
proven in a setting without domain constraints, still hold when
schema compliance is to be additionally guaranteed. An
implementation and experimental evaluation are provided to support
our claim of practical applicability.</jats:p>}},
  author       = {{Weidmann, Nils and Anjorin, Anthony}},
  issn         = {{0934-5043}},
  journal      = {{Formal Aspects of Computing}},
  publisher    = {{Springer}},
  title        = {{{Schema Compliant Consistency Management via Triple Graph Grammars and Integer Linear Programming}}},
  doi          = {{10.1007/s00165-021-00557-0}},
  year         = {{2021}},
}

@article{23526,
  abstract     = {{<jats:p>Modern and flexible application-level software platforms increase the attack surface of connected vehicles and thereby require automotive engineers to adopt additional security control techniques. These techniques encompass host-based intrusion detection systems (HIDSs) that detect suspicious activities in application contexts. Such application-aware HIDSs originate in information and communications technology systems and have a great potential to deal with the flexible nature of application-level software platforms. However, the elementary characteristics of known application-aware HIDS approaches and thereby the implications for their transfer to the automotive sector are unclear. In previous work, we presented a systematic literature review (SLR) covering the state of the art of application-aware HIDS approaches. We synthesized our findings by means of a fine-grained classification for each approach specified through a feature model and corresponding variant models. These models represent the approaches’ elementary characteristics. Furthermore, we summarized key findings and inferred implications for the transfer of application-aware HIDSs to the automotive sector. In this article, we extend the previous work by several aspects. We adjust the quality evaluation process within the SLR to be able to consider high quality conference publications, which results in an extended final pool of publications. For supporting HIDS developers on the task of configuring HIDS analysis techniques based on machine learning, we report on initial results on the applicability of AutoML. Furthermore, we present lessons learned regarding the application of the feature and variant model approach for SLRs. Finally, we more thoroughly describe the SLR study design.</jats:p>}},
  author       = {{Schubert, David and Eikerling, Hendrik and Holtmann, Jörg}},
  issn         = {{2624-9898}},
  journal      = {{Frontiers in Computer Science}},
  publisher    = {{Frontiers Media}},
  title        = {{{Application-Aware Intrusion Detection: A Systematic Literature Review, Implications for Automotive Systems, and Applicability of AutoML}}},
  doi          = {{10.3389/fcomp.2021.567873}},
  volume       = {{3}},
  year         = {{2021}},
}

@unpublished{23534,
  abstract     = {{In recent years, the World Economic Forum has identified software security as
the most significant technological risk to the world's population, as
software-intensive systems process critical data and provide critical services.
This raises the question of the extent to which German companies are addressing
software security in developing and operating their software products. This
paper reports on the results of an extensive study among developers, product
owners, and managers to answer this question. Our results show that ensuring
security is a multi-faceted challenge for companies, involving low awareness,
inaccurate self-assessment, and a lack of competence on the topic of secure
software development among all stakeholders. The current situation in software
development is therefore detrimental to the security of software products in
the medium and long term.}},
  author       = {{Dziwok, Stefan and Koch, Thorsten and Merschjohann, Sven and Budweg, Boris and Leuer, Sebastian}},
  booktitle    = {{arXiv:2108.11752}},
  title        = {{{AppSecure.nrw Software Security Study}}},
  year         = {{2021}},
}