@inbook{45552, abstract = {{The field of teaching technologies is in constant interplay between educational and industrial advances. Since the beginning of the twenty-first century, digitalization and automatization have become increasingly important. In industrial and social life, we see similar fast-moving developments. These factors challenge education, specifically vocational education, greatly, and raise two very different, yet very much connected questions: how to prepare students for their vocational lives and how to prepare teachers to communicate the necessary competencies to their students? This chapter provides an overview of advances, challenges, and possible solutions, focusing on the three key fields of vocational education in Germany: Industry 4.0, Education 4.0, and innovative teacher education. Most importantly, however, the text examines the continuous interplay between and among these fields. The beginning of the chapter is dedicated to vocational teacher education, in accordance with industrial and educational advances. Specifying this, characteristics of Industry 4.0, as well as students' and teachers' perceptions of Industry 4.0, are discussed. This is followed by an introduction to the concept of so-called learning factories as a possible way of integrating aspects of Industry 4.0 in German vocational schools. The end of the chapter is dedicated to the required changes in educational settings today and in the future. Though Industry 4.0, Education 4.0, and innovative teacher education are each widely discussed in the current literature, the interplay of all three fields reveals a research gap. This chapter tries to close this gap and provide an important contribution to the research field.}}, author = {{Jonas-Ahrend, Gabriela and Vernholz, Mats and Temmen, Katrin}}, booktitle = {{Teacher Education in the Wake of Covid-19 }}, editor = {{Craig, Cheryl J. and Mena, Juanjo and Kane, Ruth G.}}, isbn = {{9781804554630}}, issn = {{1479-3687}}, pages = {{175--191}}, publisher = {{Emerald Publishing Limited}}, title = {{{Teaching Technologies: Continuous Interplay Between Educational and Industrial Advances}}}, doi = {{10.1108/s1479-368720230000041019}}, volume = {{41}}, year = {{2023}}, } @article{45712, author = {{Häsel-Weide, Uta}}, journal = {{Die Grundschulzeitschrift}}, number = {{339}}, pages = {{6--11}}, publisher = {{Friedrich Verlag}}, title = {{{ Inklusiver Mathematikunterricht. Mathematiklernen in Vielfalt von Kompetenzen, Wegen und Lernsituationen}}}, year = {{2023}}, } @article{45713, author = {{Graf, Lara Marie and Wienhues, Inga and Häsel-Weide, Uta}}, journal = {{Die Grundschulzeitschrift}}, number = {{339}}, pages = {{20--23}}, publisher = {{Friedrich Verlag}}, title = {{{Addition und Subtraktion verstehen}}}, year = {{2023}}, } @inproceedings{45793, abstract = {{The global megatrends of digitization and sustainability lead to new challenges for the design and management of technical products in industrial companies. Product management - as the bridge between market and company - has the task to absorb and combine the manifold requirements and make the right product-related decisions. In the process, product management is confronted with heterogeneous information, rapidly changing portfolio components, as well as increasing product, and organizational complexity. Combining and utilizing data from different sources, e.g., product usage data and social media data leads to promising potentials to improve the quality of product-related decisions. In this paper, we reinforce the need for data-driven product management as an interdisciplinary field of action. The state of data-driven product management in practice was analyzed by conducting workshops with six manufacturing companies and hosting a focus group meeting with experts from different industries. We investigate the expectations and derive requirements leading us to open research questions, a vision for data-driven product management, and a research agenda to shape future research efforts.}}, author = {{Grigoryan, Khoren and Fichtler, Timm and Schreiner, Nick and Rabe, Martin and Panzner, Melina and Kühn, Arno and Dumitrescu, Roman and Koldewey, Christian}}, booktitle = {{Procedia CIRP 33}}, keywords = {{Product Management, Data Analytics, Data-Driven Design, Product-related data, Lifecycle Data, Tool-support}}, location = {{Sydney}}, title = {{{Data-Driven Product Management: A Practitioner-Driven Research Agenda}}}, year = {{2023}}, } @inproceedings{45812, author = {{Özcan, Leon and Fichtler, Timm and Kasten, Benjamin and Koldewey, Christian and Dumitrescu, Roman}}, keywords = {{Digital Platform, Platform Strategy, Strategic Management, Platform Life Cycle, Interview Study, Business Model, Business-to-Business, Two-sided Market, Multi-sided Market}}, location = {{Ljubljana}}, title = {{{Interview Study on Strategy Options for Platform Operation in B2B Markets}}}, year = {{2023}}, } @inproceedings{33734, abstract = {{Many applications require explainable node classification in knowledge graphs. Towards this end, a popular ``white-box'' approach is class expression learning: Given sets of positive and negative nodes, class expressions in description logics are learned that separate positive from negative nodes. Most existing approaches are search-based approaches generating many candidate class expressions and selecting the best one. However, they often take a long time to find suitable class expressions. In this paper, we cast class expression learning as a translation problem and propose a new family of class expression learning approaches which we dub neural class expression synthesizers. Training examples are ``translated'' into class expressions in a fashion akin to machine translation. Consequently, our synthesizers are not subject to the runtime limitations of search-based approaches. We study three instances of this novel family of approaches based on LSTMs, GRUs, and set transformers, respectively. An evaluation of our approach on four benchmark datasets suggests that it can effectively synthesize high-quality class expressions with respect to the input examples in approximately one second on average. Moreover, a comparison to state-of-the-art approaches suggests that we achieve better F-measures on large datasets. For reproducibility purposes, we provide our implementation as well as pretrained models in our public GitHub repository at https://github.com/dice-group/NeuralClassExpressionSynthesis}}, author = {{KOUAGOU, N'Dah Jean and Heindorf, Stefan and Demir, Caglar and Ngonga Ngomo, Axel-Cyrille}}, booktitle = {{The Semantic Web - 20th Extended Semantic Web Conference (ESWC 2023)}}, editor = {{Pesquita, Catia and Jimenez-Ruiz, Ernesto and McCusker, Jamie and Faria, Daniel and Dragoni, Mauro and Dimou, Anastasia and Troncy, Raphael and Hertling, Sven}}, keywords = {{Neural network, Concept learning, Description logics}}, location = {{Hersonissos, Crete, Greece}}, pages = {{209 -- 226}}, publisher = {{Springer International Publishing}}, title = {{{Neural Class Expression Synthesis}}}, doi = {{https://doi.org/10.1007/978-3-031-33455-9_13}}, volume = {{13870}}, year = {{2023}}, } @phdthesis{44323, abstract = {{Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods. Implicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit (3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified? The uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights. As a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain.}}, author = {{Kersting, Joschka}}, pages = {{208}}, publisher = {{Universität der Bundeswehr München }}, title = {{{Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining}}}, year = {{2023}}, } @inbook{45875, author = {{Götte, Thorsten and Knollmann, Till and Meyer auf der Heide, Friedhelm and Scheideler, Christian and Werthmann, Julian}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{1----20}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Capabilities and Limitations of Local Strategies in Dynamic Networks}}}, doi = {{10.5281/zenodo.8060372}}, volume = {{412}}, year = {{2023}}, } @inbook{45895, author = {{Karl, Holger and Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon and Redder, Adrian}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{183--202}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{On-The-Fly Compute Centers II: Execution of Composed Services in Configurable Compute Centers}}}, doi = {{10.5281/zenodo.8068664}}, volume = {{412}}, year = {{2023}}, } @inbook{45901, author = {{Blömer, Johannes and Bobolz, Jan and Eidens, Fabian and Jager, Tibor and Kramer, Paul}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{237--246}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Practical Cryptograhic Techniques for Secure and Privacy-Preserving Customer Loyalty Systems}}}, doi = {{10.5281/zenodo.8068755}}, volume = {{412}}, year = {{2023}}, } @inbook{45897, author = {{Gottschalk, Sebastian and Vorbohle, Christian and Kundisch, Dennis and Engels, Gregor and Wünderlich, Nacy V.}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{203--224}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Architectural Management of OTF Computing Markets}}}, doi = {{10.5281/zenodo.8068691}}, volume = {{412}}, year = {{2023}}, } @inbook{45891, author = {{Blömer, Johannes and Eidens, Fabian and Jager, Tibor and Niehues, David and Scheideler, Christian}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{145--164}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Robustness and Security}}}, doi = {{10.5281/zenodo.8068629}}, volume = {{412}}, year = {{2023}}, } @inbook{45882, author = {{Bäumer, Frederik Simon and Chen, Wei-Fan and Geierhos, Michaela and Kersting, Joschka and Wachsmuth, Henning}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{65--84}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Dialogue-based Requirement Compensation and Style-adjusted Data-to-text Generation}}}, doi = {{10.5281/zenodo.8068456}}, volume = {{412}}, year = {{2023}}, } @inbook{45884, author = {{Hanselle, Jonas Manuel and Hüllermeier, Eyke and Mohr, Felix and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed and Tornede, Alexander and Wever, Marcel Dominik}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{85--104}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Configuration and Evaluation}}}, doi = {{10.5281/zenodo.8068466}}, volume = {{412}}, year = {{2023}}, } @inbook{45878, author = {{Haake, Claus-Jochen and Hehenkamp, Burkhard and Polevoy, Gleb}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{21--44}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{The Market for Services: Incentives, Algorithms, Implementation}}}, doi = {{10.5281/zenodo.8068414}}, volume = {{412}}, year = {{2023}}, } @inbook{45886, author = {{Wehrheim, Heike and Hüllermeier, Eyke and Becker, Steffen and Becker, Matthias and Richter, Cedric and Sharma, Arnab}}, booktitle = {{On-The-Fly Computing -- Individualized IT-services in dynamic markets}}, editor = {{Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}}, pages = {{105--123}}, publisher = {{Heinz Nixdorf Institut, Universität Paderborn}}, title = {{{Composition Analysis in Unknown Contexts}}}, doi = {{10.5281/zenodo.8068510}}, volume = {{412}}, year = {{2023}}, } @misc{45917, author = {{Raeisi Nafchi, Masood}}, publisher = {{Paderborn University}}, title = {{{Reconfigurable Random Forest Implementation on FPGA}}}, year = {{2023}}, } @misc{45916, author = {{Yadalam Murali Kumar, Nihal}}, publisher = {{Paderborn University}}, title = {{{Data Analytics for Predictive Maintenance of Time Series Data}}}, year = {{2023}}, } @inproceedings{34138, abstract = {{Variational Quantum Algorithms (VQAs), such as the Quantum Approximate Optimization Algorithm (QAOA) of [Farhi, Goldstone, Gutmann, 2014], have seen intense study towards near-term applications on quantum hardware. A crucial parameter for VQAs is the depth of the variational ansatz used - the smaller the depth, the more amenable the ansatz is to near-term quantum hardware in that it gives the circuit a chance to be fully executed before the system decoheres. This potential for depth reduction has made VQAs a staple of Noisy Intermediate-Scale Quantum (NISQ)-era research. In this work, we show that approximating the optimal depth for a given VQA ansatz is intractable. Formally, we show that for any constant $\epsilon>0$, it is QCMA-hard to approximate the optimal depth of a VQA ansatz within multiplicative factor $N^{1-\epsilon}$, for $N$ denoting the encoding size of the VQA instance. (Here, Quantum Classical Merlin-Arthur (QCMA) is a quantum generalization of NP.) We then show that this hardness persists even in the "simpler" setting of QAOAs. To our knowledge, this yields the first natural QCMA-hard-to-approximate problems. To achieve these results, we bypass the need for a PCP theorem for QCMA by appealing to the disperser-based NP-hardness of approximation construction of [Umans, FOCS 1999].}}, author = {{Bittel, Lennart and Gharibian, Sevag and Kliesch, Martin}}, booktitle = {{Proceedings of the 38th Computational Complexity Conference (CCC)}}, number = {{34}}, pages = {{34:1--34:24}}, title = {{{The Optimal Depth of Variational Quantum Algorithms Is QCMA-Hard to Approximate}}}, doi = {{10.4230/LIPIcs.CCC.2023.34}}, volume = {{264}}, year = {{2023}}, } @phdthesis{45781, author = {{Pukrop, Simon}}, title = {{{On Cloud Assisted, Restricted, and Reosurce Constrained Scheduling}}}, doi = {{10.17619/UNIPB/1-1768 }}, year = {{2023}}, }