@inproceedings{53958,
  abstract     = {{To detect security vulnerabilities, static analysis tools need to be configured with security-relevant methods. Current approaches can automatically identify such methods using binary relevance machine learning approaches. However, they ignore dependencies among security-relevant methods, over-generalize and perform poorly in practice. Additionally, users have to nevertheless manually configure static analysis tools using the detected methods. Based on feedback from users and our observations, the excessive manual steps can often be tedious, error-prone and counter-intuitive.
 In this paper, we present Dev-Assist, an IntelliJ IDEA plugin that detects security-relevant methods using a multi-label machine learning approach that considers dependencies among labels. The plugin can automatically generate configurations for static analysis tools, run the static analysis, and show the results in IntelliJ IDEA. Our experiments reveal that Dev-Assist's machine learning approach has a higher F1-Measure than related approaches. Moreover, the plugin reduces and simplifies the manual effort required when configuring and using static analysis tools.}},
  author       = {{Johnson, Oshando and Piskachev, Goran and Krishnamurthy, Ranjith and Bodden, Eric}},
  booktitle    = {{Proceedings of the 46th International Conference on Software Engineering, IDE Workshop}},
  title        = {{{Detecting Security-Relevant Methods using Multi-label Machine Learning}}},
  doi          = {{10.48550/ARXIV.2403.07501}},
  year         = {{2024}},
}

@inproceedings{53796,
  author       = {{Amer, Abdelhakim and Álvarez-Tuñón, Olaya and Uğurlu, Halil İbrahim and Le Fevre Sejersen, Jonas and Brodskiy, Yury and Kayacan, Erdal}},
  booktitle    = {{2023 21st International Conference on Advanced Robotics (ICAR)}},
  publisher    = {{IEEE}},
  title        = {{{UNav-Sim: A Visually Realistic Underwater Robotics Simulator and Synthetic Data-Generation Framework}}},
  doi          = {{10.1109/icar58858.2023.10406819}},
  year         = {{2024}},
}

@article{51207,
  abstract     = {{Let $X=X_1\times X_2$ be a product of two rank one symmetric spaces of
non-compact type and $\Gamma$ a torsion-free discrete subgroup in $G_1\times
G_2$. We show that the spectrum of $\Gamma \backslash X$ is related to the
asymptotic growth of $\Gamma$ in the two direction defined by the two factors.
We obtain that $L^2(\Gamma \backslash G)$ is tempered for large class of
$\Gamma$.}},
  author       = {{Weich, Tobias and Wolf, Lasse Lennart}},
  journal      = {{Geom Dedicata}},
  title        = {{{Temperedness of locally symmetric spaces: The product case}}},
  doi          = {{https://doi.org/10.1007/s10711-024-00904-4}},
  volume       = {{218}},
  year         = {{2024}},
}

@article{54078,
  author       = {{Häsel-Weide, Uta and Graf, Lara Marie and Höveler, K. and Nührenbörger, M.}},
  journal      = {{HLZ – Herausforderung Lehrer*innenbildung}},
  number       = {{1}},
  title        = {{{Fachbezogene Professionalisierung von fachfremd Mathematik unterrichtenden Lehrkräften: Retrospektive Selbsteinschätzungen zur Expertise im Umgang mit Schwierigkeiten beim Mathematiklernen im Anfangsunterricht der Grundschule}}},
  doi          = {{10.11576/hlz-6727}},
  volume       = {{7}},
  year         = {{2024}},
}

@article{54144,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>In this paper, we propose a novel conceptual framework tailored for modeling the meaning of mathematical concepts in university-level mathematics, addressing their rigorous nature and their relationships with related concepts as well as interpretations in various contexts. Within this framework, we present a model of meaning for the concepts of total differentiability and total derivative that provides a variety of possible interpretations and aspects. We then use the proposed model of meaning as a tool for analyzing three different textbooks for mathematics majors on the topic of multidimensional differentiability. Our paper is an example of a subject matter analysis of a topic in university mathematics carried out in a structured way. The model of meaning for total differentiability presented in this paper could inspire course design and analysis including the design of assignments and assessments for students. Moreover, it could serve as a valuable research tool for further analyses. For example, it could be used as a framework for analyzing courses taught or as a basis for developing a test instrument to assess students’ understanding. With our textbook analysis, we begin to examine the landscape of textbooks regarding differentiability concepts in the multidimensional case, shedding light on the diversity of meaning facets that are covered in the textbooks. These results could be useful for guiding instructors and learners in selecting and using textbooks for teaching and learning based on their respective needs.</jats:p>}},
  author       = {{Lankeit, Elisa and Biehler, Rolf}},
  issn         = {{1863-9690}},
  journal      = {{ZDM – Mathematics Education}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{The meaning landscape of the concept of the total derivative in multivariable real analysis textbooks: an analysis based on a new model of meaning}}},
  doi          = {{10.1007/s11858-024-01584-w}},
  year         = {{2024}},
}

@book{54283,
  editor       = {{Beverungen, Daniel and Dumitrescu, Roman and Kühn, Arno and Plass, Christoph}},
  isbn         = {{9783662681152}},
  issn         = {{2523-3637}},
  publisher    = {{Springer Berlin Heidelberg}},
  title        = {{{Digitale Plattformen im industriellen Mittelstand}}},
  doi          = {{10.1007/978-3-662-68116-9}},
  year         = {{2024}},
}

@article{54017,
  author       = {{Kress, Christian and Schwabe, Tobias and Rhee, Hanjo and Scheytt, J. Christoph}},
  issn         = {{2169-3536}},
  journal      = {{IEEE Access}},
  pages        = {{1--1}},
  publisher    = {{Institute of Electrical and Electronics Engineers (IEEE)}},
  title        = {{{Compact, High-Speed Mach-Zehnder Modulator with On-Chip Linear Drivers in Photonic BiCMOS Technology}}},
  doi          = {{10.1109/access.2024.3396877}},
  year         = {{2024}},
}

@inproceedings{54355,
  author       = {{Urbaneck, Daniel and Wiegard, Jan and Schafmeister, Frank}},
  booktitle    = {{PCIM Europe 2024; IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management}},
  location     = {{Nuremberg}},
  title        = {{{Analysis of Inverter Operation Modes of an IGBT-Based ZCS LLC Converter for a 2 kW Automotive On-Board DC-DC}}},
  year         = {{2024}},
}

@inproceedings{54353,
  author       = {{Piepenbrock, Till and Keuck, Lukas  and Schachten, Sebastian  and Böcker, Joachim and Schafmeister, Frank}},
  booktitle    = {{PCIM Europe 2024; IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management}},
  location     = {{Nuremberg}},
  title        = {{{Study on Sample Geometries for Ferrite Characterisation in the MHz-Range}}},
  year         = {{2024}},
}

@inproceedings{54354,
  author       = {{Förster, Nikolas and Urbaneck, Daniel and Kohlhepp, Benedikt and Kübrich, Daniel and Schafmeister, Frank}},
  booktitle    = {{PCIM Europe 2024; IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management}},
  location     = {{Nuremberg}},
  title        = {{{Pitfalls and their Avoidability in the Double-Pulse Test}}},
  year         = {{2024}},
}

@inproceedings{54437,
  abstract     = {{Video conferencing systems have become an indispensable part of our world. Using video conferencing systems implies the expectation that online meetings run as smoothly as in-person meetings. Thus, online meetings need to be just as secure and private as in-person meetings, which are secured against disruptive factors and unauthorized persons by physical access control mechanisms.

To show the security dangers of conferencing systems and raise general awareness when using these technologies, we analyze the security of two widely used research and education open-source video conferencing systems: BigBlueButton and eduMEET. Because both systems are very different, we analyzed their architectures, considering the respective components with their main tasks, features, and user roles. In the following systematic security analyses, we found 50 vulnerabilities. These include broken access control, NoSQL injection, and denial of service (DoS). The vulnerabilities have root causes of different natures. While BigBlueButton has a lot of complexity due to many components, eduMEET, which is relatively young, focuses more on features than security. The sheer amount of results and the lack of prior work indicate a research gap that needs to be closed since video conferencing systems continue to play a significant role in research, education, and everyday life.}},
  author       = {{Heitmann, Nico and Siewert, Hendrik and Moog, Sven and Somorovsky, Juraj}},
  booktitle    = {{Applied Cryptography and Network Security}},
  location     = {{Abu Dhabi}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Security Analysis of BigBlueButton and eduMEET}}},
  doi          = {{10.1007/978-3-031-54776-8_8}},
  year         = {{2024}},
}

@inproceedings{54449,
  author       = {{KOUAGOU, N'Dah Jean and Demir, Caglar and Zahera, Hamada Mohamed Abdelsamee and Wilke, Adrian and Heindorf, Stefan and Li, Jiayi and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{Companion Proceedings of the ACM on Web Conference 2024}},
  location     = {{Singapore}},
  publisher    = {{ACM}},
  title        = {{{Universal Knowledge Graph Embeddings}}},
  doi          = {{10.1145/3589335.3651978}},
  year         = {{2024}},
}

@unpublished{54448,
  abstract     = {{Graph Neural Networks (GNNs) are effective for node classification in
graph-structured data, but they lack explainability, especially at the global
level. Current research mainly utilizes subgraphs of the input as local
explanations or generates new graphs as global explanations. However, these
graph-based methods are limited in their ability to explain classes with
multiple sufficient explanations. To provide more expressive explanations, we
propose utilizing class expressions (CEs) from the field of description logic
(DL). Our approach explains heterogeneous graphs with different types of nodes
using CEs in the EL description logic. To identify the best explanation among
multiple candidate explanations, we employ and compare two different scoring
functions: (1) For a given CE, we construct multiple graphs, have the GNN make
a prediction for each graph, and aggregate the predicted scores. (2) We score
the CE in terms of fidelity, i.e., we compare the predictions of the GNN to the
predictions by the CE on a separate validation set. Instead of subgraph-based
explanations, we offer CE-based explanations.}},
  author       = {{Köhler, Dominik and Heindorf, Stefan}},
  booktitle    = {{arXiv:2405.12654}},
  title        = {{{Utilizing Description Logics for Global Explanations of Heterogeneous  Graph Neural Networks}}},
  year         = {{2024}},
}

@inproceedings{52231,
  author       = {{Blübaum, Lukas and Heindorf, Stefan}},
  booktitle    = {{The World Wide Web Conference (WWW)}},
  location     = {{Singapore}},
  pages        = {{2204–2215}},
  publisher    = {{ACM}},
  title        = {{{Causal Question Answering with Reinforcement Learning}}},
  doi          = {{10.1145/3589334.3645610}},
  year         = {{2024}},
}

@inproceedings{54468,
  author       = {{Awais, Muhammad and Ghasemzadeh Mohammadi, Hassan and Platzner, Marco}},
  booktitle    = {{To apear in IEEE ISVLSI 2024}},
  location     = {{Knoxville, Tennessee, USA}},
  title        = {{{DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing}}},
  year         = {{2024}},
}

@article{54548,
  author       = {{Prager, Raphael Patrick and Trautmann, Heike}},
  journal      = {{IEEE Transactions on Evolutionary Computation}},
  keywords     = {{Optimization, Evolutionary computation, Benchmark testing, Hyperparameter optimization, Portfolios, Extraterrestrial measurements, Dispersion, Exploratory landscape analysis, mixed-variable problem, mixed search spaces, automated algorithm selection}},
  pages        = {{1--1}},
  title        = {{{Exploratory Landscape Analysis for Mixed-Variable Problems}}},
  doi          = {{10.1109/TEVC.2024.3399560}},
  year         = {{2024}},
}

@inproceedings{54559,
  author       = {{Tissen, Denis and Wiederkehr, Ingrid and Koldewey, Christian and Dumitrescu, Roman}},
  booktitle    = {{2023 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}},
  publisher    = {{IEEE}},
  title        = {{{Exploring data-driven model-based systems engineering: a systematic literature review}}},
  doi          = {{10.1109/ictmod59086.2023.10438129}},
  year         = {{2024}},
}

@inbook{54412,
  author       = {{Firmansyah, Asep Fajar and Moussallem, Diego and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{The Semantic Web}},
  isbn         = {{9783031606250}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{ESLM: Improving Entity Summarization by Leveraging Language Models}}},
  doi          = {{10.1007/978-3-031-60626-7_9}},
  year         = {{2024}},
}

@inbook{54580,
  author       = {{Mahmood, Yasir and Virtema, Jonni and Barlag, Timon and Ngonga Ngomo, Axel-Cyrille}},
  booktitle    = {{Lecture Notes in Computer Science}},
  isbn         = {{9783031569395}},
  issn         = {{0302-9743}},
  publisher    = {{Springer Nature Switzerland}},
  title        = {{{Computing Repairs Under Functional and Inclusion Dependencies via Argumentation}}},
  doi          = {{10.1007/978-3-031-56940-1_2}},
  year         = {{2024}},
}

@inproceedings{54642,
  author       = {{Dietrich, K. and Prager, R. and Doerr, C. and Trautmann, Heike}},
  booktitle    = {{Parallel Problem Solving from Nature — PPSN XVIII}},
  editor       = {{Affenzeller, M and Winkler, S and Kononova, A and Trautmann, H and Tušar, T and Machado, P and Baeck, T}},
  pages        = {{1--14}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Hybridizing Target- and SHAP-encoded Features for Algorithm Selection in Mixed-variable Black-box Optimization}}},
  year         = {{2024}},
}