@inproceedings{63918, abstract = {{Many real-world datasets, such as citation networks, social networks, and molecular structures, are naturally represented as heterogeneous graphs, where nodes belong to different types and have additional features. For example, in a citation network, nodes representing "Paper" or "Author" may include attributes like keywords or affiliations. A critical machine learning task on these graphs is node classification, which is useful for applications such as fake news detection, corporate risk assessment, and molecular property prediction. Although Heterogeneous Graph Neural Networks (HGNNs) perform well in these contexts, their predictions remain opaque. Existing post-hoc explanation methods lack support for actual node features beyond one-hot encoding of node type and often fail to generate realistic, faithful explanations. To address these gaps, we propose DiGNNExplainer, a model-level explanation approach that synthesizes heterogeneous graphs with realistic node features via discrete denoising diffusion. In particular, we generate realistic discrete features (e.g., bag-of-words features) using diffusion models within a discrete space, whereas previous approaches are limited to continuous spaces. We evaluate our approach on multiple datasets and show that DiGNNExplainer produces explanations that are realistic and faithful to the model's decision-making, outperforming state-of-the-art methods.}}, author = {{Das, Pallabee and Heindorf, Stefan}}, booktitle = {{Proceedings of the ACM Web Conference 2026 (WWW ’26)}}, location = {{Dubai, United Arab Emirates}}, publisher = {{ACM}}, title = {{{Discrete Diffusion-Based Model-Level Explanation of Heterogeneous GNNs with Node Features}}}, year = {{2026}}, } @inproceedings{63890, abstract = {{The computation of highly contracted electron repulsion integrals (ERIs) is essential to achieve quantum accuracy in atomistic simulations based on quantum mechanics. Its growing computational demands make energy efficiency a critical concern. Recent studies demonstrate FPGAs’ superior performance and energy efficiency for computing primitive ERIs, but the computation of highly contracted ERIs introduces significant algorithmic complexity and new design challenges for FPGA acceleration.In this work, we present SORCERI, the first streaming overlay acceleration for highly contracted ERI computations on FPGAs. SORCERI introduces a novel streaming Rys computing unit to calculate roots and weights of Rys polynomials on-chip, and a streaming contraction unit for the contraction of primitive ERIs. This shifts the design bottleneck from limited CPU-FPGA communication bandwidth to available FPGA computation resources. To address practical deployment challenges for a large number of quartet classes, we design three streaming overlays, together with an efficient memory transpose optimization, to cover the 21 most commonly used quartet classes in realistic atomistic simulations. To address the new computation constraints, we use flexible calculation stages with a free-running streaming architecture to achieve high DSP utilization and good timing closure.Experiments demonstrate that SORCERI achieves an average 5.96x, 1.99x, and 1.16x better performance per watt than libint on a 64-core AMD EPYC 7713 CPU, libintx on an Nvidia A40 GPU, and SERI, the prior best-performing FPGA design for primitive ERIs. Furthermore, SORCERI reaches a peak throughput of 44.11 GERIS (109 ERIs per second) that is 1.52x, 1.13x, and 1.93x greater than libint, libintx and SERI, respectively. SORCERI will be released soon at https://github.com/SFU-HiAccel/SORCERI.}}, author = {{Stachura, Philip and Wu, Xin and Plessl, Christian and Fang, Zhenman}}, booktitle = {{Proceedings of the 2026 ACM/SIGDA International Symposium on Field Programmable Gate Arrays (FPGA '26)}}, isbn = {{9798400720796}}, keywords = {{electron repulsion integrals, quantum chemistry, atomistic simulation, overlay architecture, fpga acceleration}}, pages = {{224--234}}, publisher = {{Association for Computing Machinery}}, title = {{{SORCERI: Streaming Overlay Acceleration for Highly Contracted Electron Repulsion Integral Computations in Quantum Chemistry}}}, doi = {{10.1145/3748173.3779198}}, year = {{2026}}, } @inproceedings{64075, author = {{Humpert, Lynn and Graunke, Jannis and Cichon, Gerrit and Ammanagi, Anuradha and Schierbaum, Anja and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Symposium on Systems Engineering (ISSE)}}, publisher = {{IEEE}}, title = {{{Generative AI in Systems Engineering: Automated Creation of System Architectures and Early-Stage Calculation in the B2B Sector}}}, doi = {{10.1109/isse65546.2025.11370000}}, year = {{2026}}, } @article{63834, abstract = {{Abstract Many Android apps collect data from users, and the European Union’s General Data Protection Regulation (GDPR) mandates clear disclosures of such data collection. However, apps often use third-party code, complicating accurate disclosures. This paper investigates how accurately current Android apps fulfill these requirements. In this work, we present a multi-layered definition of privacy-related data to correctly report data collection in Android apps. We further create a dataset of privacy-sensitive data classes that may be used as input by an Android app. This dataset takes into account data collected both through the user interface and system APIs. Based on this, we implement a semi-automated prototype that detects and labels privacy-related data collected by a given Android app. We manually examine the data safety sections of 70 Android apps to observe how data collection is reported, identifying instances of over- and under-reporting. We compare our prototype’s results with the data safety sections of 20 apps revealing reporting discrepancies. Using the results from two Messaging and Social Media apps (Signal and Instagram), we discuss how app developers under-report and over-report data collection, respectively, and identify inaccurately reported data categories. A broader study of 7,500 Android apps reveals that apps most frequently collect data that can partially identify users. Although system APIs consistently collect large amounts of privacy-related data, user interfaces exhibit some more diverse data collection patterns. A more focused study on various domains of apps reveals that the largest fraction of apps collecting personal data belong to the domain of Messaging and Social Media . Our findings show that location is collected frequently by apps, specially from the E-commerce and Shopping domain. However, it is often under-reported in app data safety sections. Our results highlight the need for greater consistency in privacy-aware app development and reporting practices. }}, author = {{Khedkar, Mugdha and Kumar Mondal, Ambuj and Bodden, Eric}}, issn = {{0928-8910}}, journal = {{Automated Software Engineering}}, number = {{2}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{A study of privacy-related data collected by Android apps}}}, doi = {{10.1007/s10515-025-00589-3}}, volume = {{33}}, year = {{2026}}, } @article{64174, author = {{Häsel-Weide, Uta and Nührenbörger, Marcus}}, journal = {{Grundschule aktuell}}, number = {{173}}, pages = {{3--6}}, title = {{{Mathematische Basiskompetenzen. Diagnose und Förderung in der Grundschule.}}}, year = {{2026}}, } @inbook{63793, author = {{Vernholz, Mats and Schäfers, Johannes and Jonas-Ahrend, Gabriela and Temmen, Katrin}}, booktitle = {{Smart Technologies for an All-Electric Society. STE 2025. Lecture Notes in Networks and Systems}}, editor = {{Auer, Michael E. and Langmann, Reinhard and May, Dominik and Morales, Manuel}}, isbn = {{9783032073150}}, issn = {{2367-3370}}, publisher = {{Springer Nature Switzerland}}, title = {{{Shaping Tomorrow’s Classrooms: Integrating AI in Technology Teacher Training and VET in Germany}}}, doi = {{10.1007/978-3-032-07316-7_10}}, year = {{2026}}, } @article{51204, abstract = {{Given a real semisimple connected Lie group $G$ and a discrete torsion-free subgroup $\Gamma < G$ we prove a precise connection between growth rates of the group $\Gamma$, polyhedral bounds on the joint spectrum of the ring of invariant differential operators, and the decay of matrix coefficients. In particular, this allows us to completely characterize temperedness of $L^2(\Gamma\backslash G)$ in this general setting.}}, author = {{Lutsko, Christopher and Weich, Tobias and Wolf, Lasse Lennart}}, journal = {{Duke Math. Journal }}, title = {{{Polyhedral bounds on the joint spectrum and temperedness of locally symmetric spaces}}}, volume = {{(to appear)}}, year = {{2026}}, } @inproceedings{64211, author = {{Wiebe, Vivien and Häsel-Weide, Uta}}, booktitle = {{Proceedings of the Nineteenth ERME Topic Conference: Connecting the Learning of Mathematics Teaching to Practice}}, editor = {{Mosvold, R. and Fauskanger, J. and Ferretti, F. and Vondrová, N.}}, location = {{Prag}}, pages = {{122--129}}, title = {{{ Initiating and establishing mathematical practices of determining and transforming numbers as a foundational skill in fostering mathematics teaching}}}, year = {{2026}}, } @article{64223, abstract = {{The complexity and interconnectivity of modern automotive systems are rapidly increasing, particularly with the rise of distributed and cooperative driving functions. These developments increase exposure to a range of disruptions, from technical failures to cyberattacks, and demand a shift towards resilience-by-design. This study addresses the early integration of resilience into the automotive design process by proposing a structured method for identifying gaps and eliciting resilience requirements. Building upon the concept of resilience scenarios, the approach extends traditional hazard and threat analyses as defined in ISO 26262, ISO 21448 and ISO/SAE 21434. Using a structured, graph-based modeling method, these scenarios enable the anticipation of functional degradation and its impact on driving scenarios. The methodology helps developers to specify resilience requirements at an early stage, enabling the integration of resilience properties throughout the system lifecycle. Its practical applicability is demonstrated through an example in the field of automotive cybersecurity. This study advances the field of resilience engineering by providing a concrete approach for operationalizing resilience within automotive systems engineering.}}, author = {{Mpidi Bita, Isaac and Ugur, Elif and Hovemann, Aschot and Dumitrescu, Roman}}, issn = {{1999-5903}}, journal = {{Future Internet}}, number = {{1}}, publisher = {{MDPI AG}}, title = {{{Resilience-by-Design: Extracting Resilience Requirements Using the Resilience Graph in the Automotive Concept Phase}}}, doi = {{10.3390/fi18010051}}, volume = {{18}}, year = {{2026}}, } @inproceedings{64224, author = {{Yee, Jingye and Hermelingmeier, Dominik and Thederajan, Abishai Asir A. and Low, Cheng Yee and Gossen, Alexander and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Symposium on Systems Engineering (ISSE)}}, publisher = {{IEEE}}, title = {{{System Architecture and Analytical Inverse Kinematics for Autonomous Docking of Passenger Boarding Bridges}}}, doi = {{10.1109/isse65546.2025.11370093}}, year = {{2026}}, } @inproceedings{64226, author = {{Hermelingmeier, Dominik and Graunke, Jannis and Menne, Leon and Schierbaum, Anja Maria and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Symposium on Systems Engineering (ISSE)}}, publisher = {{IEEE}}, title = {{{Process Model for the Development of Physical Prototypes in Context of Hardware Start-Ups using Maker Systems Engineering}}}, doi = {{10.1109/isse65546.2025.11370109}}, year = {{2026}}, } @inproceedings{64225, author = {{Grote, Eva-Maria and Koldewey, Christian and Voelk, Thomas Alexander and Schwarz, Stefan Eric and Dumitrescu, Roman and Albers, Albert}}, booktitle = {{2025 IEEE International Symposium on Systems Engineering (ISSE)}}, publisher = {{IEEE}}, title = {{{From Generic to Specific: Scalable Role Modeling for Engineering Advanced Systems}}}, doi = {{10.1109/isse65546.2025.11370103}}, year = {{2026}}, } @inproceedings{64221, author = {{Lick, Jonas and Kattenstroth, Fiona and van der Valk, Hendrik and Trienens, Malte and Kühn, Arno and Dumitrescu, Roman}}, booktitle = {{2025 Winter Simulation Conference (WSC)}}, publisher = {{IEEE}}, title = {{{Characterizing Digital Factory Twins: Deriving Archetypes for Research and Industry}}}, doi = {{10.1109/wsc68292.2025.11338979}}, year = {{2026}}, } @inproceedings{64228, author = {{Hanke, Fabian and von Heißen, Oliver and Feld, Markus and Heuwinkel, Tim and Hovemann, Aschot and Dumitrescu, Roman}}, booktitle = {{2025 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD)}}, publisher = {{IEEE}}, title = {{{Cross-View Trace Link Prediction with Multi-Feature GNNs: Creating and maintaining Traceability from Requirements to Components}}}, doi = {{10.1109/ictmod66732.2025.11371884}}, year = {{2026}}, } @inproceedings{64227, author = {{Könemann, Ulf and Niemeyer, Marcel and Schierbaum, Anja and Dumitrescu, Roman}}, booktitle = {{2025 IEEE 4th German Education Conference (GECon)}}, publisher = {{IEEE}}, title = {{{Status quo and challenges of professional Systems Engineering education in industrial practice}}}, doi = {{10.1109/gecon64629.2025.11369324}}, year = {{2026}}, } @article{64290, author = {{Niestijl, Milan}}, issn = {{0022-1236}}, journal = {{Journal of Functional Analysis}}, number = {{9}}, publisher = {{Elsevier BV}}, title = {{{Holomorphic induction beyond the norm-continuous setting, with applications to positive energy representations}}}, doi = {{10.1016/j.jfa.2026.111382}}, volume = {{290}}, year = {{2026}}, } @article{64569, abstract = {{Abstract We show how the Fourier transform for distributional sections of vector bundles over symmetric spaces of non‐compact type can be used for questions of solvability of systems of invariant differential equations in analogy to Hörmander's proof of the Ehrenpreis–Malgrange theorem. We get complete solvability for the hyperbolic plane and partial results for products and the hyperbolic 3‐space .}}, author = {{Olbrich, Martin and Palmirotta, Guendalina}}, issn = {{0025-584X}}, journal = {{Mathematische Nachrichten}}, number = {{2}}, pages = {{456--479}}, publisher = {{Wiley}}, title = {{{Solvability of invariant systems of differential equations on H2$\mathbb {H}^2$ and beyond}}}, doi = {{10.1002/mana.70100}}, volume = {{299}}, year = {{2026}}, } @inproceedings{64625, author = {{Fergusson, Anna and Podworny, Susanne and Fleischer, Yannik and Hüsing, Sven and Puloka, Malia S. and Biehler, Rolf and Pfannkuch, Maxine and Budgett, Stephanie and Dalrymple, Michelle}}, booktitle = {{Proceedings of the IASE 2025 Satellite Conference - Statistics and Data Science Education in STEAM}}, publisher = {{International Association for Statistics Education}}, title = {{{Branching out data science education: Developing task and computational environment design principles for teaching data science at the high school level through an international research collaboration}}}, doi = {{10.52041/iase25.138}}, year = {{2026}}, } @unpublished{64629, author = {{Glöckner, Helge and Neeb, Karl-Hermann}}, pages = {{1056}}, title = {{{Infinite-dimensional Lie groups}}}, year = {{2026}}, } @misc{64783, author = {{Berger, Thilo }}, title = {{{Comparing Existing Methods to Efficiently Place Drones to Connect Isolated Communication Clusters}}}, year = {{2026}}, }