Inverses Verfahren zur Bestimmung viskoelastischer Materialparameter - Johannesmann, Sarah

Investigation into Target Speaking Rate Adaptation for Voice Conversion - Kuhlmann, Michael; Seebauer, Fritz; Ebbers, Janek; Wagner, Petra; Haeb-Umbach, Reinhold (Interspeech 2022)

Far-field Calculation from magnetic Huygens Box Data using the Boundary Element Method - Marschalt, Christoph; Schroder, Dominik; Lange, Sven; Hilleringmann, Ulrich; Hedayat, Christian; Kuhn, Harald; Sievers, Denis; Förstner, Jens (2022 Smart Systems Integration (SSI))
In this publication a novel method for far-field prediction from magnetic Huygens box data based on the boundary element method (BEM) is presented. Two examples are considered for the validation of this method. The first example represents an electric dipole so that the obtained calculations can be compared to an analytical solution. As a second example, a printed circuit board is considered and the calculated far-field is compared to a fullwave simulation. In both cases, the calculations for different field integral equations are under comparison, and the results indicate that the presented method performs very well with a combined field integral equation, for the specified problem, when only magnetic Huygens box data is given.
Keywords: Near-Field Scanning; Huygens Box; Boundary Element Method; Method of Moments; tet_topic_hf

Prospective Teachers’ Diagnostic Thinking on Students’ Understanding of Multi-Digit Multiplication: A Content-Related Analysis on Unpacking of Knowledge Elements - Dröse, Jennifer; Prediger, Susanne (Journal für Mathematik-Didaktik)
Abstract Teachers’ in-depth diagnostic thinking has been shown to be crucial for student-centered teaching as they need to perceive and interpret students’ understanding for well-informed decision-making on adaptive teaching practices. The paper presents a content-related approach to analyzing diagnostic thinking processes with respect to the mathematical knowledge elements that prospective teachers identify as students’ resources and obstacles. Prospective teachers’ challenge is that some relevant knowledge elements first have to be unpacked, because compact concepts (such as the place value concept) or procedures (such as for multi-digit multiplication) comprise several smaller knowledge elements (such as the positional property) that have to be made explicit for students to foster their learning processes adequately. Our study examines what knowledge elements prospective teachers perceive and interpret in a transcript vignettes on multi-digit multiplication (of decimal and natural numbers) and its underlying basic arithmetic concepts (place value understanding and meaning of multiplication) in written diagnostic judgments on students’ resources and obstacles ( N = 196). A comparative design within the vignette is used to investigate how far the process of perceiving can be supported by thematic cues. The analysis reveals that those knowledge elements cued in the vignette by being already unpacked and explicitly addressed are perceived and interpreted more often (but with lower correctness) than those that are uncued and therefore have to be unpacked by the prospective teachers themselves. This confirms the need to prepare prospective teachers for unpacking mathematical concepts themselves.
Keywords: Education; General Mathematics

Prospective Teachers‘ Competence of Fostering Students’ Understanding in Script Writing Task - Dröse, Jennifer; Wessel, Lena (Proceedings of the 45th Conference of the International Group for the Psychology of Mathematics Education. PME)

Informed vs. Blind Beamforming in Ad-Hoc Acoustic Sensor Networks for Meeting Transcription - Gburrek, Tobias; Schmalenstroeer, Joerg; Heitkaemper, Jens; Haeb-Umbach, Reinhold (2022 International Workshop on Acoustic Signal Enhancement (IWAENC))

A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network - Gburrek, Tobias; Boeddeker, Christoph; von Neumann, Thilo; Cord-Landwehr, Tobias; Schmalenstroeer, Joerg; Haeb-Umbach, Reinhold

Threshold Independent Evaluation of Sound Event Detection Scores - Ebbers, Janek; Haeb-Umbach, Reinhold; Serizel, Romain (Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))
Performing an adequate evaluation of sound event detection (SED) systems is far from trivial and is still subject to ongoing research. The recently proposed polyphonic sound detection (PSD)-receiver operating characteristic (ROC) and PSD score (PSDS) make an important step into the direction of an evaluation of SED systems which is independent from a certain decision threshold. This allows to obtain a more complete picture of the overall system behavior which is less biased by threshold tuning. Yet, the PSD-ROC is currently only approximated using a finite set of thresholds. The choice of the thresholds used in approximation, however, can have a severe impact on the resulting PSDS. In this paper we propose a method which allows for computing system performance on an evaluation set for all possible thresholds jointly, enabling accurate computation not only of the PSD-ROC and PSDS but also of other collar-based and intersection-based performance curves. It further allows to select the threshold which best fulfills the requirements of a given application. Source code is publicly available in our SED evaluation package sed_scores_eval.

"They’re not that hard to mitigate": What Cryptographic Library Developers Think About Timing Attacks - Jancar, Jan; Fourné, Marcel; Braga, Daniel De Almeida; Sabt, Mohamed; Schwabe, Peter; Barthe, Gilles; Fouque, Pierre-Alain; Acar, Yasemin (43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022)

Committed to Trust: A Qualitative Study on Security & Trust in Open Source Software Projects - Wermke, Dominik; Wöhler, Noah; Klemmer, Jan H.; Fourné, Marcel; Acar, Yasemin; Fahl, Sascha (43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022)

"Desperate Times Call for Desperate Measures": User Concerns with Mobile Loan Apps in Kenya - Munyendo, Collins W.; Acar, Yasemin; Aviv, Adam J. (43rd IEEE Symposium on Security and Privacy, SP 2022, San Francisco, CA, USA, May 22-26, 2022)

Committed by Accident: Studying Prevention and Remediation Strategies Against Secret Leakage in Source Code Repositories - Krause, Alexander; Klemmer, Jan H.; Huaman, Nicolas; Wermke, Dominik; Acar, Yasemin; Fahl, Sascha (CoRR)

Nutzung von Process Mining in RPA-Projekten - Brock, Jonathan; von Enzberg, Sebastian; Kühn, Arno; Dumitrescu, Roman (Praxishandbuch Robotic Process Automation (RPA))

Adapting the product design to the circular economy using R-principles - Scholtysik, Michel; Rohde, Malte; Koldewey, Christian; Dumitrescu, Roman

Design and Evaluation of AR-Assisted End-User Robot Path Planning Strategies - Krings, Sarah Claudia; Yigitbas, Enes; Biermeier, Kai; Engels, Gregor (Proceedings of the 14th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2022))

Exploring the Feature Space of TSP Instances Using Quality Diversity - Bossek, Jakob; Neumann, Frank (Proceedings of the Genetic and Evolutionary Computation Conference)
Generating instances of different properties is key to algorithm selection methods that differentiate between the performance of different solvers for a given combinatorial optimization problem. A wide range of methods using evolutionary computation techniques has been introduced in recent years. With this paper, we contribute to this area of research by providing a new approach based on quality diversity (QD) that is able to explore the whole feature space. QD algorithms allow to create solutions of high quality within a given feature space by splitting it up into boxes and improving solution quality within each box. We use our QD approach for the generation of TSP instances to visualize and analyze the variety of instances differentiating various TSP solvers and compare it to instances generated by established approaches from the literature.
Keywords: instance features; instance generation; quality diversity; TSP

Evolutionary Diversity Optimization for Combinatorial Optimization: Tutorial at GECCO’22, Boston, USA - Bossek, Jakob; Neumann, Aneta; Neumann, Frank (Proceedings of the Genetic and Evolutionary Computation Conference Companion)

BBE: Basin-Based Evaluation of Multimodal Multi-objective Optimization Problems - Heins, Jonathan; Rook, Jeroen; Schäpermeier, Lennart; Kerschke, Pascal; Bossek, Jakob; Trautmann, Heike (Parallel Problem Solving from Nature (PPSN XVII))
In multimodal multi-objective optimization (MMMOO), the focus is not solely on convergence in objective space, but rather also on explicitly ensuring diversity in decision space. We illustrate why commonly used diversity measures are not entirely appropriate for this task and propose a sophisticated basin-based evaluation (BBE) method. Also, BBE variants are developed, capturing the anytime behavior of algorithms. The set of BBE measures is tested by means of an algorithm configuration study. We show that these new measures also transfer properties of the well-established hypervolume (HV) indicator to the domain of MMMOO, thus also accounting for objective space convergence. Moreover, we advance MMMOO research by providing insights into the multimodal performance of the considered algorithms. Specifically, algorithms exploiting local structures are shown to outperform classical evolutionary multi-objective optimizers regarding the BBE variants and respective trade-off with HV.
Keywords: Anytime behavior; Benchmarking; Continuous optimization; Multi-objective optimization; Multimodality; Performance metric

Co-Evolutionary Diversity Optimisation for the Traveling Thief Problem - Nikfarjam, Adel; Neumann, Aneta; Bossek, Jakob; Neumann, Frank (Parallel Problem Solving from Nature (PPSN XVII))
Recently different evolutionary computation approaches have been developed that generate sets of high quality diverse solutions for a given optimisation problem. Many studies have considered diversity 1) as a mean to explore niches in behavioural space (quality diversity) or 2) to increase the structural differences of solutions (evolutionary diversity optimisation). In this study, we introduce a co-evolutionary algorithm to simultaneously explore the two spaces for the multi-component traveling thief problem. The results show the capability of the co-evolutionary algorithm to achieve significantly higher diversity compared to the baseline evolutionary diversity algorithms from the literature.
Keywords: Co-evolutionary algorithms; Evolutionary diversity optimisation; Quality diversity; Traveling thief problem

Process-Oriented Stream Classification Pipeline: A Literature Review - Clever, Lena; Pohl, Janina Susanne; Bossek, Jakob; Kerschke, Pascal; Trautmann, Heike (Applied Sciences)
Due to the rise of continuous data-generating applications, analyzing data streams has gained increasing attention over the past decades. A core research area in stream data is stream classification, which categorizes or detects data points within an evolving stream of observations. Areas of stream classification are diverse— ranging, e.g., from monitoring sensor data to analyzing a wide range of (social) media applications. Research in stream classification is related to developing methods that adapt to the changing and potentially volatile data stream. It focuses on individual aspects of the stream classification pipeline, e.g., designing suitable algorithm architectures, an efficient train and test procedure, or detecting so-called concept drifts. As a result of the many different research questions and strands, the field is challenging to grasp, especially for beginners. This survey explores, summarizes, and categorizes work within the domain of stream classification and identifies core research threads over the past few years. It is structured based on the stream classification process to facilitate coordination within this complex topic, including common application scenarios and benchmarking data sets. Thus, both newcomers to the field and experts who want to widen their scope can gain (additional) insight into this research area and find starting points and pointers to more in-depth literature on specific issues and research directions in the field.
Keywords: big data; data mining; data stream analysis; machine learning; stream classification; supervised learning

On the Potential of Automated Algorithm Configuration on Multi-Modal Multi-Objective Optimization Problems - Rook, Jeroen; Trautmann, Heike; Bossek, Jakob; Grimme, Christian (Proceedings of the Genetic and Evolutionary Computation Conference Companion)
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.
Keywords: configuration; multi-modality; multi-objective optimization

HybridFC: A Hybrid Fact-Checking Approach for Knowledge Graphs - Qudus, Umair; Röder, Michael; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille (The Semantic Web -- ISWC 2022)
We consider fact-checking approaches that aim to predict the veracity of assertions in knowledge graphs. Five main categories of fact-checking approaches for knowledge graphs have been proposed in the recent literature, of which each is subject to partially overlapping limitations. In particular, current text-based approaches are limited by manual feature engineering. Path-based and rule-based approaches are limited by their exclusive use of knowledge graphs as background knowledge, and embedding-based approaches suffer from low accuracy scores on current fact-checking tasks. We propose a hybrid approach—dubbed HybridFC—that exploits the diversity of existing categories of fact-checking approaches within an ensemble learning setting to achieve a significantly better prediction performance. In particular, our approach outperforms the state of the art by 0.14 to 0.27 in terms of Area Under the Receiver Operating Characteristic curve on the FactBench dataset. Our code is open-source and can be found at https://github.com/dice-group/HybridFC.
Keywords: fact checking · ensemble learning · knowledge graph veracit

Semiclassical formulae For Wigner distributions - Barkhofen, Sonja; Schütte, Philipp; Weich, Tobias (Journal of Physics A: Mathematical and Theoretical)
In this paper we give an overview over some aspects of the modern mathematical theory of Ruelle resonances for chaotic, i.e. uniformly hyperbolic, dynamical systems and their implications in physics. First we recall recent developments in the mathematical theory of resonances, in particular how invariant Ruelle distributions arise as residues of weighted zeta functions. Then we derive a correspondence between weighted and semiclassical zeta functions in the setting of negatively curved surfaces. Combining this with results of Hilgert, Guillarmou and Weich yields a high frequency interpretation of invariant Ruelle distributions as quantum mechanical matrix coefficients in constant negative curvature. We finish by presenting numerical calculations of phase space distributions in the more physical setting of 3-disk scattering systems.

Von der Axiomatik bis zur Schnittstellenaufgabe: Entwicklung und Erforschung eines ganzheitlichen Lehrkonzepts für eine Veranstaltung Geometrie für Lehramtsstudierende - Hoffmann, Max
Vorgestellt wird ein Entwicklungsforschungsprojekt zur Konzeption und Durchführung einer Veranstaltung "Geometrie für Lehramtsstudierende". Die Schwerpunkte des Projekts sind zum einen die inhaltliche Gestaltung der Veranstaltung und zum anderen die Umsetzung von Professionsorientierung. Bezogen auf den inhaltlichen Aufbau wird das auf metrischen Räumen aufbauende Axiomensystem der "Saccheri-Ebene" vorgestellt und mit alternativen axiomatischen Zugängen zur ebenen Geometrie verglichen. Die Frage nach der Umsetzung von Professionsorientierung in Fachveranstaltungen ist eng mit der Problematik der zweiten Diskontinuität verbunden. In der Arbeit wird dieses Problem auf Grundlage der Synthese von theoretischen Hintergründen zur Bedeutung von mathematischem Wissen und Können für professionelle Handlungskompetenz von Mathematiklehrkräften diskutiert und darauf aufbauend werden theoriebasierte Entwurfsprinzipien für professionsorientierte Fachveranstaltungen entworfen. Zentrale Elemente der methodischen Gestaltung sind die sogenannten "Schnittstellenwochen" zu den Themen Kongruenz und Symmetrie sowie das begleitende Schnittstellen-ePortfolio. Das zentrale Ergebnis der Arbeit ist ein theoretisch fundiertes und empirisch evaluiertes ganzheitliches Veranstaltungskonzept für eine professionsorientierte Geometrie-Veranstaltung für Lehramtsstudierende, dessen Konzeption auf andere Fachveranstaltungen übertragbar ist. Darüber hinaus ergeben sich im Rahmen der durchgeführten Entwicklungsforschung verschiedene neue Beiträge zur Geometriedidaktik in Schule- und Hochschule.

Poisson transforms for trees of bounded degree - Bux, Kai-Uwe; Hilgert, Joachim; Weich, Tobias (Journal of Spectral Theory)
Keywords: Geometry and Topology; Mathematical Physics; Statistical and Nonlinear Physics

Poisson transforms for trees of bounded degree - Hilgert, Joachim; Weich, Tobias; Bux, K.-U. (J. of Spectral Theory)

Ethan D. Bolker und Maura B. Mast: Common Sense Mathematics, Second Edition. AMS/MAA Press 2021 - Hilgert, Joachim (Mathematische Semesterberichte)

Estimation of component reliability from superposed renewal processes by means of latent variables - Rodrigues, Agatha S.; Kerschke, Pascal; Pereira, Carlos Alberto De Bragança; Trautmann, Heike; Wagner, Carolin; Hellingrath, Bernd; Polpo, Adriano (Comput. Stat.)

Jupyter Notebooks for Teaching, Learning, and Doing Data Science - Fleischer, Yannik; Hüsing, Sven; Biehler, Rolf; Podworny, Susanne; Schulte, Carsten (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.

A Double Take at Conferences: The Hybrid Format - Turhan, Anni-Yasmin (KI - Künstliche Intelligenz)
Keywords: Artificial Intelligence

Rational Defeasible Subsumption in DLs with Nested Quantifiers: the Case of ELI\(\perp\) - de Camargo e Souza Câmara, Igor; Turhan, Anni-Yasmin (Proceedings of the 20th International Workshop on Non-Monotonic Reasoning, NMR 2022, Part of the Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7-9, 2022)

Computing generalizations of temporal \emph\(ϵ\)L concepts with next and global - Tirtarasa, Satyadharma; Turhan, Anni-Yasmin (SAC ’22: The 37th {ACM/SIGAPP} Symposium on Applied Computing, Virtual Event, April 25 - 29, 2022)

Rules and Reasoning - 6th International Joint Conference on Rules and Reasoning, RuleML+RR 2022, Berlin, Germany, September 26-28, 2022, Proceedings

Efficient TBox Reasoning with Value Restrictions Using the FL0wer Reasoner (Extended Abstract) - Baader, Franz; Koopmann, Patrick; Michel, Friedrich; Turhan, Anni-Yasmin; Zarrieß, Benjamin (Proceedings of the 35th International Workshop on Description Logics {(DL} 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022)

User-aware Explications of Ontology Consequences: Levelling Technicality - Peñaloza, Rafael; Turhan, Anni-Yasmin (Proceedings of the 8th Workshop on Formal and Cognitive Reasoning co-located with the 45th German Conference on Artificial Intelligence {(KI} 2022), Virtual Event, Trier, Germany, September 19, 2022)

A New Dimension to Generalization: Computing Temporal EL Concepts from Positive Examples (Extended Abstract) - Tirtarasa, Satyadharma; Turhan, Anni-Yasmin (Proceedings of the 35th International Workshop on Description Logics {(DL} 2022) co-located with Federated Logic Conference (FLoC 2022), Haifa, Israel, August 7th to 10th, 2022)

Efficient TBox Reasoning with Value Restrictions using the \(\mathscrF\)\(\mathscrL\)\(_\mbox0\)wer Reasoner - Baader, Franz; Koopmann, Patrick; Michel, Friedrich; Turhan, Anni-Yasmin; Zarrieß, Benjamin (Theory Pract. Log. Program.)

Jupyter Notebooks for Teaching, Learning, and Doing Data Science - Fleischer, Yannik; Hüsing, Sven; Biehler, Rolf; Podworny, Susanne; Schulte, Carsten (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.

"I don' know why I check this..." - Investigating Expert Users' Strategies to Detect Email Signature Spoofing Attacks - Mayer, Peter; Poddebniak, Damian; Fischer, Konstantin; Brinkmann, Marcus; Somorovsky, Juraj; Sasse, Angela; Schinzel, Sebastian; Volkamer, Melanie (Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022))

TLS-Anvil: Adapting Combinatorial Testing for TLS Libraries - Maehren, Marcel; Nieting, Philipp; Hebrok, Sven Niclas; Merget, Robert; Somorovsky, Juraj; Schwenk, Jörg (31st USENIX Security Symposium (USENIX Security 22))

Viscoelastic Cahn–Hilliard models for tumor growth - Garcke, Harald; Kovács, Balázs; Trautwein, Dennis (Mathematical Models and Methods in Applied Sciences)
We introduce a new phase field model for tumor growth where viscoelastic effects are taken into account. The model is derived from basic thermodynamical principles and consists of a convected Cahn–Hilliard equation with source terms for the tumor cells and a convected reaction–diffusion equation with boundary supply for the nutrient. Chemotactic terms, which are essential for the invasive behavior of tumors, are taken into account. The model is completed by a viscoelastic system consisting of the Navier–Stokes equation for the hydrodynamic quantities, and a general constitutive equation with stress relaxation for the left Cauchy–Green tensor associated with the elastic part of the total mechanical response of the viscoelastic material. For a specific choice of the elastic energy density and with an additional dissipative term accounting for stress diffusion, we prove existence of global-in-time weak solutions of the viscoelastic model for tumor growth in two space dimensions [Formula: see text] by the passage to the limit in a fully-discrete finite element scheme where a CFL condition, i.e. [Formula: see text], is required. Moreover, in arbitrary dimensions [Formula: see text], we show stability and existence of solutions for the fully-discrete finite element scheme, where positive definiteness of the discrete Cauchy–Green tensor is proved with a regularization technique that was first introduced by Barrett and Boyaval [Existence and approximation of a (regularized) Oldroyd-B model, Math. Models Methods Appl. Sci. 21 (2011) 1783–1837]. After that, we improve the regularity results in arbitrary dimensions [Formula: see text] and in two dimensions [Formula: see text], where a CFL condition is required. Then, in two dimensions [Formula: see text], we pass to the limit in the discretization parameters and show that subsequences of discrete solutions converge to a global-in-time weak solution. Finally, we present numerical results in two dimensions [Formula: see text].
Keywords: Applied Mathematics; Modeling and Simulation

Numerical analysis for the interaction of mean curvature flow and diffusion on closed surfaces - Elliott, Charles M.; Garcke, Harald; Kovács, Balázs (Numerische Mathematik)
Abstract An evolving surface finite element discretisation is analysed for the evolution of a closed two-dimensional surface governed by a system coupling a generalised forced mean curvature flow and a reaction–diffusion process on the surface, inspired by a gradient flow of a coupled energy. Two algorithms are proposed, both based on a system coupling the diffusion equation to evolution equations for geometric quantities in the velocity law for the surface. One of the numerical methods is proved to be convergent in the $$H^1$$ H1 norm with optimal-order for finite elements of degree at least two. We present numerical experiments illustrating the convergence behaviour and demonstrating the qualitative properties of the flow: preservation of mean convexity, loss of convexity, weak maximum principles, and the occurrence of self-intersections.
Keywords: Applied Mathematics; Computational Mathematics

Time-dependent electromagnetic scattering from thin layers - Nick, Jörg; Kovács, Balázs; Lubich, Christian (Numerische Mathematik)
Abstract The scattering of electromagnetic waves from obstacles with wave-material interaction in thin layers on the surface is described by generalized impedance boundary conditions, which provide effective approximate models. In particular, this includes a thin coating around a perfect conductor and the skin effect of a highly conducting material. The approach taken in this work is to derive, analyse and discretize a system of time-dependent boundary integral equations that determines the tangential traces of the scattered electric and magnetic fields. In a familiar second step, the fields are evaluated in the exterior domain by a representation formula, which uses the time-dependent potential operators of Maxwell’s equations. The time-dependent boundary integral equation is discretized with Runge–Kutta based convolution quadrature in time and Raviart–Thomas boundary elements in space. Using the frequency-explicit bounds from the well-posedness analysis given here together with known approximation properties of the numerical methods, the full discretization is proved to be stable and convergent, with explicitly given rates in the case of sufficient regularity. Taking the same Runge–Kutta based convolution quadrature for discretizing the time-dependent representation formulas, the optimal order of convergence is obtained away from the scattering boundary, whereas an order reduction occurs close to the boundary. The theoretical results are illustrated by numerical experiments.
Keywords: Applied Mathematics; Computational Mathematics

Maximal regularity of backward difference time discretization for evolving surface PDEs and its application to nonlinear problems - Kovács, Balázs; Li, Buyang (IMA Journal of Numerical Analysis)
Abstract Maximal parabolic $L^p$-regularity of linear parabolic equations on an evolving surface is shown by pulling back the problem to the initial surface and studying the maximal $L^p$-regularity on a fixed surface. By freezing the coefficients in the parabolic equations at a fixed time and utilizing a perturbation argument around the freezed time, it is shown that backward difference time discretizations of linear parabolic equations on an evolving surface along characteristic trajectories can preserve maximal $L^p$-regularity in the discrete setting. The result is applied to prove the stability and convergence of time discretizations of nonlinear parabolic equations on an evolving surface, with linearly implicit backward differentiation formulae characteristic trajectories of the surface, for general locally Lipschitz nonlinearities. The discrete maximal $L^p$-regularity is used to prove the boundedness and stability of numerical solutions in the $L^∞ (0,T;W^{1,∞ })$ norm, which is used to bound the nonlinear terms in the stability analysis. Optimal-order error estimates of time discretizations in the $L^∞ (0,T;W^{1,∞ })$ norm is obtained by combining the stability analysis with the consistency estimates.
Keywords: Applied Mathematics; Computational Mathematics; General Mathematics

Bulk–surface Lie splitting for parabolic problems with dynamic boundary conditions - Altmann, Robert; Kovács, Balázs; Zimmer, Christoph (IMA Journal of Numerical Analysis)
Abstract This paper studies bulk–surface splitting methods of first order for (semilinear) parabolic partial differential equations with dynamic boundary conditions. The proposed Lie splitting scheme is based on a reformulation of the problem as a coupled partial differential–algebraic equation system, i.e., the boundary conditions are considered as a second dynamic equation that is coupled to the bulk problem. The splitting approach is combined with bulk–surface finite elements and an implicit Euler discretization of the two subsystems. We prove first-order convergence of the resulting fully discrete scheme in the presence of a weak CFL condition of the form $τ \leqslant c h$ for some constant $c>0$. The convergence is also illustrated numerically using dynamic boundary conditions of Allen–Cahn type.
Keywords: Applied Mathematics; Computational Mathematics; General Mathematics

Error estimates for a splitting integrator for abstract semilinear boundary coupled systems - Csomós, Petra; Farkas, Bálint; Kovács, Balázs (IMA Journal of Numerical Analysis)
Abstract We derive a numerical method, based on operator splitting, to abstract parabolic semilinear boundary coupled systems. The method decouples the linear components that describe the coupling and the dynamics in the abstract bulk- and surface-spaces, and treats the nonlinear terms similarly to an exponential integrator. The convergence proof is based on estimates for a recursive formulation of the error, using the parabolic smoothing property of analytic semigroups, and a careful comparison of the exact and approximate flows. This analysis also requires a deep understanding of the effects of the Dirichlet operator (the abstract version of the harmonic extension operator), which is essential for the stable coupling in our method. Numerical experiments, including problems with dynamic boundary conditions, reporting on convergence rates are presented.
Keywords: Applied Mathematics; Computational Mathematics; General Mathematics

Stability and error estimates for non-linear Cahn–Hilliard-type equations on evolving surfaces - Beschle, Cedric Aaron; Kovács, Balázs (Numerische Mathematik)
Abstract In this paper, we consider a non-linear fourth-order evolution equation of Cahn–Hilliard-type on evolving surfaces with prescribed velocity, where the non-linear terms are only assumed to have locally Lipschitz derivatives. High-order evolving surface finite elements are used to discretise the weak equation system in space, and a modified matrix–vector formulation for the semi-discrete problem is derived. The anti-symmetric structure of the equation system is preserved by the spatial discretisation. A new stability proof, based on this structure, combined with consistency bounds proves optimal-order and uniform-in-time error estimates. The paper is concluded by a variety of numerical experiments.
Keywords: Applied Mathematics; Computational Mathematics

FEM-BEM Coupling for the Maxwell–Landau–Lifshitz–Gilbert Equations via Convolution Quadrature: Weak Form and Numerical Approximation - Bohn, Jan; Feischl, Michael; Kovács, Balázs (Computational Methods in Applied Mathematics)
Abstract The full Maxwell equations in the unbounded three-dimensional space coupled to the Landau–Lifshitz–Gilbert equation serve as a well-tested model for ferromagnetic materials. We propose a weak formulation of the coupled system based on the boundary integral formulation of the exterior Maxwell equations. We show existence and partial uniqueness of a weak solution and propose a new numerical algorithm based on finite elements and boundary elements as spatial discretization with backward Euler and convolution quadrature for the time domain. This is the first numerical algorithm which is able to deal with the coupled system of Landau–Lifshitz–Gilbert equation and full Maxwell’s equations without any simplifications like quasi-static approximations (e.g. eddy current model) and without restrictions on the shape of the domain (e.g. convexity). We show well-posedness and convergence of the numerical algorithm under minimal assumptions on the regularity of the solution. This is particularly important as there are few regularity results available and one generally expects the solution to be non-smooth. Numerical experiments illustrate and expand on the theoretical results.
Keywords: Applied Mathematics; Computational Mathematics; Numerical Analysis

Learning Concept Lengths Accelerates Concept Learning in ALC - KOUAGOU, N'Dah Jean; Heindorf, Stefan; Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (The Semantic Web)

Rate Splitting in MIMO RIS-Assisted Systems With Hardware Impairments and Improper Signaling - Soleymani, Mohammad; Santamaria, Ignacio; Jorswieck, Eduard A. (IEEE Transactions on Vehicular Technology)
Keywords: Electrical and Electronic Engineering; Computer Networks and Communications; Aerospace Engineering; Automotive Engineering

Improper Signaling for Multicell MIMO RIS-Assisted Broadcast Channels With I/Q Imbalance - Soleymani, Mohammad; Santamaria, Ignacio; Schreier, Peter J. (IEEE Transactions on Green Communications and Networking)
Keywords: Computer Networks and Communications; Renewable Energy; Sustainability and the Environment

Digital Security–A Question of Perspective. A Large-Scale Telephone Survey with Four At-Risk User Groups - Herbert, Franziska; Becker, Steffen; Buckmann, Annalina; Kowalewski, Marvin; Hielscher, Jonas; Acar, Yasemin; Dürmuth, Markus; Zou, Yixin; Sasse, M Angela (arXiv preprint arXiv:2212.12964)

Neue Wege im mathematischen Unterricht - Auf den Spuren Mathilde Vaertings - Werth, Gerda (Beiträge zum Mathematikunterricht)

Multi-Task fMRI Data Fusion Using IVA and PARAFAC2 - Lehmann, Isabell; Acar, Evrim; Hasija, Tanuj; Akhonda, M.A.B.S.; Calhoun, Vince D.; Schreier, Peter; Adali, Tulay (ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

Szenario-Technik mit digitalen Technologien - Ködding, Patrick; Dumitrescu, Roman (Digitalisierung souverän gestalten II)

Linguistic features of word problems that cause difficulties for learners across the curriculum: A literature review - Malik, Sara Naseem; Rezat, Sebastian (Proceedings on the Twelfth Congress on the European Society for research in Mathematics Education (CERME 12))

Scaffolding Close Reading of Mathematical Text in Pre-service Primary Teacher Education at the Tertiary Level: Design and Evaluation - Rezat, Sebastian; Malik, Sara Naseem; Leifeld, Markus (International Journal of Science and Mathematics Education)
Abstract Even in the digital age, learning mathematics at an academic level still requires much reading of mathematical text. Research has shown that reading mathematical text requires readers to engage with all the structures of the book and with its pedagogical voice, making connections, and plausible reasoning. Specific practices and strategies that support the close reading of mathematical text have been suggested; however, descriptions and empirical evaluations of materials designed to support these activities are rare. We present the design and first evaluation cycle of materials developed in a design research project that aims to scaffold close reading of mathematical text. The materials were designed and evaluated in a German university course on elementary geometry for first-year teacher education students who study mathematics to become primary teachers. The reading strategies were explained and modeled for students in reading-strategy videos. Additionally, close reading of mathematical text was scaffolded by close-reading tasks and homework tasks and problems that build on the reading strategies and were specifically designed to foster understanding of the mathematical text. Survey data were collected from 296 students to evaluate their use of and attitude toward the different materials. The quantitative results indicate that students used the materials and were generally able to learn the course content by themselves. From all provided materials, they found the close-reading tasks most helpful. A qualitative analysis of answers to open questions revealed issues with different materials, particularly with the script, and requests for additional materials. The issues with the script were categorized inductively. The categories are presented as a qualitative result of the study and discussed.
Keywords: General Mathematics; Education

Prospective teachers’ diagnostic judgments on students’ understanding of conditional probabilities - Dröse, Jennifer; Griese, Birgit; Wessel, Lena (Twelfth Congress of the European Society for Research in Mathematics Education (CERME12))

Entwicklung und Erprobung von professionsorientierten Lernumgebungen zur Wissensvernetzung in der Algebra - Dellori, Anna; Wessel, Lena (Beiträge zum Mathematikunterricht 2022)

Design principles for intertwining local and nonlocal mathematics - The case of relating registers and representations in abstract algebra - Dellori, Anna; Wessel, Lena (Proceedings of INDRUM2022)

Pre-service Teachers' Professional Development: Relating Abstract Algebra and School Algebra - Dellori, Anna; Wessel, Lena (Proceedings of the 24th Annual Conference on Research in Undergraduate Mathematics Education)

Schreiben will gelernt sein: Schreiblerngelegenheiten adaptiv gestalten - Wessel, Lena; Dröse, Jennifer (mathematik lehren)

Facilitators’ Orientations Towards Learning Goals, Perceived Challenges, and Teaching Resources for a PD Course on Conditional Probability - Nieszporek, Ralf; Griese, Birgit; Biehler, Rolf (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
The data age has led to curriculum developments promoting the relevance of stochastics in mathematics education. This has resulted in an increased demand for teacher professional development (PD) courses, and thus in a rising number of facilitators for this purpose. Their expertise, however, remains under-researched, even though facilitators are the crucial factor in PD success. Our study aims at revealing how one aspect of facilitator expertise, orientation, is connected to other aspects: views on content goals, perception of possible challenges, and attitude towards teaching resources. The explorations reveal differing orientations and learning goals with identical teaching resources for two facilitators who had also been working as a team for the re-design of the PD course for years.

Revisiting Fundamental Ideas for Statistics Education From the Perspective of Machine Learning and Its Applications - Biehler, Rolf (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
Fundamental ideas (Burrill & Biehler, 2011) have been specified to structure the curriculum across different age levels and to focus on and revisit the most important ideas. Such ideas must be based on an epistemological analysis of the scientific domain of statistics and its applications. Because these domains are changing, fundamental ideas have to be revisited from time to time. In particular, data science and machine learning have led to new methods and applications in society that must be considered for updating fundamental ideas.

Editorial: Research on Data Science Education - Biehler, Rolf; De Veaux, Richard; Engel, Joachim; Kazak, Sibel; Frischemeier, Daniel (Statistics Education Research Journal)
A very warm welcome to this Special Issue of the Statistics Education Research Journal (SERJ) on data science education. Our hope is to give an overview of selected theoretical thoughts and empirical studies on data science education from a statistics education research perspective. Data science education is rapidly developing but research into data science education is still in its infancy. The current issue presents a snapshot of this developing field.
Keywords: Education; Statistics and Probability

Alles normal?! Daten auf Normalverteilung prüfen–mit schulischen Mitteln - Biehler, Rolf; Langlotz, Hubert; Zappe, Wilfried (mathematik lehren)

Modellieren im Stochastikunterricht: Annahmen hinterfragen, Ergebnisse validieren - Biehler, Rolf; Griese, Birgit (mathematik lehren)

Teaching and Learning Data-Driven Machine Learning with Educationally Designed Jupyter Notebooks - Fleischer, Yannik; Biehler, Rolf; Schulte, Carsten (Statistics Education Research Journal)
This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students’ work is based on a teaching module about decision trees in machine learning and a worked example of such a modelling process. The study outlines the students’ performance in carrying out the machine learning technically and reasoning about bias in the data, different data preparation steps, the application context, and the resulting decision model. Furthermore, the context of the study and the theoretical backgrounds are presented.
Keywords: Education; Statistics and Probability

Facilitators’ views on content goals, learning obstacles, and teaching resources in reference to conditional probability - Griese, Birgit; Nieszporek, Ralf; Biehler, Rolf

Mathematik-Vorkurse zur Vorbereitung auf das Studium – Zielsetzungen und didaktische Konzepte - Lankeit, Elisa; Biehler, Rolf (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

The role of learning strategies for performance in mathematics courses for engineers - Liebendörfer, Michael; Göller, Robin; Gildehaus, Lara; Kortemeyer, Jörg; Biehler, Rolf; Hochmuth, Reinhard; Ostsieker, Laura; Rode, Jana; Schaper, Niclas (International Journal of Mathematical Education in Science and Technology)
Keywords: Applied Mathematics; Education; Mathematics (miscellaneous)

Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse

Data Science, Statistics, and Civic Statistics: Education for a Fast Changing World - Ridgway, Jim; Campos, Pedro; Biehler, Rolf (Statistics for Empowerment and Social Engagement)

Mini-Aufgaben in mathematischen Übungsgruppen zur Analysis: Charakteristika von Aufgaben und Abstimmungsverhalten von Studierenden - Bauer, Thomas; Biehler, Rolf; Lankeit, Elisa (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

Vorkurse und ihre Wirkungen im Übergang Schule – Hochschule - Lankeit, Elisa; Biehler, Rolf (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

Enriching videos with interactive questions to enhance students’ cognitive activity: concept and implementation - Liebendörfer, Michael; Profeta, Angelo; Krämer, Sandra; Schlüter, Sarah; Becher, Silvia; Biehler, Rolf; Mai, Tobias; Schmitz, Angela

Dokumentation der Erhebungsinstrumente des Projekts WiGeMath - Schürmann, Mirko; Büdenbender-Kuklinski, C.; Lankeit, Elisa; Liebendörfer, Michael; Hochmuth, R.; Biehler, Rolf; Schaper, N.

Einführung in das WiGeMath-Projekt: Wirkung und Gelingensbedingungen von Unterstützungsmaßnahmen für mathematikbezogenes Lernen in der Studieneingangsphase - Hochmuth, Reinhard; Biehler, Rolf; Schaper, Niclas; Liebendörfer, Michael; Büdenbender-Kuklinski, Christiane; Lankeit, Elisa; Ruge, Johanna; Schürmann, Mirko (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

Ein Rahmenmodell für hochschuldidaktische Maßnahmen in der Mathematik - Liebendörfer, Michael; Hochmuth, Reinhard; Biehler, Rolf; Schaper, Niclas; Büdenbender-Kuklinski, Christiane; Lankeit, Elisa; Ruge, Johanna; Schürmann, Mirko (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

Jupyter Notebooks for Teaching, Learning, and Doing Data Science - Fleischer, Yannik; Hüsing, Sven; Biehler, Rolf; Podworny, Susanne; Schulte, Carsten (Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics)
We report on our work with students in our data science courses, focusing on the analysis of students’ results. This study represents an in-depth analysis of students’ creation and documentation of machine learning models. The students were supported by educationally designed Jupyter Notebooks, which are used as worked examples. Using the worked example, students document their results in a so-called computational essay. We examine which aspects of creating computational essays are difficult for students to find out how worked examples should be designed to support students without being too prescriptive. We analyze the computational essays produced by students and draw consequences for redesigning our worked example.

Profession-Specific Curriculum Design in Mathematics Teacher Education: Connecting Disciplinary Practice to the Learning of Group Theory - Wessel, Lena; Leuders, Timo (Practice-Oriented Research in Tertiary Mathematics Education)

Civic Statistics for Prospective Teachers: Developing Content and Pedagogical Content Knowledge Through Project Work - Podworny, Susanne; Frischemeier, Daniel; Biehler, Rolf (Statistics for Empowerment and Social Engagement)

Data Visualization Packages for Non-inferential Civic Statistics in High School Classrooms - Frischemeier, Daniel; Podworny, Susanne; Biehler, Rolf (Statistics for Empowerment and Social Engagement)

An example of rich, real and multivariate survey data for use in school - Podworny, Susanne; Fleischer, Yannik; Stroop, Dietlinde; Biehler, Rolf

Self-regulated learning in a mathematics course for engineers in the first semester: insights into students reported resource management and cognitive strategies - Kolbe, Tim; Wessel, Lena (Fourth conference of the International Network for Didactic Research in University Mathematics)

Evaluation von Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Schürmann, Mirko; Liebendörfer, Michael; Büdenbender-Kuklinski, Christiane; Lankeit, Elisa; Ruge, Johanna; Schaper, Niclas; Biehler, Rolf; Hochmuth, Reinhard (Unterstützungsmaßnahmen in mathematikbezogenen Studiengängen - Konzepte, Praxisbeispiele und Untersuchungsergebnisse)

Effects of drawing instructions and strategic knowledge on mathematical modeling performance: Mediated by the use of the drawing strategy - Schönherr, Johanna; Schukajlow, S.; Blomberg, J.; Leopold, C. (Applied Cognitive Psychology, ac3930)

Drawing instructions, strategic knowledge, strategy-based motivation, and students' use of drawings - Schönherr, Johanna; Schukajlow, S.; Leopold, C. (Proceedings of the 45th PME Conference)

“Free” as in Freedom to Protest? - Massacci, Fabio; Sabetta, Antonino; Mirkovic, Jelena; Murray, Toby; Okhravi, Hamed; Mannan, Mohammad; Rocha, Anderson; Bodden, Eric; Geer, Daniel E. (IEEE Security & Privacy)

On the Security of Parsing Security-Relevant HTTP Headers in Modern Browsers - Siewert, Hendrik; Kretschmer, Martin; Niemietz, Marcus; Somorovsky, Juraj (2022 IEEE Security and Privacy Workshops (SPW))
Web browsers are among the most important but also complex software solutions to access the web. It is therefore not surprising that web browsers are an attractive target for attackers. Especially in the last decade, security researchers and browser vendors have developed sandboxing mechanisms like security-relevant HTTP headers to tackle the problem of getting a more secure browser. Although the security community is aware of the importance of security-relevant HTTP headers, legacy applications and individual requests from different parties have led to possible insecure configurations of these headers. Even if specific security headers are configured correctly, conflicts in their functionalities may lead to unforeseen browser behaviors and vulnerabilities. Recently, the first work which analyzed duplicated headers and conflicts in headers was published by Calzavara et al. at USENIX Security [1]. The authors focused on inconsistent protections by using both, the HTTP header X-Frame-Options and the framing protection of the Content-Security-Policy. We extend their work by analyzing browser behaviors when parsing duplicated headers, conflicting directives, and values that do not conform to the defined ABNF metalanguage specification. We created an open-source testbed running over 19,800 test cases, at which nearly 300 test cases are executed in the set of 66 different browsers. Our work shows that browsers conform to the specification and behave securely. However, all tested browsers behave differently when it comes, for example, to parsing the Strict-Transport-Security header. Moreover, Chrome, Safari, and Firefox behave differently if the header contains a character, which is not allowed by the defined ABNF. This results in the protection mechanism being fully enforced, partially enforced, or not enforced and thus completely bypassable.

User Involvement in Training Smart Home Agents - Sieger, Leonie Nora; Hermann, Julia; Schomäcker, Astrid; Heindorf, Stefan; Meske, Christian; Hey, Celine-Chiara; Doğangün, Ayşegül (International Conference on Human-Agent Interaction)
Smart home systems contain plenty of features that enhance wellbeing in everyday life through artificial intelligence (AI). However, many users feel insecure because they do not understand the AI’s functionality and do not feel they are in control of it. Combining technical, psychological and philosophical views on AI, we rethink smart homes as interactive systems where users can partake in an intelligent agent’s learning. Parallel to the goals of explainable AI (XAI), we explored the possibility of user involvement in supervised learning of the smart home to have a first approach to improve acceptance, support subjective understanding and increase perceived control. In this work, we conducted two studies: In an online pre-study, we asked participants about their attitude towards teaching AI via a questionnaire. In the main study, we performed a Wizard of Oz laboratory experiment with human participants, where participants spent time in a prototypical smart home and taught activity recognition to the intelligent agent through supervised learning based on the user’s behaviour. We found that involvement in the AI’s learning phase enhanced the users’ feeling of control, perceived understanding and perceived usefulness of AI in general. The participants reported positive attitudes towards training a smart home AI and found the process understandable and controllable. We suggest that involving the user in the learning phase could lead to better personalisation and increased understanding and control by users of intelligent agents for smart home automation.
Keywords: human-agent interaction; smart homes; supervised learning; participation

EvoLearner: Learning Description Logics with Evolutionary Algorithms - Heindorf, Stefan; Blübaum, Lukas; Düsterhus, Nick; Werner, Till; Golani, Varun Nandkumar; Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (WWW)
Classifying nodes in knowledge graphs is an important task, e.g., predicting missing types of entities, predicting which molecules cause cancer, or predicting which drugs are promising treatment candidates. While black-box models often achieve high predictive performance, they are only post-hoc and locally explainable and do not allow the learned model to be easily enriched with domain knowledge. Towards this end, learning description logic concepts from positive and negative examples has been proposed. However, learning such concepts often takes a long time and state-of-the-art approaches provide limited support for literal data values, although they are crucial for many applications. In this paper, we propose EvoLearner - an evolutionary approach to learn ALCQ(D), which is the attributive language with complement (ALC) paired with qualified cardinality restrictions (Q) and data properties (D). We contribute a novel initialization method for the initial population: starting from positive examples (nodes in the knowledge graph), we perform biased random walks and translate them to description logic concepts. Moreover, we improve support for data properties by maximizing information gain when deciding where to split the data. We show that our approach significantly outperforms the state of the art on the benchmarking framework SML-Bench for structured machine learning. Our ablation study confirms that this is due to our novel initialization method and support for data properties.

CovidPubGraph: A FAIR Knowledge Graph of COVID-19 Publications - Pestryakova, Svetlana; Vollmers, Daniel; Sherif, Mohamed; Heindorf, Stefan; Saleem, Muhammad; Moussallem, Diego; Ngonga Ngomo, Axel-Cyrille (Scientific Data)

Multilingual Verbalization and Summarization for Explainable Link Discovery - Fathi Ahmed, Abdullah; Ahmed Sherif, Mohamed; Moussallem, Diego; Ngonga Ngomo, Axel-Cyrille (Data Knowl. Eng.)

Applying Grammar-Based Compression to RDF - Röder, Michael; Frerk, Philip; Conrads, Felix; Ngonga Ngomo, Axel-Cyrille (The Semantic Web - 18th International Conference, ESWC 2021, Virtual Event, June 6-10, 2021, Proceedings)

Unsupervised Relation Extraction Using Sentence Encoding - Ali, Manzoor; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille (The Semantic Web: ESWC 2021 Satellite Events - Virtual Event, June 6-10, 2021, Revised Selected Papers)

Unsupervised Relation Extraction Using Sentence Encoding - Ali, Manzoor; Saleem, Muhammad; Ngonga Ngomo, Axel-Cyrille (The Semantic Web: ESWC 2021 Satellite Events - Virtual Event, June 6-10, 2021, Revised Selected Papers)

InferNER: an attentive model leveraging the sentence-level information for Named Entity Recognition in Microblogs - Shahzad, Moemmur; Amin, Ayesha; Esteves, Diego; Ngonga Ngomo, Axel-Cyrille (Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, North Miami Beach, Florida, USA, May 17-19, 2021)

Lemming - Example-based Mimicking of Knowledge Graphs - Röder, Michael; Thuy Sy Nguyen, Pham; Conrads, Felix; Alexandra Morim da Silva, Ana; Ngonga Ngomo, Axel-Cyrille (15th IEEE International Conference on Semantic Computing, ICSC 2021, Laguna Hills, CA, USA, January 27-29, 2021)

SYNTHG: Mimicking RDF Graphs Using Tensor Factorization - Amer Desouki, Abdelmoneim; Conrads, Felix; Röder, Michael; Ngonga Ngomo, Axel-Cyrille (15th IEEE International Conference on Semantic Computing, ICSC 2021, Laguna Hills, CA, USA, January 27-29, 2021)