Framing Goals of Mathematics Support Measures - Liebendörfer, Michael; Büdenbender-Kuklinski, Christiane; Lankeit, Elisa; Schürmann, Mirko; Biehler, Rolf; Schaper, Niclas (Practice-Oriented Research in Tertiary Mathematics Education)

Practice-Oriented Research in Tertiary Mathematics Education

Lernvideos und ihre Erstellung - Das Projekt studiVEMINTvideos - Biehler, Rolf; Liebendörfer, Michael; Schmitz, A. (Mitteilungen der Gesellschaft für Didaktik der Mathematik)

Scale4Edge – Scaling RISC-V for Edge Applications - Ecker, Wolfgang; Krstic, Milos; Ulbricht, Markus; Mauderer, Andreas; Jentzsch, Eyck; Koch, Andreas; Koppelmann, Bastian; Müller, Wolfgang; Sadiye, Babak; Bruns, Niklas; Drechsler, Rolf; Müller-Gritschneder, Daniel; et al. (RISC-V Summit Europe 2023, Barcelona, Spain, June 2023.)

Der TETRISC SoC - Ein resilientes Quad-Core System auf Pulpissimo-Basis - Müller, Wolfgang; Ulbricht, Markus; Li, Lu; Krstic, Milos (5. ITG / GMM / GI -Workshop Testmethoden und Zuverlässigkeit von Schaltungen und Systemen)

A 28-Gb/s 27.2mW NRZ Full-Rate Bang-Bang Clock and Data Recovery in 22 nm FD-SOI CMOS Technology - Iftekhar, Mohammed; Gowda, Harshan; Kneuper, Pascal; Sadiye, Babak; Müller, Wolfgang; Scheytt, Christoph (2023 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium (BCICTS))

The Dunkl-Laplace transform and Macdonald’s hypergeometric series - Brennecken, Dominik; Rösler, Margit (Transactions of the American Mathematical Society)

Scenario-based Foresight in the Age of Digitalization and Artificial Intelligence – Identification and Analysis of Existing Use Cases - Ködding, Patrick; Ellermann, Kai; Koldewey, Christian; Dumitrescu, Roman (Procedia CIRP)
Keywords: General Medicine

Think-aloud beim hochschulischen Mathematiklernen – Ergebnisse einer Pilotierung - Kolbe, Tim (Beiträge zum Mathematikunterricht 2022. 56. Jahrestagung der Gesellschaft für Didaktik der Mathematik)

AutonomROS: A ReconROS-based Autonomous Driving Unit - Lienen, Christian; Brede, Mathis; Karger, Daniel; Koch, Kevin; Logan, Dalisha; Mazur, Janet; Nowosad, Alexander Philipp; Schnelle, Alexander; Waizy, Mohness; Platzner, Marco (2023 Seventh IEEE International Conference on Robotic Computing (IRC))

On Guaranteeing Schedulability of Periodic Real-time Hardware Tasks under ReconOS64 - Clausing, Lennart; Guetattfi, Zakarya; Kaufmann, Paul; Lienen, Christian; Platzner, Marco (Proceedings of the 19th International Symposium on Applied Reconfigurable Computing (ARC))

Mapping and Optimizing Communication in ROS 2-based Applications on Configurable System-on-Chip Platforms - Lienen, Christian; Nowosad, Alexander Philipp; Platzner, Marco (Proceedings of the 2023 9th International Conference on Robotics and Artificial Intelligence (ICRAI))

fpgaDDS: An Intra-FPGA Data Distribution Service for ROS 2 Robotics Applications - Lienen, Christian; Middeke, Sorel Horst; Platzner, Marco (Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

Characterizing external visualization in mathematics education research: a scoping review - Schoenherr, Johanna; Schukajlow, Stanislaw (ZDM – Mathematics Education)
Abstract External visualization (i.e., physically embodied visualization) is central to the teaching and learning of mathematics. As external visualization is an important part of mathematics at all levels of education, it is diverse, and research on external visualization has become a wide and complex field. The aim of this scoping review is to characterize external visualizations in recent mathematics education research in order to develop a common ground and guide future research. A qualitative content analysis of the full texts of 130 studies published between 2018 and 2022 applied a deductive-inductive coding procedure to assess four dimensions: visualization product or process, type of visualization, media, and purpose. The analysis revealed different types of external visualizations including visualizations with physical resemblance ranging from pictorial to abstract visualizations as well as three types of visualizations with structural resemblance: length, area, and relational visualizations. Future research should include measures of visualization products or processes to help explain the demands and affordances that different types of visualizations present to learners and teachers.
Keywords: General Mathematics; Education

Verifying Software and Reconfigurable Hardware Services - Wehrheim, Heike; Platzner, Marco; Bodden, Eric; Schubert, Philipp; Pauck, Felix; Jakobs, Marie-Christine (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

On-The-Fly Computing -- Individualized IT-services in dynamic markets - Haake, Claus-Jochen; Meyer auf der Heide, Friedhelm; Platzner, Marco; Wachsmuth, Henning; Wehrheim, Heike
In the proposal for our CRC in 2011, we formulated a vision of markets for IT services that describes an approach to the provision of such services that was novel at that time and, to a large extent, remains so today: „Our vision of on-the-fly computing is that of IT services individually and automatically configured and brought to execution from flexibly combinable services traded on markets. At the same time, we aim at organizing markets whose participants maintain a lively market of services through appropriate entrepreneurial actions.“ Over the last 12 years, we have developed methods and techniques to address problems critical to the convenient, efficient, and secure use of on-the-fly computing. Among other things, we have made the description of services more convenient by allowing natural language input, increased the quality of configured services through (natural language) interaction and more efficient configuration processes and analysis procedures, made the quality of (the products of) providers in the marketplace transparent through reputation systems, and increased the resource efficiency of execution through reconfigurable heterogeneous computing nodes and an integrated treatment of service description and configuration. We have also developed network infrastructures that have a high degree of adaptivity, scalability, efficiency, and reliability, and provide cryptographic guarantees of anonymity and security for market participants and their products and services. To demonstrate the pervasiveness of the OTF computing approach, we have implemented a proof-of-concept for OTF computing that can run typical scenarios of an OTF market. We illustrated the approach using a cutting-edge application scenario – automated machine learning (AutoML). Finally, we have been pushing our work for the perpetuation of On-The-Fly Computing beyond the SFB and sharing the expertise gained in the SFB in events with industry partners as well as transfer projects. This work required a broad spectrum of expertise. Computer scientists and economists with research interests such as computer networks and distributed algorithms, security and cryptography, software engineering and verification, configuration and machine learning, computer engineering and HPC, microeconomics and game theory, business informatics and management have successfully collaborated here.

Compute Centers I: Heterogeneous Execution Environments - Hansmeier, Tim; Kenter, Tobias; Meyer, Marius; Riebler, Heinrich; Platzner, Marco; Plessl, Christian (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Flexible Industrial Analytics on Reconfigurable Systems-On-Chip - Boschmann, Alexander; Clausing, Lennart; Jentzsch, Felix; Ghasemzadeh Mohammadi, Hassan; Platzner, Marco (On-The-Fly Computing -- Individualized IT-services in dynamic markets)

Monocular visual simultaneous localization and mapping: (r)evolution from geometry to deep learning-based pipelines - Álvarez-Tuñón, Olaya; Brodskiy, Yury; Kayacan, Erdal (IEEE Transactions on Artificial Intelligence)

MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection - Álvarez-Tuñón, Olaya; Kanner, Hemanth; Marnet, Luiza Ribeiro; Pham, Huy Xuan; le Fevre Sejersen, Jonas; Brodskiy, Yury; Kayacan, Erdal (2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

PredictiveSLAM - Robust Visual SLAM Through Trajectory-Aware Object Masking - Heiß, Micha; Hansen, Jakob Grimm; Li, Dengyun; Kozłowski, Michał; Kayacan, Erdal (2023 International Conference on Unmanned Aircraft Systems (ICUAS))

CAMETA: Conflict-Aware Multi-Agent Estimated Time of Arrival Prediction for Mobile Robots - le Fevre Sejersen, Jonas; Kayacan, Erdal (2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))

Intersection theorems for finite general linear groups - Ernst, Alena; Schmidt, Kai-Uwe (Mathematical Proceedings of the Cambridge Philosophical Society)
Keywords: General Mathematics

Efficient Neural Network Inference for Velocity Estimation in Athletic Relay Races on a Microcontroller - Anantha Rao, Deepak Bhardwaj

Hardware-Aware AutoML for Exploration of Custom FPGA Accelerators for RadioML - Jentzsch, Felix (2023 33rd International Conference on Field-Programmable Logic and Applications (FPL))

An Evaluation of XCS on the OpenAI Gym - Mehlich, Florian

A Comparison of Algorithms for the Generation of Layouts based on Reconfigurable Slots on FPGAs - Tadakamalla, Yashwanth

Design and Realization of Optimized Intra-FPGA ROS 2 Communication - Middeke, Sorel Horst

A Hardware/Software Co-designed ORB-SLAM2 Algorithm for FPGA - Thiele, Simon

Implementation and Evaluation of a ReconROS-based Obstacle Avoidance Architecture for Autonomous Robots - Abooof, Alhussain

Multithreaded Software/Hardware Programming with ReconOS/Zephyr on a RISC-V-based System-on-Chip - Rao, Aniruddh P

Effizienzanalyse leichtgewichtiger Neuronaler Netze für FPGA-basierte Modulationsklassifikation - Simon-Mertens, Florian

Demonstrator for Dataflow-based DNN Acceleration for Vision Applications on Platform FPGAs - Oviasogie, Marvin Osaretin

Development of a Power Analysis Framework for Embedded FPGA Accelerators - Reuter, Lucas David

Verarbeitung von Sensordaten auf eingebetteten heterogenen FPGA-Systemen - Hamm, Robin

Fast Partial Reconfiguration for ReconOS64 on Xilinx MPSoC Devices - Klassen, Alexander

Ein Simulator für Schedulability-Experimente mit periodischen Tasks auf FPGAs - Tsague Dingo, Jorian

Evaluation of Classifier Migration Between Multiple XCS Populations - Brede, Mathis

Design and Realization of an Intra-FPGA ROS 2 Communication Infrastructure for the ReconROS Executor - Nowosad, Alexander

Design and Implementation of a RadioML Demonstrator based on an RFSoC Platform - AlAidroos, Salem

Bewertung der Xilinx Runtime Library zur Hardware/Software-Kommunikation - Evers, Gerrit

Reconfigurable Random Forest Implementation on FPGA - Raeisi Nafchi, Masood

Mutation Tree Reconstruction of Tumor Cells on FPGAs Using a Bit-Level Matrix Representation - Opdenhövel, Jan-Oliver; Plessl, Christian; Kenter, Tobias (Proceedings of the 13th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies (HEART))

Advanced Synchronous Rectification for an IGBT-Based ZCS LLC Converter with High Output Currents for a 2 kW Automotive DC-DC Stage - Urbaneck, Daniel; Böcker, Joachim; Schafmeister, Frank (PCIM Europe 2023; IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management)

Neural Class Expression Synthesis in ALCHIQ(D) - Kouagou, N'Dah Jean; Heindorf, Stefan; Demir, Caglar; Ngonga Ngomo, Axel-Cyrille (Machine Learning and Knowledge Discovery in Databases: Research Track)
Class expression learning in description logics has long been regarded as an iterative search problem in an infinite conceptual space. Each iteration of the search process invokes a reasoner and a heuristic function. The reasoner finds the instances of the current expression, and the heuristic function computes the information gain and decides on the next step to be taken. As the size of the background knowledge base grows, search-based approaches for class expression learning become prohibitively slow. Current neural class expression synthesis (NCES) approaches investigate the use of neural networks for class expression learning in the attributive language with complement (ALC). While they show significant improvements over search-based approaches in runtime and quality of the computed solutions, they rely on the availability of pretrained embeddings for the input knowledge base. Moreover, they are not applicable to ontologies in more expressive description logics. In this paper, we propose a novel NCES approach which extends the state of the art to the description logic ALCHIQ(D). Our extension, dubbed NCES2, comes with an improved training data generator and does not require pretrained embeddings for the input knowledge base as both the embedding model and the class expression synthesizer are trained jointly. Empirical results on benchmark datasets suggest that our approach inherits the scalability capability of current NCES instances with the additional advantage that it supports more complex learning problems. NCES2 achieves the highest performance overall when compared to search-based approaches and to its predecessor NCES. We provide our source code, datasets, and pretrained models at https://github.com/dice-group/NCES2.

Multi-stage diarization refinement for the CHiME-7 DASR scenario - Boeddeker, Christoph; Cord-Landwehr, Tobias; von Neumann, Thilo; Haeb-Umbach, Reinhold (7th International Workshop on Speech Processing in Everyday Environments (CHiME 2023))

Explaining ELH Concept Descriptions through Counterfactual Reasoning - Sieger, Leonie Nora; Heindorf, Stefan; Blübaum, Lukas; Ngonga Ngomo, Axel-Cyrille (arXiv:2301.05109)
Knowledge bases are widely used for information management on the web, enabling high-impact applications such as web search, question answering, and natural language processing. They also serve as the backbone for automatic decision systems, e.g. for medical diagnostics and credit scoring. As stakeholders affected by these decisions would like to understand their situation and verify fair decisions, a number of explanation approaches have been proposed using concepts in description logics. However, the learned concepts can become long and difficult to fathom for non-experts, even when verbalized. Moreover, long concepts do not immediately provide a clear path of action to change one's situation. Counterfactuals answering the question "How must feature values be changed to obtain a different classification?" have been proposed as short, human-friendly explanations for tabular data. In this paper, we transfer the notion of counterfactuals to description logics and propose the first algorithm for generating counterfactual explanations in the description logic $\mathcal{ELH}$. Counterfactual candidates are generated from concepts and the candidates with fewest feature changes are selected as counterfactuals. In case of multiple counterfactuals, we rank them according to the likeliness of their feature combinations. For evaluation, we conduct a user survey to investigate which of the generated counterfactual candidates are preferred for explanation by participants. In a second study, we explore possible use cases for counterfactual explanations.

Accelerating Concept Learning via Sampling - Baci, Alkid; Heindorf, Stefan (CIKM)

Digital Transformation - Towards flexible human-centric enterprises - Kehrbusch, Burkhard; Engels, Gregor (Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective)

Optimization of optical waveguide antennas for directive emission of light - Farheen, Henna; Leuteritz, Till; Linden, Stefan; Myroshnychenko, Viktor; Förstner, Jens (Journal of the Optical Society of America B)
Optical traveling wave antennas offer unique opportunities to control and selectively guide light into a specific direction, which renders them excellent candidates for optical communication and sensing. These applications require state-of-the-art engineering to reach optimized functionalities such as high directivity and radiation efficiency, low sidelobe levels, broadband and tunable capabilities, and compact design. In this work, we report on the numerical optimization of the directivity of optical traveling wave antennas made from low-loss dielectric materials using full-wave numerical simulations in conjunction with the particle swarm optimization algorithm. The antennas are composed of a reflector and a director deposited on a glass substrate, and an emitter placed in the feed gap between them serves as an internal source of excitation. In particular, we analyze antennas with rectangular- and horn-shaped directors made of either hafnium dioxide or silicon. The optimized antennas produce highly directional emissions due to the presence of two dominant guided TE modes in the director in addition to leaky modes. These guided modes dominate the far-field emission pattern and govern the direction of the main lobe emission, which predominately originates from the end facet of the director. Our work also provides a comprehensive analysis of the modes, radiation patterns, parametric influences, and bandwidths of the antennas, which highlights their robust nature.
Keywords: tet_topic_opticalantenna

Numerical analysis of the coherent mechanism producing negative polarization at backscattering from systems of absorbing particles - Alhaddad, Samer; Grynko, Yevgen; Farheen, Henna; Förstner, Jens (Optics Letters)
We study a double-scattering coherent mechanism of negative polarization (NP) near opposition that is observed for powder-like surfaces. The problem is solved numerically for absorbing structures with irregular constituents, cubes, spheres, and ellipsoids larger than the wavelength of incident light. Our simulations show that double scattering between two random irregular particles shows weak NP. Adding one more particle significantly increases the relative contribution of double scattering which enhances NP. Simulations with regular shapes and controlled geometric parameters show that the interference mechanism is sensitive to the geometry of the scattering system and can also result in no polarization or even strong enhancement of positive polarization at backscattering.
Keywords: tet_topic_scattering

Introduction to the Data-driven Services in Manufacturing Minitrack - Exploring Management, Engineering, and Organizational Transformation - Koldewey, Christian; Dumitrescu, Roman; Rabe, Martin (Proceedings of the 55th Hawaii International Conference on System Sciences)

Low-Power Low-Data-Rate Wireless PPM Receiver Based on 13-Bits Barker Coded SAW Correlator with Scalable Data-Rate and Sensitivity - Abughannam, Saed; Scheytt, J. Christoph (International Symposium on Circuits and Systems (ISCAS 2022))

Design and Measurements of a Low-power Low-Date-rate Direct-detection Wireless Receiver with Improved Co-channel Interference Robustness - Abughannam, Saed; Kruse, Stephan; Iftekhar, Mohammed; Scheytt, J. Christoph (German Microwave Conference 2022 (GeMiC 2022))

Situational Business Model Developer: A Tool-support for Situation-speciﬁc Business Model Development - Gottschalk, Sebastian; Yigitbas, Enes; Nowosad, Alexander; Engels, Gregor (Proceedings of the 17th International Conference on Wirtschaftsinformatik)
The development of business models is a challenging task that can be supported with software tools. Here, existing approaches and tools do not focus on the company’s situation in which the development takes place (e.g., ﬁnancial resources, product type). To tackle this challenge, we used design science research to develop a situation-speciﬁc business model development approach that contains three stages: First, existing knowledge in terms of tasks to do (e.g., analyze competitive advantage), and decisions to be made (e.g., social media marketing) are stored in repositories. Second, the knowledge is used to compose a development method based on the company’s situation. Third, the development method is enacted to develop a business model. This demonstration paper presents a tool-support called Situational Business Model Developer that supports all stages of our approach. We release the tool under open-source and evaluate it with a case study on developing business models for mobile apps.
Keywords: Business Model Development; Situational Method Engineering; Tool Support

Development and Evaluation of a Collaborative Stock Trading Environment in Virtual Reality - Yigitbas, Enes; Gottschalk, Sebastian; Nowosad, Alexander; Engels, Gregor (Proceedings of the 17th International Conference on Wirtschaftsinformatik)
Due to the proliferation of Virtual Reality (VR) technology, VR is finding new applications in various domains, such as stock trading. Here, traders invest in stocks intending to increase their profit. For this purpose, in conventional stock trading, traders usually make use of 2D applications on desktop or laptop devices. This leads to many drawbacks such as poor visibility due to limited 2D representation, complex interaction due to indirect interaction via mouse and keyboard, or restricted support for collaboration between traders. To overcome these issues, we have developed a novel collaborative, virtual environment for stock trading, which enables stock traders to view financial information and trade stocks with other collaborators. The main results of a usability study indicate that the VR environment, compared to conventional stock trading, shows no significant advantages concerning efficiency and effectiveness, however, we could observe an increased user satisfaction and better collaboration.
Keywords: virtual reality; stock trading; collaboration; usability

A Discrete and Continuous Study of the Max-Chain-Formation Problem - Castenow, Jannik; Kling, Peter; Knollmann, Till; Meyer auf der Heide, Friedhelm (Information and Computation)
Keywords: Computational Theory and Mathematics; Computer Science Applications; Information Systems; Theoretical Computer Science

Network and Service Coordination: Conventional and Machine Learning Approaches" - Schneider, Stefan Balthasar

A Reference Process Model for Usage Data-Driven Product Planning - Meyer, Maurice; Wiederkehr, Ingrid; Panzner, Melina; Koldewey, Christian; Dumitrescu, Roman (Proceedings of the 55th Hawaii International Conference on System Sciences)
Cyber-physical systems generate and collect huge amounts of usage data during operation. Analyzing these data may enable manufacturing companies to identify weaknesses and learn about the users of their products. Such insights are valuable in the early phases of product development like product planning, as they facilitate decision-making for product improvement. The analysis and exploitation of usage data in product planning, however, is a new task for manufacturing companies. To reduce mistakes and improve the results, companies should build upon a suitable reference process model. Unfortunately, established models for analyzing data cannot be easily applied for product planning. In this paper, we propose a reference process model for usage data-driven product planning. It builds on three well-established models for analyzing data and addresses the unique characteristics of usage data-driven product planning. Finally, we customize the model for a manufacturing company and demonstrate how it could be implemented in practice.

Enhancing Human-in-the-Loop Adaptive Systems through Digital Twins and VR Interfaces - Yigitbas, Enes; Karakaya, Kadiray; Jovanovikj, Ivan; Engels, Gregor (Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell)

Collaborative Software Modeling in Virtual Reality - Yigitbas, Enes; Gorissen, Simon; Weidmann, Nils; Engels, Gregor (Software Engineering 2022, Fachtagung des GI-Fachbereichs Softwaretechnik, 21.-25. Februar 2022, Virtuell)

Search Space Characterization for Approximate Logic Synthesis - Witschen, Linus Matthias; Wiersema, Tobias; Reuter, Lucas David; Platzner, Marco (2022 59th ACM/IEEE Design Automation Conference (DAC))

MUSCAT: MUS-based Circuit Approximation Technique - Witschen, Linus Matthias; Wiersema, Tobias; Artmann, Matthias; Platzner, Marco (Design, Automation and Test in Europe (DATE))

High-Bandwidth Arbitrary Signal Detection Using Low-Speed Electronics - Meier, Janosch; Singh, Karanveer; Misra, Arijit; Preussler, Stefan; Scheytt, Christoph; Schneider, Thomas (IEEE Photonics Journal)
The growing demand for bandwidth and energy efficiency requires new solutions for signal detection and processing. We demonstrate a concept for high-bandwidth signal detection with low-speed photodetectors and electronics. The method is based on the parallel optical sampling of a high-bandwidth signal with sinc-pulse sequences provided by a Mach-Zehnder modulator. For the electronic detection and processing this parallel sampling enables to divide the high-bandwidth optical signal with the bandwidth B into N electrical signals with the baseband bandwidth of B/(2N) . In proof-of-concept experiments with N=3 , we present the detection of 24 GHz optical signals by detectors with a bandwidth of only 4 GHz. For ideal components, the sampling and bandwidth down-conversion does not add an excess error to the signals and even for the non-ideal components of our proof-of-concept setup, it is below 1%. Thus, the rms error for the measurement of the 24 GHz signal was reduced by a factor of about 3.4 and the effective number of bits were increased by 1.8.

Locking of microwave oscillators on the interharmonics of mode-locked laser signals - Bahmanian, Meysam; Kress, Christian; Scheytt, Christoph (Optics Express)
In this paper, the theory of phase-locking of a microwave oscillator on the interharmonics, i.e. non-integer harmonics, of the repetition rate of the optical pulse train of a mode-locked laser (MLL) is developed. A balanced optical microwave phase detector (BOMPD) is implemented using a balanced Mach-Zehnder modulator and is employed to discriminate the phase difference between the envelope of the optical pulses and the microwave oscillator. It is shown mathematically that the inherent nonlinear properties of BOMPD with respect to the microwave excitation amplitude can be used for interharmonic locking. The characteristic functions of the phase detector for interharmonic locking are derived analytically and are compared with the measurement results. An opto-electronic phase-locked loop (OEPLL) is demonstrated whose output frequency locks on interharmonics of the MLL repetition rate when an appropriate modulator bias and sufficient RF amplitude are applied. Thus, for the first time theory and experiment of reliable locking on interharmonics of the repetition rate of a MLL are presented.

Evaluation of Algorithms for the Node Capacitated Clique - Roopa, Rajanna

Aufarbeitung und lmplementierung von DAG-Rider - Korzeczek, Sebastian

Hybrid Routing in Three Dimensions - Nachtigall, Marcel

mobile-env: An Open Platform for Reinforcement Learning in Wireless Mobile Networks - Schneider, Stefan Balthasar; Werner, Stefan; Khalili, Ramin; Hecker, Artur; Karl, Holger (IEEE/IFIP Network Operations and Management Symposium (NOMS))
Recent reinforcement learning approaches for continuous control in wireless mobile networks have shown impressive results. But due to the lack of open and compatible simulators, authors typically create their own simulation environments for training and evaluation. This is cumbersome and time-consuming for authors and limits reproducibility and comparability, ultimately impeding progress in the field. To this end, we propose mobile-env, a simple and open platform for training, evaluating, and comparing reinforcement learning and conventional approaches for continuous control in mobile wireless networks. mobile-env is lightweight and implements the common OpenAI Gym interface and additional wrappers, which allows connecting virtually any single-agent or multi-agent reinforcement learning framework to the environment. While mobile-env provides sensible default values and can be used out of the box, it also has many configuration options and is easy to extend. We therefore believe mobile-env to be a valuable platform for driving meaningful progress in autonomous coordination of wireless mobile networks.
Keywords: wireless mobile networks; network management; continuous control; cognitive networks; autonomous coordination; reinforcement learning; gym environment; simulation; open source

ROM-Based Multiobjective Optimization of Elliptic PDEs via Numerical Continuation - Banholzer, Stefan; Gebken, Bennet; Dellnitz, Michael; Peitz, Sebastian; Volkwein, Stefan (Non-Smooth and Complementarity-Based Distributed Parameter Systems)
Multiobjective optimization plays an increasingly important role in modern applications, where several objectives are often of equal importance. The task in multiobjective optimization and multiobjective optimal control is therefore to compute the set of optimal compromises (the Pareto set) between the conflicting objectives. Since the Pareto set generally consists of an infinite number of solutions, the computational effort can quickly become challenging which is particularly problematic when the objectives are costly to evaluate as is the case for models governed by partial differential equations (PDEs). To decrease the numerical effort to an affordable amount, surrogate models can be used to replace the expensive PDE evaluations. Existing multiobjective optimization methods using model reduction are limited either to low parameter dimensions or to few (ideally two) objectives. In this article, we present a combination of the reduced basis model reduction method with a continuation approach using inexact gradients. The resulting approach can handle an arbitrary number of objectives while yielding a significant reduction in computing time.

Efficient Virtual Design and Testing of Autonomous Vehicles - Peitz, Sebastian; Dellnitz, Michael; Bannenberg, Sebastian (German Success Stories in Industrial Mathematics)
With the ever increasing capabilities of sensors and controllers, autonomous driving is quickly becoming a reality. This disruptive change in the automotive industry poses major challenges for manufacturers as well as suppliers as entirely new design and testing strategies have to be developed to remain competitive. Most importantly, the complexity of autonomously driving vehicles in a complex, uncertain, and safety-critical environment requires new testing procedures to cover the almost infinite range of potential scenarios.

Compensation of LF Common-Mode Noise by the internal DC/DC-Stage for transformerless On-Board Chargers at Three- and Single-Phase Operation - Schafmeister, Frank (International Conference on Electric & Electronic in Hybrid and Electric Vehicles and Electric Energy Management (EEHE),)

An Open-Source Transistor Database and Toolbox as an Unified Software Engineering Tool for Managing and Evaluating Power Transistors - Förster, Nikolas; Rehlaender, Philipp; Wallscheid, Oliver; Schafmeister, Frank; Böcker, Joachim (Proc. 37th IEEE Applied Power Electronics Conference (APEC))

Robust Hysteresis Control for LLC Resonant Converters Using a Fully Isolated Measurement Scheme - Keuck, Lukas; Schafmeister, Frank; Böcker, Joachim (Proc. IEEE International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management (PCIM))

Resonant evanescent excitation of OAM modes in a high-contrast circular step-index fiber - Hammer, Manfred; Ebers, Lena; Förstner, Jens (Complex Light and Optical Forces XVI)
Resonant evanescent coupling can be utilized to selectively excite orbital angular momentum (OAM) modes of high angular order supported by a thin circular dielectric rod. Our 2.5-D hybrid-analytical coupled mode model combines the vectorial fields associated with the fundamental TE- and TM-modes of a standard silicon photonics slab waveguide, propagating at oblique angles with respect to the rod axis, and the hybrid modes supported by the rod. One observes an efficient resonant interaction in cases where the common axial wavenumber of the waves in the slab matches the propagation constant of one or more modes of the rod. For certain modes of high angular order, the incident wave is able to transfer its directionality to the field in the fiber, exciting effectively only one of a pair of degenerate OAM modes
Keywords: tet_topic_waveguide

Continuous and discrete Noether's fractional conserved quantities for restricted calculus of variations - Cresson, Jacky; Jiménez, Fernando; Ober-Blöbaum, Sina (AIMS)

Semi-guided waves in integrated optical waveguide structures - Ebers, Lena
In dieser Arbeit wird die elektromagnetische Wellenausbreitung in integrierten optischen Wellenleitern mit Hilfe von halb analytischen und numerischen Simulationsmethoden untersucht. Im ersten Teil werden 2-D Si/SiO2-Wellenleiterkonfigurationen mit hohem Brechungsindexkontrast betrachtet. Die Strukturen werden mit halb geführten Wellen unter schrägen Ausbreitungswinkeln angeregt. Dadurch kann die Leistungsübertragung zu bestimmten ausgehenden Moden unterdrückt werden, wodurch vollständig verlustfreie Systeme entstehen. Zusätzlich dient die Anregung mit einem seitlich begrenzten, einfallenden Wellenbündel aus halb geführten Wellen dazu, praktisch relevantere 3-D Konfigurationen zu realisieren. Darüber hinaus wird eine schrittweise Winkelspektrum-Methode vorgestellt, die es ermöglicht, in Kombination mit voll vektoriellen 2-D Finite-Elemente-Lösungen für Teilprobleme mit geringerer Komplexität, die Wellenausbreitung in planaren, linsenförmigen Wellenleitern numerisch in drei Raumrichtungen zu berechnen. Im zweiten Teil dieser Arbeit wird die Ausbreitung in Wellenleiterstrukturen aus Lithiumniobat untersucht, welche für quantenoptische Effekte genutzt werden. Zur Detektion einzelner Photonen werden supraleitende Nanodrähte auf eindiffundierten Lithiumniobat Wellenleitern mit zusätzlicher Taperschicht aus Silizium betrachtet. Um die Wellenausbreitung in diesen 3-D Wellenleitern zu beschreiben, wird eine einseitig gerichtete Finite-Elemente „Modal Matching“ Methode eingeführt. Abschließend werden Rippenwellenleiter aus Lithiumniobat analysiert, die auf Siliziumdioxid Plattformen aufgebracht sind. Der Schwerpunkt liegt hier auf dem nichtlinearen „Parametric Down-Conversion“ Prozess, der für die Erzeugung verschränkter Photonen verwendet wird.
Keywords: tet_topic_waveguide

Work-in-Progress: The Potential of Interactive Scripts – Supporting Conceptual Understanding and Collaborative Problem-Solving Skills - Temmen, Katrin; Kersten, Peter; Schäfer, Dominik (Mobility for Smart Cities and Regional Development - Challenges for Higher Education)

Comparative Evaluation of MVAC-LVDC SST and Hybrid Transformer Concepts for Future Datacenters - Huber, Jonas; Wallmeier, Peter; Pieper, Ralf; Schafmeister, Frank; Kolar, Johann (Proc. 9th IEEJ International Power Electronics Conference (IPEC))

Turnpike Property in Optimal Microbial Metabolite Production - Caillau, Jean-Baptiste; Djema, Walid; Gouzé, Jean-Luc; Maslovskaya, Sofya; Pomet, Jean-Baptiste (Journal of Optimization Theory and Applications)
Abstract We consider the problem of maximization of metabolite production in bacterial cells formulated as a dynamical optimal control problem (DOCP). According to Pontryagin’s maximum principle, optimal solutions are concatenations of singular and bang arcs and exhibit the chattering or Fuller phenomenon, which is problematic for applications. To avoid chattering, we introduce a reduced model which is still biologically relevant and retains the important structural features of the original problem. Using a combination of analytical and numerical methods, we show that the singular arc is dominant in the studied DOCPs and exhibits the turnpike property. This property is further used in order to design simple and realistic suboptimal control strategies.
Keywords: Applied Mathematics; Management Science and Operations Research; Control and Optimization

A Survey of Methods for Automated Algorithm Configuration - Schede, Elias; Brandt, Jasmin; Tornede, Alexander; Wever, Marcel Dominik; Bengs, Viktor; Hüllermeier, Eyke; Tierney, Kevin (arXiv:2202.01651)
Algorithm configuration (AC) is concerned with the automated search of the most suitable parameter configuration of a parametrized algorithm. There is currently a wide variety of AC problem variants and methods proposed in the literature. Existing reviews do not take into account all derivatives of the AC problem, nor do they offer a complete classification scheme. To this end, we introduce taxonomies to describe the AC problem and features of configuration methods, respectively. We review existing AC literature within the lens of our taxonomies, outline relevant design choices of configuration approaches, contrast methods and problem variants against each other, and describe the state of AC in industry. Finally, our review provides researchers and practitioners with a look at future research directions in the field of AC.

Quantification of the adhesive coupling of layered structures using guided ultrasonic waves - Nicolai, Marcel; Zeipert, Henning; Lugovtsova, Yevgeniya; Bulling, Jannis; Johannesmann, Sarah; Prager, Jens; Henning, Bernd (Fortschritte der Akustik - DAGA 2022)

Self-Adaptive Digital Assistance Systems for Work 4.0 - Yigitbas, Enes; Sauer, Stefan; Engels, Gregor (Digital Transformation: Core Technologies and Emerging Topics from a Computer Science Perspective)

Integrating Safety Guarantees into the Learning Classifier System XCS - Hansmeier, Tim; Platzner, Marco (Applications of Evolutionary Computation, EvoApplications 2022, Proceedings)

Coordinating Amoebots via Reconfigurable Circuits - Feldmann, Michael; Padalkin, Andreas; Scheideler, Christian; Dolev, Shlomi (J. Comput. Biol.)

Computation on Encrypted Data Using Dataflow Authentication - Fischer, Andreas; Fuhry, Benny; Kußmaul, Jörn; Janneck, Jonas; Kerschbaum, Florian; Bodden, Eric (ACM Transactions on Privacy and Security)
Encrypting data before sending it to the cloud ensures data confidentiality but requires the cloud to compute on encrypted data. Trusted execution environments, such as Intel SGX enclaves, promise to provide a secure environment in which data can be decrypted and then processed. However, vulnerabilities in the executed program give attackers ample opportunities to execute arbitrary code inside the enclave. This code can modify the dataflow of the program and leak secrets via SGX side channels. Fully homomorphic encryption would be an alternative to compute on encrypted data without data leaks. However, due to its high computational complexity, its applicability to general-purpose computing remains limited. Researchers have made several proposals for transforming programs to perform encrypted computations on less powerful encryption schemes. Yet current approaches do not support programs making control-flow decisions based on encrypted data. We introduce the concept of dataflow authentication (DFAuth) to enable such programs. DFAuth prevents an adversary from arbitrarily deviating from the dataflow of a program. Our technique hence offers protections against the side-channel attacks described previously. We implemented two flavors of DFAuth, a Java bytecode-to-bytecode compiler, and an SGX enclave running a small and program-independent trusted code base. We applied DFAuth to a neural network performing machine learning on sensitive medical data and a smart charging scheduler for electric vehicles. Our transformation yields a neural network with encrypted weights, which can be evaluated on encrypted inputs in \( 12.55 \,ms \) . Our protected scheduler is capable of updating the encrypted charging plan in approximately 1.06 seconds.
Keywords: Safety; Risk; Reliability and Quality; General Computer Science

Verteiltes Berechnen kompakter Routingtabellen in Unit Disk Graphen - Hillebrandt, Henning

The Ruelle zeta function at zero for nearly hyperbolic 3-manifolds - Cekić, Mihajlo; Delarue, Benjamin; Dyatlov, Semyon; Paternain, Gabriel P. (Inventiones mathematicae)
Abstract We show that for a generic conformal metric perturbation of a compact hyperbolic 3-manifold $$Σ $$ Σ with Betti number $$b_1$$ b 1 , the order of vanishing of the Ruelle zeta function at zero equals $$4-b_1$$ 4 - b 1 , while in the hyperbolic case it is equal to $$4-2b_1$$ 4 - 2 b 1 . This is in contrast to the 2-dimensional case where the order of vanishing is a topological invariant. The proof uses the microlocal approach to dynamical zeta functions, giving a geometric description of generalized Pollicott–Ruelle resonant differential forms at 0 in the hyperbolic case and using first variation for the perturbation. To show that the first variation is generically nonzero we introduce a new identity relating pushforwards of products of resonant and coresonant 2-forms on the sphere bundle $$SΣ $$ S Σ with harmonic 1-forms on $$Σ $$ Σ .
Keywords: General Mathematics

Property-Driven Testing of Black-Box Functions - Sharma, Arnab; Melnikov, Vitaly; Hüllermeier, Eyke; Wehrheim, Heike (Proceedings of the 10th IEEE/ACM International Conference on Formal Methods in Software Engineering (FormaliSE))
Testing is one of the most frequent means of quality assurance for software. Property-based testing aims at generating test suites for checking code against user-defined properties. Test input generation is, however, most often independent of the property to be checked, and is instead based on random or user-defined data generation.In this paper, we present property-driven unit testing of functions with numerical inputs and outputs. Alike property-based testing, it allows users to define the properties to be tested for. Contrary to property-based testing, it also uses the property for a targeted generation of test inputs. Our approach is a form of learning-based testing where we first of all learn a model of a given black-box function using standard machine learning algorithms, and in a second step use model and property for test input generation. This allows us to test both predefined functions as well as machine learned regression models. Our experimental evaluation shows that our property-driven approach is more effective than standard property-based testing techniques.

Model-driven Continuous Experimentation on Component-based Software Architectures - Gottschalk, Sebastian; Yigitbas, Enes; Engels, Gregor (Proceedings of the 18th International Conference on Software Architecture Companion)
To build successful software products, developers continuously have to discover what features the users really need. This discovery can be achieved with continuous experimentation, testing different software variants with distinct user groups, and deploying the superior variant for all users. However, existing approaches do not focus on explicit modeling of variants and experiments, which offers advantages such as traceability of decisions and combinability of experiments. Therefore, our vision is the provision of model-driven continuous experimentation, which provides the developer with a framework for structuring the experimentation process. For that, we introduce the overall concept, apply it to the experimentation on component-based software architectures and point out future research questions. In particular, we show the applicability by combining feature models for modeling the software variants, users, and experiments (i.e., model-driven) with MAPE-K for the adaptation (i.e., continuous experimentation) and implementing the concept based on the component-based Angular framework.
Keywords: continuous experimentation; model-driven; component-based software architectures; self-adaptation

Symmetrieverständnis von Anfang an - Häsel-Weide, Uta; Wallner, Melina; Hattermann, M. (Anfangsunterricht für alle Kinder - Willkommen in der Schule!)

A PLACE FOR A DATA SCIENCE PROJECT IN SCHOOL: BETWEEN STATISTICS AND EPISTEMIC PROGRAMMING - PODWORNY, SUSANNE; Hüsing, Sven; SCHULTE, CARSTEN (STATISTICS EDUCATION RESEARCH JOURNAL)
Aspects of data science surround us in many contexts, for example regarding climate change, air pollution, and other environmental issues. To open the “data-science-black-box” for lower secondary school students we developed a data science project focussing on the analysis of self-collected environmental data. We embed this project in computer science education, which enables us to use a new knowledge-based programming approach for the data analysis within Jupyter Notebooks and the programming language Python. In this paper, we evaluate the second cycle of this project which took place in a ninth-grade computer science class. In particular, we present how the students coped with the professional tool of Jupyter Notebooks for doing statistical investigations and which insights they gained.
Keywords: Education; Statistics and Probability

Microinverter testing update using high power modules: Efficiency, yield, and conformity to a new ”estimation formula” for variation of PV panel size - Krauter, Stefan; Bendfeld, Jörg; Möller, Marius Claus (Proceedings of the 49th IEEE Photovoltaic Specialists Conference)
The market for microinverters is growing, especially in Europe. Driven by the strongly rising prices for electricity, many small photovoltaic energy systems are being installed. Since monitoring for these plants is often quite costly, their yields are often not logged. Since 2014, microinverters have been studied at the University of Paderborn. The investigations are divided into indoor and outdoor tests. In the indoor area conversion efficiencies as a function of load have been measured with high accuracy and ranked according to Euro- and CEC weightings. In the outdoor laboratory, the behavior in the real world is tested. Energy yields have been measured outdoors via identical and calibrated crystalline silicon PV modules. Here, the investigations were carried out with modules of the power of 215 Wp until the year 2020. Because of the increasing module power nowadays, modules with an output of 360 Wp are now being used. To assess the influence of PV module size, two extremes have been investigated: A rather small module with 215 Wp - as it has been used 10 years ago, and a brand-new module (2021) offering 360 Wp. Both types of modules contain 60 solar cells in series connection. Appling the low-power modules, the challenge for the different micro-inverters has been during weak-light conditions, using the high-power modules, some inverters temporarily reach their power limits and yield is reduced. A method using a reference configuration of inverter & module and a linear equation resulting in the actual yield, any module & inverter configuration can be characterized by just the two coefficients.

Professionalisierung für inklusiven Mathematikunterricht. Interdisziplinäre Seminarkonzeption zur reflexiven Professionalisierung angehender Mathematiklehrkräfte in der Sekundarstufe - Häsel-Weide, Uta; Seitz, S.; Wallner, Melina; Wilke, Y. (Qualifizierung für Inklusion. Sekundarstufe)

Diagnosegeleitete Förderung im inklusiven Mathematikunterricht der Grundschule – Professionalisierung durch reflektierte Handlungspraxis in der Lehrer*innenbildung. - Hähn, K.; Häsel-Weide, Uta; Scherer, P. (QfI - Qualifizierung für Inklusion)

Model of a Self-Sufficient PV Home using a Hybrid Storage System based on Li-Ion Batteries and Hydrogen Storage with Waste Heat Utilization - Möller, Marius Claus; Krauter, Stefan (Proceedings of the 49th IEEE Photovoltaic Specialists Conference)
This paper provides a hybrid energy system model created in Matlab/Simulink which is based on photovoltaics as its main energy source. The model includes a hybrid energy storage which consists of a short-term lithium-ion battery and hydrogen as long-term storage to ensure autonomy even during periods of low PV production (e.g., in winter). The sectors heat and electricity are coupled by using the waste-heat generated by production and reconversion of hydrogen through an electrolyser respectively a fuel cell. A heat pump has been considered to cover the residual heat demand (for well insulated homes). Within this paper a model of the space heating system as well as the hot water heating system is presented. The model is designed for the simulation and analysis of a whole year energy flow by using a time series of loads, weather and heat profiles as input. Moreover, results of the energy balance within the energy system by simulation of a complete year by varying the orientation (elevation and azimuth) of the PV system and the component sizing, such as the lithium-ion battery capacity, are presented. It turned out that a high amount of heating energy can be saved by using the waste heat generated by the electrolyser and the fuel cell. The model is well suited for the analysis of the effects of different component dimensionings in a hydrogen-based energy system via the overall energy balance within the residential sector.

Hybrid Energy System Model in Matlab/Simulink based on Solar Energy, Lithium-Ion Battery and Hydrogen - Möller, Marius Claus; Krauter, Stefan (Energies / Special Issue "Sustainable Energy Concepts for Energy Transition")
In this paper, a model of a hybrid, hydrogen-based energy system for a household which includes the heating sector is presended. With such an energy system it's possible to enable energy autarky over a whole year based on solar energy. The scope of this study was to present a verified hybrid energy system model created in Simulink which can be used to prospectively size future similar energy systems where hydrogen in combination with a li-ion battery shall be used as energy storage type.

Koopman analysis of quantum systems - Klus, Stefan; Nüske, Feliks; Peitz, Sebastian (Journal of Physics A: Mathematical and Theoretical)
Koopman operator theory has been successfully applied to problems from various research areas such as fluid dynamics, molecular dynamics, climate science, engineering, and biology. Applications include detecting metastable or coherent sets, coarse-graining, system identification, and control. There is an intricate connection between dynamical systems driven by stochastic differential equations and quantum mechanics. In this paper, we compare the ground-state transformation and Nelson's stochastic mechanics and demonstrate how data-driven methods developed for the approximation of the Koopman operator can be used to analyze quantum physics problems. Moreover, we exploit the relationship between Schrödinger operators and stochastic control problems to show that modern data-driven methods for stochastic control can be used to solve the stationary or imaginary-time Schrödinger equation. Our findings open up a new avenue towards solving Schrödinger's equation using recently developed tools from data science.

CamBench -- Cryptographic API Misuse Detection Tool Benchmark Suite - Schlichtig, Michael; Wickert, Anna-Katharina; Krüger, Stefan; Bodden, Eric; Mezini, Mira
Context: Cryptographic APIs are often misused in real-world applications. Therefore, many cryptographic API misuse detection tools have been introduced. However, there exists no established reference benchmark for a fair and comprehensive comparison and evaluation of these tools. While there are benchmarks, they often only address a subset of the domain or were only used to evaluate a subset of existing misuse detection tools. Objective: To fairly compare cryptographic API misuse detection tools and to drive future development in this domain, we will devise such a benchmark. Openness and transparency in the generation process are key factors to fairly generate and establish the needed benchmark. Method: We propose an approach where we derive the benchmark generation methodology from the literature which consists of general best practices in benchmarking and domain-specific benchmark generation. A part of this methodology is transparency and openness of the generation process, which is achieved by pre-registering this work. Based on our methodology we design CamBench, a fair "Cryptographic API Misuse Detection Tool Benchmark Suite". We will implement the first version of CamBench limiting the domain to Java, the JCA, and static analyses. Finally, we will use CamBench to compare current misuse detection tools and compare CamBench to related benchmarks of its domain.
Keywords: cryptography; benchmark; API misuse; static analysis

Bringing Massive Parallelism and Hardware Acceleration to Linear Scaling Density Functional Theory Through Targeted Approximations - Lass, Michael