TY - CONF
AB - Digital Servitization is one of the significant trends affecting the manufacturing industry. Companies try to tackle challenges regarding their differentiation and profitability using digital services. One specific type of digital services are smart services, which are digital services built on data from smart products. Introducing these kinds of offerings into the portfolio of manufacturing companies is not trivial. Moreover, they require conscious action to align all relevant capabilities to realize the respective business goals. However, what capabilities are generally relevant for smart services remains opaque. We conducted a systematic literature review to identify them and extended the results through an interview study. Our analysis results in 78 capabilities clustered among 12 principles and six dimensions. These results provide significant support for the smart service transformation of manufacturing companies and for structuring the research field of smart services.
AU - Koldewey, Christian
AU - Fichtler, Timm
AU - Scholtysik, Michel
AU - Biehler, Jan
AU - Schreiner, Nick
AU - Sommer, Franziska
AU - Schacht, Maximilian
AU - Kaufmann, Jonas
AU - Rabe, Martin
AU - Sedlmeier, Joachim
AU - Dumitrescu, Roman
ID - 48632
KW - Digital Servitization
KW - Transformation
KW - Capabilities
KW - Maturity
KW - Smart Services
TI - Exploring Capabilities for the Smart Service Transformation in Manufacturing: Insights from Theory and Practice
ER -
TY - JOUR
AU - Herbert, Franziska
AU - Becker, Steffen
AU - Buckmann, Annalina
AU - Kowalewski, Marvin
AU - Hielscher, Jonas
AU - Acar, Yasemin
AU - Dürmuth, Markus
AU - Sasse, M. Angela
AU - Zou, Yixin
ID - 47275
JF - IEEE Symposium on Security and Privacy. IEEE, New York, NY, USA
TI - Digital Security -- A Question of Perspective. A Large-Scale Telephone Survey with Four At-Risk User Groups
ER -
TY - CONF
AU - Afroze, Lameya
AU - Merkelbach, Silke
AU - von Enzberg, Sebastian
AU - Dumitrescu, Roman
ID - 49354
T2 - ML4CPS 2023
TI - Domain Knowledge Injection Guidance for Predictive Maintenance
ER -
TY - CONF
AU - Scholtysik, Michel
AU - Rohde, Malte
AU - Koldewey, Christian
AU - Dumitrescu, Roman
ID - 49363
TI - Circular Product-Service-System Ideation Canvas – A Framework for the Design of circular Product-Service-System Ideas
ER -
TY - CONF
AU - Scholtysik, Michel
AU - Rohde, Malte
AU - Koldewey, Christian
AU - Dumitrescu, Roman
ID - 49364
TI - Business strategy taxonomy and solution patterns for the circular economy
ER -
TY - JOUR
AU - Weich, Tobias
AU - Guedes Bonthonneau, Yannick
AU - Guillarmou, Colin
ID - 32097
JF - Journal of Differential Geometry (to appear) -- arXiv:2103.12127
TI - SRB Measures of Anosov Actions
ER -
TY - CONF
AU - Kruse, Stephan
AU - Schwabe, Tobias
AU - Kneuper, Pascal
AU - Kurz, Heiko G.
AU - Meinecke, March-Michael
AU - Scheytt, Christoph
ID - 50287
T2 - German Microwave Conference (GeMiC)
TI - Analysis and Simulation of a Photonic Multiband FMCW Radar Sensor System using Nyquist Pulses
ER -
TY - JOUR
AB - We show how to learn discrete field theories from observational data of fields on a space-time lattice. For this, we train a neural network model of a discrete Lagrangian density such that the discrete Euler--Lagrange equations are consistent with the given training data. We, thus, obtain a structure-preserving machine learning architecture. Lagrangian densities are not uniquely defined by the solutions of a field theory. We introduce a technique to derive regularisers for the training process which optimise numerical regularity of the discrete field theory. Minimisation of the regularisers guarantees that close to the training data the discrete field theory behaves robust and efficient when used in numerical simulations. Further, we show how to identify structurally simple solutions of the underlying continuous field theory such as travelling waves. This is possible even when travelling waves are not present in the training data. This is compared to data-driven model order reduction based approaches, which struggle to identify suitable latent spaces containing structurally simple solutions when these are not present in the training data. Ideas are demonstrated on examples based on the wave equation and the Schrödinger equation.
AU - Offen, Christian
AU - Ober-Blöbaum, Sina
ID - 46469
IS - 1
JF - Chaos
SN - 1054-1500
TI - Learning of discrete models of variational PDEs from data
VL - 34
ER -
TY - CONF
AU - Krings, Sarah Claudia
AU - Yigitbas, Enes
ID - 50476
T2 - Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems (EICS 2024) (to appear)
TI - TARPS: A Toolbox for Enhancing Privacy and Security for Collaborative AR
ER -
TY - CHAP
AU - Prediger, Susanne
AU - Wessel, Lena
ED - Efing, Christian
ED - Kalkavan-Aydin, Zeynep
ID - 50554
SN - 978-3-11-074544-3
T2 - Berufs-und Fachsprache Deutsch in Wissenschaft und Praxis
TI - 31 Sprachbildung im berufsbezogenen Mathematikunterricht.
VL - Band 3
ER -
TY - CONF
AU - Dou, Feng
AU - Wang, Lin
AU - Chen, Shutong
AU - Liu, Fangming
ID - 50066
T2 - Proceedings of the IEEE International Conference on Computer Communications (INFOCOM)
TI - X-Stream: A Flexible, Adaptive Video Transformer for Privacy-Preserving Video Stream Analytics
ER -
TY - CONF
AU - Blöcher, Marcel
AU - Nedderhut, Nils
AU - Chuprikov, Pavel
AU - Khalili, Ramin
AU - Eugster, Patrick
AU - Wang, Lin
ID - 50065
T2 - Proceedings of the IEEE International Conference on Computer Communications (INFOCOM)
TI - Train Once Apply Anywhere: Effective Scheduling for Network Function Chains Running on FUMES
ER -
TY - CONF
AU - Hu, Haichuan
AU - Liu, Fangming
AU - Pei, Qiangyu
AU - Yuan, Yongjie
AU - Xu, Zichen
AU - Wang, Lin
ID - 50807
T2 - Proceedings of the ACM Web Conference (WWW)
TI - 𝜆Grapher: A Resource-Efficient Serverless System for GNN Serving through Graph Sharing
ER -
TY - GEN
AB - We rigorously derive novel and sharp finite-data error bounds for highly
sample-efficient Extended Dynamic Mode Decomposition (EDMD) for both i.i.d. and
ergodic sampling. In particular, we show all results in a very general setting
removing most of the typically imposed assumptions such that, among others,
discrete- and continuous-time stochastic processes as well as nonlinear partial
differential equations are contained in the considered system class. Besides
showing an exponential rate for i.i.d. sampling, we prove, to the best of our
knowledge, the first superlinear convergence rates for ergodic sampling of
deterministic systems. We verify sharpness of the derived error bounds by
conducting numerical simulations for highly-complex applications from molecular
dynamics and chaotic flame propagation.
AU - Philipp, Friedrich M.
AU - Schaller, Manuel
AU - Boshoff, Septimus
AU - Peitz, Sebastian
AU - Nüske, Feliks
AU - Worthmann, Karl
ID - 51160
T2 - arXiv:2402.02494
TI - Extended Dynamic Mode Decomposition: Sharp bounds on the sample efficiency
ER -
TY - JOUR
AB - AbstractApproximation of subdifferentials is one of the main tasks when computing descent directions for nonsmooth optimization problems. In this article, we propose a bisection method for weakly lower semismooth functions which is able to compute new subgradients that improve a given approximation in case a direction with insufficient descent was computed. Combined with a recently proposed deterministic gradient sampling approach, this yields a deterministic and provably convergent way to approximate subdifferentials for computing descent directions.
AU - Gebken, Bennet
ID - 51208
JF - Computational Optimization and Applications
KW - Applied Mathematics
KW - Computational Mathematics
KW - Control and Optimization
SN - 0926-6003
TI - A note on the convergence of deterministic gradient sampling in nonsmooth optimization
ER -
TY - GEN
AB - Given a real semisimple connected Lie group $G$ and a discrete torsion-free
subgroup $\Gamma < G$ we prove a precise connection between growth rates of the
group $\Gamma$, polyhedral bounds on the joint spectrum of the ring of
invariant differential operators, and the decay of matrix coefficients. In
particular, this allows us to completely characterize temperedness of
$L^2(\Gamma\backslash G)$ in this general setting.
AU - Lutsko, Christopher
AU - Weich, Tobias
AU - Wolf, Lasse Lennart
ID - 51204
T2 - arXiv:2402.02530
TI - Polyhedral bounds on the joint spectrum and temperedness of locally symmetric spaces
ER -
TY - JOUR
AU - Hasler, David
AU - Hinrichs, Benjamin
AU - Siebert, Oliver
ID - 51374
IS - 7
JF - Journal of Functional Analysis
KW - Analysis
SN - 0022-1236
TI - Non-Fock ground states in the translation-invariant Nelson model revisited non-perturbatively
VL - 286
ER -
TY - JOUR
AU - Weich, Tobias
AU - Guedes Bonthonneau, Yannick
AU - Guillarmou, Colin
AU - Hilgert, Joachim
ID - 32101
JF - J. Europ. Math. Soc.
TI - Ruelle-Taylor resonaces of Anosov actions
ER -
TY - GEN
AU - Hilgert, Joachim
ID - 51501
TI - Quantum-Classical Correspondences for Locally Symmetric Spaces
ER -
TY - JOUR
AB - We derive efficient algorithms to compute weakly Pareto optimal solutions for smooth, convex and unconstrained multiobjective optimization problems in general Hilbert spaces. To this end, we define a novel inertial gradient-like dynamical system in the multiobjective setting, which trajectories converge weakly to Pareto optimal solutions. Discretization of this system yields an inertial multiobjective algorithm which generates sequences that converge weakly to Pareto optimal solutions. We employ Nesterov acceleration to define an algorithm with an improved convergence rate compared to the plain multiobjective steepest descent method (Algorithm 1). A further improvement in terms of efficiency is achieved by avoiding the solution of a quadratic subproblem to compute a common step direction for all objective functions, which is usually required in first-order methods. Using a different discretization of our inertial gradient-like dynamical system, we obtain an accelerated multiobjective gradient method that does not require the solution of a subproblem in each step (Algorithm 2). While this algorithm does not converge in general, it yields good results on test problems while being faster than standard steepest descent.
AU - Sonntag, Konstantin
AU - Peitz, Sebastian
ID - 46019
JF - Journal of Optimization Theory and Applications
TI - Fast Multiobjective Gradient Methods with Nesterov Acceleration via Inertial Gradient-Like Systems
ER -
TY - GEN
AB - The efficient optimization method for locally Lipschitz continuous multiobjective optimization problems from [1] is extended from finite-dimensional problems to general Hilbert spaces. The method iteratively computes Pareto critical points, where in each iteration, an approximation of the subdifferential is computed in an efficient manner and then used to compute a common descent direction for all objective functions. To prove convergence, we present some new optimality results for nonsmooth multiobjective optimization problems in Hilbert spaces. Using these, we can show that every accumulation point of the sequence generated by our algorithm is Pareto critical under common assumptions. Computational efficiency for finding Pareto critical points is numerically demonstrated for multiobjective optimal control of an obstacle problem.
AU - Sonntag, Konstantin
AU - Gebken, Bennet
AU - Müller, Georg
AU - Peitz, Sebastian
AU - Volkwein, Stefan
ID - 51334
T2 - arXiv:2402.06376
TI - A Descent Method for Nonsmooth Multiobjective Optimization in Hilbert Spaces
ER -
TY - JOUR
AB - We present a convolutional framework which significantly reduces the complexity and thus, the computational effort for distributed reinforcement learning control of dynamical systems governed by partial differential equations (PDEs). Exploiting translational equivariances, the high-dimensional distributed control problem can be transformed into a multi-agent control problem with many identical, uncoupled agents. Furthermore, using the fact that information is transported with finite velocity in many cases, the dimension of the agents’ environment can be drastically reduced using a convolution operation over the state space of the PDE, by which we effectively tackle the curse of dimensionality otherwise present in deep reinforcement learning. In this setting, the complexity can be flexibly adjusted via the kernel width or by using a stride greater than one (meaning that we do not place an actuator at each sensor location). Moreover, scaling from smaller to larger domains – or the transfer between different domains – becomes a straightforward task requiring little effort. We demonstrate the performance of the proposed framework using several PDE examples with increasing complexity, where stabilization is achieved by training a low-dimensional deep deterministic policy gradient agent using minimal computing resources.
AU - Peitz, Sebastian
AU - Stenner, Jan
AU - Chidananda, Vikas
AU - Wallscheid, Oliver
AU - Brunton, Steven L.
AU - Taira, Kunihiko
ID - 40171
JF - Physica D: Nonlinear Phenomena
TI - Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning
VL - 461
ER -
TY - JOUR
AB - athematische Kompetenzen digital zu fördern und digitale Kompetenzen mathematisch zu fördern – dies ist eine Forderung der neuen Bildungsstandards mit Blick auf eine Bildung in der digitalen Welt. Gerade das Potenzial digitaler Medien für das fachliche Lernen wurde in vielen Studien bestätigt. Eine sinnvoll gestaltete Einbettung digitaler Medien bietet die Chance, allen fünf Prinzipien eines guten Unterrichts gerecht zu werden: Verstehensorientierung, Durchgängigkeit, kognitive Aktivierung, Lernendenorientierung & Adaptivität und Kommunikationsförderung. Die flächendeckende Nutzung digitaler Medien etabliert sich bislang nur zögerlich. Aber wie können wir Lehrkräfte stärken, digitale Medien sinnvoll einzusetzen? Wir möchten hier die Bandbreite der Möglichkeiten an Beispielen verdeutlichen, ihren Einsatz motivieren und Wege für einen guten Unterricht aufzeigen.
AU - Barzel, Bärbel
AU - Greefrath, Gilbert
AU - Nagel, Mareike
AU - Hoffmann, Max
ID - 51841
JF - mathematik lehren
TI - Digitalisierung als Chance für alle Prinzipien guten Unterrichts
VL - 242
ER -
TY - GEN
AU - Dorociak, Svitlana
ID - 52318
TI - Implementierung eines Algorithmus zur motivbasierten Schnitt-Sparsifizierung
ER -
TY - CONF
AB - Android applications collecting data from users must protect it according to the current legal frameworks. Such data protection has become even more important since the European Union rolled out the General Data Protection Regulation (GDPR). Since app developers are not legal experts, they find it difficult to write privacy-aware source code. Moreover, they have limited tool support to reason about data protection throughout their app development process.
This paper motivates the need for a static analysis approach to diagnose and explain data protection in Android apps. The analysis will recognize personal data sources in the source code, and aims to further examine the data flow originating from these sources. App developers can then address key questions about data manipulation, derived data, and the presence of technical measures. Despite challenges, we explore to what extent one can realize this analysis through static taint analysis, a common method for identifying security vulnerabilities. This is a first step towards designing a tool-based approach that aids app developers and assessors in ensuring data protection in Android apps, based on automated static program analysis.
AU - Khedkar, Mugdha
AU - Bodden, Eric
ID - 52235
KW - static program analysis
KW - data protection and privacy
KW - GDPR compliance
T2 - Proceedings of the 9th International Conference on Mobile Software Engineering and Systems
TI - Toward an Android Static Analysis Approach for Data Protection
ER -
TY - GEN
AB - We introduce the concept of a k-token signed graph and study some of its combinatorial and algebraic properties. We prove that two switching isomorphic signed graphs have switching isomorphic token graphs. Moreover, we show that the Laplacian spectrum of a balanced signed graph is contained in the Laplacian spectra of its k-token signed graph. Besides, we introduce and study the unbalance level of a signed graph, which is a new parameter that measures how far a signed graph is from being balanced. Moreover, we study the relation between the frustration index and the unbalance level of signed graphs and their token signed graphs.
AU - Dalfó, C.
AU - Fiol, M. A.
AU - Steffen, Eckhard
ID - 52342
T2 - arXiv:2403.02924
TI - On token signed graphs
ER -
TY - JOUR
AU - Bodden, Eric
AU - Pottebaum, Jens
AU - Fockel, Markus
AU - Gräßler, Iris
ID - 52587
IS - 1
JF - IEEE Security & Privacy
KW - Law
KW - Electrical and Electronic Engineering
KW - Computer Networks and Communications
SN - 1540-7993
TI - Evaluating Security Through Isolation and Defense in Depth
VL - 22
ER -
TY - JOUR
AB - Data-driven models for nonlinear dynamical systems based on approximating the underlying Koopman operator or generator have proven to be successful tools for forecasting, feature learning, state estimation, and control. It has become well known that the Koopman generators for control-affine systems also have affine dependence on the input, leading to convenient finite-dimensional bilinear approximations of the dynamics. Yet there are still two main obstacles that limit the scope of current approaches for approximating the Koopman generators of systems with actuation. First, the performance of existing methods depends heavily on the choice of basis functions over which the Koopman generator is to be approximated; and there is currently no universal way to choose them for systems that are not measure preserving. Secondly, if we do not observe the full state, we may not gain access to a sufficiently rich collection of such functions to describe the dynamics. This is because the commonly used method of forming time-delayed observables fails when there is actuation. To remedy these issues, we write the dynamics of observables governed by the Koopman generator as a bilinear hidden Markov model, and determine the model parameters using the expectation-maximization (EM) algorithm. The E-step involves a standard Kalman filter and smoother, while the M-step resembles control-affine dynamic mode decomposition for the generator. We demonstrate the performance of this method on three examples, including recovery of a finite-dimensional Koopman-invariant subspace for an actuated system with a slow manifold; estimation of Koopman eigenfunctions for the unforced Duffing equation; and model-predictive control of a fluidic pinball system based only on noisy observations of lift and drag.
AU - Otto, Samuel E.
AU - Peitz, Sebastian
AU - Rowley, Clarence W.
ID - 33461
IS - 1
JF - SIAM Journal on Applied Dynamical Systems
TI - Learning Bilinear Models of Actuated Koopman Generators from Partially-Observed Trajectories
VL - 23
ER -
TY - GEN
AB - Context
Static analyses are well-established to aid in understanding bugs or vulnerabilities during the development process or in large-scale studies. A low false-positive rate is essential for the adaption in practice and for precise results of empirical studies. Unfortunately, static analyses tend to report where a vulnerability manifests rather than the fix location. This can cause presumed false positives or imprecise results.
Method
To address this problem, we designed an adaption of an existing static analysis algorithm that can distinguish between a manifestation and fix location, and reports error chains. An error chain represents at least two interconnected errors that occur successively, thus building the connection between the fix and manifestation location. We used our tool CogniCryptSUBS for a case study on 471 GitHub repositories, a performance benchmark to compare different analysis configurations, and conducted an expert interview.
Result
We found that 50 % of the projects with a report had at least one error chain. Our runtime benchmark demonstrated that our improvement caused only a minimal runtime overhead of less than 4 %. The results of our expert interview indicate that with our adapted version participants require fewer executions of the analysis.
Conclusion
Our results indicate that error chains occur frequently in real-world projects, and ignoring them can lead to imprecise evaluation results. The runtime benchmark indicates that our tool is a feasible and efficient solution for detecting error chains in real-world projects. Further, our results gave a hint that the usability of static analyses may benefit from supporting error chains.
AU - Wickert, Anna-Katharina
AU - Schlichtig, Michael
AU - Vogel, Marvin
AU - Winter, Lukas
AU - Mezini, Mira
AU - Bodden, Eric
ID - 52663
KW - Static analysis
KW - error chains
KW - false positive re- duction
KW - empirical studies
TI - Supporting Error Chains in Static Analysis for Precise Evaluation Results and Enhanced Usability
ER -
TY - GEN
AB - We prove Feynman-Kac formulas for the semigroups generated by selfadjoint
operators in a class containing Fr\"ohlich Hamiltonians known from solid state
physics. The latter model multi-polarons, i.e., a fixed number of quantum
mechanical electrons moving in a polarizable crystal and interacting with the
quantized phonon field generated by the crystal's vibrational modes. Both the
electrons and phonons can be confined to suitable open subsets of Euclidean
space. We also include possibly very singular magnetic vector potentials and
electrostatic potentials. Our Feynman-Kac formulas comprise Fock space
operator-valued multiplicative functionals and can be applied to every vector
in the underlying Hilbert space. In comparison to the renormalized Nelson
model, for which analogous Feynman-Kac formulas are known, the analysis of the
creation and annihilation terms in the multiplicative functionals requires
novel ideas to overcome difficulties caused by the phonon dispersion relation
being constant. Getting these terms under control and generalizing other
construction steps so as to cover confined systems are the main achievements of
this article.
AU - Hinrichs, Benjamin
AU - Matte, Oliver
ID - 52691
T2 - arXiv:2403.12147
TI - Feynman-Kac formulas for semigroups generated by multi-polaron Hamiltonians in magnetic fields and on general domains
ER -
TY - JOUR
AU - Ahmed, Qazi Arbab
AU - Wiersema, Tobias
AU - Platzner, Marco
ID - 52686
JF - Journal of Hardware and Systems Security
KW - General Engineering
KW - Energy Engineering and Power Technology
SN - 2509-3428
TI - Post-configuration Activation of Hardware Trojans in FPGAs
ER -
TY - JOUR
AB - We explore the polarization hysteretic behaviour and field-dependent permittivity of ferroelectric-dielectric 2D materials formed by random dispersions of low permittivity inclusions in a ferroelectric matrix, using finite element simulations. We show how the degree of impenetrability of dielectric inclusions plays a substantial role in controlling the coercive field, remnant and saturation polarizations of the homogenized materials. The results highlight the significance of the degree of impenetrability of inclusion in tuning the effective polarization properties of such ferroelectric composites: coercive field drops significantly as percolation threshold is attained and remnant polarization decreases faster than a linear decay.
AU - Myroshnychenko, Viktor
AU - Mulavarickal Jose, Pious Mathews
AU - Farheen, Henna
AU - Ejaz, Shafaq
AU - Brosseau, Christian
AU - Förstner, Jens
ID - 52700
IS - 4
JF - Physica Scripta
KW - tet_topic_ferro
SN - 0031-8949
TI - From Swiss-cheese to discrete ferroelectric composites: assessing the ferroelectric butterfly shape in polarization loops
VL - 99
ER -
TY - CONF
AU - Sparmann, Sören
AU - Hüsing, Sven
AU - Schulte, Carsten
ID - 52380
T2 - Proceedings of the 23rd Koli Calling International Conference on Computing Education Research
TI - JuGaze: A Cell-based Eye Tracking and Logging Tool for Jupyter Notebooks
ER -
TY - CONF
AU - Hüsing, Sven
AU - Schulte, Carsten
AU - Sparmann, Sören
AU - Bolte, Mario
ID - 52379
T2 - Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1
TI - Using Worked Examples for Engaging in Epistemic Programming Projects
ER -
TY - JOUR
AB - Heteroclinic structures organize global features of dynamical systems. We analyse whether heteroclinic structures can arise in network dynamics with higher-order interactions which describe the nonlinear interactions between three or more units. We find that while commonly analysed model equations such as network dynamics on undirected hypergraphs may be useful to describe local dynamics such as cluster synchronization, they give rise to obstructions that allow to design of heteroclinic structures in phase space. By contrast, directed hypergraphs break the homogeneity and lead to vector fields that support heteroclinic structures.
AU - Bick, Christian
AU - von der Gracht, Sören
ID - 52726
IS - 2
JF - Journal of Complex Networks
KW - Applied Mathematics
KW - Computational Mathematics
KW - Control and Optimization
KW - Management Science and Operations Research
KW - Computer Networks and Communications
SN - 2051-1329
TI - Heteroclinic dynamics in network dynamical systems with higher-order interactions
VL - 12
ER -
TY - JOUR
AB - For 0 ≤ t ≤ r let m(t, r) be the maximum number s such that every t-edge-connected r-graph has s pairwise disjoint perfect matchings. There are only a few values of m(t, r) known, for instance m(3, 3) = m(4, r) = 1, and m(t, r) ≤ r − 2 for all t = 5,
and m(t, r) ≤ r − 3 if r is even. We prove that m(2l, r) ≤ 3l − 6 for every l ≥ 3 and r ≥ 2l.
AU - Ma, Yulai
AU - Mattiolo, Davide
AU - Steffen, Eckhard
AU - Wolf, Isaak Hieronymus
ID - 49905
JF - Combinatorica
KW - Computational Mathematics
KW - Discrete Mathematics and Combinatorics
SN - 0209-9683
TI - Edge-Connectivity and Pairwise Disjoint Perfect Matchings in Regular Graphs
VL - 44
ER -
TY - CONF
AU - Jafarzadeh, Hanieh
AU - Klemme, Florian
AU - Amrouch, Hussam
AU - Hellebrand, Sybille
AU - Wunderlich, Hans-Joachim
ID - 52744
T2 - European Test Symposium, The Hague, Netherlands, May 20-24, 2024
TI - Time and Space Optimized Storage-based BIST under Multiple Voltages and Variations
ER -
TY - CONF
AU - Jafarzadeh, Hanieh
AU - Klemme, Florian
AU - Amrouch, Hussam
AU - Hellebrand, Sybille
AU - Wunderlich, Hans-Joachim
ID - 52742
T2 - IEEE Latin American Test Symposium (LATS), Maceió, Brazil, April 9-12, 2024
TI - Vmin Testing under Variations: Defect vs. Fault Coverage
ER -
TY - CONF
AU - Hellebrand, Sybille
AU - Sadeghi-Kohan, Somayeh
AU - Wunderlich, Hans-Joachim
ID - 52743
T2 - International Symposium of EDA (ISEDA), Xi'an, China, May 10-13, 2024
TI - Functional Safety and Reliability of Interconnects throughout the Silicon Life Cycle
ER -
TY - CONF
AU - Wunderlich, Hans-Joachim
AU - Jafarzadeh, Hanieh
AU - Hellebrand, Sybille
ID - 52745
T2 - International Symposium of EDA (ISEDA), Xi’an, China, May 10-13, 2024
TI - Robust Test of Small Delay Faults under PVT-Variations
ER -
TY - GEN
AU - Stiballe, Alisa
AU - Reimer, Jan Dennis
AU - Sadeghi-Kohan, Somayeh
AU - Hellebrand, Sybille
ID - 50284
TI - Modeling Crosstalk-induced Interconnect Delay with Polynomial Regression
ER -
TY - CONF
AU - Hu, Lijie
AU - Habernal, Ivan
AU - Shen, Lei
AU - Wang, Di
ED - Graham, Yvette
ED - Purver, Matthew
ID - 52827
T2 - Findings of the Association for Computational Linguistics: EACL 2024, St. Julian’s, Malta, March 17-22, 2024
TI - Differentially Private Natural Language Models: Recent Advances and Future Directions
ER -
TY - CONF
AB - Neural machine translation (NMT) is a widely popular text generation task, yet there is a considerable research gap in the development of privacy-preserving NMT models, despite significant data privacy concerns for NMT systems. Differentially private stochastic gradient descent (DP-SGD) is a popular method for training machine learning models with concrete privacy guarantees; however, the implementation specifics of training a model with DP-SGD are not always clarified in existing models, with differing software libraries used and code bases not always being public, leading to reproducibility issues. To tackle this, we introduce DP-NMT, an open-source framework for carrying out research on privacy-preserving NMT with DP-SGD, bringing together numerous models, datasets, and evaluation metrics in one systematic software package. Our goal is to provide a platform for researchers to advance the development of privacy-preserving NMT systems, keeping the specific details of the DP-SGD algorithm transparent and intuitive to implement. We run a set of experiments on datasets from both general and privacy-related domains to demonstrate our framework in use. We make our framework publicly available and welcome feedback from the community.
AU - Igamberdiev, Timour
AU - Vu, Doan Nam Long
AU - Kuennecke, Felix
AU - Yu, Zhuo
AU - Holmer, Jannik
AU - Habernal, Ivan
ED - Aletras, Nikolaos
ED - De Clercq, Orphee
ID - 52842
T2 - Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
TI - DP-NMT: Scalable Differentially Private Machine Translation
ER -
TY - JOUR
AU - Boeddeker, Christoph
AU - Subramanian, Aswin Shanmugam
AU - Wichern, Gordon
AU - Haeb-Umbach, Reinhold
AU - Le Roux, Jonathan
ID - 52958
JF - IEEE/ACM Transactions on Audio, Speech, and Language Processing
KW - Electrical and Electronic Engineering
KW - Acoustics and Ultrasonics
KW - Computer Science (miscellaneous)
KW - Computational Mathematics
SN - 2329-9290
TI - TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings
VL - 32
ER -
TY - CONF
AU - Razavi, Kamran
AU - Ghafouri, Saeid
AU - Mühlhäuser, Max
AU - Jamshidi, Pooyan
AU - Wang, Lin
ID - 53095
T2 - Proceedings of the 4th Workshop on Machine Learning and Systems (EuroMLSys), colocated with EuroSys 2024
TI - Sponge: Inference Serving with Dynamic SLOs Using In-Place Vertical Scaling
ER -
TY - JOUR
AB - In this work, we consider optimal control problems for mechanical systems with fixed initial and free final state and a quadratic Lagrange term. Specifically, the dynamics is described by a second order ODE containing an affine control term. Classically, Pontryagin's maximum principle gives necessary optimality conditions for the optimal control problem. For smooth problems, alternatively, a variational approach based on an augmented objective can be followed. Here, we propose a new Lagrangian approach leading to equivalent necessary optimality conditions in the form of Euler-Lagrange equations. Thus, the differential geometric structure (similar to classical Lagrangian dynamics) can be exploited in the framework of optimal control problems. In particular, the formulation enables the symplectic discretisation of the optimal control problem via variational integrators in a straightforward way.
AU - Leyendecker, Sigrid
AU - Maslovskaya, Sofya
AU - Ober-Blöbaum, Sina
AU - Almagro, Rodrigo T. Sato Martín de
AU - Szemenyei, Flóra Orsolya
ID - 53101
JF - Journal of Computational Dynamics
KW - Optimal control problem
KW - Lagrangian system
KW - Hamiltonian system
KW - Variations
KW - Pontryagin's maximum principle.
SN - 2158-2491
TI - A new Lagrangian approach to control affine systems with a quadratic Lagrange term
ER -
TY - CONF
AU - Dann, Andreas Peter
AU - Hermann, Ben
AU - Bodden, Eric
ID - 35083
TI - UpCy: Safely Updating Outdated Dependencies
ER -
TY - JOUR
AB - As in almost every other branch of science, the major advances in data
science and machine learning have also resulted in significant improvements
regarding the modeling and simulation of nonlinear dynamical systems. It is
nowadays possible to make accurate medium to long-term predictions of highly
complex systems such as the weather, the dynamics within a nuclear fusion
reactor, of disease models or the stock market in a very efficient manner. In
many cases, predictive methods are advertised to ultimately be useful for
control, as the control of high-dimensional nonlinear systems is an engineering
grand challenge with huge potential in areas such as clean and efficient energy
production, or the development of advanced medical devices. However, the
question of how to use a predictive model for control is often left unanswered
due to the associated challenges, namely a significantly higher system
complexity, the requirement of much larger data sets and an increased and often
problem-specific modeling effort. To solve these issues, we present a universal
framework (which we call QuaSiModO:
Quantization-Simulation-Modeling-Optimization) to transform arbitrary
predictive models into control systems and use them for feedback control. The
advantages of our approach are a linear increase in data requirements with
respect to the control dimension, performance guarantees that rely exclusively
on the accuracy of the predictive model, and only little prior knowledge
requirements in control theory to solve complex control problems. In particular
the latter point is of key importance to enable a large number of researchers
and practitioners to exploit the ever increasing capabilities of predictive
models for control in a straight-forward and systematic fashion.
AU - Peitz, Sebastian
AU - Bieker, Katharina
ID - 21199
JF - Automatica
TI - On the Universal Transformation of Data-Driven Models to Control Systems
VL - 149
ER -
TY - JOUR
AB - This paper presents a model of an energy system for a private household extended by a lifetime prognosis. The energy system was designed for fully covering the year-round energy demand of a private household on the basis of electricity generated by a photovoltaic (PV) system, using a hybrid energy storage system consisting of a hydrogen unit and a lithium-ion battery. Hydrogen is produced with a Proton Exchange Membrane (PEM) electrolyser by PV surplus during the summer months and then stored in a hydrogen tank. Mainly during winter, in terms of lack of PV energy, the hydrogen is converted back into electricity and heat by a fuel cell. The model was created in Matlab/Simulink and is based on real input data. Heat demand was also taken into account and is covered by a heat pump. The simulation period is a full year to account for the seasonality of energy production and demand. Due to high initial costs, the longevity of such an energy system is of vital interest. Therefore, this model was extended by a lifetime prediction in order to optimize the dimensioning with the aim of lifetime extension of a hydrogen-based energy system. Lifetime influencing factors were identified on the basis of a literature review and were integrated in the model. An extensive parameter study was performed to evaluate different dimensionings regarding the energy balance and the lifetime of the three components, electrolyser, fuel cell and lithium-ion battery. The results demonstrate the benefits of a holistic modelling approach and enable a design optimization regarding the use of resources, lifetime and self-sufficiency of the system
AU - Möller, Marius Claus
AU - Krauter, Stefan
ID - 35428
IS - 1
JF - Solar
SN - 2673-9941
TI - Dimensioning and Lifetime Prediction Model for a Hybrid, Hydrogen-Based Household PV Energy System Using Matlab/Simulink
VL - 3
ER -
TY - CHAP
AU - Ostsieker, Laura
AU - Biehler, Rolf
ID - 35697
SN - 1869-4918
T2 - Practice-Oriented Research in Tertiary Mathematics Education
TI - Supporting Students in Developing Adequate Concept Images and Definitions at University: The Case of the Convergence of Sequences
ER -