@inproceedings{20856, author = {{Camberg, Alan Adam and Erhart, Tobias and Tröster, Thomas}}, location = {{Seoul, South Korea}}, title = {{{Predicting fracture at non-isothermal forming conditions: A temperature dependent extension of the LS-DYNA GISSMO fracture indicator framework}}}, doi = {{10.13140/RG.2.2.23924.17288}}, year = {{2020}}, } @inbook{18014, author = {{El Mesaoudi-Paul, Adil and Weiß, Dimitri and Bengs, Viktor and Hüllermeier, Eyke and Tierney, Kevin}}, booktitle = {{Learning and Intelligent Optimization. LION 2020.}}, isbn = {{9783030535513}}, issn = {{0302-9743}}, pages = {{216 -- 232}}, publisher = {{Springer}}, title = {{{Pool-Based Realtime Algorithm Configuration: A Preselection Bandit Approach}}}, doi = {{10.1007/978-3-030-53552-0_22}}, volume = {{12096}}, year = {{2020}}, } @unpublished{18017, abstract = {{We consider an extension of the contextual multi-armed bandit problem, in which, instead of selecting a single alternative (arm), a learner is supposed to make a preselection in the form of a subset of alternatives. More specifically, in each iteration, the learner is presented a set of arms and a context, both described in terms of feature vectors. The task of the learner is to preselect $k$ of these arms, among which a final choice is made in a second step. In our setup, we assume that each arm has a latent (context-dependent) utility, and that feedback on a preselection is produced according to a Plackett-Luce model. We propose the CPPL algorithm, which is inspired by the well-known UCB algorithm, and evaluate this algorithm on synthetic and real data. In particular, we consider an online algorithm selection scenario, which served as a main motivation of our problem setting. Here, an instance (which defines the context) from a certain problem class (such as SAT) can be solved by different algorithms (the arms), but only $k$ of these algorithms can actually be run.}}, author = {{El Mesaoudi-Paul, Adil and Bengs, Viktor and Hüllermeier, Eyke}}, booktitle = {{arXiv:2002.04275}}, title = {{{Online Preselection with Context Information under the Plackett-Luce Model}}}, year = {{2020}}, } @inproceedings{18276, abstract = {{Algorithm selection (AS) deals with the automatic selection of an algorithm from a fixed set of candidate algorithms most suitable for a specific instance of an algorithmic problem class, where "suitability" often refers to an algorithm's runtime. Due to possibly extremely long runtimes of candidate algorithms, training data for algorithm selection models is usually generated under time constraints in the sense that not all algorithms are run to completion on all instances. Thus, training data usually comprises censored information, as the true runtime of algorithms timed out remains unknown. However, many standard AS approaches are not able to handle such information in a proper way. On the other side, survival analysis (SA) naturally supports censored data and offers appropriate ways to use such data for learning distributional models of algorithm runtime, as we demonstrate in this work. We leverage such models as a basis of a sophisticated decision-theoretic approach to algorithm selection, which we dub Run2Survive. Moreover, taking advantage of a framework of this kind, we advocate a risk-averse approach to algorithm selection, in which the avoidance of a timeout is given high priority. In an extensive experimental study with the standard benchmark ASlib, our approach is shown to be highly competitive and in many cases even superior to state-of-the-art AS approaches.}}, author = {{Tornede, Alexander and Wever, Marcel Dominik and Werner, Stefan and Mohr, Felix and Hüllermeier, Eyke}}, booktitle = {{ACML 2020}}, location = {{Bangkok, Thailand}}, title = {{{Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis}}}, year = {{2020}}, } @unpublished{16953, abstract = {{AbstractThe C-type lectin receptor langerin plays a vital role in the mammalian defense against invading pathogens. Its function hinges on the affinity to its co-factor Ca2+ which in turn is regulated by the pH. We studied the structural consequences of pro-tonating the allosteric pH-sensor histidine H294 by molecular dynamics simulations (total simulation time: about 120 μs) and Markov models. We discovered a mechanism in which the signal that the pH has dropped is transferred to the Ca2+-binding site without transferring the initial proton. Instead, protonation of H294 unlocks a conformation in which a protonated lysine side-chain forms a hydrogen bond with a Ca2+-coordinating aspartic acid. This destabilizes Ca2+ in the binding pocket, which we probed by steered molecular dynamics. After Ca2+-release, the proton is likely transferred to the aspartic acid and stabilized by a dyad with a nearby glutamic acid, triggering a conformational transition and thus preventing Ca2+-rebinding.}}, author = {{Joswig, Jan-O. and Anders, Jennifer and Zhang, Hengxi and Rademacher, Christoph and Keller, Bettina G.}}, booktitle = {{bioRxiv}}, keywords = {{pc2-ressources}}, title = {{{Molecular Mechanism of the pH-Dependent Calcium Affinity in Langerin}}}, year = {{2020}}, } @article{16956, author = {{Chatwell, René Spencer and Vrabec, Jadran}}, issn = {{0021-9606}}, journal = {{The Journal of Chemical Physics}}, keywords = {{pc2-ressources}}, title = {{{Bulk viscosity of liquid noble gases}}}, doi = {{10.1063/1.5142364}}, year = {{2020}}, } @article{16957, author = {{Fodor, Melinda A. and Ható, Zoltán and Kristóf, Tamás and Pósfai, Mihály}}, issn = {{0009-2541}}, journal = {{Chemical Geology}}, keywords = {{pc2-ressources}}, title = {{{The role of clay surfaces in the heterogeneous nucleation of calcite: Molecular dynamics simulations of cluster formation and attachment}}}, doi = {{10.1016/j.chemgeo.2020.119497}}, year = {{2020}}, } @article{15628, abstract = {{The three-dimensional (3D) crystal structures of the GAF3 domain of cyanobacteriochrome Slr1393 (Synechocystis PCC6803) carrying a phycocyanobilin chromophore could be solved in both 15-Z dark-adapted state, Pr, λmax = 649 nm, and 15-E photoproduct, Pg, λmax = 536 nm (resolution, 1.6 and 1.86 Å, respectively). The structural data allowed identifying the large spectral shift of the Pr-to-Pg conversion as resulting from an out-of-plane rotation of the chromophore’s peripheral rings and an outward movement of a short helix formed from a formerly unstructured loop. In addition, a third structure (2.1-Å resolution) starting from the photoproduct crystals allowed identification of elements that regulate the absorption maxima. In this peculiar form, generated during X-ray exposition, protein and chromophore conformation still resemble the photoproduct state, except for the D-ring already in 15-Z configuration and tilted out of plane akin the dark state. Due to its formation from the photoproduct, it might be considered an early conformational change initiating the parental state-recovering photocycle. The high quality and the distinct features of the three forms allowed for applying quantum-chemical calculations in the framework of multiscale modeling to rationalize the absorption maxima changes. A systematic analysis of the PCB chromophore in the presence and absence of the protein environment showed that the direct electrostatic effect is negligible on the spectral tuning. However, the protein forces the outer pyrrole rings of the chromophore to deviate from coplanarity, which is identified as the dominating factor for the color regulation.}}, author = {{Xu, Xiuling and Port, Astrid and Wiebeler, Christian and Zhao, Kai-Hong and Schapiro, Igor and Gärtner, Wolfgang}}, issn = {{0027-8424}}, journal = {{Proceedings of the National Academy of Sciences}}, title = {{{Structural Elements Regulating the Photochromicity in a Cyanobacteriochrome}}}, doi = {{10.1073/pnas.1910208117}}, year = {{2020}}, } @inproceedings{15629, abstract = {{In multi-label classification (MLC), each instance is associated with a set of class labels, in contrast to standard classification where an instance is assigned a single label. Binary relevance (BR) learning, which reduces a multi-label to a set of binary classification problems, one per label, is arguably the most straight-forward approach to MLC. In spite of its simplicity, BR proved to be competitive to more sophisticated MLC methods, and still achieves state-of-the-art performance for many loss functions. Somewhat surprisingly, the optimal choice of the base learner for tackling the binary classification problems has received very little attention so far. Taking advantage of the label independence assumption inherent to BR, we propose a label-wise base learner selection method optimizing label-wise macro averaged performance measures. In an extensive experimental evaluation, we find that or approach, called LiBRe, can significantly improve generalization performance.}}, author = {{Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}}, location = {{Konstanz, Germany}}, publisher = {{Springer}}, title = {{{LiBRe: Label-Wise Selection of Base Learners in Binary Relevance for Multi-Label Classification}}}, year = {{2020}}, } @article{15025, abstract = {{In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available.}}, author = {{Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}}, journal = {{Evolutionary Computation}}, number = {{2}}, pages = {{165–193}}, publisher = {{MIT Press Journals}}, title = {{{Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}}}, doi = {{10.1162/evco_a_00266}}, volume = {{28}}, year = {{2020}}, } @inproceedings{15264, author = {{Johannesmann, Sarah and Becker, Sebastian and Webersen, Manuel and Henning, Bernd}}, booktitle = {{SMSI 2020 - Measurement Science}}, isbn = {{978-3-9819376-2-6}}, location = {{Nuremberg}}, title = {{{Determination of Murnaghan constants of plate-shaped polymers under uniaxial tensile load}}}, doi = {{10.5162/SMSI2020/D6.1}}, year = {{2020}}, } @inproceedings{16207, author = {{Heine, Jens and Wecker, Christian and Kenig, Eugeny and Bart, Hans-Joerg}}, publisher = {{Jahrestreffen der ProcessNet-Fachgruppe Extraktion}}, title = {{{Stofftransportmessung am ruhenden und bewegten Einzeltropfen}}}, year = {{2020}}, } @inproceedings{16208, author = {{Wecker, Christian and Schulz, Andreas and Heine, Jens and Bart, Hans-Joerg and Kenig, Eugeny}}, publisher = {{Jahrestreffen der ProcessNet-Fachgruppe Extraktion}}, title = {{{CFD-basierte Untersuchung stofftransportinduzierter Marangoni-konvektion in Flüssig-Flüssig-Systemen}}}, year = {{2020}}, } @article{16290, abstract = {{The control of complex systems is of critical importance in many branches of science, engineering, and industry, many of which are governed by nonlinear partial differential equations. Controlling an unsteady fluid flow is particularly important, as flow control is a key enabler for technologies in energy (e.g., wind, tidal, and combustion), transportation (e.g., planes, trains, and automobiles), security (e.g., tracking airborne contamination), and health (e.g., artificial hearts and artificial respiration). However, the high-dimensional, nonlinear, and multi-scale dynamics make real-time feedback control infeasible. Fortunately, these high- dimensional systems exhibit dominant, low-dimensional patterns of activity that can be exploited for effective control in the sense that knowledge of the entire state of a system is not required. Advances in machine learning have the potential to revolutionize flow control given its ability to extract principled, low-rank feature spaces characterizing such complex systems.We present a novel deep learning modelpredictive control framework that exploits low-rank features of the flow in order to achieve considerable improvements to control performance. Instead of predicting the entire fluid state, we use a recurrent neural network (RNN) to accurately predict the control relevant quantities of the system, which are then embedded into an MPC framework to construct a feedback loop. In order to lower the data requirements and to improve the prediction accuracy and thus the control performance, incoming sensor data are used to update the RNN online. The results are validated using varying fluid flow examples of increasing complexity.}}, author = {{Bieker, Katharina and Peitz, Sebastian and Brunton, Steven L. and Kutz, J. Nathan and Dellnitz, Michael}}, issn = {{0935-4964}}, journal = {{Theoretical and Computational Fluid Dynamics}}, pages = {{577–591}}, title = {{{Deep model predictive flow control with limited sensor data and online learning}}}, doi = {{10.1007/s00162-020-00520-4}}, volume = {{34}}, year = {{2020}}, } @inproceedings{16307, author = {{Wecker, Christian and Hoppe, Anna and Schulz, Andreas and Heine, Jens and Bart, Hans-Jörg and Kenig, Eugeny}}, publisher = {{Jahrestreffen der ProcessNet-Fachgruppe Wärme- und Stofftransport}}, title = {{{Numerische Untersuchungen des Stofftransports in Flüssig-Flüssig-Systemen unter Berücksichtigung der Marangonikonvektion}}}, year = {{2020}}, } @inproceedings{16308, author = {{Schulz, Andreas and Wecker, Christian and Kenig, Eugeny}}, publisher = {{Jahrestreffen der ProcessNet-Fachgruppe Wärme- und Stofftransport}}, title = {{{Ein PLIC-basierter Ansatz zur Erfassung des Stoffübergangs an bewegten Phasengrenzflächen}}}, year = {{2020}}, } @inproceedings{16930, author = {{Tinkloh, Steffen Rainer and Wu, Tao and Tröster, Thomas and Niendorf, Thomas}}, booktitle = {{Proceedings of the 4th International Conference Hybrid 2020 Materials and Structures}}, location = {{Web-Conference, Germany}}, title = {{{Numerical investigation of the hole-drilling method applied to intrinsic manufactured metal-CFRP hybrids}}}, year = {{2020}}, } @article{32246, abstract = {{

State-of-the-art methods in materials science such as artificial intelligence and data-driven techniques advance the investigation of photovoltaic materials.

}}, author = {{Mirhosseini, Hossein and Kormath Madam Raghupathy, Ramya and Sahoo, Sudhir K. and Wiebeler, Hendrik and Chugh, Manjusha and Kühne, Thomas D.}}, issn = {{1463-9076}}, journal = {{Physical Chemistry Chemical Physics}}, keywords = {{Physical and Theoretical Chemistry, General Physics and Astronomy}}, number = {{46}}, pages = {{26682--26701}}, publisher = {{Royal Society of Chemistry (RSC)}}, title = {{{In silico investigation of Cu(In,Ga)Se2-based solar cells}}}, doi = {{10.1039/d0cp04712k}}, volume = {{22}}, year = {{2020}}, } @unpublished{32242, abstract = {{We consider a resource-aware variant of the classical multi-armed bandit problem: In each round, the learner selects an arm and determines a resource limit. It then observes a corresponding (random) reward, provided the (random) amount of consumed resources remains below the limit. Otherwise, the observation is censored, i.e., no reward is obtained. For this problem setting, we introduce a measure of regret, which incorporates the actual amount of allocated resources of each learning round as well as the optimality of realizable rewards. Thus, to minimize regret, the learner needs to set a resource limit and choose an arm in such a way that the chance to realize a high reward within the predefined resource limit is high, while the resource limit itself should be kept as low as possible. We derive the theoretical lower bound on the cumulative regret and propose a learning algorithm having a regret upper bound that matches the lower bound. In a simulation study, we show that our learning algorithm outperforms straightforward extensions of standard multi-armed bandit algorithms.}}, author = {{Bengs, Viktor and Hüllermeier, Eyke}}, booktitle = {{arXiv:2011.00813}}, title = {{{Multi-Armed Bandits with Censored Consumption of Resources}}}, year = {{2020}}, } @article{19844, abstract = {{The defect-electronic properties of {112} microfaceted surfaces of epitaxially grown CuInSe2 thin films are investigated by scanning tunneling spectroscopy and photoelectron spectroscopy techniques after various surface treatments. The intrinsic CuInSe2 surface is found to be largely passivated in terms of electronic defect levels in the band-gap region. However, surface oxidation leads to an overall high density of defect levels in conjunction with a considerable net surface dipole, which persists even after oxide removal. Yet, a subsequent annealing under vacuum restores the initial condition. Such oxidation/reduction cycles are reversible for many times providing robust control of the surface and interface properties in these materials. Based on ab initio simulations, a mechanism where oxygen dissociatively adsorbs and subsequently diffuses to a subsurface site is proposed as the initial step of the observed dipole formation. Our results emphasize the relevance of oxidation-induced dipole effects at the thin film surface and provide a comprehensive understanding toward passivation strategies of these surfaces.}}, author = {{Elizabeth, Amala and Sahoo, Sudhir K. and Lockhorn, David and Timmer, Alexander and Aghdassi, Nabi and Zacharias, Helmut and Kühne, Thomas and Siebentritt, Susanne and Mirhosseini, Hossein and Mönig, Harry}}, journal = {{Phys. Rev. Materials}}, pages = {{063401}}, publisher = {{American Physical Society}}, title = {{{ Oxidation/reduction cycles and their reversible effect on the dipole formation at CuInSe2 surfaces}}}, doi = {{10.1103/PhysRevMaterials.4.063401}}, volume = {{4}}, year = {{2020}}, }