@misc{HerzogHoenigSchroederPreikschatetal.2019, author = {Herzog, Benedict and H{\"o}nig, Timo and Schr{\"o}der-Preikschat, Wolfgang and Plauth, Max and K{\"o}hler, Sven and Polze, Andreas}, title = {Bridging the Gap}, series = {e-Energy '19: Proceedings of the Tenth ACM International Conference on Future Energy Systems}, journal = {e-Energy '19: Proceedings of the Tenth ACM International Conference on Future Energy Systems}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6671-7}, doi = {10.1145/3307772.3330176}, pages = {428 -- 430}, year = {2019}, abstract = {The recent restructuring of the electricity grid (i.e., smart grid) introduces a number of challenges for today's large-scale computing systems. To operate reliable and efficient, computing systems must adhere not only to technical limits (i.e., thermal constraints) but they must also reduce operating costs, for example, by increasing their energy efficiency. Efforts to improve the energy efficiency, however, are often hampered by inflexible software components that hardly adapt to underlying hardware characteristics. In this paper, we propose an approach to bridge the gap between inflexible software and heterogeneous hardware architectures. Our proposal introduces adaptive software components that dynamically adapt to heterogeneous processing units (i.e., accelerators) during runtime to improve the energy efficiency of computing systems.}, language = {en} } @incollection{KohlerPoege2015, author = {Kohler, Ulrich and P{\"o}ge, Andreas}, title = {Optimal Matching}, series = {Methoden-Lexikon f{\"u}r die Sozialwissenschaften}, booktitle = {Methoden-Lexikon f{\"u}r die Sozialwissenschaften}, editor = {Diaz-Bone, Rainer and Weischer, Christoph}, publisher = {Springer}, address = {Wiesbaden}, isbn = {978-3-531-16629-2}, doi = {10.1007/978-3-531-18889-8_15}, pages = {299 -- 299}, year = {2015}, language = {de} } @article{KoehlerDoenchOttetal.2009, author = {K{\"o}hler, Ralf and Doench, Ingo and Ott, Patrick and Laschewsky, Andr{\´e} and Fery, Andreas and Krastev, Rumen}, title = {Neutron reflectometry study of swelling of polyelectrolyte multilayers in water vapors : influence of charge density of the polycation}, issn = {0743-7463}, doi = {10.1021/La901508w}, year = {2009}, abstract = {We studied the swelling of polyelectrolyte (PE) multilayers (PEM) in water (H2O) vapors. The PEM were made from polyanion poly(styrene sulfonate) (PSS) and polycation poly(diallyldimethylammonium chloride)-N-methyl-N-vinylacetamide (pDADMAC-NMVA). While PSS is a fully charged polyanion, pDADMAC-NMVA is a random copolymer made of charged pDADMAC and uncharged NMVA monomer units. Variation of the relative amount of these two units allows for controlling the charge density of pDADMAC-NMVA. The degree of swelling was studied as it function of the relative humidity in the experimental chamber (respectively water concentration in the gas phase) for PEM prepared from PSS and pDADMAC-NMVA with their different charge densities - 100\%, 89\% and 75\%. The films were prepared by means of spraying technique and consisted of six PE couples-PSS/pDADMAC-NMVA. Neutron reflectometry was applied as main tool to observe the swelling process. The technique allows to obtain in a single experiment information about film thickness and amount of water in the film. The experiments were complemented with AFM measurements to obtain the thickness of the films. It was found that the Film thickness increases when the charge density of the polycation decreases. The swelling of the PEM increases with the relative humidity and it depends on the charge density of pDADMAC-NMVA. The swelling behavior is 2-fold, splitting up in a charge dependent mode with relatively little volume increase, and a second mode With high volume expansion, which is independent from charge density of PEM. The "swelling transition" occurs for all samples at a relative humidity about 60\% and a volume increase of ca. 20\%. The results were interpreted according to the Flory-Huggins theory which assumes a phase separation in PEM network at higher water contents.}, language = {en} } @phdthesis{Koehler2009, author = {K{\"o}hler, Andreas}, title = {Recognition and investigation of temporal patterns in seismic wavefields using unsupervised learning techniques}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-29702}, school = {Universit{\"a}t Potsdam}, year = {2009}, abstract = {Modern acquisition of seismic data on receiver networks worldwide produces an increasing amount of continuous wavefield recordings. Hence, in addition to manual data inspection, seismogram interpretation requires new processing utilities for event detection, signal classification and data visualization. Various machine learning algorithms, which can be adapted to seismological problems, have been suggested in the field of pattern recognition. This can be done either by means of supervised learning using manually defined training data or by unsupervised clustering and visualization. The latter allows the recognition of wavefield patterns, such as short-term transients and long-term variations, with a minimum of domain knowledge. Besides classical earthquake seismology, investigations of temporal patterns in seismic data also concern novel approaches such as noise cross-correlation or ambient seismic vibration analysis in general, which have moved into focus within the last decade. In order to find records suitable for the respective approach or simply for quality control, unsupervised preprocessing becomes important and valuable for large data sets. Machine learning techniques require the parametrization of the data using feature vectors. Applied to seismic recordings, wavefield properties have to be computed from the raw seismograms. For an unsupervised approach, all potential wavefield features have to be considered to reduce subjectivity to a minimum. Furthermore, automatic dimensionality reduction, i.e. feature selection, is required in order to decrease computational cost, enhance interpretability and improve discriminative power. This study presents an unsupervised feature selection and learning approach for the discovery, imaging and interpretation of significant temporal patterns in seismic single-station or network recordings. In particular, techniques permitting an intuitive, quickly interpretable and concise overview of available records are suggested. For this purpose, the data is parametrized by real-valued feature vectors for short time windows using standard seismic analysis tools as feature generation methods, such as frequency-wavenumber, polarization, and spectral analysis. The choice of the time window length is dependent on the expected durations of patterns to be recognized or discriminated. We use Self-Organizing Maps (SOMs) for a data-driven feature selection, visualization and clustering procedure, which is particularly suitable for high-dimensional data sets. Using synthetics composed of Rayleigh and Love waves and three different types of real-world data sets, we show the robustness and reliability of our unsupervised learning approach with respect to the effect of algorithm parameters and data set properties. Furthermore, we approve the capability of the clustering and imaging techniques. For all data, we find improved discriminative power of our feature selection procedure compared to feature subsets manually selected from individual wavefield parametrization methods. In particular, enhanced performance is observed compared to the most favorable individual feature generation method, which is found to be the frequency spectrum. The method is applied to regional earthquake records at the European Broadband Network with the aim to define suitable features for earthquake detection and seismic phase classification. For the latter, we find that a combination of spectral and polarization features favor S wave detection at a single receiver. However, SOM-based visualization of phase discrimination shows that clustering applied to the records of two stations only allows onset or P wave detection, respectively. In order to improve the discrimination of S waves on receiver networks, we recommend to consider additionally the temporal context of feature vectors. The application to continuous recordings of seismicity close to an active volcano (Mount Merapi, Java, Indonesia) shows that two typical volcano-seismic events (VTB and Guguran) can be detected and distinguished by clustering. In contrast, so-called MP events cannot be discriminated. Comparable results are obtained for selected features and recognition rates regarding a previously implemented supervised classification system. Finally, we test the reliability of wavefield clustering to improve common ambient vibration analysis methods such as estimation of dispersion curves and horizontal to vertical spectral ratios. It is found, that in general, the identified short- and long-term patterns have no significant impact on those estimates. However, for individual sites, effects of local sources can be identified. Leaving out the corresponding clusters, yields reduced uncertainties or allows for improving estimation of dispersion curves.}, language = {en} } @book{SchubarthSeidelMauermeisteretal.2017, author = {Schubarth, Wilfried and Seidel, Andreas and Mauermeister, Sylvi and Fuhrmann, Michaela and Faaß, Marcel and Niproschke, Saskia and Zylla, Birgitta and Ulbricht, Juliane and Schulze-Reichelt, Friederike and K{\"o}hler, Anke and Erdmann, Melinda and Ratzlaff, Olaf and Kottmann, Andrea and Unger, Martin and Dibiasi, Anna and Grzywacz, Małgorzata and Miłkowska, Grażyna and Piorunek, Magdalena and Sałaciński, Lech and Grecmanov{\´a}, Helena and Dopita, Miroslav and Kantorov{\´a}, Jana and Wippermann, Melanie and Skopalov{\´a}, Jitka and V'junova, Natalja Ivanovna and Ivanova, Olga Anatol'evna and Apostolow, Benjamin}, title = {Studium nach Bologna}, series = {Potsdamer Beitr{\"a}ge zur Hochschulforschung}, journal = {Potsdamer Beitr{\"a}ge zur Hochschulforschung}, number = {3}, editor = {Schubarth, Wilfried and Mauermeister, Sylvi and Seidel, Andreas}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-399-2}, issn = {2192-1075}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-103998}, publisher = {Universit{\"a}t Potsdam}, pages = {302}, year = {2017}, abstract = {Ziel des vorliegenden dritten Bandes der Potsdamer Beitr{\"a}ge zur Hochschulforschung ist es, ausgew{\"a}hlte Aspekte der Hochschuldebatte um Studium und Lehre zu beleuchten und mit empirischen Befunden zu vertiefen. Im ­Fokus stehen solche aktuellen Debatten wie die Gestaltung des Studieneingangs, die Erh{\"o}hung der Besch{\"a}ftigungsbef{\"a}higung, die Qualit{\"a}t der Praktika sowie Probleme der Lehrerbildung. Dabei wird die Hochschuldebatte in Deutschland durch einschl{\"a}gige Beitr{\"a}ge aus anderen, west- und osteurop{\"a}ischen L{\"a}ndern erweitert. Die Reihe versteht sich als Forum verschiedener Akteure aus der Hochschulforschung, die die Diskussion zur Qualit{\"a}tsentwicklung in Lehre und Studium mit ihren Impulsen aus Analysen und empirischen Ergebnissen bereichern sollen. Der Band richtet sich an alle, die sich f{\"u}r die Entwicklung an Hochschulen interessieren.}, language = {de} } @article{PirliHainzlSchweitzeretal.2018, author = {Pirli, Myrto and Hainzl, Sebastian and Schweitzer, Johannes and K{\"o}hler, Andreas and Dahm, Torsten}, title = {Localised thickening and grounding of an Antarctic ice shelf from tidal triggering and sizing of cryoseismicity}, series = {Earth \& planetary science letters}, volume = {503}, journal = {Earth \& planetary science letters}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0012-821X}, doi = {10.1016/j.epsl.2018.09.024}, pages = {78 -- 87}, year = {2018}, abstract = {We observe remarkably periodic patterns of seismicity rates and magnitudes at the Fimbul Ice Shelf, East Antarctica, correlating with the cycles of the ocean tide. Our analysis covers 19 years of continuous seismic recordings from Antarctic broadband stations. Seismicity commences abruptly during austral summer 2011 at a location near the ocean front in a shallow water region. Dozens of highly repetitive events occur in semi-diurnal cycles, with magnitudes and rates fluctuating steadily with the tide. In contrast to the common unpredictability of earthquake magnitudes, the event magnitudes show deterministic trends within single cycles and strong correlations with spring tides and tide height. The events occur quasi-periodically and the highly constrained event sources migrate landwards during rising tide. We show that a simple, mechanical model can explain most of the observations. Our model assumes stick-slip motion on a patch of grounded ice shelf, which is forced by the variations of the ocean-tide height and ice flow. The well fitted observations give new insights into the general process of frictional triggering of earthquakes, while providing independent evidence of variations in ice shelf thickness and grounding.}, language = {en} }