Parametric shortest-path algorithms via tropical geometry

We study parameterized versions of classical algorithms for computing shortest-path trees. This is most easily expressed in terms of tropical geometry. Applications include shortest paths in traffic networks with variable link travel times.Comment: 24 pages and 8 figure

Real-time determination of laser beam quality by modal decomposition

We present a real-time method to determine the beam propagation ratio M2 of laser beams. The all-optical measurement of modal amplitudes yields M2 parameters conform to the ISO standard method. The experimental technique is simple and fast, which allows to investigate laser beams under conditions inaccessible to other methods.Comment: 8 pages, 4 figures, published in Optics Expres

Untersuchung der Evolution von Konvektionsstrukturen bei Kaltluftausbrüchen mit Hilfe eines parallelisierten Grobstrukturmodells

[no abstract

ORCA-SPOT: An Automatic Killer Whale Sound Detection Toolkit Using Deep Learning

Large bioacoustic archives of wild animals are an important source to identify reappearing communication patterns, which can then be related to recurring behavioral patterns to advance the current understanding of intra-specific communication of non-human animals. A main challenge remains that most large-scale bioacoustic archives contain only a small percentage of animal vocalizations and a large amount of environmental noise, which makes it extremely difficult to manually retrieve sufficient vocalizations for further analysis – particularly important for species with advanced social systems and complex vocalizations. In this study deep neural networks were trained on 11,509 killer whale (Orcinus orca) signals and 34,848 noise segments. The resulting toolkit ORCA-SPOT was tested on a large-scale bioacoustic repository – the Orchive – comprising roughly 19,000 hours of killer whale underwater recordings. An automated segmentation of the entire Orchive recordings (about 2.2 years) took approximately 8 days. It achieved a time-based precision or positive-predictive-value (PPV) of 93.2% and an area-under-the-curve (AUC) of 0.9523. This approach enables an automated annotation procedure of large bioacoustics databases to extract killer whale sounds, which are essential for subsequent identification of significant communication patterns. The code will be publicly available in October 2019 to support the application of deep learning to bioaoucstic research. ORCA-SPOT can be adapted to other animal species

STINHO - micro-a scale measurements and LES modelling

A micrometeorological field experiment within the scope of the STINHO-project (STructure of turbulent transport under INHOmogeneous conditions) was performed at the boundary layer research field of the Lindenberg Meteorological Observatory in the summer of 2002 to investigate the interaction of an inhomogeneously heated surface with the turbulent atmosphere. The data of this field experiment (STINHO-II, July 2002, RAABE ET AL., 2005) were used to initialize a large-eddy simulation model that has been adjusted to the area under investigation. The accuracy of the calculations is supported using analytical models. The LES initialization conditions are adapted to reach an agreement between observed as well as calculated parameters, e.g. the increase of the near surface air temperature or the time dependent rise of the height of the convective boundary layer (CBL) in the first hour after sun rise. A direct comparison between observed and calculated parameters of the CBL-development is possible for averaged data. The detailed spatial and temporal structure of the investigated morning heating process can only be compared using statistical parameter.Im Rahmen des STINHO Projektes (Struktur des turbulenten Transportes über inhomogener Unterlage) wurde im Sommer 2002 auf dem Gelände des Grenzschichtmessfeldes des Meteorologischen Observatoriums Lindenberg ein mikrometeorologisches Feldexperiment durchgeführt, um die Wechselwirkung einer sich heterogen erwärmenden Erdoberfläche mit der turbulenten Atmosphäre zu untersuchen. Die Daten aus einem Experiment (STINHO-II, Juli 2002, RAABE ET AL., 2005) werden zur Initialisierung eines an die Bedingungen des Untersuchungsgebietes angepassten Large-Eddy Simulationsmodells verwendet und mit Beobachtungsdaten verglichen. Die Effizienz der numerischen Simulationen wird durch die Verwendung eines analytischen Modells unterstützt, um eine Konsistenz zwischen Initialisierungsbedingungen und den beobachteten als auch den berechneten Parametern (bodennaher Lufttemperaturanstieg oder die Zunahme der Höhe der konvektiven Grenzschicht) in der ersten Stunde nach Sonnenaufgang herzustellen. Ein Vergleich zwischen beobachteten und berechneten Parametern der konvektiven Grenzschichtentwicklung ist nur für gemittelte Daten möglich. Die räumliche und zeitliche Darstellung der Struktur eines solchen Erwärmungsprozesses kann nur geprüft werden, indem statistische Parameter verwendet werden