TY - CONF
AU - Dreiling, Dmitrij
AU - Feldmann, Nadine
AU - Henning, Bernd
ID - 12952
KW - piezoelectric materials
KW - piezoelectric properties
KW - DC bias field
KW - non-linear material parameters
TI - A DC bias approach to the characterisation of non-linear material parameters of piezoelectric ceramics
ER -
TY - GEN
AU - Wecker, Christian
AU - Schulz, Andreas
AU - Heine, Jens
AU - Bart, Hans-Joerg
AU - Kenig, Eugeny
ID - 13397
TI - Stofftransport und Fluidmechanik bei der Tropfenbildung unter Berücksichtigung von Marangonikonvektion mittels CFD
ER -
TY - JOUR
AU - Bocchini, Adriana
AU - Neufeld, Sergej
AU - Gerstmann, Uwe
AU - Schmidt, Wolf Gero
ID - 13429
JF - Journal of Physics: Condensed Matter
SN - 0953-8984
TI - Oxygen and potassium vacancies in KTP calculated from first principles
ER -
TY - JOUR
AU - Dridger, A.
AU - Caylak, I.
AU - Mahnken, R.
AU - Penner, E.
ID - 13431
JF - Safety and Reliability
SN - 0961-7353
TI - "A possibilistic finite element method for sparse data"
ER -
TY - CHAP
AU - Camberg, Alan Adam
AU - Stratmann, Ina
AU - Tröster, Thomas
ID - 13436
SN - 2524-4787
T2 - Technologies for economical and functional lightweight design
TI - TAILORED STACKED HYBRIDS – AN OPTIMIZATION-BASED APPROACH IN MATERIAL DESIGN FOR FURTHER IMPROVEMENT IN LIGHTWEIGHT CAR BODY STRUCTURES
ER -
TY - CONF
AB - This work considers the problem of control and resource allocation in networked
systems. To this end, we present DIRA a Deep reinforcement learning based Iterative Resource
Allocation algorithm, which is scalable and control-aware. Our algorithm is tailored towards
large-scale problems where control and scheduling need to act jointly to optimize performance.
DIRA can be used to schedule general time-domain optimization based controllers. In the present
work, we focus on control designs based on suitably adapted linear quadratic regulators. We
apply our algorithm to networked systems with correlated fading communication channels. Our
simulations show that DIRA scales well to large scheduling problems.
AU - Redder, Adrian
AU - Ramaswamy, Arunselvan
AU - Quevedo, Daniel
ID - 13443
KW - Networked control systems
KW - deep reinforcement learning
KW - large-scale systems
KW - resource scheduling
KW - stochastic control
T2 - Proceedings of the 8th IFAC Workshop on Distributed Estimation and Control in Networked Systems
TI - Deep reinforcement learning for scheduling in large-scale networked control systems
ER -
TY - GEN
AU - Schiller, Leo
ID - 13450
TI - Mechanismen zur Aggregation der Meinungen einer Crowd - Ein klassifizierender Literaturüberblick
ER -
TY - JOUR
AU - Garnefeld, Ina
AU - Eggert, Andreas
AU - Husemann-Kopetzky, Markus
AU - Boehm, Eva
ID - 13455
IS - 4
JF - Journal of the Academy of Marketing Science
TI - Exploring the link between payment schemes and customer fraud: a mental accounting perspective
VL - 47
ER -
TY - CHAP
AU - Sommer, Christoph
AU - Eckhoff, David
AU - Brummer, Alexander
AU - Buse, Dominik S.
AU - Hagenauer, Florian
AU - Joerer, Stefan
AU - Segata, Michele
ID - 12072
SN - 2522-8595
T2 - Recent Advances in Network Simulation
TI - Veins: The Open Source Vehicular Network Simulation Framework
ER -
TY - GEN
AB - Die Komplexität von Steuersystemen gewinnt in der Debatte um den internationalen Steuerwettbewerb zunehmend an Bedeutung. Im vorliegenden Beitrag erfolgt, basierend auf den Daten, die dem Tax Complexity Index (www.taxcomplexity.org) zugrunde liegen, eine umfassende Gegenüberstellung der Komplexität der Steuersysteme von Deutschland und Öster-reich unter Berücksichtigung der Mittelwerte aller Länder. Die Steuergesetze weisen sowohl in Deutschland als auch in Österreich einen verhältnismäßig hohen Grad an Komplexität auf. Bei den steuerlichen Rahmenbedingungen fällt der Grad an Komplexität in beiden Ländern dagegen niedrig aus, wobei Österreich im Durchschnitt weniger komplex ist als Deutschland.
AU - Hoppe, Thomas
AU - Rechbauer, Martina
AU - Sturm, Susann
ID - 12077
TI - Steuerkomplexität im Vergleich zwischen Deutschland und Österreich – Eine Analyse des Status quo
ER -
TY - JOUR
AU - Schneider, Martin
AU - Iseke, Anja
AU - Pull, Kerstin
ID - 13246
JF - The International Journal of Human Resource Management
SN - 0958-5192
TI - The gender pay gap in European executive boards: the role of executives’ pathway into the board
ER -
TY - JOUR
AU - Hannes, Wolf-Rüdiger
AU - Meier, Torsten
ID - 13284
IS - 12
JF - Physical Review B
SN - 2469-9950
TI - Higher-order contributions and nonperturbative effects in the nondegenerate nonlinear optical absorption of semiconductors using a two-band model
VL - 99
ER -
TY - GEN
AB - Vortices are topological objects carrying quantized orbital angular momentum,
also known as topological charge, and have been widely studied in many physical
systems for their applicability in information storage and processing. Here we
focus on vortices in semiconductor microcavity polariton condensates. In
systems with spin degree of freedom the elementary excitations are so called
half-vortices. A half-vortex carries a quantum circulation only in one of the
two spin components. It has lower energy in comparison with a full-vortex and,
importantly, has a circularly polarized density peak in the vortex core region,
while elsewhere the condensate is linearly polarized. We demonstrate the
spontaneous formation of localized half-vortices in spinor polariton
condensates, non-resonantly excited by a linearly polarized ring pump. The
pseudospin structure of the condensate includes a TE-TM splitting leading to
effective spin-orbit coupling, resulting in solutions with broken cylindrical
symmetry. The cross-interaction between different spin components provides an
efficient method to realize optical vortex core switching between left- and
right-circularly polarized states. This switching can be easily detected by
measuring the polarization resolved intensity in the vortex core region and it
can also be applied to higher order half-vortex states.
AU - Pukrop, Matthias
AU - Schumacher, Stefan
AU - Ma, Xuekai
ID - 13335
T2 - arXiv:1907.10974
TI - Optical Vortex Core Switching in Spinor Polariton Condensates
ER -
TY - GEN
AB - <div>
<div>
<div>
<p>Molecular doping in conjugated polymers is a crucial process for their application in organic
photovoltaics and optoelectronics. In the present work we theoretically investigate p-type molecu-
lar doping in a series of (poly[2,6-(4,4-bis(2-ethylhexyl)-4H-cyclopenta[2,1-b;3,4-b”]dithiophene)-alt-
4,7-(2,1,3-benzothiadiazole)] (PCPDT-BT) conjugated oligomers with different lengths and three
widely-used dopants with different electron affinities, namely F4TCNQ, F6TCNNQ, and CN6-CP.
We study in detail the molecular geometry of possible oligomer-dopant complexes and its influence
on the doping mechanisms and electronic system properties. We find that the mechanisms of dop-
ing and charge transfer observed sensitively depend on the specific geometry of the oligomer-dopant
complexes. For a given complex different geometries may exist, some of which show transfer of
an entire electron from the oligomer chain onto the dopant molecule resulting in an integer-charge
transfer complex, leaving the system in a ground state with broken spin symmetry. In other ge-
ometries merely hybridization of oligomer and dopant frontier orbitals occurs with partial charge
transfer but spin-symmetric ground state. Considering the resulting electronic density of states both
cases may well contribute to an increased electrical conductivity of corresponding film samples while
the underlying physical mechanisms are entirely different.
</p>
</div>
</div>
</div>
AU - Dong, Chuanding
AU - Schumacher, Stefan
ID - 13347
TI - Molecular Doping of PCPDT-BT Copolymers: Comparison of Molecular Complexes with and Without Integer Charge Transfer
ER -
TY - CONF
AB - In this paper, we first outline a Hypothetical Learning Trajectory (HLT), which aims at a formal understanding of the rules for manipulating integers. The HLT is based on task formats, which promote algebraic thinking in terms of generalizing rules from the analysis of patterns and should be familiar to students from their mathematics education experiences in elementary school. Second, we analyze two students' actual learning process based on Peircean semiotics. The analysis shows that the actual learning process diverges from the hypothesized learning process in that the students do not relate the different levels of the diagrams in a way that allows them to extrapolate the rule for the subtraction of negative numbers. Based on this finding, we point out consequences for the design of the tasks.
AU - Schumacher, Jan
AU - Rezat, Sebastian
ED - Jankvist, Uffe Thomas
ED - Van den Heuvel-Panhuizen, Marja
ED - Veldhuis, Michiel
ID - 13107
KW - diagrammatic reasoning
KW - hypothetical learning trajectory
KW - induction extrapolatory method
KW - integers
KW - negative numbers
KW - permanence principle
KW - semiotics
T2 - Proceedings of the Eleventh Congress of the European Society for Research in Mathematics Education (CERME11, February 6 – 10, 2019)
TI - A Hypothetical Learning Trajectory for the Learning of the Rules for Manipulating Integers
ER -
TY - GEN
AB - Many basic properties in Tutte's flow theory for unsigned graphs do not have
their counterparts for signed graphs. However, signed graphs without long
barbells in many ways behave like unsigned graphs from the point view of flows.
In this paper, we study whether some basic properties in Tutte's flow theory
remain valid for this family of signed graphs. Specifically let $(G,\sigma)$ be
a flow-admissible signed graph without long barbells. We show that it admits a
nowhere-zero $6$-flow and that it admits a nowhere-zero modulo $k$-flow if and
only if it admits a nowhere-zero integer $k$-flow for each integer $k\geq 3$
and $k \not = 4$. We also show that each nowhere-zero positive integer $k$-flow
of $(G,\sigma)$ can be expressed as the sum of some $2$-flows. For general
graphs, we show that every nowhere-zero $\frac{p}{q}$-flow can be normalized in
such a way, that each flow value is a multiple of $\frac{1}{2q}$. As a
consequence we prove the equality of the integer flow number and the ceiling of
the circular flow number for flow-admissible signed graphs without long
barbells.
AU - Lu, You
AU - Luo, Rong
AU - Schubert, Michael
AU - Steffen, Eckhard
AU - Zhang, Cun-Quan
ID - 13114
T2 - arXiv:1908.11004
TI - Flows on signed graphs without long barbells
ER -
TY - JOUR
AU - Breitmayer, Bastian
AU - Hasso, Tim
AU - Pelster, Matthias
ID - 13121
JF - Economics Letters
SN - 0165-1765
TI - Culture and the disposition effect
VL - 184
ER -
TY - THES
AU - Khaluf, Lial
ID - 13126
TI - Organic Programming of Dynamic Real-Time Applications
ER -
TY - CONF
AU - Feldkord, Björn
AU - Knollmann, Till
AU - Malatyali, Manuel
AU - Meyer auf der Heide, Friedhelm
ID - 12870
T2 - Proceedings of the 17th Workshop on Approximation and Online Algorithms (WAOA)
TI - Managing Multiple Mobile Resources
ER -
TY - CONF
AB - Signal dereverberation using the Weighted Prediction Error (WPE) method has been proven to be an effective means to raise the accuracy of far-field speech recognition. First proposed as an iterative algorithm, follow-up works have reformulated it as a recursive least squares algorithm and therefore enabled its use in online applications. For this algorithm, the estimation of the power spectral density (PSD) of the anechoic signal plays an important role and strongly influences its performance. Recently, we showed that using a neural network PSD estimator leads to improved performance for online automatic speech recognition. This, however, comes at a price. To train the network, we require parallel data, i.e., utterances simultaneously available in clean and reverberated form. Here we propose to overcome this limitation by training the network jointly with the acoustic model of the speech recognizer. To be specific, the gradients computed from the cross-entropy loss between the target senone sequence and the acoustic model network output is backpropagated through the complex-valued dereverberation filter estimation to the neural network for PSD estimation. Evaluation on two databases demonstrates improved performance for on-line processing scenarios while imposing fewer requirements on the available training data and thus widening the range of applications.
AU - Heymann, Jahn
AU - Drude, Lukas
AU - Haeb-Umbach, Reinhold
AU - Kinoshita, Keisuke
AU - Nakatani, Tomohiro
ID - 12875
T2 - ICASSP 2019, Brighton, UK
TI - Joint Optimization of Neural Network-based WPE Dereverberation and Acoustic Model for Robust Online ASR
ER -