115,250 research outputs found
A New Multi-vehicle Trajectory Generator to Simulate Vehicle-to-Vehicle Encounters
Generating multi-vehicle trajectories from existing limited data can provide
rich resources for autonomous vehicle development and testing. This paper
introduces a multi-vehicle trajectory generator (MTG) that can encode
multi-vehicle interaction scenarios (called driving encounters) into an
interpretable representation from which new driving encounter scenarios are
generated by sampling. The MTG consists of a bi-directional encoder and a
multi-branch decoder. A new disentanglement metric is then developed for model
analyses and comparisons in terms of model robustness and the independence of
the latent codes. Comparison of our proposed MTG with -VAE and InfoGAN
demonstrates that the MTG has stronger capability to purposely generate
rational vehicle-to-vehicle encounters through operating the disentangled
latent codes. Thus the MTG could provide more data for engineers and
researchers to develop testing and evaluation scenarios for autonomous
vehicles.Comment: 6 pages, accepted by ICRA 201
Charged Einstein-aether black holes and Smarr formula
In the framework of the Einstein-Maxwell-aether theory, we present two new
classes of exact charged black hole solutions, which are asymptotically flat
and possess the universal as well as Killing horizons. We also construct the
Smarr formulas, and calculate the temperatures of the horizons, using the Smarr
mass-area relation. We find that, in contrast to the neutral case, such
obtained temperature is not proportional to its surface gravity at any of the
two kinds of the horizons. Einstein-Maxwell-aether black holes with the
cosmological constant and their topological cousins are also given.Comment: revtex4, 3 figures. To appear in Phys. Rev. D. arXiv admin note: text
overlap with arXiv:1202.4497 by other author
Dynamic Process of Money Transfer Models
We have studied numerically the statistical mechanics of the dynamic
phenomena, including money circulation and economic mobility, in some transfer
models. The models on which our investigations were performed are the basic
model proposed by A. Dragulescu and V. Yakovenko [1], the model with uniform
saving rate developed by A. Chakraborti and B.K. Chakrabarti [2], and its
extended model with diverse saving rate [3]. The velocity of circulation is
found to be inversely related with the average holding time of money. In order
to check the nature of money transferring process in these models, we
demonstrated the probability distributions of holding time. In the model with
uniform saving rate, the distribution obeys exponential law, which indicates
money transfer here is a kind of Poisson process. But when the saving rate is
set diversely, the holding time distribution follows a power law. The velocity
can also be deduced from a typical individual's optimal choice. In this way, an
approach for building the micro-foundation of velocity is provided. In order to
expose the dynamic mechanism behind the distribution in microscope, we examined
the mobility by collecting the time series of agents' rank and measured it by
employing an index raised by economists. In the model with uniform saving rate,
the higher saving rate, the slower agents moves in the economy. Meanwhile, all
of the agents have the same chance to be the rich. However, it is not the case
in the model with diverse saving rate, where the assumed economy falls into
stratification. The volatility distribution of the agents' ranks are also
demonstrated to distinguish the differences among these models.Comment: 11 pages, 4 figures. In 'Econophysics of Wealth Distributions',
Springer-Verlag Italia, Ed. A. Chatterjee, B. K. Chakrabarti and S.
Yarlagadda (2005); Conf. Proc. Econophys-Kolkata I: International Workshop on
Econophysics of Wealth Distributions, Kolkata, India, March 200
Generalized Bi-Schr\"odinger Flows and Vortex Filament on Symmetric Lie Algebras
The theory of the vortex filament in three-dimensional fluid dynamics,
consisting mainly of the models up to the third-order approximation, is an
attractive subject in both physics and mathematics. Many efforts have been
devoted to the extension of the theory to higher-dimensional symmetric Lie
algebras. However, such a generalization known in literature is strongly
restricted by the integrable method. In this article, we endeavor to establish
the third-order models of the vortex filament on symmetric Lie algebras in a
purely geometric way by generalized bi-Schr\"odinger flows. Our generalization
overcomes the limitation of integrability and creates successfully the desired
models on Hermitian or para-Hermitian symmetric Lie algebras. Combining the
result in this article with what have been known in literature for the
leading-order and the second-order models, we actually exhibit the basic models
and the related theory of the vortex filament on symmetric Lie algebras up to
the third-order approximation
Non-iterative Joint Detection-Decoding Receiver for LDPC-Coded MIMO Systems Based on SDR
Semi-definite relaxation (SDR) detector has been demonstrated to be
successful in approaching maximum likelihood (ML) performance while the time
complexity is only polynomial. We propose a new receiver jointly utilizing the
forward error correction (FEC) code information in the SDR detection process.
Strengthened by the code constraints, the joint SDR detector provides soft
information of much improved reliability to downstream decoder and therefore
outperforms existing receivers with substantial gain.Comment: 5 pages, 3 figures, conference. arXiv admin note: substantial text
overlap with arXiv:1806.04295, arXiv:1803.0584
Thermodynamical study on universal horizons in higher -dimensional spacetime and aether waves
We investigate thermodynamic behaviors of the -dimensional gravity coupled
to a dynamical unit timelike vector, the aether, present two kinds of exact
charged solutions and study the linearized wave spectrum of this theory. There
is an universal horizon behind the Killing horizon in these aether black holes.
It is interesting that there exist -dimensional Schwarzschild,
Reissner-Nordstr\"{o}m and charged Schwarzschild black holes but now with an
universal horizon inside. We find that in the uncharged case for both kinds, or
charged case but the charge for the first kind, one can
construct a Smarr formula and the (slightly modified) first law of black hole
mechanics at the universal horizons for the aether black holes. An entropy can
be associated with the universal horizon and a temperature can be defined
there. For the second kind aether black hole and for the first kind one in the
extremal higher dimensions, the work term involving charge
disappeared. For aether wave, our results show that the spin-1 and spin-2 modes
are the same as those in 4-dimensional spacetime, and only the spin-0 one is
different and dependant on the dimension number .Comment: 26 pages, no figure. In this version, 5 pages added, accepted by Phys
Rev D. arXiv admin note: substantial text overlap with arXiv:1608.0029
Krichever-Novikov Vertex Algebras on Compact Riemann Surfaces
We give a notation of Krichever-Novikov vertex algebras on compact Riemann
surfaces which is a bit weaker, but quite similar to vertex algebras. As
example, we construct Krichever-Novikov vertex algebras of generalized
Heisenberg algebras on arbitrary compact Riemann surfaces, which are reduced to
be Heisenberg vertex algebra when restricted on Riemann spheres
Extracting Traffic Primitives Directly from Naturalistically Logged Data for Self-Driving Applications
Developing an automated vehicle, that can handle complicated driving
scenarios and appropriately interact with other road users, requires the
ability to semantically learn and understand driving environment, oftentimes,
based on analyzing massive amounts of naturalistic driving data. An important
paradigm that allows automated vehicles to both learn from human drivers and
gain insights is understanding the principal compositions of the entire
traffic, termed as traffic primitives. However, the exploding data growth
presents a great challenge in extracting primitives from high-dimensional
time-series traffic data with various types of road users engaged. Therefore,
automatically extracting primitives is becoming one of the cost-efficient ways
to help autonomous vehicles understand and predict the complex traffic
scenarios. In addition, the extracted primitives from raw data should 1) be
appropriate for automated driving applications and also 2) be easily used to
generate new traffic scenarios. However, existing literature does not provide a
method to automatically learn these primitives from large-scale traffic data.
The contribution of this paper has two manifolds. The first one is that we
proposed a new framework to generate new traffic scenarios from a handful of
limited traffic data. The second one is that we introduce a nonparametric
Bayesian learning method -- a sticky hierarchical Dirichlet process hidden
Markov model -- to automatically extract primitives from multidimensional
traffic data without prior knowledge of the primitive settings. The developed
method is then validated using one day of naturalistic driving data. Experiment
results show that the nonparametric Bayesian learning method is able to extract
primitives from traffic scenarios where both the binary and continuous events
coexist.Comment: 7 pages, 8 figures, 2 tables, ICRA 201
W-symmetries on the Homogeneous Space G/U(1)^r
A construction of -symmetries is given only in terms of the nonlocal
fields (parafermions {\ps}_{\al}), which take values on the homogeneous space
, where is a simply connected compact Lie group manifold (its
accompanying Lie algebra is a simple one of rank ). Only certain
restriction of the root set of Lie algebra on which the parafermionic fields
take values are satisfied, then a consistent and non-trivial extension of the
stress momentum tensor may exist. For arbitrary simple-laced algebras, i.e. the
cases, a more detailed discussion is given. The OPE of spin three
primary field are calculated, in which a primary field with spin four is
emerging.Comment: 20 pages, Late
Improve bone age assessment by learning from anatomical local regions
Skeletal bone age assessment (BAA), as an essential imaging examination, aims
at evaluating the biological and structural maturation of human bones. In the
clinical practice, Tanner and Whitehouse (TW2) method is a widely-used method
for radiologists to perform BAA. The TW2 method splits the hands into Region Of
Interests (ROI) and analyzes each of the anatomical ROI separately to estimate
the bone age. Because of considering the analysis of local information, the TW2
method shows accurate results in practice. Following the spirit of TW2, we
propose a novel model called Anatomical Local-Aware Network (ALA-Net) for
automatic bone age assessment. In ALA-Net, anatomical local extraction module
is introduced to learn the hand structure and extract local information.
Moreover, we design an anatomical patch training strategy to provide extra
regularization during the training process. Our model can detect the anatomical
ROIs and estimate bone age jointly in an end-to-end manner. The experimental
results show that our ALA-Net achieves a new state-of-the-art single model
performance of 3.91 mean absolute error (MAE) on the public available RSNA
dataset. Since the design of our model is well consistent with the well
recognized TW2 method, it is interpretable and reliable for clinical usage.Comment: Early accepted to MICCAI202
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