43,113 research outputs found
PEPSI deep spectra. II. Gaia benchmark stars and other M-K standards
We provide a homogeneous library of high-resolution, high-S/N spectra for 48
bright AFGKM stars, some of them approaching the quality of solar-flux spectra.
Our sample includes the northern Gaia benchmark stars, some solar analogs, and
some other bright Morgan-Keenan (M-K) spectral standards. Well-exposed deep
spectra were created by average-combining individual exposures. The
data-reduction process relies on adaptive selection of parameters by using
statistical inference and robust estimators.We employed spectrum synthesis
techniques and statistics tools in order to characterize the spectra and give a
first quick look at some of the science cases possible. With an average
spectral resolution of R=220,000 (1.36 km/s), a continuous wavelength coverage
from 383 nm to 912 nm, and S/N of between 70:1 for the faintest star in the
extreme blue and 6,000:1 for the brightest star in the red, these spectra are
now made public for further data mining and analysis. Preliminary results
include new stellar parameters for 70 Vir and alpha Tau, the detection of the
rare-earth element dysprosium and the heavy elements uranium, thorium and
neodymium in several RGB stars, and the use of the 12C to 13C isotope ratio for
age-related determinations. We also found Arcturus to exhibit few-percent CaII
H&K and H-alpha residual profile changes with respect to the KPNO atlas taken
in 1999.Comment: in press, 15 pages, 7 figures, data available from pepsi.aip.d
Modeling of elastically mounted vertical rotor
The evaluation of the dynamic behavior of a rotating system is possible by means of modal parameters (Eigenvalues and Eigenvectors). A mixed analytical and experimetal approach is used to identify the modal parameters of a specially designed test rig. The modal identification is done both for nonrotating as well as rotating systems. These modal parameters are used to validate a developed Finite Element Model
Lifelong Learning of Spatiotemporal Representations with Dual-Memory Recurrent Self-Organization
Artificial autonomous agents and robots interacting in complex environments
are required to continually acquire and fine-tune knowledge over sustained
periods of time. The ability to learn from continuous streams of information is
referred to as lifelong learning and represents a long-standing challenge for
neural network models due to catastrophic forgetting. Computational models of
lifelong learning typically alleviate catastrophic forgetting in experimental
scenarios with given datasets of static images and limited complexity, thereby
differing significantly from the conditions artificial agents are exposed to.
In more natural settings, sequential information may become progressively
available over time and access to previous experience may be restricted. In
this paper, we propose a dual-memory self-organizing architecture for lifelong
learning scenarios. The architecture comprises two growing recurrent networks
with the complementary tasks of learning object instances (episodic memory) and
categories (semantic memory). Both growing networks can expand in response to
novel sensory experience: the episodic memory learns fine-grained
spatiotemporal representations of object instances in an unsupervised fashion
while the semantic memory uses task-relevant signals to regulate structural
plasticity levels and develop more compact representations from episodic
experience. For the consolidation of knowledge in the absence of external
sensory input, the episodic memory periodically replays trajectories of neural
reactivations. We evaluate the proposed model on the CORe50 benchmark dataset
for continuous object recognition, showing that we significantly outperform
current methods of lifelong learning in three different incremental learning
scenario
An adjustable focusing system for a 2 MeV H- ion beam line based on permanent magnet quadrupoles
A compact adjustable focusing system for a 2 MeV H- RFQ Linac is designed,
constructed and tested based on four permanent magnet quadrupoles (PMQ). A PMQ
model is realised using finite element simulations, providing an integrated
field gradient of 2.35 T with a maximal field gradient of 57 T/m. A prototype
is constructed and the magnetic field is measured, demonstrating good agreement
with the simulation. Particle track simulations provide initial values for the
quadrupole positions. Accordingly, four PMQs are constructed and assembled on
the beam line, their positions are then tuned to obtain a minimal beam spot
size of (1.2 x 2.2) mm^2 on target. This paper describes an adjustable PMQ beam
line for an external ion beam. The novel compact design based on commercially
available NdFeB magnets allows high flexibility for ion beam applications.Comment: published in JINST (4th Feb 2013
Thermally regenerable carbon dioxide absorbent system Final report, 1 May 1964 - 31 Jan. 1966
Carbon dioxide absorption by solid state ion exchange resin
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