581 research outputs found
Human and Machine Speaker Recognition Based on Short Trivial Events
Trivial events are ubiquitous in human to human conversations, e.g., cough,
laugh and sniff. Compared to regular speech, these trivial events are usually
short and unclear, thus generally regarded as not speaker discriminative and so
are largely ignored by present speaker recognition research. However, these
trivial events are highly valuable in some particular circumstances such as
forensic examination, as they are less subjected to intentional change, so can
be used to discover the genuine speaker from disguised speech. In this paper,
we collect a trivial event speech database that involves 75 speakers and 6
types of events, and report preliminary speaker recognition results on this
database, by both human listeners and machines. Particularly, the deep feature
learning technique recently proposed by our group is utilized to analyze and
recognize the trivial events, which leads to acceptable equal error rates
(EERs) despite the extremely short durations (0.2-0.5 seconds) of these events.
Comparing different types of events, 'hmm' seems more speaker discriminative.Comment: ICASSP 201
Rapid Rotation of an Erupting Prominence and the Associated Coronal Mass Ejection on 13 May 2013
In this paper, we report the multiwavelength observations of an erupting
prominence and the associated CME on 13 May 2013. The event occurs behind the
western limb in the field of view of SDO/AIA. The prominence is supported by a
highly twisted magnetic flux rope and shows rapid rotation in the
counterclockwise direction during the rising motion. The rotation of the
prominence lasts for 47 minutes. The average period, angular speed, and
linear speed are 806 s, 0.46 rad min, and 355 km
s, respectively. The total twist angle reaches 7, which is
considerably larger than the threshold for kink instability. Writhing motion
during 17:4217:46 UT is clearly observed by SWAP in 174 {\AA} and EUVI on
board the behind STEREO spacecraft in 304 {\AA} after reaching an apparent
height of 405\,Mm. Therefore, the prominence eruption is most probably
triggered by kink instability. A pair of conjugate flare ribbons and post-flare
loops are created and observed by STA/EUVI. The onset time of writhing motion
is consistent with the commencement of the impulsive phase of the related
flare. The 3D morphology and positions of the associated CME are derived using
the graduated cylindrical shell (GCS) modeling. The kinetic evolution of the
reconstructed CME is divided into a slow-rise phase (330 km s) and
a fast-rise phase (1005 km s) by the writhing motion. The edge-on
angular width of the CME is a constant (60), while the face-on
angular width increases from 96 to 114, indicating a
lateral expansion. The latitude of the CME source region decreases slightly
from 18 to 13, implying an equatorward
deflection during propagation.Comment: 28 pages, 20 figures, accepted for publication in Solar Physics,
comments are welcom
MQENet: A Mesh Quality Evaluation Neural Network Based on Dynamic Graph Attention
With the development of computational fluid dynamics, the requirements for
the fluid simulation accuracy in industrial applications have also increased.
The quality of the generated mesh directly affects the simulation accuracy.
However, previous mesh quality metrics and models cannot evaluate meshes
comprehensively and objectively. To this end, we propose MQENet, a structured
mesh quality evaluation neural network based on dynamic graph attention. MQENet
treats the mesh evaluation task as a graph classification task for classifying
the quality of the input structured mesh. To make graphs generated from
structured meshes more informative, MQENet introduces two novel structured mesh
preprocessing algorithms. These two algorithms can also improve the conversion
efficiency of structured mesh data. Experimental results on the benchmark
structured mesh dataset NACA-Market show the effectiveness of MQENet in the
mesh quality evaluation task
Sunspot shearing and sudden retraction motion associated with the 2013 August 17 M3.3 Flare
In this Letter, we give a detailed analysis to the M3.3 class flare that
occurred on August 17, 2013 (SOL2013-08-17T18:16). It presents a clear picture
of mutual magnetic interaction initially from the photosphere to the corona via
the abrupt rapid shearing motion of a small sunspot before the flare, and then
suddenly from the corona back to the photosphere via the sudden retraction
motion of the same sunspot during the flare impulsive phase. About 10 hours
before the flare, a small sunspot in the active region NOAA 11818 started to
move northeast along a magnetic polarity inversion line (PIL), creating a
shearing motion that changed the quasi-static state of the active region. A
filament right above the PIL was activated following the movement of the
sunspot and then got partially erupted. The eruption eventually led to the M3.3
flare. The sunspot was then suddenly pulled back to the opposite direction upon
the flare onset. During the backward motion, the Lorentz force underwent a
simultaneous impulsive change both in magnitude and direction. Its directional
change is found to be conformable with the retraction motion. The observation
provides direct evidence for the role of the shearing motion of the sunspot in
powering and triggering the flare. It especially confirms that the abrupt
motion of a sunspot during a solar flare is the result of a back reaction
caused by the reconfiguration of the coronal magnetic field
Empirical ResearchonTeaching KnowledgeSharingin University Townand Its Influential Factors
The implement of knowledge sharing in University Town facilitates to aggregate education resource and improve overall strength of University Town. According to factors and performance of teaching knowledge sharing in University Town, the model and theoretical hypothesis of teaching knowledge sharing in University Town are proposed. Questionnaire and structural equation model are used to empirically study teaching knowledge sharing model in University Town. The results indicate that three factors including the characteristics of knowledge, the cluster of University Town and the system and mechanism for University Town have a significant correlation with teaching knowledge sharing in University Town, while teaching knowledge sharing in University Town has a significant correlation with Knowledge Innovation, comprehensive strength and education quality of University Town. By analysis results, effective strategies are designed for knowledge sharing mechanism in University Town
Compressed Air Energy Storage
ústav energetik
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