3,046 research outputs found
Excitable Patterns in Active Nematics
We analyze a model of mutually-propelled filaments suspended in a
two-dimensional solvent. The system undergoes a mean-field isotropic-nematic
transition for large enough filament concentrations and the nematic order
parameter is allowed to vary in space and time. We show that the interplay
between non-uniform nematic order, activity and flow results in spatially
modulated relaxation oscillations, similar to those seen in excitable media. In
this regime the dynamics consists of nearly stationary periods separated by
"bursts" of activity in which the system is elastically distorted and solvent
is pumped throughout. At even higher activity the dynamics becomes chaotic.Comment: 4 pages, 4 figure
Reduction and reconstruction of stochastic differential equations via symmetries
An algorithmic method to exploit a general class of infinitesimal symmetries
for reducing stochastic differential equations is presented and a natural
definition of reconstruction, inspired by the classical reconstruction by
quadratures, is proposed. As a side result the well-known solution formula for
linear one-dimensional stochastic differential equations is obtained within
this symmetry approach. The complete procedure is applied to several examples
with both theoretical and applied relevance
Hybrid Method for Digits Recognition using Fixed-Frame Scores and Derived Pitch
This paper presents a procedure of frame normalization based on the traditional dynamic time warping (DTW) using the LPC coefficients. The redefined method is called as the DTW frame-fixing method (DTW-FF), it works by normalizing the word frames of the input against the
reference frames. The enthusiasm to this study is due to neural network limitation that entails a fix number of input nodes for when processing multiple inputs in parallel. Due to this problem, this research is initiated to reduce the amount of computation and complexity in a neural network by reducing the number of inputs into the network. In this study, dynamic warping process is used, in which local distance scores of the warping path are fixed and collected so that their scores are of equal number of frames. Also studied in this paper is the
consideration of pitch as a contributing feature to the speech recognition. Results showed a good performance and
improvement when using pitch along with DTW-FF feature.
The convergence rate between using the steepest gradient
descent is also compared to another method namely conjugate
gradient method. Convergence rate is also improved when
conjugate gradient method is introduced in the back-propagation algorithm
Spatially Resolved Mapping of Local Polarization Dynamics in an Ergodic Phase of Ferroelectric Relaxor
Spatial variability of polarization relaxation kinetics in relaxor
ferroelectric 0.9Pb(Mg1/3Nb2/3)O3-0.1PbTiO3 is studied using time-resolved
Piezoresponse Force Microscopy. Local relaxation attributed to the
reorientation of polar nanoregions is shown to follow stretched exponential
dependence, exp(-(t/tau)^beta), with beta~~0.4, much larger than the
macroscopic value determined from dielectric spectra (beta~~0.09). The spatial
inhomogeneity of relaxation time distributions with the presence of 100-200 nm
"fast" and "slow" regions is observed. The results are analyzed to map the
Vogel-Fulcher temperatures on the nanoscale.Comment: 23 pages, 4 figures, supplementary materials attached; to be
submitted to Phys. Rev. Let
Artificial Neural Network-based error compensation procedure for low-cost encoders
An Artificial Neural Network-based error compensation method is proposed for
improving the accuracy of resolver-based 16-bit encoders by compensating for
their respective systematic error profiles. The error compensation procedure,
for a particular encoder, involves obtaining its error profile by calibrating
it on a precision rotary table, training the neural network by using a part of
this data and then determining the corrected encoder angle by subtracting the
ANN-predicted error from the measured value of the encoder angle. Since it is
not guaranteed that all the resolvers will have exactly similar error profiles
because of the inherent differences in their construction on a micro scale, the
ANN has been trained on one error profile at a time and the corresponding
weight file is then used only for compensating the systematic error of this
particular encoder. The systematic nature of the error profile for each of the
encoders has also been validated by repeated calibration of the encoders over a
period of time and it was found that the error profiles of a particular encoder
recorded at different epochs show near reproducible behavior. The ANN-based
error compensation procedure has been implemented for 4 encoders by training
the ANN with their respective error profiles and the results indicate that the
accuracy of encoders can be improved by nearly an order of magnitude from
quoted values of ~6 arc-min to ~0.65 arc-min when their corresponding
ANN-generated weight files are used for determining the corrected encoder
angle.Comment: 16 pages, 4 figures. Accepted for Publication in Measurement Science
and Technology (MST
Consumer palatability scores and volatile beef flavor compounds of five USDA quality grades and four muscles
Proximate data, consumer palatability scores and volatile compounds were investigated for four beef muscles (Longissimus lumborum, Psoas major, Semimembranosus and Gluteus medius) and five USDA quality grades (Prime, Upper 2/3 Choice, Low Choice, Select, and Standard). Quality grade did not directly affect consumer scores or volatiles but interactions (P < 0.05) between muscle and grade were determined. Consumer scores and volatiles differed (P < 0.05) between muscles. Consumers scored Psoas major highest for tenderness, juiciness, flavor liking and overall liking, followed by Longissimus lumborum, Gluteus medius, and Semimembranosus (P < 0.05). Principal component analysis revealed clustering of compound classes, formed by related mechanisms. Volatile n-aldehydes were inversely related to percent fat. Increases in lipid oxidation compounds were associated with Gluteus medius and Semimembranosus, while greater quantities of sulfur-containing compounds were associated with Psoas major. Relationships between palatability scores and volatile compound classes suggest that differences in the pattern of volatile compounds may play a valuable role in explaining consumer liking
Quantum effects in linguistic endeavors
Classifying the information content of neural spike trains in a linguistic
endeavor, an uncertainty relation emerges between the bit size of a word and
its duration. This uncertainty is associated with the task of synchronizing the
spike trains of different duration representing different words. The
uncertainty involves peculiar quantum features, so that word comparison amounts
to measurement-based-quantum computation. Such a quantum behavior explains the
onset and decay of the memory window connecting successive pieces of a
linguistic text. The behavior here discussed is applicable to other reported
evidences of quantum effects in human linguistic processes, so far lacking a
plausible framework, since either no efforts to assign an appropriate quantum
constant had been associated or speculating on microscopic processes dependent
on Planck's constant resulted in unrealistic decoherence times
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