1,092 research outputs found
Shallow Triple Stream Three-dimensional CNN (STSTNet) for Micro-expression Recognition
In the recent year, state-of-the-art for facial micro-expression recognition
have been significantly advanced by deep neural networks. The robustness of
deep learning has yielded promising performance beyond that of traditional
handcrafted approaches. Most works in literature emphasized on increasing the
depth of networks and employing highly complex objective functions to learn
more features. In this paper, we design a Shallow Triple Stream
Three-dimensional CNN (STSTNet) that is computationally light whilst capable of
extracting discriminative high level features and details of micro-expressions.
The network learns from three optical flow features (i.e., optical strain,
horizontal and vertical optical flow fields) computed based on the onset and
apex frames of each video. Our experimental results demonstrate the
effectiveness of the proposed STSTNet, which obtained an unweighted average
recall rate of 0.7605 and unweighted F1-score of 0.7353 on the composite
database consisting of 442 samples from the SMIC, CASME II and SAMM databases.Comment: 5 pages, 1 figure, Accepted and published in IEEE FG 201
Quantum error correction of coherent errors by randomization
A general error correction method is presented which is capable of correcting
coherent errors originating from static residual inter-qubit couplings in a
quantum computer. It is based on a randomization of static imperfections in a
many-qubit system by the repeated application of Pauli operators which change
the computational basis. This Pauli-Random-Error-Correction (PAREC)-method
eliminates coherent errors produced by static imperfections and increases
significantly the maximum time over which realistic quantum computations can be
performed reliably. Furthermore, it does not require redundancy so that all
physical qubits involved can be used for logical purposes.Comment: revtex 4 pages, 3 fig
Systematic Electromagnetic Interference Filter Design Based on Information From In-Circuit Impedance Measurements
Based on a two-probe measurement approach, the noise source and noise termination impedances of a switched-mode power supply (SMPS) under its normal operating condition are measured. With the accurate noise source and noise termination impedances, an electromagnetic interference (EMI) filter can be optimally designe
Computing normalisers of highly intransitive groups
We investigate the normaliser problem, that is, given , ≤ ₙ, compute [sub](). The fastest known theoretical algorithm for this problem is simply exponential, but more efficient algorithms are known for some restriction of classes for and . In this thesis, we will focus on highly intransitive groups, which are groups with many orbits. We give new algorithms to compute [sub](ₙ)() for highly intransitive groups ≤ ₙ and for some subclasses that perform substantially faster than previous implementations in the computer algebra system GAP."This work was supported by the University of St Andrews (School of Computer Science
and St Leonard’s College Scholarship)." -- Fundin
Computing normalisers of intransitive groups
Funding: The first and third authors would like to thank the Isaac Newton Institute for Mathematical Sciences, Cambridge, for support and hospitality during the programme “Groups, Representations and Applications: New perspectives”, where work on this paper was undertaken. This work was supported by EPSRC grant no EP/R014604/1. This work was also partially supported by a grant from the Simons Foundation. The first and second authors are supported by the Royal Society (RGF\EA\181005 and URF\R\180015).The normaliser problem takes as input subgroups G and H of the symmetric group Sn, and asks one to compute NG(H). The fastest known algorithm for this problem is simply exponential, whilst more efficient algorithms are known for restricted classes of groups. In this paper, we will focus on groups with many orbits. We give a new algorithm for the normaliser problem for these groups that performs many orders of magnitude faster than previous implementations in GAP. We also prove that the normaliser problem for the special case G=Sn is at least as hard as computing the group of monomial automorphisms of a linear code over any field of fixed prime order.Publisher PDFPeer reviewe
Polymer translocation through a nanopore under an applied external field
We investigate the dynamics of polymer translocation through a nanopore under
an externally applied field using the 2D fluctuating bond model with
single-segment Monte Carlo moves. We concentrate on the influence of the field
strength , length of the chain , and length of the pore on forced
translocation. As our main result, we find a crossover scaling for the
translocation time with the chain length from for
relatively short polymers to for longer chains, where
is the Flory exponent. We demonstrate that this crossover is due to the
change in the dependence of the translocation velocity v on the chain length.
For relatively short chains , which crosses over to for long polymers. The reason for this is that with increasing
there is a high density of segments near the exit of the pore, which slows down
the translocation process due to slow relaxation of the chain. For the case of
a long nanopore for which , the radius of gyration along
the pore, is smaller than the pore length, we find no clear scaling of the
translocation time with the chain length. For large , however, the
asymptotic scaling is recovered. In this regime, is almost independent of . We have previously found that for a polymer,
which is initially placed in the middle of the pore, there is a minimum in the
escape time for . We show here that this minimum
persists for a weak fields such that is less than some critical value,
but vanishes for large values of .Comment: 25 Pages, 10 figures. Submitted to J. Chem. Phys. J. Chem. Phys. 124,
in press (2006
Selective formation of pyridinic-type nitrogen-doped graphene and its application in lithium-ion battery anodes
We report a high-yield single-step method for synthesizing nitrogen-doped graphene nanostripes (N-GNSPs) with an unprecedentedly high percentage of pyridinic-type doping (>86% of the nitrogen sites), and investigate the performance of the resulting N-GNSPs as a lithium-ion battery (LIB) anode material. The as-grown N-GNSPs are compared with undoped GNSPs using scanning electron microscopy (SEM), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), helium ion-beam microscopy (HIM), and electrochemical methods. As an anode material we find that pyridinic-type N-GNSPs perform similarly to undoped GNSPs, suggesting that pyridinic sites alone are not responsible for the enhanced performance of nitrogen-doped graphene observed in previous studies, which contradicts common conjectures. In addition, post-mortem XPS measurements of nitrogen-doped graphene cycled as a lithium-ion battery anode are conducted for the first time, which reveal direct evidence for irreversible chemical changes at the nitrogen sites during cycling. These findings therefore provide new insights into the mechanistic models of doped graphene as LIB anodes, which are important in improving the anode designs for better LIB performance
TRUNK AND SHOULDER MUSCLE ACTIVITIES DURING PUSH-UP EXERCISE ON STABLE AND UNSTBLE SURFACES
The purpose of this study was to evaluate muscle activity of the prime movers and core stabilizers on stable and unstable surfaces during push-up exercise. Subject: Fourteen healthy male participants (age, 21.6 ±2.3 years; height, 174.7 ±8.1cm; weight, 68.2 ±16.4kg) without low back pain and shoulder injury in the past year were recruited. The participants completed push-up exercise in three conditions: on the ground, air disc and sling. EMG activities of external abdominal oblique, pectoralis major, and anterior deltoid muscles and elbow joint kinematics were recorded. Our results showed that external abdominal oblique muscle had significantly greater activity in the sling group (
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