29,221 research outputs found
Multiple wavemode scanning for near and far-side defect characterisation
The combination of ultrasonic inspections using different wavemodes can give more information than is available with single mode inspection. In this work, the response of shear and Rayleigh waves to surface-breaking defects propagating on the near-side and far-side of a sample is investigated. The directivity of shear waves generated by a racetrack coil electromagnetic acoustic transducer (EMAT) is identified and used to set an ideal separation for a pair of transmit-receive EMATs. Defects are indicated by a reduction in the transmitted Rayleigh wave amplitude, and by blocking of the shear wave. Used together, these can identify features in the bulk wave behaviour which are due to near-face surface-breaking defects, and give a full picture of both surfaces. By using a combination of the two wavemodes, the angle of propagation and length of any near-side defects can additionally be identified. A scanning method for samples is proposed
A new class of parallel data convolutional codes
We propose a new class of parallel data convolutional
codes (PDCCs) in this paper. The PDCC encoders inputs
are composed of an original block of data and its interleaved version.
A novel single self-iterative soft-in/soft-out a posteriori probability
(APP) decoder structure is proposed for the decoding of
the PDCCs. Simulation results are presented to compare the performance
of PDCCs
On the capacity and normalisation of ISI channels
[Abstract]: We investigate the capacity of various ISI channels with additive white Gaussian noise. Previous papers showed
a minimum Eb/N0 of −4.6 dB, 3 dB below the capacity of
a flat channel, is obtained using the water-pouring capacity
formulas for the 1 + D channel. However, these papers did
not take into account that the channel power gain can be
greater than unity when water-pouring is used. We present a
generic power normalization method of the channel frequency
response, namely peak bandwidth normalisation, to facilitate the fair capacity comparison of various ISI channels. Three types of ISI channel, i.e., adder channels, RC channels and magnetic recording channels, are examined. By using our channel power gain normalization, the capacity curves of these ISI channels are shown
Quantifying and Transferring Contextual Information in Object Detection
(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other work
Unsupervised learning of generative topic saliency for person re-identification
(c) 2014. The copyright of this document resides with its authors.
It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors. Existing approaches to person re-identification (re-id) are dominated by supervised learning based methods which focus on learning optimal similarity distance metrics. However, supervised learning based models require a large number of manually labelled pairs of person images across every pair of camera views. This thus limits their ability to scale to large camera networks. To overcome this problem, this paper proposes a novel unsupervised re-id modelling approach by exploring generative probabilistic topic modelling. Given abundant unlabelled data, our topic model learns to simultaneously both (1) discover localised person foreground appearance saliency (salient image patches) that are more informative for re-id matching, and (2) remove busy background clutters surrounding a person. Extensive experiments are carried out to demonstrate that the proposed model outperforms existing unsupervised learning re-id methods with significantly simplified model complexity. In the meantime, it still retains comparable re-id accuracy when compared to the state-of-the-art supervised re-id methods but without any need for pair-wise labelled training data
Material removal investigation in bonnet polishing of CoCr alloy
The manufacture of orthopaedic joint bearings surfaces requires exceptionally high levels of control of not only the surface finish but also the surface form. In the case of hip joints, the form of femoral head should be controlled to within ± 50ìm from a given diameter. It has been shown that a better form control of bearing component could enhance clearances creating the correct volume of lubrication to fill the bearing surface gap and reduce wear particle generation. This element is especially critical for the new generation non-spherical head designs. Bonnet polishing which is used successfully in the area of optics is potentially an excellent finishing process to control the form and finish of artificial joints. In the process of form control polishing an “influence function” which defines the material removal rate is of vital importance in developing a corrective polishing procedure. However, the effects of polishing parameters (such as precess angle, head speed, tool pressure and tool offset) on influence function are not very clear for CoCr alloys. These elements must be assessed if a deterministic polishing process is to be developed. Therefore, it is of paramount importance to understand the contribution of each polishing factors to influence function and consequent part polishing. This study has investigated the effects of polishing parameters on influence function, including geometric size and volumetric material removal rate (MRR). The
experimental results indicate that the polishing parameter of precess angle and tool offset affect the geometric size of influence function significantly; the polishing parameter of head speed and tool pressure affect the geometric size of influence function to a lesser degree; the polishing parameter of precess angle, head speed and tool offset affect MRR greatly
Room-Temperature Ferrimagnet with Frustrated Antiferroelectricity: Promising Candidate Toward Multiple State Memory
On the basis of first-principles calculations we show that the M-type
hexaferrite BaFe12O19 exhibits frustrated antiferroelectricity associated with
its trigonal bipyramidal Fe3+ sites. The ferroelectric (FE) state of BaFe12O19,
reachable by applying an external electric field to the antiferroelectric (AFE)
state, can be made stable at room temperature by appropriate element
substitution or strain engineering. Thus M-type hexaferrite, as a new type of
multiferoic with coexistence of antiferroelectricity and ferrimagnetism,
provide a basis for studying the phenomenon of frustrated antiferroelectricity
and realizing multiple state memory devices.Comment: supporting material available via email. arXiv admin note: text
overlap with arXiv:1210.7116 by other author
Observation of topological transition of Fermi surface from a spindle-torus to a torus in large bulk Rashba spin-split BiTeCl
The recently observed large Rashba-type spin splitting in the BiTeX (X = I,
Br, Cl) bulk states due to the absence of inversion asymmetry and large charge
polarity enables observation of the transition in Fermi surface topology from
spindle-torus to torus with varying the carrier density. These BiTeX systems
with high spin-orbit energy scales offer an ideal platform for achieving
practical spintronic applications and realizing non-trivial phenomena such as
topological superconductivity and Majorana fermions. Here we use Shubnikov-de
Haas oscillations to investigate the electronic structure of the bulk
conduction band of BiTeCl single crystals with different carrier densities. We
observe the topological transition of the Fermi surface (FS) from a
spindle-torus to a torus. The Landau level fan diagram reveals the expected
non-trivial {\pi} Berry phase for both the inner and outer FSs. Angle-dependent
oscillation measurements reveal three-dimensional FS topology when the Fermi
level lies in the vicinity of the Dirac point. All the observations are
consistent with large Rashba spin-orbit splitting in the bulk conduction band.Comment: 28 pages, supplementary informatio
Exit chart analysis of parallel data convolutional codes
We recently proposed a new class of turbo-like codes
called parallel data convolutional codes (PDCCs). The distinct characteristics of PDCCs include parallel data input bits and a self-iterative soft-in/soft-out a posteriori probability(APP) decoder. In this paper, we analyse this turbolike code by means of the extrinsic information transfer chart (EXIT chart). Our results show that the threshold Eb/N0 point for a rate 1/2 8-state PDCC is 0.6 dB, which is the same as the threshold point for a punctured rate 1/2 16-state parallel concatenated convolutional code (turbo code)
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