35,726 research outputs found
An automated wrapper-based approach to the design of dependable software
The design of dependable software systems invariably comprises two main activities: (i) the design of dependability mechanisms, and (ii) the location of dependability mechanisms. It has been shown that these activities are intrinsically difficult. In this paper we propose an automated wrapper-based methodology to circumvent the problems associated with the design and location of dependability mechanisms. To achieve this we replicate important variables so that they can be used as part of standard, efficient dependability mechanisms. These well-understood mechanisms are then deployed in all relevant locations. To validate the proposed methodology we apply it to three complex software systems, evaluating the dependability enhancement and execution overhead in each case. The results generated demonstrate that the system failure rate of a wrapped software system can be several orders of magnitude lower than that of an unwrapped equivalent
Temporal phase unwrapping using deep learning
The multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical
phase unwrapping algorithm for fringe projection profilometry (FPP), is capable
of eliminating the phase ambiguities even in the presence of surface
discontinuities or spatially isolated objects. For the simplest and most
efficient case, two sets of 3-step phase-shifting fringe patterns are used: the
high-frequency one is for 3D measurement and the unit-frequency one is for
unwrapping the phase obtained from the high-frequency pattern set. The final
measurement precision or sensitivity is determined by the number of fringes
used within the high-frequency pattern, under the precondition that the phase
can be successfully unwrapped without triggering the fringe order error.
Consequently, in order to guarantee a reasonable unwrapping success rate, the
fringe number (or period number) of the high-frequency fringe patterns is
generally restricted to about 16, resulting in limited measurement accuracy. On
the other hand, using additional intermediate sets of fringe patterns can
unwrap the phase with higher frequency, but at the expense of a prolonged
pattern sequence. Inspired by recent successes of deep learning techniques for
computer vision and computational imaging, in this work, we report that the
deep neural networks can learn to perform TPU after appropriate training, as
called deep-learning based temporal phase unwrapping (DL-TPU), which can
substantially improve the unwrapping reliability compared with MF-TPU even in
the presence of different types of error sources, e.g., intensity noise, low
fringe modulation, and projector nonlinearity. We further experimentally
demonstrate for the first time, to our knowledge, that the high-frequency phase
obtained from 64-period 3-step phase-shifting fringe patterns can be directly
and reliably unwrapped from one unit-frequency phase using DL-TPU
Micro Fourier Transform Profilometry (FTP): 3D shape measurement at 10,000 frames per second
Recent advances in imaging sensors and digital light projection technology
have facilitated a rapid progress in 3D optical sensing, enabling 3D surfaces
of complex-shaped objects to be captured with improved resolution and accuracy.
However, due to the large number of projection patterns required for phase
recovery and disambiguation, the maximum fame rates of current 3D shape
measurement techniques are still limited to the range of hundreds of frames per
second (fps). Here, we demonstrate a new 3D dynamic imaging technique, Micro
Fourier Transform Profilometry (FTP), which can capture 3D surfaces of
transient events at up to 10,000 fps based on our newly developed high-speed
fringe projection system. Compared with existing techniques, FTP has the
prominent advantage of recovering an accurate, unambiguous, and dense 3D point
cloud with only two projected patterns. Furthermore, the phase information is
encoded within a single high-frequency fringe image, thereby allowing
motion-artifact-free reconstruction of transient events with temporal
resolution of 50 microseconds. To show FTP's broad utility, we use it to
reconstruct 3D videos of 4 transient scenes: vibrating cantilevers, rotating
fan blades, bullet fired from a toy gun, and balloon's explosion triggered by a
flying dart, which were previously difficult or even unable to be captured with
conventional approaches.Comment: This manuscript was originally submitted on 30th January 1
Condition Monitoring of Power Cables
A National Grid funded research project at Southampton has investigated possible methodologies for data acquisition, transmission and processing that will facilitate on-line continuous monitoring of partial discharges in high voltage polymeric cable systems. A method that only uses passive components at the measuring points has been developed and is outlined in this paper. More recent work, funded through the EPSRC Supergen V, UK Energy Infrastructure (AMPerES) grant in collaboration with UK electricity network operators has concentrated on the development of partial discharge data processing techniques that ultimately may allow continuous assessment of transmission asset health to be reliably determined
Image fusion techniqes for remote sensing applications
Image fusion refers to the acquisition, processing and synergistic combination of information provided by various sensors or by the same sensor in many measuring contexts. The aim of this survey paper is to describe three typical applications of data fusion in remote sensing. The first study case considers the problem of the Synthetic Aperture Radar (SAR) Interferometry, where a pair of antennas are used to obtain an elevation map of the observed scene; the second one refers to the fusion of multisensor and multitemporal (Landsat Thematic Mapper and SAR) images of the same site acquired at different times, by using neural networks; the third one presents a processor to fuse multifrequency, multipolarization and mutiresolution SAR images, based on wavelet transform and multiscale Kalman filter. Each study case presents also results achieved by the proposed techniques applied to real data
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