High stability interleaved fibre Michelson interferometer for on-line precision displacement measurements

A self-reference fiber Michelson interferometer measurement system, which employs fiber Bragg gratings (FBGs) as in-fiber reflective mirrors and interleaves together two fiber Michelson interferometers that share the common-interferometric-optical path, is presented. One of the fiber interferometers is used to stabilise the system by the use of an electronic feedback loop to compensate the influences resulting from the environmental disturbances, while the other one is used to perform the measurement task. The influences resulting from the environmental disturbances have been eliminated by the compensating action of the electronic feedback loop, this makes the system suitable for on-line precision measurement. By means of the homodyne phase-tracking technique, the linearity of the measurement results of displacement measurements has been very high.

Investigation of some critical aspects of on-line surface measurement by a wavelength-division-multiplexing technique

Some critical aspects of a new kind of on-line measurement technique for micro and nanoscale surface measurements are described. This attempts to use spatial light-wave scanning to replace mechanical stylus scanning, and an optical fibre interferometer to replace optically bulky interferometers for measuring the surfaces. The basic principle is based on measuring the phase shift of a reflected optical signal. Wavelength-division-multiplexing and fibre Bragg grating techniques are used to carry out wavelength-to-field transformation and phase-to-depth detection, allowing a large dynamic measurement ratio (range/resolution) and high signal-to-noise ratio with remote access. In effect the paper consists of two parts: multiplexed fibre interferometry and remote on-machine surface detection sensor (an optical dispersive probe). This paper aims to investigate the metrology properties of a multiplexed fibre interferometer and to verify its feasibility by both theoretical and experimental studies. Two types of optical probes, using a dispersive prism and a blazed grating, respectively, are introduced to realize wavelength-to-spatial scanning.

Progressive structural analysis for dynamic recognition of on-line handwritten mathematical expressions

Structural analysis in handwritten mathematical expressions focuses on interpreting the recognized symbols using geometrical information such as relative sizes and positions of the symbols. Most existing approaches rely on hand-crafted grammar rules to identify semantic relationships among the recognized mathematical symbols. They could easily fail when writing errors occurred. Moreover, they assume the availability of the whole mathematical expression before being able to analyze the semantic information of the expression. To tackle these problems, we propose a progressive structural analysis (PSA) approach for dynamic recognition of handwritten mathematical expressions. The proposed PSA approach is able to provide analysis result immediately after each written input symbol. This has an advantage that users are able to detect any recognition errors immediately and correct only the mis-recognized symbols rather than the whole expression. Experiments conducted on 57 most commonly used mathematical expressions have shown that the PSA approach is able to achieve very good performance results.

High stability multiplexed fiber interferometer and its application on absolute displacement measurement and on-line surface metrology

We propose a self-reference multiplexed fibre interferometer (MFI) by using a tunable laser and fibre Bragg grating (FBG). The optical measurement system multiplexes two Michelson fibre interferometers with shared optical path in the main part of optical system. One fibre optic interferometer is used as a reference interferometer to monitor and control the high accuracy of the measurement system under environmental perturbations. The other is used as a measurement interferometer to obtain information from the target. An active phase tracking homodyne (APTH) technique is applied for signal processing to achieve high resolution. MFI can be utilised for high precision absolute displacement measurement with different combination of wavelengths from the tuneable laser. By means of Wavelength-Division-Multiplexing (WDM) technique, MFI is also capable of realising on-line surface measurement, in which traditional stylus scanning is replaced by spatial light-wave scanning so as to greatly improve the measurement speed and robustness.

Investigation of some critical aspects of on-line surface measurement by a wavelength-division-multiplexing technique

Some critical aspects of a new kind of on-line measurement technique for micro and nanoscale surface measurements are described. This attempts to use spatial light-wave scanning to replace mechanical stylus scanning, and an optical fibre interferometer to replace optically bulky interferometers for measuring the surfaces. The basic principle is based on measuring the phase shift of a reflected optical signal. Wavelength-division-multiplexing and fibre Bragg grating techniques are used to carry out wavelength-to-field transformation and phase-to-depth detection, allowing a large dynamic measurement ratio (range/resolution) and high signal-to-noise ratio with remote access. In effect the paper consists of two parts: multiplexed fibre interferometry and remote on-machine surface detection sensor (an optical dispersive probe). This paper aims to investigate the metrology properties of a multiplexed fibre interferometer and to verify its feasibility by both theoretical and experimental studies. Two types of optical probes, using a dispersive prism and a blazed grating, respectively, are introduced to realize wavelength-to-spatial scanning.

On-line learning in a changing environment

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Improving scheduling techniques in heterogeneous systems with dynamic, on-line optimisations

Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive applications. However, implementations for such heterogeneous systems are often hand-crafted and optimised to one computation scenario, and it can be challenging to maintain high performance when application parameters change. In this paper, we demonstrate that machine learning can help to dynamically choose parameters for task scheduling and load-balancing based on changing characteristics of the incoming workload. We use a financial option pricing application as a case study. We propose a simulation of processing financial tasks on a heterogeneous system with GPUs and FPGAs, and show how dynamic, on-line optimisations could improve such a system. We compare on-line and batch processing algorithms, and we also consider cases with no dynamic optimisations.