Gaussian Process training with input noise

In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods.

Acoustic radiation force of a Bessel beam on a porous sphere.

The possibility of using acoustic Bessel beams to produce an axial pulling force on porous particles is examined in an exact manner. The mathematical model utilizes the appropriate partial-wave expansion method in spherical coordinates, while Biot's model is used to describe the wave motion within the poroelastic medium. Of particular interest here is to examine the feasibility of using Bessel beams for (a) acoustic manipulation of fine porous particles and (b) suppression of particle resonances. To verify the viability of the technique, the radiation force and scattering form-function are calculated for aluminum and silica foams at various porosities. Inspection of the results has shown that acoustic manipulation of low porosity (<0.3) spheres is similar to that of solid elastic spheres, but this behavior significantly changes at higher porosities. Results have also shown a strong correlation between the backscattered form-function and the regions of negative radiation force. It has also been observed that the high-order resonances of the particle can be effectively suppressed by choosing the beam conical angle such that the acoustic contribution from that particular mode vanishes. This investigation may be helpful in the development of acoustic tweezers for manipulation of micro-porous drug delivery carrier and contrast agents.

State-space inference and learning with Gaussian processes

State-space inference and learning with Gaussian processes (GPs) is an unsolved problem. We propose a new, general methodology for inference and learning in nonlinear state-space models that are described probabilistically by non-parametric GP models. We apply the expectation maximization algorithm to iterate between inference in the latent state-space and learning the parameters of the underlying GP dynamics model. Copyright 2010 by the authors.

Robust filtering and smoothing with gaussian processes

We propose a principled algorithm for robust Bayesian filtering and smoothing in nonlinear stochastic dynamic systems when both the transition function and the measurement function are described by non-parametric Gaussian process (GP) models. GPs are gaining increasing importance in signal processing, machine learning, robotics, and control for representing unknown system functions by posterior probability distributions. This modern way of system identification is more robust than finding point estimates of a parametric function representation. Our principled filtering/smoothing approach for GP dynamic systems is based on analytic moment matching in the context of the forward-backward algorithm. Our numerical evaluations demonstrate the robustness of the proposed approach in situations where other state-of-the-art Gaussian filters and smoothers can fail. © 2011 IEEE.

Development of a servo-hydraulic earthquake actuator for the Cambridge Turner beam centrifuge

Dynamic centrifuge modelling has been carried out at Cambridge since the late 1970s. Over this period, three different mechanical earthquake actuators were developed. In this paper the development of a new servo-hydraulic earthquake actuator is described. The basic design principles are explained along with the need to carry out these designs to match the existing services and systems of the 35 year old Turner beam centrifuge at Cambridge. In addition, some of the features of the Turner beam centrifuge are exploited in the design of this new earthquake actuator. The paper also explains the mechanical fabrication of the actuator and the control systems that were developed in order to generate real earthquake motions. Finally, the performance of this new servo-hydraulic earthquake actuator is presented and assessed based on a wide range of earthquake input motions.

Rapid Electron Beam Reacted Tantalum/Titanium Bilayers on Silicon : Semiconductors and Semiconductor Devices

The electrical and structural characteristics of tantalum-titanium bilayers on silicon reacted by electron beam heating have been investigated over a wide range of temperature and time conditions. The reacted layers exhibit low sheet resistance and stable electrical characteristics up to at least 1100℃. Titanium starts reacting from 750℃ onwards for 100 milliseconds reaction times whereas tantalum starts reacting only above 900℃ for such short reaction times. RBS results confirm that silicon is the major diffusing species and there is no evidence for the formation of ternary silicides. Reactions have also been explored on millisecond time scales by non-isothermal heating.

Effects of multi-scattering on the performance of a single-beam acoustic manipulation device.

The effects of multiple scattering on acoustic manipulation of spherical particles using helicoidal Bessel-beams are discussed. A closed-form analytical solution is developed to calculate the acoustic radiation force resulting from a Bessel-beam on an acoustically reflective sphere, in the presence of an adjacent spherical particle, immersed in an unbounded fluid medium. The solution is based on the standard Fourier decomposition method and the effect of multi-scattering is taken into account using the addition theorem for spherical coordinates. Of particular interest here is the investigation of the effects of multiple scattering on the emergence of negative axial forces. To investigate the effects, the radiation force applied on the target particle resulting from a helicoidal Bessel-beam of different azimuthal indexes (m = 1 to 4), at different conical angles, is computed. Results are presented for soft and rigid spheres of various sizes, separated by a finite distance. Results have shown that the emergence of negative force regions is very sensitive to the level of cross-scattering between the particles. It has also been shown that in multiple scattering media, the negative axial force may occur at much smaller conical angles than previously reported for single particles, and that acoustic manipulation of soft spheres in such media may also become possible.

The Gaussian mixture MCMC particle algorithm for dynamic cluster tracking

We present a novel filtering algorithm for tracking multiple clusters of coordinated objects. Based on a Markov chain Monte Carlo (MCMC) mechanism, the new algorithm propagates a discrete approximation of the underlying filtering density. A dynamic Gaussian mixture model is utilized for representing the time-varying clustering structure. This involves point process formulations of typical behavioral moves such as birth and death of clusters as well as merging and splitting. For handling complex, possibly large scale scenarios, the sampling efficiency of the basic MCMC scheme is enhanced via the use of a Metropolis within Gibbs particle refinement step. As the proposed methodology essentially involves random set representations, a new type of estimator, termed the probability hypothesis density surface (PHDS), is derived for computing point estimates. It is further proved that this estimator is optimal in the sense of the mean relative entropy. Finally, the algorithm's performance is assessed and demonstrated in both synthetic and realistic tracking scenarios. © 2012 Elsevier Ltd. All rights reserved.

A backward-simulation based Rao-Blackwellized particle smoother for conditionally linear Gaussian models

In this article, we develop a new Rao-Blackwellized Monte Carlo smoothing algorithm for conditionally linear Gaussian models. The algorithm is based on the forward-filtering backward-simulation Monte Carlo smoother concept and performs the backward simulation directly in the marginal space of the non-Gaussian state component while treating the linear part analytically. Unlike the previously proposed backward-simulation based Rao-Blackwellized smoothing approaches, it does not require sampling of the Gaussian state component and is also able to overcome certain normalization problems of two-filter smoother based approaches. The performance of the algorithm is illustrated in a simulated application. © 2012 IFAC.

Occurrence of particle debris field during focused Ga ion beam milling of glassy carbon

To explore the machining characteristics of glassy carbon by focused ion beam (FIB), particles induced by FIB milling on glassy carbon have been studied in the current work. Nano-sized particles in the range of tens of nanometers up to 400 nm can often be found around the area subject to FIB milling. Two ion beam scanning modes - slow single scan and fast repetitive scan - have been tested. Fewer particles are found in single patterns milled in fast repetitive scan mode. For a group of test patterns milled in a sequence, it was found that a greater number of particles were deposited around sites machined early in the sequence. In situ EDX analysis of the particles showed that they were composed of C and Ga. The formation of particles is related to the debris generated at the surrounding areas, the low melting point of gallium used as FIB ion source and the high contact angle of gallium on glassy carbon induces de-wetting of Ga and the subsequent formation of Ga particles. Ultrasonic cleaning can remove over 98% of visible particles. The surface roughness (Ra) of FIB milled areas after cleaning is less than 2 nm. © 2010.

Ion beam, focused ion beam, and plasma discharge machining

Non-conventional methods of machining are used for many engineering applications where the traditional processes fail to be cost-effective. Such processes include Ion Beam Machining (IBM), focused ion beam (FIB) machining and plasma discharge machining. The mechanisms of material removal and associated hardware and software developed for industrial applications of these fascinating electro-physical and chemical machining processes are reviewed together with the latest research findings. © 2009 CIRP.

In process laser beam diagnostics (403)

Laser beam diagnosis is usually carried out off-line in order to minimise the disruption to the process being carried out. This paper presents the results of a fractional sampling device for a high power beam diagnosis system capable of measuring in process beam properties such as beam diameter, intensity and beam position. The paper discusses the application of this sampling technique for monitoring beam properties during the laser materials processing operation.