Point-wise confidence interval estimation by neural networks: A comparative study based on automotive engine calibration.

In developing neural network techniques for real world applications it is still very rare to see estimates of confidence placed on the neural network predictions. This is a major deficiency, especially in safety-critical systems. In this paper we explore three distinct methods of producing point-wise confidence intervals using neural networks. We compare and contrast Bayesian, Gaussian Process and Predictive error bars evaluated on real data. The problem domain is concerned with the calibration of a real automotive engine management system for both air-fuel ratio determination and on-line ignition timing. This problem requires real-time control and is a good candidate for exploring the use of confidence predictions due to its safety-critical nature.

Delay estimation for multivariate time series

Most traditional methods for extracting the relationships between two time series are based on cross-correlation. In a non-linear non-stationary environment, these techniques are not sufficient. We show in this paper how to use hidden Markov models (HMMs) to identify the lag (or delay) between different variables for such data. We first present a method using maximum likelihood estimation and propose a simple algorithm which is capable of identifying associations between variables. We also adopt an information-theoretic approach and develop a novel procedure for training HMMs to maximise the mutual information between delayed time series. Both methods are successfully applied to real data. We model the oil drilling process with HMMs and estimate a crucial parameter, namely the lag for return.

Emulation of dynamic computer models with multivariate output

This preliminary report describes work carried out as part of work package 1.2 of the MUCM research project. The report is split in two parts: the ?rst part (Sections 1 and 2) summarises the state of the art in emulation of computer models, while the second presents some initial work on the emulation of dynamic models. In the ?rst part, we describe the basics of emulation, introduce the notation and put together the key results for the emulation of models with single and multiple outputs, with or without the use of mean function. In the second part, we present preliminary results on the chaotic Lorenz 63 model. We look at emulation of a single time step, and repeated application of the emulator for sequential predic- tion. After some design considerations, the emulator is compared with the exact simulator on a number of runs to assess its performance. Several general issues related to emulating dynamic models are raised and discussed. Current work on the larger Lorenz 96 model (40 variables) is presented in the context of dimension reduction, with results to be provided in a follow-up report. The notation used in this report are summarised in appendix.

The use of multivariate methods in the identification of subtypes of Alzheimer's disease: a comparison of principal components and cluster analysis

Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer's disease (AD). To compare the two methods, 78 cases of AD were analyzed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.

Statnote 17: using a regression line for prediction and calibration

Two types of prediction problem can be solved using a regression line viz., prediction of the ‘population’ regression line at the point ‘x’ and prediction of an ‘individual’ new member of the population ‘y1’ for which ‘x1’ has been measured. The second problem is probably the most commonly encountered and the most relevant to calibration studies. A regression line is likely to be most useful for calibration if the range of values of the X variable is large, if there is a good representation of the ‘x,y’ values across the range of X, and if several estimates of ‘y’ are made at each ‘x’. It is poor statistical practice to use a regression line for calibration or prediction beyond the limits of the data.

A new variational radial basis function approximation for inference in multivariate diffusions

In this paper we present a radial basis function based extension to a recently proposed variational algorithm for approximate inference for diffusion processes. Inference, for state and in particular (hyper-) parameters, in diffusion processes is a challenging and crucial task. We show that the new radial basis function approximation based algorithm converges to the original algorithm and has beneficial characteristics when estimating (hyper-)parameters. We validate our new approach on a nonlinear double well potential dynamical system.

Prediction of Klason lignin and lignin thermal degradation products by Py-GC/MS in a collection of Lolium and Festuca grasses

A rapid method for the analysis of biomass feedstocks was established to identify the quality of the pyrolysis products likely to impact on bio-oil production. A total of 15 Lolium and Festuca grasses known to exhibit a range of Klason lignin contents were analysed by pyroprobe-GC/MS (Py-GC/MS) to determine the composition of the thermal degradation products of lignin. The identification of key marker compounds which are the derivatives of the three major lignin subunits (G, H, and S) allowed pyroprobe-GC/MS to be statistically correlated to the Klason lignin content of the biomass using the partial least-square method to produce a calibration model. Data from this multivariate modelling procedure was then applied to identify likely "key marker" ions representative of the lignin subunits from the mass spectral data. The combined total abundance of the identified key markers for the lignin subunits exhibited a linear relationship with the Klason lignin content. In addition the effect of alkali metal concentration on optimum pyrolysis characteristics was also examined. Washing of the grass samples removed approximately 70% of the metals and changed the characteristics of the thermal degradation process and products. Overall the data indicate that both the organic and inorganic specification of the biofuel impacts on the pyrolysis process and that pyroprobe-GC/MS is a suitable analytical technique to asses lignin composition. © 2007 Elsevier B.V. All rights reserved.

Have the GIPSI settled down? Breaks and multivariate stochastic volatility models for, and not against, the European financial integration

We investigate the integration of the European peripheral financial markets with Germany, France, and the UK using a combination of tests for structural breaks and return correlations derived from several multivariate stochastic volatility models. Our findings suggest that financial integration intensified in anticipation of the Euro, further strengthened by the EMU inception, and amplified in response to the 2007/2008 financial crisis. Hence, no evidence is found of decoupling of the equity markets in more troubled European countries from the core. Interestingly, the UK, despite staying outside the EMU, is not worse integrated with the GIPSI than Germany or France. © 2013 Elsevier B.V.

A multivariate examination of the relationship between strategic planning and organisational performance

Strategic planning and more specifically, the impact of strategic planning on organisational performance has been the subject of significant academic interest since the early 1970's. However, despite the significant amount of previous work examining the relationship between strategic planning and organisational performance, a comprehensive literature review identified a number of areas where contributions to the domain of study could be made. In overview, the main areas for further study identified from the literature review were a) a further examination of both the dimensionality and conceptualisation of strategic planning and organisational performance and b) a further, multivariate, examination of the relationship between strategic planning and performance, to capture the newly identified dimensionality. In addition to the previously identified strategic planning and organisational performance constructs, a comprehensive literature based assessment was undertaken and five main areas were identified for further examination, these were a) organisational b) comprehensive strategic choice, c) the quality of strategic options generated, d) political behavior and e) implementation success. From this, a conceptual model incorporating a set of hypotheses to be tested was formulated. In order to test the conceptual model specified and also the stated hypotheses, data gathering was undertaken. The quantitative phase of the research involved a mail survey of senior managers in medium to large UK based organisations, of which a total of 366 fully useable responses were received. Following rigorous individual construct validity and reliability testing, the complete conceptual model was tested using latent variable path analysis. The results for the individual hypotheses and also the complete conceptual model were most encouraging. The findings, theoretical and managerial implications, limitations and directions for future research are discussed.

The development of calibration and adaptive filtering procedures for neuromagnetic studies of human visual function

This thesis first considers the calibration and signal processing requirements of a neuromagnetometer for the measurement of human visual function. Gradiometer calibration using straight wire grids is examined and optimal grid configurations determined, given realistic constructional tolerances. Simulations show that for gradiometer balance of 1:104 and wire spacing error of 0.25mm the achievable calibration accuracy of gain is 0.3%, of position is 0.3mm and of orientation is 0.6°. Practical results with a 19-channel 2nd-order gradiometer based system exceed this performance. The real-time application of adaptive reference noise cancellation filtering to running-average evoked response data is examined. In the steady state, the filter can be assumed to be driven by a non-stationary step input arising at epoch boundaries. Based on empirical measures of this driving step an optimal progression for the filter time constant is proposed which improves upon fixed time constant filter performance. The incorporation of the time-derivatives of the reference channels was found to improve the performance of the adaptive filtering algorithm by 15-20% for unaveraged data, falling to 5% with averaging. The thesis concludes with a neuromagnetic investigation of evoked cortical responses to chromatic and luminance grating stimuli. The global magnetic field power of evoked responses to the onset of sinusoidal gratings was shown to have distinct chromatic and luminance sensitive components. Analysis of the results, using a single equivalent current dipole model, shows that these components arise from activity within two distinct cortical locations. Co-registration of the resulting current source localisations with MRI shows a chromatically responsive area lying along the midline within the calcarine fissure, possibly extending onto the lingual and cuneal gyri. It is postulated that this area is the human homologue of the primate cortical area V4.

Fabrication of high quality optical coherence tomography (OCT) calibration artefacts using femtosecond inscription

Optical coherence tomography (OCT) is a non-invasive three-dimensional imaging system that is capable of producing high resolution in-vivo images. OCT is approved for use in clinical trials in Japan, USA and Europe. For OCT to be used effectively in a clinical diagnosis, a method of standardisation is required to assess the performance across different systems. This standardisation can be implemented using highly accurate and reproducible artefacts for calibration at both installation and throughout the lifetime of a system. Femtosecond lasers can write highly reproducible and highly localised micro-structured calibration artefacts within a transparent media. We report on the fabrication of high quality OCT calibration artefacts in fused silica using a femtosecond laser. The calibration artefacts were written in fused silica due to its high purity and ability to withstand high energy femtosecond pulses. An Amplitude Systemes s-Pulse Yb:YAG femtosecond laser with an operating wavelength of 1026 nm was used to inscribe three dimensional patterns within the highly optically transmissive substrate. Four unique artefacts have been designed to measure a wide variety of parameters, including the points spread function (PSF), modulation transfer function (MTF), sensitivity, distortion and resolution - key parameters which define the performance of the OCT. The calibration artefacts have been characterised using an optical microscope and tested on a swept source OCT. The results demonstrate that the femtosecond laser inscribed artefacts have the potential of quantitatively and qualitatively validating the performance of any OCT system.

Three-dimensional calibration targets for optical coherence tomography

The recent expansion of clinical applications for optical coherence tomography (OCT) is driving the development of approaches for consistent image acquisition. There is a simultaneous need for time-stable, easy-to-use imaging targets for calibration and standardization of OCT devices. We present calibration targets consisting of three-dimensional structures etched into nanoparticle-embedded resin. Spherical iron oxide nanoparticles with a predominant particle diameter of 400 nm were homogeneously dispersed in a two part polyurethane resin and allowed to harden overnight. These samples were then etched using a precision micromachining femtosecond laser with a center wavelength of 1026 nm, 100kHz repetition rate and 450 fs pulse duration. A series of lines in depth were etched, varying the percentage of inscription energy and speed of the translation stage moving the target with respect to the laser. Samples were imaged with a dual wavelength spectral-domain OCT system and point-spread function of nanoparticles within the target was measured.

Managers' perceptual errors revisited:the role of knowledge calibration

Insights from the stream of research on knowledge calibration, which refers to the correspondence between accuracy and confidence in knowledge, enable a better understanding of consequences of inaccurate perceptions of managers. This paper examines the consequences of inaccurate managerial knowledge through the lens of knowledge calibration. Specifically, the paper examines the antecedent role of miscalibration of knowledge in strategy formation. It is postulated that miscalibrated managers who overestimate external factors and display a high level of confidence in their estimates are likely to enact strategies that are relatively more evolutionary and incremental in nature, whereas miscalibrated managers who overestimate internal factors and display a high level of confidence in their estimates are likely to enact strategies that are relatively more discontinuous and disruptive in nature. Perspectives from social cognitive theory provide support for the underlying processes. The paper, in part, explains the paradox of the prevalence of inaccurate managerial perceptions and efficacious performance. It also advances the literature on strategy formation through the application of the construct of knowledge calibration.

Calibration of consumer knowledge of the web

Calibration of consumer knowledge of the web refers to the correspondence between accuracy and confidence in knowledge of the web. Being well-calibrated means that a person is realistic in his or her assessment of the level of knowledge that he or she possesses. This study finds that involvement leads to better calibration and that calibration is higher for procedural knowledge and common knowledge, as compared to declarative knowledge and specialized knowledge. Neither usage, nor experience, has any effect on calibration of knowledge of the web. No difference in calibration is observed between genders. But, in agreement with previous findings, this study also finds that males are more confident in their knowledge of the web. The results point out that calibration could be more a function of knowledge-specific factors and less that of individual-specific factors. The study also identifies flow and frustration with the web as consequences of calibration of knowledge of the web and draws the attention of future researchers to examine these aspects.