Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck's parameters.

An object-orient designed FDTD simulator: Applications to high field systems

An object-oriented finite-difference time-domain (FDTD) simulator has been developed for electromagnetic study and design applications in Magnetic Resonance Imaging. It is aimed to be a complete FDTD model of an MRI system including all high and low-frequency field generating units and electrical models of the patient. The design method is described and MRI-based numerical examples are presented to illustrate the function of the numerical solver, particular emphasis is placed on high field studies.

Evolutionary economics: Foundation of liberal economic philosophy

This is a schools brief style of introduction to evolutionary economics. It addresses the nature of evolutionary theory in relation to economics, and examines why evolutionary economists argue that market-capitalism is an evolutionary system. Finally, it argues that liberal economic philosophy has much stronger and more direct relationship with evolutionary economic analysis than neoclassical economic analysis.

Using the EM Algorithm to Train Neural Networks: Misconceptions and a New Algorithm for Multiclass Classification

The expectation-maximization (EM) algorithm has been of considerable interest in recent years as the basis for various algorithms in application areas of neural networks such as pattern recognition. However, there exists some misconceptions concerning its application to neural networks. In this paper, we clarify these misconceptions and consider how the EM algorithm can be adopted to train multilayer perceptron (MLP) and mixture of experts (ME) networks in applications to multiclass classification. We identify some situations where the application of the EM algorithm to train MLP networks may be of limited value and discuss some ways of handling the difficulties. For ME networks, it is reported in the literature that networks trained by the EM algorithm using iteratively reweighted least squares (IRLS) algorithm in the inner loop of the M-step, often performed poorly in multiclass classification. However, we found that the convergence of the IRLS algorithm is stable and that the log likelihood is monotonic increasing when a learning rate smaller than one is adopted. Also, we propose the use of an expectation-conditional maximization (ECM) algorithm to train ME networks. Its performance is demonstrated to be superior to the IRLS algorithm on some simulated and real data sets.

Utility functions on locally connected spaces

We investigate the role of local connectedness in utility theory and prove that any continuous total preorder on a locally connected separable space is continuously representable. This is a new simple criterion for the representability of continuous preferences, and is not a consequence of the standard theorems in utility theory that use conditions such as connectedness and separability, second countability, or path-connectedness. Finally we give applications to problems involving the existence of value functions in population ethics and to the problem of proving the existence of continuous utility functions in general equilibrium models with land as one of the commodities. (C) 2003 Elsevier B.V. All rights reserved.

A probabilistic switch model of information flow in social networks: Application for virtual circuits to organizational design

Network building and exchange of information by people within networks is crucial to the innovation process. Contrary to older models, in social networks the flow of information is noncontinuous and nonlinear. There are critical barriers to information flow that operate in a problematic manner. New models and new analytic tools are needed for these systems. This paper introduces the concept of virtual circuits and draws on recent concepts of network modelling and design to introduce a probabilistic switch theory that can be described using matrices. It can be used to model multistep information flow between people within organisational networks, to provide formal definitions of efficient and balanced networks and to describe distortion of information as it passes along human communication channels. The concept of multi-dimensional information space arises naturally from the use of matrices. The theory and the use of serial diagonal matrices have applications to organisational design and to the modelling of other systems. It is hypothesised that opinion leaders or creative individuals are more likely to emerge at information-rich nodes in networks. A mathematical definition of such nodes is developed and it does not invariably correspond with centrality as defined by early work on networks.

Evidence about tele-oncology applications and associated benefits for patients and their families

We conducted a systematic review of evidence on the ability of tele-oncology applications to improve access to care closer to home for adult rural patients affected by cancer. From 269 publications identified in the literature search, 54 studies met our inclusion criteria. Forty two were clinical studies (32 quantitative, eight qualitative and two that included both quantitative and qualitative methodology). Strength of evidence from quantitative clinical studies was assessed using an approach that takes account of both study design and study quality. Qualitative studies were appraised by giving scores for six areas of interest. In terms of the continuum of cancer care, the most common study area was psychosocial and supportive care. While there were a number of high quality studies, overall the evidence of benefit from tele-oncology was limited and few investigations had proceeded beyond the stage of establishing feasibility. The literature suggests some useful possibilities for new services to cancer patients in rural areas but it seems likely that these would need validation with suitable local studies.

Personalising context-aware applications

The immaturity of the field of context-aware computing means that little is known about how to incorporate appropriate personalisation mechanisms into context-aware applications. One of the main challenges is how to elicit and represent complex, context-dependent requirements, and then use the resulting representations within context-aware applications to support decision-making processes. In this paper, we characterise several approaches to personalisation of context-aware applications and introduce our research on personalisation using a novel preference model.