Soliton propagation through a disordered system:statistics of the transmission delay

We have studied the soliton propagation through a segment containing random pointlike scatterers. In the limit of small concentration of scatterers when the mean distance between the scatterers is larger than the soliton width, a method has been developed for obtaining the statistical characteristics of the soliton transmission through the segment. The method is applicable for any classical particle traversing through a disordered segment with the given velocity transformation after each act of scattering. In the case of weak scattering and relatively short disordered segment the transmission time delay of a fast soliton is mostly determined by the shifts of the soliton center after each act of scattering. For sufficiently long segments the main contribution to the delay is due to the shifts of the amplitude and velocity of a fast soliton after each scatterer. Corresponding crossover lengths for both cases of light and heavy solitons have been obtained. We have also calculated the exact probability density function of the soliton transmission time delay for a sufficiently long segment. In the case of weak identical scatterers the latter is a universal function which depends on a sole parameter—the mean number of scatterers in a segment.

Inference by belief propagation in composite systems

We devise a message passing algorithm for probabilistic inference in composite systems, consisting of a large number of variables, that exhibit weak random interactions among all variables and strong interactions with a small subset of randomly chosen variables; the relative strength of the two interactions is controlled by a free parameter. We examine the performance of the algorithm numerically on a number of systems of this type for varying mixing parameter values.

40Gbit/s single channel dispersion managed pulse propagation in standard fibre over 509km

Error free propagation of a single polarisation optical time division multiplexed 40Gbit/s dispersion managed pulse data stream over 509km has been achieved in standard (non-dispersion shifted) fibre. Dispersion compensating fibre was used after each amplifier to reduce the high local dispersion of the standard fibre. © IEE 1999.

Autosoliton propagation at 80 Gbit/s using concatenated nonlinear loop switches in standard fibre

Experimental observation of autosoliton propagation in a nonlinear switch-guided, dispersion-managed system operating at 80 Gbit/s is reported for the first time. The system is based on a strong dispersion map and supports autosoliton propagation over 3000 km.

A constructive learning algorithm based on back-propagation

There are been a resurgence of interest in the neural networks field in recent years, provoked in part by the discovery of the properties of multi-layer networks. This interest has in turn raised questions about the possibility of making neural network behaviour more adaptive by automating some of the processes involved. Prior to these particular questions, the process of determining the parameters and network architecture required to solve a given problem had been a time consuming activity. A number of researchers have attempted to address these issues by automating these processes, concentrating in particular on the dynamic selection of an appropriate network architecture.The work presented here specifically explores the area of automatic architecture selection; it focuses upon the design and implementation of a dynamic algorithm based on the Back-Propagation learning algorithm. The algorithm constructs a single hidden layer as the learning process proceeds using individual pattern error as the basis of unit insertion. This algorithm is applied to several problems of differing type and complexity and is found to produce near minimal architectures that are shown to have a high level of generalisation ability.

"Crack down on the celebrity junkies": does media coverage of celebrity drug use pose a risk to young people?

This study analysed news media content to examine the role played by celebrity drug use in young people's perceptions of drug use. We know that young people have access to discourses of drug use through music and other media which may emphasise short term gains (of pleasure or sexual success) over longer term health and social problems. This study goes beyond a simple modelling approach by using Media Framing Analysis (MFA) to take an in-depth look at the messages themselves and how they are 'framed'. New stories about Amy Winehouse's drug use were used and we conducted focus groups with young people asking them questions about drugs, celebrity and the media. Frames identified include: 'troubled genius', 'losing patience' and 'glamorization or gritty realism'. Initially, the press championed Winehouse's musical talent but soon began to tire of her recklessness; the participants tended to be unimpressed with Winehouse's drug use, characterising her as a promising artist who had 'gone off the rails'. Young people were far more critical of Winehouse than might be expected, demonstrating that concerns about the influence of celebrity drug use and its impact on future health risk behaviour among young people may have been over-simplified and exaggerated. This study illustrates the need to understand young people and their frames of reference within popular culture when designing drug awareness information relevant to them. Furthermore, it indicates that critical media skills analysis may contribute to health risk education programmes related to drug use.

Palette-colouring: a belief propagation approach

We consider a variation of the prototype combinatorial optimization problem known as graph colouring. Our optimization goal is to colour the vertices of a graph with a fixed number of colours, in a way to maximize the number of different colours present in the set of nearest neighbours of each given vertex. This problem, which we pictorially call palette-colouring, has been recently addressed as a basic example of a problem arising in the context of distributed data storage. Even though it has not been proved to be NP-complete, random search algorithms find the problem hard to solve. Heuristics based on a naive belief propagation algorithm are observed to work quite well in certain conditions. In this paper, we build upon the mentioned result, working out the correct belief propagation algorithm, which needs to take into account the many-body nature of the constraints present in this problem. This method improves the naive belief propagation approach at the cost of increased computational effort. We also investigate the emergence of a satisfiable-to-unsatisfiable 'phase transition' as a function of the vertex mean degree, for different ensembles of sparse random graphs in the large size ('thermodynamic') limit.

Crack-growth of medical-grade silicone using pure shear tests

Silicone elastomers are commonly used in the manufacture of single-piece joint replacement implants for the finger joints. However, the survivorship of these implants can be poor, with failure typically occurring from fracture of the stems. The aim of this paper was to investigate the crack growth of medical-grade silicone using pure shear tests. Two medical-grade silicones (C6-180 and Med82-5010-80) were tested. Each sample had a 20 mm crack introduced and was subjected to a sinusoidally varying tensile strain, with a minimum of 0 per cent and a maximum in the range 10 to 77 per cent. Testing was undertaken at a frequency of 10 Hz. At various times during testing, the testing machine was stopped, the number of cycles completed was noted, and the crack length measured. Graphs of crack length against number of cycles were plotted, as well as the crack growth rate against tearing energy. The results show that Med82-5010-80 is more crack resistant than C6-180. Graphs of crack growth rate against tearing energy can be used to predict the failure of these medical-grade elastomers.

Proposal and design of airy-based rocket pulses for invariant propagation in lossy dispersive media

A novel kind of Airy-based pulse with an invariant propagation in lossy dispersive media is proposed. The basic principle is based on an optical energy trade-off between different parts of the pulse caused by the chromatic dispersion, which is used to compensate the attenuation losses of the propagation medium. Although the ideal concept of the proposed pulses implies infinite pulse energy, the numerical simulations show that practical finite energy pulses can be designed to obtain a partially invariant propagation over a finite distance of propagation.

Using min-sum loopy belief propagation for decentralised supply chain formation

Modern business trends such as agile manufacturing and virtual corporations require high levels of flexibility and responsiveness to consumer demand, and require the ability to quickly and efficiently select trading partners. Automated computational techniques for supply chain formation have the potential to provide significant advantages in terms of speed and efficiency over the traditional manual approach to partner selection. Automated supply chain formation is the process of determining the participants within a supply chain and the terms of the exchanges made between these participants. In this thesis we present an automated technique for supply chain formation based upon the min-sum loopy belief propagation algorithm (LBP). LBP is a decentralised and distributed message-passing algorithm which allows participants to share their beliefs about the optimal structure of the supply chain based upon their costs, capabilities and requirements. We propose a novel framework for the application of LBP to the existing state-of-the-art case of the decentralised supply chain formation problem, and extend this framework to allow for application to further novel and established problem cases. Specifically, the contributions made by this thesis are: • A novel framework to allow for the application of LBP to the decentralised supply chain formation scenario investigated using the current state-of-the-art approach. Our experimental analysis indicates that LBP is able to match or outperform this approach for the vast majority of problem instances tested. • A new solution goal for supply chain formation in which economically motivated producers aim to maximise their profits by intelligently altering their profit margins. We propose a rational pricing strategy that allows producers to earn significantly greater profits than a comparable LBP-based profitmaking approach. • An LBP-based framework which allows the algorithm to be used to solve supply chain formation problems in which goods are exchanged in multiple units, a first for a fully decentralised technique. As well as multiple-unit exchanges, we also model in this scenario realistic constraints such as factory capacities and input-to-output ratios. LBP continues to be able to match or outperform an extended version of the existing state-of-the-art approach in this scenario. • Introduction of a dynamic supply chain formation scenario in which participants are able to alter their properties or to enter or leave the process at any time. Our results suggest that LBP is able to deal easily with individual occurences of these alterations and that performance degrades gracefully when they occur in larger numbers.