Evaluating zero error noise thresholds by replica method for Gallager code ensembles

The replica method, developed in statistical physics, is employed in conjunction with Gallager's methodology to accurately evaluate zero error noise thresholds for Gallager code ensembles. Our approach generally provides more optimistic evaluations than those reported in the information theory literature for sparse matrices; the difference vanishes as the parity check matrix becomes dense.

Density evolution for multistage CDMA multiuser detector

An analytical framework to analyze the stage-by-stage detection dynamics of the multistage CDMA multiuser detector is presented. The density evolution idea is applied to analyze the multistage detector. Message distribution is treated basically by a Gaussian approximation, but interstage correlation of messages is systematically taken into account, which turns out to provide significant improvement.

A statistical-mechanical analysis of coded CDMA with regular LDPC codes

We analyze, using the replica method of statistical mechanics, the theoretical performance of coded code-division multiple-access (CDMA) systems in which regular low-density parity-check (LDPC) codes are used for channel coding.

Statistical mechanics of broadcast channels using low-density parity-check codes

We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.

Knowledge management systems:finding a way with technology

Purpose - To consider the role of technology in knowledge management in organizations, both actual and desired. Design/methodology/approach - Facilitated, computer-supported group workshops were conducted with 78 people from ten different organizations. The objective of each workshop was to review the current state of knowledge management in that organization and develop an action plan for the future. Findings - Only three organizations had adopted a strongly technology-based "solution" to knowledge management problems, and these followed three substantially different routes. There was a clear emphasis on the use of general information technology tools to support knowledge management activities, rather than the use of tools specific to knowledge management. Research limitations/implications - Further research is needed to help organizations make best use of generally available software such as intranets and e-mail for knowledge management. Many issues, especially human, relate to the implementation of any technology. Participation was restricted to organizations that wished to produce an action plan for knowledge management. The findings may therefore represent only "average" organizations, not the very best practice. Practical implications - Each organization must resolve four tensions: Between the quantity and quality of information/knowledge, between centralized and decentralized organization, between head office and organizational knowledge, and between "push" and "pull" processes. Originality/value - Although it is the group rather than an individual that determines what counts as knowledge, hardly any previous studies of knowledge management have collected data in a group context.

Noisy random Boolean formulae:a statistical physics perspective

Properties of computing Boolean circuits composed of noisy logical gates are studied using the statistical physics methodology. A formula-growth model that gives rise to random Boolean functions is mapped onto a spin system, which facilitates the study of their typical behavior in the presence of noise. Bounds on their performance, derived in the information theory literature for specific gates, are straightforwardly retrieved, generalized and identified as the corresponding macroscopic phase transitions. The framework is employed for deriving results on error-rates at various function-depths and function sensitivity, and their dependence on the gate-type and noise model used. These are difficult to obtain via the traditional methods used in this field.

Polymer fractionation by continuous chromatography

A review is given of general chromatographic theory, the factors affecting the performance of chromatographi c columns, and aspects of scale-up of the chromatographic process. The theory of gel permeation chromatography (g. p. c.) is received, and the results of an experimental study to optimize the performance of an analytical g.p.c. system are reported. The design and construction of a novel sequential continuous chromatographic refining unit (SCCR3), for continuous liquid-liquid chromatography applications, is described. Counter-current operation is simulated by sequencing a system of inlet and outlet port functions around a connected series of fixed, 5.1 cm internal diameter x 70 cm long, glass columns. The number of columns may be varied, and, during this research, a series of either twenty or ten columns was used. Operation of the unit for continuous fractionation of a dextran polymer (M. W. - 30,000) by g.p.c. is reported using 200-400 µm diameter porous silica beads (Spherosil XOB07S) as packing, and distilled water for the mobile phase. The effects of feed concentration, feed flow rate, and mobile and stationary phase flow rates have been investigated, by means of both product, and on-column, concentrations and molecular weight distributions. The ability to operate the unit successfully at on-column concentrations as high as 20% w/v dextran has been demonstrated, and removal of both high and low molecular weight ends of a polymer feed distribution, to produce products meeting commercial specifications, has been achieved. Equivalent throughputs have been as high as 2.8 tonnes per annum for ten columns, based on continuous operation for 8000 hours per annum. A concentration dependence of the equilibrium distribution coefficient, KD observed during continuous fractionation studies, is related to evidence in the literature and experimental results obtained on a small-scale batch column. Theoretical treatments of the counter-current chromatographic process are outlined, and a preliminary computer simulation of the SCCR3 unit t is presented.

On the robustness of random Boolean formulae

Random Boolean formulae, generated by a growth process of noisy logical gates are analyzed using the generating functional methodology of statistical physics. We study the type of functions generated for different input distributions, their robustness for a given level of gate error and its dependence on the formulae depth and complexity and the gates used. Bounds on their performance, derived in the information theory literature for specific gates, are straightforwardly retrieved, generalized and identified as the corresponding typical-case phase transitions. Results for error-rates, function-depth and sensitivity of the generated functions are obtained for various gate-type and noise models. © 2010 IOP Publishing Ltd.

The production of fructose from carbohydrate feedstocks

A review of the general chromatographic theory and of continuous chromatographic techniques has been carried out. Three methods of inversion of sucrose to glucose and fructose in beet molasses were explored. These methods were the inversion of sucrose using the enzyme invertase, by the use of hydrochloric acid and the use of the resin Amberlite IR118 in the H+ form. The preferred method on economic and purity considerations was by the use of the enzyme invertase. The continuous chromatographic separation of inverted beet molasses resulting in a fructose rich product and a product containing glucose and other non-sugars was carried out using a semi-continuous counter-current chromatographic refiner (SCCR6), consisting of ten 10.8cm x 75cm long stainless steel columns packed with a calcium charged 8% cross-linked polystyrene resin Zerolit SRC 14. Based on the literature this is the first time such a continuous separation has been attempted. It was found that the cations present in beet molasses displaced the calcium ions from the resin resulting in poor separation of the glucose and fructose. Three methods of maintaining the calcium form of the resin during the continuous operation of the equipment were established. Passing a solution of calcium nitrate through the purge column for half a switch period was found to be most effective as there was no contamination of the main fructose rich product and the product concentrations were increased by 50%. When a 53% total solids (53 Brix) molasses feedstock was used, the throughput was 34.13kg sugar solids per m3 of resin per hour. Product purities of 97% fructose in fructose rich (FRP) and 96% glucose in the glucose rich (GRP) products were obtained with product concentrations of 10.93 %w/w for the FRP and 10.07 %w/w for the GRP. The effects of flowrates, temperature and background sugar concentration on the distribution coefficients of fructose, glucose, betaine and an ionic component of beet molasses were evaluated and general relationships derived. The computer simulation of inverted beet molasses separations on an SCCR system has been carried out successfully.

Statistical physics of error-correcting codes

In this thesis we use statistical physics techniques to study the typical performance of four families of error-correcting codes based on very sparse linear transformations: Sourlas codes, Gallager codes, MacKay-Neal codes and Kanter-Saad codes. We map the decoding problem onto an Ising spin system with many-spins interactions. We then employ the replica method to calculate averages over the quenched disorder represented by the code constructions, the arbitrary messages and the random noise vectors. We find, as the noise level increases, a phase transition between successful decoding and failure phases. This phase transition coincides with upper bounds derived in the information theory literature in most of the cases. We connect the practical decoding algorithm known as probability propagation with the task of finding local minima of the related Bethe free-energy. We show that the practical decoding thresholds correspond to noise levels where suboptimal minima of the free-energy emerge. Simulations of practical decoding scenarios using probability propagation agree with theoretical predictions of the replica symmetric theory. The typical performance predicted by the thermodynamic phase transitions is shown to be attainable in computation times that grow exponentially with the system size. We use the insights obtained to design a method to calculate the performance and optimise parameters of the high performance codes proposed by Kanter and Saad.

Analysis of magnetoencephaoographic data as a nonlinear dynamical system

This thesis presents the results from an investigation into the merits of analysing Magnetoencephalographic (MEG) data in the context of dynamical systems theory. MEG is the study of both the methods for the measurement of minute magnetic flux variations at the scalp, resulting from neuro-electric activity in the neocortex, as well as the techniques required to process and extract useful information from these measurements. As a result of its unique mode of action - by directly measuring neuronal activity via the resulting magnetic field fluctuations - MEG possesses a number of useful qualities which could potentially make it a powerful addition to any brain researcher's arsenal. Unfortunately, MEG research has so far failed to fulfil its early promise, being hindered in its progress by a variety of factors. Conventionally, the analysis of MEG has been dominated by the search for activity in certain spectral bands - the so-called alpha, delta, beta, etc that are commonly referred to in both academic and lay publications. Other efforts have centred upon generating optimal fits of "equivalent current dipoles" that best explain the observed field distribution. Many of these approaches carry the implicit assumption that the dynamics which result in the observed time series are linear. This is despite a variety of reasons which suggest that nonlinearity might be present in MEG recordings. By using methods that allow for nonlinear dynamics, the research described in this thesis avoids these restrictive linearity assumptions. A crucial concept underpinning this project is the belief that MEG recordings are mere observations of the evolution of the true underlying state, which is unobservable and is assumed to reflect some abstract brain cognitive state. Further, we maintain that it is unreasonable to expect these processes to be adequately described in the traditional way: as a linear sum of a large number of frequency generators. One of the main objectives of this thesis will be to prove that much more effective and powerful analysis of MEG can be achieved if one were to assume the presence of both linear and nonlinear characteristics from the outset. Our position is that the combined action of a relatively small number of these generators, coupled with external and dynamic noise sources, is more than sufficient to account for the complexity observed in the MEG recordings. Another problem that has plagued MEG researchers is the extremely low signal to noise ratios that are obtained. As the magnetic flux variations resulting from actual cortical processes can be extremely minute, the measuring devices used in MEG are, necessarily, extremely sensitive. The unfortunate side-effect of this is that even commonplace phenomena such as the earth's geomagnetic field can easily swamp signals of interest. This problem is commonly addressed by averaging over a large number of recordings. However, this has a number of notable drawbacks. In particular, it is difficult to synchronise high frequency activity which might be of interest, and often these signals will be cancelled out by the averaging process. Other problems that have been encountered are high costs and low portability of state-of-the- art multichannel machines. The result of this is that the use of MEG has, hitherto, been restricted to large institutions which are able to afford the high costs associated with the procurement and maintenance of these machines. In this project, we seek to address these issues by working almost exclusively with single channel, unaveraged MEG data. We demonstrate the applicability of a variety of methods originating from the fields of signal processing, dynamical systems, information theory and neural networks, to the analysis of MEG data. It is noteworthy that while modern signal processing tools such as independent component analysis, topographic maps and latent variable modelling have enjoyed extensive success in a variety of research areas from financial time series modelling to the analysis of sun spot activity, their use in MEG analysis has thus far been extremely limited. It is hoped that this work will help to remedy this oversight.

The application of artificial neural networks to the interpretation and classification of freshwater benthic invertebrate communities

This thesis presents a thorough and principled investigation into the application of artificial neural networks to the biological monitoring of freshwater. It contains original ideas on the classification and interpretation of benthic macroinvertebrates, and aims to demonstrate their superiority over the biotic systems currently used in the UK to report river water quality. The conceptual basis of a new biological classification system is described, and a full review and analysis of a number of river data sets is presented. The biological classification is compared to the common biotic systems using data from the Upper Trent catchment. This data contained 292 expertly classified invertebrate samples identified to mixed taxonomic levels. The neural network experimental work concentrates on the classification of the invertebrate samples into biological class, where only a subset of the sample is used to form the classification. Other experimentation is conducted into the identification of novel input samples, the classification of samples from different biotopes and the use of prior information in the neural network models. The biological classification is shown to provide an intuitive interpretation of a graphical representation, generated without reference to the class labels, of the Upper Trent data. The selection of key indicator taxa is considered using three different approaches; one novel, one from information theory and one from classical statistical methods. Good indicators of quality class based on these analyses are found to be in good agreement with those chosen by a domain expert. The change in information associated with different levels of identification and enumeration of taxa is quantified. The feasibility of using neural network classifiers and predictors to develop numeric criteria for the biological assessment of sediment contamination in the Great Lakes is also investigated.

The interactive effect of workplace stressors and mood on creativity and implementation activities: a dual level approach

This thesis analyses the impact of workplace stressors and mood on innovation activities. Based on three competitive frameworks offered by cognitive spreading activation theory, mood repair perspective, and mood-as-information theory, different sets of predictions are developed. These hypotheses are tested in a field study involving 41 R&D teams and 123 individual R&D workers, and in an experimental study involving 54 teams of students. Results of the field study suggest that stressors and mood interact to predict innovation activities in such a way that with increasing stressors a high positive ( or negative) mood is more detrimental to innovation activities than a low positive (or negative) mood, lending support to the mood repair perspective. These effects are found for both individuals and teams. In the experimental study this effect is replicated and potential boundary conditions and mediators are tested. In addition, this thesis includes the development of an instrument to assess creativity and implementation activities within the realm of task-related innovative performance.

Approaching the non-linear Shannon limit

We review the recent progress of information theory in optical communications, and describe the current experimental results and associated advances in various individual technologies which increase the information capacity. We confirm the widely held belief that the reported capacities are approaching the fundamental limits imposed by signal-to-noise ratio and the distributed non-linearity of conventional optical fibres, resulting in the reduction in the growth rate of communication capacity. We also discuss the techniques which are promising to increase and/or approach the information capacity limit.

Basic principles of design and functioning of multifunctional laser diagnostic system for non-invasive medical spectrophotometry

The devising of a general engineering theory of multifunctional diagnostic systems for non-invasive medical spectrophotometry is an important and promising direction of modern biomedical engineering. We aim in this study to formalize in scientific engineering terms objectives for multifunctional laser non-invasive diagnostic system (MLNDS). The structure-functional model as well as a task-function of generalized MLNDS was formulated and developed. The key role of the system software for MLNDS general architecture at steps of ideological-technical designing has been proved. The basic principles of block-modules composition of MLNDS hardware are suggested as well. © 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).