On the theory of autosoliton propagation in optical fibers guided by in-line nonlinear devices

A theoretical model is developed to describe the propagation of ultra-short optical pulses in fiber transmission systems in the quasi-linear regime, with periodically inserted in-line lumped nonlinear optical devices. Stable autosoliton solutions are obtained for a particular application of the general theory.

Information-theory analysis of skewed coding for suppression of pattern-dependent errors in digital communications

We present information-theory analysis of the tradeoff between bit-error rate improvement and the data-rate loss using skewed channel coding to suppress pattern-dependent errors in digital communications. Without loss of generality, we apply developed general theory to the particular example of a high-speed fiber communication system with a strong patterning effect. © 2007 IEEE.

On the theory of autosoliton propagation in optical fibers guided by in-line nonlinear devices

A theoretical model is developed to describe the propagation of ultra-short optical pulses in fiber transmission systems in the quasi-linear regime, with periodically inserted in-line lumped nonlinear optical devices. Stable autosoliton solutions are obtained for a particular application of the general theory.

Bayesian invariant measurements of generalisation

The problem of evaluating different learning rules and other statistical estimators is analysed. A new general theory of statistical inference is developed by combining Bayesian decision theory with information geometry. It is coherent and invariant. For each sample a unique ideal estimate exists and is given by an average over the posterior. An optimal estimate within a model is given by a projection of the ideal estimate. The ideal estimate is a sufficient statistic of the posterior, so practical learning rules are functions of the ideal estimator. If the sole purpose of learning is to extract information from the data, the learning rule must also approximate the ideal estimator. This framework is applicable to both Bayesian and non-Bayesian methods, with arbitrary statistical models, and to supervised, unsupervised and reinforcement learning schemes.

The data type of spatial objects

A spatial object consists of data assigned to points in a space. Spatial objects, such as memory states and three dimensional graphical scenes, are diverse and ubiquitous in computing. We develop a general theory of spatial objects by modelling abstract data types of spatial objects as topological algebras of functions. One useful algebra is that of continuous functions, with operations derived from operations on space and data, and equipped with the compact-open topology. Terms are used as abstract syntax for defining spatial objects and conditional equational specifications are used for reasoning. We pose a completeness problem: Given a selection of operations on spatial objects, do the terms approximate all the spatial objects to arbitrary accuracy? We give some general methods for solving the problem and consider their application to spatial objects with real number attributes. © 2011 British Computer Society.

Conditional probability calculations for the nonlinear Schrödinger equation with additive noise

The method for the computation of the conditional probability density function for the nonlinear Schrödinger equation with additive noise is developed. We present in a constructive form the conditional probability density function in the limit of small noise and analytically derive it in a weakly nonlinear case. The general theory results are illustrated using fiber-optic communications as a particular, albeit practically very important, example.

Advanced mean field methods:theory and practice

A major problem in modern probabilistic modeling is the huge computational complexity involved in typical calculations with multivariate probability distributions when the number of random variables is large. Because exact computations are infeasible in such cases and Monte Carlo sampling techniques may reach their limits, there is a need for methods that allow for efficient approximate computations. One of the simplest approximations is based on the mean field method, which has a long history in statistical physics. The method is widely used, particularly in the growing field of graphical models. Researchers from disciplines such as statistical physics, computer science, and mathematical statistics are studying ways to improve this and related methods and are exploring novel application areas. Leading approaches include the variational approach, which goes beyond factorizable distributions to achieve systematic improvements; the TAP (Thouless-Anderson-Palmer) approach, which incorporates correlations by including effective reaction terms in the mean field theory; and the more general methods of graphical models. Bringing together ideas and techniques from these diverse disciplines, this book covers the theoretical foundations of advanced mean field methods, explores the relation between the different approaches, examines the quality of the approximation obtained, and demonstrates their application to various areas of probabilistic modeling.

Bridging the gap from the general to the specific by linking knowledge management to business process

A phenomenon common to almost all fields is that there is a gap between theory and practical implementation. However, this is a particular problem in knowledge management, where much of the literature consists of general principles written in the context of a ‘knowledge world’ that has few, if any, references to how to carry out knowledge management in organisations. In this chapter, we put forward the view that the best way to bridge this gap between general principles and the specific issues facing a given organisation is to link knowledge management to the organisation’s business processes. After briefly reviewing, and rejecting alternative ways in which this gap might be bridged, the chapter goes on to explain the justification for, and the potential benefits and snags of, linking knowledge management to business processes. Successful and unsuccessful examples are presented. We concentrate especially on the issues of establishing what knowledge is relevant to an organisation at present, the need for organisational learning to cope with the inevitable change, and the additional problems posed by the growing internationalisation of operations. We conclude that linking knowledge management in terms of business processes is the best route for organisations to follow, but that it is not the answer to all knowledge management problems, especially where different cultures and/or cultural change are involved.

On the opportunism-independent theory of the firm

Previous developments in the opportunism-independent theory of the firm are either restricted to special cases or are derived from the capabilities or resource-based perspective. However, a more general opportunism-independent approach can be developed, based on the work of Demsetz and Coase, which is nevertheless contractual in nature. This depends on 'direction', that is, deriving economic value by permitting one set of actors to direct the activities of another, and of non-human factors of production. Direction helps to explain not only firm boundaries and organisation, but also the existence of firms, without appealing to opportunism or moral hazard. The paper also considers the extent to which it is meaningful to speak of 'contractual' theories in the absence of opportunism, and whether this analysis can be extended beyond the employment contract to encompass ownership of assets by the firm. © The Author 2005. Published by Oxford University Press on behalf of the Cambridge Political Economy Society. All rights reserved.

Introduction to the theory and application of data envelopment analysis:a foundation text with integrated software

The book aims to introduce the reader to DEA in the most accessible manner possible. It is specifically aimed at those who have had no prior exposure to DEA and wish to learn its essentials, how it works, its key uses, and the mechanics of using it. The latter will include using DEA software. Students on degree or training courses will find the book especially helpful. The same is true of practitioners engaging in comparative efficiency assessments and performance management within their organisation. Examples are used throughout the book to help the reader consolidate the concepts covered. Table of content: List of Tables. List of Figures. Preface. Abbreviations. 1. Introduction to Performance Measurement. 2. Definitions of Efficiency and Related Measures. 3. Data Envelopment Analysis Under Constant Returns to Scale: Basic Principles. 4. Data Envelopment Analysis under Constant Returns to Scale: General Models. 5. Using Data Envelopment Analysis in Practice. 6. Data Envelopment Analysis under Variable Returns to Scale. 7. Assessing Policy Effectiveness and Productivity Change Using DEA. 8. Incorporating Value Judgements in DEA Assessments. 9. Extensions to Basic DEA Models. 10. A Limited User Guide for Warwick DEA Software. Author Index. Topic Index. References.

The classical theory of field evaporation

The field evaporation literature has been carefully analysed and is shown to contain various confusions. After redefining consistent terminology, this thesis investigates the mechanisms of field evaporation, in particular, the relevance of the theoretical mechanisms by analysing the available experimental data. A new formalism `extended image-hump formalism' is developed and is used to devise several tests of whether the image-hump mechanism is operating. The general conclusion is that in most cases the Mueller mechanism is not operating and escape takes place via Gomer-type mechanisms.

Prediction of the equilibrium structures and photomagnetic properties of the Prussian blue analogue RbMn[Fe(CN)6] by density functional theory

A periodic density functional theory method using the B3LYP hybrid exchange-correlation potential is applied to the Prussian blue analogue RbMn[Fe(CN)6] to evaluate the suitability of the method for studying, and predicting, the photomagnetic behavior of Prussian blue analogues and related materials. The method allows correct description of the equilibrium structures of the different electronic configurations with regard to the cell parameters and bond distances. In agreement with the experimental data, the calculations have shown that the low-temperature phase (LT; Fe(2+)(t(6)2g, S = 0)-CN-Mn(3+)(t(3)2g e(1)g, S = 2)) is the stable phase at low temperature instead of the high-temperature phase (HT; Fe(3+)(t(5)2g, S = 1/2)-CN-Mn(2+)(t(3)2g e(2)g, S = 5/2)). Additionally, the method gives an estimation for the enthalpy difference (HT LT) with a value of 143 J mol(-1) K(-1). The comparison of our calculations with experimental data from the literature and from our calorimetric and X-ray photoelectron spectroscopy measurements on the Rb0.97Mn[Fe(CN)6]0.98 x 1.03 H2O compound is analyzed, and in general, a satisfactory agreement is obtained. The method also predicts the metastable nature of the electronic configuration of the high-temperature phase, a necessary condition to photoinduce that phase at low temperatures. It gives a photoactivation energy of 2.36 eV, which is in agreement with photoinduced demagnetization produced by a green laser.

A mean field theory of coded CDMA systems

We present a mean field theory of code-division multiple access (CDMA) systems with error-control coding. On the basis of the relation between the free energy and mutual information, we obtain an analytical expression of the maximum spectral efficiency of the coded CDMA system, from which a mean field description of the coded CDMA system is provided in terms of a bank of scalar Gaussian channels whose variances in general vary at different code symbol positions. Regular low-density parity-check (LDPC)-coded CDMA systems are also discussed as an example of the coded CDMA systems.

Enhancing creativity in a general work environment : the role of problem-solving demand

Prior research suggests management can employ cognitively demanding job attributes to promote employee creativity. However, it is not clear what specific type of cognitive demand is particularly important for creativity, what processes underpin the relationship between demanding job conditions and creativity and what factors lead to employee perceptions of demanding job attributes. This research sets out to address the aforementioned issues by examining: (i) problem-solving demand (PDS), a specific type of cognitive demand, and the processes that link PSD to creativity, and (ii) antecedents to PSD. Based on social cognitive theory, PSD was hypothesized to be positively related to creativity through the motivational mechanism of creative self-efficacy. However, the relationship between PSD and creative self-efficacy was hypothesized to be contingent on levels of intrinsic motivation. Social information processing perspective and the job crafting model were used to identify antecedents of PSD. Consequently, two social-contextual factors (supervisor developmental feedback and job autonomy) and one individual factor (proactive personality) were hypothesized to be precursors to PSD perceptions. The theorized model was tested with data obtained from a sample of 270 employees and their supervisors from 3 organisations in the People’s Republic of China. Regression results revealed that PSD was positively related to creativity but this relationship was partially mediated by creative self-efficacy. Additionally, intrinsic motivation moderated the relationship between PSD and creative self-efficacy such that the relationship was stronger for individuals high rather than low in intrinsic motivation. The findings represent a productive first step in identifying a specific cognitive demand that is conducive to employee creativity. In addition, the findings contribute to the literature by identifying a psychological mechanism that may link cognitively demanding job attributes and creativity.

Reconstruction of an unsteady flow from incomplete boundary data:Part I. Theory

Purpose – To propose and investigate a stable numerical procedure for the reconstruction of the velocity of a viscous incompressible fluid flow in linear hydrodynamics from knowledge of the velocity and fluid stress force given on a part of the boundary of a bounded domain. Design/methodology/approach – Earlier works have involved the similar problem but for stationary case (time-independent fluid flow). Extending these ideas a procedure is proposed and investigated also for the time-dependent case. Findings – The paper finds a novel variation method for the Cauchy problem. It proves convergence and also proposes a new boundary element method. Research limitations/implications – The fluid flow domain is limited to annular domains; this restriction can be removed undertaking analyses in appropriate weighted spaces to incorporate singularities that can occur on general bounded domains. Future work involves numerical investigations and also to consider Oseen type flow. A challenging problem is to consider non-linear Navier-Stokes equation. Practical implications – Fluid flow problems where data are known only on a part of the boundary occur in a range of engineering situations such as colloidal suspension and swimming of microorganisms. For example, the solution domain can be the region between to spheres where only the outer sphere is accessible for measurements. Originality/value – A novel variational method for the Cauchy problem is proposed which preserves the unsteady Stokes operator, convergence is proved and using recent for the fundamental solution for unsteady Stokes system, a new boundary element method for this system is also proposed.