Modeling of complex-valued Wiener systems using B-spline neural network

In this brief, a new complex-valued B-spline neural network is introduced in order to model the complex-valued Wiener system using observational input/output data. The complex-valued nonlinear static function in the Wiener system is represented using the tensor product from two univariate B-spline neural networks, using the real and imaginary parts of the system input. Following the use of a simple least squares parameter initialization scheme, the Gauss-Newton algorithm is applied for the parameter estimation, which incorporates the De Boor algorithm, including both the B-spline curve and the first-order derivatives recursion. Numerical examples, including a nonlinear high-power amplifier model in communication systems, are used to demonstrate the efficacy of the proposed approaches.

August Thienemann and Loch Lomond - an approach to the design of a system for monitoring the state of north-temperate standing waters

Limnologists had an early preoccupation with lake classification. It gave a necessary structure to the many chemical and biological observations that were beginning to form the basis of one of the earliest truly environmental sciences. August Thienemann was the doyen of such classifiers and his concept with Einar Naumann of oligotrophic and eutrophic lakes remains central to the world-view that limnologists still have. Classification fell into disrepute, however, as it became clear that there would always be lakes that deviated from the prescriptions that the classifiers made for them. Continua became the de rigeur concept and lakes were seen as varying along many chemical, biological and geographic axes. Modern limnologists are comfortable with this concept. That all lakes are different guarantees an indefinite future for limnological research. For those who manage lakes and the landscapes in which they are set, however, it is not very useful. There may be as many as 300000 standing water bodies in England and Wales alone and maybe as many again in Scotland. More than 80 000 are sizable (> 1 ha). Some classification scheme to cope with these numbers is needed and, as human impacts on them increase, a system of assessing and monitoring change must be built into such a scheme. Although ways of classifying and monitoring running waters are well developed in the UK, the same is not true of standing waters. Sufficient understanding of what determines the nature and functioning of lakes exists to create a system which has intellectual credibility as well as practical usefulness. This paper outlines the thinking behind a system which will be workable on a north European basis and presents some early results.

Complex-valued B-spline neural networks for modeling and inverting Hammerstein systems

Many communication signal processing applications involve modelling and inverting complex-valued (CV) Hammerstein systems. We develops a new CV B-spline neural network approach for efficient identification of the CV Hammerstein system and effective inversion of the estimated CV Hammerstein model. Specifically, the CV nonlinear static function in the Hammerstein system is represented using the tensor product from two univariate B-spline neural networks. An efficient alternating least squares estimation method is adopted for identifying the CV linear dynamic model’s coefficients and the CV B-spline neural network’s weights, which yields the closed-form solutions for both the linear dynamic model’s coefficients and the B-spline neural network’s weights, and this estimation process is guaranteed to converge very fast to a unique minimum solution. Furthermore, an accurate inversion of the CV Hammerstein system can readily be obtained using the estimated model. In particular, the inversion of the CV nonlinear static function in the Hammerstein system can be calculated effectively using a Gaussian-Newton algorithm, which naturally incorporates the efficient De Boor algorithm with both the B-spline curve and first order derivative recursions. The effectiveness of our approach is demonstrated using the application to equalisation of Hammerstein channels.

Involving users in expert system development

The ultimate criterion of success for interactive expert systems is that they will be used, and used to effect, by individuals other than the system developers. A key ingredient of success in most systems is involving users in the specification and development of systems as they are being built. However, until recently, system designers have paid little attention to ascertaining user needs and to developing systems with corresponding functionality and appropriate interfaces to match those requirements. Although the situation is beginning to change, many developers do not know how to go about involving users, or else tackle the problem in an inadequate way. This paper discusses the need for user involvement and considers why many developers are still not involving users in an optimal way. It looks at the different ways in which users can be involved in the development process and describes how to select appropriate techniques and methods for studying users. Finally, it discusses some of the problems inherent in involving users in expert system development, and recommends an approach which incorporates both ethnographic analysis and formal user testing.

Exploring the feasibility of farmers' rights

In many developing countries, there is concern that a conventional system of plant breeders' rights provides no rewards to farmers for their role in the conservation and enhancement of agro-biodiversity. To redress this imbalance, developing countries are incorporating farmers' rights provisions in their plant variety protection legislation. This article examines the feasibility of farmers' rights provisions based on intellectual property rights. It argues that the farmers' rights provisions crafted by some developing countries will involve enormous operational difficulties, while IPR-based farmers' rights are unlikely to provide significant economic returns to farmers or farming communities. At the same time, farmers' rights provisions, as currently conceived, are likely significantly to dilute the incentives for innovation provided to institutional plant breeders.

Plant variety protection in developing countries: A view from the private seed industry in India

Many developing countries are currently engaged in designing and implementing plant variety protection systems. Encouraging private investment in plant breeding is the key rationale for extending intellectual property rights to plant varieties. However, the design of plant variety protection systems in developing countries has been dominated by concerns regarding the inequities of a plant variety protection system, especially the imbalance in the reward structure between plant breeders and farmers. The private seed industry, a key stakeholder in plant variety protection, appears to be playing only a peripheral role in the design of the intellectual property rights regime. This paper explores the potential response of the private seed industry in India to plant variety protection legislation based on a survey of major plant breeding companies. The survey finds that the private seed industry in India is generally unenthusiastic about the legislation and plant variety protection is likely to have only a very limited impact on their research profile and expenditures on plant breeding. Measures designed to curb the 'excessive' profits of breeders, farmers' rights provisions and poor prospects for enforcement of rights are seen to be seriously diluting breeders' rights, leaving few incentives for innovation. If the fundamental objective of plant variety protection is to stimulate private investment in plant breeding, then developing countries need to seriously address the question of improving appropriability of returns from investment.

Plant variety protection, innovation, and transferability: Some empirical evidence

Under the Agreement on Trade-Related Aspects of Intellectual Property Rights, all member-countries of the World Trade Organization are required to provide an "effective" system of plant variety protection within a specific time frame. In many developing countries, this has led to a divisive debate about the fundamental desirability of extending intellectual property rights to agriculture. Empirical studies on the economic impacts of plant variety protection, especially its ability to generate large private sector investments in plant breeding and to facilitate the transfer of technology, have been very limited. This paper examines two aspects of the international experience of plant variety protection: (a) the relationship between legislation, research, and development expenditures and plant variety protection grants, i.e., the innovation effect and (b) the role of plant variety protection in facilitating the flow of varieties across countries, i.e., the transferability effect.

E-commerce system simulation for construction and demolition waste exchange

This article introduces a quantitative approach to e-commerce system evaluation based on the theory of process simulation. The general concept of e-commerce system simulation is presented based on the considerations of some limitations in e-commerce system development such as the huge amount of initial investments of time and money, and the long period from business planning to system development, then to system test and operation, and finally to exact return; in other words, currently used system analysis and development method cannot tell investors about some keen attentions such as how good their e-commerce system could be, how many investment repayments they could have, and which area they should improve regarding the initial business plan. In order to exam the value and its potential effects of an e-commerce business plan, it is necessary to use a quantitative evaluation approach and the authors of this article believe that process simulation is an appropriate option. The overall objective of this article is to apply the theory of process simulation to e-commerce system evaluation, and the authors will achieve this though an experimental study on a business plan for online construction and demolition waste exchange. The methodologies adopted in this article include literature review, system analysis and development, simulation modelling and analysis, and case study. The results from this article include the concept of e-commerce system simulation, a comprehensive review of simulation methods adopted in e-commerce system evaluation, and a real case study of applying simulation to e-commerce system evaluation. Furthermore, the authors hope that the adoption and implementation of the process simulation approach can effectively support business decision-making, and improve the efficiency of e-commerce systems.

The Spanish system of food controls - its administration and enforcement

Following a number of major food safety problems in Europe, including in particular the issues of BSE and dioxin, consumers have become increasingly concerned about food safety. This has led authorities in Europe to revise their systems of food control. The establishment of the European Food Safety Authority (EFSA) is one of the main structural changes made at the moment within the European Union, and similar action at national level has been or is being taken by many EU member states. In Spain a law creating the Spanish Agency of Food Safety has been approved. This has general objectives that include the promotion of food security and offering guarantees and the provision of objective information to consumers and food businesses in the Spanish agrifood sector. This paper reviews the general structure of the current food control system in Spain. At a national level this involves three different Ministries. Spain however also has a devolved system involving Autonomous Communities the paper considers Castilla y Leon as an example. In conclusion the paper recognises that Spain has a complex system for food control. and considers that it will take time before a full evaluation of the new system is possible. (C) 2003 Elsevier Ltd. All rights reserved.

Modelling the interdependence between the stoichiometry of receptor oligomerization and ligand binding for a coexisting dimer/tetramer receptor system

Many G protein-coupled receptors have been shown to exist as oligomers, but the oligomerization state and the effects of this on receptor function are unclear. For some G protein-coupled receptors, in ligand binding assays, different radioligands provide different maximal binding capacities. Here we have developed mathematical models for co-expressed dimeric and tetrameric species of receptors. We have considered models where the dimers and tetramers are in equilibrium and where they do not interconvert and we have also considered the potential influence of the ligands on the degree of oligomerization. By analogy with agonist efficacy, we have considered ligands that promote, inhibit or have no effect on oligomerization. Cell surface receptor expression and the intrinsic capacity of receptors to oligomerize are quantitative parameters of the equations. The models can account for differences in the maximal binding capacities of radioligands in different preparations of receptors and provide a conceptual framework for simulation and data fitting in complex oligomeric receptor situations.

Requirements analysis for an e-government system to support multi-organisational collaborative groups

We present a conceptual architecture for a Group Support System (GSS) to facilitate Multi-Organisational Collaborative Groups (MOCGs) initiated by local government and including external organisations of various types. Multi-Organisational Collaborative Groups (MOCGs) consist of individuals from several organisations which have agreed to work together to solve a problem. The expectation is that more can be achieved working in harmony than separately. Work is done interdependently, rather than independently in diverse directions. Local government, faced with solving complex social problems, deploy MOCGs to enable solutions across organisational, functional, professional and juridical boundaries, by involving statutory, voluntary, community, not-for-profit and private organisations. This is not a silver bullet as it introduces new pressures. Each member organisation has its own goals, operating context and particular approaches, which can be expressed as their norms and business processes. Organisations working together must find ways of eliminating differences or mitigating their impact in order to reduce the risks of collaborative inertia and conflict. A GSS is an electronic collaboration system that facilitates group working and can offer assistance to MOCGs. Since many existing GSSs have been primarily developed for single organisation collaborative groups, even though there are some common issues, there are some difficulties peculiar to MOCGs, and others that they experience to a greater extent: a diversity of primary organisational goals among members; different funding models and other pressures; more significant differences in other information systems both technologically and in their use than single organisations; greater variation in acceptable approaches to solve problems. In this paper, we analyse the requirements of MOCGs led by local government agencies, leading to a conceptual architecture for an e-government GSS that captures the relationships between 'goal', 'context', 'norm', and 'business process'. Our models capture the dynamics of the circumstances surrounding each individual representing an organisation in a MOCG along with the dynamics of the MOCG itself as a separate community.

A tunable radial basis function model for nonlinear system identification using particle swarm optimisation

A tunable radial basis function (RBF) network model is proposed for nonlinear system identification using particle swarm optimisation (PSO). At each stage of orthogonal forward regression (OFR) model construction, PSO optimises one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is computationally more efficient.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Uniformization of affine dependence programs for parallel embedded system design

This paper is concerned with the uniformization of a system of afine recurrence equations. This transformation is used in the design (or compilation) of highly parallel embedded systems (VLSI systolic arrays, signal processing filters, etc.). In this paper, we present and implement an automatic system to achieve uniformization of systems of afine recurrence equations. We unify the results from many earlier papers, develop some theoretical extensions, and then propose effective uniformization algorithms. Our results can be used in any high level synthesis tool based on polyhedral representation of nested loop computations.