Global exponential periodicity of a class of neural networks with recent-history distributed delays

In this paper, we propose to study a class of neural networks with recent-history distributed delays. A sufficient condition is derived for the global exponential periodicity of the proposed neural networks, which has the advantage that it assumes neither the differentiability nor monotonicity of the activation function of each neuron nor the symmetry of the feedback matrix or delayed feedback matrix. Our criterion is shown to be valid by applying it to an illustrative system. (c) 2005 Elsevier Ltd. All rights reserved.

Error estimates for a fully discrete spectral scheme for a class of nonlinear, nonlocal dispersive wave equations

We analyze a fully discrete spectral method for the numerical solution of the initial- and periodic boundary-value problem for two nonlinear, nonlocal, dispersive wave equations, the Benjamin–Ono and the Intermediate Long Wave equations. The equations are discretized in space by the standard Fourier–Galerkin spectral method and in time by the explicit leap-frog scheme. For the resulting fully discrete, conditionally stable scheme we prove an L2-error bound of spectral accuracy in space and of second-order accuracy in time.

On a class of non-self-adjoint periodic eigenproblems with boundary and interior singularities

We prove that all the eigenvalues of a certain highly non-self-adjoint Sturm–Liouville differential operator are real. The results presented are motivated by and extend those recently found by various authors (Benilov et al. (2003) [3], Davies (2007) [7] and Weir (2008) [18]) on the stability of a model describing small oscillations of a thin layer of fluid inside a rotating cylinder.

On a class of nonselfadjoint periodic boundary value problems with discrete real spectrum

In a previous paper (J. of Differential Equations, Vol. 249 (2010), 3081-3098) we examined a family of periodic Sturm-Liouville problems with boundary and interior singularities which are highly non-self-adjoint but have only real eigenvalues. We now establish Schatten class properties of the associated resolvent operator.

Power to the people: working-class demand for household power in 1930s Britain

The 1930s witnessed an intense struggle between gas and electricity suppliers for the working class market, where the incumbent utility—gas—was also a reasonably efficient (and cheaper) General Purpose Technology for most domestic uses. Local monopolies for each supplier boosted substitution effects between fuel types—as alternative fuels constituted the only local competition. Using newly-rediscovered returns from a major national household expenditure survey, we employ geographically-determined instrumental variables, more commonly used in the industrial organization literature, to show that gas provided a significant competitor, tempering electricity prices, while electricity demand was also responsive to marketing initiatives.

Optimal control of a class of discrete–continuous non-linear systems — decomposition and hierarchical structure

A technique is derived for solving a non-linear optimal control problem by iterating on a sequence of simplified problems in linear quadratic form. The technique is designed to achieve the correct solution of the original non-linear optimal control problem in spite of these simplifications. A mixed approach with a discrete performance index and continuous state variable system description is used as the basis of the design, and it is shown how the global problem can be decomposed into local sub-system problems and a co-ordinator within a hierarchical framework. An analysis of the optimality and convergence properties of the algorithm is presented and the effectiveness of the technique is demonstrated using a simulation example with a non-separable performance index.

A combined SMOTE and PSO based RBF classifier for two-class imbalanced problems

This contribution proposes a powerful technique for two-class imbalanced classification problems by combining the synthetic minority over-sampling technique (SMOTE) and the particle swarm optimisation (PSO) aided radial basis function (RBF) classifier. In order to enhance the significance of the small and specific region belonging to the positive class in the decision region, the SMOTE is applied to generate synthetic instances for the positive class to balance the training data set. Based on the over-sampled training data, the RBF classifier is constructed by applying the orthogonal forward selection procedure, in which the classifier's structure and the parameters of RBF kernels are determined using a PSO algorithm based on the criterion of minimising the leave-one-out misclassification rate. The experimental results obtained on a simulated imbalanced data set and three real imbalanced data sets are presented to demonstrate the effectiveness of our proposed algorithm.

Identifying and investigating pesticide application types to promote a more sustainable pesticide use: the case of smallholders in Boyacá, Colombia

The present paper investigates pesticide application types adopted by smallholder potato producers in the Department of Boyacá , Colombia. In this region, environmental, health and adverse economic effects due to pesticide mis- or over-use respectively have been observed. Firstly, pesticide application types were identified based on input-effectiveness. Secondly, their determinants of adoption were investigated. Finally suggestions were given to develop intervention options for transition towards a more sustainable pesticide use. Three application types were identified for fungicide and insecticide. The types differed in terms of input (intensity of pesticide application), effect (damage control), frequency of application, average quantity applied per application, chemical class, and productivity. Then, the determinants of different pesticide application types were investigated with a multinomial logistic regression approach and applying the integrative agent centred (IAC) framework. The area of the plot, attendance at training sessions and educational and income levels were among the most relevant determinants. The analysis suggested that better pesticide use could be fostered to reduce pesticide-related risks in the region. Intervention options were outlined, which may help in targeting this issue. They aim not only at educating farmers, but to change their social and institutional context, by involving other agents of the agricultural system (i.e. pesticide producers), facilitating new institutional settings (i.e. cooperatives) and targeting social dynamics (i.e. conformity to social norms).