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BACKGROUND Various lines of evidence have shown that bisphenol A [BPA; HO-C6H4-C(CH3)2-C6H4-OH] acts as an endocrine disruptor when present in very low doses. We have recently demonstrated that BPA binds strongly to human estrogen-related receptor-gamma (ERR-gamma ) in a binding assay using [3H]4-hydroxytamoxifen ([3H]4-OHT). We also demonstrated that BPA(More)
—Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO). Most current EMO algorithms perform well on problems with two or three objectives, but encounter difficulties in their scalability to many-objective optimization. This paper proposes a Grid-based Evolutionary Algorithm (GrEA) to solve many-objective(More)
In this paper we address the problem of traffic sign recognition. Novel image representation and discrimi-native feature selection algorithms are utilised in a traditional three-stage framework involving detection, tracking and recognition. The detector captures instances of equiangular polygons in the scene which is first appropriately filtered to extract(More)
Real-time road sign recognition has been of great interest for many years. This problem is often addressed in a two-stage procedure involving detection and classification. In this paper a novel approach to sign representation and classification is proposed. In many previous studies focus was put on deriving a set of discriminative features from a large(More)
Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus set of clusters from a number of clustering methods should improve confidence in gene-expression analysis. Here we introduce consensus clustering, which provides such an advantage.(More)
In this paper, we deal with the robust H ∞ filtering problem for a class of uncertain nonlinear time-delay stochastic systems. The system under consideration contains parameter uncertainties, Itô-type stochastic disturbances, time-varying delays, as well as sector-bounded nonlinearities. We aim at designing a full-order filter such that, for all admissible(More)
—It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of the Pareto dominance relation for a high-dimensional space leads diversity maintenance mechanisms to play the leading role during the evolutionary(More)
In this paper, we explore the automatic explanation of Multivariate Time Series (MTS) through learning Dynamic Bayesian Networks (DBNs). We have developed an evolutionary algorithm which exploits certain characteristics of process MTS in order to generate good networks as quickly as possible. We compare this algorithm to other standard learning algorithms(More)
OBJECTIVE Progressive loss of the field of vision is characteristic of a number of eye diseases such as glaucoma which is a leading cause of irreversible blindness in the world. Recently, there has been an explosion in the amount of data being stored on patients who suffer from visual deterioration including field test data, retinal image data and patient(More)