Worldwide topology of the scientific subject profile: a macro approach in the country level

[Background] Models for the production of knowledge and systems of innovation and science are key elements for characterizing a country in view of its scientific thematic profile. With regard to scientific output and publication in journals of international visibility, the countries of the world may be classified into three main groups according to their thematic bias.[Methodology/Principal Findings] This paper aims to classify the countries of the world in several broad groups, described in terms of behavioural models that attempt to sum up the characteristics of their systems of knowledge and innovation. We perceive three clusters in our analysis: 1) the biomedical cluster, 2) the basic science & engineering cluster, and 3) the agricultural cluster. The countries are conceptually associated with the clusters via Principal Component Analysis (PCA), and a Multidimensional Scaling (MDS) map with all the countries is presented.[Conclusions/Significance] As we have seen, insofar as scientific output and publication in journals of international visibility is concerned, the countries of the world may be classified into three main groups according to their thematic profile. These groups can be described in terms of behavioral models that attempt to sum up the characteristics of their systems of knowledge and innovation

Genetic algorithm based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy

Proliferative diabetic retinopathy (PDR) is a condition that carries a high risk of severe visual impairment. The hallmark of PDR is the growth of abnormal new vessels. In this paper, an automated method for the detection of new vessels from retinal images is presented. This method is based on a dual classification approach. Two vessel segmentation approaches are applied to create two separate binary vessel map which each hold vital information. Local morphology features are measured from each binary vessel map to produce two separate 4-D feature vectors. Independent classification is performed for each feature vector using a support vector machine (SVM) classifier. The system then combines these individual outcomes to produce a final decision. This is followed by the creation of additional features to generate 21-D feature vectors, which feed into a genetic algorithm based feature selection approach with the objective of finding feature subsets that improve the performance of the classification. Sensitivity and specificity results using a dataset of 60 images are 0.9138 and 0.9600, respectively, on a per patch basis and 1.000 and 0.975, respectively, on a per image basis

The Past and Future of Evolutionary Economics : Some Reflections Based on New Bibliometric Evidence

This document is the Accepted Manuscript version of the following article: Geoffrey M. Hodgson, and Juha-Antti Lamberg, ‘The past and future of evolutionary economics: some reflections based on new bibliometric evidence’, Evolutionary and Institutional Economics Review, first online 20 June 2016. The final publication is available at Springer via doi: http://dx.doi.org/10.1007/s40844-016-0044-3 © Japan Association for Evolutionary Economics 2016The modern wave of ‘evolutionary economics’ was launched with the classic study by Richard Nelson and Sidney Winter (1982). This paper reports a broad bibliometric analysis of ‘evolutionary’ research in the disciplines of management, business, economics, and sociology over 25 years from 1986 to 2010. It confirms that Nelson and Winter (1982) is an enduring nodal reference point for this broad field. The bibliometric evidence suggests that ‘evolutionary economics’ has benefitted from the rise of business schools and other interdisciplinary institutions, which have provided a home for evolutionary terminology, but it has failed to nurture a strong unifying core narrative or theory, which in turn could provide superior answers to important questions. This bibliometric evidence also shows that no strong cluster of general theoretical research immediately around Nelson and Winter (1982) has subsequently emerged. It identifies developmental problems in a partly successful but fragmented field. Future research in ‘evolutionary economics’ needs a more integrated research community with shared conceptual narratives and common research questions, to promote conversation and synergy between diverse clusters of research.Peer reviewedFinal Accepted Versio

Automated identification of diabetic retinal exudates in digital colour images

Aim: To identify retinal exudates automatically from colour retinal images