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José Luis Hervás Oliver

Researcher at Polytechnic University of Valencia

Publications -  71
Citations -  853

José Luis Hervás Oliver is an academic researcher from Polytechnic University of Valencia. The author has contributed to research in topics: Wavelet & Encoder. The author has an hindex of 16, co-authored 71 publications receiving 800 citations. Previous affiliations of José Luis Hervás Oliver include Florida State University & University of Alicante.

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Clusters and industrial districts: where is the literature going? Identifying emerging sub-fields of research

TL;DR: In this article, bibliometric methods are used to analyze cluster literature published between 1957 and 2014 in order to explore prospective research priorities through the method of bibliographic coupling, which shifts the focus away from the practice of analyzing co-citations and seminal contributions to one of looking at current and emerging trends in the literature.
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Simple determination of nitrate in soils by second-derivative spectroscopy

TL;DR: In this article, a new and simple method for nitrate analysis in soil extracts and soil solution is described using the second derivative of the direct ultra-violet (UV) spectrum, available from most microprocessor-controlled spectrophotometers with a UV source.
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An algorithm for ranking the nodes of an urban network based on the concept of PageRank vector

TL;DR: A new method to establish a ranking of nodes in an urban network, adapting the concept of PageRank vector to urban networks, and is applied to a real example, in which a part of the city of Murcia (Spain) is considered.
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External Ties and the Reduction of Knowledge Asymmetries among Clusters within Global Value Chains: The Case of the Ceramic Tile District of Castellon

TL;DR: In this paper, the authors examined the process of knowledge exchange between clusters through external ties using the global value chain approach, which considers connections between clusters in similar activities and even when both are located in developed nations.
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How to measure IC in clusters: empirical evidence

TL;DR: A comprehensive model to describe, map, measure and value IC on clusters and systematically control the IC evolution is provided and is a very useful tool of information and practical assessment for IC.