ENEKuS – a key model for managing the transformation of the normalisation of the Basque language in the workplace

The aim of this study is to develop a reference model for intervention in the language processes applied to the transformation of language normalisation within organisations of a socio-economic nature. It is based on the case study of an experience carried out over10 years within a trades’ union confederation, and has pursued a strategy of a basically qualitative research carried out in three stages: 1) undertaking field work through application of action-research methodology, 2) reconstructing experiences following processes of systematisation and conceptualisation of the systematised data, applying methodologies for the Systematisation of Experiences and Grounded Theory, and 3) formulating a model for intervention, applying the Systems Approach methodology. Finally, we identified nine key ideas that make up the conceptual framework for the ENEKuS reference model, which is structured in nine ‘action points', each having an operating sub-model applicable in practice.

Ontologies for representation of folk song metadata

The digital management of collections in museums, archives, libraries and galleries is an increasingly important part of cultural heritage studies. This paper describes a representation for folk song metadata, based on the Web Ontology Language (OWL) implementation of the CIDOC Conceptual Reference Model. The OWL representation facilitates encoding and reasoning over a genre ontology, while the CIDOC model enables a representation of complex spatial containment and proximity relations among geographic regions. It is shown how complex queries of folk song metadata, relying on inference and not only retrieval, can be expressed in OWL and solved using a description logic reasoner.

A semantic middleware to enhance current multimedia retrieval systems with content-based functionalities

210 p. : graf.

Reference Points and Optimal Management in Stochastic Age-Structured Fisheries Models

The purpose of this article is to characterize dynamic optimal harvesting trajectories that maximize discounted utility assuming an age-structured population model, in the same line as Tahvonen (2009). The main novelty of our study is that uses as an age-structured population model the standard stochastic cohort framework applied in Virtual Population Analysis for fish stock assessment. This allows us to compare optimal harvesting in a discounted economic context with standard reference points used by fisheries agencies for long term management plans (e.g. Fmsy). Our main findings are the following. First, optimal steady state is characterized and sufficient conditions that guarantees its existence and uniqueness for the general case of n cohorts are shown. It is also proved that the optimal steady state coincides with the traditional target Fmsy when the utility function to be maximized is the yield and the discount rate is zero. Second, an algorithm to calculate the optimal path that easily drives the resource to the steady state is developed. And third, the algorithm is applied to the Northern Stock of hake. Results show that management plans based exclusively on traditional reference targets as Fmsy may drive fishery economic results far from the optimal.

New climate scenario framework implementation in the GCAM integrated assessment model

48 p.