A regulation-based classification system for marine protected areas (MPAs)

Marine protected areas (MPAs) are a global conservation and management tool to enhance the resilience of linked social-ecological systems with the aim of conserving biodiversity and providing ecosystem services for sustainable use. However, MPAs implemented worldwide include a large variety of zoning and management schemes from single to multiple-zoning and from no-take to multiple-use areas. The current IUCN categorisation of MPAs is based on management objectives which many times have a significant mismatch to regulations causing a strong uncertainty when evaluating global MPAs effectiveness. A novel global classification system for MPAs based on regulations of uses as an alternative or complementing, the current IUCN system of categories is presented. Scores for uses weighted by their potential impact on biodiversity were built. Each zone within a MPA was scored and an MPA index integrates the zone scores. This system classifies MPAs as well as each MPA zone individually, is globally applicable and unambiguously discriminates the impacts of uses. (C) 2016 The Authors. Published by Elsevier Ltd.

Atlantic Area Eunis Habitats. Adding new habitat types from European Atlantic coast to the EUNIS Habitat Classification

Marine protection has been emphasized through global and European conventions which highlighted the need for the establishment of special areas of conservation. Classification and habitat mapping have been developed to enhance the assessment of marine environment and improve spatial and strategic planning of human activities and to help on the implementation of ecosystem based management. European Nature information System (EUNIS) is a comprehensive habitat classification system to facilitate the harmonised description and collection of habitat and biotopes that has been developed by the European Environment Agency (EEA) in collaboration with experts from institutions throughout Europe.

Image summarisation: human action description from static images

Dissertação de Mestrado, Processamento de Linguagem Natural e Indústrias da Língua, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2014

Neural network classification of cerebral embolic signals

The presence of circulating cerebral emboli represents an increased risk of stroke. The detection of such emboli is possible with the use of a transcranial Doppler ultrasound (TCD) system.