Éditeur(s) : Elsevier
Résumé : This paper presents a survey of French Eastern English Channel fishers' observations of the past and current state of the marine ecosystem and their wishes for the future, as a first step towards formulating management objectives. Twenty-nine semi-directive interviews were carried out in June 2006 among fishers and shellfish farmers. Cognitive maps proved useful to formalise their experience and knowledge. Most interviewees mentioned a decrease of the resource in recent years and pointed out the presence of several problems, such as pollution, degradation of the ocean floor and harmful impacts of human activities, including fishing. The indicators used by the fishers as the basis to form their opinion were similar to those generally used by scientists for assessing the state of exploited marine populations and communities (average fish length, CPUE, fished biomass...); additional indicators were the timing and duration of fishing seasons. (c) 2008 Elsevier Ltd. All rights reserved.
Ocean & Coastal Management (0964-5691) (Elsevier), 2008-06 , Vol. 51 , N. 6 , P. 450-462

Droits : 2008 Elsevier Ltd All rights reserved.
http://archimer.ifremer.fr/doc/2008/publication-6134.pdf
DOI:10.1016/j.ocecoaman.2008.04.005
http://archimer.ifremer.fr/doc/00000/6134/

Éditeur(s) : HAL CCSD
Résumé : 6 pages
In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed both in time and in the network architecture. Since a current feature of SNNs is a low average activity, efficient implementations of SNNs are usually based on an Event-Driven Simulation (EDS). On the other hand, simulations of large scale neural networks can take advantage of distributing the neurons on a set of processors (either workstation cluster or parallel computer). This article presents DAMNED, a large scale SNN simulation framework able to gather the benefits of EDS and parallel computing. Two levels of parallelism are combined: Distributed mapping of the neural topology, at the network level, and local multithreaded allocation of resources for simultaneous processing of events, at the neuron level. Based on the causality of events, a distributed solution is proposed for solving the complex problem of scheduling without synchronization barrier.
https://hal.archives-ouvertes.fr/hal-00015137

hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137v2/document
https://hal.archives-ouvertes.fr/hal-00015137/file/hal_damned.pdf
ARXIV : cs.NE/0512018