934 resultados para TRAINING PROGRAMMES
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Participants were exposed to concepts and information about Ecosystem Approach to Fisheries Management (EAFM) using a structured, participatory method of delivery. The learning strategy involved specifically designed exercises, using real examples, to consolidate learning. Daily monitoring and reviews were conducted together with pre-and post-course assessment.
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Participants were exposed to concepts and information about EAFM using a structured, participatory method of delivery. The learning strategy involved specifically designed exercises, using real examples, to consolidate learning. Daily monitoring and reviews were conducted together with pre-and post-course assessment.
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This workshop was held at the National Bureau of Fish Genetic Resources and followed on from the Indian mackerel Working group meeting in Colombo (28-29 May, 2012). Activities included; DNA extraction; PCR (Polymerase Chain Reaction) for microsatellites; genotyping microsatellites; data analysis; emerging technologies; and an action plan
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Training included: Geographic Information System (GIS)concept and software; Global Positioning System (GPS); Ecological Gap Analysis and Marine Protected Area (MPA) design using Marine Reserve Design using Spatially Explicit Annealing (MARXAN); and cartography.
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Participants consisted of 25 middle and junior level personnel from BOBLME countries. Modules included: Integrated Coastal Management (ICM) concept and principles; ICM development and implementation; indicators of good practice; and action planning.
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The Socio-economic Monitoring (SocMon) training workshop followed up from the capacity building workshop held in Mannar, 2015. It's aims were to validate information collected at the previous workshop, assist in filling in any gaps and develop a vision tree fro future actions. Planned outputs included: a detailed workplan; a workshop process report; and a final socioeconomic base line report for Vidathaltivu village.
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Trainers from the region contributed theory and practical training to trainees from government departments, universities and NGOs relevant to conservation of seagrasses and monitoring methods.
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Objectives of the workshop included; introduction to various Marine Protected Area (MPA) tools with a focus on Management Effectiveness Assessment Tool (MEAT); report on selected MPAs in Bangladesh; undertake initial assessments using MEAT; and develop workplans for other MPAs
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Objectives included a desk-top feasibility study to explore opportunities to adapt the Scientific Educational Resources and Experience Associated with the Deployment of Argo profiling floats in the South Pacific Ocean (SEREAD) to BOBLME country schools.The programme included teacher resources on climate change and facilitating interactions between scientists, students and teachers.
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This report presents presentations from representatives of 12 countries, key outcomes and recommendations for the future.
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This report presents presentations from representatives of 12 countries, key outcomes and recommendations for the future.
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Trawling experiments carried out by the United Nations Development Programme Project and the Uganda Department of Fisheries, strongly suggest that the trawling method of fishing, if introduced on Lake Victoria, would bring about a tremendous increase in fish production from the lake. It is recognised, however, that before trawling is introduced, its economic, social, technical, biological and manpower implications must be carefully analysed. I now propose to discuss the training aspects of a trawl fishery on Lake Victoria.
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In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods.
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Vector Taylor Series (VTS) model based compensation is a powerful approach for noise robust speech recognition. An important extension to this approach is VTS adaptive training (VAT), which allows canonical models to be estimated on diverse noise-degraded training data. These canonical model can be estimated using EM-based approaches, allowing simple extensions to discriminative VAT (DVAT). However to ensure a diagonal corrupted speech covariance matrix the Jacobian (loading matrix) relating the noise and clean speech is diagonalised. In this work an approach for yielding optimal diagonal loading matrices based on minimising the expected KL-divergence between the diagonal loading matrix and "correct" distributions is proposed. The performance of DVAT using the standard and optimal diagonalisation was evaluated on both in-car collected data and the Aurora4 task. © 2012 IEEE.