1000 resultados para Fundraising methods


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We evaluated the use of strip-transect survey methods for manatees through a series of replicate aerial surveys in the Banana River, Brevard County, Florida, during summer 1993 and summer 1994. Transect methods sample a representative portion of the total study area, thus allowing for statistical extrapolation to the total area. Other advantages of transect methods are less flight time and less cost than total coverage, ease of navigation, and reduced likelihood of double-counting. Our objectives were: (1) to identify visibility biases associated with the transect survey method and to adjust the counts accordingly; (2) to derive a population estimate with known variance for the Banana River during summer; and (3) to evaluate the potential value of this survey method for monitoring trends in manatee population size over time. (51 page document)

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On 17-20 July 2007, 45 experts on sea turtles, fisheries, conservation and finance from 10 countries convened at the Bellagio Sea Turtle Conservation Initiative workshop in Terengganu to focus on methods to save the imperiled Pacific leatherback from extinction. The group developed a strategic plan to guide the prioritization and long term financing of Pacific leatherback turtle conservation and recovery objectives. Participants identified critical conservation actions and agreed that a business plan is urgently needed to reverse the trajectory towards extinction of the Pacific leatherback. The conservation actions prioritized by the participants encompassed protecting nesting beaches including eggs and nesting females; reducing direct and indirect turtle take in coastal fisheries; and strengthening regional and sub-regional cooperation. The group committed to work together on fundraising and implementation of these urgent conservation actions. This report presents outputs and the plan that was produced from the workshop.

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Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. In EDAs based on Markov networks, methods for generating new populations usually discard information contained in the model to gain in efficiency. Other methods like Gibbs sampling use information about all interactions in the model but are computationally very costly. In this paper we propose new methods for generating new solutions in EDAs based on Markov networks. We introduce approaches based on inference methods for computing the most probable configurations and model-based template recombination. We show that the application of different variants of inference methods can increase the EDAs’ convergence rate and reduce the number of function evaluations needed to find the optimum of binary and non-binary discrete functions.