875 resultados para Colony algorithms
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This paper proposes a multicast implementation based on adaptive routing with anticipated calculation. Three different cost measures for a point-to-multipoint connection: bandwidth cost, connection establishment cost and switching cost can be considered. The application of the method based on pre-evaluated routing tables makes possible the reduction of bandwidth cost and connection establishment cost individually
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In image segmentation, clustering algorithms are very popular because they are intuitive and, some of them, easy to implement. For instance, the k-means is one of the most used in the literature, and many authors successfully compare their new proposal with the results achieved by the k-means. However, it is well known that clustering image segmentation has many problems. For instance, the number of regions of the image has to be known a priori, as well as different initial seed placement (initial clusters) could produce different segmentation results. Most of these algorithms could be slightly improved by considering the coordinates of the image as features in the clustering process (to take spatial region information into account). In this paper we propose a significant improvement of clustering algorithms for image segmentation. The method is qualitatively and quantitative evaluated over a set of synthetic and real images, and compared with classical clustering approaches. Results demonstrate the validity of this new approach
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The population dynamics of long-lived birds are thought to be very sensitive to changes in adult survival. However, where natal philopatry is low, recruitment from the larger metapopulation may have the strongest effect on population growth rate even in long-lived species. Here, we illustrate such a situation where changes in a seabird colony size appeared to be the consequence of changes in recruitment. We studied the population dynamics of a declining colony of Ancient Murrelets (Synthliboramphus antiquus) at East Limestone Island, British Columbia. During 1990-2010, Ancient Murrelet chicks were trapped at East Limestone Island while departing to sea, using a standard trapping method carried on throughout the departure period. Adult murrelets were trapped while departing from the colony during 1990-2003. Numbers of chicks trapped declined during 1990-1995, probably because of raccoon predation, increased slightly from 1995-2000 and subsequently declined again. Reproductive success was 30% lower during 2000-2003 than in earlier years, mainly because of an increase in desertions. The proportion of nonbreeders among adult birds trapped at night also declined over the study period. Mortality of adult birds, thought to be mainly prebreeders, from predators more than doubled over the same period. Apparent adult survival of breeders remained constant during 1991-2002 once the first year after banding was excluded, but the apparent survival rates in the first year after banding fell and the survival of birds banded as chicks to age three halved over the same period. A matrix model of population dynamics suggested that even during the early part of the study immigration from other breeding areas must have been substantial, supporting earlier observations that natal philopatry in this species is low. The general colony decline after 2000 probably was related to diminished recruitment, as evidenced by the lower proportion of nonbreeders in the trapped sample. Hence the trend is determined by the recruitment decisions of externally reared birds, rather than demographic factors operating on the local breeding population, an unusual situation for a colonial marine bird. Because of the contraction in the colony it may now be subject to a level of predation pressure from which recovery will be impossible without some form of intervention.
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Worldwide marine protected areas (MPAs) have been designated to protect marine resources, including top predators such as seabirds. There is no conclusive information on whether protected areas can improve population trends of seabirds when these are further exploited as tourist attractions, an activity that has increased in past decades. Humboldt Penguins (Spheniscus humboldti) and Magellanic Penguins (S. magellanicus) breed sympatrically on Puñihuil Islets, two small coastal islands off the west coast of Chiloé Island (41° S) in southern Chile that are subject to exploitation for tourism. Our goal was to compare the population size of the mixed colony of Humboldt and Magellanic Penguins before and after protection from unregulated tourism and freely roaming goats in 1997. For this purpose, two censuses were conducted in 2004 and 2008, and the numbers compared with those obtained in 1997 by other authors. The proportion of occupied, unoccupied, and collapsed/flooded burrows changed between years; there were 68% and 34% fewer collapsed burrows in 2004 and 2008, respectively, than in 1997. For the total number of burrows of both species, we counted 48% and 63% more burrows in 2004 and 2008, respectively, than in 1997. We counted 13% more burrows of Humboldt Penguins in 2008 than in 1997, and for Magellanic Penguins, we estimated a 64% increase in burrows in 2008. Presumably, this was as a result of habitat improvement attributable to the exclusion of tourists and the removal of goats from the islets. Although tourist visits to the islets are prohibited, tourism activities around the colonies are prevalent and need to be taken into account to promote appropriate management.
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Many algorithms have been developed to achieve motion segmentation for video surveillance. The algorithms produce varying performances under the infinite amount of changing conditions. It has been recognised that individually these algorithms have useful properties. Fusing the statistical result of these algorithms is investigated, with robust motion segmentation in mind.
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The authors present a systolic design for a simple GA mechanism which provides high throughput and unidirectional pipelining by exploiting the inherent parallelism in the genetic operators. The design computes in O(N+G) time steps using O(N2) cells where N is the population size and G is the chromosome length. The area of the device is independent of the chromosome length and so can be easily scaled by replicating the arrays or by employing fine-grain migration. The array is generic in the sense that it does not rely on the fitness function and can be used as an accelerator for any GA application using uniform crossover between pairs of chromosomes. The design can also be used in hybrid systems as an add-on to complement existing designs and methods for fitness function acceleration and island-style population management
Resumo:
This paper presents the results of the application of a parallel Genetic Algorithm (GA) in order to design a Fuzzy Proportional Integral (FPI) controller for active queue management on Internet routers. The Active Queue Management (AQM) policies are those policies of router queue management that allow the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. Two different parallel implementations of the genetic algorithm are adopted to determine an optimal configuration of the FPI controller parameters. Finally, the results of several experiments carried out on a forty nodes cluster of workstations are presented.
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We have designed a highly parallel design for a simple genetic algorithm using a pipeline of systolic arrays. The systolic design provides high throughput and unidirectional pipelining by exploiting the implicit parallelism in the genetic operators. The design is significant because, unlike other hardware genetic algorithms, it is independent of both the fitness function and the particular chromosome length used in a problem. We have designed and simulated a version of the mutation array using Xilinix FPGA tools to investigate the feasibility of hardware implementation. A simple 5-chromosome mutation array occupies 195 CLBs and is capable of performing more than one million mutations per second. I. Introduction Genetic algorithms (GAs) are established search and optimization techniques which have been applied to a range of engineering and applied problems with considerable success [1]. They operate by maintaining a population of trial solutions encoded, using a suitable encoding scheme.
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A parallel hardware random number generator for use with a VLSI genetic algorithm processing device is proposed. The design uses an systolic array of mixed congruential random number generators. The generators are constantly reseeded with the outputs of the proceeding generators to avoid significant biasing of the randomness of the array which would result in longer times for the algorithm to converge to a solution. 1 Introduction In recent years there has been a growing interest in developing hardware genetic algorithm devices [1, 2, 3]. A genetic algorithm (GA) is a stochastic search and optimization technique which attempts to capture the power of natural selection by evolving a population of candidate solutions by a process of selection and reproduction [4]. In keeping with the evolutionary analogy, the solutions are called chromosomes with each chromosome containing a number of genes. Chromosomes are commonly simple binary strings, the bits being the genes.