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servers. The name resolvers do not usually store information, nor are they programmed with information like a name server. All information is kept in the server. Name servers keep information about some part of the name space, called a zone. Name servers can be authoritative about one or more zones. Being authoritative means that this server is all-knowing about the zone. A server can be authoritative for more than one zone, and it can be a primary name server for one zone and a secondary name server for another. However, these functions rarely cross; name servers are either primary or secondary for the zones they load. There are two types of name servers: primary masters and secondary masters. The primary master builds its database from files that were preconfigured on its hosts, called zone or database files. The name server reads these files and builds a database for the zone it is authoritative for. Secondary masters can provide information to resolvers just like the primary masters, but they get their information from the primary. Any updates to the database are provided by the primary. This system was set up for ease of use. It is also important to note that there should be more than one name server per zone or domain.

In these circumstances I had the privilege of working with one particular group of villages on a biodiversity conservation project that had to focus upon con ict management The central stakeholders involved were the village elders the traditional male authority gures; the young men of the villages who undertook most of the harvesting of the bark, using mostly unsustainable methods and operating outside of legal controls; the representatives of a French pharmaceutical company that were the major purchasers of the bark from these communities; and the local and regional of cers of the Ministry of Forests who were charged with the conservation of the species and it protection from illegal harvesting.

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mandatory for food safety. In small food workshops, they can per se be the foundation of so-called light HACCP. It may be assumed in extremis that a well-trained person with access to guidance is able to implement inhouse HACCP methods.

The unsupervised classi cation of images [1, 2] can be viewed as a simple computational procedure that uses the results of the preliminary similarity analysis, namely the computed similarity degrees between the new (unknown) image and all existing images from the image base. For classi cation purposes, these results have to be sorted in descending order of the similarity degrees for each pair of images. Then, according to a preliminary, assumed reasonable threshold for the similarity degree, the new (unknown) image is classi ed as belonging to the class of the most similar image or rejected as non-belonging to any known class of images. Now it becomes clear that in order to achieve a satisfactory solution to this problem we rst need to extract the most representative characteristics (features) from the original images in appropriate numerical form that corresponds to the speci c of this image. We can view each separate image as a kind of data cloud in the three-dimensional RGB space, which has its speci c density distribution, shape, and location in this space. All three correspond in some indirect way to the diversity and the overall ratio of the colors in the original two-dimensional image. Therefore, the problem of computing the similarity degree between a given pair of images becomes a problem of evaluating the difference between the respective features of the three-dimensional data clouds in the RGB space. It seems natural to assume that the rst (and probably the most important) feature that can be extracted from a given data cloud is its center of gravity (COG), de ned as the vector CG CG1 ; CG2 ; CG3 , which can be directly computed from the original raw data as follows: CGj

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where the approximation is based on the error probability for the BSC being a small number p 1. In order to determine the error-correction capability of a linear block code Cb (n, k), an integer number t that ts the condition 2t + 1 dmin 2t + 2 (42)

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