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EXAMPLES At this point, it is useful to consider three examples of cluster analysis from the literature. The rst example is based on kinship data from Rosenberg and Kim (1975), which has been analyzed in detail by Carroll and Arabie (1983), De Soete and Carroll (1996), and others. The task that the subjects performed in the initial study was to sort kinship terms into any number of piles so that each pile consisted of related terms and there were at least two piles. By taking the total number of times that a subject put two terms in the same pile, one can construct a similarity matrix between terms. Rosenberg and Kim (1975) asked some subjects to sort the terms once, while others were asked to sort the terms multiple times. Using the data matrix from female subjects, De Soete and Carroll (1996) constructed a dendrogram, as shown in Figure 7.2, using a leastsquares ultrametric tree- tting procedure called LSULT (De Soete, 1984). The resulting ultrametric tree representation, which accounts for 96.0% of the variance in the original data matrix, encapsulates the standard anthropological model of kinship terms (Carroll & Arabie, 1983). The tree divides direct kin, such as grandparents, from collaterals, such as cousins. It further divides the direct kin into the immediate family versus 2 generations. Within these clusters, further groupings occur on the basis of generation (e.g., mother and father are clustered). In this case, there is great bene t in considering the entire representation. That is, if one were to truncate the tree and declare that kin terms are best represented as three clusters or seven clusters, much information would be lost.

(ii) Use a 0.22 m lter to sterilize. (iii) Store at 20 C for up to one year. (iv) (v) Make a 1 10 5 M working solution by 1/100 dilution of 1 10 3 M stock in DMEM. Aliquot (1 2 ml in sterile cryotubes) and store at 20 C. This solution is stable for up to 30 days at 4 C and for 1 year at 20 C.

OmniTRACS/USA (global coverage) Main characteristics Development Current status Perspectives C-band and Ku-band relays on board geostationary satellites, developed by Qualcomm ($100 m) Since 1988, rst message and localization of mobile system. Mainly used for real-time monitoring of truck, ship, container eets Deployment of more than 540,000 terminals all over the world Integration of the future GPS signals as well as the Galileo ones EutelTRACS/Eutelsat (Europe/Mediterranean/Middle-East) Main characteristics Development Current status Perspectives Ku-band relay on board two geostationary satellites (W1 and Sesat-1) Closed network of secured message and localization, providing for eet management, since 1990 Diversi cation of services for the 25,000 terminals already in use (developed by Qualcomm and Alcatel) Combined use of modernized GPS and Galileo signals for the next generation

9.22 9.24 9.26

Essential Windows CE Application Programming by Robert Burdick Wiley Computer Publishing, John Wiley & Sons, Inc. ISBN: 0471327476 Pub Date: 03/01/99

Figure 1.3 Selecting a target build configuration. If you have installed more than one Windows CE Platform SDK, a second combo box will be included in the

Sum-dist. This method is also known as DV-distance [16]. The most simple solution for determining the distance to the anchors is simply adding the ranges encountered at each hop during the network ood. Sum-dist starts at the anchors, which send a message including their identity, position, and a path length set to 0. Each receiving node adds the measured range to the path length and forwards (broadcasts) the message if the ood limit allows it to do so. Another constraint is that when the node has already received information about the particular anchor, it is only allowed to forward the message if the current path length is less than the previous one. The end result is that each node will have stored the position and minimum path length to at least ood-limit anchors.

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