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Note: Personalization on the Web mimics the work of a good salesperson in the real world. Over time, the seller observes the behavior of an individual prospect, perhaps categorizing that potential buyer into one of several general categories: impulse buyer, looker, family-in uenced, and so on. By continually analyzing and comparing recommendations against behavior, the salesperson reinforces the value of the categories and his or her observations. Then the salesperson steps in to make the sale. Personalization works much the same way on a Web site, but across a larger number of prospects and in real time.

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g2 e1 dx dy g2 G dx0 dy0 (6.114)

whether on the circumference or not, belongs to the invisible region. At the invisible region, does not assume a real value. The polynomial in (1.74) can be expressed in terms of a product of N 1 factors as AF z = AN 1 z z1 z z2 z zN 1 (1.76)

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8 May 2018 ... Post summary: How to extract text from PDF in C# . PDF verification ... iTextSharp . iTextSharp is a library that allows you to manipulate PDF files.

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Anderson, JL, et al, Muscles, Genes, and Athletic Performance, Sci Am (Sept 2000) Cavalli-Sforza, LL, Genes, Peoples, and Languages New York: Northpoint Press (2000) Duster, T, Backdoor to Eugenics New York: Rutledge (1990) Foster, MW et al, The Role of Community Review in Evaluating the Collective Risks of Human Genetic Variation Research, Am J Hum Genet, 64, 1719 1727 (1999) Foster, MW and RR Sharp, Involving Study Populations in the Review of Genetic Research, J L Med Ethics, 28, 41 51 (2000) Foster, MW, et al, A Model Agreement for Genetic Research in Socially Identi able Populations, Am J Hum Genet, 63, 696 702 (1998) Foster, MW and WL Freeman, Naming Names in Human Genetic Variation Research, Genet Res, 8, 755 757 (1998) Freeman, WL, In: Weir, RF.

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Figure N.7 shows a module with an output re ection connected to a cable, which is terminated in its characteristic impedance R0 . The module is matched at its input. The noise factor for a cable with an input mismatch must produce the same effective increase in the source noise whether its value is that for a standard cascade or the theoretical value, each used within its corresponding system. We will show that our value of noise factor for the standard cascade implies the cable noise temperature given by Pozar s (2001) expression for use in a theoretical cascade. Equations (3.27) and (3.29) for the standard system give a noise factor of fcbl = 1 + [1/g2 + | 1 |2 (1 g2 ) 1]T /T0 . (44)

indirect and support costs, which cannot directly re ect variation from nal cost objects, and there are also cost object to cost object assignments. An example of the latter assignment type is the cost to process a special order (versus a standard order), traced to a speci c customer or a group of customers consuming a unique quantity and mix of products, services, or outputs. The model in Figure 12.2 is analogous to Charles Darwin s model for the evolution of the species. The left graphic is like a single-celled paramecium or amoeba. The middle graphic is analogous to reptiles, amphibians, and snakes. The right graphic is like humans beginning to walk upright. In Figure 12.2 the left graphic is primitive. It represents traditional accounting s cost allocation method, which simply and arbitrarily redistributes the source costs into destinations such as product costs, without regard to logical causality. Many nancial controllers still allocate costs this way.1 But without any causal relationship, there is an expected, undesirable error in calculating the costs of cost objects. The results are inaccurate costs. The nancial controllers who continue to allocate costs this way are misleading their end-users with awed data. The middle graphic in Figure 12.2 represents the ABM two-stage cost allocation model, in which the expenditures for resources are assigned at the work activity level, not at a department level (i.e., using verb-adjective-noun grammar to de ne activities). But this method is too simplistic to be adequate. The right-hand side of Figure 12.2 symbolizes the activity-based costing vertical cost assignment as a multistage cost assignment network with an expanded

(ed), Stored Tissue Samples: Ethical, Legal, and Policy Implications Iowa City: Univ Iowa Press, pp 267 301 (1998) Greely, HT, The Control of Genetic Research: Involving the Groups Between, Hous L Rev, 33, 1397 1430 (1997a) Greely, HT, The Ethics of the Human Genome Diversity Project: The North American Regional Committee s Proposal Model Ethical Protocol, in Human DNA Sampling: Law and Policy International and Comparative Perspectives Kluwer Law Intl, pp 239 256 (1997b) Human Genome Diversity Project, Summary Document (1994), available at http://wwwstanfordedu/group/morrinst/hgdp/summary93html HUGO Ethics Committee, Statement on Bene t Sharing (April 9, 2000), available at http://wwwgeneuclacuk/hugo/bene thtml Jones, J, Bad Blood: The Tuskegee Syphilis Experiment, 2d ed, New York: Maxwell McMillian Intl (1993) Juengst, ET, Group Identity and Human Diversity: Keeping Biology Straight from Culture, Am J Hum Genet.

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