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Imagine that you have a number of connectors or adapters that take information from external systems and feed it through a standard set of business rules. Moreover, imagine that you can t implement a common data model because these applications are a combination of legacy and new code. Step 1 is to look at the types of beans you want to use. In this case, you might want to use message-driven beans as the access points for the business rules, but Entity and Session Beans as the implementations of those rules. Figure 8.15 shows an example of how you might mix beans like this. Within the same system, you might also add new code that does rely on a common data model. In this case, you could reuse the Session Beans to provide transformation logic to map to and from the common model.

I1 =

J2EE provides several layers of technology. For example, you can write an application that uses RMI directly or a Session Bean that you access with RMI. Choosing the wrong level to work at will affect the reliability and overall performance of your final solution.

It is easy for suspects to exploit service providers by using stolen identities, which can make it dif cult to identify and zero in on the actual perpetrators of the crimes..

Mathiowetz, N A and McGonagle, K A (2000) An assessment of the current state of dependent interviewing in household surveys Journal of Official Statistics, 16, 401 418 Moore, J and Griffiths, J K (2003) Asset ownership, program participation, and asset and program income: improving reporting in the Survey of Income and Program Participation In Proceedings of the American Statistical Association (pp 2896 2903) Alexandria VA: American Statistical Association Moore, J and Kasprzyk, D (1984) Month to month recipiency turnover in the ISDP In Proceedings of the Survey Research Methods Section (pp 726 731) Washington, DC: American Statistical Association Moore, J, Pascale, J, Doyle, P, Chan, A and Griffiths, J K (2004) Using field experiments to improve instrument design: the SIPP Methods Panel Project In S Presser et al (Eds), Methods for Testing and Evaluating Survey Questionnaires (pp 189 207) New York: John Wiley & Sons, Inc.

Murray, T S, Michaud, S, Egan, M and Lemaitre, G (1991) Invisible seams The experience with the Canadian Labour Market Activity Survey In Proceedings of the US Bureau of the Census Annual Research Conference (pp 715 730) Washington, DC: US Census Bureau Neter, J and Waksberg, J (1964) A study of response errors in expenditure data from household interviews Journal of the American Statistical Association, 59, 18 55 Pascale, J and Bates, N (2004) Dependent interviewing in the US Census Bureau s Survey of Income and Program Participation (SIPP) Presentation given at the Workshop on Dependent Interviewing (16 17 September 2004), University of Essex, Colchester Retrieved March 6, 2008, from http://wwwiseressexacuk/home/plynn/ismie/Workshophtm Pascale, J and Mayer, T S (2004) Exploring confidentiality issues related to dependent interviewing: preliminary findings Journal of Official Statistics, 20, 357 377 Phillips, M, Woodward, C, Collins, D.

and O Connor, W (2002) Encouraging and maintaining participation in the Families and Children Survey: understanding why people take part Working Paper London: Department of Work and Pensions Polivka, A E and Rothgeb, J M (1993) Redesigning the CPS questionnaire Monthly Labor Review, September, 10 28 Rips, L J, Conrad, F G and Fricker, S S (2003) Straightening the seam effect in panel surveys Public Opinion Quarterly, 67, 522 554 Ryscavage, P (1993) The seam effect in SIPP s labor force data: did the recession make it worse SIPP Working Paper, No 180 Washington DC: US Census Bureau Retrieved March 6, 2008, from http://wwwsippcensusgov/sipp/wp9308pdf Tourangeau, R, Rips, L J and Rasinski, K (2000) The Psychology of Survey Response New York: Cambridge University Press Young, N (1989) Wave seam effects in the SIPP In Proceedings of the Survey Research Methods Section (pp 393 398).

r being the position vector. Using calculus of variations, Eq. (8.3-1) can be converted to the ray equation given by d dr n r rn r 8:3-2 ds ds where r is the gradient operator. The ray equation is derived rigorously in Section 8.4 by using the Eikonal equation. The ray equation given above is expressed in vector form. In Cartesian coordinates, the component equations can be written as d dx @n n ds ds @x d dx @n n ds ds @y d dx @n n ds ds @z Solution of Eq. (8.3-2) is not trivial. It can be considerably simpli ed by using the paraxial approximation in which the rays are assumed to be traveling close to the optical axis so that ds dz. Equation (8.3-2) can then be written in terms of two

Washington, DC: American Statistical Association..

Figure 2.3 Visual masking Two faces are shown on the screen, one after the other. If the interval between the first face and the second face is less than about 40 msec, you are not aware of the first face. Source: Faces from: Ekman, P., & Friesen, W.V. (1976). Pictures of facial affect. Palo Alto, CA: Consulting Psychologists.