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servation angles are computed and averaged over many realizations. Figure 1.2.4 shows the results when 600 such realizations are averaged. The measured brightness temperatures are also shown in Fig. 1.2.4, along with the results which would be expected from a uniform density profile and the same temperature profile. The layered scattering model gives good agreement of brightness temperature with the measured results out to an observation angle of 50 0 Note that the discrete layering used by the theory (Fig. 1.2.2) is statistically similar to the observed profile (Fig. 1.2.1). No ad-hoc correction factors are required. The half-space model of uniform density does not give adequate results. The half-space model results show much less polarization contrast. The half-space model of homogeneous density gives much higher brightness temperatures that does not agree with experimental observations. These simulations show that layer scattering with centimeter layer thickness is an important phenomenon at C- band passive remote sensing of Antarctica. Extensions have been made to a Poisson process with a modified spectral density. Good agreement with data have also been found for Vestestraumen, Amundsen Ice and Base Camp stations [West, 1994].

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This last line of code de nes the form as an MDI child form 4 Add code in the Click event for the menu or toolbar option to display the form You normally show the form as a modeless window Your MDI child forms should not be modal The Click event handler code in the MDI parent form is similar to the following:

Figure 1.2.3 A histogram of the measured density profile superimposed on a histogram of one realization of a density profile using the discrete random profile described in Fig. 1.2.2.

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In this regard, capturing data from gene chips and other tests for incorporation into biological databases is a prerequisite for creating dis ease pro les that can provide the basis for automated decision support tools Several biotech companies are attempting to devise gene chips that can quickly, cheaply, and accurately detect gene sequences related to spe ci c diseases Furthermore, data regarding the expression of speci c genes and their association with particular diseases will increase as these prod ucts begin to be used on a regular basis by clinicians, other health-care workers, and the lay public In the areas of infectious disease, gene therapy, and genetic engineer ing, one of the enabling technologies is nanotechnology, in the form of arti cial viruses, which may eventually be used to treat diseases.

Jandhyala, V, E Michielssen, S Balasubramaniam, and W C Chew (1998a), A combined steepest descent-fast multipole algorithm for the fast analysis of three-dimensional scattering by rough surfaces, IEEE Trans Geosci Remote Sens, 36(3), 738-748 Jandhyala, V, B Shanker, E Michielssen, and W C Chew (1998b), A fast algorithm for the analysis of scattering by dielectric rough surface, J Opt Soc Am A, 1877-1885 Johnson, J T (1996), Applications of numerical models for rough surface scattering, PhD thesis, Massachusetts Institute of Technology Johnson, J T and H T Chou (1998), Numerical studies of low grazing angle backscatter from I-D and 2-D impedance surfaces, Proc IGRASS 1998, Seattle WA, 7295-2297 Johnson, J T, R T Shin, J C Eidson, L Tsang, and J A Kong (1997), A method of moments model for VHF propagation, IEEE Trans Antennas Propagat, 45, 115--125 Johnson, J T, R T.

Shin, J A Kong, and L Tsang (1999), A numerical study of ocean polarimetric thermal emission, IEEE Trans Geosci Remote Sens, 37(1), 8-20 Johnson, J T, L Tsang, R Shin, K Pak, C H Chan, A Ishimaru, and Y Kuga (1996), Backscattering enhancement of electromagnetic waves from two-dimensional perfectly conducting random rough surfaces: A comparison of Monte Carlo simulations with experimental data, IEEE Trans Antennas Propagat, 44, 748-756 Kapp, D A and G S Brown (1996), A new numerical method for rough surface scattering calculations, IEEE Trans Antennas Propagat, 44, 711-72I Krause, K C, S H Lou, L Tsang, and C H Chan (1991), Application of the finite element method to Monte Carlo simulations of random rough surface scattering with Neumann boundary conditions, Microwave Opt Technol Lett, 4(7), 255--258 Kuga, Y, J S Colburn, and P.

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