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Suppose the materials in medium 1 and in medium 3 are different, that is, 1 3, and we wish to minimize the re ection of electric eld intensity from a material slab. An example of this case occurs for photographic ash light propagating in air and striking glass at an orthogonal direction, as is shown in Figure 2.7. The manufacturers of eyeglasses typically offer a nonglare option that minimizes the re ection from their products. This involves a surface coat of material (medium 2) on the lens glass (medium 3 with 3 = 260 ) that reduces re ection back into air (medium 1 with 1 = 377 ). How do they choose the coating material and thickness to best accomplish this nonglare option

Virtual Force (Vector-Based) Approach. Sensors move according to a movement vector computed using the relative position of their neighbors. Voronoi-Based Approach. Sensors adjust their location to reduce uncovered local area in its Voronoi polygon possibly in multiple rounds. Load Balancing Approach. The number of sensors in the regions of a partitioned sensor eld is balanced through multiple rounds of scans. Stochastic Approach. Sensors spread out through random walk. Point-Coverage Approach. The area coverage problem is converted to a point-coverage problem over certain geographic graph. Incremental Approach. Sensors are deployed incrementally, that is, one at a time, based on the information gathered from previously deployed sensors. Maximum-Flow Approach. Sensors deployment is modeled as minimumcost, maximum- ow problem from source regions to whole regions in ROI. Genetic-Algorithm Approach. Sensor movement plan is generated by multiround selection and reproduction simulating genes and nature selection.

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correlation, aggregation, and orchestration. Academic research programs, such as TAP at Stanford, are bridging the gap between disparate Web servicebased data sources and creating a coherent Semantic Web from disparate chunks. 6 Among other things, TAP enables semantic search capabilities, using ontology-based knowledge bases of information. Companies are heavily investing in Semantic Web technologies. Adobe, for example, is reorganizing its software meta data around RDF, and they are using Web ontology-level power for managing documents. Because of this change, the information in PDF files can be understood by other software even if the software doesn t know what a PDF document is or how to display it. 7 In its recent creation of the Institute of Search and Text Analysis in California, IBM is making significant investments in Semantic Web research. Other companies, such as Germany s Ontoprise, are making a business out of ontologies, creating tools for knowledge modeling, knowledge retrieval, and knowledge integration. In the same Gartner report mentioned at the beginning of this chapter, which said Semantic Web ontologies will play a key role in 75 percent of application integration by 2005, the group also recommended that enterprises should begin to develop the needed semantic modeling and information management skills within their integration competence centers. 8 So, to answer the question of this section: Yes, we are ready for the Semantic Web. The building blocks are here, Semantic Web-supporting technologies and programs are being developed, and companies are investing more money into bringing their organizations to the level where they can utilize these technologies for competitive and monetary advantage.

is the Fourier transform of the real incident electric eld intensity evaluated just outside the propagating medium, and the term in square brackets is the transmission coef cient. Here, the wave number, k z ( ) = r ( ) c, is generally complex, with the positive imaginary part corresponding to absorption of energy during propagation. Using frequency as the variable of integration in Equation 5.114 permits us to utilize Equation 5.110 in the integrand exponent. Landau and Lifschitz21 solve the real and imaginary part of the complex permittivity function to express the nal integral. Jackson uses a one resonance model to prove that within our multiresonance analysis for permittivity, no signal can propagate with a velocity greater than c, whatever the medium. Gauthier and Boyd22 have shown how the group velocity of a pulse of light propagating through a dispersive material can exceed the speed of light in vacuum. The author recommends students read this article for a sense of enjoyment and understanding that, in very special circumstances, such as that which occurs when the derivative of the index of refraction becomes negative in the neighborhood of one of the resonances in Equation 5.110, group velocity, ug = c/[n( ) + dn( )/d ],

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