The electromagnetic environment in urban areas is growing increasingly complex. Sources of electromagnetic exposure like TV, FM, GSM, Wifi and others are spreading continuously and in the case of Wifi their geographical locations cannot be cataloged exhaustively anymore. Furthermore, the complexity of any highly urbanized environment and the lack of information about the dielectric properties of buildings lead to complex configuration so that a precise deterministic modeling of the electromagnetic exposure at any a given location of interest is probably out-of-reach.On the other hand there is a growing demand to assess the human exposure induced by these wireless communications. In a project between France Télécom R & D, Ecole des Mines and Supélec the application of geostatistical methods in this context is being explored.Geostatistics provides the right framework for setting up such exposure maps and its spatial statistical model yields an estimate of exposure as well as an associated error (De Doncker et al., 2006).The project consists of three phases: geostatistical evaluation of data generated by the numerical model EMF Visual (both in free space and with the addition of obstacles), statistical analysis of measurements performed in the area of the Quartier Latin in Paris and, finally, joint evaluation of an urban area both by statistical and deterministic numerical modeling.The paper reports about the third phase of this ongoing project, in which the spatial variation is modeled using the variogram, followed by a spatial regression known as kriging. The paper presents results about using a kriging algorithm that integrates numerical model output as an external drift.

Abstract-This paper describes a novel technique which has the potential to make a significant impact on the mapping of the human brain. This technique has been designed for 3D full-wave electromagnetic simulation of waves at very low frequencies and has been applied to the problem of modeling of brain waves which can be modeled as electromagnetic waves lying in the frequency range of 0.1-100 Hz. The use of this technique to model the brain waves inside the head enables one to solve the problem on a regular PC within 24 hrs, and requires just 1 GB of memory, as opposed to a few years of run time and nearly 200 Terabyte (200,000 GB) needed by the conventional FDTD (Finite Difference Time Domain) methods. The proposed technique is based on scaling the material parameters inside the head and solving the problem at a higher frequency (few tens of MHz) and then obtaining the actual fields at the frequency of interest (0.1-100 Hz) by using the fields computed at the higher frequency. The technique has been validated analytically by using the Mie Series solution for a homogeneous sphere, as well as numerically for a sphere, a finite lossy dielectric slab and the human head using the conventional Finite Difference Time Domain (FDTD) Method. The presented technique is universal and can be used to obtain full-wave solution to low-frequency problems in electromagnetics by using any numerical technique.

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By using a n e-formulation associating finite elements in t h e conductor a n d boundary elements on its surface, we compute t h e current which appears in a weakly conducting domain submitted to t h e action of a n electromagnetic wave. T h e obtained results are compared' with those given by a finite difference time domain method.