Authors derived an electromagnetic theory of the contactless measuring method of electric conductivity of nonmagnetic semiconductor circular wafer referring to the arrangement shown in Fig. 1, and have got the result for d'd:(16)where V is electromotive force induced along measuring coil due to the eddy current in the wafer induced by exciting coil, for the lower frequency range:f50 MHz, λ6 m, for R 1 m (1')where R is a symbolic representation of scale of arbitrary element used in this arrangement, and under the condition that the thickness t of the wafer is much smaller than the depth of penetration δ of the semiconductor. We discussed practical measurement of V, especially separation of V and V0 which is electromotive force induced by direct field from exciting coil to measuring coil, using the phase difference between V and V0. We use SI unit system and time factor ejwt in this paper.

This paper proposes a new method of estimating real-time traffic matrices that only incurs small errors in estimation. A traffic matrix represents flows of traffic in a network. It is an essential tool for capacity planning and traffic engineering. However, the high costs involved in measurement make it difficult to assemble an accurate traffic matrix. It is therefore important to estimate a traffic matrix using limited information that only incurs small errors. Existing approaches have used IP-related information to reduce the estimation errors and computational complexity. In contrast, our method, called spike flow measurement (SFM) reduces errors and complexity by focusing on spikes. A spike is transient excessive usage of a communications link. Spikes are easily monitored through an SNMP framework. This reduces the measurement costs compared to that of other approaches. SFM identifies spike flows from traffic byte counts by detecting pairs of incoming and outgoing spikes in a network. A matrix is then constructed from collected spike flows as an approximation of the real traffic matrix. Our experimental evaluation reveals that the average error in estimation is 28%, which is sufficiently small for the method to be applied to a wide range of network nodes, including Ethernet switches and IP routers.