Toponyms and other named entities are main issues in unknown word processing problem. Our purpose is to salvage unknown toponyms, not only for avoiding noises but also providing them information of area candidates to where they may belong. Most of previous toponym resolution methods were targeting disambiguation among area candidates, which is caused by the multiple existence of a toponym. These approaches were mostly based on gazetteers and contexts. When it comes to the documents which may contain toponyms worldwide, like newspaper articles, toponym resolution is not just an ambiguity resolution, but an area candidate selection from all the areas on Earth. Thus we propose an automatic toponym resolution method which enables to identify its area candidates based only on their surface statistics, in place of dictionary-lookup approaches. Our method combines two modules, area candidate reduction and area candidate examination which uses block-unit data, to obtain high accuracy without reducing recall rate. Our empirical result showed 85.54% precision rate, 91.92% recall rate and .89 F-measure value on average. This method is a flexible and robust approach for toponym resolution targeting unrestricted number of areas.

We have numerically evaluated the filtering characteristics of two vertically coupled microring resonator filters. In this evaluation we used the finite-difference time-domain method as the numerical analysis method. The structure we designed allows only a specific wavelength to pass. The filtering characteristics of this structure can be altered by changing the layout of the microring resonator. By using this structure the interval between peak wavelengths at a specific wavelength in the output spectrum can be increased. Specifically, the interval between peak wavelengths can be increased from 20 nm to 40 nm at wavelengths near 1.46 µm.