Bulletin of the Computational Statistics of Japan

Pathological diagnostic reports are created after the result of diagnosing specimen images which may contain cancerous tissues in histopathological diagnosis. We have developed a histopathological information database system which stores and retrieves both diagnostic reports as text information and histological samples as images. Similar images are retrieved in the database using feature vectors made by Wavelet transformation and neural network. In addition, diagnostic probability based on Bayes' theorem was created after digitization of diagnostic data with text mining technique. Then the accuracy of image retrieval is improved by the diagnostic probability model linked with images.

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Supersaturated designs are fractional factorial designs in which the number of columns is greater than or equal to the number of runs. They are helpful when the number of factors to be assigned in an experiment is large, for example, when screening to find a few active factors from many candidates in the primary stage of a scientific investigation and product development. There are several theoretical and computational approaches to construct supersaturated designs, such as random balance design, application of BIBD, algorithmic approach including permutation of rows and columns and so forth. This paper constructs supersaturated designs by an application of random generation and swap method as a two-stage optimization technique. The first stage intends to minimize the total dependency of all paired columns by applying the random generation. The second stage swaps some elements in columns based on the coincidence numbers of rows. The constructed designs are compared with the previous studies by numerical examples. It is demonstrated that the proposed designs have advantages in terms of low-dependency measured by χ^2 values comparing with the previous studies.

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This paper studies how changes in land prices affected spatial population movement in Tokyo from 1983 to 2006. We first estimate land prices in Tokyo by universal cokriging, which capitalizes on the spatial and temporal correlations in land prices. We next build a structural equation model (SEM) for migration among the municipalities in Tokyo using economic variables, including land prices. The Kullback-Leibler (KL) information for all combinations of two municipalities in Tokyo is then computed from the estimated SEM. Finally, we classify the municipalities in Tokyo based on the KL information. The resultant four groups are characterized from an economic viewpoint. More applications are needed to test the reliability of our approach.

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