In this paper, we examine effective policies for financing preservation of the forest on Mt. Ryuoh in the city of Higashi-Hiroshima by multiattribute utility analysis. In multiattribute utility analysis, we deal with decision making problems using multiple attributes and can select the most effective solution among several alternatives by assessing single-attribute utility functions and identifying multiattribute utility functions regarding preference of the decision maker such as tradeoffs between attributes. The alternatives are characterized by financing methods for preserving the forest and by allocation methods of the obtained funds. The decision maker in our problem is an NPO which is established to preserve the forest. Ideas of residents and companies such as sake brewers in Higashi-Hiroshima are paid serious attention for evaluation of the alternatives.
Fuzzy theory has attracted a lot of attention as a method that introduces human subjectivity into science. Recently, the importance of utilization of a user's subjective view has been pointed out in the field of Chance Discovery. This paper proposes a method that visualizes the user's subjective view of multi-dimensional data. The user lists words that he/she considers appropriate to explain some of the features of data, and selects variables associated with each word based on his/her view. A visualized space is constructed with projection axes that are obtained as linear combinations of the selected variables for each word. The proposed method employs the Principal Component Analysis (PCA) or Multiple Discriminant Analysis (MDA) for identifying the projection axes. Through the visualized data, the user can observe his/her own subjective view of the data, and he/she can share and discuss it with other people. This paper applies the proposed method to a data set of decathlon in the Sydney Olympic Games. In this experiment, the user's subjective view of data is visualized. This paper shows that the proposed method succeeds in providing the user with a new interpretation of the data different from the conventional ones. This paper also shows that the visualization of the data using subjective variable selection can yield meaningful results different from those of the PCA applied to all the combinations from ten variables, and that of factor analysis.
In this paper, we will present the cellular automata simulation of the traffic flow on the freeway including a construction zone. Two-lane and three-lane freeways with a construction zone are considered as the object domains and the simulation results are compared with the results of one-lane and two-lane freeways without a construction zone. Although it is predicted that the traffic flow of the freeway with the construction zone depends only on the number of the freely available lanes, the simulation results shows that the traffic flow depends not only on the number of the available lanes but also the length of the construction zone.
Binocular disparity is one of the most important cues for depth perception in humans. Previously, some of the authors performed electroencephalogram (EEG) measurement in subjects viewing random dot stereograms (RDSs) with 3 binocular disparities: no, small or large disparity, and estimated the brain sites where the visual information was processed for human stereopsis, using equivalent current dipole source localization (ECDL) method. The results showed that: 1) the postcentral gyrus (PstCG) is involved in visual processing of stereopsis; and 2) all-channel average EEGs converge and the convergence time for larger RDS disparity is longer than that for smaller one. With reference with the above findings, the present study divided the cerebral visual processing for stereopsis into the processing before and after when PstCG is estimated, and compared the brain sites and their temporal transition in observing RDSs with different disparities. Subjects wore crystal shutter glasses for observing RDSs and an electrode cap for EEG measurement. By difference waves between small and no disparities and between large and no disparities, temporal features for cerebral processing of the RDSs with disparities were extracted. Application of the ECDL method to the average data for small and large disparities revealed that the visual processing before the PstCG localization consists of two pathways: one is from V1 to V4 and then to the TE field; and the other from V1 to the MT field and then to the PstCG. This result did not depend on the amount of disparity. After the PstCG localization, ECDs were localized to the superior colliculus (SC) and frontal visual field (FEF), both of which are involved in ocular movements. At the interval between the FEF localization and the EEG convergence, ECDs were located at the inferior frontal gyrus (IFG) and middle frontal gyrus (MFG). For RDSs with large disparities, the IFG and MFG ECDs were estimated earlier than those for small disparities, while for large disparities the convergence time and the time when ECDs were localized to the IFG just before the convergence time were later than those for small disparities.