In this paper, we propose the detection method of plural polygonal figures, regardless of the figure's configuration. In this proposed method, we use the immune algorithm which can search local solutions effectively, as optimization method, and we use antibodies coding some kinds of figure's configuration respectively. In our experiment using objective image with several kinds of polygons which have less than 6 vertices, we have proven that our proposed method can search plural polygons which have different size and number of vertices.

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Open access movement is a hot issue in a recent Library and Information Science. This article analyzed 'the Budapest Open Access Initiative (BOAI),' which triggered the open access movement. First, this article introduced the foundation, 'the Open Society Institute (OSI),' which has proposed and supported BOAI, and its founder, George Soros. We also surveyed their philosophical basis, the concept of 'Open Society' -Karl R. Popper advocated. In addition, we revealed that BOAI was affected by the concept of 'Open Society'. Second, we revealed how people accepted the concept of 'Open Society' by quantitative analysis of literatures about open access. As a result, it was revealed that while OSI participated to the open access movements to achieve the concept of 'Open Society' people in open access movement have not referred to OSI's intention.

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In this study, the "structural highangle-view" proposed by the authors, in which knowledge is expressed structurally in highangle views, is extended, and the Cosut (Concept Support Tool) is proposed, in which the highangle-view map is produced by adding attributes and descriptions to the items of knowledge which form the view, upon providing the meaning of each relationship between the items of knowledge to which such attribute information, etc., have been added. By using Cosut, it becomes possible to further organize and analyze the set of items of knowledge. That is, it is thought that it can be used to effectively utilize knowledge in various scenes such as in developing new products or solving problems in enterprises, or further, in considering new theories in research organizations. In an evaluation experiment, a quantitative comparison with the case of not using Cosut was made, and changes in the structure of concepts were analyzed. As a result, the tendency of a quantitative increase in the number of ideas for developing hypotheses was confirmed, and further, effects of supporting idea generation, such as making possible the identification of the parts where Cosut directly influenced the subject's structure of concepts, were found.

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Community Question Answering (CQA) has recently become a popular means of satisfying personal information needs. However, as the quality of the answers posted to CQA sites vary widely, there is a need for effectively extracting high-quality answers from CQA data. In this study, we first manually analyzed high-quality answers from the Yahoo! Chiebukuro data, and then constructed a system that automatically detects high-quality answers based on the analysis. More specifically, we randomly sampled 50 questions from four Yahoo! question categories, namely, ``Love Consultation,'' ``Personal Computer,'' ``General Knowledge'' and ``Politics,'' and two of the authors manually selected high-quality answers from the answers to these questions. Then, based on the analysis of these answers, we constructed an answer quality estimator based on a machine learning algorithm that uses detailedness, presence of evidence, and politeness as features. Our system outperformed the human assessors for the Personal Computer and General Knowledge categories, while its evaluation was comparable to the assessors for Love Consultation and Politics. These findings suggest the possibility of the system that automatically discovers high-quality answers from the CQA archives.

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To evaluate how the deposition of journal articles in Institutional Repositories (IRs) affects the number of citations and e-journal usage, we placed some articles published in Zoological Science in two Japanese IRs and collected their usage data in IRs and e-journals, as well as with the number of resulting citations. The experiment was started in 2008 and we compared the number of e-journal usage and citations of articles deposited in IRs before and after the experiment with those were not. In addition, we analyzed users' behaviour in IRs and compared user groups in IRs with those in e-journals based on users' IP addresses. The results revealed that deposition in IRs did not reduce e-journal usage. Moreover, whereas the journals gained new readers, this did not have an effect on the number of citations because most of new readers may be not researchers in Zoology but those in other fields or lay people.

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