Journal of Coastal Zone Studies
Online ISSN : 2436-9837
Print ISSN : 1349-6123
Volume 31, Issue 1
Displaying 1-3 of 3 articles from this issue
  • Junya IIDA, Daisuke WATANABE, Kenta NAGATA, Masahiro MATSUDA
    2018Volume 31Issue 1 Pages 21-32
    Published: June 30, 2018
    Released on J-STAGE: April 17, 2023
    JOURNAL FREE ACCESS

    ABSTRACT : In order to optimize Supply Chain Management, we focus on how to share procedure status information of ocean containers in real time such as customs clearance and Delivery Order clearance across countries using Information Technology. We review studies and practical implementations related to IT systems for sharing the information and identify issues on them. Finally, we find that it would be better to use the decentralized type system for sharing the information, without attaching any additional devices such as RFID tags.

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  • Maya MATSUSHIGE, Yasunori KOZUKI, Ryoichi YAMANAKA
    2018Volume 31Issue 1 Pages 33-44
    Published: June 30, 2018
    Released on J-STAGE: April 17, 2023
    JOURNAL FREE ACCESS

    ABSTRACT:Aiming to determine the effect that the active learning (AL) style of environmental education has on the quality of learning, a study was conducted at Amagasaki Canal among elementary school children. The children engaged in the AL style of environmental education were likely to recognize the education as a series of contents and turn it into deep learning. Furthermore, the percentage of those who have developed self-directed attitudes regarding Amagasaki Canal was large among the children who had deep learning. While it was difficult to understand the effect of turning the education into the AL style on learning just by asking quantitative questions about direct emotional aspects, we was able to take children’s short open-end responses, extract and analyze sentences that represent knowledge integration and comparison, and propose a new method to understand the effect.

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  • Rikito HISAMATSU, Sooyoul KIM, Shigeru TABETA
    2018Volume 31Issue 1 Pages 45-56
    Published: June 30, 2018
    Released on J-STAGE: April 17, 2023
    JOURNAL FREE ACCESS

    ABSTRACT : The storm surge hazard maps released by the Japanese government are predicted based on scenario-based deterministic methods, but there is little accumulation of studies on probabilistically-evaluated inundation maps. By probabilistically evaluating possible strengths and paths of typhoons, it is expected that the storm surge risk with return periods in each region would be estimated, including the area considered to be low risk in the conventional evaluation method. In this study, typhoon data projected by the probabilistic typhoon model are used to estimate distributions of storm surge height with the return period in Tokyo Bay. First, the storm surges for the period of 10,000 years are calculated by an empirical formula and the top 200 typhoons are extracted. Secondly, the extracted typhoons are analyzed by a coupled model of surge, wave and tide (SuWAT) to estimate the distributions of inundation depth. Finally, the obtained inundation depths are rearranged for each mesh, and the depth distribution for each return period is estimated.

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