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Titlebook: Japan Study as a Public Good in Asia; Lin Huang,Jin-wen Song,Mei Huang Book 2019 The Author(s), under exclusive license to Springer Nature

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發(fā)表于 2025-3-21 17:12:40 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Japan Study as a Public Good in Asia
編輯Lin Huang,Jin-wen Song,Mei Huang
視頻videohttp://file.papertrans.cn/501/500466/500466.mp4
概述Describes and clarifies how common problems can be resolved in Japan and Asia.Collects results from researchers in Japan, China, South Korea, and Indonesia.Focuses on birthrates, aging society, techno
叢書名稱SpringerBriefs in Economics
圖書封面Titlebook: Japan Study as a Public Good in Asia;  Lin Huang,Jin-wen Song,Mei Huang Book 2019 The Author(s), under exclusive license to Springer Nature
描述This book describes and clarifies how certain problems can be resolved in Japan and Asia. For the future, the focus should be on Japan, which can provide "common knowledge" as a public good. The book collects the results of researchers in Japan, China, South Korea, and Indonesia on declining birthrates and aging, rapid technological innovation and societal changes, and recovery from natural disasters..Chapter 1 covers Japanese social welfare system reform and transformation of social governance. Chapter 2 deals with the decreasing birthrate and national security. Chapters 3 to 5 discuss three aspects of the impact of modern technology on Japanese society. Chapter 6 and 7 include the research results on recovery from the earthquake disasters in Indonesia and East Japan.? ..Through reading this book, the increasingly necessity to capture Japanese studies in Asia as a public good can be understood. The authors believe that sharing of knowledge as a public good is of great help in solving problems for the future..
出版日期Book 2019
關(guān)鍵詞Common knowledge as a public good; Declining birthrate; Aging society; Technological innovation; Differe
版次1
doihttps://doi.org/10.1007/978-981-13-6336-8
isbn_softcover978-981-13-6335-1
isbn_ebook978-981-13-6336-8Series ISSN 2191-5504 Series E-ISSN 2191-5512
issn_series 2191-5504
copyrightThe Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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Kijeong Nams no clear understanding of the way these algorithms complete the search. For that reason, in this work we exploit the probabilistic models that EDAs based on Bayesian networks are able to learn in order to provide new information about their behavior. Particularly, we analyze the . solutions with t
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