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Germany's energy transition （Energiewende） is a paradigm shift into a low-carbon and nuclear-free economy. As part of the European Union's climate neutralization drive, aiming to reduce greenhouse gases to net-zero by the middle of the century. Generous financial support for wind and solar power has boosted renewable energy to produce more electricity than fossil fuels for the first time in 2020. Germany's energy transition is not a policy shift after the Fukushima nuclear disaster, but a long-term process of policy making in response to public opinion and technological trends. Germany's energy transition is still underway and needs to be extended beyond the power supply. However, it may already be pushing more thoroughly through pricing and volume regulations, such as the European Emissions Trading Scheme （EU-ETS） and changes to the carbon tax, which provides incentives for changes to low-carbon technologies. This paper analyses Germany's energy transition and climate policy. The purpose of this paper is to clarify the actual conditions and issues of the reduction effects of greenhouse gas emissions, which are the main policy issues of the energy conversion policy that has been developed mainly on renewable energy for these 20 years.

In this study, we present a new method for estimating input coefficient matrix with deep learning. We use the data of prefectures of Japan as the training data. However, the data is small and is likely to cause overfitting. Therefore, we attempt to avoid the over-fitting by creating new data of virtual areas aggregating multiple prefectures. The approach is based on the concept of data augmentation. As a result of predicting the input coefficient matrix of Yamaguchi prefecture and Gujo city, we showed that the method using deep learning can estimate the matrix with more stable accuracy than RAS method for these areas.

This paper examines : (1) the medical governance of infectious diseases in Taiwan based on the experience of infectious diseases and the background of medical governance reform, (2) the role of big data and digital technology in infectious disease control, (3) medical strategy and non-pharmaceutical intervention, and (4) socio-political viewpoints regarding the COVID-19 pandemic in Taiwan. It will be possible to confirm that Taiwan's non-pharmaceutical intervention strategies, including mask wearing, AHH practices, quarantine / quarantine, travel restrictions and the implementation of social distancing, are increasing the effectiveness of preventive measures during the COVID-19 pandemic. In addition, the combination of extensive risk communication highlighting the importance of early border control, government leadership and preventive action has prevented Taiwan from locking down. These comprehensive preventive measures against COVID-19 in 2020 are more efficient and effective than those implemented during SARS in 2003, as well as immunoassay responses. In addition, democracy provided institutional support for vibrant civil society and synergies between state and civil society, strengthened the legitimacy of Taiwan's crisis governance, and enhanced voluntary compliance among citizens.

1990年代後半, 単独での経済発展の限界を認識したシンガポールは, リージョナライゼーションに乗り出した。そして自国をアジアのハブとすべく「世界をシンガポールへ, シンガポールを世界へ」を打ち出した。このアジアのハブ構想ではヒトの移動が不可欠な要素であった。そこで, 本論は, ヒトの移動の観点から, リージョナライゼーションの時代におけるシンガポールの国家ブランディング戦略及びその戦略のなかでの人材活用の方策を明らかにしようと試みた。観光政策と人材政策から分析をすすめた結果, ヒトが集まるアジアのハブという国家ブランドを確立しようとしていたこと, そしてアジアのハブ構想のなかで国内の労働力だけでなく観光客や国外とのネットワークをつなぐ存在としての移民を活用してきたことを明らかにした。