The real Voices of British Citizens on the Referendum 2016

Britain held the EU referendum on 23 June 2016, and came into the process for leaving the European Union. I was in Coventry, UK, from April to August in 2016, as Visiting Fellow, at the School of Law, the University of Warwick. I often discussed the referendum with many citizens during and after the referendum. My report is an inquiry into their feelings on it. However, it was not made through collecting random samples of their voices. This is the report of their real voices on the referendum. I have found their feelings in their ordinary lives, concerning the referendum, in my communication with my many friends in Coventry. This inquiry illuminates the actual feelings and opinions of the both sides of the referendum. It is impossible to find them through public opinion polls. This is the reason why my report is important

Development of a general-purpose algorithm to measure motion and state of attention object - Study report on method of using deep learning for quantitative science research -

本報告文は、深層学習がなぜ高い表現力を持つのかの説明をした後、畳み込み層1相のシンプルな深層学習アルゴリズムを用いて、深層学習はどのように基礎研究に応用できるのかの具体例を示す。その例とは、動画データの中で、注目したい観察対象の位置推定を行い、その推定位置の近傍の画像を用いて観察対象の状態分類の学習を行なえば、高い精度の状態識別が行なえるというものである。具体的に、収縮ユニットであるサルコメアが振動のパターンを作り出している筋原線維に対して、注目するサルコメアの位置を捉えつつ、その注目しているサルコメアが収縮しているか伸展しているかを識別する解析と、手ぶれで揺れる動画の中で電線にとまっている鳥の挙動を識別する解析を、同じ解析アルゴリズムで行なった。どちらの解析でも、数十枚以下の画像による2,30回の学習(CPUノートPCで数秒で完了)で識別率100%の状態認識に至った。すなわち、位置推定などの精密解析を行う際に、その推定位置近傍の微小画像を状態識別に用いることで、手動だと大変でかつ再現性を疑われる、対象の状態に関する情報を容易に取得できることが分かった

Possibility of floating foundation for reducing damage by ground liquefaction

In order to confirm the effect of liquefaction countermeasure of the floating foundation method, the authors conducted a field survey after the disaster of the 2011 Tohoku Pacific Offshore Earthquake using a model shaking table test and simple numerical analysis. As a result, it is confirmed that the settlement and tilting of houses by liquefaction can be suppressed by the application of the floating foundation method

Survey of Mammal Fauna using Camera Trapping method at the Chikusui forest, Kasugai, Aichi Prefecture, Japan

愛知県春日井市築水の森に生息する哺乳類相を明らかにするため,2017年7～11月の期間,5台の自動撮影カメラを用いて調査した.本調査でのカメラ稼働日数は5台のカメラの合計で695日となり,全撮影枚数2,019枚のうち有効撮影枚数は1,980 枚となった.本調査で撮影された哺乳類は中・大型哺乳類7 種で,撮影頻度が最も高くなったのはイノシシ Sus scrofa (57.3 枚/100日,以降同様) で,次いでイエネコ Felis catus (1.9),ハクビシン Paguma larvata (1.2),キツネ Vulpes vulpes (1.0),タヌキ Nyctereutes procyonoides (0.7),ニホンノウサギ Lepus brachyurus (0.1),イタチ属 Mustela sp.(0.1) の順となった.希薄化曲線を作成した結果,すべての哺乳類を撮影するためには約250 日間のカメラ稼働日数が必要であることが明らかとなったため,本調査地に生息するすべての哺乳類を撮影できていなかったと考えられた.しかし,本調査では在来の中・大型地上性哺乳類種4種(イノシシ,キツネ,タヌキ及びニホンノウサギ)の生息が確認できたことから,築水の森は愛知県東部丘陵地の在来種生息地として貢献していることを明らかにすることはできた.その一方で,最も撮影頻度が高かったイノシシと築水の森の利用者の行動時間については早朝4〜6時,夕方16〜19 時に重複していたため,この時間帯に行動する際にはイノシシとの遭遇に注意が必要であると考えられた.Survey of Mammal Fauna using Camera Trapping method in the Chikusui forest, Kasugai, Aichi Prefecture, Japan was conducted from July to November, 2017. For confirmation of mammal habitation, we set up a total of five automatic digital cameras in this forest. In 695 camera days, we obtained the 1,980 effective photographs. At the result, seven species have been photo-captured. The most frequently photographed was Sus scrofa (Relative abundance index: 57.3 photographs / 100 camera-days) and followed by Felis catus (1.9), Paguma larvata (1.2), Vulpes vulpes (1.0), Nyctereutes procyonoides (0.7), Lepus brachyurus (0.1) and Mustela sp. (0.1) have been photo-captured. To predict the number of mammal species inhabited in this forest from the number of photo-captured mammal species in this survey, a camera days-based rarefaction curve was calculated for each camera. From these results, it was predicted that about 250 days of camera days would be needed to photo-capture all mammal species in this forest. However, since this forest function as habitats for local wildlife which are representative four medium and large sized mammal species (S. scrofa, V. vulpes, N. procyonoides and L. brachyurus) in eastern foothills area of Aichi Prefecture, this forest is considered to contribute positively towards regional biodiversity conservation. As for S. scrofa and forest user activity time, it overlapped at in the morning (AM 4:00-6:00) and in the evening (PM 4:00-7:00). So, it was thought that caution is need for encounters with S. scrofa when forest user acts during this period