| Project/Area Number |
15H01713
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Kansei informatics
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| Research Institution | Kyushu University |
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Principal Investigator |
HAYASHI Kenshi 九州大学, システム情報科学研究院, 教授 (50202263)
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| Co-Investigator(Kenkyū-buntansha) |
中野 幸二 九州大学, 工学研究院, 准教授 (10180324)
冨浦 洋一 九州大学, システム情報科学研究院, 教授 (10217523)
李 丞祐 北九州市立大学, 国際環境工学部, 教授 (60326460)
内田 誠一 九州大学, システム情報科学研究院, 教授 (70315125)
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| Co-Investigator(Renkei-kenkyūsha) |
SASSA Fumihiro 九州大学, システム情報科学研究院, 助教 (30722681)
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| Research Collaborator |
LIU Chuanjun (株)ユー・エス・イー, 主幹研究員
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥43,810,000 (Direct Cost: ¥33,700,000、Indirect Cost: ¥10,110,000)
Fiscal Year 2017: ¥9,100,000 (Direct Cost: ¥7,000,000、Indirect Cost: ¥2,100,000)
Fiscal Year 2016: ¥14,560,000 (Direct Cost: ¥11,200,000、Indirect Cost: ¥3,360,000)
Fiscal Year 2015: ¥20,150,000 (Direct Cost: ¥15,500,000、Indirect Cost: ¥4,650,000)
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| Keywords | 匂いセンサ / イメージング / 分子認識 / 可視化画像解析 / 匂いマップ / センサ / 匂い予測 / 二次元化学センサ / 匂い / 可視化 / 画像解析 |
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| Outline of Final Research Achievements |
In order to treat odors which are difficult to measure, model and analyze as digital information, we have researched on development of basic technology of odor image sensor and analysis technology of odor quality. Following results are successfully attained; host molecules which selectively responding to odor molecules, acceptor peptide synthesis, selective extraction technology of odorants and medical applications, visualization of odor flow and traces as multispectral images, fluorescence probe visualization film and odor composition analysis of ingredients, development of odor visualization film by molecular imprinting polymer, technology to characterize odor quality by olfactory odor map on olfactory bulb, technology to predict odor quality by machine learning by molecular parameter, and intuitive odor quality presentation methods by relationship graphs.
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