Developement of sensor hardware/software toward breath diagnostics based on multi-dimensional data analysis algorithm
| Project/Area Number |
15H03588
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
General applied physics
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| Research Institution | National Institute for Materials Science |
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Principal Investigator |
Yoshikawa Genki 国立研究開発法人物質・材料研究機構, 国際ナノアーキテクトニクス研究拠点, グループリーダー (70401172)
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| Co-Investigator(Renkei-kenkyūsha) |
Washio Takashi 大阪大学, 産業科学研究所, 教授 (00192815)
Shiba Kota 国立研究開発法人物質・材料研究機構, 国際ナノアーキテクトニクス研究拠点, 主任研究員 (20638126)
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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 |
¥14,820,000 (Direct Cost: ¥11,400,000、Indirect Cost: ¥3,420,000)
Fiscal Year 2017: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2016: ¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2015: ¥5,980,000 (Direct Cost: ¥4,600,000、Indirect Cost: ¥1,380,000)
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| Keywords | olfactory sensors / MSS / nanomechanical sensors / receptor materials / nanoparticles / data analysis / machine learning / 嗅覚センサ / データサイエンス / ナノメカニカルセンサ / ビッグデータ解析 |
|---|
| Outline of Final Research Achievements |
Accurate identification of complex smell/odor (e.g. exhaled breath) composed of diverse molecules requires optimization of both hardware (multiple sensors with diverse chemical selectivity) and software (multidimensional data analysis). In this study, sensor system components including receptor materials have been developed together with the detailed investigation into basic analytical methods of sensing data. Further, significant enhancement of predication accuracy of complex smell/odor has been demonstrated through the optimization of sensors based on machine learning of multidimensional sensing data. These studies provide a guideline for hardware-software mutual optimization of sensors.
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Report
(4 results)
Research Products
(86 results)
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[Book] 質量分析学会誌2018
Author(s)
南皓輔, 柴弘太, Thien Huynh Ngo, 今村岳, 吉川元起
Total Pages
62
Publisher
一般社団法人 日本質量分析学会
Related Report
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