Prediction of fire risk in the biological resource layer by microbial flora activity space map utilizing data mining
Project/Area Number |
18K04645
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Review Section |
Basic Section 25020:Safety engineering-related
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Research Institution | Oita University (2020) Oita National College of Technology (2018-2019) |
Principal Investigator |
TADASHI KONISHI 大分大学, 減災・復興デザイン教育研究センター, 客員教授 (00225468)
|
Co-Investigator(Kenkyū-buntansha) |
野中 尋史 長岡技術科学大学, 工学研究科, 准教授 (70544724)
古川 隼士 北里大学, 医療衛生学部, 講師 (90632729)
廣田 雅春 岡山理科大学, 総合情報学部, 講師 (70750628)
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Project Period (FY) |
2018-04-01 – 2021-03-31
|
Project Status |
Completed (Fiscal Year 2020)
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Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2019: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
Keywords | 消防統計 / 火災統計 / ビックデータ / データサイエンス / 共起ネットワーク / ディープラーニング / 火災要因の予測 / 火災 / データマイニング / 微生物 / バイオマス / 危険性予測 |
Outline of Final Research Achievements |
In this research, we created an automatic extraction program for microbial names from a microbial database published on the Internet by data mining and a program for identifying fire-related microbial names by automatically extracting papers that have been compiled into a database in the past regarding fires.Using the original data of the Ministry of Internal Affairs and Communications Fire White Paper obtained from the Oita City Information Management Division, which is the 10-year data on fire factors and fire fatalities under the jurisdiction of the Oita City Fire Bureau, this data visually shows the connection of fire factors. The fire network was built. We built a model to predict the cause of fire by deep learning.
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Academic Significance and Societal Importance of the Research Achievements |
火災研究において,メタゲノム解析の生物学的手法および局所的環境計測の工学的手法を,データマイニングという人工知能データ解析手法で統合した方法論および目視できない微生物を仮想的に可視化する科学的手法を考案したことにに学術的意義がある.また、データマイニングによる微生物叢活性空間マップ法は,下水汚泥,糞便,食中毒,感染症予測,バイオハザード等の微生物叢動態予測に対する社会安全性への波及効果が期待される.
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Report
(4 results)
Research Products
(28 results)
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[Journal Article] Complete genome sequencing and comparative genomic analysis of KPC-2-producing Klebsiella pneumoniae isolated from a hospital sewage water in Japan.2021
Author(s)
Ryotaro Eda, Shotaro Maehana, Aki Hirabayashi, Masaki Nakamura, Takashi Furukawa, Shinsuke Ikeda, Kouji Sakai, Fumiaki Kojima, Kazunari Sei, Masato Suzuki, Hidero Kitasato.
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Journal Title
J Glob Antimicrob Resist.
Volume: 24
Pages: 180-182
DOI
Related Report
Peer Reviewed / Open Access / Int'l Joint Research
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[Journal Article] Relationship between detection of hepatitis B virus in saliva and periodontal disease in hepatitis B virus carriers in Japan, Journal of Infection and Chemotherapy2021
Author(s)
Kamimura Hiroteru, Jun Watanabe, Tomoyuki Sugano, Junji Kohisa, Hiroyuki Abe, Keny Kamimura, Atsunori Tsuchiya, Masaaki Takamura, Shogo Okoshi, Yoshinari Tanabe, Ritsuo Takagi, Hirofumi Nonaka, Shuji Terai
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Journal Title
Journal of Infection and Chemotherapy
Volume: Vol.27, No.3
Issue: 3
Pages: 492-496
DOI
Related Report
Peer Reviewed / Open Access
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[Presentation] Development the simple, specific and sensitive method to detect Biomphalaria glabrata, the intermediate host snail of Schistosoma mansoni, by applying environmental DNA approach2019
Author(s)
Furukawa, T., Kamei, T., Tsubokawa, D., Hatta, T., Tsuji, N., and Sei, K.
Organizer
20th International Symposium on HealthRelated Water Microbiology (HRWM), ABSTRACTBOOK
Related Report
Int'l Joint Research
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