NUKAZAWA Kei

写真a

Affiliation

Engineering educational research section Department of Civil and Environmental Engineerring Program

Title

Associate Professor

External Link

Degree 【 display / non-display

  • Doctor (Engineering) ( 2013.3   Tohoku University )

Research Areas 【 display / non-display

  • Environmental Science/Agriculture Science / Environmental dynamic analysis

  • Social Infrastructure (Civil Engineering, Architecture, Disaster Prevention) / Hydroengineering

 

Papers 【 display / non-display

  • Prediction of Microcystis Occurrences and Analysis Using Machine Learning in High-Dimension, Low-Sample-Size and Imbalanced Water Quality Data Reviewed

    Mori M., Gonzalez Flores R., Suzuki Y., Nukazawa K., Hiraoka T., Nonaka H.

    Harmful Algae   117   2022.8

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Harmful Algae  

    Machine learning, Deep learning, and water quality data have been used in recent years to predict the outbreak of harmful algae, especially Microcystis, and analyze outbreak causes. However, for various reasons, water quality data are often High-Dimension, Low-Sample- Size (HDLSS), meaning the sample size is lower than the number of dimensions. Moreover, imbalance problems may arise due to bias in the occurrence frequency of Microcystis. These problems make predicting the occurrence of Microcystis and analyzing its causes with machine learning difficult. In this study, a machine learning model that applies Feature Engineering (FE) and Feature Selection (FS) algorithms are used to predict outbreaks of Microcystis and analyze the outbreak factors from imbalanced HDLSS water quality data. The prediction performance was verified with binary classification to determine whether Microcystis would occur in the future by applying three machine learning models to four data patterns. The cause analysis of Microcystis occurrence was performed by visualizing the results of applying FE and FS. For the test data, the predictive performance of FE and FS methods was significantly better than that of the conventional method, with an accuracy of .108 points and an F-value of .691 points higher than the conventional method. A prediction performance increase was observed with a smaller model capacity. Data-driven analysis suggested that total nitrogen, chemical oxygen demand, chlorophyll-a, dissolved oxygen saturation, and water temperature are associated with Microcystis occurrences. The results also indicated that basic statistics of the water quality distribution (especially mean, standard deviation, and skewness) over a year, not the concentrations of water components, are related to the occurrence of Microcystis. These are new findings not found in previous studies and are expected to contribute significantly to future studies of algae. This study provides a method for analyzing water quality data with high-dimensionality and small samples, imbalance problems, or both.

    DOI: 10.1016/j.hal.2022.102273

    Scopus

  • Antibiotic-resistant Escherichia coli isolated from dairy cows and their surrounding environment on a livestock farm practicing prudent antimicrobial use Reviewed

    Suzuki Y., Hiroki H., Xie H., Nishiyama M., Sakamoto S.H., Uemura R., Nukazawa K., Ogura Y., Watanabe T., Kobayashi I.

    International Journal of Hygiene and Environmental Health   240   2022.3

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:International Journal of Hygiene and Environmental Health  

    On a livestock farm where antimicrobial administration and its history had been managed for prudent use of antimicrobials, we surveyed antibiotic-resistant Escherichia coli strains isolated from cow feces and the surrounding environment (i.e., rat and crow feces, and water samples from a drainage pit and wastewater processing tank) every month for 1 year. Two strains (1.7%) in cow feces were resistant to tetracycline, whereas all other strains were susceptible to all other antimicrobials. Among 136 strains isolated from cows and wild animals, only one ampicillin-resistant strain was identified. The antibiotic resistance rate in the drainage from the barn was 8.3% (10/120), and all strains showed susceptibility for 8 months of the year. Tetracycline resistance was common in all resistant strains isolated from animal feces and water samples; all tetracycline-resistant strains carried tetA. These results strongly support the proper use and management of antibiotics on farms to minimize the outbreak and spread of antibiotic-resistant bacteria.

    DOI: 10.1016/j.ijheh.2022.113930

    Scopus

  • Plant debris are hotbeds for pathogenic bacteria on recreational sandy beaches Reviewed

    Suzuki Y., Shimizu H., Kuroda T., Takada Y., Nukazawa K.

    Scientific Reports   11 ( 1 )   2021.12

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Scientific Reports  

    On recreational sandy beaches, there are guidelines for the management of bacterial pollution in coastal waters regarding untreated sewage, urban wastewater, and industrial wastewater. However, terrestrial plant debris on coastal beaches can be abundant especially after floods and whilst it has rarely been considered a concern, the bacterial population associated with this type of pollution from the viewpoint of public health has not been adequately assessed. In this study, microbes associated with plant debris drifting onto Kizaki Beach in Japan were monitored for 8 months throughout the rainy season, summer, typhoon season, and winter. Here we show that faecal-indicator bacteria in the plant debris and sand under the debris were significantly higher than the number of faecal bacteria in the sand after a 2015 typhoon. When we focused on specific pathogenic bacteria, Brevundimonas vesicularis and Pseudomonas alcaligenes were commonly detected only in the plant debris and sand under the debris during the survey period. The prompt removal of plant debris would therefore help create safer beaches.

    DOI: 10.1038/s41598-021-91066-w

    Scopus

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  • Dengue disease dynamics are modulated by the combined influences of precipitation and landscape: A machine learning approach Reviewed

    Francisco M.E., Carvajal T.M., Ryo M., Nukazawa K., Amalin D.M., Watanabe K.

    Science of the Total Environment   792   2021.10

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:Science of the Total Environment  

    Background: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints. Objectives: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence. Methods: Entomological, epidemiological, and landscape data from the rainy season (July–December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. Results: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas. Conclusions: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.

    DOI: 10.1016/j.scitotenv.2021.148406

    Scopus

  • Enhancement of sunlight irradiation for wastewater disinfection by mixing with seawater

    Suzuki Y., Uno M., Nishiyama M., Nukazawa K., Masago Y.

    Journal of Water and Health   19 ( 5 )   836 - 845   2021.10

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Journal of Water and Health  

    There is a need for developing a simple and easy-to-maintain disinfection technique for sewage treatment for use in developing countries and disaster-affected areas. We propose a novel disinfection technology that inactivates bacteria in wastewater via sunlight irradiation under high salt concentration by mixing with seawater. The disinfection efficiency of the proposed method was quantitatively evaluated and examined using fecal indicator bacteria. When the salinity in wastewater was adjusted to 30 practical salinity units by mixing with seawater, the constant of inactivation irradiation energy Ks (m2/MJ) was 1.6-2.2-fold greater than that without seawater for total coliforms and Escherichia coli. By contrast, although enterococci were inactivated by sunlight irradiation, an increase in salinity did not enhance disinfection. On setting the irradiation energy of sunlight to 5.5 MJ/m2,.99% of the fecal indicator bacteria were inactivated. Finally, we examined the relationship between the attenuation of irradiance and water depth and accordingly proposed a design of a treatment system wherein wastewater and seawater were adequately mixed and passed via a disinfection tank under the natural flow with sunlight irradiation.

    DOI: 10.2166/wh.2021.153

    Scopus

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Books 【 display / non-display

  • 宮崎県一ツ瀬川における濁水長期化 ~その原因と産官学民が連携した対策~

    杉尾哲, 糠澤桂, 鈴木祥広( Role: Edit)

    パブフル  2022.2 

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    Book type:Scholarly book

  • 河川工学

    風間 聡, 小森 大輔, 峠 嘉哉, 糠澤 桂, 横尾 善之, 渡辺 一也( Role: Contributor)

    理工図書  2020.9  ( ISBN:9784844608844

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    Language:Japanese Book type:Textbook, survey, introduction

    CiNii Books

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MISC 【 display / non-display

  • ダム堆砂対策による河川生態系の応答に関する事例紹介 Invited

    糠澤桂,鈴木祥広

    電力土木   2020.1

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)  

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Presentations 【 display / non-display

  • Catchment scale modeling of riverine species diversity using hydrological simulation Invited International conference

    Nukazawa K.

    Guest Lecture in Water Resources Engineering Dept. Engineering Faculty, Universitas Brawijaya 

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    Event date: 2022.3.19

    Language:English   Presentation type:Oral presentation (invited, special)  

  • コロイド吸着と泡沫濃縮法を利用した細胞外 DNA の超高感度検出・定量法の開発

    玉井荘一郎,小椋義俊,糠澤桂,鈴木祥広

    第56回日本水環境学会年会(オンライン) 

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    Event date: 2022.3.16 - 2022.3.18

    Language:Japanese   Presentation type:Oral presentation (general)  

  • 下水処理場における ESBL 耐性大腸菌・大腸菌群の消長と ESBL 関連遺伝子の保有率変化

    山田佳奈,謝暉,糠澤桂,鈴木祥広

    第56回日本水環境学会年会(オンライン) 

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    Event date: 2022.3.16 - 2022.3.18

    Language:Japanese   Presentation type:Oral presentation (general)  

  • 河川の上流から河口に至る薬剤耐性菌の菌数・菌叢の変動解析

    加藤優貴,謝暉,糠澤桂,鈴木祥広

    第56回日本水環境学会年会(オンライン) 

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    Event date: 2022.3.16 - 2022.3.18

    Language:Japanese   Presentation type:Oral presentation (general)  

  • 海岸に漂着したプラスチックゴミと植物デブリに存在する細菌の菌数と細菌叢の比較

    杉山航,糠澤桂,鈴木祥広

    第56回日本水環境学会年会(オンライン) 

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    Event date: 2022.3.16 - 2022.3.18

    Language:Japanese   Presentation type:Oral presentation (general)  

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Awards 【 display / non-display

  • 第55回環境工学研究フォーラム 優秀ポスター発表賞

    2018.12   土木学会  

    西村恵美,糠澤桂,鈴木祥広

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • 応用生態工学会第22回研究発表会 優秀ポスター研究発表賞

    2018.9   応用生態工学会  

    糠澤桂

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • 平成28年度建設工学研究奨励賞

    2017.6   一般財団法人建設工学研究振興会   宮崎における分布型汚濁流出モデルの開発とその利用による河川環境・生物多様性評価

    糠澤桂

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    Award type:International academic award (Japan or overseas)  Country:Japan

  • 第21回地球環境シンポジウム 優秀講演賞

    2014.9   土木学会地球環境委員会  

    糠澤桂, 風間聡, 渡辺幸三

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • 平成24年度東北大学 工学研究科長賞

    2013.3   東北大学  

    糠澤桂

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    Country:Japan

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Grant-in-Aid for Scientific Research 【 display / non-display

  • 人口減少下での中小河川の水文・環境変化と新しい管理手法の研究

    Grant number:20H00256  2020.04 - 2024.03

    科学研究費補助金  基盤研究(A)

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    Authorship:Coinvestigator(s) 

  • 蚊共生細菌ボルバキアによるデング熱の生態学的制御:安心・安価な新技術の提案

    Grant number:19KK0107  2019.10 - 2022.03

    独立行政法人日本学術振興会  科学研究費補助金  国際共同研究加速基金(国際共同研究強化(B))

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    Authorship:Coinvestigator(s) 

  • 流出解析に基づく流域一貫の河川生息場モデルの高度化: 流況と空間解像度に着目して

    Grant number:19K15101  2019.04 - 2022.03

    科学研究費補助金  若手研究

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    Authorship:Principal investigator 

  • Eco-epidemiology of Dengue Mosquitoes in Bandung, Indonesia in Relation to Viral Tra nsmission and Climate Change

    2019.04 - 2022.03

    Grant-in-Aid for Scientific Research 

  • 健全な流砂系の回復によるサステナブル流域総合土砂管理の実証研究

    2017.04 - 2020.03

    科学研究費補助金  基盤研究(B)

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    Authorship:Coinvestigator(s) 

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Other research activities 【 display / non-display

  • 小丸川水系生物調査

    2018.04