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Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. / Чижик, Владимир Иванович; Trufanov , Alexander ; Чижик, Анна Владимировна.

Digital Geography. IMS 2023. ed. / M Bakaev; R Bolgov; A. V. Chugunov; R. Pereira; W. Zhang. Springer Nature, 2024. p. 323–332 (Springer Geography; Vol. Part F3643).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Harvard

Чижик, ВИ, Trufanov , A & Чижик, АВ 2024, Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. in M Bakaev, R Bolgov, AV Chugunov, R Pereira & W Zhang (eds), Digital Geography. IMS 2023. Springer Geography, vol. Part F3643, Springer Nature, pp. 323–332, International Conference “Internet and Modern Society” (IMS-2023), Санкт-Петербург, Russian Federation, 26/06/23. https://doi.org/10.1007/978-3-031-67762-5_25

APA

Чижик, В. И., Trufanov , A., & Чижик, А. В. (2024). Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. In M. Bakaev, R. Bolgov, A. V. Chugunov, R. Pereira, & W. Zhang (Eds.), Digital Geography. IMS 2023 (pp. 323–332). (Springer Geography; Vol. Part F3643). Springer Nature. https://doi.org/10.1007/978-3-031-67762-5_25

Vancouver

Чижик ВИ, Trufanov A, Чижик АВ. Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. In Bakaev M, Bolgov R, Chugunov AV, Pereira R, Zhang W, editors, Digital Geography. IMS 2023. Springer Nature. 2024. p. 323–332. (Springer Geography). https://doi.org/10.1007/978-3-031-67762-5_25

Author

Чижик, Владимир Иванович ; Trufanov , Alexander ; Чижик, Анна Владимировна. / Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. Digital Geography. IMS 2023. editor / M Bakaev ; R Bolgov ; A. V. Chugunov ; R. Pereira ; W. Zhang. Springer Nature, 2024. pp. 323–332 (Springer Geography).

BibTeX

@inproceedings{eb8ee19993d24379964c143c518c3fe1,
title = "Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations",
abstract = "Many applied research studies require a convenient web interface that would allow making a set of hypotheses, due to the fact that the data or the operation of algorithms is visualized. This chapter describes an experiment to create such an interface. We have chosen the theme of the production of goods from recycled materials. This process involves, for example, the use of cellulose. The first cycle of working with it involves the process of dissolution. In order for this to be economically feasible, it is necessary to select an ionic liquid. It is obvious that the process of selecting a substance can be automated; appropriate algorithms are developing every year. And so that people who are not related to chemistry and physics can make decisions, it is necessary to provide them with a tool that helps in this. Thus, we have chosen a sphere where there are ML models, and the visualized conclusions of algorithms can help a nonspecialist to make decisions.",
keywords = "Ionic liquids, ML models, Web service",
author = "Чижик, {Владимир Иванович} and Alexander Trufanov and Чижик, {Анна Владимировна}",
note = "Anna V. Chizhik, Vladimir Chizhik, Alexander Trufanov . Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations. In: Bakaev, M., Bolgov, R., Chugunov, A.V., Pereira, R., R, E., Zhang, W. (eds) Digital Geography. IMS 2023. Springer Geography. Springer, Cham. Conference paper. First Online: 09 November 2024. pp 323–332. ; International Conference “Internet and Modern Society” (IMS-2023), IMS-2023 ; Conference date: 26-06-2023 Through 28-06-2023",
year = "2024",
doi = "10.1007/978-3-031-67762-5_25",
language = "English",
isbn = "978-3-031-67761-8",
series = "Springer Geography",
publisher = "Springer Nature",
pages = "323–332",
editor = "M Bakaev and R Bolgov and Chugunov, {A. V.} and R. Pereira and W. Zhang",
booktitle = "Digital Geography. IMS 2023",
address = "Germany",
url = "https://ims.itmo.ru/, https://ims.itmo.ru",

}

RIS

TY - GEN

T1 - Machine Learning Deployment as a Web Service to Evaluate the Production Cycle of Environmental Goods: Primary Analysis of Ionic Liquids with Visualizations

AU - Чижик, Владимир Иванович

AU - Trufanov , Alexander

AU - Чижик, Анна Владимировна

N1 - Conference code: 26

PY - 2024

Y1 - 2024

N2 - Many applied research studies require a convenient web interface that would allow making a set of hypotheses, due to the fact that the data or the operation of algorithms is visualized. This chapter describes an experiment to create such an interface. We have chosen the theme of the production of goods from recycled materials. This process involves, for example, the use of cellulose. The first cycle of working with it involves the process of dissolution. In order for this to be economically feasible, it is necessary to select an ionic liquid. It is obvious that the process of selecting a substance can be automated; appropriate algorithms are developing every year. And so that people who are not related to chemistry and physics can make decisions, it is necessary to provide them with a tool that helps in this. Thus, we have chosen a sphere where there are ML models, and the visualized conclusions of algorithms can help a nonspecialist to make decisions.

AB - Many applied research studies require a convenient web interface that would allow making a set of hypotheses, due to the fact that the data or the operation of algorithms is visualized. This chapter describes an experiment to create such an interface. We have chosen the theme of the production of goods from recycled materials. This process involves, for example, the use of cellulose. The first cycle of working with it involves the process of dissolution. In order for this to be economically feasible, it is necessary to select an ionic liquid. It is obvious that the process of selecting a substance can be automated; appropriate algorithms are developing every year. And so that people who are not related to chemistry and physics can make decisions, it is necessary to provide them with a tool that helps in this. Thus, we have chosen a sphere where there are ML models, and the visualized conclusions of algorithms can help a nonspecialist to make decisions.

KW - Ionic liquids

KW - ML models

KW - Web service

UR - https://www.mendeley.com/catalogue/c1211d6d-c0d6-3398-9716-fa25367d8f5b/

U2 - 10.1007/978-3-031-67762-5_25

DO - 10.1007/978-3-031-67762-5_25

M3 - Conference contribution

SN - 978-3-031-67761-8

T3 - Springer Geography

SP - 323

EP - 332

BT - Digital Geography. IMS 2023

A2 - Bakaev, M

A2 - Bolgov, R

A2 - Chugunov, A. V.

A2 - Pereira, R.

A2 - Zhang, W.

PB - Springer Nature

T2 - International Conference “Internet and Modern Society” (IMS-2023)

Y2 - 26 June 2023 through 28 June 2023

ER -

ID: 127288256