Mathematical modeling of systemic factors determining the risk of deterioration of drinking water supply and development of allergic diseases of population

Yurii G. Bespalov; Konstantin V. Nosov; Olena V. Vysotska; Andrii P. Porvan; Zbigniew Omiotek; Aron Burlibay; Azat Assembay; Małgorzata Szatkowska

doi:10.1117/12.2280964

7 August 2017 Mathematical modeling of systemic factors determining the risk of deterioration of drinking water supply and development of allergic diseases of population

Yurii G. Bespalov, Konstantin V. Nosov, Olena V. Vysotska, Andrii P. Porvan, Zbigniew Omiotek, Aron Burlibay, Azat Assembay, Małgorzata Szatkowska

Author Affiliations +

Proceedings Volume 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017; 104453K (2017) https://doi.org/10.1117/12.2280964
Event: Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2017, 2017, Wilga, Poland

Abstract

This study aims at mathematical modeling of systemic factors threatening the sanitary and hygienic state of sources of water supply. It is well-known, that this state affects health of population consuming water from different water sources (lakes, reservoirs, rivers). In particular, water quality problem may cause allergic reactions that are the important problem of health care. In the paper, the authors present the mathematical model, that enables on the basis of observations of a natural system to predict the system's behavior and determine the risks related to deterioration of drinking water resources. As a case study, we uses supply of drinking water from Lake Sevan, but the approach developed in the study can be applied to wide area of adjacent problems.

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Yurii G. Bespalov, Konstantin V. Nosov, Olena V. Vysotska, Andrii P. Porvan, Zbigniew Omiotek, Aron Burlibay, Azat Assembay, and Małgorzata Szatkowska "Mathematical modeling of systemic factors determining the risk of deterioration of drinking water supply and development of allergic diseases of population", Proc. SPIE 10445, Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2017, 104453K (7 August 2017); https://doi.org/10.1117/12.2280964

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KEYWORDS

Water

Mathematical modeling

Ecosystems

Neodymium

Data modeling

Binary data

Magnetism

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