Abstract:The paper discusses the coefficient inverse problem for one-dimensional heat equation with inaccurate initial data. A conjugate difference problem is developed on difference level. The problem is solved by method of interval analysis. Condition of applicability of Thomas method and its computational convergence are obtained. Estimates of the interval width of solutions of difference problems and functions of Thomas method are also gained.
The nuclear decay of uranium is one of the cleanest ways to meet the growing energy demand. The uranium needed for power plants is mainly extracted by two methods in roughly equal amounts: quarries (underground and open pit) and in-situ leaching (ISL). The effective use of ISL requires, among other things, the correct determination of the filtration characteristics of the host rocks. In Kazakhstan, this calculation is still based on methods that were developed more than 50 years ago, and in some cases, give inaccurate results. At the same time, knowledge of filtration characteristics is necessary for the calculation of recoverable reserves, prediction of production dynamics, calculation of the optimum number of wells, etc. This paper describes a method for calculating the filtration coefficient of ore-bearing rocks using machine learning. The proposed method is based on nonlinear regression models. It also allows the estimation of the filtration properties of rocks within the process acidification zone, where the existing method is not applicable. The proposed method applies to approximately half of the uranium mined in the world and makes it possible to significantly (by 22 %-70%) increase the accuracy of the filtration coefficient determination and, accordingly, improve the accuracy of recoverable reserves calculation and economic indicators of mining processes.
The paper presents the results of a correlation analysis between the information trends in the electronic media of Kazakhstan and indicators of the epidemiological situation of COVID-19 according to the World Health Organization (WHO). The developed method is based on topic modeling and some other methods of processing natural language texts. The method allows for calculating the correlations between media topics, moods, the results of full-text search queries, and objective WHO data. The analysis of the results shows how the attitudes of society towards the problems of COVID-19 changed from 2021–2022. Firstly, the results reflect a steady trend of decreasing interest of electronic media in the topic of the pandemic, although to an unequal extent for different thematic groups. Secondly, there has been a tendency to shift the focus of attention to more pragmatic issues, such as remote learning problems, remote work, the impact of quarantine restrictions on the economy, etc.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.