ON THE ISSUE OF PLANNING SOWING AGRICULTURAL CROPS WITH THE MINIMUM RISK UNDER THE PRESENCE OF VARIOUS AGROCLIMATIC CONDITIONS

The present paper deals with one problem of quantitative controlling the seeding of the sown area by agricultural crops in different agroclimatic conditions. The considered problem is studied from the standpoint of three strategies: from the seeding planning perspective aiming at minimal risk associated with possible unfavourable agroclimatic conditions (a probabilistic approach is used); from the perspective of obtaining the maximum crops sales profit (a deterministic approach is used); from the perspective of obtaining the maximum crops harvest. For the considered problem, mathematical models are constructed (one probabilistic model and two deterministic models, respectively), their analytical solutions are found, and then, using a specific example, the application of the constructed and solved mathematical models is illustrated as well as the obtained numerical results are analysed.

Обзор рентгенодиагностических on-line сервисов, основанных на искусственных нейронных сетях в стоматологии

Aim. This review is devoted to the analysis of available on-line services and programs using artificial neural networks (ANNs) in dentistry, especially for cephalometric analysis.Materials and methods. We searched for scientific publications in the information and analytical databases PubMed, Google Scholar and eLibrary using combinations of the following keywords: artificial intelligence, deep learning, computer vision, neural network, dentistry, orthodontics, cephalometry, cephalometric analysis. 1612 articles were analyzed, of which 23 publications were included in our review.Results. Deep machine learning based on ANN has been successfully used in various branches of medicine as an analytical tool for processing various data. ANNs are especially successfully used for image recognition in radiology and histology. In dentistry, computer vision is used to diagnose diseases of the maxillofacial region, plan surgical treatment, including dental implantation, as well as for cephalometric analysis for the needs of orthodontists and maxillofacial surgeons.Conclusion. Currently, there are many programs and on-line services for cephalometric analysis. However, only 7 of them use ANNs for automatic landmarking and image analysis. Also, there is not enough data to evaluate the accuracy of their work and convenience.Цель исследования: анализ доступных on-line сервисов и программ, использующих искусственные нейронные сети (ИНС), в стоматологии, в особенности для цефалометрического анализа.Материал и методы. Проведен поиск научных публикаций в информационно-аналитических системах PubMed, Google Scholar и eLibrary без ограничения по срокам публикации по комбинациям из следующих ключевых слов: artificial intelligence, deep learning, computer vision, neural network, dentistry, orthodontics, cephalometry, cephalometric analysis. Были проанализированы 1612 статей, из которых 23 публикации использованы для составления обзора.Результаты. Глубокое машинное обучение на основе ИНС успешно применяется в различных разделах медицины в качестве аналитического инструмента для обработки различных данных. Особенно успешно ИНС применяются для распознавания изображений в рентгенологии и гистологии. В частности, в стоматологии компьютерное зрение используется для диагностики заболеваний челюстно-лицевой области, планирования оперативного лечения, в том числе имплантации, а также для цефалометрического анализа для нужд врачей-ортодонтов и челюстно-лицевых хирургов.Заключение. В настоящее время существует множество программ и on-line сервисов для цефалометрического анализа. Однако лишь 7 из них используют ИНС для автоматической разметки и анализа снимков. Также недостаточно данных для оценки точности их работы и удобства

MATHEMATICAL MODEL OF THE STEPPED-SECTION CAVITY FOR THE VIBRATION-AMPLITUDE OF THE DENSITY OF THE LIQUID

The design procedure of the tubular resonator for a vibrating and peak densitometer is developed

Mathematical model for determination of exhaust concentration dynamics in urban atmosphere under unknown turbulent air flow velocity

The paper proposes the 3-D nonlinear mathematical model for analytic determination of exhaust concentration dynamics in the city regions under the important stipulation that an airflow velocity is not a priory known. To determine an unknown airflow velocity the nonlinear mathematical model is proposed and this nonlinear model is solved by analytical method. In this model it is provided that the turbulent and molecular diffusion coefficient changes depending on the vertical remoteness above the ground surface. The proposed model can be used for solutions of operative problems on urban traffic organization, of long-term planning of urban agglomeration development and new highway building

Time-dependent problem for determination of exhaust concentration in urban transport system

The paper proposes the 3-D mathematical model for analytic determination of exhaust concentration dynamics in the city regions under a priori information on airflow velocity. In this model it is provided that the turbulent and molecular diffusion coefficient changes depending on the vertical remoteness above the ground surface. The numerical example of problem solving is presented. The created model can be used for solutions of operative problems on urban traffic organization, of long-term planning of urban agglomeration development and new highway building

Curvilinear integrals of discontinuous functions over nonrectifiable paths and Riemann boundary-value problem

© 2019 John Wiley & Sons, Ltd. We study a generalization of the concept of curvilinear integral for the case where path of integration is nonrectifiable, and integrand has discontinuities. Then we apply that integrals for solving of the Riemann boundary-value problem for domains with nonrectifiable boundaries and discontinuous boundary data. The research is supported by RFBR (grant 18-31-00060) and is performed according to a special programme of the Russian government supporting research at Kazan Federal University. Mathematical Methods in the Applied Sciences journal encourages authors to share the data and other artifacts supporting the results in the paper by archiving it in an appropriate public repository. Authors may provide a data availability statement, including a link to the repository they have used, in order that this statement can be published in their paper. Shared data should be cited