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In the conditions of the development of modern economy, human capital is one of the main factors of economic growth. The formation of human capital begins with the birth of a person and continues throughout life, so the value of human capital is inseparable from its carriers, which in turn makes it difficult to account for this factor. This has led to the fact that currently there are no generally accepted methods of calculating the value of human capital. There are only a few approaches to the measurement of human capital: the cost approach (by income or investment) and the index approach, of which the most well-known approach developed under the auspices of the UN.

This paper presents the assigned task in conjunction with the task of demographic dynamics solved in the time-age plane, which allows to more fully take into account the temporary changes in the demographic structure on the dynamics of human capital.

The task of demographic dynamics is posed within the framework of the Mac-Kendrick – von Foerster model on the basis of the equation of age structure dynamics. The form of distribution functions for births, deaths and migration of the population is determined on the basis of the available statistical information. The numerical solution of the problem is given. The analysis and forecast of demographic indicators are presented. The economic and mathematical model of human capital dynamics is formulated on the basis of the demographic dynamics problem. The problem of modeling the human capital dynamics considers three components of capital: educational, health and cultural (spiritual). Description of the evolution of human capital components uses an equation of the transfer equation type. Investments in human capital components are determined on the basis of budget expenditures and private expenditures, taking into account the characteristic time life cycle of demographic elements. A one-dimensional kinetic equation is used to predict the dynamics of the total human capital. The method of calculating the dynamics of this factor is given as a time function. The calculated data on the human capital dynamics are presented for the Russian Federation. As studies have shown, the value of human capital increased rapidly until 2008, in the future there was a period of stabilization, but after 2014 there is a negative dynamics of this value.

Automatic recognition of personal identity by biometric features is based on unique peculiarities or characteristics of people. Biometric identification process consist in making of reference templates and comparison with new input data. Iris pattern recognition algorithms presents high accuracy and low identification errors percent on practice. Iris pattern advantages over other biometric features are determined by its high degree of freedom (nearly 249), excessive density of unique features and constancy. High recognition reliability level is very important because it provides search in big databases. Unlike one-to-one check mode that is applicable only to small calculation count it allows to work in one-to-many identification mode. Every biometric identification system appears to be probabilistic and qualitative characteristics description utilizes such parameters as: recognition accuracy, false acceptance rate and false rejection rate. These characteristics allows to compare identity recognition methods and asses the system performance under any circumstances. This article explains the mathematical model of iris pattern biometric identification and its characteristics. Besides, there are analyzed results of comparison of model and real recognition process. To make such analysis there was carried out the review of existing iris pattern recognition methods based on different unique features vector. The Python-based software package is described below. It builds-up probabilistic distributions and generates large test data sets. Such data sets can be also used to educate the identification decision making neural network. Furthermore, synergy algorithm of several iris pattern identification methods was suggested to increase qualitative characteristics of system in comparison with the use of each method separately.

Magnetic systems, in which due to competition between the direct Heisenberg exchange and the Dzyaloshinskii –Moriya interaction, magnetic vortex structures — skyrmions appear, were studied using the Metropolis algorithm.

The conditions for the nucleation and stable existence of magnetic skyrmions in two-dimensional magnetic films in the frame of the classical Heisenberg model were considered in the article. A thermal stability of skyrmions in a magnetic film was studied. The processes of the formation of various states in the system at different values of external magnetic fields were considered, various phases into which the Heisenberg spin system passes were recognized. The authors identified seven phases: paramagnetic, spiral, labyrinth, spiralskyrmion, skyrmion, skyrmion-ferromagnetic and ferromagnetic phases, a detailed analysis of the configurations is given in the article.

Two phase diagrams were plotted: the first diagram shows the behavior of the system at a constant $D$ depending on the values of the external magnetic field and temperature $(T, B)$, the second one shows the change of the system configurations at a constant temperature $T$ depending on the magnitude of the Dzyaloshinskii – Moriya interaction and external magnetic field: $(D, B)$.

The data from these numerical experiments will be used in further studies to determine the model parameters of the system for the formation of a stable skyrmion state and to develop methods for controlling skyrmions in a magnetic film.

This article solves the problem of developing a technology for collecting initial data for building models for assessing the functional state of a person. This condition is assessed by the pupil response of a person to a change in illumination based on the pupillometry method. This method involves the collection and analysis of initial data (pupillograms), presented in the form of time series characterizing the dynamics of changes in the human pupils to a light impulse effect. The drawbacks of the traditional approach to the collection of initial data using the methods of computer vision and smoothing of time series are analyzed. Attention is focused on the importance of the quality of the initial data for the construction of adequate mathematical models. The need for manual marking of the iris and pupil circles is updated to improve the accuracy and quality of the initial data. The stages of the proposed technology for collecting initial data are described. An example of the obtained pupillogram is given, which has a smooth shape and does not contain outliers, noise, anomalies and missing values. Based on the presented technology, a software and hardware complex has been developed, which is a collection of special software with two main modules, and hardware implemented on the basis of a Raspberry Pi 4 Model B microcomputer, with peripheral equipment that implements the specified functionality. To evaluate the effectiveness of the developed technology, models of a single-layer perspetron and a collective of neural networks are used, for the construction of which the initial data on the functional state of intoxication of a person were used. The studies have shown that the use of manual marking of the initial data (in comparison with automatic methods of computer vision) leads to a decrease in the number of errors of the 1st and 2nd years of the kind and, accordingly, to an increase in the accuracy of assessing the functional state of a person. Thus, the presented technology for collecting initial data can be effectively used to build adequate models for assessing the functional state of a person by pupillary response to changes in illumination. The use of such models is relevant in solving individual problems of ensuring transport security, in particular, monitoring the functional state of drivers.

Examining the spectral response of plants from data collected using remote sensing has a lot of potential for solving real-world problems in different fields of research. In this study, we have used the spectral property to identify the invasive plant Heracleum sosnowskyi Manden from satellite imagery. H. sosnowskyi is an invasive plant that causes many harms to humans, animals and the ecosystem at large. We have used data collected from the years 2018 to 2020 containing sample geolocation data from the Moscow Region where this plant exists and we have used Sentinel-2 imagery for the spectral analysis towards the aim of detecting it from the satellite imagery. We deployed a Random Forest (RF) machine learning model within the framework of Google Earth Engine (GEE). The algorithm learns from the collected data, which is made up of 12 bands of Sentinel-2, and also includes the digital elevation together with some spectral indices, which are used as features in the algorithm. The approach used is to learn the biophysical parameters of H. sosnowskyi from its reflectances by fitting the RF model directly from the data. Our results demonstrate how the combination of remote sensing and machine learning can assist in locating H. sosnowskyi, which aids in controlling its invasive expansion. Our approach provides a high detection accuracy of the plant, which is 96.93%.

The article is devoted to description the author's method of multidimensional analysis for generate an predictive assessment of organizations’ credit risk, based on the credit history information, which taking into account value and period of credit. An example of credit risk assessment is given.

Technical diagnosis’ current trends are connected to application of FEM computer simulation, which allows, to some extent, replace real experiments, reduce costs for investigation and minimize risks. Computer simulation, just at the stage of research and development, allows carrying out of diagnostics of equipment to detect permissible fluctuations of parameters of equipment’s work. Peculiarity of diagnosis of rolling equipment is that functioning of rolling equipment is directly tied with manufacturing of product with required quality, including accuracy. At that design of techniques of technical diagnosis and diagnostical modelling is very important. Computer simulation of cold rolling of strip was carried out. At that upper working roll was doing vibrations in horizontal direction according with published data of experiments on continuous 1700 rolling mill. Vibration of working roll in a stand appeared due to gap between roll’s craft and guide in a stand and led to periodical fluctuations of strip’s thickness. After computer simulation with the help of DEFORM software strip with longitudinal and transversal thickness variation was gotten. Visualization of strip’s geometrical parameters, according with simulation data, corresponded to type of inhomogeneity of surface of strip rolled in real. Further analysis of thickness variation was done in order to identify, on the basis of simulation, sources of periodical components of strip’s thickness, whose reasons are malfunctions of equipment. Advantage of computer simulation while searching the sources of forming of thickness variation is that different hypothesis concerning thickness formations may be tested without conducting real experiments and costs of different types may be reduced. Moreover, while simulation, initial strip’s thickness will not have fluctuations as opposed to industrial or laboratorial experiments. On the basis of spectral analysis of random process, it was established that frequency of changing of strip’s thickness after rolling in one stand coincides with frequency of working roll’s vibration. Results of computer simulation correlate with results of the researches for 1700 mill. Therefore, opportunity to apply computer simulation to find reasons of formation of thickness variation of strip on the industrial rolling mill is shown.

Transport of respiratory gases by respiratory and circulatory systems is one of the most important processes associated with living conditions of the human body. Significant and/or long-term deviations of oxygen and carbon dioxide concentrations from the normal values in blood can be a reason of significant pathological changes with irreversible consequences: lack of oxygen (hypoxia and ischemic events), the change in the acidbase balance of blood (acidosis or alkalosis), and others. In the context of a changing external environment and internal conditions of the body the action of its regulatory systems aimed at maintaining homeostasis. One of the major mechanisms for maintaining concentrations (partial pressures) of oxygen and carbon dioxide in the blood at a normal level is the regulation of minute ventilation, respiratory rate and depth of respiration, which is caused by the activity of the central and peripheral regulators.

In this paper we propose a mathematical model of the regulation of pulmonary ventilation parameter. The model is used to calculate the minute ventilation adaptation during hypoxia and hypercapnia. The model is developed using a single-component model of the lungs, and biochemical equilibrium conditions of oxygen and carbon dioxide in the blood and the alveolar lung volume. A comparison with laboratory data is performed during hypoxia and hypercapnia. Analysis of the results shows that the model reproduces the dynamics of minute ventilation during hypercapnia with sufficient accuracy. Another result is that more accurate model of regulation of minute ventilation during hypoxia should be developed. The factors preventing from satisfactory accuracy are analysed in the final section.

Respiratory function is one of the main limiting factors of the organism during intense physical activities. Thus, it is important characteristic of high performance sport and extreme physical activity conditions. Therefore, the results of this study have significant application value in the field of mathematical modeling in sport. The considered conditions of hypoxia and hypercapnia are partly reproduce training at high altitude and at hypoxia conditions. The purpose of these conditions is to increase the level of hemoglobin in the blood of highly qualified athletes. These conditions are the only admitted by sport committees.

The article deals with the process of creating an effective algorithm for determining the amount of emitted quanta from an X-ray tube in computer tomography (CT) studies. An analysis of domestic and foreign literature showed that most of the work in the field of radiometry and radiography takes the tabulated values of X-ray absorption coefficients into account, while individual dose factors are not taken into account at all since many studies are lacking the Dose Report. Instead, an average value is used to simplify the calculation of statistics. In this regard, it was decided to develop a method to detect the amount of ionizing quanta by analyzing the noise of CT data. As the basis of the algorithm, we used Poisson and Gauss distribution mathematical model of owns’ design of logarithmic value. The resulting mathematical model was tested on the CT data of a calibration phantom consisting of three plastic cylinders filled with water, the X-ray absorption coefficient of which is known from the table values. The data were obtained from several CT devices from different manufacturers (Siemens, Toshiba, GE, Phillips). The developed algorithm made it possible to calculate the number of emitted X-ray quanta per unit time. These data, taking into account the noise level and the radiuses of the cylinders, were converted to X-ray absorption values, after which a comparison was made with tabulated values. As a result of this operation, the algorithm used with CT data of various configurations, experimental data were obtained, consistent with the theoretical part and the mathematical model. The results showed good accuracy of the algorithm and mathematical apparatus, which shows reliability of the obtained data. This mathematical model is already used in the noise reduction program of the CT of own design, where it participates as a method of creating a dynamic threshold of noise reduction. At the moment, the algorithm is being processed to work with real data from computer tomography of patients.

A critical analysis of existing approaches, methods and models to solve the problem of financial resources operational management has been carried out in the article. A number of significant shortcomings of the presented models were identified, limiting the scope of their effective usage. There are a static nature of the models, probabilistic nature of financial flows are not taken into account, daily amounts of receivables and payables that significantly affect the solvency and liquidity of the company are not identified. This necessitates the development of a new model that reflects the essential properties of the planning financial flows system — stochasticity, dynamism, non-stationarity.

The model for the financial flows distribution has been developed. It bases on the principles of optimal dynamic control and provides financial resources planning ensuring an adequate level of liquidity and solvency of a company and concern initial data uncertainty. The algorithm for designing the objective cash balance, based on principles of a companies’ financial stability ensuring under changing financial constraints, is proposed.

Characteristic of the proposed model is the presentation of the cash distribution process in the form of a discrete dynamic process, for which a plan for financial resources allocation is determined, ensuring the extremum of an optimality criterion. Designing of such plan is based on the coordination of payments (cash expenses) with the cash receipts. This approach allows to synthesize different plans that differ in combinations of financial outflows, and then to select the best one according to a given criterion. The minimum total costs associated with the payment of fines for non-timely financing of expenses were taken as the optimality criterion. Restrictions in the model are the requirement to ensure the minimum allowable cash balances for the subperiods of the planning period, as well as the obligation to make payments during the planning period, taking into account the maturity of these payments. The suggested model with a high degree of efficiency allows to solve the problem of financial resources distribution under uncertainty over time and receipts, coordination of funds inflows and outflows. The practical significance of the research is in developed model application, allowing to improve the financial planning quality, to increase the management efficiency and operational efficiency of a company.