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The paper is devoted to the secondary use of spectrum in telecommunication networks. It is emphasized that one of the solutions to this problem is the use of cognitive radio technologies and dynamic spectrum access for the successful functioning of which a large amount of information is required, including the parameters of base stations and network subscribers. Storage and processing of information should be carried out using a radio environment map, which is a spatio-temporal database of all activity in the network and allows you to determine the frequencies available for use at a given time. The paper presents a two-level model for forming a map of the radio environment of a cellular communication system LTE, in which the local and global levels are highlighted, which is described by the following parameters: a set of frequencies, signal attenuation, signal propagation map, grid step, current time count. The key objects of the model are the base station and the subscriber unit. The main parameters of the base station include: name, identifier, cell coordinates, range number, radiation power, numbers of connected subscriber devices, dedicated resource blocks. For subscriber devices, the following parameters are used: name, identifier, location, current coordinates of the device cell, base station identifier, frequency range, numbers of resource blocks for communication with the station, radiation power, data transmission status, list of numbers of the nearest stations, schedules movement and communication sessions of devices. An algorithm for the implementation of the model is presented, taking into account the scenarios of movement and communication sessions of subscriber devices. A method for calculating a map of the radio environment at a point on a coordinate grid, taking into account losses during the propagation of radio signals from emitting devices, is presented. The software implementation of the model is performed using the MatLab package. The approaches are described that allow to increase the speed of its work. In the simulation, the choice of parameters was carried out taking into account the data of the existing communication systems and the economy of computing resources. The experimental results of the algorithm for the formation of a radio environment map are demonstrated, confirming the correctness of the developed model.

In this paper, we consider two variants of the concept of sharp minimum for mathematical programming problems with quasiconvex objective function and inequality constraints. It investigated the problem of describing a variant of a simple subgradient method with switching along productive and non-productive steps, for which, on a class of problems with Lipschitz functions, it would be possible to guarantee convergence with the rate of geometric progression to the set of exact solutions or its vicinity. It is important that to implement the proposed method there is no need to know the sharp minimum parameter, which is usually difficult to estimate in practice. To overcome this problem, the authors propose to use a step adjustment procedure similar to that previously proposed by B. T. Polyak. However, in this case, in comparison with the class of problems without constraints, it arises the problem of knowing the exact minimal value of the objective function. The paper describes the conditions for the inexactness of this information, which make it possible to preserve convergence with the rate of geometric progression in the vicinity of the set of minimum points of the problem. Two analogs of the concept of a sharp minimum for problems with inequality constraints are considered. In the first one, the problem of approximation to the exact solution arises only to a pre-selected level of accuracy, for this, it is considered the case when the minimal value of the objective function is unknown; instead, it is given some approximation of this value. We describe conditions on the inexact minimal value of the objective function, under which convergence to the vicinity of the desired set of points with a rate of geometric progression is still preserved. The second considered variant of the sharp minimum does not depend on the desired accuracy of the problem. For this, we propose a slightly different way of checking whether the step is productive, which allows us to guarantee the convergence of the method to the exact solution with the rate of geometric progression in the case of exact information. Convergence estimates are proved under conditions of weak convexity of the constraints and some restrictions on the choice of the initial point, and a corollary is formulated for the convex case when the need for an additional assumption on the choice of the initial point disappears. For both approaches, it has been proven that the distance from the current point to the set of solutions decreases with increasing number of iterations. This, in particular, makes it possible to limit the requirements for the properties of the used functions (Lipschitz-continuous, sharp minimum) only for a bounded set. Some computational experiments are performed, including for the truss topology design problem.

In this paper, we consider predator – prey models and carry out a global bifurcation analysis of the Leslie –Gower system with an additive Allee effect and a simplified Holling type III functional response, which models the dynamics of predator and prey populations in a given ecological or biomedical system. This system uses the most common mathematical form of expressing the Allee effect (or law) through the prey growth function. Allee’s law states that there is a very specific relationship between individual fitness to living conditions and the number or density of individuals of a given species, namely: with an increase in the population size, the ability to survive and reproductive ability also increases. After algebraic transformations, the rational Leslie –Gower system with additive Allee effect and simplified Holling type III functional response can be written as a quantic-sextic dynamical system, i. e., as a system with polynomials of the fifth and sixth degrees. Using information about its singular points and applying our bifurcation-geometric approach to qualitative analysis, we study global bifurcations of limit cycles of the quintic-sextic system. To control all limit cycle bifurcations, especially bifurcations of multiple limit cycles, it is necessary to know the properties and combine the actions of all parameters rotating the vector field of the system. This can be done using the Wintner – Perko termination principle, according to which a maximal one-parameter family of multiple limit cycles terminates either at a singular point, which typically has the same multiplicity (cyclicity), or at a separatrix cycle, which also typically has the same multiplicity (cyclicity). This principle is a consequence of the principle of natural termination which was stated for higher-dimensional dynamical systems by Wintner who studied one-parameter families of periodic orbits of the restricted three-body problem and proved that in the analytic case any oneparameter family of periodic orbits can be uniquely continued through any bifurcation except a period-doubling bifurcation. Applying the planar Wintner – Perko principle, we prove that if the cyclicity of the focus in the system under consideration is three, then the system can have at most three limit cycles surrounding one singular point.

The work presents an experimental study of the tree structure that occurs during a medical examination. At each meeting with a medical specialist, the patient receives a certain number of areas for consulting other specialists or for tests. A tree of directions arises, each branch of which the patient should pass. Depending on the branching of the tree, it can be as final — and in this case the examination can be completed — and endless when the patient’s goal cannot be achieved. In the work both experimentally and theoretically studied the critical properties of the transition of the system from the forest of the final trees to the forest endless, depending on the probabilistic characteristics of the tree.

For the description, a model is proposed in which a discrete function of the probability of the number of branches on the node repeats the dynamics of a continuous gaussian distribution. The characteristics of the distribution of the Gauss (mathematical expectation of $x_0$, the average quadratic deviation of $\sigma$) are model parameters. In the selected setting, the task refers to the problems of branching random processes (BRP) in the heterogeneous model of Galton – Watson.

Experimental study is carried out by numerical modeling on the final grilles. A phase diagram was built, the boundaries of areas of various phases are determined. A comparison was made with the phase diagram obtained from theoretical criteria for macrosystems, and an adequate correspondence was established. It is shown that on the final grilles the transition is blurry.

The description of the blurry phase transition was carried out using two approaches. In the first, standard approach, the transition is described using the so-called inclusion function, which makes the meaning of the share of one of the phases in the general set. It was established that such an approach in this system is ineffective, since the found position of the conditional boundary of the blurred transition is determined only by the size of the chosen experimental lattice and does not bear objective meaning.

The second, original approach is proposed, based on the introduction of an parameter of order equal to the reverse average tree height, and the analysis of its behavior. It was established that the dynamics of such an order parameter in the $\sigma = \text{const}$ section with very small differences has the type of distribution of Fermi – Dirac ($\sigma$ performs the same function as the temperature for the distribution of Fermi – Dirac, $x_0$ — energy function). An empirical expression has been selected for the order parameter, an analogue of the chemical potential is introduced and calculated, which makes sense of the characteristic scale of the order parameter — that is, the values of $x_0$, in which the order can be considered a disorder. This criterion is the basis for determining the boundary of the conditional transition in this approach. It was established that this boundary corresponds to the average height of a tree equal to two generations. Based on the found properties, recommendations for medical institutions are proposed to control the provision of limb of the path of patients.

The model discussed and its description using conditionally-infinite trees have applications to many hierarchical systems. These systems include: internet routing networks, bureaucratic networks, trade and logistics networks, citation networks, game strategies, population dynamics problems, and others.

The article presents a technology for building clinical decision support systems (CDSS) based on service containers using Docker and a web interface that runs directly in the browser without installing specialized software on workstation of a clinician. A modular architecture is proposed in which each application module is packaged as an independent service container combining a lightweight web server, a user interface, and computational components for medical image processing. Communication between the browser and the server side is implemented via a persistent bidirectional WebSocket connection with binary message serialization (MessagePack), which provides low latency and efficient transfer of large data. For local storage of images and analysis of results, browser facilities (IndexedDB with the Dexie.js wrapper) are used to speed up repeated data access. Three-dimensional visualization and basic operations with DICOM data are implemented with Three.js and AMI.js: this toolchain supports the integration of interactive elements arising from the task context (annotations, landmarks, markers, 3D models) into volumetric medical images.

Server components and functional modules are assembled as a set of interacting containers managed by Docker. The paper discusses the choice of base images, approaches to minimizing containers down to runtime-only executables without external utilities, and the organization of multi-stage builds with a dedicated build container. It describes a hub service that launches application containers on user request, performs request proxying, manages sessions, and switches a container from shared to exclusive mode at the start of computations. Examples of application modules are provided (fractional flow reserve estimation, quantitative flow ratio computation, aortic valve closure modeling), along with the integration of a React-based interface with a three-dimensional scene, a versioning policy, automated reproducibility checks, and the deployment procedure on the target platform.

It is demonstrated that containerization ensures portability and reproducibility of the software environment, dependency isolation and scalability, while the browser-based interface provides accessibility, reduced infrastructure requirements, and interactive real-time visualization of medical data. Technical limitations are noted (dependence on versions of visualization libraries and data formats) together with practical mitigation measures.

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.

The proteins of the Major Histocompatibility Complex (MHC) play a key role in the functioning of the adaptive immune system, and the identification of peptides that bind to them is an important step in the development of vaccines and understanding the mechanisms of autoimmune diseases. Today, there are a number of methods for predicting the binding of a particular MHC allele to a peptide. One of the best such methods is NetMHCpan-4.0, which is based on an ensemble of artificial neural networks. This paper presents a methodology for qualitatively improving the underlying neural network underlying NetMHCpan-4.0. The proposed method uses the ensemble construction technique and adds as input an estimate of the Potts model taken from static mechanics, which is a generalization of the Ising model. In the general case, the model reflects the interaction of spins in the crystal lattice. Within the framework of the proposed method, the model is used to better represent the physical nature of the interaction of proteins included in the complex. To assess the interaction of the MHC + peptide complex, we use a two-dimensional Potts model with 20 states (corresponding to basic amino acids). Solving the inverse problem using data on experimentally confirmed interacting pairs, we obtain the values of the parameters of the Potts model, which we then use to evaluate a new pair of MHC + peptide, and supplement this value with the input data of the neural network. This approach, combined with the ensemble construction technique, allows for improved prediction accuracy, in terms of the positive predictive value (PPV) metric, compared to the baseline model.

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.

This paper demonstrates the advantages of using artificial intelligence algorithms for the design of experiment theory, which makes possible to improve the accuracy of parameter identification for an elastostatic robot model. Design of experiment for a robot consists of the optimal configuration-external force pairs for the identification algorithms and can be described by several main stages. At the first stage, an elastostatic model of the robot is created, taking into account all possible mechanical compliances. The second stage selects the objective function, which can be represented by both classical optimality criteria and criteria defined by the desired application of the robot. At the third stage the optimal measurement configurations are found using numerical optimization. The fourth stage measures the position of the robot body in the obtained configurations under the influence of an external force. At the last, fifth stage, the elastostatic parameters of the manipulator are identified based on the measured data.

The objective function required to finding the optimal configurations for industrial robot calibration is constrained by mechanical limits both on the part of the possible angles of rotation of the robot’s joints and on the part of the possible applied forces. The solution of this multidimensional and constrained problem is not simple, therefore it is proposed to use approaches based on artificial intelligence. To find the minimum of the objective function, the following methods, also sometimes called heuristics, were used: genetic algorithms, particle swarm optimization, simulated annealing algorithm, etc. The obtained results were analyzed in terms of the time required to obtain the configurations, the optimal value, as well as the final accuracy after applying the calibration. The comparison showed the advantages of the considered optimization techniques based on artificial intelligence over the classical methods of finding the optimal value. The results of this work allow us to reduce the time spent on calibration and increase the positioning accuracy of the robot’s end-effector after calibration for contact operations with high loads, such as machining and incremental forming.

When modeling turbulent flows in practical applications, it is often necessary to carry out a series of calculations of bodies of similar topology. For example, bodies that differ in the shape of the fairing. The use of convolutional neural networks allows to reduce the number of calculations in a series, restoring some of them based on calculations already performed. The paper proposes a method that allows to apply a convolutional neural network regardless of the method of constructing a computational mesh. To do this, the flow field is reinterpolated to a uniform mesh along with the body itself. The geometry of the body is set using the signed distance function and masking. The restoration of the flow field based on part of the calculations for similar geometries is carried out using a neural network of the UNet type with a spatial attention mechanism. The resolution of the nearwall region, which is a critical condition for turbulent modeling, is based on the equations obtained in the nearwall domain decomposition method.

A demonstration of the method is given for the case of a flow around a rounded plate by a turbulent air flow with different rounding at fixed parameters of the incoming flow with the Reynolds number $Re = 10^5$ and the Mach number $M = 0.15$. Since flows with such parameters of the incoming flow can be considered incompressible, only the velocity components are studied directly. The flow fields, velocity and friction profiles obtained by the surrogate model and numerically are compared. The analysis is carried out both on the plate and on the rounding. The simulation results confirm the prospects of the proposed approach. In particular, it was shown that even if the model is used at the maximum permissible limits of its applicability, friction can be obtained with an accuracy of up to 90%. The work also analyzes the constructed architecture of the neural network. The obtained surrogate model is compared with alternative models based on a variational autoencoder or the principal component analysis using radial basis functions. Based on this comparison, the advantages of the proposed method are demonstrated.