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The problem of restoration of an element f of Euclidean functional space  L²(X) based on the results of measurements of a finite set of its linear functionals, distorted by (random) error is solved. A priori data aren't assumed. Family of linear subspaces of the maximum (effective) dimension for which the projections of element f to them allow estimates with a given accuracy, is received. The effective rank ρ(δ) of the estimation problem is defined as the function equal to the maximum dimension of an orthogonal component Pf of the element f which can be estimated with a error, which is not surpassed the value δ. The example of restoration of a spectrum of radiation based on a finite set of experimental data is given.

We consider integration Clein–Gordon and Dirac equations in Bianchi IX cosmology model. Using the noncommutative integration method we found the new exact solutions for Taub universe.

Noncommutative integration method for Bianchi IX model is based on the use of the special infinite-dimensional holomorphic representation of the rotation group, which is based on the nondegenerate orbit adjoint representation, and complex polarization of degenerate covector. The matrix elements of the representation of form a complete and orthogonal set and allow you to use the generalized Fourier transform. Casimir operator for rotation group under this transformation becomes constant. And the symmetry operators generated by the Killing vector fields in the linear differential operators of the first order from one dependent variable. Thus, the relativistic wave equation on the rotation group allow non-commutative reduction to ordinary differential equations. In contrast to the well-known method of separation of variables, noncommutative integration method takes into account the non-Abelian algebra of symmetry operators and provides solutions that carry information about the non-commutative symmetry of the task. Such solutions can be useful for measuring the vacuum quantum effects and the calculation of the Green’s functions by the splitting-point method.

The work for the Taub model compared the solutions obtained with the known, which are obtained by separation of variables. It is shown that the non-commutative solutions are expressed in terms of elementary functions, while the known solutions are defined by the Wigner function. And commutative reduced by the Klein–Gordon equation for Taub model coincides with the equation, reduced by separation of variables. A commutative reduced by the Dirac equation is equivalent to the reduced equation obtained by separation of variables.

The study of the physiological and pathophysiological processes in the cardiovascular system is one of the important contemporary issues, which is addressed in many works. In this work, several approaches to the mathematical modelling of the blood flow are considered. They are based on the spatial order reduction and/or use a steady-state approach. Attention is paid to the discussion of the assumptions and suggestions, which are limiting the scope of such models. Some typical mathematical formulations are considered together with the brief review of their numerical implementation. In the first part, we discuss the models, which are based on the full spatial order reduction and/or use a steady-state approach. One of the most popular approaches exploits the analogy between the flow of the viscous fluid in the elastic tubes and the current in the electrical circuit. Such models can be used as an individual tool. They also used for the formulation of the boundary conditions in the models using one dimensional (1D) and three dimensional (3D) spatial coordinates. The use of the dynamical compartment models allows describing haemodynamics over an extended period (by order of tens of cardiac cycles and more). Then, the steady-state models are considered. They may use either total spatial reduction or two dimensional (2D) spatial coordinates. This approach is used for simulation the blood flow in the region of microcirculation. In the second part, we discuss the models, which are based on the spatial order reduction to the 1D coordinate. The models of this type require relatively small computational power relative to the 3D models. Within the scope of this approach, it is also possible to include all large vessels of the organism. The 1D models allow simulation of the haemodynamic parameters in every vessel, which is included in the model network. The structure and the parameters of such a network can be set according to the literature data. It also exists methods of medical data segmentation. The 1D models may be derived from the 3D Navier – Stokes equations either by asymptotic analysis or by integrating them over a volume. The major assumptions are symmetric flow and constant shape of the velocity profile over a cross-section. These assumptions are somewhat restrictive and arguable. Some of the current works paying attention to the 1D model’s validation, to the comparing different 1D models and the comparing 1D models with clinical data. The obtained results reveal acceptable accuracy. It allows concluding, that the 1D approach can be used in medical applications. 1D models allow describing several dynamical processes, such as pulse wave propagation, Korotkov’s tones. Some physiological conditions may be included in the 1D models: gravity force, muscles contraction force, regulation and autoregulation.

Reduction of the fire hazard of polymeric materials is one of the important scientific and technical problems. Since complexity of experimental procedures associated with flame spread, establishing reacting flows theoretical basics turned out to be crucial field of modern fundamental science. In order to determine parameters of flame spread over solid combustible materials numerical modelling methods have to be improved. Large amount of physical and chemical processes taking place needed to be resolved not just separately one by one but in connection with each other in gas and solid phases.

Upward flame spread over vertical solid combustible material is followed by unsteady eddy structures of gas flow in the vicinity of flame zone caused by thermal instability and natural convection forces accelerating hot combustion products. At every moment different amount of heat energy is transferred from hot gas-phase flame to solid material because of eddy flow structures. Therefore, satisfactory heat flux and eddy flow modelling are important to estimate flame spread rate.

In the current study we evaluated parameters of numerical method for flame spread over solid combustible material problem taking into account coupled nature of complex interaction between gas phase, solid material and eddy flow resulted from natural convection. We studied aspects of different approximation schemes used in differential equations integration process over space and time, of fields relaxation during iterations procedure carried out inside time step, of different time step values.

Mathematical model formulated allows to simulate flame spread over solid combustible material. Fluid dynamics is modeled by Navier – Stokes system of equations, eddy flow is described by combined turbulent model RANS–LES (DDES), turbulent combustion is resolved by modified turbulent combustion model Eddy Break-Up taking into account kinetic effects, radiation transfer is modeled by spherical harmonics method of first order approximation (P1). The equations presented are solved in OpenFOAM software.

The simplest and most desirable method of traffic signal control is precalculated regulation, when the parameters of the traffic light object operation are calculated in advance and activated in accordance to a schedule. This work proposes a method of forming a signal plan that allows one to calculate the control programs and set the period of their activity. Preparation of initial data for the calculation includes the formation of a time series of daily traffic intensity with an interval of 15 minutes. When carrying out field studies, it is possible that part of the traffic intensity measurements is missing. To fill up the missing traffic intensity measurements, the spline interpolation method is used. The next step of the method is to calculate the daily set of signal plans. The work presents the interdependencies, which allow one to calculate the optimal durations of the control cycle and the permitting phase movement and to set the period of their activity. The present movement control systems have a limit on the number of control programs. To reduce the signal plans' number and to determine their activity period, the clusterization using the $k$-means method in the transport phase space is introduced In the new daily signal plan, the duration of the phases is determined by the coordinates of the received cluster centers, and the activity periods are set by the elements included in the cluster. Testing on a numerical illustration showed that, when the number of clusters is 10, the deviation of the optimal phase duration from the cluster centers does not exceed 2 seconds. To evaluate the effectiveness of the developed methodology, a real intersection with traffic light regulation was considered as an example. Based on field studies of traffic patterns and traffic demand, a microscopic model for the SUMO (Simulation of Urban Mobility) program was developed. The efficiency assessment is based on the transport losses estimated by the time spent on movement. Simulation modeling of the multiprogram control of traffic lights showed a 20% reduction in the delay time at the traffic light object in comparison with the single-program control. The proposed method allows automation of the process of calculating daily signal plans and setting the time of their activity.

This article explores a method of machine learning based on the theory of random functions. One of the main problems of this method is that decision rule of a model becomes more complicated as the number of training dataset examples increases. The decision rule of the model is the most probable realization of a random function and it's represented as a polynomial with the number of terms equal to the number of training examples. In this article we will show the quick way of the number of training dataset examples reduction and, accordingly, the complexity of the decision rule. Reducing the number of examples of training dataset is due to the search and removal of weak elements that have little effect on the final form of the decision function, and noise sampling elements. For each $(x_i,y_i)$-th element sample was introduced the concept of value, which is expressed by the deviation of the estimated value of the decision function of the model at the point $x_i$, built without the $i$-th element, from the true value $y_i$. Also we show the possibility of indirect using weak elements in the process of training model without increasing the number of terms in the decision function. At the experimental part of the article, we show how changed amount of data affects to the ability of the method of generalizing in the classification task.

The technique of simplification of mathematical model of a chemical reaction by reducing the number of steps of the reaction scheme, based on an analysis of sensitivity to changes in the objective function of the model parameters, is proposed. The reduced scheme of model reaction of formaldehyde oxidation is received. Functional characterizes the measure of proximity to the calculated values for the initial kinetic reaction scheme and the scheme resulting disturbance of its parameters. The advantage of this technique is the ability to analyze complex kinetic schemes and reduction of kinetic models to a size suitable for practical use. The results of computational experiments under different reaction conditions can be included in the functional and thus to receive the reduce scheme, which is consistent the detailed scheme for the desired range of conditions. Sensitivity analysis of the functional model allows to identify those parameters, which provide the largest (or smallest) the contribution to the result of the process simulation. The mathematical model can contain parameters, which change of values do not affect the qualitative and quantitative description of the process. The contribution of these parameters in the functional value won’t be of great importance. Thus it can be eliminated from consideration, which do not serve for modeling kinetic curves substances. The kinetic scheme of formaldehyde oxidation, the detailed mechanism which includes 25 stages and 15 substances, were investigated using this method. On the basis of the local and global sensitivity analysis, the most important stage of the process that affect the overall dynamics of the target concentrations of the reaction. The reduced scheme of model reaction of formaldehyde oxidation is received. This scheme also describes the behavior of the main substances, as detailed scheme, but has a much smaller number of reaction stages. The results of the comparative analysis of modeling of formaldehyde oxidation on detailed and reduced schemes are given. Computational aspects of the problems of chemical kinetics by Sobol’ global method an example of this reaction are specified. The comparison results are local, global and total sensitivity indices are given.

The different types of the reduced equations are known in the dynamics a heavy rigid body with a fixed point. Since the Euler−Poisson’s equations admit the three first integrals, then for the first approach the obtaining new forms of equations are usually based on these integrals. The system of six scalar equations can be transformed to a third-order system with them. However, in indicated approach the reduced system will have a feature as in the form of radical expressions a relatively the components of the angular velocity vector. This fact prevents the effective the effective application of numerical and asymptotic methods of solutions research. In the second approach the different types of variables in a problem are used: Euler’s angles, Hamilton’s variables and other variables. In this approach the Euler−Poisson’s equations are reduced to either the system of second-order differential equations, or the system for which the special methods are effective. In the article the method of finding the reduced system based on the introduction of an auxiliary variable is applied. This variable characterizes the mixed product of the angular momentum vector, the vector of vertical and the unit vector barycentric axis of the body. The system of four differential equations, two of which are linear differential equations was obtained. This system has no analog and does not contain the features that allows to apply to it the analytical and numerical methods. Received form of equations is applied for the analysis of a special class of solutions in the case when the center of mass of the body belongs to the barycentric axis. The variant in which the sum of the squares of the two components of the angular momentum vector with respect to not barycentric axes is constant. It is proved that this variant exists only in the Steklov’s solution. The obtained form of Euler−Poisson’s equations can be used to the investigation of the conditions of existence of other classes of solutions. Certain perspectives obtained equations consists a record of all solutions for which the center of mass is on barycentric axis in the variables of this article. It allows to carry out a classification solutions of Euler−Poisson’s equations depending on the order of invariant relations. Since the equations system specified in the article has no singularities, it can be considered in computer modeling using numerical methods.

Optical systems with two-dimensional feedback demonstrate wide possibilities for studying the nucleation and development processes of dissipative structures. Feedback allows to influence the dynamics of the optical system by controlling the transformation of spatial variables performed by prisms, lenses, dynamic holograms and other devices. A nonlinear interferometer with a mirror image of a field in two-dimensional feedback is one of the simplest optical systems in which is realized the nonlocal nature of light fields.

A mathematical model of optical systems with two-dimensional feedback is a nonlinear parabolic equation with rotation transformation of a spatial variable and periodicity conditions on a circle. Such problems are investigated: bifurcation of the traveling wave type stationary structures, how the form of the solution changes as the diffusion coefficient decreases, dynamics of the solution’s stability when the bifurcation parameter leaves the critical value. For the first time as a parameter bifurcation was taken of diffusion coefficient.

The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds allows to prove a theorem on the existence and form of the traveling wave type solution neighborhood of the bifurcation value. The first traveling wave born as a result of the Andronov –Hopf bifurcation in the transition of the bifurcation parameter through the сritical value. According to the central manifold theorem, the first traveling wave is born orbitally stable.

Since the above theorem gives the opportunity to explore solutions are born only in the vicinity of the critical values of the bifurcation parameter, the decision to study the dynamics of traveling waves of change during the withdrawal of the bifurcation parameter in the supercritical region, the formalism of the Galerkin method was used. In accordance with the method of the central manifold is made Galerkin’s approximation of the problem solution. As the bifurcation parameter decreases and its transition through the critical value, the zero solution of the problem loses stability in an oscillatory manner. As a result, a periodic solution of the traveling wave type branches off from the zero solution. This wave is born orbitally stable. With further reduction of the parameter and its passage through the next critical value from the zero solution, the second solution of the traveling wave type is produced as a result of the Andronov –Hopf bifurcation. This wave is born unstable with an instability index of two.

Numerical calculations have shown that the application of the Galerkin’s method leads to correct results. The results obtained are in good agreement with the results obtained by other authors and can be used to establish experiments on the study of phenomena in optical systems with feedback.

The article deals with the development of the noise-reduction algorithm based on anisotropic nonlinear data filtering of computed tomography (CT). Analysis of domestic and foreign literature has shown that the most effective algorithms for noise reduction of CT data use complex methods for analyzing and processing data, such as bilateral, adaptive, three-dimensional and other types of filtrations. However, a combination of such techniques is rarely used in practice due to long processing time per slice. In this regard, it was decided to develop an efficient and fast algorithm for noise-reduction based on simplified bilateral filtration method with three-dimensional data accumulation. The algorithm was developed on C ++11 programming language in Microsoft Visual Studio 2015. The main difference of the developed noise reduction algorithm is the use an improved mathematical model of CT noise, based on the distribution of Poisson and Gauss from the logarithmic value, developed earlier by our team. This allows a more accurate determination of the noise level and, thus, the threshold of data processing. As the result of the noise reduction algorithm, processed CT data with lower noise level were obtained. Visual evaluation of the data showed the increased information content of the processed data, compared to original data, the clarity of the mapping of homogeneous regions, and a significant reduction in noise in processing areas. Assessing the numerical results of the algorithm showed a decrease in the standard deviation (SD) level by more than 6 times in the processed areas, and high rates of the determination coefficient showed that the data were not distorted and changed only due to the removal of noise. Usage of newly developed context dynamic threshold made it possible to decrease SD level on every area of data. The main difference of the developed threshold is its simplicity and speed, achieved by preliminary estimation of the data array and derivation of the threshold values that are put in correspondence with each pixel of the CT. The principle of its work is based on threshold criteria, which fits well both into the developed noise reduction algorithm based on anisotropic nonlinear filtration, and another algorithm of noise-reduction. The algorithm successfully functions as part of the MultiVox workstation and is being prepared for implementation in a single radiological network of the city of Moscow.