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We suggested some approaches for solving image processing tasks in the decision support system (DSS) of the Center for Automated Recording of Administrative Offenses of the Road Traffic (CARAO). The main task of this system is to assist the operator in obtaining accurate information about the vehicle registration plate and the vehicle brand/model based on images obtained from the photo and video recording systems. We suggested the approach for vehicle registration plate recognition and brand/model classification on the images based on modern neural network models. LPRNet neural network model supplemented by Spatial Transformer Layer was used to recognize the vehicle registration plate. The ResNeXt-101-32x8d neural network model was used to classify for vehicle brand/model. We suggested the approach to construct the training set for the neural network of vehicle registration plate recognition. The approach is based on computer vision methods and machine learning algorithms. The SIFT algorithm was used to detect and describe local features on images with the vehicle registration plate. DBSCAN clustering was used to detect and delete outliers in such local features. The accuracy of vehicle registration plate recognition was 96% on the testing set. We suggested the approach to improve the efficiency of using the ResNeXt-101-32x8d model at additional training and classification stages. The approach is based on the new architecture of convolutional neural networks with “freezing” weight coefficients of convolutional layers, an additional convolutional layer for parallelizing the classification process, and a set of binary classifiers at the output. This approach significantly reduced the time of additional training of neural network when new vehicle brand/model classification was needed. The final accuracy of vehicle brand/model classification was 99% on the testing set. The proposed approaches were tested and implemented in the DSS of the CARAO of the Republic of Tatarstan.

The repressilator is the first genetic regulatory network in synthetic biology, which was artificially constructed in 2000. It is a closed network of three genetic elements $lacI$, $\lambda cI$ and $tetR$, which have a natural origin, but are not found in nature in such a combination. The promoter of each of the three genes controls the next cistron via the negative feedback, suppressing the expression of the neighboring gene. In our previous paper [Bratsun et al., 2018], we proposed a mathematical model of a delayed repressillator and studied its properties within the framework of a deterministic description. We assume that delay can be both natural, i.e. arises during the transcription / translation of genes due to the multistage nature of these processes, and artificial, i.e. specially to be introduced into the work of the regulatory network using gene engineering technologies. In this work, we apply the stochastic description of dynamic processes in a delayed repressilator, which is an important addition to deterministic analysis due to the small number of molecules involved in gene regulation. The stochastic study is carried out numerically using the Gillespie algorithm, which is modified for time delay systems. We present the description of the algorithm, its software implementation, and the results of benchmark simulations for a onegene delayed autorepressor. When studying the behavior of a repressilator, we show that a stochastic description in a number of cases gives new information about the behavior of a system, which does not reduce to deterministic dynamics even when averaged over a large number of realizations. We show that in the subcritical range of parameters, where deterministic analysis predicts the absolute stability of the system, quasi-regular oscillations may be excited due to the nonlinear interaction of noise and delay. Earlier, we have discovered within the framework of the deterministic description, that there exists a long-lived transient regime, which is represented in the phase space by a slow manifold. This mode reflects the process of long-term synchronization of protein pulsations in the work of the repressilator genes. In this work, we show that the transition to the cooperative mode of gene operation occurs a two order of magnitude faster, when the effect of the intrinsic noise is taken into account. We have obtained the probability distribution of moment when the phase trajectory leaves the slow manifold and have determined the most probable time for such a transition. The influence of the intrinsic noise of chemical reactions on the dynamic properties of the repressilator is discussed.

There are conditions of uneven combustion for tubular powder elements of large elongation used in artillery propelling charges. Here it is necessary to consider in parallel the processes of combustion and movement of powder gases inside and outside the channels of the powder tubes. Without this, it is impossible to adequately formulate and solve the problems of ignition, erosive combustion and stress-strain state of tubular powder elements in the shot process. The paper presents a physical and mathematical formulation of the main problem of the internal ballistics of an artillery shot for a charge consisting of a set of powder tubes. Combustion and movement of a bundle of powder tubes along the barrel channel is modeled by an equivalent tubular charge of all-round combustion. The end and cross-sectional areas of the channel of such a charge (equivalent tube) are equal to the sum of the areas of the ends and cross-sections of the channels of the powder tubes, respectively. The combustion surface of the channel is equal to the sum of the inner surfaces of the tubes in the bundle. The outer combustion surface of the equivalent tube is equal to the sum of the outer surfaces of the tubes in the bundle. It is assumed that the equivalent tube moves along the axis of the bore. The speed of motion of an equivalent tubular charge and its current position are determined from Newton’s second law. To calculate the flow parameters, we used two-dimensional axisymmetric equations of gas dynamics, for the solution of which an axisymmetric orthogonalized difference mesh is constructed, which adapts to the flow conditions. When the tube moves and burns, the difference grid is rearranged taking into account the changing regions of integration. The control volume method is used for the numerical solution of the system of gas-dynamic equations. The gas parameters at the boundaries of the control volumes are determined using a self-similar solution to the Godunov problem of decay for an arbitrary discontinuity. The developed technique was used to calculate the internal ballistics parameters of an artillery shot. This approach is considered for the first time and allows a new approach to the design of tubular artillery charges, since it allows obtaining the necessary information in the form of fields of velocity and pressure of powder gases for calculating the process of gradual ignition, unsteady erosive combustion, stress-strain state and strength of powder elements during the shot. The time dependences of the parameters of the internal ballistics process and the distribution of the main parameters of the flow of combustion products at different times are presented.

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.

Technical carbon (soot) is a product obtained by thermal decomposition (pyrolysis) of hydrocarbons (usually oil) in a stream of heat carrier gas. Technical carbon is widely used as a reinforcing component in the production of rubber and plastic masses. Tire production uses 70% of all carbon produced. In furnace carbon production, the liquid hydrocarbon feedstock is injected into the natural gas combustion product stream through nozzles. The raw material is atomized and vaporized with further pyrolysis. It is important for the raw material to be completely evaporated before the pyrolysis process starts, otherwise coke, that contaminates the product, will be produced. It is impossible to operate without mathematical modeling of the process itself in order to improve the carbon production technology, in particular, to provide the complete evaporation of the raw material prior to the pyrolysis process. Mathematical modelling is the most important way to obtain the most complete and detailed information about the peculiarities of reactor operation.

A three-dimensional mathematical model and calculation method for raw material atomization and evaporation in the thermal gas flow are being developed in the FlowVision software package PC. Water is selected as a raw material to work out the modeling technique. The working substances in the reactor chamber are the combustion products of natural gas. The motion of raw material droplets and evaporation in the gas stream are modeled in the framework of the Eulerian approach of interaction between dispersed and continuous media. The simulation results of raw materials atomization and evaporation in a real reactor for technical carbon production are presented. Numerical method allows to determine an important atomization characteristic: average Sauter diameter. That parameter could be defined from distribution of droplets of raw material at each time of spray forming.

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.

Cloud technologies are already wide spread among IT industry and start to gain popularity in academic field. There are several fundamental cloud models: infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). The article describes the cloud infrastructure deployed at the Laboratory of Information Technologies of the Joint Institute for Nuclear Research (LIT JINR). It explains the goals of the cloud infrastructure creation, specifics of the implementation, its utilization, current work and plans for development.

The paper has a goal to identify a set of parameters of the environment and infrastructure with the most significant impact on institutional-matrices that dominate in different countries. Parameters of environmental conditions includes raw statistical indices, which were directly derived from the databases of open access, as well as complex integral indicators that were by method of principal components. Efficiency of discussed parameters in task of dominant institutional matrices type recognition (X or Y type) was evaluated by a number of methods based on machine learning. It was revealed that greatest informational content is associated with parameters characterizing risk of natural disasters, level of urbanization and the development of transport infrastructure, the monthly averages and seasonal variations of temperature and precipitation.

The biohydrochemical portrait of the White Sea is constructed on the CNPSi-model calculations based on long-term mean annual observations (average monthly hydrometeorological, hydrochemical and hydrobiological parameters of the marine environment) as well as on updated information on the nutrient input to the sea with the runoff of the main river tributaries (Niva, Onega, Northern Dvina, Mezen, Kem, Keret). Parameters of the marine environment are temperature, light, transparency, and biogenic load. Ecological characteristics of the sea “portrait” were calculated for nine marine areas (Kandalaksha, Onega, Dvinsky, Mezensky Bays, Solovetsky Islands, Basin, Gorlot, Voronka, Chupa Bay), these are: the concentration changes of organic and mineral compounds of biogenic elements (C, N, P, Si), the biomass of organisms of the lower trophic level (heterotrophic bacteria, diatomic phytoplankton, herbivorous and predatory zooplankton) and other ones (rates of substance concentration and organism biomass changes, internal and external substance flows, balances of individual substances and nutrients as a whole). Parameters of the marine environment state (water temperature, ratio of mineral fractions N < P) and dominant diatom phytoplankton in the sea (abundance, production, biomass, chlorophyll content a) were calculated and compared with the results of individual surveys (for 1972–1991 and 2007–2012) of the White Sea water areas. The methods for estimating the values of these parameters from observations and calculations differ, however, the calculated values of the phytoplankton state are comparable with the measurements and are similar to the data given in the literature. Therefore, according to the literature data, the annual production of diatoms in the White Sea is estimated at 1.5–3 million tons C (at a vegetation period of 180 days), and according to calculations it is ~2 and 3.5 million tons C for vegetation period of 150 and 180 days respectively.

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.