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This article solves the problem of vehicles drivers intoxication functional statedetermining. Its solution is relevant in the transport security field during pre-trip medical examination. The problem solution is based on the papillomometry method application, which allows to evaluate the driver state by his pupillary reaction to illumination change. The problem is to determine the state of driver inebriation by the analysis of the papillogram parameters values — a time series characterizing the change in pupil dimensions upon exposure to a short-time light pulse. For the papillograms analysis it is proposed to use a neural network. A neural network model for determining the drivers intoxication functional state is developed. For its training, specially prepared data samples are used which are the values of the following parameters of pupillary reactions grouped into two classes of functional states of drivers: initial diameter, minimum diameter, half-constriction diameter, final diameter, narrowing amplitude, rate of constriction, expansion rate, latent reaction time, the contraction time, the expansion time, the half-contraction time, and the half-expansion time. An example of the initial data is given. Based on their analysis, a neural network model is constructed in the form of a single-layer perceptron consisting of twelve input neurons, twenty-five neurons of the hidden layer, and one output neuron. To increase the model adequacy using the method of ROC analysis, the optimal cut-off point for the classes of solutions at the output of the neural network is determined. A scheme for determining the drivers intoxication state is proposed, which includes the following steps: pupillary reaction video registration, papillogram construction, parameters values calculation, data analysis on the base of the neural network model, driver’s condition classification as “norm” or “rejection of the norm”, making decisions on the person being audited. A medical worker conducting driver examination is presented with a neural network assessment of his intoxication state. On the basis of this assessment, an opinion on the admission or removal of the driver from driving the vehicle is drawn. Thus, the neural network model solves the problem of increasing the efficiency of pre-trip medical examination by increasing the reliability of the decisions made.

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.

In the paper we construct the adjoint problem for the explicit and implicit parabolic quazi-linear grid boundary-value problems with one spatial variable; the coefficients of the problems depend on the solution at the same time and earlier times. Dependence on the history of the solution is via the state vector; its evolution is described by the differential equation. Many models of diffusion mass transport are reduced to such boundary-value problems. Having solutions to the direct and adjoint problems, one can obtain the exact value of the gradient of a functional in the space of parameters the problem also depends on. We present solving algorithms, including the parallel one.

In the paper we consider the inverse problem of evaluating kinetic parameters of the model of dehydriding of metal powder using experimental data. The «blind search» in the space of parameters revealed multiple physically reasonable solutions. The solutions were obtained using high–performance computational modeling based on BOINC–grid.

We study the motion and destruction of Chelyabinsk meteoroid using simple physical and mathematical models. We evaluate the parameters of the motion, taking into account the ablation and mechanical destruction of the meteoroid, and compare our results to the observation data.

In this paper, we consider the problem of restoring the correspondence matrix based on the observations of real correspondences in Moscow. Following the conventional approach [Gasnikov et al., 2013], the transport network is considered as a directed graph whose edges correspond to road sections and the graph vertices correspond to areas that the traffic participants leave or enter. The number of city residents is considered constant. The problem of restoring the correspondence matrix is to calculate all the correspondence from the $i$ area to the $j$ area.

To restore the matrix, we propose to use one of the most popular methods of calculating the correspondence matrix in urban studies — the entropy model. In our work, which is based on the work [Wilson, 1978], we describe the evolutionary justification of the entropy model and the main idea of the transition to solving the problem of entropy-linear programming (ELP) in calculating the correspondence matrix. To solve the ELP problem, it is proposed to pass to the dual problem. In this paper, we describe several numerical optimization methods for solving this problem: the Sinkhorn method and the Accelerated Sinkhorn method. We provide numerical experiments for the following variants of cost functions: a linear cost function and a superposition of the power and logarithmic cost functions. In these functions, the cost is a combination of average time and distance between areas, which depends on the parameters. The correspondence matrix is calculated for multiple sets of parameters and then we calculate the quality of the restored matrix relative to the known correspondence matrix.

We assume that the noise in the restored correspondence matrix is Gaussian, as a result, we use the standard deviation as a quality metric. The article provides an overview of gradient-free optimization methods for solving non-convex problems. Since the number of parameters of the cost function is small, we use the grid search method to find the optimal parameters of the cost function. Thus, the correspondence matrix calculated for each set of parameters and then the quality of the restored matrix is evaluated relative to the known correspondence matrix. Further, according to the minimum residual value for each cost function, we determine for which cost function and at what parameter values the restored matrix best describes real correspondence.

Modern methods of complex planning the execution of task packages in multistage systems are characterized by the presence of restrictions on the dimension of the problem being solved, the impossibility of guaranteed obtaining effective solutions for various values of its input parameters, as well as the impossibility of registration the conditions for the formation of sets from the result and the restriction on the interval duration of time of the system operating. The decomposition of the generalized function of the system into a set of hierarchically interconnected subfunctions is implemented to solve the problem of scheduling the execution of task packages with generating sets of results and the restriction on the interval duration of time for the functioning of the system. The use of decomposition made it possible to employ the hierarchical approach for planning the execution of task packages in multistage systems, which provides the determination of decisions by the composition of task groups at the first level of the hierarchy decisions by the composition of task packages groups executed during time intervals of limited duration at the second level and schedules for executing packages at the third level the hierarchy. In order to evaluate decisions on the composition of packages, the results of their execution, obtained during the specified time intervals, are distributed among the packages. The apparatus of the theory of hierarchical games is used to determine complex solutions. A model of a hierarchical game for making decisions by the compositions of packages, groups of packages and schedules of executing packages is built, which is a system of hierarchically interconnected criteria for optimizing decisions. The model registers the condition for the formation of sets from the results of the execution of task packages and restriction on duration of time intervals of its operating. The problem of determining the compositions of task packages and groups of task packages is NP-hard; therefore, its solution requires the use of approximate optimization methods. In order to optimize groups of task packages, the construction of a method for formulating initial solutions by their compositions has been implemented, which are further optimized. Moreover, a algorithm for distributing the results of executing task packages obtained during time intervals of limited duration by sets is formulated. The method of local solutions optimization by composition of packages groups, in accordance with which packages are excluded from groups, the results of which are not included in sets, and packages, that aren’t included in any group, is proposed. The software implementation of the considered method of complex optimization of the compositions of task packages, groups of task packages, and schedules for executing task packages from groups (including the implementation of the method for optimizing the compositions of groups of task packages) has been performed. With its use, studies of the features of the considered planning task are carried out. Conclusion are formulated concerning the dependence of the efficiency of scheduling the execution of task packages in multistage system under the introduced conditions from the input parameters of the problem. The use of the method of local optimization of the compositions of groups of task packages allows to increase the number of formed sets from the results of task execution in packages from groups by 60% in comparison with fixed groups (which do not imply optimization).

In the paper the statistical relationships between the size and production characteristics of phytoplankton and zooplankton of the Vistula and Curonian lagoons, the Baltic Sea, were investigated. Research phytoplankton and zooplankton within the Russian part of the area of the Vistula and the Curonian lagoon was carried out on the monthly basis (from April to November) within the framework of long-term monitoring program on evaluating of ecological status of the lagoons. The size structure of plankton is the basis for understanding of the development of production processes, mechanisms of formation of the plankton species diversity and functioning of the lagoon ecosystems. As results of the work it was found that the maximum rate of photosynthesis and the integral value of the primary production with a change in cell volume of phytoplankton are changed according to a power law. The result shows that the smaller the size of algal cells in phytoplankton communities the more actively occur metabolism and the more effective they assimilate the solar energy. It is shown that the formation of plankton species diversity in ecosystems of lagoons is closely linked with the size structure of plankton communities and with features of development of the production processes. It is proposed the structure of a spatially homogenous mathematical model of the plankton food chain for the lagoon ecosystems taking into account the size spectrum and the characteristics of phytoplankton and zooplankton. The model parameters are the sizedependent indicators allometrically linked with average volumes of cells and organisms in different ranges of their sizes. In the model the algorithm for changes over time the coefficients of food preferences in the diet of zooplankton was proposed. Developed the size-dependent mathematical model of aquatic ecosystems allows to consider the impact of turbulent exchange on the size structure and temporal dynamics of the plankton food chain of the Vistula and Curonian lagoons. The model can be used to study the different regimes of dynamic behavior of plankton systems depending on the changes in the values of its parameters and external influences, as well as to quantify the redistribution of matter flows in ecosystems of the lagoons.

We present results of a study aimed at identification of a controlled object’s channels based on postprocessing of measurements with development of a model of a multiple-input controlled object and subsequent active modelling experiment. The controlled object model is developed using approximation of its behavior by a neural network model using trends obtained during a passive experiment in the mode of normal operation. Recurrent neural network containing feedback elements allows to simulate behavior of dynamic objects; input and feedback time delays allow to simulate behavior of inertial objects with pure delay. The model was taught using examples of the object’s operation with a control system and is presented by a dynamic neural network and a model of a regulator with a known regulation function. The neural network model simulates the system’s behavior and is used to conduct active computing experiments. Neural network model allows to obtain the controlled object’s response to an exploratory stimulus, including a periodic one. The obtained complex frequency response is used to evaluate parameters of the object’s transfer system using the least squares method. We present an example of identification of a channel of the simulated control system. The simulated object has two input ports and one output port and varying transport delays in transfer channels. One of the input ports serves as a controlling stimulus, the second is a controlled perturbation. The controlled output value changes as a result of control stimulus produced by the regulator operating according to the proportional-integral regulation law based on deviation of the controlled value from the task. The obtained parameters of the object’s channels’ transfer functions are close to the parameters of the input simulated object. The obtained normalized error of the reaction for a single step-wise stimulus of the control system model developed based on identification of the simulated control system doesn’t exceed 0.08. The considered objects pertain to the class of technological processes with continuous production. Such objects are characteristic of chemical, metallurgic, mine-mill, pulp and paper, and other industries.