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The paper concerns the study of the Rice statistical distribution’s peculiarities which cause the possibility of its efficient application in solving the tasks of high precision phase measuring in optics. The strict mathematical proof of the Rician distribution’s stable character is provided in the example of the differential signal consideration, namely: it has been proved that the sum or the difference of two Rician signals also obey the Rice distribution. Besides, the formulas have been obtained for the parameters of the resulting summand or differential signal’s Rice distribution. Based upon the proved stable character of the Rice distribution a new original technique of the high precision measuring of the two quasi-harmonic signals’ phase shift has been elaborated in the paper. This technique is grounded in the statistical analysis of the measured sampled data for the amplitudes of the both signals and for the amplitude of the third signal which is equal to the difference of the two signals to be compared in phase. The sought-for phase shift of two quasi-harmonic signals is being calculated from the geometrical considerations as an angle of a triangle which sides are equal to the three indicated signals’ amplitude values having been reconstructed against the noise background. Thereby, the proposed technique of measuring the phase shift using the differential signal analysis, is based upon the amplitude measurements only, what significantly decreases the demands to the equipment and simplifies the technique implementation in practice. The paper provides both the strict mathematical substantiation of a new phase shift measuring technique and the results of its numerical testing. The elaborated method of high precision phase measurements may be efficiently applied for solving a wide circle of tasks in various areas of science and technology, in particular — at distance measuring, in communication systems, in navigation, etc.

We present the iterative algorithm that solves numerically both Urysohn type Fredholm and Volterra nonlinear one-dimensional nonsingular integral equations of the second kind to a specified, modest user-defined accuracy. The algorithm is based on descending recursive sequence of quadratures. Convergence of numerical scheme is guaranteed by fixed-point theorems. Picard’s method of integrating successive approximations is of great importance for the existence theory of integral equations but surprisingly very little appears on numerical algorithms for its direct implementation in the literature. We show that successive approximations method can be readily employed in numerical solution of integral equations. By that the quadrature algorithm is thoroughly designed. It is based on the explicit form of fifth-order embedded Runge–Kutta rule with adaptive step-size self-control. Since local error estimates may be cheaply obtained, continuous monitoring of the quadrature makes it possible to create very accurate automatic numerical schemes and to reduce considerably the main drawback of Picard iterations namely the extremely large amount of computations with increasing recursion depth. Our algorithm is organized so that as compared to most approaches the nonlinearity of integral equations does not induce any additional computational difficulties, it is very simple to apply and to make a program realization. Our algorithm exhibits some features of universality. First, it should be stressed that the method is as easy to apply to nonlinear as to linear equations of both Fredholm and Volterra kind. Second, the algorithm is equipped by stopping rules by which the calculations may to considerable extent be controlled automatically. A compact C++-code of described algorithm is presented. Our program realization is self-consistent: it demands no preliminary calculations, no external libraries and no additional memory is needed. Numerical examples are provided to show applicability, efficiency, robustness and accuracy of our approach.

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.

The Industrial Internet of Things (IIoT) networks plays a significant role in enhancing industrial automation systems by connecting industrial devices for real time data monitoring and predictive maintenance. However, this connectivity introduces new vulnerabilities which demand the development of advanced intrusion detection systems. The nuclear facilities are considered one of the closest examples of critical infrastructures that suffer from high vulnerability through the connectivity of IIoT networks. This paper develops a robust intrusion detection approach using machine and ensemble learning algorithms specifically determined for IIoT networks. This approach can achieve optimal performance with low time complexity suitable for real-time IIoT networks. For each algorithm, Grid Search is determined to fine-tune the hyperparameters for optimizing the performance while ensuring time computational efficiency. The proposed approach is investigated on recent IIoT intrusion detection datasets, WUSTL-IIOT-2021 and Edge-IIoT-2022 to cover a wider range of attacks with high precision and minimum false alarms. The study provides the effectiveness of ten machine and ensemble learning models on selected features of the datasets. Synthetic Minority Over-sampling Technique (SMOTE)-based multi-class balancing is used to manipulate dataset imbalances. The ensemble voting classifier is used to combine the best models with the best hyperparameters for raising their advantages to improve the performance with the least time complexity. The machine and ensemble learning algorithms are evaluated based on accuracy, precision, recall, F1 Score, and time complexity. This evaluation can discriminate the most suitable candidates for further optimization. The proposed approach is called the XCL approach that is based on Extreme Gradient Boosting (XGBoost), CatBoost (Categorical Boosting), and Light Gradient- Boosting Machine (LightGBM). It achieves high accuracy, lower false positive rate, and efficient time complexity. The results refer to the importance of ensemble strategies, algorithm selection, and hyperparameter optimization in enhancing the performance to detect the different intrusions across the IIoT datasets over the other models. The developed approach produced a higher accuracy of 99.99% on the WUSTL-IIOT-2021 dataset and 100% on the Edge-IIoTset dataset. Our experimental evaluations have been extended to the CIC-IDS-2017 dataset. These additional evaluations not only highlight the applicability of the XCL approach on a wide spectrum of intrusion detection scenarios but also confirm its scalability and effectiveness in real-world complex network environments.

The present article sets out the scientific approach of Dmitry Sergeevich Chernavskii to the modelling of economic processes. It recounts the history of works of Dmitry Sergeyevich on the economic front, its milestones and achievements. One of the most important advances in the economic analysis was the prediction by a team of scientists headed by D. S. Chernavskii, the major crises that have occurred in our country over the last 20 years, namely, the default of 1998, the crisis of industrial production in the second half of the 2000s, the 2008 crisis and the ensuing recession. As an example, the dynamic analysis of the global macroeconomic processes shows the model of functioning of the dollar as the world currency. On this particular example shows the possibility of seigniorage due to the issue of the dollar and the calculated “window of opportunity” that allows you to issue dollars as the global currency, without prejudice to its own economy.

A model for the development of a closed society (without external economic relations) in the one-product approach is considered as an example of dynamic analysis of the economy of a separate state. The model is based on the principles of market economy, i.e. the dynamics of prices is determined by the balance of supply and demand. It is shown that in the general case, the state of market equilibrium is not unique. Several steady states with different levels of production and consumption are possible. Effect of addressed emission of money in underproductive state is considered. It is shown that, depending on its size it can lead to the transition to a highly productive condition, and just cause inflation without transition. The relationship of these results with the “Keynesian” and “monetarist” approaches is discussed.

The paper develops a new mathematical method of the joint signal and noise parameters determination at the Rice statistical distribution by method of moments based upon the analysis of data for the 1-st and the 3-rd raw moments of the random rician value. The explicit equations’ system have been obtained for required parameters of the signal and noise. In the limiting case of the small value of the signal-to-noise ratio the analytical formulas have been derived that allow calculating the required parameters without the necessity of solving the equations numerically. The technique having been elaborated in the paper ensures an efficient separation of the informative and noise components of the data to be analyzed without any a-priori restrictions, just based upon the processing of the results of the signal’s sampled measurements. The task is meaningful for the purposes of the rician data processing, in particular in the systems of magnetic-resonance visualization, in ultrasound visualization systems, at the optical signals’ analysis in range measuring systems, in radio location, etc. The results of the investigation have shown that the two parameter task solution of the proposed technique does not lead to the increase in demanded volume of computing resources compared with the one parameter task being solved in approximation that the second parameter of the task is known a-priori There are provided the results of the elaborated technique’s computer simulation. The results of the signal and noise parameters’ numerical calculation have confirmed the efficiency of the elaborated technique. There has been conducted the comparison of the accuracy of the sought-for parameters estimation by the technique having been developed in this paper and by the previously elaborated method of moments based upon processing the measured data for lower even moments of the signal to be analyzed.

The article presented the computational algorithm developed to study chemical processes in the internal flows of a multicomponent gas under the influence of laser radiation. The mathematical model is the gas dynamics’ equations with chemical reactions at low Mach numbers. It takes into account dissipative terms that describe the dynamics of a viscous heat-conducting medium with diffusion, chemical reactions and energy supply by laser radiation. This mathematical model is characterized by the presence of several very different time and spatial scales. The computational algorithm is based on a splitting scheme by physical processes. Each time integration step is divided into the following blocks: solving the equations of chemical kinetics, solving the equation for the radiation intensity, solving the convection-diffusion equations, calculating the dynamic component of pressure and calculating the correction of the velocity vector. The solution of a stiff system of chemical kinetics equations is carried out using a specialized explicit second-order accuracy scheme or a plug-in RADAU5 module. Numerical Rusanov flows and a WENO scheme of an increased order of approximation are used to find convective terms in the equations. The code based on the obtained algorithm has been developed using MPI parallel computing technology. The developed code is used to calculate the pyrolysis of ethane with radical reactions. The superequilibrium concentrations’ formation of radicals in the reactor volume is studied in detail. Numerical simulation of the reaction gas flow in a flat tube with laser radiation supply is carried out, which is in demand for the interpretation of experimental results. It is shown that laser radiation significantly increases the conversion of ethane and yields of target products at short lengths closer to the entrance to the reaction zone. Reducing the effective length of the reaction zone allows us to offer new solutions in the design of ethane conversion reactors into valuable hydrocarbons. The developed algorithm and program will find their application in the creation of new technologies of laser thermochemistry.

Authors describe a two-stage traffic assignment model. It contains of two blocks. The first block consists of a model for calculating a correspondence (demand) matrix, whereas the second block is a traffic assignment model. The first model calculates a matrix of correspondences using a matrix of transport costs (it characterizes the required volumes of movement from one area to another, it is time in this case). To solve this problem, authors propose to use one of the most popular methods of calculating the correspondence matrix in urban studies — the entropy model. The second model describes exactly how the needs for displacement specified by the correspondence matrix are distributed along the possible paths. Knowing the ways of the flows distribution along the paths, it is possible to calculate the cost matrix. Equilibrium in a two-stage model is a fixed point in the sequence of these two models. In practice the problem of finding a fixed point can be solved by the fixed-point iteration method. Unfortunately, at the moment the issue of convergence and estimations of the convergence rate for this method has not been studied quite thoroughly. In addition, the numerical implementation of the algorithm results in many problems. In particular, if the starting point is incorrect, situations may arise where the algorithm requires extremely large numbers to be computed and exceeds the available memory even on the most modern computers. Therefore the article proposes a method for reducing the problem of finding the equilibrium to the problem of the convex non-smooth optimization. Also a numerical method for solving the obtained optimization problem is proposed. Numerical experiments were carried out for both methods of solving the problem. The authors used data for Vladivostok (for this city information from various sources was processed and collected in a new dataset) and two smaller cities in the USA. It was not possible to achieve convergence by the method of fixed-point iteration, whereas the second model for the same dataset demonstrated convergence rate $k^{-1.67}$.

Carpooling has gained considerable importance as an effective solution for reducing pollution, mitigation of traffic and congestion on the roads, reduced demand for parking facilities, lesser energy and fuel consumption and most importantly, reduction in carbon emission, thus improving the quality of life in cities. This work presents a hybrid GA-A* algorithm to obtain optimal routes for the carpooling problem in the domain of multiobjective optimization having multiple conflicting objectives. Though the Genetic Algorithm provides optimal solutions, the A* algorithm because of its efficiency in providing the shortest route between any two points based on heuristics, enhances the optimal routes obtained using the Genetic algorithm. The refined routes obtained using the GA-A* algorithm, are further subjected to dominance test to obtain non-dominating solutions based on Pareto-Optimality. The routes obtained maximize the profit of the service provider by minimizing the travel and detour distance as well as pick-up/drop costs while maximizing the utilization of the car. The proposed algorithm has been implemented over the Salt Lake area of Kolkata. Route distance and detour distance for the optimal routes obtained using the proposed algorithm are consistently lesser for the same number of passengers when compared to the corresponding results obtained from an existing algorithm. Various statistical analysis like boxplots have also confirmed that the proposed algorithm regularly performed better than the existing algorithm using only Genetic Algorithm.