According to the findings of an analysis of the types and structures of digital filters with finite- and infinite-impulse responses and the principles of their operation, a method for establishing a universal and stable system for signal processing has been developed using a configurable complex function block of digital signal processing based on the programming logical integral schemes and various types of filters in order to develop a software and hardware devices suitable for a set of processing parameters.

The article presents findings of manual, semi-automatic, and automatic approaches to generate test questions based on such methods as annotation, keyword extraction, and learning datasets for compiling tests for studying material, along with a description of each method algorithm, examples of generated questions, and their quality assessment. These examples demonstrate the advantages of an algorithm for generating a method using a dataset and a combination of methods, as well as their possible practical application.

The study presents the results of amplitude and phase errors in the formation of radio-impulse signals based on the Frank codes influencing their correlation characteristics, which will be beneficial for the development and optimization of compound signals. The findings obtained can be applied to radar and communication systems.

The relevance of the study is demonstrated through the issues of rapid urban development and search for optimal approaches to settle the issues using an analysis and forecasting of various cases arising when implementing designs for urban development. A model is proposed to implement the agent-based approach and analyze the dynamic urban development patterns according to the individual properties of system objects and rules for their cooperation. The allowance for the basic model is described. Simulation experiments are conducted to investigate the dynamic urban properties and recommendations are proposed to upgrade them.

The article discusses the application of the transfer learning method for the ensemble of artificial convolutional neural networks with preliminary digital image segmentation for blood cells in order to classify them later. The results obtained during neural networks classification demonstrate the efficiency of such technologies used for improving the accuracy of artificial neural networks when solving the problems of medical images segmentation for leukocytes in order to diagnose hematologic diseases.

The article discusses a method for determining the wind velocity values at a desired point of the atmospheric boundary layer using a multirotor unmanned aerial vehicle. Wind velocity is calculated via a multicopter in hovering mode at a target point using current measurements of the thrust vector angle, the power consumed by each engine, and the angle of the frame orientation relative to the boresight. Wind vector measurement errors associated with different angles and windage of the body are compensated by rotating the unmanned aerial vehicle around the vertical axis with subsequent averaging of the accumulated data.

The article presents findings of the analysis of threats arising due to the spread of information, which can have a negative impact on a person’s psychological condition. Modern mechanisms for detection and blocking of malicious information are considered; a mathematical apparatus for assessing the quality of information detection is established; and a functional model of informational and technological processes for the examination of an information source for malicious information is designed.

The article presents an examination of the movement trajectory of a single liquid drop of sludge containing water, oil, and iron scale in a swirling high-temperature gas flow. Taking into account a two-phase transition area from liquid water to vapor, temperature fields in a drop are determined, as is an algorithm for calculating the movement trajectory of a drop in a swirling gas flow when heating it up according to a two-phase area of water evaporation. When designing a drying chamber for drops of scale- and oil-containing sludge, a mathematical model helps predict its typical size as well as control the drying process for drops produced by a disk atomizer.

In the setting of ambiguous weather forecasting, neural networks outperform traditional approaches in identifying nonlinear temperature dynamics with uncertainty. However, in order to improve neural network accuracy, an intelligent adaptation for a specific location that is implemented through an intelligent forecasting system with a modified fuzzy neural network with an attention mechanism adapted for conditions of weather forecasting ambiguity registered on various meteorological websites is required. The study describes the design and test simulation of an intelligent system for a temperature forecast based on a modified fuzzy neural network with an adaptive attention mechanism, highlighting significant forecasting aspects such as nonlinear temperature dynamics based on repository data, using modified authors’ software. The findings of the system developed demonstrate its robustness and a decrease in the root mean square error of its forecast by three on average compared to the recurrent neural networks in the setting of undefined and ambiguous weather forecast.

The article is devoted to the solution of a problem of multi-criterial scheduling for execution of calculations of a large number of time-consuming computational tasks being solved simultaneously when implementing the time-sharing mode for their solutions in software and hardware’s multiprocessor computing systems by the spacecraft control center. A dynamic recurrent model with dead-end controls is used to implement the schedule of organizing software command information with control sectors. The criteria for selecting an efficient option of a daily schedule for the control sectors’ operation are determined, with the schedule being presented as time intervals of access to the computing system’s resources. Compared to the traditional algorithms of discrete optimization, the method of dead-ends control is more efficient in calculation in the frame-work of a dynamic model. An example of calculations conducted by the dead-end controls algorithm for the operational program, which is used on board of the spacecraft during a communication session, is given.

The article reviews literature on identification methods for parameters of regression models, including those based on Chebyshev metrics. The publications contain data on the development of an algorithm for the unambiguous definition of Chebyshev projection; a new method that combines Minkowskian distance and Chebyshev distance, with both being used as a similarity measure in the clustering process when grouping data; generalizations of particular goal setting for curves and surface fitting to the data observed or calculated as a result of replacing least squares with the Chebyshev norm; and integral estimates of the anthropogenic transformation of the territory using multidimensional statistical methods. Using the anti-robust method of estimation, the authors have developed a method to estimate unknown parameters of a regression piecewise linear risk function, whose aim is to solve a linear Boolean programming problem. The risk function of the dynamics of the price per square meter of living space of dwellings in the housing market in the Russian Federation is built using the least modules method and the anti-robust estimation method. Average pricing for silicate wall blocks, concrete floor slabs, and ready-mixed concrete are used as independent factors in the model. Both versions of the models built describe the dynamics of the output indicator profoundly, as evidenced by the high values of adequacy criteria, and therefore can efficiently solve the forecasting problems. It has been established that the number of maximum module errors of the risk model approximation is equal to three, i. e. the number of independent variables, when applying the anti-robust method.