Top drive systems, mounted on mobile drilling complexes, are used for repairing oil and gas wells. Our team collected and analyzed data on the causes and downtime of more than 60 units of top drive systems operating in the fi elds of Western Siberia. Operators use top drive systems under adverse conditions that have a high level and unsteadiness of actual loads. Consequently, the functional reliability of these systems often falls short, leading to numerous repair and recovery activities and frequent replacement of elements that have exceeded their service life. Failure of top drive systems elements leads to the stop of the entire technological process of well repair and, as a result, to large economic losses. Therefore, one of the important directions in the problem of managing the reliability of top drive systems is the improvement methods for substantiating and analyzing reliability indicators based on statistical data from actual use. We have calculated reliability indicators and determined distribution laws that enable us to assess the functional reliability of top drive system elements in a qualitative manner. This will enable us to make informed decisions while ensuring the necessary level of reliability.

The article examines the projected PC sales dynamics for the period 2022–2030, which allows estimating the potential market size. We conducted a survey among experts in computer hardware maintenance and analyzed the results using the Python programming language. The team analyzed the survey results and constructed an illustrative model of an information system for diagnosing computer hardware, which they will use during program development.

The article describes metrics and algorithms that allow evaluating the difference or similarity of the objects under study: Hamming distance, Levenshtein distance, Jaro-Winkler similarity, Dice-Sørensen coeffi cient, SIFT, Perceptual Hash algorithm. To identify an algorithm that is optimally suitable for evaluating the uniqueness of logos by comparing them with each other, we implemented metrics and algorithms as programs in the Python programming language. Then, we tested their speed and quality of work. The fastest working algorithm for comparing logos is based on the calculation of a perceptual hash sum, followed by the calculation of the Hamming distance.
The most accurate results of comparing logos were obtained during the operation of the program based on the calculation of the Hamming distance. We chose a software-implemented algorithm based on Hamming distance
calculation as the optimal algorithm that combines high speed of operation and the quality of the obtained results.

The article discusses the concept of a web platform designed for collecting and summarizing news in information technology. The platform gathers data from various sources, offering users a convenient interface for searching and reading news materials. The key features of the system are the ability to classify articles, make summaries, and assign tags using large language models (LLM), as well as the automatic translation of articles into other languages.

The paper gives a brief review of publications on the application of mathematical modeling methods in pension provision. Regarding the application of the Heston-Hull-White model in pension fund manage ment, specifi cally, we examine: the description of pension fund returns in Spain and Great Britain using an autoregressive model and neural network; the model of pension plan participants in the Slovak Republic; the problem of optimal management of defi ned contribution pension funds; the problem of optimal investment of a pension scheme participant facing stochastic infl ation; the nonlinear optimization model for the Italian defi ned contribution pension system. The paper develops two versions of the Leontief piecewise linear function for the total annual funding of the Russian Social Fund’s Irkutsk Oblast branch: the ordinary version and the version with optimal transformations of the independent variables. Both versions are characterized by acceptable accuracy. Their triggering vectors indicate that the factor determining the dynamics of the output variable is the number of self-employed (payers of contributions for themselves).

The research analyzes the working architecture for a neural network decoding algorithm based on belief propagation. It is found that the weight distribution and an effi cient computational graph determine the number of trainable parameters and computations in the neural network. The weight distribution involves calculating the weighted sum of the output signals of the neurons of a layer, multiplied by the corresponding weights, and adding the biases. The data region extraction method involves applying a nonlinear activation function to the output signals of neurons. After several iterations of local decoding, the algorithm calculates the loss value using the mean square error loss function. The simulation results indicated that using an approach similar to the neural network Belief Propagation (BP) algorithm improved the performance compared to the standard decoder built using the standard BP algorithm. A robust neural network-based decoding scheme for wireless communication systems is proposed. This recurrent neural network architecture, based on gating and weight distribution algorithms, is designed to perform belief propagation decoding without prior knowledge of the coding scheme.

The analysis of soft clustering methods of documents and probabilistic distributions of terms and topics leads us to consider computational methods and tools for modeling the dynamics of polytopic fl ows in a multidimensional information space. We propose an optimized stochastic model that captures the dynamics of soft clustering of knowledge networks in an information space. This model is based on semantic connections
in texts of a specifi c subject area, which are extracted from scientometric and bibliographic databases. Using the theoretical model, we developed an algorithm and methodology for applying advanced text analytics,
which includes the identifi cation of hidden topics and the prediction of trends. The developed methodology allows, with a certain level of scientifi c objectivity, to predict new technologies and current scientifi c directions
in a given specifi c research area, including for solving theoretical, applied and management problems. The practical results led to the development of a glossary of predictive terms “Information Technologies and Communications”. We recommend using this glossary in the educational process of the general and vocational education system

The analysis of the causes of occurrence and ways of minimizing voids that are formed inside soldered joints is carried out. Voids that form during soldering signifi cantly reduce both the mechanical and electrical strength of the joint. In addition, thermal conductivity signifi cantly decreases, especially in component housings, where the soldered joint also acts as a heatsink.
We propose two alternative approaches leading to a decrease in the formation of voids in soldered joints. The fi rst approach involves changing the roughness of the solder mask, which affects the distribution of fl ux
around the contact pad. Research shows that a higher roughness of the solder mask positively affects the better spreading of the fl ux released during solder refl ow. Here, the fl ux spot is larger and less of it gets into the
solde red joint, which leads to a minimization of the volume and number of voids. The second approach includes applying not one large amount of solder paste, but several small ones, separated by small gaps. Moreover, to maintain the volume of the solder dose, it is proposed to use thicker stencils
to apply solder paste. The presence of gaps between the spots of solder paste contributes to better displacement of gases released during refl ow.

The work is devoted to the development of a model for forecasting the price of any product based on the study of input data using the wavelet analysis. This method is a convenient tool for processing and transforming various types of initial data. Each element of the market mechanism is asassociated with a price, which is the key criterion affecting supply and demand. The processes of planning, stimulating and managing economic activity at all stages of reproduction are associated with pricing. Forecasting the consequences of decisions taken is a very important task. In the course of experiments on data from open sources, satisfactory results were obtained. It was established that it is possible to build a forecast for no more than three subsequent days.

The paper proposes a method for using a code matrix as a private key for the Walsh-Hadamard code. The number of possible code matrices has been calculated. For example, there are almost 10 million possible keys for a Walsh matrix of the order 32, they are also level 5. The paper describes the method of decoding information and the procedure for isolating the code matrix from the encrypted Walsh matrix

The wide usage of complex signals in radiolocation and communication determines the relevance of synthesizing, researching, and optimizing such signals. This article aims to derive calculation formulas for estimating the minimum limit of the achievable level of sidelobes of the zero section for the ambiguity function of discretely encoded radio pulse sequences. The introduction of the optimality coeffi cient provides a measure of the excess of the sidelobe level above the potentially achievable minimum. Radio pulse sequences based on Barker codes are shown to be optimal according to the criterion of the minimum level of the sidelobes of the zero section for the ambiguity function. The results of the optimality analysis of multiphase radio pulse sequences based on the Frank code, multiphase sequences based on the Chu code and phase-manipulated M-sequences are presented. The results can be used in radiolocation and communication.