Model multiparameter distributions used in science and technology are analyzed and systematized. Particular attention is paid to the Rozin-Rammler-Weibull-Gnedenko and Kolmogorov-Gauss distributions, which adequately describe single and multiple crushing. The suitability of these distributions for modeling the granulometric composition of industrial waste from mechanical processing is confirmed by physical and computer experiments.

Keywords: distribution function, mathematical model, generalized hyperbolic distributions, crushing, bulk medium, mechanical processing

Samples of metal dust generated during milling of gray cast iron were collected experimentally. The machine operating mode, dust collection points, and blowing conditions were varied in the experiments. To ensure the reliability of the result, the physical stage of the analysis of the dimensional characteristics of the dust was performed using two methods: sieving and direct optical measurements. Significant discrepancies in the statistical parameters obtained by different methods were revealed. A hypothesis explaining the differences was proposed and confirmed. An integrated approach to the physical stage of dispersion analysis of bulk media is recommended.

Keywords: wood dust, parametric identification, sieve analysis, laser diffraction, micrographs, mathematical modeling, digital twin

This article presents a study on the approach to the development of a medical decision support system (DSS) for the selection of formulas for calculating the optical strength of intraocular lenses (IOLs) used in the surgical treatment of cataracts. The system is based on the methods of building recommendation systems, which allows you to automate the process of choosing an IOL and minimize the risk of human error. The implementation of the system in the practice of medical organizations is expected to be highly accurate and efficient, significantly reduce the time allowed for decision-making, as well as improve the results of surgical interventions.

Keywords: intraocular lens, ophthalmology, formulas for calculating optical strength, web application, machine learning, eye parameters, prognostic model, recommendation system, prediction accuracy, medical decision

The situation of occurrence, identification and management of risks arising during the construction process is analyzed. Uncertainty of decision-making in construction projects involves the creation of methods that ensure the reliability of decisions and their effectiveness. Such a method was developed in the Russian Project Management Association. The paper provides an example of using this method on a real construction site. An analysis of risks arising during the implementation of a construction project was conducted, a risk map was created for this project and the PERT method was applied when creating a calendar plan.

Keywords: uncertainty, risk event, probability, risk, damage, danger, reliability, risk analysis, investment and construction project, PERT method

Modern simulation model design involves a wide range of specialists from various fields. Additional resources are also required for the development and debugging of software code. This study is aimed at demonstrating the capabilities of large language models (LLM) applied at all stages of creating and using simulation models, starting from the formalization of dynamic systems models, and assessing the contribution of these technologies to speeding up the creation of simulation models and reducing their complexity.The model development methodology includes stages of formalization, verification, and the creation of a mathematical model based on dialogues with LLMs. Experiments were conducted using the example of creating a multi-agent community of robots using hybrid automata. The results of the experiments showed that the model created with the help of LLMs demonstrates identical outcomes compared to the model developed in a specialized simulation environment. Based on the analysis of the experimental results, it can be concluded that there is significant potential for the use of LLMs to accelerate and simplify the process of creating complex simulation models.

Keywords: Simulation modeling, large language model, neural network, GPT-4, simulation environment, mathematical model

The growing popularity of large language models in various fields of scientific and industrial activity leads to the emergence of solutions using these technologies for completely different tasks. This article suggests using the BERT, GPT, and GPT-2 language models to detect malicious code. The neural network model, previously trained on natural texts, is further trained on a preprocessed dataset containing program files with malicious and harmless code. The preprocessing of the dataset consists in the fact that program files in the form of machine instructions are translated into a textual description in a formalized language. The model trained in this way is used for the task of classifying software based on the indication of the content of malicious code in it. The article provides information about the conducted experiment on the use of the proposed model. The quality of this approach is evaluated in comparison with existing antivirus technologies. Ways to improve the characteristics of the model are also suggested.

Keywords: antivirus, neural network, language models, malicious code, machine learning, model training, fine tuning, BERT, GPT, GPT-2

In the article, the authors propose a methodology for managing connections in a community based on the developed heuristic algorithm for optimal seating of participants in a multi-round networking event to maximize the likelihood of new partnerships within offline events. The seating algorithm is based on solving the NP-complete problem of the maximum clique. Optimization of the resulting solution is implemented based on the permutation crossover algorithm.

Keywords: In the article, the authors propose a methodology for managing connections in a community based on the developed heuristic algorithm for optimal seating of participants in a multi-round networking event to maximize the likelihood of new partnerships withi

The article discusses the application of neural network autoencoder in the problem of monochrome image colorization. The description of the network architecture, the applied training method and the method of preparing training and validation data is given. A dataset consisting of 540 natural landscape images with a resolution of 256 by 256 pixels was used for training. The results of comparing the quality of the outputs of the obtained model were evaluated and the average coefficients of metrics as well as the mean squared error of the VGG model outputs are presented.

Keywords: neural networks, machine learning, autoencoder, image quality analysis, colorization, CIELAB

The article is devoted to the development of an algorithm for three-dimensional terrain reconstruction based on single satellite images. The algorithm is based on the algorithmic formation of three-dimensional models based on the output data of two deep learning models to solve the problems of elevation restoration and instance segmentation, respectively. The paper also presents methods for processing large satellite images with deep learning models. The algorithm proposed in the framework of the work makes it possible to significantly reduce the requirements for input data in the problem of three-dimensional reconstruction.

Keywords: three-dimensional reconstruction, deep learning, computer vision, elevation restoration, segmentation, depth determination, contour approximation

This article presents a study aimed at evaluating the use of the Matlab Simulink software environment for the development of microcontroller systems of the STM32 family. The possibilities of Simulink in the field of modeling and testing control algorithms, as well as in generating code that can be directly applied to microcontrollers, are analyzed. The article describes in detail the process of creating conceptual models and their dynamic modeling. The advantages of using Simulink include speeding up the development process through automated assembly and the ability to adjust model parameters in real time. In addition, Simulink allows you to generate processor-optimized code, which significantly increases the efficiency of microcontroller systems. However, attention is also drawn to some limitations associated with using Simulink, such as the need to create a configuration file in STM32CubeMX and potential difficulties in configuring it. The article provides an in-depth analysis of the application of Simulink in the context of the development of STM32 microcontrollers and can become a key material for those who want to deepen their knowledge in this area.

Keywords: model-oriented programming, MatLab, Simulink, STM32, microcontroller, code generation, automatic control system, DC motor

The article is devoted to the creation of a highly specialized automated information system for recording the parameters of the technological process of production of an industrial enterprise. The development of such software products will simplify and speed up the work of technologists and reduce the influence of the human factor in collecting and processing data.

Keywords: automated information system, system for recording production process parameters, Rammler-Breich diagram, role-based data access system

The paper proposes a hybrid multi-agent solution search algorithm containing procedures that simulate the behavior of a bee colony, a swarm of agents and co-evolution methods, with a reconfigurable architecture. The developed hybrid algorithm is based on a hierarchical multi-population approach, which allows, using the diversity of a set of solutions, to expand the areas of search for solutions. Formulations of metaheuristics for a bee colony and a swarm of agents of a canonical species are presented. As a measure of the similarity of two solutions, affinity is used - a measure of equivalence, relatedness (similarity, closeness) of two solutions. The principle of operation and application of the directed mutation operator is revealed. A description of the modified chromosome swarm paradigm is given, which provides the ability to search for solutions with integer parameter values, in contrast to canonical methods. The time complexity of the algorithm is O(n2)-O(n3).

Keywords: swarm of agents, bee colony, co-evolution, search space, hybridization, reconfigurable architecture

Information technologies are used in all spheres of modern society. Databases and document flow in organizations must be clearly organized, streamlined, and the interconnected work of company departments and services must be ensured to collect and process information flows and make effective management decisions. The article reflects the place of the stages of planning and designing information technologies and methods of their development in the algorithm for forming the strategy of an organization's IT project. Approaches to the formation of automated workplaces are shown using the example of the organizational and managerial structure of an enterprise. The services and departments of the organization responsible for planning, accounting, analysis and control of its financial results have been identified, which led to the conclusion about the directions for improving the quality of IT project development.

Keywords: information system, IT project, planning, design, modeling, automated workstations

The article provides a brief description of the existing methods of vectorization of texts in natural language. The evaluation is described by the method of determining the similarity of words. A comparative analysis of the operation of several vectorizer models is carried out. The process of selecting data for evaluation is described. The results of evaluating the performance of the models are compared.

Keywords: natural language processing, vectorization, word-form embedding, semantic similarity, correlation

Our lives are permeated by data, with endless streams of information passing through computer systems. Today it is impossible to imagine modern software without interaction with databases. There are many different DBMSs depending on the purpose of using the information. The article discusses the Locality-sensitive hashing (LSH) algorithm based on the Pl/PgSQL language, which allows you to search for similar documents in the database.

Keywords: LSH, hashing, field, string, text data, query, software, SQL

The article describes the process of developing and optimizing a Telegram bot for remote server management. As part of the study, an application was developed, implemented in Python using the Telegram API and using the PostgreSQL DBMS to store data as part of the workflow. The system is designed to optimize the workflow in the field of administration, providing users with an easy way to manage servers via Telegram. With the help of the created bot, users will be able to control servers, execute the necessary commands remotely, receive up-to-date information and monitor the status of servers in real time. The development of the bot included several stages, from architecture design to testing and implementation. Particular attention was paid to data security and system reliability to ensure stable operation and protection from unauthorized access. As a result, a functional and convenient tool was created that significantly simplifies administration tasks and increases the efficiency of server management.

Keywords: python, ssh, it-service, telegram-api, postgresql, psycopg2, aiogram, sql, bot, administration, remote control

The paper proposes a method for identifying patterns of the relative positions of buildings, which can be used to analyze the dispersion of air pollutants in urban areas. The impact of building configuration on pollutant dispersion in the urban environment is investigated. Patterns of building arrangements are identified. The methods and techniques for recognizing buildings are examined. The outcomes of applying the proposed method to identify building alignments are discussed.

Keywords: patterns of building location, geoinformation technologies, GIS, geoinformation systems, atmospheric air

This article is dedicated to developing a method for diagnosing depression using the analysis of user behavior in a video game on the Unity platform. The method involves employing machine learning to train classification models based on data from gaming sessions of users with confirmed diagnoses of depression. As part of the research, users are engaged in playing a video game, during which their in-game behavior is analyzed using specific depression criteria taken from the DSM-5 diagnostic guidelines. Subsequently, this data is used to train and evaluate machine learning models capable of classifying users based on their in-game behavior. Gaming session data is serialized and stored in the Firebase Realtime Database in text format for further use by the classification model. Classification methods such as decision trees, k-nearest neighbors, support vector machines, and random forest methods have been applied. The diagnostic method in the virtual space demonstrates prospects for remote depression diagnosis using video games. Machine learning models trained based on gaming session data show the ability to effectively distinguish users with and without depression, confirming the potential of this approach for early identification of depressive states. Using video games as a diagnostic tool enables a more accessible and engaging approach to detecting mental disorders, which can increase awareness and aid in combating depression in society.

Keywords: videogame, unity, psychiatric diagnosis, depression, machine learning, classification, behavior analysis, in-game behavior, diagnosis, virtual space

As the space industry accelerates the trend to reduce development and production costs and simplify the use of space hardware, small spacecraft, including CubeSats, have become popular representatives of this trend. Over the last decade, the development, production and operation of small spacecraft has become in demand because of a number of advantages: simplicity of design, short design and production times, and reduced development costs. The main problem in the design of CubeSats is their miniaturisation. This paper presents the results of the development of the optical cell of collecting and processing video information for remote sensing systems of the CubeSat 3U format satellite, with the aim of obtaining the maximum possible image characteristics, taking into account the strict physical limitations of the CubeSat unit. In the course of the work, using computer-aided design systems Altium Designer and Creo Parametric, the structural diagram, electrical circuit diagram, topology, 3D model, as well as the design of the housing of the cell of collection and processing of video information were developed. PCB size: 90x90 mm, PCB thickness: 1.9 mm, number of PCB layers: 10, accuracy class: 5, cell height: 20 mm, cell weight: 110 grams.

Keywords: space hardware, Earth remote sensing, small spacecraft, nanosatellite, printed circuit board, small satellite development trend, printed circuit board topology, CubeSat

The article deals with multi-criteria mathematical programming problems aimed at optimizing food production. One of the models of one-parameter programming is associated with solving the problem of combining crop production, animal husbandry and product processing. It is proposed to use the time factor as the main parameter, since some production and economic characteristics can be described by significant trends. The second multi-criteria parametric programming model makes it possible to optimize the production of agricultural products and harvesting of wild plants. in relation to the municipality, which is important for territories with developed agriculture and high potential of food forest resources.

Keywords: parametric programming, agricultural production, two-criteria model

The calculation of the coefficients of the linear best method for restoring the second derivative at zero of a bounded analytical function given in a unit circle by the values of the function and its derivative at specified points forming a regular polygon centered at zero is pointed in that paper. It also determines the error of the best method and finds the corresponding extreme function. It is proved that the extremal function is unique. At the end of the work, formulas are got that can be used to calculate the coefficients of the linear best method. In finding of these formulas, the method of duality of extreme problems was applied, which was deeply developed by S.Y. Havinson. It is proved that these coefficients are the only one.

Keywords: optimal recovery, error of the best method, linear best method, coefficients of the linear best method

The use of simulation analysis requires a large number of models and computational time. Reduce the calculation time in complex complex simulation and statistical modeling, allowing the implementation of parallel programming technologies in the implemented models. This paper sets the task of parallelizing the algorithmization of simulation modeling of the dynamics of a certain indicator (using the example of a model of the dynamics of cargo volume in a storage warehouse). The model is presented in the form of lines for calculating input and output flows, specified as: a moving average autoregressive model with trend components; flows of the described processes, specified according to the principle of limiting the limitation on the volume (size) of the limiting parameter, with strong stationarity of each of them. A parallelization algorithm using OpenMP technology is proposed. The efficiency indicators of the parallel algorithm are estimated: speedup, calculated as the ratio of the execution time of the sequential and parallel algorithm, and efficiency, reflecting the proportion of time that computational threads spend in calculations, and representing the ratio of the speedup to the sequential result of the processors. The dependence of the execution of the sequential and parallel algorithm on the number of simulations has been constructed. The efficiency of the parallel algorithm for the main stages of the simulation implementation was obtained at the level of 73%, the speedup is 4.38 with the number of processors 6. Computational experiments demonstrate a fairly high efficiency of the proposed parallel algorithm.

Keywords: simulation modeling, parallel programming, parallel algorithm efficiency, warehouse loading model, OpenMP technology

The article presents a systematic review of scientific works by domestic and foreign authors devoted to modeling fires in tunnels for various purposes. Using the search results in the databases of scientific publications eLIBRARY.RU and Google Scholar, 30 of the most relevant articles were identified that meet the following criteria: the ability to access the full-text version, the material was published in a peer-reviewed publication, the article has a significant number of citations, and the presence of a description of the results of the authors’ own experiments. An analysis was made of the methodology used in the research, as well as the results of studying fires in transport tunnels (road, railway, subway) and mine workings presented in the works. A classification of publications was carried out according to the types of tunnel structures, cross-sectional shape, subject of research, mathematical model used to describe the processes of heat and mass transfer in a gaseous environment and heating of enclosing structures, software used, validation of experimental data, and the use of scaling in modeling. It has been established that the problems of mathematical modeling of fires in deep tunnel structures, as well as modeling of a fire in a tunnel taking into account the operation of fire protection systems, are poorly studied.

Keywords: fire modeling, tunnel, mathematical model, fire prediction, heat transfer, structures, systematic review

In today's highly competitive business environment, understanding customer needs, preferences and behavior is of paramount importance. Customer identification software is a digital solution for accurate customer identification and authentication used in various sectors such as banking, healthcare, and e-commerce. Big data, machine learning, and artificial intelligence technologies have greatly improved the customer identification process, allowing companies to improve personalization of services and products, and increase customer satisfaction. However, implementing AI for customer identification faces challenges related to protecting data privacy, training staff, and selecting the right AI tools. In the future, deep learning, neural networks and the Internet of Things may provide new opportunities for customer identification, providing higher levels of security and privacy. However, there is a need to comply with privacy legislation and ensure an ethical approach to the use of AI in customer identification.

Keywords: software, customer identification, traditional methods, machine learning, artificial intelligence, evolution of identification software, future trends

The article discusses the possibilities of using virtual reality technologies to organize fire safety training for schoolchildren. The requirements for the virtual simulator are formulated from the point of view of ensuring the possibility of conducting classes on practicing evacuation skills from the building of a specific educational organization. A functional model of a virtual simulator is presented, built on the basis of the methodology of structural analysis and design, describing the process of developing a virtual space with interactive elements and organizing training for the evacuation of students based on it. A semantic description of the control signals of the functional model, its inputs, mechanisms and outputs is given. The contents of the model subsystems are revealed. Requirements for software, hardware and methodological support for training using virtual reality technologies when conducting fire training are formulated. The concept of creating a digital twin of a building of a general education organization in virtual space is substantiated. Examples of improving virtual space by using the results of mathematical modeling of fire are given. The use of visualization of smoke and flame in virtual space is justified to avoid the occurrence of panic in children during evacuation in fire conditions. Conclusions are drawn about the advantages of the proposed virtual simulator. The prospects for further research and solution to the problem of developing skills for evacuating students from a building of a general education organization in case of fire are listed.

Keywords: virtual reality, virtual simulator, virtual space, fire safety, evacuation, fire training, mathematical modeling of fire, educational technologies, functional modeling