The article discusses methods for optimizing floating point calculations on microcontroller devices. Hardware and software methods for accelerating calculations are considered. Algorithms of Karatsuba and Schönhage-Strassen for the multiplication operation are given. A method for replacing floating-point calculations with integer calculations is proposed. Describes how to use fixed point instead of floating point. The option of using hash memory and code optimization is considered. The results of measuring calculations on the AVR microcontroller are presented.

Keywords: floating point calculations, fixed point calculations, microcontroller, AVR, ARM

This article analyzes data processing problems for training a neural network. The first stage of model training - feature extraction - is discussed in detail. The article discusses the method of mel-frequency cepstral coefficients. The spectrum of the voice signal was plotted. By multiplying the vectors of the signal spectrum and the window function, we found the signal energy that falls into each of the analysis windows. Next, we calculated the mel-frequency cepstral coefficients. The use of a chalk scale helps in audio analysis tasks and is used in training neural networks when working with speech. The use of mel-cepstral coefficients significantly improved the quality of recognition due to the fact that it made it possible to see the most informative coefficients. These coefficients have already been used as input to the neural network. The method with mel-frequency cepstral coefficients made it possible to reduce the input data for training, increase productivity, and improve recognition clarity.

Keywords: machine learning, data preprocessing, audio analysis, mel-cepstral coefficients, feature extraction, voice signal spectrum, Fourier transform, Hann window, discrete cosine transform, short Fourier transform

This article describes the first stage of the research work on the development of an FPGA-based camera for vehicle identification tasks, which are widely used in automated weight and size control points. Since the FPGA is an alternative to conventional processors, which features the ability to perform multiple tasks in parallel, an FPGA-equipped camera will be able to perform the functions of detecting and identifying vehicles at the same time.Thus, the camera will not only transmit the image, but also transmit the result of processing for problem-oriented control systems, decision-making and optimization of data flow processing, after which the server will only need to confirm or deny the results of the camera, which will significantly reduce the image processing time from all automated points of weight and size control.In the course of development, a simple VGA port board, a static image program for displaying it on a monitor in 640x480 resolution, and a pixel counter program were implemented. EP4CE6E22C8 is used as FPGA, the power of which is more than enough to achieve the result.

Keywords: system analysis methods, optimization, FPGA, VGA adapter, Verilog, recognition camera, board design, information processing, statistics

This paper considers existing classical and neural network methods for combating noise in computer vision systems. Despite the fact that neural network classifiers demonstrate high accuracy, it is not possible to achieve stability on noisy data. Methods for improving an image based on a bilateral filter, a histogram of oriented gradients, integration of filters with Retinex, a gamma-normal model, a combination of a dark channel with various tools, as well as changes in the architecture of convolutional neural networks by modifying or replacing its components and the applicability of ensembles of neural networks are considered.

Keywords: image processing, image filtering, machine vision, pattern recognition

This article explores the LTE-R group, in which the OFDM system has a special place, and considers the possibility of developing new methods for detecting error-correcting coding to test high data transmission under rate estimation conditions. The problems associated with the transmission of large amounts of information in conditions of high speed of movement of trains and the volatility of the environment are considered, as well as the features of interference associated with the railway infrastructure. As noise-immune codes, modular codes are used, which, unlike criminal BCH codes, are arithmetic.

Keywords: LTE-R standard, OFDM system, modular codes, noise immunity, error hit interval, BCH codes, error packet, error rate

The method of analyzing hierarchies has long been described, studied and applied in practice. In order to reduce the factor of subjectivity inherent in many decisions, we are considering the option of using the hierarchy analysis method, in which the assessment is carried out not by the decision maker, but by a group of independent experts. Thus, we propose a method for solving multicriteria optimization problems based on mixing (combination) of two methods - the method of analyzing hierarchies and the method of expert assessment.

Keywords: Optimality criteria, alternative, decision maker, optimization, method of expert assessments, method of hierarchy analysis, competence of experts, consistency of expert opinions

The purpose of the study is to improve the efficiency of Dijkstra's algorithm by using the shared memory model with OpenMP library and working on the principle of parallel execution in the implementation of the algorithm. Using Dijkstra's algorithm to find the shortest path between two nodes in a graph is quite common. However, the time complexity of the algorithm increases as the size of the graph increases, resulting in longer execution time, so parallel execution is a good option to solve the time complexity problem. In this research work, we propose a parallel computing method to improve the efficiency of Dijkstra's algorithm for large graphs.The method involves dividing the array of paths in Dijkstra's algorithm into a specified number of processors for parallel execution. We provide an implementation of the parallelized Dijkstra algorithm and access its performance using actual datasets and with different number of nodes. Our results show that Dijkstra's parallelized algorithm can significantly speed up the process compared to the sequential version of the algorithm, while reducing execution time and continuously improving CPU efficiency, making it a useful choice for finding shortest paths in large graphs.

Keywords: Dijkstra algorithm, graph, shortest paths, parallel computing, shared memory model, OpenMP library

Often in practice, construction times are estimated using deterministic methods, for example, based on a network schedule of the construction plan with deterministic values for the timing of specific works. This approach does not reflect the reality associated with the probabilistic nature of risks and leads to a systematic underestimation of the time and, as a consequence, the cost of construction. The research proposes to use a Markov discrete heterogeneous Markov chain to assess the risks of non-completion of construction in due time. The states of the Markov process are proposed to correspond to the stages of construction of the object. Probabilities of system transitions from state to state are proposed to be estimated on the basis of empirical data on previously implemented projects and/or expertly, taking into account the risks characterising construction conditions in dynamics. The dynamic model of the construction plan development allows to determine such characteristics as: the probability of the construction plan realisation within the established terms, the probability that the object will ever be completed, the time of construction to the stage of completion with a given degree of reliability; unconditional probabilities of the system states (construction stage) in a given period of time relative to the beginning of construction. The model has been tested. The proposed model allows us to estimate the time of completion of construction, to assess the risks of failure to complete construction within the established deadlines in the planned conditions of construction realisation, taking into account the dynamics of risks.

Keywords: construction time, risk assessment, markov model, discrete Markov chain, inhomogeneous random process

In the conditions of modern economy, where optimal personnel decisions are very important for any organizations, especially in the dynamically divisive electric power industry, the issue of developing an intelligent system for making personnel decisions in the electric power industry becomes relevant. This paper analyzes the existing tools for selection of candidates for vacant positions including managerial positions and vacancies from the electric power industry. Based on the analysis and earlier research, a competency profile of managers of the electric power industry is formed. The development of the program product was conducted using various programming languages in the Visual Studio development environment. The program represents a dynamic and interactive process of managerial decision-making, where users face different scenarios to assess the formed competencies, with the output of a detailed report on their skills, which provides employers with an objective assessment of the candidate's potential for a vacant managerial position.

Keywords: electric power industry, competences, personnel, personnel, optimal personnel management decisions, intellectual system, personnel management, competence assessment, software product

It is estimated that more than 9% of the Russian population is hearing impaired, and the development of dactyl recognition systems is becoming critical to facilitate their social communication. The introduction of dactyl recognition systems will improve communication for these people, providing them with equal opportunities and improving their quality of life. The research focused on learning the characters of the dactyl alphabet, as well as developing a labeled dataset and training a neural network for gesture recognition. The aim of the work is to create tools capable of recognizing the signs of the Russian dactyl alphabet. Within the framework of this research the method of computer vision was applied. The process of gesture recognition consists of the following steps: first the camera captures the video stream, after the images of hands are preprocessed. Then a pre-trained neural network analyzes these images and extracts important features. Next, gesture classification takes place, where the model determines whether the sign belongs to a certain letter of the alphabet. Finally, the recognition results are interpreted into a suitable symbol associated with the gesture. During the research process, the signs of the dactyl alphabet and interaction features of people with auditory impairment were studied and a dataset of more than 25000 trained data was also created. A model was developed and trained based on the most appropriate architecture for the task of the work. The model was tested and optimized to improve its accuracy. The results of this work can be used in the creation of devices to compensate for poor hearing, providing people with hearing impairment comfort in society.

Keywords: computer vision, sign recognition, dactyl classification, transfer learning, Russian dactyl alphabet, deep learning, computerization, software, assistive technology, convolutional neural networks

In this paper, we consider a technique for automatic analysis of video files for detecting the presence of persons and attractions, using recognition by key, non-repeating frames, based on algorithms for their extraction. Recognition of landmarks and faces only by keyframes will significantly reduce computational costs, as well as avoid overflowing with repetitive information. The effectiveness of the proposed technique is evaluated in terms of accuracy and speed on a set of test videos.

Keywords: keyframe, recognition, computer vision, algorithm, video

A new mathematical apparatus is proposed for monitoring the adequacy of the choice of signal sampling interval from the point of view of taking into account the main high-frequency components and identifying the possibilities of increasing it. It is based on the construction of special aliasing grams based on measured signal samples. Aliasing grams are graphs of standard deviations of the amplitude spectra of a conventionally reference discrete signal, specified with the highest sampling frequency, and auxiliary discrete signals obtained over the same observation interval, but with lower sampling frequencies. By analyzing such graphs, it is easy to identify sampling frequencies that lead to the appearance of the aliasing effect in the case of sampling, and, consequently, to distortion of the signal spectrum. To speed up and simplify the construction of aliasinggrams, it is proposed to use as auxiliary signals obtained from the reference one by thinning. It has been shown that this device is also effective in the case of the spectrum spreading effect. It can be used in self-learning measuring systems.

Keywords: sampling interval, aliasing, amplitude spectrum, aliasing-gram, sample decimation, spectrum spreading

The article discusses a graphical notation using three-dimensional visualization for representing models of automated systems according to the Methodology of Automation of Intellectual Labor (MAIL). The research aims to enhance the efficiency of modeling automated systems by providing a more comprehensive representation of the models. Research methods employed include a systems approach. The study results in the formulation of descriptions and rules for creating the corresponding graphical notation for the initial and conceptual modeling stages of subject tasks in MAIL, as well as rules for forming representations for static and dynamic model structures and representing their interrelations. Additionally, rules for visually highlighting and concealing elements within the diagrams of the graphical notation are examined, rendering it suitable for implementation as a software module with a graphical interface for CASE tools, facilitating modeling according to MAIL. Such an approach enables the visualization of the model as a whole and enhances the efficiency of analysts conducting modeling following the methodology.

Keywords: methodology of Automation of Intellectual Labor, modeling of automated systems, conceptual modeling, graphical notation, three-dimensional visualization

This paper reveals many topical problems related to the modernization of inclusive education in Russia, with an emphasis on the practice of teaching foreign language in higher educational institutions. The paper also presents models of inclusion of persons with disabilities relevant to the modern educational environment. A brief description of the historical and legal basis of inclusion in Russia is also given. The authors note that in higher education institutions inclusive education is still at the stage of formation and that for its successful implementation it is necessary to comprehend the problem and create a methodological basis.

Keywords: inclusive education, persons with disabilities, equal access, quality education, integration, synergy, legal framework, adaptation, transformation.

The work is aimed at modeling the control system of a slitting machine of a paper machine in order to improve the quality of products and eliminate defects in winding density. The developed automated system implements the functions of controlling the operating modes of the machine, distributing the loads of the bearing shafts, braking the roll and tensioning the paper web.

Keywords: slitting machine, paper machine, automated control system, rewinder, pressure roller, decoiler, reeler, accelerating shaft, deflecting shaft, cutting section

The article discusses a method for detecting local areas with hidden defects in products whose length is several orders of magnitude greater than other dimensions, when processing information from non-destructive testing of the product. To obtain the necessary information, various means of introscopy and radiation of different nature are used. Processing of information obtained using scanning control should detect areas with defects and determine their nature. To compare different processing methods and select the optimal method for processing information, a computer modeling method was used, with the help of which the process of obtaining information and processing it was simulated, which simplifies the selection of the most suitable method for detecting a defect. The article describes typical models of the received signal and presents the simulation results.

Keywords: defects, non-destructive testing, extended products, simulation model, moving averaging, time series

The article presents expressions that allow you to calculate the amount of power consumption of end nodes when transmitting a message in a wireless sensor network. Data are obtained on the values that the value of power consumption of the end node of the sensor network takes, depending on the attenuation of signals during transmission over a wireless channel, as well as on the set values of the output power and the spreading factor of the transmitted signals.

Keywords: internet of Things, sensor network, LoRaWAN, IoT system, end node power consumption, spreading factor, output power

The article discusses the conducted studies of changes in the output signal from a measuring device to assess the quality of mixing natural and chemical fibers in semi-finished products of spinning production obtained on a belt machine at various transitions. The construction of polynomial models in data analysis makes it possible to interpret information about the uniformity of fiber distribution in the tape, without taking into account the effect on changes in its linear density.

Keywords: fiber mixing quality, linear density, infrared estimation method, data estimation, linear polynomial, polynomial function

The article considers the problem of cryptanalysis of an information security system based on a difficult-to-solve problem of Diophantine equations. A mathematical model of such a protection system is described in the article and a solution to the cryptanalysis problem using an artificial immune system adapted for solving Diophantine equations is proposed. The paper discusses the basic principles of building artificial immune systems and presents the results of experiments on evaluating the effectiveness of the proposed system of Diophantine equations of a degree not exceeding six. The results obtained demonstrate the possibility of using artificial immune systems to solve the problem of cryptanalysis of information security systems based on Diophantine equations.

Keywords: cryptanalysis, information security system, diophantine equations, artificial immune system, adaptive algorithm, efficiency assessment

A low-profile wideband circularly polarized antenna is proposed for use in navigation satellite systems. The VSWR ≤2 bandwidth is 75%. The 3-dB axial ratio (circular polarization) bandwidth is 54%. The designed radiating element was fabricated and measured as part of the antenna array.

Keywords: circular polarization, wideband antenna,, antenna array, axial ratio

Determining human emotions from speech is a pressing task at the moment, because it can be applied in various industries, such as economics, medicine, marketing, security and education. This work examines the recognition of human emotions specifically from speech, because speech is an informative indicator that is quite difficult to fake. The paper discusses a neural network approach to solving the problem. A recurrent neural network with LSTM memory was implemented, and our own dataset was collected on which the model was trained. The dataset includes the speech of Russian-speaking actors, which will improve the quality of the model for Russian-speaking users.

Keywords: neural network, emotion detection, speech, classification, deep learning, recurrent model, LSTM

This article describes aspects of ontology design for the sphere of information security. There are some examples of the use of ontologies in the sphere of information security including risk management, classification of threats and vulnerabilities, monitoring incidents, as well as examples of existing developments of ontologies for information security. The relevance of the development of legal ontologies is determined and examples of their use in practice are given. Also, the importance of designing a legal ontology for the subject area of information security under consideration is given due to the presence of a large legal framework. The paper presents the developed ontology model for one of the regulatory documents in the field of personal data protection. The approach to ontology design presented in the paper is proposed to be applied in the development of an information security learning system.

Keywords: security, information security, protection of information, information, domain model, normative legal act, ontology, ontological approach, design, legal ontology

This article presents a research study dedicated to the application of the YOLOv8 neural network model for road sign detection. During the study, a model based on YOLOv8 was developed and trained, which successfully detects road signs in real-time. The article also presents the results of experiments in which the YOLOv8 model is compared to other widely used methods for sign detection. The obtained results have practical significance in the field of road traffic safety, offering an innovative approach to automatic road sign detection, which contributes to improving speed control, attentiveness, and reducing accidents on the roads.

Keywords: machine learning, road signs, convolutional neural networks, image recognition

In this article we present a study on Natural Language Processing (NLP) and Machine Learning (ML) techniques, specifically focusing on deep learning algorithms. The research explores the application of Long Short-Term Memory (LSTM) models with attention mechanisms for text summarization tasks. The dataset used for experimentation consists of news articles and their corresponding summaries. The article discusses the preprocessing steps, including text cleaning and tokenization, performed on the data. The study also investigates the impact of different hyperparameters on the model's performance. The results demonstrate the effectiveness of the proposed approach in generating concise summaries from lengthy texts. The findings contribute to the advancement of Natural Language Processing and Machine Learning techniques for text summarization.

Keywords: extractive text summarization, sequence-to-sequence, long short-term memory, encoder_decoder, summarization model, natural language processing, machine learning, deep learning, attention mechanism

The article presents a mathematical model for assessing the applicability of intelligent chatbots in the context of studying dialects of foreign languages. The model is based on the analysis of key parameters and characteristics of chatbots, as well as their ability to adapt to various dialects. The model's parameters include questions, answers, evaluation criteria, types, and costs of errors. The quality of the chatbot's responses is evaluated both according to individual criteria and overall. To test the effectiveness of the proposed method, an experimental study was conducted using the dialects of the German language as examples. During the research, such intelligent chatbots as ChatGPT-3.5, GPT-4, YouChat, Bard, DeepSeek, and Chatsonic were evaluated. The analysis of the results of applying the developed mathematical model showed that at present, the models by OpenAI (ChatGPT-3.5 and GPT-4) offer the broadest range of possibilities. ChatGPT-3.5 demonstrated the best results in communication in Bavarian and Austrian dialects, while YouChat excelled in the Swiss dialect. The obtained results allow for important practical recommendations to be made for selecting intelligent chatbots in the field of studying dialects of foreign languages and serve as a basis for further research in the area of evaluating the effectiveness of educational technologies based on artificial intelligence.

Keywords: large language model, chatbot, quality assessment, foreign language learning, artificial intelligence technology in education