This article proposes a method for determining the emotional state of a person using a chatbot. The article defines a chat bot, justifies the choice of the type of chat bot, and defines the basic principles of their work. Based on the identified differences in the work of algorithms for determining text by chat bots, the most suitable technology for solving the task is described - working with neural networks.

Keywords: chatbot, neural network, text tone, emotions, augmented reality

The issue of changing scientific interest in the methods of combining images in technical systems is considered. The material is based on the analysis of open publications, patents presented in the scientific electronic library eLibrary for the period 1980 – 2021, as well as not included in it for any reason. The types of sources for formation of image, goals and features of the most common ways of combining are considered. The areas of preferential use methods of combining are given. The issues of image preprocessing to increase the informativeness of the result of the combination are considered.

Keywords: visual data, foundation image, image combination, information combination, image preprocessing

The article presents economic indicators characterizing the introduction of robots of various types into the global industry, describes the legal aspects of the existence of a digital personality in society, talks about the perception of robots as a living person, describes legal ways of interpreting "robot rights".

Keywords: robot, society, robot rights, artificial intelligence, legal aspects of robot rights

In a number of branches of agricultural production, including agriculture, land reclamation, etc., there are problems, the solution of which requires the use of artificial intelligence. In particular, the assessment of the reclamation state of agricultural fields in large areas is a very time-consuming task, even with the use of unmanned aerial vehicles. To automate these intelligent approaches, it is effective to use artificial neural networks (INS) implemented in the form of computer programs. The use of software as a service (SaaS) is a modern approach to computer support of various intelligent production processes, including agricultural. Agriculture is a promising industry for the introduction of such technologies. The aim of the study is to develop a methodology and create a cloud-based SaaS system for identifying defective areas of agricultural fields based on INS. The development of neural network technologies and cloud services makes it possible to process a large amount of information in the cloud and provide user access to computing power. The article describes the methodology of building a service architecture for recognizing problem areas of cultivated agricultural fields, data preparation, network training, development of client and server parts. Such implementation is possible with the use of such technologies and tools as CUDA, CNN, PyTorch. As a result, the strengths and weaknesses of their use for solving the problem of image recognition on the example of problem areas of agricultural fields were identified. It has been established that classification-type INS are capable of solving problems of recognizing the reclamation state of fields, and modern information technologies make it possible to transfer calculations to the cloud, while the cloud service can be monetized as a SaaS model.

Keywords: agriculture, color images, SaaS system, artificial neural network, image classification

Artificial intelligence methods can be used to solve the problems of agricultural production. Assessing the condition of crops in large areas, even with the use of unmanned aerial vehicles, is a time-consuming task. The peculiarities of the task of such an assessment are the multifactorial nature of the analyzed structures, which require the use of a systematic approach at all stages of the study from the formation of a database of color images to the intelligent solution of problems of their analysis. The results of the analysis of the U-net architecture of the INS and its limitations for the problem of image segmentation are presented. The purpose of the study is to substantiate the architecture of the segmentation artificial neural network (INS) to identify problem areas of agricultural fields. The hypothesis of the segmentation network advantage was tested on the DeepLabV3 ResNet50 architecture. Numerical experiments have established that the increase in the accuracy of segmentation of images of agricultural fields is constrained by the limited resolution and accuracy of manual markup dataset. The built architectures can be used as an algorithmic core for creating SaaS systems, while the performance of the used configuration of the INS can be crucial.

Keywords: color images, segmentation task, agropole plots, deep neural network, INS architecture, convolutional layers

This work is devoted to modeling the absorption of microwave electromagnetic field energy in a device for milk pasteurization. Using CAD FEKO, a 3D model of the device was built and its operation was simulated. A study was made of the influence of the tilt angle of quartz tubes on the distribution of the electromagnetic field in the waveguide. The influence of the diameter and material of the tubes is also considered. The distributions of the electric field and the specific power absorbed per kg of dielectric in the waveguide are obtained. The accuracy of the results was assessed.

Keywords: pasteurization, microwave, heat treatment of dielectrics

The widespread use of Educational Data Mining (EDM) allows the collection of data in the educational field for the analysis and adjustment of the educational process. Based on the analysis of the areas of training of construction specialties, a choice of job requests from the site was made hh.ru . A chain of nodes has been built in the Knime program for analyzing vacancies in construction specialties. Based on Knime queries, a semantic analysis of employers' requirements for construction specialties was carried out. The dependence of the result of the analysis of employers' requirements on the number of terms in the topic was considered. The preparation of the material was carried out to compare the data obtained from the work programs with the data extracted from the job search site hh.ru .

Keywords: analysis, data, work program, education, query, term, table, employer requirement

This article discusses the problems of constructing convolutional neural networks for determining road objects. The general relevance and formulation of the problem of determining road objects is presented. The rationale for the use of artificial neural networks for determining road objects has been formed. The Retinanet network architecture is used as the main architecture of an artificial neural network for determining road objects. The general concept of this architecture and the main subnets are visualized. Error functions for the main subnets of the Retina net network are described. The design description of algorithms for constructing data annotation for training an artificial neural network, as well as algorithms for constructing the neural network architecture of classification, regression and feature pyramid is given. The dynamics of changes in the general error function when determining road objects is determined. The result of training an artificial neural network is presented.

Keywords: convolutional neural networks, classification, regression, convolutional neural networks, deep learning, big data, mathematical modeling, computer science, RetinaNet architecture

The article describes a method for translating pictogram messages into text in Russian language based on machine learning. The text of the article contains the concept of alternative communication systems, a description of the training data preparing process, a description of the neural network architecture and the results of training.

Keywords: alternative communication systems, machine translation, machine learning, neural network, transformer architecture, Python, software

The question of creating an automated accompaniment is still an undisclosed part within the current automation of the musical field. The construction of accompaniment is used not only in the musical field, but also in related ones. Automatically generated accompaniment is used in audio and video studios for advertising, by people with and without musical education. In this paper, the existing methods for constructing automated accompaniment, audio file formats will be considered, and the developed algorithm and method for automatic accompaniment generation will be described.

Keywords: accompaniment, auto generated accompaniment, auto accompaniment, melody, MIDI

The article is devoted to the organization of data transmission from seismic stations via radio channel. The analysis of noise and noise immunity of phase-locked frequency systems, as well as the effect of noise on the synchronization of signals over time, is carried out.

Keywords: earthquake, data transmission, synchronization, encoding, frequency, noise, interference, refraction, time

The article represents the results of the research of economic effectiveness of NIIOKR results. There are investigated the possibilities of using mathematic models for the evaluation of scientific production, the opportunities of its introduction into the economic practice.

Keywords: mathematic models, prognosis, economic effectiveness, economically valuable features, sorts

In the process of conducting information activities, a large set of data accumulates, which reflects the specific features of the work performed. The stored information is not always in an orderly and understandable form, which makes it very difficult to work with it. This complicates the analysis, increases the processing time. Neural networks can solve this problem. Today, neural networks are widely used in many fields of activity, due to their application, for example, it becomes possible to analyze the market situation more thoroughly and make appropriate decisions that directly affect success. Thanks to the use of a neural network, it is possible to carry out a set of information in a convenient form for analysis. The article will provide a list of information about the self-organizing Kohonen map, concerning the principles of the neural network. The processing of test data with visualization of maps is considered.

Keywords: Kohonen self-organizing map, Kohonen networks, neural networks, cluster, processing, Self Organizing Map, SOM

The main directions of the energy strategy of railway transport are to improve the management structure of the railway energy complex, reduce the cost of electric energy and reduce the cost of its acquisition. The initial information for planning optimal operating modes in the management of the energy complex is provided by the forecast of electricity consumption. According to the rules of functioning of retail markets, consumers are required to accurately plan the volume of electricity consumption. If the power consumption deviates by more than 5% of the planned volume, the company incurs additional costs. To make an accurate forecast, it is necessary to analyze the source data – the archive of electricity consumption. At the initial stage of data analysis, the problem of omissions is revealed. If there are gaps in the data, the process of forecasting electricity consumption can be difficult, and sometimes impossible. The most rational solution is to fill in the gaps using modern methods of information processing. This will allow you to clearly present the data structure, calculate the necessary values and interpret the results of the analysis.

Keywords: power consumption, time series, data gaps, recovery of missing values, forecasting of power consumption, train traction, railway transport, neural networks

The construction of a regression model of errors in the approximation of the current curve from factors affecting this error is described. The following factors are selected as influencing factors: the number of coefficients of the Bessel-Fourier decomposition and the number of points on which the original function is constructed. Experimental data were obtained as a result of modeling electrical processes occurring in a pulsed magnetization reversal system.

Keywords: permanent magnet, regression model, Bessel-Fourier decomposition, approximation, momentum, factors, function, curve, momentum, error

This article is devoted to the possibility of using random access memory as a pluggable disk array in order to speed up calculations within a heterogeneous computing system. The problems of using a RAID array of hard drives as the main disk space for storing data generated by applications for a heterogeneous system of tasks are considered. The principles of using random access memory as a disk space are presented, as well as the features of connecting to the thus obtained data storage via a network.

Keywords: parallel computing, file system, random access memory, mounting, heterogeneity, computer complex

The development of cyber intelligence as a new way of detecting information (information technology) objects in cyberspace is considered, its relationship with the OSI network model is shown, the development of cyber intelligence systems in everyday conditions is determined. Models of information technology object detection systems in the conditions of a complex electronic environment in the information space are presented.

Keywords: cyber intelligence, classification, cyberspace, detection, information and technical objects

The article discusses the use of cybernetic space for the detection of n-dimensional information technology objects and their subsequent identification. A conceptual model of a multidimensional intelligence and search system is presented, the intelligence cycle of searching for information and technical objects is described, as well as the relationship of radio intelligence with cybernetic intelligence.

Keywords: identification, information technology object, infosphere, cyberspace, detection, intelligence, intelligence cycle, recognizing

The article shows that the preparation of data for further use in algorithms plays an important role and this should be given attention. raw data is often corrupted and unreliable: it may contain out-of-range values ​​(noise), outliers (outliers), and gaps (missing values). Data Preparation is a very time-consuming iterative process that takes up to 80% of all resource and time costs in the life cycle and includes the following tasks of processing initial ("raw") data: data sampling, data cleaning, feature generation, integration, formatting. Data exploration consists in studying the following steps: summarizing data, grouping data, exploring relationships between different attributes. Cluster analysis is a data analysis technique used to find groups that share common attributes (also called grouping). An algorithm of actions for preparing data within the framework of information security log events for further clustering is given.

Keywords: data, data clustering, events, information security log, algorithm, Data Mining, Data Preparation, dataset, Machine Learning

The article is devoted to the control system for the process of moving textile material in an apparatus for impregnating fabrics with periodic action. The control is implemented using a programmable logic controller (PLC). We consider a program developed in the Ladder Diagram (LD) programming language that implements motion control taking into account the change in torque.

Keywords: solution, immersion, technological process, algorithm, programming language LD

This paper describes the process of developing machine learning models for predicting problem states. The formation of decision support systems in problem situations is based on the using of ensemble methods of machine learning: bagging, boosting and stacking. The algorithms of undersampling and oversampling is applied for improving the quality of the models. Using of complex machine learning models reduces the ability to explain the result obtained, therefore various ways of interpreting the constructed models are given. Based on the results of the study, a method for predicting problem states was formed. This approach contributes to the gradual solution of the identified problem situation and the consistent achievement of the goal.

Keywords: machine learning, bagging, boosting, stacking, problem states, data balancing, shap-values

This article discusses the problem of choosing a monitoring system for the IT infrastructure. A comparative analysis of monitoring systems applied to various types of IT infrastructures was carried out and a solution was selected for a specific IT infrastructure of the company.

Keywords: monitoring, infrastructure, Zabbix, Grafana, Kubernetes, metrics

Mobile applications are widely used by many people in everyday tasks. Every year there is an increasing need for more functional, convenient and reliable software tools that can provide fast and safe work in various fields. But to develop such an application, it is necessary to use an architecture that meets all the requirements. In this paper, we will talk about the use of components from Android Architecture Components developed by Google, which allow you to implement some design patterns taking into account the features of the Android operating system. The article will provide a list of the most used components, as well as a brief reference on their functionality. The work of one of the components with the basic elements of the Android operating system is considered. The interaction of components is also schematically shown by the example of the implementation of one of the design patterns.

Keywords: application architecture, Android Architecture Components, application, android

In this work, we studied the effect of fog on machine vision systems, in particular, on the correctness of the pattern recognition algorithm. As part of this work, a filter is implemented that eliminates distortions caused by fog. A corrective filter has been developed, an analysis of the operation of a neural network with images of various definitions has been carried out, on the basis of which recommendations have been made to improve the accuracy of pattern recognition.

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

The article considers a variant of formalization of the task of determining the demand for training areas and possible areas of employment of graduates by comparing the skills obtained in the framework of training and the requirements of the labor market on the basis of semantic analysis of job descriptions. The formalized model is used for further algorithmization of the solution and software implementation within the module of the complex tools of remote career guidance.

Keywords: API requests, vacancies, demand for training areas, career guidance, digitalization of career guidance activities, formalized model