production processes during the fourth industrial revolution according to the concept of Industry 4.0. The concept of Industry 4.0 provides for the digital transformation of production using modern automated production technologies and information technologies. Such transformation accelerates the pace of production and management integration of production and reduces the costs of servicing control systems and equipment. Automated production equipment of modern enterprises should be controlled using information and communication technologies. The basic technology that ensures the exchange of information between devices and facilitates decision-making on the network is the Internet of Things. Artificial intelligence, cyber-physical systems, service orientation, high-speed communication systems and remote access are technologies that allow organizing harmonious intelligent production. Thanks to this, production will have the maximum level of automation of processes and their full control, feedback between production links and product properties, reduced costs per unit of production and improved quality. Modern automation systems are analyzed and it is indicated that in order to create flexible intelligent production environments, it is necessary to use effective models of component-based industrial automation systems with high reliability. The ways to improve the efficiency of component-based systems based on modern technologies are presented: artificial intelligence, machine learning, high-speed wireless networks, forecasting systems, monitoring and data processing in real time. The creation of effective component-based industrial automation systems will reduce the time and cost per unit of production, improve its quality and reliability of production systems.

Keywords: automation, industry 4.0, efficiency, digitalization, component-based systems

Support for decision-making in response to forest fires is a complex multi-criteria process. This article provides a comparative assessment of the validity of decisions made using three decision support tools. The analytic hierarchy process, analytical network method, and TOPSIS method were used for the assessment. The uncertainty, volume, and degree of heterogeneity of the data taken into account when making decisions were considered as validity criteria. The conducted studies have proven the possibility of using the intelligent decision support system developed by the authors to respond to forest fire threats, as well as increasing their validity compared to other tools.management decisions. The validity of management decisions is understood as an objective representation of the state of the external environment (uncertainty of data and decisions, the volume of processed data, the dimension of the feature space) from the point of view of the problem being solved by the decision maker. The evaluation of tools allows you to determine the preference of tools in terms of the criteria under consideration.

Keywords: multi-criteria assessment, forest fires, validity, intelligent decision support system

The work is devoted to the problems of assessing and predicting the reliability of photovoltaic generation devices. The purpose of the work is to identify factors affecting the volume of electricity generation, as well as to build models and procedures for predicting the reliability of the panels during their use depending on these factors. An overview of the types of solar power plants and the photovoltaic panels used is given. An analysis of the factors affecting their reliability is performed, on the basis of which a hierarchy of fuzzy factors related to each other by fuzzy production rules is built. It is proposed to use a statistical two-parameter Weibull model to predict the reliability of the panels. An algorithm for neuro-fuzzy tuning of the reliability forecasting model depending on the factors considered is developed and software implemented, which can be used to create information and analytical systems for decision support in the design and operation of solar power plants.

Keywords: solar energy, photovoltaic panel, reliability prediction, statistical model, neuro-fuzzy network

The widespread use of social media platforms has led to the accumulation of vast amounts of stored data, enabling the prediction of rare events based on user interaction analysis. This study presents a method for predicting rare events using graph theory, particularly graphlets. The social network VKontakte, with over 90 million users, serves as the data source. The ORCA algorithm is utilized to identify characteristic graph structures within the data. Throughout the study, user interactions were analyzed to identify precursors of rare events and assess prediction accuracy. The results demonstrate the effectiveness of the proposed method, its potential for threat monitoring, and the possibilities for further refinement of graphlet-based prediction models.

Keywords: social media, security event, event prediction, graph theory, graphlet, interaction analysis, time series analysis, correlation analysis, data processing, anomalous activity

The article considers the problem of dynamic control of a 3-connected manipulator designed for trajectory following in conditions of external dynamic disturbances. To ensure the stability of the system, an adaptive PID controller based on the methods of kinematics and dynamics of a multi-link system is proposed. The analytical conclusions of direct kinematics, the calculation of the Jacobian matrix, and the perturbation compensation algorithm are described in detail. The experimental part is presented in the form of MATLAB modeling, the results of which are illustrated by graphs of motion, error convergence, dependence of link angles and control moments, as well as comparative tables of system characteristics at various levels of disturbances.

Keywords: robotics, manipulator, adaptive PID controller, dynamic control, direct kinematics, Jacobian matrix, perturbation compensation

A project is a single system, an interconnected network of elements: participants, resources, processes, and goals. This relationship is critically important for successful implementation by the technical customer service. Processes that are clearly defined and managed ensure consistency and efficiency. Therefore, project design and management requires a systematic approach that takes into account all relationships and strives to optimize each element to achieve a common goal. A system approach is a method that considers a problem or task in terms of its interrelationships and interactions of all elements of the system. In the context of a technical customer service, this approach can be particularly useful for project management, process optimization, and work efficiency improvement.

Keywords: construction project, technical customer, planning, technologies, risks, system approach, project management, documentation of processes, construction site, system

The article considers issues related to making management decisions when ensuring safety in emergency situations. It reflects the features of making management decisions in emergency situations, when achieving a guaranteed level of safety is not always possible. The control loop is presented and the connections between the elements of the first and second stages are analyzed. It is shown that uncertainty in making management decisions arises due to a lack of information about the control object or is caused by unprofessional actions of the decision maker. It is proposed to create and use in practice a digital twin of safety in an emergency situation to eliminate uncertainties in making management decisions. Decomposition of the task into subtasks allows for the process of collecting and analyzing aggregate information about the control object to eliminate uncertainties and minimize risks in the development, adoption and implementation of management decisions in an emergency situation when ensuring safety.

Keywords: control model, control loop, uncertainty, risk, digital twin, decomposition, emergency safety

The importance of recycling construction waste for the development of closed-loop economy technologies in the construction industry is considered. The effect of replacing high-quality granite and limestone crushed stone with secondary aggregate obtained by crushing concrete scrap on the strength properties of geopolymer concrete was investigated. It was established that such a replacement does not lead to a decrease in the strength of such concrete, and the impact resistance increases significantly.

Keywords: demolition waste, concrete scrap, recycling, geopolymer concrete, blast furnace granular slag, crushed stone crushing screening, closed-loop economy technologies, secondary aggregate, strength, impact resistance

In this work, an approach is considered, which makes it possible to obtain scientific-based management decisions on the development of organizational systems. The purpose of the work is to show in a particular example the development of a fuzzy cognitive model development process, to analyze the model for sustainability, to determine the activation vertex complexes. The toolkit for describing and analyzing a fuzzy cognitive model is based on the basic concepts of fuzzy graph theory. Simulation results are given, directed to the development of possible scenarios for the development of situations of a socio-economic system of the Rostov region. The results are clearly illustrated by examples of fourteen scenarios, the matching of which to the main factors made it possible to determine a plurality of pessimistic and optimistic and to give recommendations to the face receiving the decision.

Keywords: control, organizational system, cognitive model, simulation modeling, fuzzy graph, sustainability

The number of information security incidents and the amount of damage caused by them are increasing every year. The relevance of information security incident response remains high. The primary response action is an information security incident localization. The purpose of this study is to reduce the time taken to localize detected information security incidents by information security incident response teams. The purpose is achieved by issuing and using a mandate for information security incident localization by orchestration tools and/or artificial intelligence systems in an automated mode. Analysis and synthesis of available publicly materials were applied as research methods. The results of the analysis and evaluation of different criteria applicability for granting a mandate to localize an information security incident in an incident response are presented in the article. A mandate is granted to orchestration tools and/or artificial intelligence systems to perform localization of an information security incident in an automatic mode, i.e., without the involvement of information security incident response team forces. In evaluation the applicability of various criteria for granting a mandate, unlike the known ones, the level of difficulty in determining values for the criteria in question by information security incident response team forces alone was assessed. Criteria and their values are defined, which, unlike the known ones, highlight the area for information security incidents localization in automatic mode.

Keywords: response team, response area, response, automatic localization, orchestration, artificial intelligence

The paper analyzes existing 3D printing technologies in the context of application in construction. The experience of 3D printing application in commercial projects is considered. Scientific research on the improvement of various technologies is summarized. 3D printing technologies promising for construction - wire-arc and ultrasonic additive manufacturing - are identified.

Keywords: 3D printing, construction, additive technologies

This paper presents the results of a study aimed at developing a method for semantic segmentation of thermal images using a modified neural network algorithm that differs from the original neural network algorithm by a higher speed or processing graphic information. As part of the study, a modification of the DeepLabv3+ semantic segmentation neural network algorithm was carried out by reducing the number of parameters of the neural network model, which made it possible to increase the speed of processing graphic information by 48% – from 27 to 40 frames per second. A training method is also presented that allows to increase the accuracy of the modified neural network algorithm; the accuracy value obtained was 5% lower than the accuracy of the original neural network algorithm.

Keywords: neural network algorithms, semantic segmentation, machine learning, data augmentation

The dynamic time warping algorithm (DTW) is designed to compare two time series by measuring the distance between them. DTW is widely used in medicine, speech recognition, financial market and gaze trajectories analysis. Considering the classic version of DTW, as well as its various modifications, it was found that in the tasks of analyzing the distance between gaze trajectories, they are not able to correctly take into account the duration of its fixations on visual stimuli. The problem has not attracted much attention so far, although its solution will improve the accuracy and interpretation of the results of many experimental studies, since assessing the time of visual focus on objects is an important factor in visual analysis. Hence the need to adapt DTW for such tasks. The goal of this work is to adapt the classic DTW to the problem of finding the distance between two time series with periods of low variability of values. During the demonstration of the developed algorithm, it was proven that the effect of a given minimum threshold of fixation duration on the result is significant. The proposed adaptation of DTW will improve the quality of visual data analysis and can be applied to understanding the mechanisms of human perception and decision-making in various fields of activity, such as psychology and marketing, as well as to developing effective methods for testing interfaces.

Keywords: dynamic time warping algorithm, eye tracking, time series, gaze trajectory, gaze fixation duration

The article shows the importance of the role of clinical engineering departments to ensure high-quality comprehensive control of the state of medical equipment at all stages of its life cycle. The main resource of such departments is the competence resource of clinical engineers and their working time resource. In order to rationalize the use of these resources, we systematized the causes of failures of medical devices. Based on this, a number of general metrics were developed that characterize the adaptability of clinical engineering departments to the conditions of a specific medical institution, such as the competence profile of the department and the profile of the need for technical maintenance of medical devices. The use of these data made it possible to formalize the algorithm for managing the clinical engineering department, aimed at maximizing the useful use of the human capital of these departments.

Keywords: clinical engineering, clinical engineer, time budget, performance metrics, medical device maintenance

This paper addresses the limited accuracy of existing automatic systems for detecting deepfake audio content in real time. A solution is proposed to increase the efficiency of detecting signs of deepfake use by improving neural network models and algorithms for analyzing audio recordings of human voices. An algorithm and corresponding software for a voice attack detection system have been developed. For training and testing, datasets were created containing real voice audio recordings and deepfake audio samples. Evaluation on a real-world test set demonstrated an accuracy rate of 83%, confirming the effectiveness and practical applicability of the proposed solution in combating audio deepfake threats.

Keywords: deepfake, speech audio signal, machine learning models, convolutional neural network, vishing