Purpose of research of this work was to study the porosity of samples obtained by selective fusion of electroerosive ferro-chromium nickel powders produced by processing metal waste.

   Methods. When carrying out research aimed at achieving this goal, the following equipment was used in accordance with the experimental plan: an installation for producing electroerosive iron-chromium-nickel powders - original patented; raw materials for producing iron–chromium-nickel powders – alloy grade 20X25H20X2; working fluid – isopropyl alcohol; installation for selective alloying – original patented; equipment for studying the microstructure of an additive sample – Nova NanoSEM 450 electronic scanning microscope; equipment for studying the porosity of an additive sample - Olympus GX51 optical inverted microscope, equipped with software designed for quantitative analysis of digital images of the microstructure.

   Results. As part of the task aimed at studying the porosity of samples obtained by the method of selective fusion of electro-eroded iron-chromium-nickel powders, the following results were obtained. It was found that the total porosity of the material is about 2.64 %. Moreover, more than 70 % of the identified pores have a size of less than 0.5 microns. The formation of an almost poreless structure of additive samples is due to the presence of particles of various fractions in the electro-eroded iron-chromium-nickel powders, which contributes to their more compact packing during the fusion process. The microstructure study revealed that the additive sample has a uniform fine-grained structure with an average grain size of approximately 5 μm. The level of porosity and the distribution of pores in size have a significant impact on the mechanical properties of the material and determine its potential applications.

   Conclusion. The results obtained indicate that the porosity and pore size distribution in the additive sample are key factors that significantly determine its mechanical properties and potential applications in science and industry.

   Purpose of research. The study focuses on enhancing the environmental safety of multigeneration thermal power plants (MGTP). Measures are proposed for cleaning exhaust gases from an absorption refrigeration machine that operates on flue gases as part of a multigeneration system, through the development of an advanced exhaust gas purification system for the absorption refrigeration machine (ARM) within the power plant complex.

   The relevance of the work is determined by the need to minimize harmful emissions while simultaneously improving the energy efficiency of modern MGTPs.

   Methods. The research was conducted in several stages using a set of complementary methods. At the first stage, a comprehensive analytical review of scientific literature and patent sources was carried out to systematize knowledge about modern multi-generational systems, their advantages, and environmental problems. This method made it possible to identify the problem of atmospheric pollution by flue gases from ACHP (Absorption Chiller/Heat Pump) and substantiate the relevance of developing an additional purification system. At the second stage, the method of computer modeling in the SOLIDWORKS Flow Simulation software package was applied to solve the set task. This software product was chosen due to its extensive capabilities for modeling stationary and non-stationary flows of liquids and gases, heat transfer, and mass transfer. To justify the choice of catalytic material (manganese oxides) and describe the purification mechanism, an analysis of their physicochemical properties and catalytic activity, based on the principles of chemical thermodynamics and kinetics, was conducted. The presumed chemical reactions for the oxidation of NOx and SOx were considered.

   Results. As a result of theoretical research into existing multigeneration heat and power installations, it was revealed that utilizing an exhaust gas-fired absorption chiller is the most optimal method for generating cooling within the system under investigation. However, the flue gases involved in the heat conversion process have a negative impact on the environment. The analysis of multigeneration systems led to the development of a method for purifying the flue gases generated during the utilization of thermal energy by a two-stage lithium bromide absorption chiller.

   Conclusion. A solution has been proposed to improve environmental safety in the process of using multigenerational thermal power plants. It has been revealed that the proposed method of flue gas purification using an adsorber in the form of a Laval nozzle at the outlet, as well as manganese oxides on a copper grid, is a promising way to increase environmental safety when using the studied systems for the joint generation of energy resources.

   Purpose of research of this article is to analyze the problem of maintaining a microclimate in religious buildings that is optimal for preserving church buildings and their interior decorative elements (wall paintings, iconostases, icons, etc.), and to identify ways to improve the energy efficiency of ventilation and air conditioning systems.

   Methods. A study of the moisture content of the enclosing structures of the Resurrection Church revealed significant excess of regulatory values in the basement and on the first floor, confirming the presence of persistent moisture zones that affect the durability of the masonry and decorative coatings. Scanning microscopy analysis of plaster samples revealed structural heterogeneity and varying degrees of degradation caused by localized fluctuations in humidity, temperature fluctuations, and exposure to soot.

   Results. The spatial distribution of damage allowed us to establish a relationship between the condition of the engineering systems and the deterioration of the decorative layer. Archaeological work in 2015 contributed to improved drainage conditions and partial stabilization of the humidity regime. Based on the data obtained, key risk areas were identified and recommendations for upgrading utility systems were developed.

   Particular attention was paid to the need to implement energy-efficient ventilation and air conditioning with heat recovery.

   Conclusions. The analysis showed that the existing microclimate of the Resurrection Church does not ensure the preservation of the structures and decorative elements, and the identified areas of high humidity create conditions for accelerated deterioration of materials. To stabilize the internal environment, a comprehensive modernization of utility systems is required, including the installation of energy-efficient supply and exhaust ventilation with heat recovery, proper air exchange, and the use of modern air conditioning systems. Compliance with the requirements of Code of Practice 60.13330.2020, State Standard 30494-2011, and the provisions of Federal Law No. 261 will reduce heat loss, lower operating costs, and ensure stable temperature and humidity conditions. Implementation of the proposed measures will create conditions for the long-term preservation of the architectural structure and its artistic content.

   Рurpose of research is to develop a prototype automated system for laboratory testing of small structural wood specimens under cyclic loading.

   The tasks of the study are to identify test parameters amenable to automation and remote control using a cyclic load testing setup for small wooden specimens; develop control schemes for the selected parameters; and conduct trial tests using the proposed system.

   In Russia, there are no standards or codes of practice for obtaining experimental data and designing wood-based structures subject to high-cycle loads (more than 10,000 cycles). Cyclic loads include transport, wind, and dynamic load mechanisms. Cyclic testing is very time-consuming, so automation and remote control should be used to improve their performance.

   Methods. The prototype automated system includes video surveillance of the test object and remote activation and shutdown of the setup. Automated motor temperature monitoring and emergency shutdown are provided. The laboratory microclimate is also monitored.

   Results. A prototype automated system for laboratory testing of material samples under cyclic force loading is proposed. Following pilot testing, the system and setup can be further improved and used to develop an automated method for cyclic testing of small wooden specimens, as well as other types of long-term static and cyclic testing of building materials and structures.

   Conclusion. The proposed prototype is applicable for controlling and monitoring long-term cyclic and static laboratory testing of building materials and structures.

   Purpose of research is to analyze algorithms for searching for an element in a dynamic structure that is formed in the receiver during the message source identification process. This structure is formed when using identification methods based on block chaining encoding, which provides higher reliability of identification with the same size of the identifier field or hash value from the data of the previous message. The proposed approach is based on the possibility of using the results of identification from multiple sources. Each message has its own unique dynamic structure. However, messages from the same source may be included in other dynamic structures due to collisions of identifiers or hash values. If the source of the message is determined, it should be removed from all parallel dynamic structures. Since it is not known in advance which position in the structure such a message will be inserted, the deletion becomes a complete search through all the elements of the structure.

   Methods. The paper considers three alternative algorithms for searching through the elements of a dynamic structure, which is typical for identification based on coding in the block coupling mode. The structure itself is assumed to be placed in a register matrix with a fixed number of columns, equal to the length of the message sequence. However, the number of elements in each column can vary. We consider three approaches to searching: starting from the beginning of the columns, searching for the maximum elements in the columns, and searching for the minimum elements in the columns. Given the probabilistic model for placing the desired element and completing the search after it is found, each algorithm has its own average number of operations to access the dynamic structure. A mathematical model has been created to determine the complexity of each algorithm.

   Results. Based on the well-known model for placing elements in a dynamic structure and the original model for estimating the probability of an authentic or extraneous message being placed in a matrix storing elements of a dynamic structure, numerical dependencies of the average number of accesses to a column of the matrix were obtained. The size of the authentication tag (hash from previous message data) and the number of devices the receiver interacts with are used as model parameters. It was shown that a reasonable algorithm for searching elements in the considered structures is the algorithm that searches by the highest number in each column of the matrix. This algorithm, with equal parameter values, yields a number of operations 10-20 % lower than the alternatives considered in the paper.

   Conclusion. The paper discusses various variants of the dynamic element enumeration algorithm and creates mathematical models to estimate the computational complexity of each variant. It also derives the dependencies of the average number of operations for accessing the structure based on the parameters of the received messages by the receiver. It has been established that the algorithm based on the enumeration of the dynamic structure from the higher column numbers of the register matrix is suitable for organizing the removal of messages issued by external sources from the dynamic structure.

   Purpose of research. The Russian Federation and the Republic of Kazakhstan are member countries of the Kyoto Protocol, an international agreement aimed at reducing greenhouse gas emissions in order to combat climate change. This requires the formation of a model bank for automated management of the allocation of quotas for greenhouse gas emissions into the atmosphere.

   Methods. Based on the analysis of carbon accounting features, a new trading methodology based on Blockchain technology and the VCG algorithm is proposed, aimed at increasing transparency, security and automation of transactions between market participants. A method and algorithm for implementing carbon emission quotas through the auction system has been developed, which ensures the openness and transparency of the distribution process.

   Results. In this paper, we have modeled a digital platform for automated carbon emissions trading using Blockchain technology. A study of the existing tools and mechanisms of the carbon emissions quota market has been carried out, its main problems have been identified, such as insufficient transparency of transactions, the risk of fraud and difficulties in monitoring compliance with regulatory requirements. As part of the simulation, smart contracts were developed and tested, which automate the fulfillment of transaction conditions and transaction accounting. The use of Blockchain technology makes it possible to ensure high information security, control the course of trading and prevent unauthorized data changes. An automated system for accounting and conducting transactions increases the efficiency of quota management and reduces transaction costs.

   Conclusion. The developed prototype of the digital platform promotes the development of an environmentally responsible economy, encourages enterprises to reduce their carbon footprint, and ensures transparency and security in trading environmental quotas. As a result, the proposed model increases the confidence of market participants and contributes to the formation of a sustainable system for regulating greenhouse gas emissions.

   Purpose of research: detecting a decline in engagement of a distance learning student by monitoring fatigue, which enables real-time adaptation of the learning process for that student. Based on data about the learner's state, the system can suggest a break, change the type of task, or adjust its difficulty (simplify to reduce the load or make it more challenging to maintain interest).

   Methods. А method for detecting the fatigue state of a remote learner has been developed, based on the analysis of eye movement activity and the use of machine learning methods. The method consists of two sequential stages: model training and the actual determination of fatigue. In the first stage, a machine learning model intended for classifying fatigue states based on eye movement data is trained. In the second stage, fatigue is detected. Current research suggests that eye movement characteristics are sensitive indicators of fatigue. In particular, parameters such as peak saccade velocity, duration of saccades and fixations, frequency and duration of blinks, as well as changes in pupil diameter demonstrate statistically significant changes under the influence of fatigue.

   Results. The results of the conducted analysis unequivocally showed that the configuration based on the Random Forest ensemble algorithm, using a combination of features from Group 1 and Group 3, demonstrates the best performance. It was this approach that achieved the maximum values of the key metrics: an F1-score of 0.85 and an average precision of 0.80. The high and balanced scores for both the F1-score, which combines precision and recall, and the average precision, which is robust to class imbalance, indicate the overall reliability of this model for solving the given classification task..

   Conclusions. The developed method for monitoring fatigue in distance learning, based on the analysis of eye movement activity and the application of machine learning, has proven to be highly effective and practically significant. The proposed method enables the real-time detection of signs of decreased student engagement and fatigue, which opens the possibility for adaptive adjustment of the learning process (such as timely provision of breaks or changes to the type or difficulty of tasks). Implementing this system can significantly enhance the quality of distance education by personalizing learning and maintaining an optimal level of cognitive load.

   Purpose of research. To develop and describe an approach to integrating physical and virtual models in real time that takes into account the existing limitations of the classical Kalman filter for nonlinear systems.

   Methods. The study utilized the classic and extended Kalman filters, as well as their modifications with separate processing of various components of the model state and adaptive noise tuning, obtained during model state measurements. Transmitted data was analyzed to assess the model's stability in the face of time delays and optimize the model's algorithms, accounting for communication channel delays.

   Particular attention was paid to scenarios involving desynchronization of sampling frequencies between the physical setup and the virtual model, with the introduction of compensators to account for measurement gaps.

   Results. It has been shown that using a classic Kalman filter in systems integrating physical data into a digital module significantly degrades the results and, consequently, the quality of the assessment. This leads to data inaccuracies, delays, and time losses. A modified filtering architecture is proposed. It is demonstrated that this addition significantly improves system stability and reduces sensitivity to short-term communication interruptions. Simulations confirm a reduction in the mean square error compared to the classic scheme. Moreover, the level of computing power is comparable. Therefore, the proposed approach is applicable in real-time control and monitoring systems for complex objects.

   Conclusion. The study identified existing limitations of the classic Kalman filter. This is particularly noticeable when integrating physical and virtual models in real time. The proposed modification of the extended filter, which includes adaptive tuning, improves the robustness of state estimation, especially in the presence of noise and delays. The results are applicable to the construction of digital twins in robotics and industrial control systems.

   Purpose of research. Methods for embedding digital watermarks into digital objects constitute a scientific field at the intersection of information security and digital signal processing. Digital watermarks serve to ensure the authentication of digital objects by being inseparably embedded into them through the manipulation of data elements that constitute the digital object.

   A key requirement for digital watermarking methods is robustness, which entails that a watermark remains intact even after transmission over a heavily noisy channel.

   Therefore, the purpose of the research is to evaluate the robustness of watermarks to noise arising from the implementation of neural network removal attacks using the example of a watermark embedding algorithm that is robust to classical laboratory attacks.

   Methods. The study was conducted using the example of an algorithm for embedding a digital watermark into the coefficients of the discrete cosine transform of digital images using metaheuristic optimization. To implement a BlackBox removal attack, three neural network models were trained: one based on a convolutional neural network, a recurrent neural network, and a multilayer perceptron.

   Results. According to the results of experiments aimed at removing watermarks from the watermarked images as part of the BlackBox attack, the convolutional neural network architecture demonstrated the greatest efficiency. The watermarking algorithm demonstrated resistance to watermark removal by two other neural network models.

   Conclusion. The conducted research showed that the resilience of a digital watermark embedding algorithm to classical attacks does not guarantee resilience to neural network-based removal attacks. Resilience to this class of attacks must be incorporated at the stage of embedding algorithm synthesis. This can be achieved by reducing the determinism in the selection of watermark embedding areas in the image and by implementing anti-attack techniques at the embedding optimization stage.

   Purpose of research is to develop high-precision mathematical models for the read channel of TLC flash memory to conduct a comparative analysis of the effectiveness of error-correcting coding for flash memory from different manufacturers.

   Methods. This article presents static and dynamic models of the read channel of TLC flash memory. The static channel model is a set of Gaussian distributions defined by their mean and variance.

   A new feature of the static model is the proposed function for calculating the variances of the TLC flash memory read channel distributions in accordance with the specified RBER (Raw Bit Error Rate) parameter.

   Dynamic models of the read channel are used to estimate temporal changes in the distribution parameters over the life of the flash memory. In this article, a vector autoregressive model is proposed as a dynamic model of the flash memory read channel.

   Results. The result of this research is the development of mathematical models of flash memory. The static model simplifies the analysis of flash memory from different vendors without the need for specific IBIS (Input/Output Buffer Information Specification) models for each variant. This model can be used to analyze the effectiveness of various error-correcting coding schemes. The proposed dynamic model improves the accuracy of expectation estimation, taking into account flash memory operating time and the number of rewrites. On average, the estimation error of the proposed autoregressive model is 25 % lower. The autoregressive model of TLC flash memory improves the effectiveness of dynamic thresholds to reduce the RBER estimation bias.

   Conclusion. Static and autoregressive models of flash memory, along with methods for calculating/optimizing their parameters, are obtained. Using these models improves the cost-effectiveness of flash memory hardware development and its reliability by reducing dependence on lengthy low-level modeling and the adaptability of the models to different memory types.

   Purpose of research. The article addresses the problem of defects (rejects) occurring during the drying process of lumber. It substantiates the need to integrate the mathematically non-formalizable knowledge of an experienced operator with the mathematical model of the system to improve the quality of the final product.

   The process of identifying defects requires consideration of many factors affecting product quality, including aspects such as uneven temperature and humidity distribution within the material, changes in the structure of the wood, and the presence of hidden defects in the raw materials.

   Methods. A hybrid cognitive modeling approach is proposed, based on combining physico-mathematical modeling of the heat and moisture regime, the creation of a digital twin of the drying chamber, and a mechanism for automatic generation and labeling of data for subsequent machine learning using expert qualitative descriptions. The digital twin serves as a scenario generator (risk of mold, surface cracking, internal stresses), which helps overcome the shortage of available data on the causes of defects. A “human-in-the-loop” framework is implemented, where the operator acts as an expert, correcting and enriching the cognitive knowledge base. This approach improves the accuracy of diagnosing potential problems by combining objective environmental monitoring data with subjective observations from a specialist with many years of professional experience.

   Results. The results of numerical modeling confirm the correctness of reproducing the dynamics of the drying process and justify the feasibility of using the digital twin as a generator of synthetic data. The adequacy of the model is validated through the application of the oscillating drying method.

   Conclusion. The proposed idea forms a conceptual foundation for developing adaptive systems, enabling the overcoming of the problem of scarce labeled datasets without the need for lengthy full-scale experiments that deliberately induce defects.