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Journal impact factors were devised to qualify and compare university library holdings but are frequently repurposed for use in ranking applications, research papers, and even individual applicants in mycology and beyond. The widely held assumption that mycological studies published in journals with high impact factors add more to systematic mycology than studies published in journals without high impact factors nevertheless lacks evidential underpinning. The present study uses the species hypothesis system of the UNITE database for molecular identification of fungi and other eukaryotes to trace the publication history and impact factor of sequences uncovering new fungal species hypotheses. The data show that journal impact factors are poor predictors of discovery potential in systematic mycology. There is no clear relationship between journal impact factor and the discovery of new species hypotheses for the years 2000–2021. On the contrary, we found journals with low, and even no, impact factor to account for substantial parts of the species hypothesis landscape, often discovering new fungal taxa that are only later picked up by journals with high impact factors. Funding agencies and hiring committees that insist on upholding journal impact factors as a central funding and recruitment criterion in systematic mycology should consider using indicators such as research quality, productivity, outreach activities, review services for scientific journals, and teaching ability directly rather than using publication in high impact factor journals as a proxy for these indicators.

The purpose of the study is to develop an approach for identifying and processing invalid events in critical information infrastructure (CII) based on the concepts of taxonomy and categorization. The approach aims to improve the efficiency of identifying, classifying, and managing information security (IS) incidents. The article addresses the current tasks of ensuring the required level of CII protection and minimizing the negative consequences of information security incidents resulting from invalid events. The identification of these events is associated with the complexity of detecting such events, the need to process large volumes of data, insufficient speed in detecting IS events, as well as technological limitations.The relevance of identifying and classifying invalid events in information security, especially for CII, is driven by the need for timely detection and response to incidents that could lead to negative consequences. Understanding the nature and characteristics of such events allows for effective system protection and prevention of significant damage. To enhance the effectiveness of ensuring security, it is necessary to identify the class of invalid events among the numerous information security events by considering the characteristics that define invalid events.The novelty of the proposed approach lies in solving the task of identifying the class of invalid information security events based on taxonomy methods, involving the use of event categorization tools with the attributes of invalid events.Materials and methods. The approach to identifying invalid events in CII, based on the principles of information security event taxonomy, was used to solve the task. It was shown that identifying invalid information security events is directly related to solving the problem of searching for and analyzing their attributes, which represent the characteristics or parameters used to describe and classify security incidents. Based on the key principles of taxonomy, a model of the structure of the set of invalid events was developed to determine the characteristics that can be the basis for classifying invalid events. The process of identifying invalid information security events includes a sequence of stages: taxonomy, categorization, and classification, with appropriate methods and tools implemented at each stage.Results. Approaches to identifying invalid events in CII have been analyzed. Problems related to large data volumes, the complexity of event processing, the considerable time required for their detection, and technological limitations were considered. It was shown that the concept of taxonomy and categorization allows for effective identification and classification of information security incidents, ensuring efficient processing and response. The feasibility of applying taxonomy for describing and identifying the attributes of invalid events was justified, contributing to the development of effective protection strategies and improving security levels. A generalized scheme for processing invalid events was proposed, including a set of interconnected stages of identification, categorization, impact assessment, response, documentation, and analysis. An algorithm for structured description and classification of incidents was developed, allowing for more accurate and timely responses to information security threats.Conclusion. The results obtained increase the effectiveness of solving the task of classifying information security incidents by identifying invalid events, which reduces the level of negative consequences of incidents and enhances the security of CII objects.

Arbuscular mycorrhizal (AM) fungi - Glomeromycota and Endogonomycetes - comprise multiple species and higher-level taxa that have remained undescribed. We propose a mixed morphology- and DNA-based classification framework to promote taxonomic communication and shed light into the phylogenetic structure of these ecologically essential fungi. Based on eDNA samples and long reads as type materials, we describe 15 new species and corresponding genera (Pseudoentrophospora kesseensis, Hoforsa rebekkae, Kahvena rebeccae, Kelottijaervia shannonae, Kungsaengena shadiae, Langduoa dianae, Lehetua indrekii, Lokruma stenii, Moostea stephanieae, Nikkaluokta mahdiehiae, Parnigua craigii, Riederberga sylviae, Ruua coralieae, Tammsaarea vivikae and Unemaeea nathalieae), the genus Parvocarpum as well as 19 families (Pseudoentrophosporaceae, Hoforsaceae, Kahvenaceae, Kelottijaerviaceae, Kungsaengenaceae, Langduoaceae, Lehetuaceae, Lokrumaceae, Moosteaceae, Nikkaluoktaceae, Parniguaceae, Riederbergaceae, Ruuaceae, Tammsaareaceae, Unemaeeaceae, Bifigurataceae, Planticonsortiaceae, Jimgerdemanniaceae and Vinositunicaceae) and 17 orders (Hoforsales, Kahvenales, Kelottijaerviales, Kungsaengenales, Langduoales, Lehetuales, Lokrumales, Moosteales, Nikkaluoktales, Parniguales, Riederbergales, Ruuales, Tammsaareales, Unemaeeales, Bifiguratales and Densosporales), and propose six combinations (Diversispora bareae, Diversispora nevadensis, Fuscutata cerradensis, Fuscutata reticulata, Viscospora deserticola and Parvocarpum badium) based on phylogenetic evidence. We highlight further knowledge gaps in the phylogenetic structure of AM fungi and propose an alphanumeric coding system for preliminary communication and reference-based eDNA quality-filtering of the remaining undescribed genus- and family-level groups. Using AM fungi as examples, we hope to offer a sound, mixed framework for classification to boost research in the alpha taxonomy of fungi, especially the “dark matter fungi”.

Phylogenetic diversity (PD) represents a fundamental measure of biodiversity, encapsulating the extent of evolutionary history within species groups. This measure, pivotal for understanding biodiversity's full dimension, has gained recognition by major environmental and scientific organisations, including the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services. Unlike traditional taxonomic richness, PD offers a comprehensive, evolutionary perspective on biodiversity, essential for conservation planning and biodiversity management. This manuscript describes the development of a BioDT (Biodiversity Digital Twin) prototype, aimed at facilitating the calculation and visualisation of biodiversity metrics from global, dynamic data sources. By utilising the PhyloNext pipeline and integrating with global phylogenetic and species occurrence databases like the Open Tree of Life (OToL) and the Global Biodiversity Information Facility (GBIF), the prototype aims to significantly reduce computation time and enhance user interaction. This enables dynamic visualisation and potentially hypothesis testing, making it a valuable tool for researchers, monitoring initiatives, policy-makers and the public. The prototype's development focuses on improving the PhyloNext pipeline's scalability and creating a more intuitive user interface, expanding its utility for conservation efforts and biodiversity exploration. Our work illustrates the potential impact of the BioDT prototype in supporting diverse user groups in visualising and exploring PD, thus contributing to more informed decision-making in conservation and biodiversity management.

Antibiotic resistance crisis dictates the need for resistance monitoring and the search for new antibiotics. The development of monitoring protocols is hindered by the great diversity of resistance factors, while the “streetlight effect” denies the possibility of discovering novel drugs based on existing databases. In this study, we address these challenges using high-throughput environmental screening viewed from a trait-based ecological perspective. Through an in-depth analysis of the metagenomes of 658 topsoil samples spanning Europe, we explored the distribution of 241 prokaryotic and fungal genes responsible for producing metabolites with antibiotic properties and 485 antibiotic resistance genes. We analyzed the diversity of these gene collections at different levels and modeled the distribution of each gene across environmental gradients. Our analyses revealed several nonparallel distribution patterns of the genes encoding sequential steps of enzymatic pathways synthesizing large antibiotic groups, pointing to gaps in existing databases and suggesting potential for discovering new analogues of known antibiotics. We show that agricultural activity caused a continental-scale homogenization of microbial antibiotic-related machinery, emphasizing the importance of maintaining indigenous ecosystems within the landscape mosaic. Based on the relationships between the proportion of the genes in the metagenomes with the main predictors (soil pH, land cover type, climate temperature and humidity), we illustrate how the properties of chemical structures dictate the distribution of the genes responsible for their synthesis across environments. With this understanding, we propose general principles to facilitate the discovery of antibiotics, including principally new ones, establish abundance baselines for antibiotic resistance genes, and predict their dissemination.

Abstract The effects of generating pulsed radiation by a long spark discharge are important for the development of lightning models and applications related to lightning protection. In experiments with a Marx generator simulating a lightning discharge, we detected the radiation in the form of a single ultrawideband electromagnetic pulse (UWB EMP) about 200 ps in duration, and rising time about 100 ps. UWB EMP generation occurs during the breakdown of a “rod–rod” 4 m long gap. Pulses of almost unipolar shape are observed in more than half of all positive discharges. EMP emission occurs before the main stage, and corresponds to the start of the upward leader from a grounded electrode. In negative discharges, pulses are also observed, but less frequently and with a smaller amplitude. The UWB EMPs, given their large amplitude (more than 100 V/m at a distance of 90 m from the discharge), can be considered as possible new lightning damage factors.

The subject of the study is the disproportion in the number of men and women at young ages in the regions of Russia. The aim of the study is to assess the impact of interregional and international migration on the formation of gender imbalances in the regions of Russia. As a hypothesis, it was assumed that the results of the analysis of migration statistics would coincide with the results presented in the 2020 census. The available statistical series of the inter-census period 2017-2019 were used for the study. The indicator of accumulated migration gender imbalance by the age of 29 was developed and applied and correlated with the population aged 25-29 years, maps were built based on the results obtained. It is noted that in most regions of Russia there is an emigration of women starting in very early childhood. Young women are actively moving out of poor regions, from regions with a low level of social development, mainly to metropolitan agglomerations of St. Petersburg and Moscow, Moving to agglomerations with expensive housing entails postponing marriage, a drop in the birth rate, regions lose their reproductive potential. At the same time, there is a labor immigration of young men, mainly from the republics of Tajikistan and Kyrgyzstan, which, combined with the outflow of girls, creates a numerical male preponderance at young ages, especially in the resource-raw regions of the Far East and Siberia, in the coastal Kaluga region, in the Republic of Mordovia, which is confirmed by the 2020 census data. At the age of 25-29, there are departures of men from southern regions to more northern ones for forced work with separation from families, which negatively affects family life and demographic development. Income equalization is necessary to eliminate gender imbalances, correct negative demographic trends, increase fertility, and strengthen family ties. Financial resources, including resource and raw material rents, and bank capital should be used to raise wages, to recreate traditional industries in the southern regions and countries; and to create a high level of social infrastructure comfortable for families with children in the regions of the North. The results of the study can be applied in regional and international politics to develop government decisions involving large businesses to invest in countries and regions. The conduct of future gender studies by country and region will be closely linked to the quality and availability of statistical material on this topic.

Various trends are transforming the organizational, consumer and methodological landscape of enterprises whose activities relate to the fashion industry. The relevance of the chosen research topic is due to changes in the strategies currently used in this area, which is associated with the current geopolitical situation, as well as with the dominance of the trend of humanity (empathy) in strategic branding. The purpose of the study was to identify the features of promoting fashion brands on the Russian market in the absence of foreign competitors using the example of the LIME clothing brand, which is among the most popular (over 100 stores in Russia and the CIS countries). The methods of analysis and synthesis, abstraction, generalization, comparison, and questionnaire survey were used in the course of the work. The authors concluded that the effectiveness of brand development depends both on the right strategic decisions and on understanding the characteristics of the target audience, real-time communications with customers and prompt response to their requests through the use of high-tech strategic planning tools, in particular, personalized value propositions. Based on the research, recommendations have been developed for the promotion of Russian fashion brands in modern conditions, which can find practical application.

Russian firms are facing sanctions imposed by foreign countries. These restrictions forced the corporations to suddenly refuse the distribution of profits or shift the timing of dividend payments. This unusual practice created the need for appropriate regulatory parameters for the net profit distribution mechanism to shareholders. These circumstances reflect significant gaps in the legal regime of dividends, as well as the lack of a unified doctrinal position on best practices in this area. This paper fills the gaps in the legal regulation of dividend policy, complicated by corporate specificity. Hence, this study aims to identify, analyze, and comprehensively investigate the areas of uncertainty in the regulatory mechanism that describes the adoption and implementation of dividend distribution policy for LLC and JSC, while testing the consistency of legal analogy as a strong protective tool in the corporate field. The methodology of this study was based on executing general logical techniques of analysis and synthesis of the order and terms of dividend payment, as well as determining the ways of casual overcoming these gaps using legal analogy. The results reflected that overcoming uncertainty in the legal regime of dividends of LLC and JSC promptly seems possible through active use of the analogy of law. This will make it possible not only to counteract the unfair, unreasonable, and unfair practice of freezing net profit but also to increase the lack of freedom to determine the frequency of announcements and ensure the mechanism flexibility for establishing the timing of actual dividend payments.

Fungal metabarcoding of substrates such as soil, wood, and water is uncovering an unprecedented number of fungal species that do not seem to produce tangible morphological structures and that defy our best attempts at cultivation, thus falling outside the scope of the International Code of Nomenclature for algae, fungi, and plants. The present study uses the new, ninth release of the species hypotheses of the UNITE database to show that species discovery through environmental sequencing vastly outpaces traditional, Sanger sequencing-based efforts in a strongly increasing trend over the last five years. Our findings challenge the present stance of some in the mycological community – that the current situation is satisfactory and that no change is needed to “the code” – and suggest that we should be discussing not whether to allow DNA-based descriptions (typifications) of species and by extension higher ranks of fungi, but what the precise requirements for such DNA-based typifications should be. We submit a tentative list of such criteria for further discussion. The present authors hope for a revitalized and deepened discussion on DNA-based typification, because to us it seems harmful and counter-productive to intentionally deny the overwhelming majority of extant fungi a formal standing under the International Code of Nomenclature for algae, fungi, and plants.

The purpose of the study. The article discusses the research and further development of modern cyber-physical systems of the Internet of Things (CPS IoT). Researchers in the field of psychology, logic, lin- guistics, philosophy, for the study of artificial intelligence, used many different models of this phenomenon of “man”. Currently, the search for new approaches continues. One of the interesting approaches lies in the development of the application of cognitive mechanisms that a person uses in solving everyday tasks. The application of methods of gestalt processing of states of the CPS IoT worldview is considered to solve an ever-expanding range of tasks. Hybrid or, as they are also called, combined models can be used for gestalt processing to solve various tasks of cyber-physical systems of the Internet of Things related to forecasting indexes of the functioning of socio-economic systems. To do this, you can use a long-known approach to hybrid- ization, the essence of which is to split the entire set of initial data into subsets of initial data. The main stages of gestalt processing and one of the initial stages – the formation of a need are shown. The significant moments of the organization of interaction of CPS IoT modules with the environment are presented. In the demo example, the CPS IoT of the estate museum is considered. The main elements of the formation of the need for CPS IoT in organizing and conducting excursions are described.Materials and methods of research. To solve problems within the framework of gestalt processing of CPS IoT, new methods and developments of specialists in the field of intelligent systems are re- quired. Hybrid, combined models can be used for gestalt processing for various tasks of cyber-physical systems of the Internet of Things related to forecasting indexes of the functioning of socio-economic systems. You can use a long-known approach to hybridization, the essence of which is to split the entire set of initial data into subsets of initial data. It is possible to use gestalt processing within the framework of a holistic approach when splitting into subsets of the initial data - clusters. The cognitive approach uses sensory images, concept-representations, concept-scenarios and gestalts. The CPS IoT gestalt can be considered as one of the approaches to solving modern problems within the framework of Industry 4.0 technology. The article describes intelligent cyber-physical systems using methods of gestalt processing of their states - a picture of the world. Approaches to the use of needs and one of the many approaches to the formation of the needs of cyber-physical systems of the Internet of Things are considered.Results. Within the framework of the cognitive approach, con- cepts-representations of CPS IoT for arising (emerging) needs and their fixation are proposed. After fixing the need, as the main stages of its formation, the following are highlighted: concretization of the event, collection of relevant initial data for the need; formation (folding of perceived information) of the gestalt: checking the state of the necessary elements, searching for resources in the environment; organization of contact with the environment. These stages of the formation of the need relate to CPS IoT of any nature and are fo- cused on any tasks of the Internet of Things. It is advisable to save scenarios for the formation of needs for possible reuse in the future. The demo example shows an example of the formation of a need for CPS IoT during an excursion.Conclusion. The article considers a cognitive approach related to the use and development of intelligent cyber-physical systems for the Internet of Things and the Internet of everything. The main stages of the formation of the need for CPS IoT are considered. The implementation of the proposed approach, the development and use of gestalt concepts will allow reflecting CPS IoT with new emergent properties.

Purpose of the study. The aim of the study is to improve the methodological apparatus of cognitive modeling of socio-economic systems (SES) and predicting the indicators of their functioning and development, which ensures an increase in the accuracy and reliability of the results obtained. Existing models and methods do not fully provide the necessary accuracy and reliability of models that requires the development of the mathematical apparatus of cognitive modeling in terms of improving the quality of the developed cognitive models.Materials and methods. To achieve this goal, methods of an integrated approach to solving the problem, decomposing it into interrelated stages, describing the content of each stage in their relationship and presenting a generalized version of the methodology, taking into account the characteristics of the object of study, were used. The developed approach provides creating a more accurate and reliable cognitive model. The effectiveness of the developed methodological apparatus is shown.Results. A detailed analysis of the existing criteria and approaches to solving the problem of verification of cognitive models was carried out, which showed the absence of a unified methodology and an integrated approach in solving problems of cognitive modeling of SES based on cognitive maps. A set of techniques that implement the stages of cognitive modeling has been developed. The results of a comparative analysis of the developed approach with the existing ones are presented.Conclusion. A comprehensive solution to the problem of creating a cognitive model for analyzing and predicting the activities of a university is proposed, which includes a set of stages: the stage of creating the problem field of the situation; identification of factors and relationships between them; the stage of making a cognitive map and its verification, as well as the stage of analyzing the system characteristics of the cognitive model, validating the cognitive model. The developed methodological apparatus includes a set of techniques aimed at obtaining an adequate model that provides more accurate and reliable results of modeling the object of study.

To help solve the actual problem of global climate warming, it is important to comprehensively study soil organic carbon (SOC), soil fungi, and other parameters at different depths in the soil. This study was aimed at investigating the chemical and microbiological parameters and their interactions at various soil depths (0–5 to 195–200 cm) in an Arenosol in a Scots pine stand in southwestern Lithuania, with a focus on the main groups of fungi and their influence on SOC. The highest diversity of soil fungi species was found at a depth of 50–55 cm. Saprotrophs were dominant at all investigated soil depths. Ectomycorrhizal fungi were mostly abundant at depths of up to 50–55 cm. The C:N ratio gradually decreased down to 50–55 cm, then increased in deeper soil layers (from 50–55 to 195–200 cm). This means that the most active mineralization processes occur at depths of between 0 and 55 cm. Carbon stabilization processes occur at depths of 100–105 to 195–200 cm, and most of this carbon does not enter the atmosphere nor contribute to the process of climate change.

Purpose of the study. The purpose of the study is to develop a model for predicting university performance indicators based on a cognitive approach, which is based on the construction of a cognitive map that reflects the influence of a set of latent factors on the basic indicators and provides a solution to the problem of scenario forecasting. The degree of achievement of the required values of the basic indicators that determine the ranking of the university depends on the magnitude of the increment of the identified latent factors. The developed model makes it possible to choose the most preferable variant of scenario forecasting under the existing restrictions on the resources allocated for the increment of latent factors.Materials and methods. To achieve this goal, cognitive modeling methods based on gray fuzzy cognitive maps (FCM) were used in combination with methods of interval mathematics and causal algebra. The application of the considered approach made it possible to reduce the uncertainty of expert estimates of the strength of the relationship between the concepts of the cognitive map due to the use of special constructions in the form of interval estimates rather than point estimates when describing the relationships between the concepts, which ensured an increase in the reliability of the modeling results. The developed model is created based on an ensemble of gray FCMs, which, in turn, made it possible to increase the accuracy and reliability of the predictive model. The proposed approach to solving the problem of predicting the activities of the university made it possible to develop an adequate cognitive model.Results. The developed cognitive model of the university’s activities made it possible to analyze the dynamics of changes in factors and their influence on basic indicators, as well as the dynamics of the development of the system of indicators. The calculation made it possible to choose the most cost-effective scenario for incrementing the values of latent factors to obtain the required value of the university ranking in the framework of the QS international institutional ranking of universities. A comparative analysis of the results of scenario forecasting based on conventional FCM, gray FCM, and an ensemble of gray FCM was carried out, which showed the advantage of the proposed approach.Conclusion. During the study, a fuzzy cognitive model was developed for scenario forecasting of measures to achieve the required values of university performance targets in the QS international institutional ranking based on an ensemble of gray FCMs. The developed model provides, under the given constraints, obtaining the most acceptable scenario for planning the increment of basic indicators to target values by identifying the latent factors influencing them and calculating the required values of impulse effects on latent factors.

Purpose of the study. The aim of the study is to create and develop modern cyber physical systems. The evolution of cyber physical systems (CPS) is associated with the development of a cognitive approach within the framework of the application of mechanisms used by humans to solve their daily tasks. In the cognitive approach to working with cyber physical systems, gestalt is considered as one of the ways of solving modern tasks within the framework of the new Industry 4.0 technology. In the cognitive approach a simple task is considered for cyber physical systems of the Internet of Things (CPS IoT) with gestalt processing. When investigating such a task for a simple cyber physical system, it will be possible to use a gestalt with a simple structure. The complication of the task and structure of gestalt can occur with the development of CPS IoT. The article examines an intelligent cyber physical system of the Internet of Things using methods of gestalt processing of their states - a picture of the world, while solving various problems of the Internet of Things.Materials and research methods. To solve tasks within the framework of a cognitive approach to the construction and development of cyber physical systems, new methods and developments of specialists in the field of intelligent systems are required. In the context of Industry 4.0 technologies, the Internet of Things the gestalt processing of CPS IoT is considered. Within the framework of the cognitive approach sensory images, concept-representations, concept-scenarios, concept-gestalts of cyber physical systems are used to interact with the real world. It is important to use concept gestalts that can reflect CPS IoT with new emergent properties. CPS IoT gestalt refers to a certain state of the cyber physical system and its habitat, which occurs when a need arises and closes after the need is satisfied. The main task of gestalt processing for a cyber physical system is to satisfy its needs. The solution to this problem includes: the organization of the collection and the direct collection of the necessary elements for the formation of the gestalt, and later for its closure; the formation of the gestalt; the closure of the gestalt. For the accumulation of experience, its use and development, it is proposed to use machine learning methods. Machine learning results can be presented in the form of concept representations, concept scenarios.Results. The concepts-gestalts of CPS IoT, gestalt processing of CPS IoT are proposed within the framework of the cognitive approach. As the main stages of gestalt processing, the article highlights: - preparation of initial data for the formation of the need for CPS IoT: - formation of an imaginative perception - a picture of the world, including the current state of CPS IoT and necessary for the closure of the gestalt; - formation of gestalt; – formation of initial data for planning the control actions necessary for closing the CPS IoT gestalt; - implementation of control actions to close the CPS IoT gestalt; - saving the gestalt processing scenario for possible reuse in the future. These stages of gestalt processing relate to IoT CPS of any nature and are focused on any tasks of the Internet of Things. The demo example shows the use of gestalt processing for CPS IoT with a simple model without training.Conclusion. The article discusses the cognitive approach that refers to the use and development of intelligent cyber physical systems for the Internet of things and the Internet of everything. A method related to the gestalt processing of CPS IoT situations is proposed, which allows recognizing a need, and forming of a gestalt. Based on the generated CPS IoT gestalt, control actions are planned to close the CPS IoT gestalt. The implementation of the proposed approach, development and use of gestalt concepts will allow to reflect CPS IoT with new emergent properties.

The purpose of the study is to improve the incident management process. The article considers the process approach to incident management in case of technical failures and its main stages: detection, response, investigation, elimination, resolution. At the stages of response and investigation of the incident, as well as its elimination, there is an urgent problem, which is the violation of the deadlines adopted in the Service Level Agreement (SLA).A comparative analysis of the indicators before and after the application of the proposed use case approach is carried out. The proposed algorithm, applying the base of use cases, allows reducing the number of incidents that are returned for revision, as well as reduce the number of incidents, the resolution period of which exceeds the limits accepted according to the SLA.The scientific novelty lies in the use of the case analysis device for incident processing in the technical support service.Materials and methods. To solve the above problem related to the violation of the deadlines for processing incidents accepted in the SLA, the article considers an approach to improving the incident management process based on the use case analysis of incidents. The use of the case analysis device is a cycle of reasoning based on use cases. By the value of the degree of similarity to the incident, a specific use case and the associated decision-making scenario are selected. The method of plausible reasoning allows us to solve the problem of multiple escalations as an integrated automation tool and, as a result, reduce the number of violations of the deadlines for resolving incidents. This approach allows you to increase the efficiency of finding similar scenarios for responding to incidents. The nearest neighbor method is used to compare and extract use cases. This method does not require large computational costs and provides the required degree of reliability (error) of the decision. The application of the nearest neighbor method is based on calculating the degree of proximity of the current situation to the use cases stored in the base of use cases.Results. The proposed approach allowed us to develop a new algorithm for classifying incidents in the information system based on the use case and statistical analysis, which reduces the response time and eliminates incidents. The analysis of statistical data is carried out; the efficiency is estimated as a result of the application of the algorithm based on the use case analysis. The assessment showed a significant reduction in unnecessary escalations of incidents to the second support line, so the application of the base of use cases in resolving incidents allowed for improving the incident management process.Conclusion. In the course of the study, the main problem in the incident management process was identified - violation of the deadlines adopted in the SLA. The basic incident management algorithm is analyzed. The application of the method of plausible reasoning and the nearest neighbor method is justified. The cycle of updating the base of use cases and the conceptual model of the incident management process are considered. Within the framework of the developed conceptual model, the base of use cases includes decisions made by experts, which use the knowledge of previous experience to get out of a particular situation. An algorithm for finding a solution in the base of use cases is implemented. A distinctive feature of the developed algorithm is the application of a use case recognition algorithm and the search for similar images contained in the base of use cases using the nearest neighbor method.