Harvester open publications of NAS Ukraine
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Мікроморфологічні особливості поверхні листка видів роду Sansevieriа Thunb. s.str. (Asparagaceae)
No full textThis study investigated the leaf surface micromorphology of 12 species of the genus Sansevieria using light microscopy and scanning electron microscopy. The research focused on identifying micromorphological traits associated with plant stress tolerance, including epidermal cell shape, cuticle thickness, stomatal distribution and density, and cuticular characteristics with epicuticular wax deposits. In most of the studied Sansevieria species, the leaves are amphistomatic, whereas hypostomatic leaves are observed in S. cylindrica, S. canaliculata, and S. suffruticosa. In all studied taxa, the epidermis consists of a single layer of cells and lacks trichomes.The examined Sansevieria species are characterized by a well-developed cuticular layer and the presence of wax deposits that perform protective and water-conserving functions. The thickness of the cuticle and its ornamentation vary both among species and between leaf surfaces within the same species. The abaxial leaf surface generally exhibits a more developed cuticle than the adaxial surface, a feature particularly pronounced in S. cylindrica, S. canaliculata, S. kirkii, S. roxburghiana, S. gracilis, S. suffruticosa, and S. intermedia. All investigated species possess anomocytic stomata. Stomatal density on the abaxial leaf surface ranged from 9 to 27 mm2 among the studied species. These interspecific variations reflect distinct strategies for optimizing water balance under arid conditions.At the level of leaf micromorphology, amphistomaty, the spatial organization of epidermal cells, the presence of a cuticular layer with epicuticular wax deposits of various configurations, differences in stomatal sunkenness and density, and the occurrence of underdeveloped stomata can be considered markers of stress tolerance in this genus. The identified micromorphological markers provide insight into the adaptive xeromorphic traits of Sansevieria and have potential applications in applied research, including biotechnological projects and phytoremediation, including green infrastructure development
Semantic approach to automated formation of information security systems documentation
No full textThe article investigates the problem of automated generation of complex documentation for information secu rity systems based on semantic analysis of the regulatory and legal framework. A systematic analysis of the re quirements of regulatory documents and international standards for information security system documentation is conducted. Critical contradictions between the dynamic nature of regulatory requirements and the static na ture of existing automation tools are identified. It is shown that manual processing of large volumes of weakly structured documents does not ensure acceptable quality and speed, while the use of generative artificial intel ligence models does not guarantee the reliability of the generated information. The necessity of integrating se mantic analysis tools with generative artificial intelligence to ensure guaranteed and explainable results is sub stantiated. Existing approaches to document generation automation are analyzed, including template-based sys tems, markup tools, ontological models, and large language models. A conceptual model of an intelligent in formation security authorization support system is proposed, combining a multi-agent architecture, ontological knowledge representation, and the capabilities of large language models. A semantic approach to the genera tion of complex documents based on ontological modeling of the information security engineering domain is developed. The proposed model ensures traceability between requirements, solutions, and knowledge sources, supports dynamic updates of the regulatory framework, and enables automated generation of documentation in accordance with current security standards. The developed approach significantly reduces the time and labor required for preparing information security documentation.Prombles in programming 2025; 4: 78-8
Ontological modeling of adult learning ecosystem as a personalization tool
No full textThe article is devoted to the development of methods for semantic expansion of adult learners' profiles for per sonalization of education in the context of the digital transformation. We analyse metadata standards used for describing of learners and learning objects and define that these standards have insufficient flexibility for pro filing adults, especially in the andragogical context. We consider some practical situations that demonstrate the need for additional semantic properties of the profile (professional specialisation, educational mobility and multilingualism, the life circumstances of the learner, special needs for inclusive learning, informal education and micro-qualifications, learning under fire in a state of martial law, and psycho-emotional trauma) and de termine the additional semantic properties and the expected effect of their use. On this base an approach to flexible extension of standards based on ontological modelling of the adult learning ecosystem is proposed. This approach uses classification of additional semantic properties of the profile of an adult learner by groups: type of educational activity, learning context, motivation, professional goal, social role, psycho-emotional state, institution. An prototype system for intelligent support of postgraduate students based on Semantic MediaWiki and large language mdels is described. The system implements a generation architecture with advanced search, combining ontologically structured knowledge with the capabilities of generative text analysis. Testing of the approach at the Institute of Software Systems of the National Academy of Sciences of Ukraine confirmed the effectiveness of semantic profiling for building personalised educational trajectories and intelligent search for educational resources.Prombles in programming 2025; 4: 63-7
Соматичні мутації сортів інтродукованих садових троянд у колекції Національного ботанічного саду імені М.М. Гришка
No full textThe article analyzes the manifestations of somatic (bud) mutational variability of traits in garden roses (Rosa L.) under the conditions of the collection of the M.M. Gryshko National Botanical Garden of the National Academy of Sciences of Ukraine. The study is based on the results of long-term phenotypic observations of cultivars of different origin and garden groups. It was established that mutational variability in roses is not random but follows regular and largely predictable patterns determined by the genotype, origin, and breeding history of the initial cultivars. A relationship between the direction of mutational changes and the affinity of cultivars with particular garden groups was revealed: forms closer in origin to wild rose species more frequently produce mutants with enhanced expression of decorative traits, whereas cultivars of modern, evolutionarily advanced groups predominantly give rise to mutants with reduced expression of these traits. Both stable somatic mutants and cases of partial or complete reversion to the phenotype of the original cultivar were recorded. The practical significance of somatic mutations for cultivar assessment, cultivar identification, trait stability assessment, and mutation breeding in ornamental plants is substantiated
Implementation of the reconstruction process for constructive-synthesizing models of fractal time series
No full textThe presented method focuses on reconstructing constructive models for predefined fractal time series. This work generalizes the approach to implementing the software system that ensures effective automation while considering the specifics of working with model series of various natures– both deterministic and stochastic. Two main approaches to system implementation based on a genetic algorithm were analyzed: the monolithic and the multi-agent. Considering the complexity of calculating chromosome viability indicators when working with stochastic series, it was decided to separate certain elements of the genetic algorithm– specifically, crossover and mutation– from the selection stage by introducing subpopulations. This made it possible to perform distrib uted computation of chromosome fitness indicators. The introduced solution enabled independent scaling of various elements of the reconstruction process, which increased the overall efficiency of the system. To ensure consistent interaction between elements, different types of communication were considered, among which the asynchronous approach proved to be the most effective. Mechanisms were implemented to optimize interaction between computational entities, as well as a node pattern for implementing crossover and mutation operations. This approach made it possible to eliminate problems associated with processing stochastic time series and en sure controlled and efficient horizontal scaling of the process of reconstructing constructive models.Problems in programming 2025; 4: 3-1
Defining of cloud service priority for dynamic creating WAF rules
No full textThe article examines the process of determining the prioritization of cloud services and their coverage by network firewalls. The structure and key parameters of previously collected hybrid cloud configurations are analyzed. Particular attention is given to the specifics of cloud service deployment within hybrid clouds and their coverage by web application firewalls. Frequently, such firewalls are included among the standard ser vices offered by providers such as Cloudflare, allowing comprehensive protection of the entire hybrid cloud environment. The article also discusses different types of access to cloud services, which may provide either direct access or employ reverse proxying. In the latter case, secure connections are terminated, and both static and dy namic firewall rules are applied. This study focuses on descriptive data collected from previous research on hybrid clouds, particularly concerning cloud services and their interconnections. Within the context of this study, priority patterns are intended to be used for the dynamic generation of firewall rules. These priority patterns are necessary for dynamically creating either permissive or restrictive rules. This approach is espe cially relevant for automating firewall configuration using generative artificial intelligence tools. The article proposes two indicators for the development of firewall rule priority patterns: the availability priority and the firewall coverage priority. The availability priority determines the level of criticality in ensuring uninter rupted access to a specific cloud service, whereas the firewall coverage priority defines the degree of access restriction to that service. An expert survey was conducted as part of this research to evaluate the availabil ity and protection parameters of all cloud services collected in previous studies. The article proposes using these two metrics for creating priority patterns for the web application firewall.Problems in programming 2025; 4: 32-40
Adaptive ensemble decision integration for indicator of resource security: methodology and statistical validation of stability
No full textEnsuring effective decision support in complex distributed organizational systems (especially in national security and defense planning) requires reliable classification methods capable of rapid diagnosis of resource states and risks to strategic interests. The effectiveness of a resource security indicator (RSI) built on machine learning methods critically depends on the stability and reliability of integrated predictions under conditions typical of this domain: significant class imbalance (where missing a negative state is critical), limited data volume, log normal feature distribution with "long tails", and noise components that reduce the stability of individual classifiers. To address these challenges, an adaptive ensemble integration mechanism (RSI) was developed, implementing weighted soft voting of models (NB, SVM, RF, kNN, LR) with unified probability calibration. The central element is a composite dynamic quality metric (KQ), which combines 1 (prioritizing the minority class), , and , adapting their weights based on correlation. Trust coefficients (KDR) are integrated to adjust the influence of models depending on their vulnerability to data properties. Algorithm validation was performed on synthetic data simulating log-normal distribution and lag effects of real-world conditions. A large-scale experiment (250 runs, paired design) confirmed high statistical significance ( 0.001 by Wilcoxon test) of RSI superiority over the best single classifier (Random Forest) across all metrics (Δ, Δ1, Δ). The effect size (Cohen's ≥ 1.41) indicates large practical value. The results demonstrate that adaptive integration ensures stability and reliability of risk diagnosis, critically necessary for security applications.Problems in programming 2025; 4: 88-10
Methods for implementing quadrotors autonomy based on hybrid learning methods
No full textThis paper reviews and analyzes methods for achieving quadcopter autonomy. It shows disadvantages and lim itations of the classical "Perception-Planning-Control" pipeline. A fundamental limitation of this approach is the inability of mathematical models to take into account all complex effects of the unpredictable environment. In return, the application of machine learning algorithms enables the implementation of control agents based on experience of interactions with real or simulated environments, significantly improving system adaptability to non-standard conditions. The core of this work compares machine learning methods applied to quadcopter au tonomy task. It provides a detailed overview of reinforcement learning. It is shown that model-free algorithms are able to outperform professional human pilots in specific tasks. However, they require significant amounts of data and training time. In return, model-based reinforcement learning improves training efficiency. During the training, the agent learns a world model that can be used to predict environment dynamics. The article also explores imitation learning and derived methods. An effective approach is to sequentially apply imitation learn ing and reinforcement learning, which combines the strengths of both approaches. The paper reviews works relying on physics-informed methods using differentiable simulators. Differentiable simulators are used to cal culate loss function gradients relative to control parameters. All discussed methods are analyzed regarding data efficiency, computational resource requirements, and fundamental limitations. The analysis results can be used to select quadcopter control architectures based on available computational resources and specific task require ments.Problems in programming 2025; 4: 53-6
Oxalis purpurea L. (Oxalidaceae): морфоструктура цибулини, рекаулесценція
No full textThe morphostructure of Oxalis purpurea bulbs during the growing season, with an emphasis on the number and functional purpose of their scales, has been investigated. It was found that two protective membranous scales, two leathery scales, and three fleshy scales are constantly present in the investigated species. The first fleshy scale has a narrow hyaline edge. Additionally, the phenomenon of metatopy in a representative of the Oxalidaceae family and recaulescence in a bulbous plant are described for the first time
A simulator providing theoretical research of human integrative physiology
No full textTraditional (empiric) methodology based on direct measurements of fragmentary biological data limits the research of human integrative physiology (IP). Even assistant research based on animal experiments operates with fragmentary data. Therefore, IP’s current concepts, not covering many aspects of IP’s complex dynamics, cannot explain pathophysiological transformations that finally lead to non-trivial diseases. This methodological dead-end requires alternative research technology. This article presents a technology and software (SimHIP), widening the research potential in the area of human IP. The technology is based on two novelties. The first one is the physiological concept of a functional super-system (FSS) that optimizes cells' life despite environmental instabilities. The second novelty is the mathematical model (MM) of FSS. Fragments of MM were separately created and tuned using test scenarios. SimHIP integrating these fragments provides the physiologist-researcher with an intuitive interface to: a) construct a simulation scenario; b) execute the simulation; c) visualize input-output physiological dynamic dependencies for every chosen combination; and d) save every simulation data for future considerations and publications. SimHIP is an autonomous C# software provided as an Exe module for IBM-compatible computers. Medical students can be additional users of SimHIP.Problems in programming 2025; 4: 12-2