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Ультраструктура поверхні листків Ginkgo biloba L. в умовах спеки (на прикладі м. Києва)
No full textObjective — to investigate the anatomical and morphological structure of Ginkgo biloba leaves in the heat conditions of Kyiv.
Material and methods. The study was carried out on the territory of Academician O.V. Fomin Botanical Garden and M.M. Gryshko National Botanical Garden of the NAS of Ukraine. It was used light and scanning electron microscopy.
Results. The investigated plants in O.V. Fomin Botanical Garden have hipostomatic leaves. Adaxial epidermis is formed by polygonal cells. The epidermal tissue cells are large (773.3 cells per 1 mm2). External periclinal walls are curved. The boundaries between the cells are obscure. The surface relief is colycular. Epicuticular wax is present (represented by piddling wax sticks). Abaxial epidermis is formed by epidermal cells and stoma complex. Epidermal cells are polygonal or isodiametral. External periclinal walls of epidermal cells are curved and have papillas formed by external periclinal walls. Epicuticular wax is well-developed, represented by wax sticks. Stomata are not oriented by their stomatal slits along leaf vein and are located between main fascicles, under the level of main epidermal cells. Number of stomata is low (168.6 per 1 mm2).
In M.M. Gryshko National Botanical Garden G. biloba trees are characterized by similar micromorphological structure of leaf plates and almost identical to plants from O.V. Fomin Botanical Garden by their epidermal tissue structure. Differences are related to quantitative indicators (plants from M.M. Gryshko National Botanical Garden have more developed epicuticullar wax on both of epidermises, number of stomata per 1 mm2 — 165.3).
Conclusion. Taking into account the existing global climate change in the direction of aridization Gingko biloba is promising for use in park landscaping
Conflict controlled network modeling: evolutionary games approach
No full textPrombles in programming 2014; 4: 67-7
Technological solutions for intelligent analysis of Big Data. Programming languages
No full textWe consider the problems arising during in the process of application of data analysis methods to Big Data. Modern programming languages are analyzed from the point of view of efficiency of their application for development of machine learning (ML) tools focused on Big Data.We analyzed the main types of machine learning tasks associated with information acqusition from Big Data that can be useful for practical use. This analysis shows that these tasks are solved by methods of statistical processing and training of neural networks. Therefore, it is advisable to have appropriate libraries in software tools aimed at solving these problems.Availability of the large number of ML algorithms that are focused on the different types of input information and different representations of result knowledge indicates the need for specialized libraries of machine learning implemented these algorithms. Another important factor in choosing a tool environment where ML tasks are solved for Big Data is processing speed: this requirement is caused by the large volumes of data to be compiled.External services for ML and Big Data processing , proposed by Google, Amazon, etc., greatly simplify the process of developing of intelligent data analysis tools for those programming languages that support the use of such services.Thus, for creation of experimental prototypes that combine modern approaches to machine learning with elements of artificial intelligence (AI) the most suitable programming language is Python. This conclusion is also confirmed by the world's results of surveys of developers in the field of Data Sciences. But other programming languages analyzed in this paper can become more useful under certain additional conditions: for example, C++ for projects oriented on specific software and hardware or Java and Scala for corporate applications.Problems in programming 2018; 4: 45-58
Big Data Analytics: principles, trends and tasks (a survey)
No full textWe review directions (avenues) of Big Data analysis and their practical meaning as well as problems and tasks in this field. Big Data Analytics appears a dominant trend in development of modern information technologies for management and planning in business. A few examples of real applications of Big Data are briefly outlined. Analysis of Big Data is aimed to extract useful sense from raw data collection. Big Data and Big Analytics have evolved as computer society’s response to the challenges raised by rapid grows in data volumes, variety, heterogeneity, velocity and veracity. Big Data Analytics may be seen as today’s phase of researches and developments known under names ‘Data Mining’, ‘Knowledge Discovery in Data’, ‘intelligent data analysis’ etc. We suggest that there exist three modes of large-scale usage of Big Data: 1) ‘intelligent information retrieval; 2) massive “intermediate” data processing (concentration, mining), which may be performed during one or two scanning; 3) model inference from data; 4) knowledge discovery in data. Stages in data analysis cycle are outlined. Because of Big Data are raw, distributed, unstructured, heterogeneous and disaggregated (vertically splitted), this data should be prepared for deep analysis. Data preparation may comprise such jobs as data retrieval, access, filtering, cleaning, aggregation, integration, dimensionality reduction, reformatting etc. There are several classes of typical data analysis problems (tasks), including: cases grouping (clustering), predictive model inference (regression, classification, recognition etc.), generative model inference, extracting structures and regularities from data. Distinction between model inference and knowledge discovery is elucidated. We give some suggestion why ‘deep learning’ (one of the most attractive topic by now) is so successive and popular. One of drawbacks of traditional models is they disability to make prediction under incomplete list of predictors (when some predictors are missed) or under augmented list of predictors. One may overcome this drawback using causal model. Causal networks are illuminated in the survey as attractive in that they appear to be expressive generative models and (simultaneously) predictive models in strict sense. This means they pretend to explain how the object at hand is acting (provided they are adequate). Being adequate, causal network facilitates predicting causal effect of local intervention on the object.Methods used in Big Data Analytics will be reviewed in the next paper.
An approach for problem area elaboration and usage of organization’s strategic decisions risks
No full textA Conceptual Model is proposed for Problem Area of Strategic Decisions’ Risks within Organizational Management Systems (OS) being a result of selection, addition and interpretation operations caused by the proper Risk Object specifics and applied to the elements of regular conceptual basis for risk treatment within the other domains. The Model includes such the Concepts: Decision, Consequences for both Decision and OS; Source, Factor, Aspect and Event of Risk, Vulnerability, Hazard, Affected Property and their interrelations. Based on the Model proposed for Strategic Decision life cycle and integration of well-known Strategic Management practices the System of Strategic Decisions Risks Management Measures is considered being represented as actions with hazards, threats, vulnerabilities, risk objects and consequences. The Usage of Conceptual Model proposed is demonstrated for the Method elaboration of knowledge ambiguity- caused Risks Assessment for the decisions of Expertise using different business groups and «Value Tree» model. The Method is based on the model, where the set of knowledge ambiguity-caused Risk Factors is formalized. The Factors’ Sources are the elements of expert problem statement. Factors‘ types are the types of non-coherent knowledge interrelations, Vulnerabilities relate to experts activity nature, Hazards are caused by the systems of expert estimates in use producing Risk Events during the process of decision life cycle. Each Risk Aspect is specialized with decision Properties being Risk targets due to Risk Events. The Method produces Risk estimates to conclude about expertise satisfactoriness and to enable selection the least risky form of its process organization.Enhancing and using of Conceptual Model proposed for Strategic Decisions Risks is advantageous for tools elaboration to support Defense Planning processes with the mechanisms of ontology based experience operation concerning with Problem Situations and Anti-crisis Measures.Problems in programming 2019; 4: 75-9
Use of thesauruses for search of complex information objects on Web on the basis of ontologies
No full textAn ontological model of interaction between objects and subjects of the Web semantic search is proposed, its basic elements are characterized, methods for its replenishment and use for filtering information that is pertinent to the personalized needs of users are considered. The types of relations between the instances and classes of this model and their characteristics that can have an influence on the time complexity of processing knowledge presented on the basis of this model, are analyzed. One of the important elements of the proposed model are thesauri that represent knowledge regarding tasks for which users are looking for information, and about information resources where such information can be contained. The expediency of using particular cases of ontology – thesauruses – to find semantically similar information objects is substantiated. The types of thesauruses that are used for semantic search are considered, methods for their replenishment and utilization are proposed, and their characteristics are analyzed. In this paper we proposes an algorithm for the automated construction of simple thesaurus, which is formed on the base of the domain ontology and a natural language description of the user’s problem, and methods for generating composite thesauri that are pertinent to new user tasks which are based on the set of simple thesauruses previously built by user. The expressiveness and computational complexity of the proposed methods which depend on the domain ontology characteristics and on the size of the problem description are estimated. Methods of use of the semantically marked Wiki resources as a source of knowledge for constructing ontologies of subject areas and associated typical information objects are considered.Problems in programming 2019; 4: 28-5
Еколого-біологічні показники представників роду Quercus L. у зелених насадженнях Кривого Рогу
No full textObjective – to study basic biometrical, ecological and biological characteristics of the genus Quercus L. representatives in green plantations of Kryvyi Rih and in the arboretum of Kryvyi Rih Botanical Garden of the NAS of Uk raine.
Material and methods. Modern state of the genus Quercus species in green plantations of Kryvyi Rih and the arboretum of Kryvyi Rih Botanical Garden of the NAS of Ukraine is studied. To study the age of trees, the diameter of trunk was measured at a height of 1.3 m and their whole height. The vital state of plants was assessed by L.S. Savelieva 8-point scale (1975), drought resistance – according to S.S. Pyatnitsky 6point scale (1961), frost resistance – according to I.A. Dobrovolsky 5-point scale (1961), the intensity of blossoming and fruiting – acording to A.G. Golo vach 6-point scale (1980).
Results. The most of introduced species of the genus Quercus in the collection of Kryvyi Rih Botanical Garden of the NAS of Ukraine reach the sizes corresponding to their age. The trees have a high viability score (VIIVIII). According to the results of the analysis in the park plantations of Kryvyi Rih city, Q. robur L. trees aged from 7 to 200 years were found. The 30–40 yearsaged trees are predominating, their height is 15–18 m, a trunk diameter – 25–40 cm. The vital state of the most of plants corresponded to VII and VIII scores, but there were oaks, the index of which did not exceed V and VI scores. Plants of the genus Quercus are well developed, regularly bloom and bear fruit and are practically unaffected by pests and diseases, except for the less stable species Q. robur.
Conclusions. The genus Quercus in parks and squares of Kryvyi Rih is represented by three species and one cultivar, in the collection of Kryvyi Rih Botanical Garden of the NAS of Ukraine – 10 species and one cultivar. They have a good vital state and high decorativeness. Perspective for regional culture by complex of ecological and biological properties are following species: Q. castaneifolia C.A. Mey., Q. imbricaria Stev., Q. macranthera Fisch. et Mey. which were held in Kryvyi Rih Botanical Garden of the NAS of Ukraine for many years introductory test
Оцінка морозо- та зимостійкості Calluna vulgaris (L.) Hull та його культиварів в умовах Правобережного Лісостепу України
No full textObjective – to investigate the frost resistance of Calluna vulgaris (L.) Hull and its cultivars by the method of direct laboratory freezing of annual shoots. Compare with field studies of winter hardiness of it in 2016–2017.
Material and methods. Objects of research are C. vulgaris and its 10 cultivars (Alicia, Mullion, Golden Carpet, Golden Wonder, Winter Red, Dirry, H.E. Beale, Red Star, Silver Knight, Bonita) from the collection of M.M. Gryshko National Botanical Garden of the NAS of Ukraine. The shoots were freezed in the laboratory of plant physiology of the Institute of horticulture of the NAAS of Ukraine in the refrigerating chamber "CRO/400/40". Field winter hardiness was assessed visually on 8point scale of S.Ya. Sokolov during 2016–2017.
Results. The potential frost resistance of C. vulgaris and its cultivars is determined using the laboratory method of direct freezing of shoots. The degree of damage to phloem (cortex), cambium, xylem (wood), cores in the apical, middle part of the shoot, in the section through the node, and bud tissues was determined using binocular microscope. It was revealed that common heather and its varieties are characterized by different degrees of frost resistance.
Conclusions. C. vulgaris and his cultivars are sufficiently frostresistant in conditions of Right-Bank of Forest Steppe of Ukraine. C. vulgaris plants are more resistant to low temperatures compared to cultivars. The most sensitive to the effect of frost are the bud and apical part of the shoot (up to 80.0 and 72.6 %, respectively). The least sensitive is the middle part of the shoot in the section through the internode. Plants of the cultivars H.E. Beale, Golden Wonder, Golden Carpet suffer the most from the effect of low temperatures. C. vulgaris, ‘Dirry’, ‘Winter Red’, ‘Alicia’ had less damage. More than 50 % of tissues of annual shoots are damaged at temperature –30 °C set in the laboratory conditions. According to a visual assessment of winter hardiness, the cultivars Silver Knight, Golden Wonder, Red Star, H.E. Beale suffer the most from winter conditions