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Біолого-морфологічні особливості рослин роду Lophanthus Adanson при інтродукції в Кременецькому ботанічному саду
Get PDFObjective – to conduct a comprehensive study of the biological and morphological characteristics of plants of the genus Lophanthus Adanson depending on the feeding area under the conditions of the Kremenets Botanical Garden.
Material and methods. The research was carried out in the Kremenets Botanical Garden during 2016–2018. Studied the laws of the passage of growth processes and the development of plants of Lophanthus, depending on the plant nutrition area, it has been determined the soil similarity without preliminary preparation depending on the time of sowing. The material for research was plant specimens L. anisatus cv. Siniy veleten and cv. Leleka. Seeds of plants were obtained from the M.M. Gryshko National Botanical Garden of the NAS of Ukraine. The trial included four variants in three repetitions. Variants differed according to the arrangement of plants: 20 × 20, 35 × 35, 45 × 45, 70 × 70 cm. Such methods as field, laboratory and measurement-weighted have been used.
Results. The plants reproduce well by the seminal method, forming self-seedling. Not damaged by diseases and pests, drought and winter hardiness. The genotypes studied are commonly adapted to local conditions.
Conclusions. It has been established that the determining factor of the active growth of plants Lophanthus, the optimum area of nutrition, namely – 4900 cm2, which makes it possible to form a large overland mass and powerful root system. It was established that the soil similarity of the seed without preliminary preparation has a direct dependence on the sowing dates. The best seeds sprouts of L. anisatus were observed during sowing the I decade March (82 %), II decade April (80 %), and the highest were the average indices of similarity of seed sown in the III decade April (95 %)
First-order composition-nominative logics with predicates of weak equality and of strong equality
No full textDevelopment of the new software-oriented logical formalisms is a topical problem. The paper introduces logics of partial predicates with predicate complement and equality predicates, we denote them LCE. They extend logics of quasiary predicates with equality and logics with predicate complement. The composition of the predicate complement is used in Floyd-Hoare program logics’ extensions on the class of partial predicates. We define predicates of weak equality and of strong equality. Thus, LCE with predicates of weak equality (denoted by LCEw) and LCE with predicates of strong equality (denoted by LCEs) can be specified. LCE can be studied on the first order and renominative levels. We consider composition algebras of LCE, investigate properties of their compositions and describe first order languages of such logics. We concentrate on the properties related to the equality predicates and the composition of the predicate complement. Various variants of logical consequence relations for the first order LCE are introduced and studied: P|=T, P|=F, R|=T, R|=F, P|=TF, R|=TF, P|=IR. In particular, we obtained that LCEw are somewhat degenerate, as for them all the relations are incorrect except for the irrefutability logical consequence relation under the conditions of undefinedness |=IR^. At the same time, all of the listed relations are correct for LCEs. Properties of the logical consequence relations are the semantic basis for construction of the respective calculi of sequential type. Further investigation of logical consequence relations for LCE includes adding the conditions of undefinedness and constructing the corresponding sequent calculi; it is planned to be displayed in the forthcoming articles. Problems in programming 2019; 3: 28-44
Methods of recognition by the agent of the unknown environment
No full textThe methods used by the agent to recognize an unknown environment are outlined. They include: a method for determining the distance to the nearest visible object and the coordinates of the intersection with this object of the beam (as a simulated direction of the agent's view) directed from the agent; the method of dynamically changing the gradation of the beam angle directed by the agent into the environment; a method for constructing a set of points belonging to objects of the environment visible from the point of the current location of the agent; the method of agent's summarizing a set of points with the construction of semantic map fragments of unknown environment; methods of recognition of the corners of rooms in the environment.Problems in programming 2019; 1: 78-8
Tasks and methods of Big Data analysis (a survey)
No full textWe review tasks and methods most relevant to Big Data analysis. Emphasis is made on the conceptual and pragmatic issues of the tasks and methods (avoiding unnecessary mathematical details). We suggest that all scope of jobs with Big Data fall into four conceptual modes (types): four modes of large-scale usage of Big Data: 1) intelligent information retrieval; 2) massive (large-scale) conveyed data processing (mining); 3) model inference from data; 4) knowledge extraction from data (regularities detection and structures discovery). The essence of various tasks (clustering, regression, generative model inference, structures discovery etc.) are elucidated. We compare key methods of clustering, regression, classification, deep learning, generative model inference and causal discovery. Cluster analysis may be divided into methods based on mean distance, methods based on local distance and methods based on a model. The targeted (predictive) methods fall into two categories: methods which infer a model; "tied to data" methods which compute prediction directly from data. Common tasks of temporal data analysis are briefly overviewed. Among diverse methods of generative model inference we make focus on causal network learning because models of this class are very expressive, flexible and are able to predict effects of interventions under varying conditions. Independence-based approach to causal network inference from data is characterized. We give a few comments on specificity of task of dynamical causal network inference from timeseries. Challenges of Big Data analysis raised by data multidimensionality, heterogeneity and huge volume are presented. Some statistical issues related to the challenges are summarized.Problems in programming 2019; 3: 58-8
Application of machine learning in software engineering: an overview
No full textToday, software is one of the main technologies contributing to the development of society. Therefore, its quality is a major requirement for both the global software industry and software engineering, which deals with all aspects of improving the quality and reliability of software products at all stages of their life cycle. To solve software engineering problems, the use of artificial intelligence methods is becoming increasingly relevant. The article presents a brief description of machine learning methods such as artificial neural networks, support vector machine, decision trees, inductive logic programming and others. Also, examples of the application of these methods to solve some problems of forecasting and quality assessment in software engineering are presented, recommendations for applying machine learning algorithms to solving problems of software engineering are given. The review will be useful by researchers and practitioners as a starting point, because it identifies important and promising areas of research. This will ultimately lead to more effective solving of software engineering problems, providing better, more reliable and cost effective software products.Problems in programming 2019; 4: 92-11
Building automated monitoring systems structural elements method MDP-planning
No full textPrombles in programming 2014; 4: 94-9
Propositional logics of partial predicates with composition of predicate complement
No full textThe paper studies new software-oriented logical formalisms – the logics of partial predicates with predicate complement. Such logics are denoted LC. A characteristic feature of these logics is the presence of a special non-monotonic operation (composition) of the predicate complement. Such operations are used in various versions of the Floyd-Hoare logic with partial pre- and post-conditions. Properties of LC propositional compositions are similar to the properties of the traditional logical connectives. Properties of the new composition of the predicate complement are investigated. The class of P-predicates (partial single-valued) is closed under the composition of the predicate complement, but the class of T-predicates (total) is not closed. Therefore, it is possible to consider the general class LC – the logic of R-predicates (relational predicates) with the composition of the predicate complement, and its subclass LPC – the logic of P-predicates with such a composition. The focus of the work is the study of PLC – propositional LC. Propositional composition algebras and PLC languages are described. For LC of partial single-valued predicates, an irrefutability logical consequence relation |=IR^ is proposed and investigated under the conditions of undefinedness. The conditions for the validity of the |=IR^ and the properties of the decomposition of formulas are given. Based on the properties of the |=IR^, for PLC of P-predicates a calculus of sequential type is constructed. The basic sequential forms of this calculus and closure conditions of the sequents are given. For the constructed calculus, correctness and completeness theorems are hold. Proofs of these theorems will be given in the forthcoming articles.Problems in programming 2019; 1: 03-1