Harvester open publications of NAS Ukraine
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Improving performance of Python code using rewriting rules technique
No full textPython is a popular programming language used in many areas, but its performance is significantly lower than many compiled languages. We propose an approach to increasing performance of Python code by transforming fragments of code to more efficient languages such as Cython and C++. We use high-level algebraic models and rewriting rules technique for semi-automated code transformation. Performance-critical fragments of code are transformed into a low-level syntax model using Python parser. Then this low-level model is further transformed into a high-level algebraic model that is language-independent and easier to work with. The transformation is automated using rewriting rules implemented in Termware system. We also improve the constructed high-level model by deducing additional information such as data types and constraints. From this enhanced high-level model of code we generate equivalent fragments of code using code generators for Cython and C++ languages. Cython code is seamlessly integrated with Python code, and for C++ code we generate a small utility file in Cython that also integrates this code with Python. This way, the bulk of program code can stay in Python and benefit from its facilities, but performance-critical fragments of code are transformed into more efficient equivalents, improving the performance of resulting program. Comparison of execution times between initial version of Python code, different versions of transformed code and using automatic tools such as Cython compiler and PyPy demonstrates the benefits of our approach – we have achieved performance gains of over 50x compared to the initial version written in Python, and over 2x compared to the best automatic tool we have tested.Problems in programming 2020; 2-3: 115-125
Automated methods of coherence evaluation of Ukrainian texts using machine learning techniques
No full textThe main methods of coherence evaluation of texts with the usage of different machine learning techniques have been analyzed. The principles of methods with the usage of recurrent and convolutional neural networks have been described in details. The advantages of a semantic similarity graph method have been considered. Other approaches to perform the vector representation of sentences for the estimation of semantic similarity between the elements of a text have been suggested to use. The experimental examination of methods has been performed on the set of Ukrainian scientific articles. The training of recurrent and convolutional networks with the usage of early stopping has been performed. The accuracy of the solving of document discrimination and insertion tasks has been calculated. The comparative analysis of the results obtained has been performed.Problems in programming 2020; 2-3: 295-30
Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach
Get PDFWe design a new technique for the distributional semantic modeling with a neural network-based approach to learn distributed term representations (or term embeddings) – term vector space models as a result, inspired by the recent ontology-related approach (using different types of contextual knowledge such as syntactic knowledge, terminological knowledge, semantic knowledge, etc.) to the identification of terms (term extraction) and relations between them (relation extraction) called semantic pre-processing technology – SPT. Our method relies on automatic term extraction from the natural language texts and subsequent formation of the problem-oriented or application-oriented (also deeply annotated) text corpora where the fundamental entity is the term (includes non-compositional and compositional terms). This gives us an opportunity to changeover from distributed word representations (or word embeddings) to distributed term representations (or term embeddings). The main practical result of our work is the development kit (set of toolkits represented as web service APIs and web application), which provides all necessary routines for the basic linguistic pre-processing and the semantic pre-processing of the natural language texts in Ukrainian for future training of term vector space models.Problems in programming 2020; 2-3: 341-351
Порівняльний аналіз агрохімічних, алелопатичних та мікробіологічних особливостей ґрунтового середовища Actinidia arguta (Siebold et Zucc.) Planch. ex Miq. в Україні та двох провінціях Китаю
No full textThe objective of this study was to evaluate agrochemical, allelopathic and microbiological characteristics of the soil under Actinidia arguta plants cultivated in Ukraine and two provinces of China.
Material and methods. The rhizosphere soil was sampled at 0–15 cm layer under A. arguta plants in the stage of fruit ripening in Ukraine (Kyiv city: North of Ukraine, Forest-Steppe zone, a temperate continental climate) and two provinces of China (Shandong: East China, a temperate monsoon zone; and Heilongjiang: Northeast China, continental monsoon climate). The concentrations of carbon, available forms of macro- and micronutrients, phenolic compounds in the soil samples were determined. pH and redox potential of soil were measured. Soil phytotoxicity was studied by direct bioassay method on cress (Lepidium sativum) root growth. Microbiological analyses of soil samples were conducted.
Results. The dissimilarities in the concentrations of carbon, macro- and micronutrients in the examined soil samples were shown. The reduction conditions (Eh < 400 mV) in the soils under A. аrguta might slow down the humification processes. A similar effect may be caused by mobile forms of organic compounds with allelopathic properties. The redox potential decreased with the increase of pH values. This fact reflects the intensifying of reduction processes. The soil phytotoxicity under A. аrguta reached 20–70 % compared with the control, probably due to the accumulation of phenolic compounds, as well as iron and manganese. In soils under A. аrguta, the relationship between pH, phytotoxicity, and the abundance of main taxonomical and ecotrophic groups of microorganisms was evaluated.
Conclusions. Calcic Luvisols from the M.M. Gryshko National Botanical Garden of the NAS of Ukraine (Kyiv city, Ukraine) and Luvic Chernozems from Jiamusi (Heilongjiang province, China) were determined to be the most favorable for A. arguta cultivation. Salic Solonetz from Harbin (Heilongjiang province, China) and Haplic Luvisols from Linyi (Shandong province, China) had the least suitable soil conditions for A. arguta
Сучасна біотехнологія в оптимізації утилізації рослинних відходів
No full textThe study aimed to develop a modern, cheap, and environmentally safe technology for the disposal of plant waste, with the participation of the most active microorganisms-destructors.The microorganisms’ ability to help transform plant waste into viable, fertile soil was extensively studied. We selected strains of micromycetes Penicillium roseopurpureum, Trichoderma hamatum, T. koningii, Alternaria alternata, and bacteria of the genus Cytophaga, which are characterized by high growth rate and the absence of phytotoxicity. To accelerate microorganism development, we used silicon-containing mineral analcime, which contained immobilized spores of micromycetes and bacterial cells’ suspensions. Modified analcime was added to the waste in a ratio of 10 : 1. The plant remains prepared in this method were analyzed under conditions of both model and vegetation experiments.An evidence for the expediency of using the silicon-containing mineral analcime as a starting substrate for immobilization of spores and suspension of bacterial cells in the culture fluid was provided. The microorganisms involved in the experiment showed a positive result in transforming plant waste during the 30-day observation period. The highest destructive activity against apple and grape waste is characteristic for the T. hamatum strain, for beet waste – P. roseopurpureum. The species-specificity of these destructive microorganisms on plant growth processes was proved. The maximum growth of corn sprouts in apple waste was detected by inoculation with T. koningii spores, grape waste – T. hamatum, and beet waste – a mixture of micromycetes with a Cytophaga sp. suspension. The optimal duration of plant waste transformation using analcime, inoculated with microorganisms, is 20–30 days. In the indoor farming conditions, the standard for utilizing the modified vegetable waste placement was 10 % of the total volume of a substrate during the preparation of soil mixes.The environmental safety of plant waste after their destruction was confirmed. The presence of a silicon-containing mineral in the mixture leads to increased growth and plant development, optimization of the agrophysical, agrochemical, and biological parameters of the soil, reducing soil fatigue, and increasing fertility
Organizational and legal mechanisms of cybersecurity and cyber defense in Ukraine: essentiality, conditions and development prospects
No full textThis article is devoted to the organizational and legal mechanisms of the cyber security public administration and cyber security in Ukraine, the definitions of essence, the role in the system of strategic planning and management of the security and defense sector are given. Some aspects of cyber security in Ukraine have been evaluated. In addition, recommendations of improving the cyber security system in Ukraine are proposed, such as, proposals were made to eliminate the existing gaps in the main legal acts regulating the sphere of ensuring national, information and cyber security of Ukraine, including through the harmonization of Ukrainian legislation with international legal acts in this field.Problems in programming 2020; 2-3: 278-28
Ontological methods and tools for semantic extension of the media WIKI technology
Get PDFPractical aspects of ontological approach to organization of intelligent Wiki-based information resources (IR) are considered. We analyze the main features, capabilities and limitations of MediaWiki as a technological platform for development of the Web-based information resource and suggest main directions of its refinement. We propose an abstract model of MediaWiki architecture that formalizes relations between the main components of this software environment and analyze the ways of its semantic extensions based on ontological representation of domain knowledge. An original algorithm of semantic Wiki pages matching with domain ontology is developed. We propose an ontological model of IR that formalizes its knowledge base structure and explicitly performs main features of typical information objects (TIO) of this IR. Such TIOs depend on domain specifics and purposes of IR, therefore their development has to involve domain experts and knowledge engineers. Use of ontology corresponding to the set of Wiki pages (either with semantic markup or without it) provides new IR functions associated with semantic search and navigation. Other important aspect of intelligent Wiki resource development deals with adaptation of user interface to the specifics of IR: enabling various tools of navigation, visualization and content analysis by processing of TIO features enriches IR functionality, reduces access time to information and makes usage of IR more efficient. Developing additional MediaWiki functionality with new requests to the MediaWiki API using TIO templates, extends data analysis and integration capabilities, and offers different, user-focused, IR content views expands the possibilities of data integration and proposes various user-oriented representations of IR content. Wiki resource semantization allows the use knowledge acquired from such IR by external application, or example, by search engines for intelligent Web retrieval. Domain ontologies based on various subsets of the Wiki pages and generated by them thesauri can be used by various Semantic Web applications, both independently or in general technological chain for personified retrieval focused on individual users and their tasks. Approbation of this approach is demonstrated by MAIPS retrieval system. We consider the use semantic similarity of concepts represented by Wiki-pages of IR as an additional way of intelligent navigation between these pages. Such approach allows to group Wiki pages according to user interests by different aspects of their content and structure. Wiki ontologies are considered as the basis for estimation of semantic similarity between domain concepts pertinent to user task. Such elements of Wiki ontology as classes, property values of class instances and relations between them are used as parameters for the quantitative assessment of semantic similarity of Wiki pages. We propose to use local similarity and generate the sets of semantically similar concepts (SSC) that takes into account some subset of page properties and categories defined by user needs. Such sets of SSCs can be considered as user task thesauri for other applications. In addition, we propose to enrich the basic tools of MediaWiki used for access management to the IR content with specialized software code that performs content classification that take into consideration separate namespaces, categories, templates and semantic properties of TIO acquired from Wiki markup. We demonstrate the software implementation of proposed solutions by developing of portal version of the Great Ukrainian Encyclopedia (e-VUE) that contains heterogeneous multimedia content with complex structure. We analyze the specifics of e-VUE knowledge system and develop its formalized TIO representation based on Semantic Web technologies and ontological analysis. Ontological model of e-VUE and original methods of its processing used for this project extend the functionality of the portal in the area of search, navigation, integration and protection of content based on background domain knowledge. In addition, original user interface of e-VUE is developed with an allowance for Encyclopedia knowledge specifics, substantially differs from the standard Wiki, meets the requirements, goals and objectives of this IR and provides a lot of additional features.Prombles in programming 2020; 2-3: 61-7
About using special data structures in coverage algorithms
No full textThe aim of this work is to increase the efficiency of methods and algorithms for solving the problem of finding coverage. Efficiency is understood as the minimum delay of the procedure that implements this method. To increase the efficiency of the “Columnization” method, a characteristic vector (CV) is introduced into the decision tree construction procedure, obtained by summing the units in columns / rows of the coverage table (CT); it characterizes the current state of the coverage table. The idea of this method is to gradually decompose CT into sub-tables using their reduction according to certain rules. We consider 3 ways to reduce the original table / current sub-tables in the methods: 1) "Border search over a concave set"; 2) "Using the properties of the coverage table"; 3) "The minimum column is the maximum row." In the latter method, CV was used for the first time, which made it possible to accelerate the coating finding procedure up to one and a half times. The complexity estimates for the considered coating methods are calculated; we have: S1 = O (n ^ 3); S2 = O (2 ^ n); S3 = O (n ^ 2), where n is the determining parameter of the coverage problem (number of columns), and the applicability limits of these methods are determined. It is shown that the use of CV in methods 1 and 2 is impractical.Problems in programming 2020; 2-3: 138-14
Models of concurrent program running in resource constrained environment
Get PDFThe paper considers concurrent program modeling using resource constrained automatons. Several software samples are considered: real time operational systems, video processing including object recognition, neural network inference, common linear systems solving methods for physical processes modeling. The source code annotating and automatic extraction of program resource constraints with the help of profiling software are considered, this enables the modeling for concurrent software behavior with minimal user assistance.Problems in programming 2020; 2-3: 149-15
Validation of correctness of autotuning code transformations with rewriting rules technique
No full textArticle presents an approach to correctness validation of autotuning optimizational transformations. Autotuner is considered as dynamic discrete system and validation is reduced to verification of characteristic of equivalence by result of representation of initial and optimized program versions in autotuning formal model. In partial cases this validation can be done automatically using source code and rewriting rules technique.Problems in programming 2020; 2-3: 368-37