Harvester open publications of NAS Ukraine
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An approach of intelligent searching of information in texts
Get PDFPaper proposes an approach aimed at question oriented searching of information in texts. Texts are parsed, keywords and extra features of questions are marked, and sentences in text with the most relevant information to question are defined. Proposed approach is applied to Cyrillic and Latin languages.Case study illustrates how to obtain answers to questions about Bulgarian fairytale that is represented on different languages (Bulgarian and English). Evaluation of the proposed approach is introduced. Description of the software architecture and source code of the corresponding software system are represented. Data structures and examples of *.xml files for storing information about question and answers are outlined.Prombles in programming 2022; 3-4: 281-28
Principles and models of expert-analytical methodology for adaptive organizational decisions forming under deep uncertainty
No full textThe paper depicts and analyzes Expert-Analytical Methodology named EAM DMDU to support Proactive Anti-crisis Decisions within Organizational Systems under deep uncertainty. Complex tools are proposed for Decisions Domain Knowledge analytical operation. The Benefit is no essential resource demands while keeping the basic principles to deal with deep uncertainty (uncertainties and inconsisten- cies eliciting; Decision vulnerabilities searching instead prediction; threats resilience priority over effectiveness).EAM DMDU enables Deliberative multi-staged Process for Adaptive Decision forming aimed at expected future conflict situation solving. The Process stages are: Problem situation Analysis, Impact on Problem Situation Goal Proposition, Goal proposals Assessment; Efforts for Goal achieving Proposals; Effort Proposals Assessment; reference Proposal option Selection and Decision adaptations accordingly to Decision Frame changes Recommendation. Knowledge operation is enabled with the procedures such as: formal analysis, individual expert assessment, Decision elements deliberative forming. EAM DMDU common information space of is based on Domain Ontology and ensures equal participants’ awareness, expert judgments with their arguments constructive representation and knowledge reuse. Expert-analytical Selection of Proposals uses their Perspectivity Model. It is a sub-goals hierarchy to achieve the goal being formed over previous Process stages. Hierarchy knot is represented with ontologically formalized definition for State of the Art corresponding sub-goal achievement. Leaf node depicts State of the Art with explicit expert Estimates of Certainty factor (from the Stanford model) being provided concerning its implementation through Decision element Proposal being assessed. The Estimate’s arguments are elements of information space used by expert. Under incomplete certainty of element expert provides its boundary values and State of the Art estimates both pessimistic and optimistic. Perspectivity Model contains also conditions for goal achievement violation being caused with environmental threats. Procedures for Estimates formal integration up to Model provide extreme estimates of Proposals Perspectivity and Robustness regarding current uncertainty. Under unsatisfactory properties of integrated Estimates their deliberative adjustment is carried out using Uncertainty Map and arguments provided. The final reference Decision contains selected Goal-Means option and guides to adapt it when decision frame changes. Further research is carried out for EAM DMDU instrumental tools development and its usage for defense resource management.Prombles in programming 2022; 3-4: 364-375
Flow based bonet traffic detection using AI
No full textThis paper outlines the generalized framework for building end-to-end botnet network activity detection systems using artificial intelligence (AI) techniques. The paper describes network flows reconstruction as a primary feature-extraction method and considers different AI classifiers for achieving a better detection rate. The results of the latest research by other authors in the field are incorporated to implement a more efficient approach for botnet discovery. The described intrusion detection pipeline was tested on a dataset with real botnet activity traces. The performance metrics for different AI classification models were obtained and analyzed in detail. Different data preprocessing techniques were tried and described which helped improve the results even further. Some options for future enhancement of network feature selection were proposed as well. The comparison of the obtained performance metrics was drawn against the results provided by other researchers in this field.Prombles in programming 2022; 3-4: 376-38
On the formalization of emergency action plans
No full textThe problem of formalization of action plans to counter emergency situations is being studied. It is noted that traditional action plans are text documents that are not suitable for solving the tasks of automating the management of emergency situations. A formal description of the state space is given and the expediency of using the state space graph to represent electronic action plans is substantiated. Based on the analysis of the internal structure of the process of countering an abstract emergency, a set of functional groups and their constituent operations are identified, using which an arbitrary action plan can be built. The identification of a set of types of parameters is carried out, through which the formalization of operations is provided. The advantages of using the proposed formalization of action plans for automating the processes of emergency response management are given.Prombles in programming 2023; 1: 38-4
Fuzzy data in semantic Wiki-resources: models, sources and processing methods
No full textWe analyze main types of dirty data processed by intelligente information systems, criteria of data classification and means of detection non-classical properties of data. Results of this analysis are represented by ontological model that contains taxonomy of classical and nonclassical data and knowledge-oriented methods of their transformation. Special attention is paid to semantically incorrect data that corresponds to vague knowledge. This ontological model intended to provide more effectively methods for transforming raw data into smart data suitable for automatic analysis, knowledge acquisition and reuse in other information systems. The ontological approach provides integration of the proposed model with other external ontologies that formalize characteristics of various methods and software tools that can be used fo data analysis (data mining, inductive inference, semantic queries, and instrimental tools for testing various aspects of the ontology quality, etc.).The work uses the experience of knowledge base developing of the portal version of the Great Ukrainian Encyclopedia e-VUE. This information resource is based on the semantic Wiki technology, it has a large volume, a complex structure and contains a large number of various heterogeneous information objects. Wiki resources are interesting from the point of view of collaborative processing the fuzzy datathat describe heterogeneous information objects and knowledge structures. Due to the fact that the creation of this information resource involves a large number of specialists of various scientific fields, who have different areas of expertise and qualifications in use of knowledge-oriented technologies, there are many differences in the understanding of the rules for presenting and structuring data, and therefore a significant part of the Encyclopedia content needs additional verification of its correctness. Therefore, we need in formalized and scalable solutions for detection and processing various types of inconsistence, incompleteness and semantic incorrectness of data. The proposed approach can be useful for the creation of other large-scale resources based on both the semantic Wiki technology and other technological platforms for collaborative processing of distributed data and knowledge.Prombles in programming 2023; 2: 67-83
VuFind: an open solution for integrating library collections
No full textThe article discusses the VuFind system as an open solution for effective integration of library collections. VuFind is a powerful search interface designed to improve access to a variety of resources, including books, articles, journals, scientific reports, and other materials. The authors discuss the key features of VuFind, such as flexible customization, search capabilities, metadata support, and integration with various data sources. They emphasize the role of VuFind in simplifying search for users and optimizing the management of collections from different libraries. VuFind provides an open and available solution for building modern library systems, facilitating effective integration and increasing user satisfaction.Prombles in programming 2023; 4: 15-2
Діброва Дендропарку “Олександрія”. Частина 1. Від корінного до антропогенно трансформованого насадження
No full textThis study aimed to determine the level of preservation of primeval forest criteria and the extent of anthropogenic transformation in the old-growth oak forest of the Dendropark “Оlexandria”. This age-old oak forest of natural origin covers an area of 31.8 ha with 1413 oaks. Another 8.8 ha of the oak plantations with 462 oaks belong to artificial landscape compositions.For over 200 years of existence since the creation of the Dendropark “Оlexandria”, the oak forest has preserved a number of criteria characteristics of virgin forests. In particular, it kept the complex mosaic-tiered forest structure. The indigenous associations of oak forests of hazel-ash (Quercetа (roboris) coryloso-aegopodiosum) and Tatar maple-stellar (Quercetа (roboris) acerioso (tatarici) stellariosum) remained. The dominant species, Quercus robur, retained the function of a unifier with a share in the first tier of 70–100 %. The floristic core of the main forest-forming species has been preserved too.The oak forest is a habitat for many woody and herbaceous plants of the local flora, including threatened species. The oak forest is characterized by high structural complexity, particularly a diverse epiphytic lichen flora, the presence of rare species, and 15 indicator species of old-growth forests and virgin forests. The oak forest is a habitat for 62 species of birds, mostly inhabitants of forests. A large part of the oak forest contains dead wood of the uniflorus species and its companions in various stages of decomposition.The anthropogenic interference in the oak forest has been long and varied. Since the foundation of the park and subsequently, the oak forest has been subjected to excessive fragmentation and introduction of introductions, creating decorative landscape compositions within the oak forest, mainly in the central part. This caused significant ecotonisation of the oak forest and displacement of Q. robur.Current research has revealed a number of criteria that classify the oak forest as a successor to the primeval forest, which gives the oak forest an exceptional value
Metadata as a tool of the semantic analysis of the complex contents of the big data. The images
No full textThe purpose of the research is to specify effective approaches for improving the semantic analysis of graphic contents of big data. This article considers images or video scenes as examples of such complex contents. Proposed approach takes into account the special features of these contents and create a hybrid annotation model that extends the text annotation model with more specific elements. For the visual data, these are characteristics of visualization. Determining the similarity of information contents is a critical problem for solving big data tasks. It is the basis for the big data categorization and enables the composition of the documents, conversion of an unstructured contents to relevant knowledge structures and the visualization of the information. Semantic analysis of information contents is usually based on their metadata, which form the basis of semantic annotations. Also, they are elements of a structured semantic description of the content and the basis for its automated processing. The approach is based on using ontologies to define semantic annotations. Ontologies provide various sources of knowledge to measure semantic similarity, contain a lot of information about the interpretation of concepts and other semantic relationships with a hierarchical structure based on hyponymy relations. But, in recent years, there is the rapid growth of the number of images and video resources. And, at this time, we can note a significant enrichment of available visual information. From a visual point of view, it is easier to understand whether two concepts are similar. Therefore, the integration of semantic and visual information of the image ensures the optimization of the ontological methods for similarity estimation and allows to obtain similarity metrics that are more consistent with human perception. De facto, such assessments of the complex semantic similarity of concepts are defined by the composition of two functions, the first of which, in fact, is an ontological measure of similarity, and the second is built on the basis of a complex facilities vector. It is a concatenation of semantic and visual characteristics with an established weight balance between these two types of features. The combination of visualization features with semantic and ontological characteristics of the contents in the similarity metrics is the central idea of this study.Prombles in programming 2023; 1: 58-6
60 Years of Databases (final part)
No full textThe article provides an overview of research and development of databases since their appearance in the 60s of the last century to the present time. The following stages are distinguished: the emergence formation and rapid development, the era of relational databases, extended relational databases, post-relational databases and big data. At the stage of formation, the systems IDS, IMS, Total and Adabas are described. At the stage of rapid development, issues of ANSI/X3/ SPARC database architecture, CODASYL proposals, concepts and languages of conceptual modeling are highlighted. At the stage of the era of relational databases, the results of E. Codd’s scientific activities, the theory of dependencies and normal forms, query languages, experimental research and development, optimization and standardization, and transaction management are revealed. The extended relational databases phase is devoted to describing temporal, spatial, deductive, active, object, distributed and statistical databases, array databases, and database machines and data warehouses. At the next stage, the problems of post-relational databases are disclosed, namely, NOSQL-, NewSQL- and ontological databases. The sixth stage is devoted to the disclosure of the causes of occurrence, characteristic properties, classification, principles of work, methods and technologies of big data. Finally, the last section provides a brief overview of database research and development in the Soviet Union.
A Convolutional Neural Network Model and Software Tool for Classifying the Presence of a Medical Mask on a Human Face
No full textA model of a convolutional neural network, a database for training a neural network, and a software tool for classifying the presence of a medical mask on a person’s face, which allows recognizing the presence of a medical mask from the transmitted image, have been developed. The structure of the neural network model was optimized to improve classification results. In addition, the development of the user interface was carried out. The developed application was tested on a set of random images. The resulting model demonstrated high accuracy and robustness in solving the task of classifying the presence of a medical mask on a person’s face, which allows automating measures to protect people from the spread of diseases. The implemented application meets the requirements for speed and quality of classification. Further improvement of the classification quality of CNN can be done by collecting a larger dataset and researching other CNN architectures.Problems in programming 2023; 2: 59-6