DOI: 10.7256/2454-0714.2021.4.37019

Abstract: The subject of this research is the development of the architecture of an expert system for distributed content aggregation system, the main purpose of which is the categorization of aggregated data. The author examines the advantages and disadvantages of expert systems, a toolset for the development of expert systems, classification of expert systems, as well as application of expert systems for categorization of data. Special attention is given to the description of the architecture of the proposed expert system, which consists of a spam filter, a component for determination of the main category for each type of the processed content, and components for the determination of subcategories, one of which is based on the domain rules, and the other uses the methods of machine learning methods and complements the first one. The conclusion is made that an expert system can be effectively applied for the solution of the problems of categorization of data in the content aggregation systems. The author establishes that hybrid solutions, which combine an approach based on the use of knowledge base and rules with the implementation of neural networks allow reducing the cost of the expert system. The novelty of this research lies in the proposed architecture of the system, which is easily extensible and adaptable to workloads by scaling existing modules or adding new ones.

DOI: 10.7256/2454-0714.2021.4.37072

Abstract: This article is dedicated to the problem of detecting intrusions of unknown type based on neural networks that bypass the system of information security in automated data processing systems and are not recognized as spiteful. Development of the means, methods and measures for detecting or preventing such hidden attacks is of particular relevance. Methodological research on the development of procedure for detecting intrusions are based on the achievements of systemic analysis, systemic-conceptual approach towards protection of information in automated data processing systems and achievements of the theory of neural systems in the area of ensuring information security. The object of this research is the intrusions of unknown type in automated data processing systems. The subject is the neural networks, namely neural networks of direct action. The main result lies in the development of neural network of direct action in form of the diagram of neural network links for detecting intrusions. For solving this task, the author developed: 1) The system of input indicators of the neural system;                2) Scales for the assessment of values of the formed indicators; 3)  General procedure for detecting intrusions based on neural networks, the essence of which consists in implementation of the following sequence of actions: a) formation of the list of all the main parties to the process of detection of intrusion; b) formation of the set of parameters that characterize each of them; c) formation of the set of numerical characteristics for each parameter using the assessment scales of the formed indicators; d) analysis of the parameters of the configuration of neural network The developed procedure may serve as the basic in further practical developments of the concept of detecting intrusions of unknown types based on neural networks.

DOI: 10.7256/2454-0714.2021.4.37012

Abstract: There is currently a wide variety of navigation system, which allow determining the exact GPS coordinates and building a route taking based on the specified parameters. However, such systems are not suitable for indoor use, mostly due to no access to the floor plans. In view of this, it is relevant to minimize the time of searching for the location of a particular object, including in a building with complex hierarchical structure. The article examines the theoretical and practical developments in the sphere of navigation, conducts their comparative analysis, which indicated the need for designing the module for indoor navigation in a multi-storey building, considering the peculiarities of its floor plan. As a result, the authors designed the structure of the indoor navigation module in a building with complex hierarchical structure using the graph theory for detecting the shortest route and affine transformation algorithms for graphical representation of floor plan of a building on the example of the main building of the Nosov Magnitogorsk State Technical University. The article provides the description of its subsystems and blocks, as well as instruments for determining geopositioning of the object. The authors outline the prospects for the development of indoor navigation system, taking into account the peculiarities of creating electronic floor plans of a building based on the graph theory, as well as development of the algorithm for modification of the parameters of the existing 3D-objects. As a result of full implementation of the project, there will be designed the system of indoor navigation in a multi-storey building with complex hierarchical structure using a mobile app; it will help to easily find the geopositioning of the object and shortcuts.

DOI: 10.7256/2454-0714.2021.4.34845

Abstract: The existing approaches towards formation of a single information space for accessing from various information resources are not effective enough from the economic and operational perspective. The subject of this research is the information assets from different sources used for the work of intelligent situational centers. The goal lies in the development of methodology for unification of such resources into a single information space, which is essential for the processing of large volumes of unstructured and poorly structured information. The article explores the models and types of data, information space of the activity for determining the end type of data representation, and the algorithm of transitioning from the object to NoSQL model. As a result of the conducted research, the author built a new information structure of the intelligent situational center. The proposed methodology for the formation of physical data models is compatible with the four types of NoSQL databases: columns, documents, graphs, and a key value. The data models (conceptual, logical, and physical) used in the developed process comply with the meta-models: from conceptual to logical stage, followed by from logical to physical stage. The offered solution should be implemented in the form of a hardware-in-the-loop complex that utilizes the described methodology for integrating the information flows from various situational centers. This would ensure the adaptive dynamic transformation of incoming data and their further use within the situational center.

DOI: 10.7256/2454-0714.2021.4.35383

Abstract: One of the developing trends in programming is the logic programming associated with the implementation of tools for creating artificial intelligence. One of such programming languages is the nonprocedural declarative logic programming language Prolog. This article is dedicated to the use of recursive rules in Prolog software. The goal of this work lies in analysis of the methods for completing recursive calls in recursive rules, as well as in explication of the use of such methods on the examples of programs with recursion. The author explores the specialized literature on the topic, generalized and systematizes the data, as well as tested the programs and the progress of their implementation. Recursive rule in the Prolog software sets an infinite cycle of repetition of predicates. For completing the recursive cycle, it is necessary to set a condition within the program that would end the cycle. The article examines the variants of organizing recursions with the completion of infinite cycle. The examples used in the article allows using them as the basis for programming in language Prolog for solving similar tasks. The acquired results are valuable for further development of the use of recursive predicates in logic programming languages.