Software & Systems

Articles of journal № 4 at 2022 year.

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21. Requirements for the software implementation of the Industrie 4.0 system for creating network enterprises [№4 за 2022 год]
Authors: Telnov, Yu.F., Kazakov, V.A., Danilov, A.V. , A.A. Denisov
Visitors: 2301
The digital transformation of enterprises based on the digital technologies leads to a radical change in busi-ness models and the formation of new organizational and production structures, which include network en-terprises. Network enterprises as dynamically formed production structures in the business ecosystem that unite many enterprises participating in joint economic activity; in modern conditions they are based on digi-tal platforms. Nowadays, an approach to building digital platforms is actively developing within the frame-work of the Industrie 4.0. The subject of the study is to determine the requirements for software implementa-tion of Industrie 4.0 systems (i4.0 systems) based on digital platforms using multi-agent technologies and an ontological approach. As a research method, the authors propose to use the method of decomposing the i4.0 system into plat-form software components and software administrative shells related to managing and functioning of net-work enterprise resources (assets) – i4.0 components. The reference architectural model of the Industrie 4.0 (RAMI 4.0) is chosen as the basis for building the architecture of the i4.0 system. It is proposed to use an on-tological approach in order to implement multi-agent interaction of i4.0 components within the framework of building the value-added chain of a network enterprise. The main results of the study are the formulated requirements for the software implementation of the i4.0 system with regard to the i4.0 platform software components formation and the software administrative shells of the i4.0 components at the levels of the RAMI architecture. As a software mechanism for the inter-action of i4.0 components the paper proposes an algorithm for the i4.0-components interaction using a do-main ontology. The software implementation of the formulated requirements for constructing the i4.0 system architec-ture will increase the flexibility and efficiency of creating and functioning of value-added chains of network enterprises in the dynamically developing business ecosystem of industrial manufacturing of products and services.

22. A precedent approach to evaluating a lightning impact on a street lighting system using the ontologies [№4 за 2022 год]
Authors: M.V. Chernovalova, Chernensky L.L., Makarova I.M.
Visitors: 1628
The paper considers the possibility of improving the energy efficiency and energy security of street lighting systems under conditions of direct and indirect electromagnetic effects of atmospheric electricity and light-ning discharges based on the development and use of an intelligent decision support system. A case-based approach is used as a research method with the representation of knowledge in the form of ontologies. This approach provides the possibility of forming decisions based on knowledge of similar situa-tions that have taken place before, which allows working in open, dynamic, poorly formalized subject areas, where uncertainty can be of an improbable nature. Ontological models provide the possibility of applying a case-based approach in the absence of the necessary amount of statistical information for decision making by representing knowledge in the form of a hierarchy of conceptual terms of a given subject area and a set of relationships. The paper proposes an ontology of the subject area that describes an artificial thundercloud. It is used to identify patterns in information arrays in the integrated management of the processes of energy supply and energy security of street lighting systems under conditions of a different spectrum of electromagnetic effects of atmospheric electricity and lightning. There is a developed algorithm for generating decisions on managing the elements of the specified system using a case-based approach and ontology: its distinctive feature is the possibility of forming quantitative solutions, adapting to the current situation the results of previously im-plemented and described in a linguistic form situations when managing elements of street lighting systems. The developed model and algorithm were implemented in the form of an intelligent decision support sys-tem focused on automating the process of managing these systems, the use of which in practice allows in-creasing the efficiency, validity and effectiveness of decisions made.

23. A GraphQL dynamic schema in integrated information system implementation [№4 за 2022 год]
Authors: Chernysh, B.A., Murygin, A.V.
Visitors: 1936
The paper discusses the possibility of using the GraphQL toolkit with a dynamically changing data schema. The standard way to define data types and operations in GraphQL is a static schema. When using it, the en-tire data structure is determined in advance and cannot be changed dynamically while the application serv-ing requests is running. This circumstance does not allow using GraphQL in applications where the data struc-ture can change dynamically. To solve this problem, there is an approach that consists in storing the data schema in the application memory, and regenerating this schema in case of metadata changes. This paper presents a method for implementing this approach using the SciCMS software platform de-veloped by the authors as an example. A feature of the system is its focus on the requirements for working with data on technically complex products. These requirements include data storage in a tree view with op-timizing retrieval mechanisms, product version control, the ability to use different language representations of products, product lifecycle management, and advanced integration with multiple data sources. The paper outlines the techniques and technologies involved in building the system, provides UML dia-grams and diagrams of the main structures and processes of the application core. It also describes the im-plementation details of individual platform subsystems. Experimental data sampling was carried out in order to evaluate the efficiency of executing queries using joins. The most effective tools for optimizing the selection of hierarchical data were selected based on the data obtained. The paper presents the possibilities of the platform for its integration with other systems with-in a single information space.

24. Classification of common design patterns for multi-agent systems [№4 за 2022 год]
Author: S.A. Chernyshev
Visitors: 1862
Typically, developing multi-agent systems (MAS) involves using special frameworks or simulation model development environments. They provide the developer with the necessary functionality of an agent launch-ing environment, communication between agents, organization of access to resources and much more. However, there are cases when a stakeholder stipulates that it is necessary to avoid dependencies in the form of these toolkits. The lack of a unified database of MAS design patterns without their binding to specific domain in this case is a significant problem. Therefore, developers are coming up with solutions that have been already described earlier. The purpose of this work is to review and analyze the existing classifications of MAS design patterns, to identify common design patterns without their binding to specific domain, which can be used in the design of multi-agent systems and their classification. From more than 200 MAS design patterns in the public domain, the author has formed a base of 60 pat-terns that are not related to a specific domain. He also proposed the following classification of common MAS design patterns: structural, behavioral, migration, communication, architectural (system), protective and cognitive. Some of the classes of patterns allow introducing additional elements that extend functionali-ty of the system, while others aim to implement different aspects of both the agent and MAS. The most prominent class of all proposed patterns is architectural (systemic) patterns, as they specify different types of agent architectures, multi-agent systems or elements that lay down rigid software constraints on the functioning of the developed system or its parts.

25. Informational and algorithmic support of an environmental air monitoring intelligent system based on neural networks [№4 за 2022 год]
Authors: Yarygin G.A., Bayukin M.V., Kornyushko V.F., Shmakova E.G., Sadekov L.V.
Visitors: 2049
The article discusses algorithmic and informational support of an intelligent control system for modern gas analyzers used in environmental air monitoring systems called the Electronic nose. Neural networks form the base of information support. The paper describes a modern automatic odor recognition system based on measurements using low-selective sensors in multi-sensor systems for detecting components of gas mixtures in ambient air. It also shows the advantage of the proposed system compared with traditional systems with highly selective sensing elements. There is a library of smell images based on a series of prerecorded respons-es from the sensor matrix. It is stored in the intelligent system database. Then the responses of an analyzed gas are compared with the responses of individual substances from the image library. The authors propose a two-stage data clustering method for information processing. First, observational data is normalized so that each input parameter equally affects the system. Then the data are assembled in-to clusters using self-organizing Kohonen maps and the k-means algorithm. Each cluster represents an odor with a similar smell. Specific assessments are based on experimental data collected in the environmental monitoring system in the area of the waste incineration plant in Kozhukhovo. The paper considers the choice of an odor identification criteria, which will be used by experts in deciding on odor identification. There is a substantiation of choosing the proximity metric of analytical samples as the norm of the distance between the odor vectors in each sample as a criterion. The authors have developed an algorithm for identifying a substance’s gas analytical sample using neu-ral networks and the selected criterion for decision-making support. There is also a developed (using R pro-gramming language) software product that allows assessing data membership obtained from a device to a certain smell followed by providing visual results of a odors’ spread dynamics in real-time. The paper pre-sents the application results of the developed algorithm in the eco-monitoring system of the incinerator plant in the Kosino-Ukhtomsky district of the Moscow region.

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