Software & Systems

Articles of journal № 1 at 2023 year.

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1. An intelligent system for monitoring and analyzing competencies in the learning process [№1 за 2023 год]
Authors: Kulikov G., Antonov V.V. , L. Rodionova , Fakhrullina A. , Kromina L. , E.V. Palchevsky, Breikin T.
Visitors: 2356
The article proposes an intelligent system (a software-analytical complex) based on an artificial neural net-work for managing the educational process based on data received from corporate business units. Modelling business process improvement involves using the Deming cycle. The paper presents a structure (model) of a software-analytical complex that makes it possible to identi-fy and trace explicitly interconnected vertical and horizontal processes, which gives a formalized description of the system that meets the algorithm requirements. There is an ontological model of the program analytics complex structure built; it is linked to a set of solutions using databases and knowledge bases; it is divided in-to classes of objects and categories with hierarchical relationships between them. In order to share this knowledge, a specific description of this data must be provided to the SAC. This description must be formal enough to be understood by another system and written in the same language. The novelty is in the consideration of a variant of solving the problem of integrating information systems associated with weakly structured subject-oriented information flows of an educational institution using the methods of set theory and category theory. The properties of relations between accounting objects are de-scribed at a high abstraction level; it becomes possible to significantly expand the scope of the proposed method for constructing a software-analytical complex based on an ontological model for various subject areas, taking into account the multi-level consideration of the subject area itself, the same consideration of finite and infinite ranges of values. At the same time, the necessary abstraction level is automatically deter-mined to ensure the structural and parametric integrity of the system being formed and the interpretation of the emerging problems of data analysis represented by semantic models.

2. Industrial robotic intelligent robust control system:  applying quantum soft computing technologies  and quantum software engineering  in unpredicted control situations [№1 за 2023 год]
Authors: Ulyanov, S.V., A.G. Reshetnikov, Zrelova D.P.
Visitors: 2456
The strategy for designing intelligent control systems based on quantum and soft computing technologies is described. The synergetic effect of quantum self-organization of a robust knowledge base, extracted from imperfect knowledge bases of an intelligent fuzzy controller, is presented. The developed technology im-proves the reliability of intelligent cognitive control systems in unforeseen control situations, for example, with various types of interacting robots. Benchmarks demonstrated the effective implementation of a quantum fuzzy inference circuit as a ready-made programmable algorithmic solution for lower-level control systems embedded in a standard board, demonstrated the quantum superiority of quantum intelligent control of classical control objects, ex-panding the Feynman-Manin thesis. The correct physical interpretation of the process of controlling self-organization at the quantum level is discussed on the basis of quantum information-thermodynamic models of exchange and extraction of quantum (hidden) valuable information from/between classical particle trajectories in the “swarm of inter-acting particles” model. A new information synergetic effect is demonstrated: a robust knowledge base of a quantum fuzzy controller is created in real time from two unreliable knowledge bases of a fuzzy controller. This effect is purely quantum in nature and uses hidden quantum information extracted from classical states. The main physical and information-thermodynamic aspects of the model of quantum intelligent con-trol of classical control objects are discussed.

3. Developing and modeling a hybrid dynamic routing protocol [№1 за 2023 год]
Authors: L.I. Abrosimov , H. Khayou, M.A. Orlova
Visitors: 2159
Nowadays, the growth of network services significantly increases the requirements for the quality and speed of solving network management problems in ever-growing data centers. The load increase in data centers leads to the need for structural scaling that implies increasing the number of servers and routers. There is a need for simple scalable routing protocols to facilitate automation and management of ever-growing net-works, especially in data centers. The work aims to present and simulate a new hybrid dynamic routing protocol including an upgraded dis-tance vector routing algorithm and a link state algorithm. The article discusses the solution to the problems of developing a hybrid dynamic routing protocol, which guarantees loop freedom and provides scaling requirements through the development and implementation of simple algorithms that ensure reliable transmission of data and service traffic containing route infor-mation and detects channels, networks, and directly connected neighboring routers connected to the current router. The scalability requirements of the new hybrid dynamic routing protocol are met since the distance vector routing algorithm calculates the distances to infrastructure nodes, and not to the network prefixes themselves. The link state algorithm advertises network prefixes only once, which leads to a reduction in the link state database and a reduction in calculations after topology changes. Loop freedom is achieved by in-troducing a newly developed distributed sequence number algorithm. A simulation model has been developed to simulate the hybrid dynamic routing protocol. The simulation allowed estimating the amount and volume of service traffic, which confirmed the effectiveness of the de-veloped protocol in the conditions of scaling the data center network.

4. Modeling the intelligent agent behavior based on machine learning methods in competition models [№1 за 2023 год]
Authors: A.O. Anokhin , D.S. Parygin , Sadovnikova, N.P. , Finogeev A.A., Gurtyakov A.S.
Visitors: 2442
The article discusses the aspects of applying machine learning methods to existing methods for modeling the behavior of intelligent agents to enable agents to improve their performance in competition models. The practical significance of the study is represented by developing an approach to modeling the behav-ior of intelligent agents in order to increase the efficiency of their functioning in such areas as computer games, developing unmanned aerial vehicles and search robots, studying urban and transport mobility, as well as other complex systems. There is a review of the existing machine learning methods (reinforcement learning, deep learning, Q-learning) and methods for modeling the agents’ behavior (a rule-based model, a finite automaton model of behavior, behavior trees). The authors have chosen the most appropriate combination of a learning method and a behavior model for the task: behavior trees and reinforcement learning. A test platform was implemented using Unity tools, behavior models were developed for the four main archetypes of agents that must compete in collecting resources in a limited time. A trained agent was imple-mented using Unity ML and TensorFlow tools. The test platform has become a basis for a series of experiments under various conditions: limited re-sources, resource abundance, average amount of resources. As part of the experiment, the authors tested the ability of the developed intelligent agent’s behavior model to win in a competitive environment with agents equipped with various variants of traditional behavior models based on behavior trees. The efficiency and advantages of using the developed behavior model were evaluated. The paper analyzes the experimental re-sults and draws conclusions regarding the potential of the selected combination of methods.

5. Integrating the subject area subspace into the “mathematics” semantic space [№1 за 2023 год]
Authors: Ataeva O.M., Serebryakov V.A., Tuchkova N.P.
Visitors: 2818
The paper studies the problem of developing a semantic library by adding a new applied scientific area. The authors use the example of a journal on applied issues of composite materials in order to build an addition to the main content of the library, to expand the description of the original subject area, and to detail UDC and MSC articles corresponding to the local subject area. At the same time, they solve the tasks of adding terms to the thesaurus, building a reference corpus of the applied subject area of mathematics, and creating a custom interface. Formulas and equations of the local subject area are semantically linked to the main content of the library. The main advantage of using semantic libraries for this kind of tasks is to enrich the existing knowledge base of the library and identify relationships in data. To study these problems, it is necessary to interact with subject matter experts and use modern tools and methods for natural language processing, machine learning approaches to knowledge representation. The above tasks are implemented by means of the LibMeta se-mantic library, which allows considering such concepts as the thematic area/subdomain and their hierar-chical relationships, in particular, the automatic inclusion of the enclosing area concepts in the subdomain knowledge system; the possibility of personalizing the built structures and using LibMeta as a construction tool, in particular, building the ontology itself. Data integration within the library allows expanding the de-scription of subject areas related to the applications of mathematics in interdisciplinary research and tech-nology. As an example of one of the applied sections of mathematical physics problems, the procedure for including specific dictionaries, thesauri, as well as an array of publications of a specialized journal in a se-mantic library is shown. The proposed approach will allow using the content of the “mathematics” semantic library for scientific research and minimizing the process of searching for information in the local subject ar-ea, without losing more general results contained outside this area.

6. An algorithm for using distributed computing resources based on the Edge computing principles [№1 за 2023 год]
Authors: Vorobev A.M., Vorobeva M.S., Boganyuk Yu.V.
Visitors: 1943
The article describes the issues of implementing the algorithm for distributing computational tasks over a set of distributed computing resources with subsequent aggregation of the results. This algorithm is the key one in the framework of the data center implementation project based on the sharing economy principles. The mechanism prototype is implemented in Python 3.8 using the PostgreSQL 14 DBMS, the message passing system is implemented on the basis of RabbitMQ 3.9, the computing node platform is CentOS 8 Stream OS. The purpose of the work is to implement a scalable distributed computing mechanism for using as the main instrument of task distribution and aggregation of results within the framework of the data center con-cept based on the sharing economy principles. The subject of the study is the methods of computing power redundancy and use, aggregation of the working results of software algorithms. The proposed mechanism solves the computing distribution problem with subsequent aggregation of re-sults among computing nodes with different technical characteristics. There is an implemented interface suitable for integrating into client information systems as a means of uploading calculations with access in the REST API gateway format. The theoretical significance of the work is in combining the existing principles and ideas of Edge compu-ting to solve a different class of problems, where the problem is the lack of a computing resource for infor-mation system tasks, and not insufficient characteristics of the existing model. The practical significance is in the development of an application tool for using external computing pow-er to solve a wide class of client tasks, which gives the possibility of organizing commercial interaction be-tween owners of unused computing resources and owners of information systems that lack computing pow-er.

7. The procedure of automatic radar-less speed measurement of mobile objects using a stationary camera [№1 за 2023 год]
Authors: Epifanov V.A., I.O. Temkin, Kalgov I.V.
Visitors: 1449
This paper considers the problem of automatic road scene marking to determine the speed of objects by the radar-less method based on data from only one stationary camera. In addition to the limit in the number of used cameras (no more than one camera per scene), the solution is required to be able to automatically calculate the road markings on a microcomputer. To obtain correct mark- ings, we apply calculating of vanishing points based on the analysis of information about moving road scene participants and calculating of the top view transformation matrix for a scene. Scene marking is defined as a set of virtual lines on a roadway, which allow determining the speed of a vehicle when it is crossing these lines consecutively. The combined use of vanishing points calculation and the construction of the bird's-eye view makes it possible to obtain the required result with minimum computational cost and with sufficient accuracy, despite the problems caused by the image perspective. The paper shows how to apply the approach for automatic marking of road scenes to determine speed on different types of devices, such as x86 platforms and nvidia jetson microcomputers. A distinctive feature of the method is the full automation of the road marking, in which all the stages are implemented automati-cally without operator's help. In addition, the algorithm does not require any pre-calculations related to the characteristics of a camera for taking images. The possibility of deploying the proposed solution on microcomputers allows scaling different systems of monitoring and analyzing road infrastructure. To add a new location to the system it is enough to install a single device, which includes both an input device (camera) and a calculator (microcomputer).

8. A control panel generation module for web projects [№1 за 2023 год]
Authors: Zhukov S.V. , Suslin A.A. , Kovaleva O.A.
Visitors: 1185
The article considers the problems of creating a control panel for web projects. It describes the implementa-tion of a program module written in the php programming language, which allows creating an admin panel for web resources. The module does not require skills in HTML template layout due to the Gentelella Admin template preinstalled in the module (developed and maintained by Colorlib and AigarsSilkalns). The de-scribed module can be used both in projects built on the basis of the popular MVC model and in resources written on the basis of the PHP framework. The control panel includes many standard controls (input fields, switches, tables, lists, etc.), and can also support custom components that add new controls. The purpose of the work is to optimize the process of developing web projects using the developed mod-ule. The subject of the research are ways to implement the administrative panel of a web application. The presented module allows generating html, css and js code for visualizing the control panel. The user interface is set in the form of php code. The objects created in it are interface elements that grouped into forms and panels that a developer needs. Using the module allows reducing the development time spent on the forming the control panel, and also allows creating applications without skills in layout and organization of the client side of the user interface. The theoretical significance of the work is in the analysis of typical elements of the admin panel, the de-scription of the principles of operation of the created module for generating the admin panel. The practical significance is to reduce the development time of web projects using the control panel generation module.

9. Recognition complexity when developing video monitoring software [№1 за 2023 год]
Author: A.Yu. Kruchinin
Visitors: 1190
The paper considers the problem of choosing an optimal video monitoring mode when using neural network models as a recognizer when different models are more effective on a video stream at different times. Video monitoring tasks are different while the conditions for obtaining data are different, which can be expressed in the recognition complexity concept. Evaluation of the recognition complexity in monitoring allows saving computing resources, thereby reducing the cost of implementation and use. After evaluating the average complexity of recognition, it is possible to choose the optimal recognition mode in terms of speed and relia-bility during post-processing, when time for it is limited. The paper shows the problem solution in the task of two type object detection using YOLOv5 models, when the video stream must be processed in real time with a minimum delay when the result is returned after each frame. The metrics used in the object detection are analyzed in terms of a possibility of assessing the reliability of the results when there is no final information about an object. There is a chosen efficiency crite-rion based on the sum of the F1-score and the cost of computing resources, which makes it possible to eval-uate the model effectiveness for specific objects. The paper shows the dependence of the efficiency criterion on the F1-score for two models. There are the results of testing two models and a dynamic mode based on choosing an appropriate model depending on the input object. The paper describes the limitations of the ap-proach, which can be used only for streaming recognition, when the images received for recognition are only slightly different from the previous ones. in the end, there is a conclusion about the approach applicability for a number of problems in accordance with the restrictions.

10. An IT system for assessing the impact of energy objects on environment [№1 за 2023 год]
Authors: Kuzmin V.R. , L.V. Massel
Visitors: 1974
The subject of the article is the author's information and computer system called WICS for assessing the im-pact of energy facilities on the environment. The paper substantiates the necessity of both performing such assessments and developing an appropriate system. When building an information and computer system, the authors used the following methods: methods for building client-server Web applications to optimize the requirements for users' computers and to organize teamwork; methods for constructing multi-agent systems for optimizing calculations. In order to implement the database, the authors applied ontological engineering of subject areas that are energy and ecology. The article shows the architecture of the developed system, describes the developed information subsystems based on approved normative methods for performing calculations. Empirical Bayesian kriging is used to in-terpolate the results of the analysis of snow tests for pollutants. There are the results of approbating the de-veloped system on the example of data on the Central Ecological Zone of the Baikal Natural Territory. The proposed system can be used both for assessing the current situation with environmental pollution by energy objects, and when planning measures to reduce their harmful effects or installation of new gener-ating capacities.

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