Software & Systems

Articles of journal № 1 at 2023 year.

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11. 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: 2489
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.

12. 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: 1470
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).

13. 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: 1963
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.

14. Developing and modeling a hybrid dynamic routing protocol [№1 за 2023 год]
Authors: L.I. Abrosimov , H. Khayou, M.A. Orlova
Visitors: 2193
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.

15. Developing a software tool for constructing a social graph of a social network user in the task of analyzing its security from multi-pass social engineering attacks [№1 за 2023 год]
Authors: Khlobystova, A.O. , Abramov, M.V. , Sazanov, V.A.
Visitors: 2419
The study is based on the problem of lacking visualization tools showing the intensity of interaction between users of the VK online social network, namely the display of metrics that allow evaluating and ranking the intensity of interaction both between a user and his friends, and between friends with each other. The aim of this paper is to improve the accessibility and timeliness of users’ interaction intensity analysis by automating social graph visualization. It is assumed that the numerical coefficients of the social graph arcs will be compared with an assessment of user interaction intensity based on data extracted from publicly available sources of the VK social network. To achieve this goal, the authors considered the following issues: optimization of aggregating necessary data on observed interaction of friends in the VK social network, software implementation of functions for building a social graph, visualization of users' interaction intensity with the possibility of choosing metrics of interest, creation of convenient interface and embedding the developed toolkit into a web-application. The subject of the research is the data of interaction between VK users and the ways of their visualiza-tion. The research methods are based on optimizing sending queries to VK API, as well as developing func-tions and settings to build a social graph. The theoretical significance of the proposed solution is in the development of approaches to analyze the proliferation of multistep social engineering attacks and to validate models for estimating user interaction in-tensity. The result has significant practical relevance consisting in automating the process of assessing the in-tensity of employee interaction, thereby laying the foundation for taking effective measures to mitigate the risks of successful social engineering attacks. The novelty of the research is in the proposed improvement of visualization of VK users' social graph construction by adding new metrics to assess the intensity of users' in-teraction.

16. Recognition complexity when developing video monitoring software [№1 за 2023 год]
Author: A.Yu. Kruchinin
Visitors: 1210
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.

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