«Systems and Means of Informatics»
Scientific journal
Volume 35, Issue 3, 2025
Content | About Authors
Abstract and Keywords
- Yu. G. Diachenko
- L. P. Plekhanov
- N. V. Morozov
- D. Yu. Stepchenkov
- G. A. Orlov
- D. Yu. Diachenko
Abstract: The article considers the self-timed (ST) flip-flop development issues based on the original description of their synchronous counterparts functioning at the behavioral level. The options of synchronous flip-flops and their compliance with the ST flip-flop's behavioral features are analyzed. The implementations of some typical ST flip-flops with preset options are represented. A method for converting synchronous flip-flop behavioral description into an ST counterpart taking into account the ST circuit operation specifics is proposed. Asynchronous reset and set of the synchronous flip-flop remain asynchronous in the ST counterpart as well, they are not indicated. Synchronous reset and set are transformed into ST reset and ST set, respectively. Their successful completion is indicated. The paper shows that it is advisable to implement ST reset and ST set by preliminary mixing of reset and set signals with the flip-flop information input. Substitution of the ST flip-flop instead of the synchronous prototype is carried out using templates that ensure the replacement adequacy, the optimality of the hardware implementation, and the self-timing of the resulting circuit.
Keywords: self-timed circuit; flip-flop, Verilog description; operating range; register; element base; robotic system
- P. O. Arkhipov
- S. L. Philippskih
- M. V. Tsukanov
Abstract: The paper examines the limitations of modern data augmentation methods when applied to images captured by unmanned aerial vehicles in scenarios characterized by high object density and small object sizes. A specialized method, Contextual Small-Object Augmentation, is proposed to intelligently place visually enhanced objects into semantically relevant regions of the image while preserving spatial realism. In particular, the study focuses on a data augmentation module that utilizes super-resolution (SR) networks to improve the visual quality of small objects. For this purpose, several state-of-the-art SR neural models - RCAN, Real-ESRGAN, and SwinIR - were selected.
Their impact on the accuracy of object detection and classification was evaluated using the SSD MobileNet V2 FPNLite 320 x 320 model trained on various versions of the VisDrone benchmark dataset. The detection results were compared against a baseline model trained on the original dataset following the evaluation protocol of the COCO Evaluation Metrics. The experimental results demonstrate that incorporating high-resolution networks into the augmentation pipeline significantly improves the detection accuracy of small objects while maintaining computational efficiency.
Keywords: object detection; object classification; transformer; convolutional neural network; generative adversarial network; data augmentation
- I. N. Sinitsyn
- V. I. Sinitsyn
- E. R. Korepanov
- T. D. Konashenkova
Abstract: New method of optimal synthesis of multidimensional linear stochastic system on Bayes criterion (BC) based on quantitative estimate of output stochastic process (StP). Stochastic system is described by Pugachev equation for input and output StP. Input StP contains useful signal and random additive multidimensional normal noise with zero mathematical expectation and known matrix of covariance functions. Random noise does not depend upon vector of random parameters of useful signal. Distribution of random vector parameters is known. Model of BC optimal estimate of output StP is constructed on the basis of wavelet canonical expansion (CE) of random noise and wavelet CE of input StP. For finding unknown parameters in optimal output StP estimate, the architecture of multilayer wavelet neural networks (WNN) is developed. The WNN training algorithm for inverse error prevalence by method steepest descent is used. Formulae for mathematical expectation, second initial probabilistic moment, and error covariance matrix of BC optimal estimate of output StP is obtained. Numerical example illustrates CE WNN preference with wavelet CE.
Keywords: Bayes criterion; canonical expansion; covariance function; covariance matrix; modeling; loss function; optimal estimate; stochastic process; stochastic system; wavelet; wavelet-neural network
Abstract: The solution of navigation problems by the state of a stochastic dynamic system filtering on indirect observations is based on two models of equal importance. The first is motion model of the object whose position needs to be estimated. The second is the observation model, the specific features of which are dictated by the variety of measurement instruments used. The article discusses a typical noncooperative scenario in which an object is monitored by an independent complex of external measurements. The physical quantities measured in this scenario are directional angles (azimuth, or bearing, and elevation) and range. However, the impact on the measurement results of external uncontrolled factors formed by the environment in which the movement-observation takes
place can be quite diverse. The article proposes several typical options for describing such an impact. The first, the standard one, assumes simple additive errors of observations. In the second case, this model is complicated by the assumption that measurement errors are correlated with the current state of the moving object. The physical meaning of this option is provided by the range measurement. Both cases assume stable (without failures) operation of the monitoring complex. The third option is based on a well-known model of switching observation channels and allows for flexible modeling of both short- and long-term failures of some measuring devices. The final version takes into account the specific features of using sonars - acoustic sensors, i.e., motion in an aquatic environment. To illustrate the differences between the models considered, calculations are provided using position estimates based on direct measurements which are not affected by the motion model.
Keywords: navigation; target tracking; unmanned vehicles; stochastic dynamic observation system; additive disturbances; correlated noise; Markov chains; acoustic sonars
Abstract: Currently, in addition to end-to-end congestion control mechanisms, RED-like (RED - Random Early Detection) queue management mechanisms are being actively implemented in routers in existing information networks. The paper considers a model of the G/M/1 queue system in which the queue is controlled by
a two-threshold RED-like algorithm with probabilistic dumping of requests.
In the model under consideration, the decision to reset is made at the time of completion of the client service depending on the current queue length. Theoretically, the behavior of a weighted function of criteria (the intensity of the accepted customer flow, the average delay of served customers, the intensity of rejected customers at the entrance, the intensity of customers dropped from the queue, and the average downtime of the device) is studied when changing the value of the lower threshold parameter of the algorithm. A number of statements about the properties of particular criteria and the statement that the weighted function of particular criteria is unimodal in terms of the lower threshold parameter are proved. A simple rule for correcting the value of the lower threshold parameter is proposed which is guaranteed to find the maximum value of a weighted function of particular criteria.
Keywords: queuing system; RED-like algorithm; queue updating; unimodality
Abstract: The article constructs a model of the sequence of sojourn times {V} based on the available assumptions regarding the characteristics of the queuing system and the specified data sets. For statistical control of the stability of the queuing system, the ARIMA-model (AutoRegressive Integrated Moving Average) has been used. The main reasons for this are as follows: the process {Vi} can be both stationary and nonstationary with the dependence of individual states; testing a simplified version of the ARIMA-model when instability is detected has shown its effectiveness; and there is a corresponding software
implementation - the forecasting package of the R platform. At the same time, statistical stability control is a pioneer direction and there is practically no experience in building appropriate statistical models. The article clarifies the subtleties of the general principles of model construction taken into action in the case of monitoring the stability of the queuing system. To illustrate the capabilities of ARIMA-modeling, sequences for a dual-processor M/M/2 job processing system with a random selection of the number The ARIMA-model takes into account the features of the process {Vi}; the adopted method of fitting the model demonstrates reliability; and using only model parameters for stability control is not effective. The emerged predictive capability does not contradict the overall results on the behavior of stable or unstable systems, can make adjustments to the decision on stability, and can also serve as a starting point for analyzing and assessing the risks of using queueing system. The adequacy of the proposed model is investigated.
Keywords: queueing system; time series; tests of stability; automatic forecasting; ARIMA- modeling; statistics with R
Abstract: The paper explores the application of machine learning techniques to the development of an intelligent attack simulation system designed to automate penetration testing as a part of network security assurance. Traditional penetration testing methods are often labor-intensive and require significant time and resource investment. The proposed model integrates Generative Adversarial Imitation Learning and reinforcement learning algorithms, enabling the simulation of attacker behavior and the generation of realistic scenarios that closely mimic the actions of professional security experts. A key feature of the model is the incorporation of semantic rewards which account not only for the achievement of attack objectives but also for factors such as the novelty and stealthiness of the actions. To improve adaptability in dynamic network environments, the model can be extended with dual discriminators. Additionally, support for multi-agent interaction makes it possible to simulate coordinated attacks involving multiple adversaries.
Keywords: information security; generative adversarial imitation learning; attack simulation; machine learning
Abstract: The article is devoted to the issues of data protection in business intelligence systems and the use of depersonalized data for analytical purposes, which allows to increase their protection in case of unauthorized access to analytical information storage systems or the organization as a whole. It is shown that depersonalization of data in the perimeter of the organization, although it reduces the risk of data leakage, but does not exclude it in case of unauthorized access to many systems of the organization including the depersonalization system.
The issue of delegating the procedure of personal identifiers depersonalization to
the third, trusted, party called a trusted depersonalization center is considered.
The algorithm of receiving depersonalized data from clients of information systems in already depersonalized form using the trusted center of personal identifiers depersonalization is given. The recommendations are given on how to improve data security when using a trusted depersonalization center as well as recommendations on depersonalization, which allow minimizing changes in business intelligence systems when switching from processing personal user data to processing depersonalization user identifiers.
Keywords: data depersonalization; trusted depersonalization center; personal identifiers; data protection; data leakage
- A. A. Zatsarinny
- S. V. Kozlov
Abstract: The review article provides an analysis of the experience of creating, the current state, and prospects for the development of integrated control systems. The stages of the evolutionary development of systems are shown: from the structural integration of hardware and software means of infocommunication and control systems in the 1980s to the functional integration of heterogeneous functional systems at the turn of the early 21st century and in the future to the integration of target and supporting processes in the hierarchy of control bodies and in the horizontal interaction of heterogeneous functional systems. The main elements of the ontology of the integrated systems domain are presented in the form of a relationship between enterprise standards (BPM, ERP, CRM, etc.) and a system of corresponding notations (IDEF). The problems of their application caused by the expansion of the variety of elements and scales of integrated systems are highlighted. The article demonstrates the need to choose a new basis for
integrating information and communication systems and control systems in the form of a system of processes, including target functional processes, supporting system engineering processes, and processes that prevent the creation and operation of integrated systems.
Keywords: integrated system; structural, functional, and process integration; organization standards; notation system for integrated systems; system of complete groups of target, supporting, and countering processes
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