«Systems and Means of Informatics»
Scientific journal
Volume 36, Issue 3, 2026
Content | About Authors
Abstract and Keywords
- V. Yu. Korolev
- D. Yu. Volkanov
- T. D. Gerasin
Abstract: An algorithm is proposed for forecasting the risks of adverse events related to anomalous values of quality of service characteristics in data transmission channels. This method is based on a modified Peaks-Over-Threshold technique. The study considers data represented by a time series of values for four quality of service characteristics: bandwidth, round-trip-time, jitter, and relative number of lost packets aggregated per second. These characteristics were computed from real data collected in a real data transmission and processing network. As adverse events, overloads, packet losses, and large values of round- trip times are considered. The proposed method makes it possible to forecast the risks of adverse events by calculating the probabilities that an adverse event occurs during a specified time interval or estimation of the distribution of the time interval till the next adverse event. The method is designed to be applied in the sliding window mode which makes it possible to use this approach for the analysis of nonhomogeneous and nonstationary processes and/or flows of events.
The purpose of forecasting is to choose the optimal transmission channel with the account of the corresponding requirements to the quality of transmission and the network state providing the given values of the parameters of quality of service.
Keywords: data transmission and processing networks; quality of service; generalized Renyi theorem; Balkema-Pickands-De Haan theorem; Peaks- Over- Threshold method; forecasting of risks of adverse events
Abstract: The paper provides a new, short proof of the stability criterion for a multiclass stochastic M/G/m-type queueing system with an unlimited buffer for the waiting customers and different classes of customers such that the service time of a customer depends both on their class and the assigned server. The proof is based on the theory of regenerative processes and a balance relation for the number of customers in the system, unlike the proof found earlier which used a balance relation for the workload process. The criterion is constructively formulated and has the following evident intuitive interpretation: the input rate must be less than the (properly defined) maximal capacity of the system. Moreover, the proof shows all the main steps of the regenerative stability analysis method of stochastic queueing systems.
Keywords: multiserver queueing system; regeneration; nonidentical servers; customers of different classes; stability criterion
- Fengrui Guo
- R. L. Smeliansky
Abstract: The paper proposes a combined TCP (Transmission Control Protocol) congestion control algorithm that integrates a traditional reactive congestion window control mechanism with a congestion window (Cwnd) prediction procedure based on exponential vector autoregression (EVAR). The method is intended to reduce the period during which the available bandwidth remains underutilized after a congestion event. Once congestion or its signs are detected, EVAR is used to predict the Cwnd value for the next observation interval, and this forecast is applied as a new Cwnd value if it satisfies an additional safety constraint. The safety threshold is defined through the round-trip time (RTT) and limits the use of the forecast when rapid Cwnd recovery may increase queues and cause additional congestion events. The proposed algorithm is evaluated on an ns-3 test stand and compared with NewReno, CUBIC, and BBRV1 . The results show that, compared with the baseline congestion control algorithms, the proposed algorithm makes it possible to obtain at least 0.5 Mbit/s of additional available bandwidth.
Keywords: TCP congestion control; exponential vector autoregression; congestion window prediction; available bandwidth; ns-3 simulation
- M. V. Sapozhnikov
- S. Yu. Kazantsev
- Yu. B. Mironov
- B. M. Shabanov
- A. E. Matyunin
Abstract: The paper evaluates the feasibility of using quantum key distribution in satellite optical communications. A methodology for calculating the performance indicators of satellite quantum key distribution, including the overall throughput efficiency of such a communication channel, is verified. The methodology is verified by qualitatively comparing the obtained results with data from a full- scale satellite quantum key distribution experiment between the Micius quantum satellite and a ground station located in Zvenigorod. The maximum effective length of the satellite channel is estimated for three standard wavelengths: 850,
1310, and 1550 nm. For a wavelength of 850 nm, the performance indicators of quantum key distribution are calculated taking into account the BB84 and B92 protocols. The study confirms the fundamental feasibility of using quantum key distribution in satellite optical communications.
Keywords: satellite optical communication; quantum key distribution; quantum key distribution efficiency; photon detection rate; dark count rate
- A. A. Kudryavtsev
- O. V. Shestakov
Abstract: Wavelet analysis methods are widely used to solve tomographic image reconstruction problems in medicine, biology, astronomy, and other fields. Their appeal lies in the speed of the algorithms, adaptability to image features, and the ability to reconstruct local image regions from incomplete projection data.
This is particularly important for medical applications where it is undesirable to expose a patient to an unnecessary radiation dose. Error analysis of these methods is an important practical task as it allows one to evaluate the quality of both the methods themselves and the equipment used. This paper considers the problem of image function reconstruction using the Radon operator inversion.
The asymptotic properties of the risk estimate are investigated under thresholding of the coefficients of the wavelet-vaguelette decomposition of the image function. Conditions are presented under which the asymptotic normality and strong consistency of the unbiased risk estimate hold.
Keywords: Radon transform; wavelet-vaguelette decomposition; thresholding; risk estimate
- A. V. Panteleev
- N. V. Turbin
- N. A. Tuchkov
- R. L. Talya
- K. V. Akchupanov
- K. K. Ibrishev
Abstract: The article presents the results of a polymer composite material (PCM) matrix cracking analysis performed using a newly developed method for crack density detection based on computed tomography data. This method allows for the automatic detection and tracking of microcracks across successive tomographic sections. The underlying algorithm is based on modern computer vision concepts.
An aircraft-grade carbon fiber with a 33-layer stacking sequence representative of key aircraft wing structural components such as load-bearing panels and spars, was investigated. Matrix cracking in the PCM samples occurred as a result of the application of cyclic tensile loads. Prior to cyclic loading, quasi-static tensile tests were performed to determine the tensile strength of the samples. The number of applied load cycles was selected experimentally from the conditions for maintaining the integrity of the sample, on the one hand, and the significant development of matrix cracking in the layers on the other. The tomographic image crack search algorithm consists of several stages, including determination of the orientation and thickness boundaries of layers, detecting areas with cracks, and correcting identified cracks based on data obtained in adjacent layers. Scharr and Sobel filters, morphological operations, and binarization were used to process the tomographic images. As a result of the application of the method for the studied PCM, crack density distributions in layers, ratios of long and short cracks, as well as statistical characteristics of the distributions obtained - representing the basis for analyzing PCM crack resistance necessary for the high-quality processing of PCM characterization tests - were obtained.
Keywords: composite materials; matrix cracking; computed tomography; filtration; binarization; morphological transformations
- I. N. Sinitsyn
- V. I. Sinitsyn
- E. R. Korepanov
- T. D. Konashenkova
Abstract: The paper is devoted to methodological and algorithmical support of wavelet neural network (WNN) mean square estimation (MSE) synthesis for an observable bilinear stochastic system (BLStS). The BLStS is described by the Pugachev equations for the input and output stochastic processes (StP). The output StP is dependent on the random parameters vector. The input StP contains random noise independent of random parameters. The random parameters vector is defined by a probability density function. The linear operator for MSE optimal StS is the approximate solution of the operator equation connecting probability second-order moments. The approximate solution is based on the theory of multiscale analysis and a WNN. The random noise is approximated by a wavelet canonical expansion (WLCE) built upon an orthonormal basis of wavelets with compact carrier. This WLCE is constructed on a WNN and is denoted as CEWNN. Input is approximated by linear combination of basic wavelets with random coefficients. The optimal MSE is composed as a linear combination of basic wavelets with random coefficients. Accuracy estimates for the output StP are provided in terms of probability moments of the first and second order. Experimental software tools "BLStS-Synthesis-WNN" and test examples are developed.
Keywords: bilinear stochastic system; mean square criterion; modeling; optimal estimate; stochastic process; stochastic system; wavelet; wavelet canonical expansion; wavelet neural network
- A. A. Sachko
- A. M. Sachko
- V. Yu. Pozdyshev
Abstract: Documentation quality at specialized industrial enterprises is a critical factor influencing order lead times, manufacturing process stability, production costs, and product performance. However, existing documentation control approaches primarily focus on identifying already manifested nonconformities and underutilize statistical analysis methods for management decision support, particularly in pattern recognition and risk forecasting. This study aims to develop and validate a statistical analysis methodology for documentation quality to enhance decision support systems at specialized industrial enterprises. The study is based on a comprehensive census of 6,739 documents that underwent standard compliance control (normative control) at a defense industrial enterprise over 12 quarters from Q1 2023 to Q4 2025. These documents were categorized into four types (engineering, software, and graphical documentation, along with change notices) and three quality levels ("Good," "Average," and "Poor"). The research methods included contingency table analysis (Pearson's x2 test, Cramers's V, and standardized residuals) with bootstrap estimation for result robustness; time- trend modeling of the logit-transformed proportion of high-quality documents with residual diagnostics (Shapiro-Wilk, Breusch-Pagan, and Durbin-Watson tests) and forecasting; the Chow test for structural break detection; analysis of covariance (ANCOVA); seasonality analysis; and correlation analysis.
Keywords: statistical analysis; documentation quality; decision support system; contingency tables; logit model; analysis of covariance (ANCOVA); correlation; forecasting
- A. A. Grusho
- N. A. Grusho
- M. I. Zabezhailo
- A. A. Zatsarinny
- V. O. Piskovski
Abstract: The article discusses historical aspects as well as current capabilities of using network-centric technologies in management and control systems and decision support. Special attention is paid to the problem of integrating artificial intelligence methods and solutions into network-centric control systems (NCCS).
The authors formulate a number of current issues related to the application of situational control methods and technologies in modern NCCS to support decision-making in a dynamically changing environment. Furthermore, the paper outlines specific features of the contemporary approach to creating networkcentric military management and control systems. Taking into account recent advancements in information technology infrastructure development and the widespread use of new promising solutions in the field of artificial intelligence, the possibilities of using the NCCS as a platform for integrating various methods and means of data representation and intelligent analysis, particularly to maintain the situational awareness of decision makers, are discussed.
Keywords: network-centric control systems; artificial intelligence; data analysis and decision making; situational awareness; methods and means integration
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