«Systems and Means of Informatics»
Scientific journal
Volume 34, Issue 3, 2024
Content | About Authors
Abstract and Keywords
- A. A. Grusho
- N. A. Grusho
- M. I. Zabezhailo
- A. A. Zatsarinny
- D. V. Smirnov
- E. E. Timonina
Abstract: The functional purpose of information support of the organization’s activities can be described in the form of a set of business processes. The article deals with monitoring the sustainability of the implementation on one platform of a large number of business processes for servicing a large number of customers, requesting a large number of different services at the same time, and requiring partial modification of business functions in real time. The consequence of these conditions is a significant number of conflicts, errors, and failures at different levels of implementation of the same services under time constraints. Business process monitoring is designed to identify and classify conflicts, errors, and failures for further management decision-making. In the article, the collection of functional, behavioral, structural, and information models of all business processes of the organization together with models and models of connected support is called organization metadata. Metadata are the basis for organizing current management and future development. The tasks of dividing the system into subsystems for organizing monitoring of functional security and using monitoring data to determine the root cause of the failure have been solved.
Keywords: information support of business processes; functional safety monitoring; large service systems; metadata
- D. V. Smirnov
- A. A. Grusho
- M. I. Zabezhailo
Abstract: Research aspects of the problem of identifying failures in complex information technology (IT) systems are discussed. A failure is understood as an abnormal mode of operation of the IT infrastructure, in which the specified functionality of the business processes supported by it is not provided but the existing means of monitoring the functioning of the IT infrastructure do not raise alarms. In such situations, the conclusion about the failure can be formed only by indirect data, in particular, by the reaction of users contacting the support service, etc. The tasks of building identification systems for such abnormal situations, the so-called downdetectors, are considered in the context of some research problems of modern artificial intelligence: intellectual analysis of natural language texts, identification of cause-and-effect relationships in the analyzed data, training on precedents in open subject areas, etc. The paper proposes directions of scientific research and formulation of tasks, the solution of which is necessary to significantly increase the efficiency of detecting failures using downdetector methods.
Keywords: information infrastructure; indirect data monitoring; downdetectors; cause-and-effect; artificial intelligence
- V. E. Gavrilov
- A. A. Zatsarinny
Abstract: The article is devoted to the consideration of the features of ensuring the functional safety of automated systems both with and without the use of artificial intelligence technology. The factors affecting the quality of functional software in both cases are compared. It is shown that most of the attacks specific to artificial intelligence systems are blocked by standard means of protecting information from unauthorized access. The effectiveness of protection against an evasion attack is determined by the quality of the artificial intelligence system and the data used for training. For automated systems without the use of artificial intelligence technology, evasion attacks are also relevant and the effectiveness of protection against them is determined by the quality of functional software.
Keywords: artificial intelligence systems; information technology security; functional security; software quality; attacks; information protection
- S. V. Listopad
- I. A. Kirikov
Abstract: The complexity of automatic solution of practical problems is largely due to their weak formalization and sometimes, the absence of a clear statement at the time of their occurrence. As a result, significant time and labor costs are required for formulation, identification of the composition and structure of the problem, selection or development of methods relevant to its parts, as well as their synthesis. The paper considers the concept of the problem and develops its macro- and microlevel models, an analysis of the methods of automatic and automated identification of its structure is performed for their possible use in hybrid and synergetic artificial intelligence systems, in particular, hybrid intelligent multiagent systems for solving weakly formalized problems.
Keywords: problem; complex task; decomposition; reduction; team of specialists; hybrid intelligent multiagent system
Abstract: The article is devoted to probabilistic (analytical) and statistical modeling methods in implicit (continuous, discrete, and continuous-discrete) stochastic systems (StS). A survey in the fields: method of probabilistic modeling (MPM) and method of statistical modeling (MSM) is given. Basic implicit StS reduced to differential, discrete, and continuous-discrete are considered for smooth StS. Main attention is paid to
 accuracy. Special attention is paid to the nonsmooth implicit StS. The methods of linear and polynomial regression were implemented. The example is devoted to scalar implicit StS with smooth and nonsmooth functions. Basic conclusions and directions of combined MPM and MSM for StS with inclusions generalizations are given. Canonical expansions of applications to MPM and MSM are suggested.
Keywords: implicit stochastic system; method of probabilistic modeling; method of statistical modeling (MSM); stochastic system with unsolved derivatives (StS USD); strong and weak approximations
Abstract: The paper is devoted to probabilistic and statistical modeling methods of stochastic processes (StP) in continuous and continuous-discrete implicit hereditary stochastic systems (StS). A survey of methods for probabilistic modeling (MPM) and methods for statistical modeling (MSM) in hereditary StS (HStS) is given. Basic differential implicit HStS are considered. Two practical methods of implicit HStS reduction to differential StS are presented. For smooth and nonsmooth implicit functions, MPM based on the normal approximation method are given for various stages of reduction. Stationary and nonstationary StP are considered. Numerical MSM of various accuracy for reducible differential HStS are considered. Both MPM and MSM for systems described by continuous-discrete implicit equations are given. An illustrative example for scalar integrodifferential with smooth and nonsmooth implicit HStS is presented.
Basic conclusions and directions for future investigations are discussed.
Keywords: hereditary stochastic system (HStS); implicit stochastic system; method of probabilistic modeling (MPM); method of statistical modeling (MSM); stochastic process (StP)
- I. N. Sinitsyn
- V. I. Sinitsyn
- E. R. Korepanov
- T. D. Konashenkova
Abstract: The paper is devoted to the new synthesis method for linear optimal stochastic systems according to the criterion of minimum mean square error (MSE) and neural network technology. It is supposed that one-dimensional input signal is the sum of known signal and additive Gaussian noise. Noise is independent of signal parameters. At output, it is necessary to perform corresponding input transformation. The paper describes architecture of three-layer wavelet neural network (WNN) with one reserved layer. The activation function of reserved layer is described using orthonormal wavelet basis with compact carrier. For WNN functioning, a tutoring algorithm based on the method of quick descend is used.
The MSE optimal operator is constructed. The MSE estimate is presented in the form of linear combination of basis wavelet functions. An illustrative example is given. The basic results are formulated and discussed.
Keywords: canonical expansion; mean square estimate; modeling; optimal estimate; optimal system; stochastic process; stochastic system; wavelet; wavelet- neural network
Abstract: Statistical analysis is an indispensable element in the construction of a mathematical model of the object under study. Queuing systems as an object of research have specific features that make it necessary to go beyond the general theory of stochastic processes. The article discusses the construction of the models of the input flow of multiprocessor systems based on the trace of the real workload of the Mustang cluster obtained as a part of the Atlas project (www.project-atlas.org). Mustang data features include a long observation period, an impressive amount of data collected, a wide field of research due to the simplified nature of previous studies and fuzzy conclusions already made, the combination of fragments with different flow intensities, the presence of stationary and nonstationary areas, and the inapplicability of the simple Poisson flow model. As a solution to the problems that arise for stationary data fragments, it is proposed to use the branching Poisson process model. The well-known methods of estimating the model parameters are supplemented by the procedure for refining estimates and formalized methods of confirmatory analysis. Given the large amounts of data being processed, it is important to build effective algorithms for calculating the characteristics of streams and smoothing out sample indicators.
Keywords: trace repository; LANL Mustang cluster; branching Poisson process (BPP); statistical analysis of series of events
- Yu. A. Stepchenkov
- Yu. G. Diachenko
- N. V. Morozov
- D. Yu. Stepchenkov
- D. Yu. Diachenko
Abstract: The article is devoted to the problem of self-timed (ST) binary up counter implementation. The ST circuits are an alternative to the synchronous ones when implementing digital units. The ST basis ensures stable operation of a digital unit regardless of any delays in the internal logical cells. A two-phase operating discipline and full indication of all circuit's switches provide such behavior but they require some hardware redundancy. In terms of permissible operating conditions including supply voltage and ambient temperature, ST circuits have a significant advantage over synchronous counterparts. Sequential ST counters are less redundant than combinational ST circuits due to the simpler indication subcircuit. Their synthesis is quite simply formalized on the readymade counting ST flip-flops basis. However, to implement their ST preset, one should perform a certain time sequence of their inputs. The article considers the circuitry basis for the ST up counter implementation and proposes optimal circuitry solutions in terms of hardware complexity that provide ST counter preset.
Keywords: self-timed circuit; binary counter; indication; preset; hardware complexity; performance; self-timed analysis
Abstract: The article is devoted to the practical implementation of a technique for modeling efficiency in an air transport system (ATS). Air transport system is an important component of the socioeconomic development of any country and tools for modeling and analyzing the state of such complex systems allow solving a wide range of tasks — from assessing the quality of activities to optimizing management and forecasting results. The main attention is paid to the development of a software package for situational modeling of the quality of passenger transportation of the ATS of the Russian Federation and demand for them. The proposed version of the software package allows one to evaluate its functioning according to various efficiency criteria. The key implemented functional blocks are described: the module for assessing the quality of the air transport network for passengers and the module for assessing the potential for changes in demand for transportation when replacing existing types of aircraft with promising aircraft. The developed components operate with statistical information about air transportation available for collection or acquisition through a designed database.
Keywords: mathematical modeling; air transport system; software package; database
Abstract: An approach to study of online encyclopedias as S-symbolic knowledge systems is proposed. The online encyclopedia is considered as an updatable collection of hypermedia information resources designed in the form of a web site and united by the rules of creation, modification, classification, search, and use of resources. The rules define the functional requirements for the online encyclopedia software (as a web system) implemented as an online encyclopedia engine. The results of a comparative analysis of the conceptual, organizational, and technological foundations of three modern Russian universal online encyclopedias (The Great Russian Encyclopedia (electronic versions 2017 and 2022), Runiversalis, and Ruwiki) are presented. The examples of successful and erroneous decisions affecting the prospects for the development of online encyclopedias are given. Among urgent organizational problems, the task of attracting experts to create and review encyclopedic resources is highlighted. To solve it (with the existing system of evaluating the effectiveness of scientific activities of employees of research and educational institutions), it is advisable to take into account expert publications in Russian online encyclopedias.
Keywords: online encyclopedia; web system; S-symbolic knowledge system; hypermedia information resources; online encyclopedia engine; expert publications of online encyclopedias
|
