Objectives. The exponential growth of urbanized territories and urban populations required the development of new models and methods for describing and optimally managing the risks of modern cities as large and complex social, technological, and logistical systems. The paper is devoted to the problem of analyzing the risks of the development of a "smart city" as a complex sociotechnical system from the standpoint of the hypothesis of seven generations of "smart cities" using elements of mathematical modeling.
Methods. The analysis of literary sources, modeling the seven generations of the "smart city" as a complex sociotechnical system based on linear differential equations and a numerical analysis of the development of the "smart city" concept are used.
Results. The general characteristics of the "smart city" concept are presented and the risks of disruption of services and processes of the "smart city" are considered. The hypothesis of seven generations of the "smart city" is substantiated. Systems of linear differential equations have been developed that characterize each of the generations of the "smart city". An approach to modeling and assessing the integrated risk of a "smart city" is proposed.
Conclusion. Systems of linear differential equations have been developed that characterize each of the seven generations of the "smart city", as well as the risks associated with them. A generalized model of integrated risk assessment of a "smart city" as a complex sociotechnical system based on a nonlinear differential equation is proposed. The fundamentals of the methodology for managing the risks of disorganization of services and life processes for different generations of the "smart city" as an evolving sociotechnical system are formulated

Objectives. At present, rapid detection of the location and size of building objects from remote sensing images is important for scientific research value and has practical significance for urban planning, environmental monitoring and disaster management.
Methods. This paper proposes an object detection method based on improved YOLOv10 network, which incorporates Super Token Attention, RepConv and Normalized Weighted Distance to more precisely detect buildings in remote sensing images. This method improves the detection accuracy and efficiency especially for small objects. The LEVIR-CD dataset is used for model training and testing.
Results. The experimental results show that the method demonstrates better accuracy on the building detection task than the traditional YOLOv10 and other methods.
Conclusion. The proposed method significantly enhances the accuracy and efficiency of building detection in remote sensing images

Objectives. The problem of computation of the main probabilistic characteristics of operation of a semi-open queueing network, in which the intensity of the input flow to the nodes has several possible levels, is considered. When the changing the level of flow intensity occurs, it is possible to change the rate of requests service in the nodes in order to optimize the network functioning.
Methods. The solution is based on the apparatus of multidimensional Markov chains with continuous time and a special block structure of the infinitesimal generator.
Results. The generator blocks of this chain are calculated using algorithms and formulas, which allows the invariant probability distribution to be determined. Formulas for calculating the main characteristics of network performance using the known invariant probability distribution of the states of the Markov chain are derived. A numerical example is provided to illustrate how the dependence of the main characteristics of network performance depend on the throughput of its nodes. Using the selected economic criterion for network performance quality, it is demonstrated that the redistribution of network resources between its nodes can be optimised with the change of the arrival flow level.
Conclusion. The obtained results can be used to optimize the functioning of various real objects described by semi-open queueing networks, for example, telecommunication and logistic systems, mobile robotic fulfillment systems, by adapting the distribution of network resources between its nodes to the changing rate of incoming requests

Objectives. The problem of constructing controlled random tests is solved by two-dimensional scaling of initial templates using Hadamard matrices. The limitations of classical approaches to generating test patterns based on enumeration of candidates for test patterns are shown. With an increase in the threshold values of the difference measures of binary test patterns, the computational complexity of constructing such tests increases. The main goal of this article is to develop methods for constructing tests based on initial templates and their expansion to the required bit size based on the application of formal rules.
Methods. For two-dimensional scaling of initial templates with specified Hamming distance thresholds, Hadamard matrices and the Sylvester recursive procedure for their construction are applied. The experimental research employed the method of statistical trials.
Results. It is demonstrated that methods for constructing controlled random tests based on templates can be viewed as a procedure for scaling controlled random tests to the required bit size. Both templates characterized by the minimum bit size of patterns and any controlled random tests are used to construct the desired tests. The procedure itself is characterized as one-dimensional scaling, which increases the bit size of patterns while maintaining their quantity. To simultaneously increase the bit size and quantity of test sets, a method based on two-dimensional scaling of templates using Hadamard matrices is proposed. This allows for the construction of controlled random tests without the labor-intensive process of enumerating candidate test patterns and computing their difference measure values. It is shown that the unique orthogonality property of Hadamard matrices, as their order increases, enables achieving ratios of the average Hamming distance between test patterns to their bit size close to 1/2. It is noted that the characteristics of the initial templates do not significantly affect the characteristics of the resulting tests constructed using Hadamard matrices obtained through the Sylvester recursive procedure. The feasibility and efficiency of the proposed approach to constructing controlled random tests are evaluated for the case of testing memory devices. It is demonstrated that controlled random tests constructed using Hadamard matrices have significantly higher coverage capability compared to random tests.
Conclusion. An approach for generating test patterns in the formation of controlled random tests using Hadamard matrices is considered. The proposed approach is based on two-dimensional scaling of initial templates using these matrices. It is shown that the use of various templates and their two-dimensional scaling allows for the construction of controlled random tests with the required bit size of test patterns and a larger number of them

Objectives. High-throughput sequencing methods have recently become widely used in the fundamental and applied research of various human diseases. Sequencing of functionally significant regions of the human genome enables the simultaneous identification of multiple genetic polymorphism sites that have diagnostic and/or prognostic significance for human genetic diseases. One of the key goals in this area is to develop efficient software tools for processing genomic data and identifying single nucleotide polymorphism sites using computer modelling and big data analysis methods.
Methods. A software complex has been developed for simulation modelling and identification of single nucleotide polymorphism sites using machine learning methods. The methods for the approach to simulation modelling and analysis of single nucleotide polymorphism sites in DNA molecules are implemented based on the beta or normal distributions, the parameters of which are determined from the available experimental data, and machine learning models trained on simulated data and used to accurately identify single nucleotide polymorphism sites. The software complex includes an R package, a web application, and auxiliary computational tools for processing experimental genomic sequencing data.
Results. The performance of the developed software complex was tested on sets of simulated and experimental data from human cell genomic sequencing. A comparative analysis of the most effective algorithms for identifying single nucleotide polymorphism sites was performed. The best results were obtained for machine learning models.
Conclusion. The use of the software complex increases the accuracy of identifying genetic polymorphism sites during the analysis of big genomic sequencing data. The software can be used for modelling synthetic data, based on experimental data or independently, for the purpose of comprehensive testing and selection of the best algorithms for identifying single nucleotide polymorphisms, as well as for generative data modelling used in training identification algorithms based on machine learning methods

Objectives. The purpose of the analytical and research work carried out is to design and implement a prototype system for establishing user identity and privileges based on the joint use of passwordless FIDO2 authentication and attribute-based access control. It is proposed that electronic identification means compliant with ICAO standards be used as a source of user attributes.
Methods. The following were used in this paper: systematization and analysis of literature and technical specifications; systematic approach to the analysis of existing implementations of passwordless attribute access systems and theoretical models used in their design; the SCn- and SCg-code of OSTIS technology for semantic description of basic concepts and concepts related to FIDO2-authentication; software platforms and libraries.
Results. The result of the work is a prototype of the system of attributive access to information resources in the digital environment using the eID-card of the Republic of Belarus and FIDO2-authentication. The developed application was containerized and deployed on the online server. Its performance was then tested from different platforms using standard browsers.
Conclusion. A study on the development and initial evaluation of a prototype of an information resource access control system based on authentication to the FIDO2 specification and an attribute-based access control model is presented. At the same time, as a source of user attributes the means of electronic identification that meet the standards of the International Civil Aviation Organization, including the eID-card of the Republic of Belarus, are used