Proceeding of the Institute for Systems Analysis of the Russian Academy of Science

Theoretical and applied approaches to assessing synergy effects under organizational activity are researched based on the models and techniques of the modern natural monopoly theory for solving problems of analysis and strategic design for infrastructure subsystems. The relationships between adequate theoretical foundation of effective market organization and the approaches to assessing natural monopoly synergy are analyzed. Within the normative identification, approaches to assessing the synergetic effects using key technological determinants/ natural monopoly activity indicators have been elaborated. The directions are determined for analyzing factors associated with assessing synergy effects within the framework of theoretical concepts of behavioral identification, and, accordingly, expanding the set of using characteristics. Some measures of state regulation related to the formation of market economic behavior of natural monopolist, primarily pricing behavior, are highlighted; these measures determine the possibility of adjusting estimates of synergy effects under organizational activity.

The article formalizes the task of generating output (reporting) forms of documents based on dynamically changing data storage structures in information systems. An approach to automating the process of generating output forms is proposed. The data structures necessary and sufficient for representing digital data of information systems in output (reporting) documents are considered. The advantage of the proposed approach is the simplification and significant acceleration of the process of generating output forms, which is currently quite labor-intensive.

A set of new numerical methods for solving linear differential-algebraic equation systems is developed. Homogenous systems can be solved, and nonhomogeneous systems with piecewise-polynomial right-hand side function. Calculation of system state at each integration step requires solving one or several (depending on the method order) systems of linear algebraic equations. The methods are based on decomposition of Pade approximation of the matrix exponent to simplest fractions. The proposed formulas make possible to avoid conversion of the differential-algebraic equation system to the ordinary differential equation system at the stage of system solving. The new methods are equivalent to some well-known Runge-Kutta type methods like Radau and Lobatto methods in terms of accuracy and steady areas. However, new methods are much more simple in theory and practical implementation, and they require several times less computational work. Methods with diagonal Pade approximations are A-stable, and methods with subdiagonal Pade approximations are L-stable. New methods can be used for solving stiff, oscillative and stiff-oscillative systems.

Modern methods for detecting text in images are based on computationally expensive deep learning models and require a large amount of training data, including real data. In the case of text retrieval in arbitrary scenarios, the process of collecting and annotating real data for training is extremely labor-intensive and expensive due to the high variability of possible scenes. This paper presents a new method for detecting text in arbitrary images, which does not require photographs of text in real scenes to be trained and can be trained on simple synthetic data in the form of strings. The proposed neural network model is 42 times smaller than the text detector in one of the best text recognition systems in terms of quality and speed, PaddleOCR (84 KB versus 3.6 MB), which makes it an excellent choice for mobile devices. The model was tested as part of a phone number recognition system, where with its help it was possible to achieve 80.35% of correctly recognized numbers.

The paper deals with the problem of analyzing the nature of data arising at the boundary of knowledge and being. It shows the contradictory view of data science as a set of technologies and algorithms designed to solve problems of processing large amounts of poorly structured data, predicting correlations unrecognised earlier. The etymological and cognitive analysis of the transformation of the concept “data” is presented. The conceptual foundations of the formation of a new epistemological paradigm for displaying the surrounding world, which allows us to consider the problem of data in a new way.

The work presents an nested contours algorithm designed for detecting pathological changes that may correspond to breast cancer on X-ray mammographic images, and provides the results of evaluating its generalization ability. This algorithm was tested on a large dataset of mammographic images with all possible variations of changes corresponding to verified breast cancer, including faintly visible and invisible ones. The overall detection accuracy of the algorithm was 90.73% for film and 96.82% for digital mammograms. A comparative analysis of using this algorithm and other modern methods of change detection on mammograms, with publicly available databases (INbreast and CBIS-DDSM), is also provided. The higher accuracy of the proposed algorithm is demonstrated. The high efficiency of detecting pathological changes, regardless of the differences in mammogram characteristics obtained from different systems, indicates the high generalization ability of the proposed algorithm.

This article highlights the significance of integrating DevSecOps (Development, security and Operations) practices into the research on detecting common attacks in Kubernetes environments. As Kubernetes gains rapid traction as a prominent container orchestration platform, the security challenges associated with containerized applications have grown in magnitude. However, traditional security methodologies often struggle to keep pace with the dynamic and fast-evolving nature of containerized environments, leaving potential vulnerabilities for malicious actors to exploit. By emphasizing the importance of DevSecOps, this article aims to underscore its role in improving the security posture of Kubernetes deployments and promoting a proactive approach to safeguarding containerized applications. The article also discusses key considerations and benefits of implementing DevSecOps in the context of Kubernetes security research.