Eastern-European Journal of Enterprise Technologies

Designing the structure and architecture of situation-aware security information systems for residential complexes

Nataliia Kunanets — 2025-02-28

Security information systems constitute a significant application domain for the concept of situational awareness. The object of this study is security information systems for residential complexes. The task addressed involved devsigning an efficient, flexible, and adaptive structure to ensure situational awareness in security information systems. Unlike existing systems, this structure is based on the integration of intelligent agents, server services, and a central unit that interacts with the Internet of Things (IoT) network. The proposed system ensures the autonomy of intelligent agents, which perform specialized tasks using integrated intelligent sensors, while server services handle basic computational tasks such as machine learning, pattern matching, and model construction. The central unit aggregates information, implements reasoning procedures, and identifies situations for the entire system.

An architecture has been proposed that includes three main subsystems: video surveillance, access control, and operator service management. The essence of the results is the development of a flexible architecture that effectively combines IoT technologies with the situational awareness approach.

The research results were achieved by integrating innovative approaches such as the use of intelligent agents, machine learning, and situational analysis, enabling a flexible distribution of functions among system components depending on the specific task requirements. The distinctive features of this architecture facilitate the implementation of the situational awareness principle and support continuous system learning processes.

Given its modular architecture, the proposed system could be applied in extensive residential networks serviced by Internet providers, as well as in associations of co-owners of multi-apartment buildings. The formalization of architectural elements simplifies the process of designing and deploying systems, making them accessible for a wide range of applications in residential complexes by Internet service providers

Estimation of software structures dimension influence on data processing time increasing

Yevhen Danylets — 2025-02-28

The object of the study is the phenomenon of an extreme increase in the time of program code execution at certain sizes of data processed by it. The problem to be solved was to verify the general nature of the phenomenon for different equipment.

The evolution of modern computing technology, its RAM often takes place in an extensive way – by increasing the number of structural elements. Problems can manifest themselves in the fact that periodic processes in the code begin to exhibit a resonance effect, which leads to different indicators of data processing time, the sizes of which are multiples and non-multiples of the block structures. The work is studied the influence of the dimensionality of data blocks on the speed of execution of the cycle that iterates them. The tools of differential regression analysis are used. Experiments were carried out on equipment with different architecture, type and amount of RAM, running different operating systems. In all of them resonant effects were revealed. It led to differences in the average code execution time by 1.6–3.6 times, and the time of memory access operations increased up to 136 times. Special attention was drawn to the fact that the increase in operating time was found for structures whose size is a power of two multiple (2^N), specifically for the values 512 and 1024. These dimensions are present in many types of tasks, in particular, cryptographic purposes or stream-based data processing. Following the recommendations given in the paper can help identify time delays in applications, and improve the performance of applications by eliminating them

Development of post-quantum cryptosystems based on the Rao-Nam scheme

Yevhen Melenti — 2025-02-28

The object of the research is the process of ensuring the protection of data transmission in communication channels of critical infrastructure objects based on mobile and smart technologies. The development of quantum computing technologies based on Grover and Shor algorithms provides practical cracking of symmetric and asymmetric cryptosystems in polynomial time. The emergence of systems based on artificial intelligence allows creating hybrid systems for detecting weaknesses (critical points) in security systems not only on critical infrastructure objects. In addition, a full-scale quantum computer will open a new era of implementing post-quantum cryptography algorithms. Among the winners of post-quantum algorithms, the crypto-code constructions (CCC) of McEliece and Niederreiter are separately highlighted, which allow to provide the required level of protection and the required level of reliability of information transmission in an integrated manner. But a significant drawback is the possibility of cracking such systems on linear codes, as well as the need to build them on the Galois field 2¹⁰–2¹³, which significantly reduces their use in low-capacity systems based on smart and mobile technologies. To solve this drawback, the work proposes the use of a symmetric CCC based on the Rao-Nam scheme on algebrogeometric and flawed codes, which provides the possibility of significantly reducing the volume of key data (construction of CCC over the Galois field 2⁴–2⁶). When using the Rao-Nam CCC, a quantum symmetric algorithm is formed, which ensures the preservation of the level of stability and reliability of information transmission (safe time 10²⁵–10³⁵). This approach provides the possibility of forming intelligent information protection systems (IIPS). The given structural scheme of the IIPS construction ensures timely detection of threats with an assessment of the computational and financial and human capabilities of attackers, as well as the use of the necessary CCC/algebraic (flawed) codes to ensure the required level of security

Improving the process of control and correction of errors in non-positional code structures

Alina Yanko — 2025-02-28

The object of this study is the processes of operational control and correction of data errors in non-positional code structures (NCS). Based on a critical analysis of the existing data control method based on the use of the projection of a number in RCS, limited control efficiency and the ability to detect only single errors have been established.

The study improves methods for rapid control and data correction of a real-time computer system (CS) operating in a non-positional number system, in the so-called residual class system (RCS). A comprehensive approach to control and eliminate errors in RCS is built on the basis of non-positional coding, underlying which is the Chinese residual theorem. This theorem proves that NSC is the next stage in the development of the theory of information control using arithmetic control by modulus. The use of the property of complete arithmetic of NSC has made it possible to improve the method and increase the efficiency of data control due to information processing in RCS without controlling each intermediate result obtained. Comparison with the most efficient existing method has made it possible to establish that the devised method provides an increase in the speed of data control by 1.2–1.3 times.

An effective process of operational and accurate error detection based on an improved method of data control in RCS, which is based on the use of the corrective properties of NCS, has been proposed. Parallel error correction in NCS increases the efficiency of error correction by 2 times, due to a decrease in the number of intermediate operations in the improved method. At the same time, with an increase in the bit grid of the operands being processed, the efficiency of the application of the considered error correction process improves

Devising a method for determining the coordinates of an air object by a network of two SDR receivers

Hennadii Khudov — 2025-02-28

The object of this study is the process of determining the coordinates of an air object. The main hypothesis of the study assumed that the use of a network of two Software-Defined Radio (SDR) receivers would make it possible to determine the coordinates of an air object. The determined coordinates could be used as preliminary target designation for the radar.

A method for determining the coordinates of an air object by a network of two SDR receivers has been improved, which, unlike the known ones, involves:

– using signals from the airborne systems of the air object;

– using SDR receivers as network elements;

– using the triangulation method for determining the coordinates of an air object.

The accuracy of determining the coordinates of an air object by a network of two SDR receivers has been assessed. It was found that:

– the accuracy of measuring the coordinates of an air object decreases sharply as the polar angle of observation from the middle of the base approaches 0 or π;

– the smallest coordinate measurement error can be ensured when the air object is located on the traverse to the middle of the base and when the distance to the air object is close to the base size;

– with small bases, the non-uniformity of the dependence of the coordinate determination error on the position of the air object relative to the SDR receivers is more pronounced than with large ones;

– at a long range, the error values for small bases grow rapidly, which is primarily due to the small angle of intersection of the bearing lines;

– it is advisable to place SDR receivers at a sufficiently large distance from each other (recommended value: (1–3) times the distance to the air object);

– the errors of measuring the coordinates of the air object have a value of (250–350) m in a sufficiently wide range of directions;

– with a decrease in the base size, the errors grow rapidly (reaching a value of more than 1000 m) when the observation angle deviates from the 90° direction

Implementation of advanced vibration analysis techniques for predictive maintenance of rotating machinery

Gulsim Rysbayeva — 2025-02-28

This study focuses on the predictive maintenance of rotating machinery – a fundamental asset in industries such as manufacturing, energy production, and transportation. The problem addressed is the frequent occurrence of undetected faults, such as bearing defects and shaft bending, which can lead to unexpected downtime and significant maintenance costs due to the limitations of traditional diagnostic methods in complex, noisy environments. To overcome these challenges, an integrated framework was developed that combines advanced vibration analysis techniques (including wavelet transforms and matching pursuit) with a suite of state-of-the-art machine learning models, including Random Forest, Support Vector Machine (SVM), Gradient Boosting, Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM). This innovative approach, characterized by robust feature extraction and data-driven modeling capabilities, achieves fault detection accuracies of up to 97 %, distinguishing it from conventional solutions. The findings demonstrate that the improved accuracy and reliability of the proposed framework effectively address long-standing issues related to incomplete fault detection and downtime in maintenance processes. By providing a scalable, noise-robust solution, the study contributes to industrial systems through significant reductions in operational overhead and downtime, thereby maintaining core business operations at peak performance

Development of in-pipe defects detection and classification system

Perizat Rakhmetova — 2025-02-28

The object of the research is in-pipe defect detection and classification. The primary problem to be solved is the inefficiency, high cost, and inaccuracy of traditional manual inspection methods, which are often time-consuming and prone to human error. The results obtained include the creation of a multi-modal platform that integrates Red-Green-Blue (RGB) imaging and depth data with advanced artificial intelligence algorithms, Canny edge detection, and Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering, achieving a 93 % mean Average Precision (mAP) in detecting and classifying various defects such as cracks, corrosion, and debris. A brief interpretation of the findings reveals that the high performance is due to the synergy between multi-modal sensing, artificial intelligence pattern recognition, and robust robotic navigation. This integrated approach ensures that the system not only detects defects accurately but does so in real time. Features and characteristics of the obtained results that directly address the identified problem include real-time high-precision defect identification, and reduced inspection downtime. As a result, inspection time is shortened, costs are lowered, and the safety of the pipeline system is increased, leading to accurate measurement of indicators (93 % mAP) and a reduction in occupational safety risks. The developed system is designed for use in traditional industrial environments, especially in large pipeline networks and in conditions where traditional methods are ineffective

Development of an information system for blood bag screening as an important step in blood transfusion handling in Indonesia

Andiani Abimanyu — 2025-02-28

The implementation of blood bag screening test is very important to identify and prevent transfusion-transmitted diseases such as hepatitis B, hepatitis C, HIV, and syphilis. This paper discusses the development of a blood bag data filtering information system in Indonesia. The object of this research is the management of blood donor and blood bag data.

The results of this study indicate a better operational framework, accurate data management and timely decision-making, related to the safety of blood services. By using modern programming languages such as PHP with the Laravel framework and leveraging the MySQL database, this system integrates blood donor management and screening test results, significantly reducing the risk of disease transmission.

The main feature of this system is its ability to effectively integrate donor data and screening results, which allows real-time access and decision-making. This feature enables the system to solve problems previously identified by conventional methods, significantly reducing the risk of errors and disease transmission. The results of the study indicate that the system can be implemented effectively in the internal environment of blood transfusion units in Indonesia, thereby improving operational services and comprehensive reporting. Hence, proper data and information management will result in better decision-making in the health sector, especially in maintaining high blood safety standards. Thus, this study highlights that the developed information system plays an important and effective role in strengthening blood transfusion management in Indonesia, opening up opportunities for continuous training of health workers