Abstract. Traditional PID controllers remain widely used in embedded flight control and stabilization systems. However, in small aircraft Attitude and Heading Reference Systems (AHRS), classical PID approaches are insufficient under sensor noise, drift, vibration, and energy limitations typical for lightweight avionics platforms.
This paper proposes a context-aware, risk-sensitive PID framework for AHRS modernization. The controller integrates sensor reliability estimation, energy-aware modulation, and multi-objective optimization into the PID decision logic. The method reduces oscillatory corrections caused by gyroscope and accelerometer noise while preserving attitude tracking accuracy. Simulation results demonstrate reduced integrated control energy, lower multi-objective cost, improved stability, and enhanced robustness under sensor uncertainty typical for MEMS-based AHRS systems. The proposed structure transforms PID from a purely error-compensation mechanism into an intelligent stabilization module suitable for modern small aircraft avionics.
Keywords: PID controller, AHRS modernization, small aircraft stabilization, contextual control, risk-aware control, energy-efficient avionics, sensor reliability, multi-objective optimization.
Abstract. This paper considers the problem of automated assessment of atmospheric transparency in urban conditions based on images obtained from an unmanned aerial vehicle, using computer vision and deep learning methods. The study explores an approach focused on analyzing visual signs of smoke near the horizon, where the concentration of aerosol pollution is usually most pronounced. For the experimental study, a specialized dataset was formed, including aerial photographs of the urban atmosphere of Almaty taken in January-February 2024, followed by spatial division of the images into nine sectors and manual visual assessment of the transparency level on a discrete scale. This method of marking allowed us to record the spatial heterogeneity of pollution within a single frame and take into account the differences between the sky background, the horizon line, and urban development. Based on the pre-trained MobileNetV2 architecture, two model variants were implemented — classification and regression — which made it possible to compare discrete and continuous approaches to the interpretation of visual information. A comparative analysis showed that the classifier provides higher accuracy of strict class matching (83.9%), while the regression model, when rounding predictions to whole values, demonstrates higher accuracy within a tolerance of ±1 class (97.2%) and a lower level of systematic errors. The results confirm the promise of using UAVs in combination with computer vision methods for local monitoring of atmospheric transparency and highlight the potential of this approach as a supplement to traditional ground-based environmental monitoring systems in urban environments, which is particularly relevant given the limited density of stationary stations.
Keywords: air quality monitoring, UAV data; computer vision; atmospheric transparency, smog; deep learning.
Abstract. The continuous growth of unstructured textual data volumes in aircraft maintenance systems creates a demand for automated analysis methods. Traditional defect categorization using standard codes is often insufficiently detailed to reveal the true root causes of failures, as routine operations and critical malfunctions are frequently combined within a single system category. The subject of this study is the semantic structure of textual fault descriptions related to the exterior lighting system (ATA 33–40) of an aircraft fleet of a single model. The objective of the study is to develop and validate a method for the automatic identification of latent operational patterns and failure modes without the use of labeled data. The methodological foundation of the research is probabilistic topic modeling based on the Latent Dirichlet Allocation (LDA) algorithm. To improve model quality, a specialized text preprocessing procedure was implemented, including the expansion of industry-specific abbreviations and the removal of contextual noise. The optimal model configuration was determined through quantitative analysis of the topic coherence metric (Cv) and an assessment of topic semantic stability. Experimental results show that a six-topic model provides the highest level of interpretability. Analysis of the resulting clusters made it possible to identify design-related defect occurrence zones and to classify failures according to their manifestation type. Latent subgroups corresponding to electrical circuit failures and mechanical damage to structural components were automatically identified. The proposed approach enables the transformation of unstructured maintenance personnel records into detailed diagnostic information, thereby creating opportunities to improve maintenance programs and to transition toward predictive reliability management of specific aircraft subsystems.
Keywords: aircraft, maintenance, external lighting, textual descriptions, natural language processing, topic modeling, Latent Dirichlet Allocation.
Absract. In the context of increasing air traffic intensity and the growing proportion of night and long-haul flights, the management of crew fatigue is becoming a critically important factor in ensuring flight safety. Crew fatigue is recognized as a significant factor affecting the reliability of flight operations and decision-making processes. At the same time, traditional working time limitations do not provide a comprehensive assessment of fatigue-related risks, which necessitates the implementation of integrated approaches. Modern methods, including heart rate variability (HRV) analysis and simulation modeling, enable a more accurate assessment of the functional state of crew members and facilitate the identification of fatigue formation patterns. The research problem lies in the limitations of the prescriptive approach based on Flight Time Limitations (FTL), which does not account for physiological and circadian characteristics of humans. The aim of this study is to develop recommendations for assessing crew fatigue levels in airlines of the Republic of Kazakhstan based on an integrated model consistent with international standards of ICAO, IATA, and EASA. The objectives include the analysis of international fatigue management approaches, the development of a mathematical model of the fatigue index, its statistical validation, and the formulation of practical recommendations. The research methods include multiple and logistic regression, ROC analysis, calculation of sensitivity and specificity, Monte Carlo simulation, and heart rate variability (HRV) analysis. The results demonstrated the superiority of the integrated FRMS model (AUC = 0.623) compared to the prescriptive FTL-based model (AUC = 0.574). Simulation modeling showed a reduction in fatigue risk by up to 17% under optimized scheduling conditions. A statistically significant relationship between fatigue, night workload, and decreased HRV was identified. It is concluded that the implementation of an integrated fatigue index within the safety management systems of airlines in the Republic of Kazakhstan is justified. The proposed recommendations enable a transition to proactive fatigue risk management and are consistent with international standards.
Keywords: crew fatigue, fatigue risk management, safety management system, working time limitations, heart rate variability, biomathematical modeling analysis, aviation safety.
Abstract. This article examines approaches to improving the reliability and resilience of information exchange for unmanned systems, taking into account the presence of external interference. The primary issue addressed in this article is the analysis of natural and artificial factors that may affect the operation of data transmission channels. Emphasis is also placed on the impact of artificial electromagnetic disturbances. The paper’s scientific innovation is that it considers the unmanned system as a multi-agent environment. The agents are the operator, the aircraft, and the external environment. The goal of the study is to improve the reliability of the data exchange channel by implementing Visible Light Communication technology. To achieve this goal, the authors formalized quantitative control assessment methods, developed a structural and functional model of the control system, and conducted simulation tests to assess risks. An analysis of experimental data and computer modeling demonstrated that Visible Light Communication, operating in the infrared range, provides a stable information exchange channel over a distance of up to 3 kilometers. This result demonstrates the potential of using this technology to build a noise-resistant and secure information exchange channel for unmanned systems.
Keywords: Unmanned aerial vehicle system, Visible Light Communication technology, risk assessment, simulation model, control system model.
Abstract. This work presents a mathematical model for determining the coordinates of integrated groups of unmanned aerial vehicles (UAVs). The main application areas of UAVs and promising directions for the development of unmanned aviation systems, integrating complexes of remotely controlled vehicles, are analyzed. To improve the stability and reliability of interaction in such systems, stable structures of integrated groups are proposed. Special attention is given to methods for modeling integrated UAV groups, including mathematical description and computer simulation. The structures of integrated groups are analyzed, taking into account the criteria of topological stability during movement and the reliability of data transmission channels based on visible light communication (VLC) technologies. To obtain results, mathematical descriptions and corresponding computer models of integrated UAV groups were developed, meeting the criteria of topological stability and reliability of data transmission channels. Modeling was performed in Matlab R2020b, where computer models of UAV swarms were constructed in a three-dimensional coordinate system.
Additionally, the work considers different types of topologies for integrated UAV groups and their impact on the stability and reliability of system performance.
Keywords: method, group of unmanned aerial vehicles, control, model, data transmission channels, artificial intelligence.
Abstract. Reverse supply chains (RSCs) have been increasingly promoted as a mechanism for improving resource efficiency and reducing environmental impacts in mining industries. However, in emerging economies such as Kazakhstan, the economic feasibility of mining waste recycling remains uncertain due to long transportation distances, high operational costs, and limited processing infrastructure. While previous studies have demonstrated the potential of optimization-based reverse logistics models, conversion efficiency is commonly treated as an assumed or fixed parameter rather than a critical feasibility condition. This limits the practical applicability of existing models for decision-makers. This study addresses this gap by conducting a threshold (break-even) analysis to identify the minimum conversion efficiency required for reverse supply chain operations to achieve economic viability in Kazakhstan’s mining sector. Building upon an established reverse supply chain cost structure, the proposed approach evaluates system profitability across a range of conversion efficiency levels under alternative logistics scenarios. The analysis focuses on the relationship between conversion efficiency and aggregated cost drivers, including transportation, processing, and fixed operational costs.
The results demonstrate that reverse supply chain feasibility is highly sensitive to conversion efficiency and that profitability can only be achieved once a clearly defined conversion threshold is exceeded. Below this threshold, improvements in logistics efficiency alone are insufficient to offset total system costs. The findings highlight conversion efficiency as a dominant strategic parameter in early-stage reverse supply chain planning for mining waste recycling. By explicitly defining conversion efficiency thresholds, this study provides a practical decision-support tool for policymakers and industry stakeholders. The results contribute to the development of economically grounded reverse supply chain strategies and support the transition toward sustainable and circular mining practices in Kazakhstan.
Key words: reverse supply chain, conversion efficiency, break-even analysis, mining waste recycling, economic feasibility
Abstract. The development of the global economy, the growth of international trade, and the increasing complexity of supply chains are increasing the strategic importance of transport and logistics systems. As part of these processes, transport and logistics services are becoming a key driver of economic growth for countries with high transit potential. The Republic of Kazakhstan is located in the center of the Eurasian continent and at the intersection of major land routes connecting Europe and Asia. This situation creates objective preconditions for strengthening the country’s role in the system of international transport corridors and effectively utilizing its transport and logistics potential. The purpose of this article is to comprehensively analyze the possibilities for increasing Kazakhstan’s transport and logistics potential in the context of developing international transport corridors and identify priority areas for its implementation. The study examined the operations of the main international transport corridors passing through Kazakhstan, the dynamics of transit freight traffic, and the level of development of transport infrastructure. Particular attention was paid to the role of rail transport and multimodal logistics hubs. The results of the study showed that the country’s transport and logistics potential is currently realized primarily through transit, and the level of added value is limited. In conclusion, it was substantiated that improving transport infrastructure, developing a network of logistics hubs, and introducing digital technologies are the main conditions for increasing Kazakhstan’s competitiveness in the international transport system.
Key words: transport and logistics potential, international transport corridors, transit, rail transport, multimodal transportation, logistics hub, transport infrastructure.
Abstrakt. The article addresses the issues related to the study of digital logistics and the analysis of the degree of implementation of modern technologies in the transport and logistics sector of Kazakhstan. The research is based on an assessment of the interconnection between technological readiness, innovation-driven development, and logistics efficiency. Since the late 1990s, when the concepts of internet technologies and the digital economy were first widely discussed, significant transformations have taken place, fundamentally reshaping business processes and consumer practices. Over more than two decades, digitalization has evolved into a crucial driver of competitiveness and efficiency in transport logistics. Today, digitalization is no longer perceived as an innovative phenomenon but as a normative standard of industry development. Practical examples include electronic tickets, online passenger check-in systems, digital navigation platforms, and mobile applications for taxi services. These technologies, which once appeared unattainable, are now integrated into everyday logistics operations and consumer practices. At the same time, the ongoing digital transformation is increasingly oriented towards the adoption of advanced solutions, such as unmanned vehicles, intelligent traffic management systems, and smart transport infrastructure capable of monitoring compliance with traffic regulations. Digital platforms are becoming a cornerstone of the modern global economy by ensuring transparency, accessibility, and efficiency of logistics chains. Their role is particularly significant in enhancing the integration of Kazakhstan’s transport and logistics system into global supply chains, thereby supporting sustainable economic development and strengthening the country’s transit potential.
Keywords: digital logistics, digitalization, innovation, transport infrastructure, freight transportation.
Abstract. At present, the organization of parking spaces constitutes a pressing issue in many cities worldwide, including in our country. This trend is driven by the sustained growth in the level of motorization. Its consequences are manifested in increased traffic flow intensity on urban arterial streets, reduced capacity of major roadways and transport nodes, heightened transportation load on elements of the street and road infrastructure. Under these conditions, municipal authorities face the task of developing a comprehensive project for the organization and management of parking spaces. It is well recognized that the transport infrastructure of each city possesses individual characteristics, historically shaped features and specific challenges. At the same time, the analysis and application of experience from foreign countries with high levels of motorization represent valuable practical and methodological resources that should be taken into account when addressing parking organization issues in large cities of our country. The implementation of substantial changes on arterial streets aimed at increasing the capacity of urban road networks is characteristic of most cities. During certain periods of traffic demand, the reduction of priority transport load on arterial streets may be achieved through the operation of park-and-ride systems. Within the framework of the present study, the isochrone method is considered as the principal methodological tool for assessing the spatiotemporal efficiency of transport systems. The proposed approach is primarily oriented toward the analysis of traffic flows at the urban level.
Keywords: park-and-ride, peak hour, traffic delay, parking systems, traffic flow rate, isochrone, transport load, motor vehicles, arterial streets, traffic composition, street and road network.
Abstract. Quantum computing – is an advanced technology which has a great impact on the traditional methods of computation causing a major challenge for the cryptographic systems that form the basis of our digital security. This research thesis is on cryptographic resilience in the age of quantum when the public key algorithms such as RSA and elliptic curve cryptography get compromised with the use of Shor’s algorithm, while symmetric primitives additionally lose half of their security against Grover’s search. The aim of the research is to thoroughly understand the quantum threat model and through experiments, figure out what is the realistic “cost of quantum safety” for the classical and post-quantum cryptographic mechanisms. The methodology combines systematic literature review with an experiment which is carried out using a reproducible benchmarking framework that (QCCB) outputs statistical performance estimates (mean, dispersion, and confidence intervals) and machine-readable result artifacts. The experimental findings support the migration viewpoint based on the risk quantified (i) the vulnerability window of RSA, 2048 and other classical public, key schemes, of which (ii) the comparative performance and size characteristics of the post-quantum candidates that agree with the NIST standardization. Furthermore, the study introduces a decision-making oriented evaluation metric, the Security Cost Index (SCI), that facilitates the understanding of a correlation of target security levels with the computational overhead enabling different deployment planning scenarios to be fathomed depending on the existing tradeoffs. The paper argues for migration to post-quantum cryptography that has been standardized, and is measurable, at reproducible and with the figure of the clear trade-off should be the mainstay of the efforts for securing confidentiality, integrity, and authenticity against the “harvest now, decrypt later” risk in the long run.
Keywords: Quantum Computing, Post-Quantum Cryptography, NIST FIPS 203/204/205, ML-KEM, ML-DSA, Cryptographic Resilience, Shor’s Algorithm, Grover’s Algorithm, Hybrid Cryptography, Security Migration, HNDL Attack, Lattice-Based Cryptography
Abstract. The article discusses the development of an ontology designed to formalize and support the process of teacher professional development in the context of digital transformation of education with an emphasis on STEM-based approaches. The relevance of the research is determined by the need for a systematic presentation of the professional competencies of teachers of the 21st century and ensuring their measurability in digital educational environments. The aim of the work is to create an ontological model that ensures the integration of STEM methods, competencies, indicators of their formation, assessment tools and forms of control in a single information structure. The study used methods of ontological modeling, formal description of knowledge using OWL, as well as SPARQL queries for data analysis and extraction. As a result, an ontology has been developed that implements the “STEM-method – competence – indicators – tools – forms of control” compliance matrix and supports automated monitoring of teachers’ professional development. The scientific novelty of the work lies in the comprehensive formalization of the professional development process based on an ontological approach. The practical significance is determined by the possibility of using ontology in digital professional development platforms, decision support systems and quality analysis of teacher education.
Keywords: STEM education, teacher training, professional competencies, digital transformation of education, STEM methods, methodological model, competence assessment.