October 31 · Article · Eastern-European Journal of Enterprise Technologies · Electrical and Electronic Engineering
The object of this study is the deformation process in reinforced-concrete structural elements equipped with embedded fiber-optic sensors. The problem addressed corresponds to unresolved issues identified in previous studies – namely, the lack of standardized quantitative evaluation of accuracy and stability in fiber-optic deformation measurement. Despite high laboratory precision, existing methods show reduced long-term reliability, temperature-strain cross-sensitivity, and calibration inconsistency when applied to real structures. The main results show that fiber Bragg grating (FBG) and interferometric sensors achieved sub-micrometer deformation resolution with deviations below 2–3 με and long-term drift under 0.5%. Measurements remained stable under variable loading and temperature, confirming high reproducibility and electromagnetic immunity. These findings validate the hypothesis that optical wavelength shifts directly correspond to mechanical strain, ensuring reliable strain detection without recalibration. This effectiveness stems from the intrinsic photoelastic coupling and refractive-index sensitivity of the optical fiber, which provide nanometric resolution, corrosion resistance, and long-term operational stability. The proposed method is applicable for long-term monitoring of bridges, tunnels, and high-rise facilities exposed to environmental and cyclic stresses. Therefore, research on high-precision fiber-optic deformation measurement remains scientifically relevant for improving the safety and durability of modern civil engineering structures.
NKNurzhamal KashkimbayevaOpen access
October 31 · Article · Eastern-European Journal of Enterprise Technologies · Information Systems
The object of the research is a monitoring and analysis system for software quality based on user feedback collected from open-source projects on GitHub. The problem addressed is the lack of effective automated tools that can process large volumes of unstructured user feedback to identify quality issues, prioritize tasks, and detect negative trends in real time. Traditional quality assurance methods, while important, fail to capture the nuance of user sentiment and the contextual details present in natural language feedback, leading to delays in problem detection and resolution. The developed system integrates three key modules: sentiment analysis for assessing user satisfaction, issue categorization for structuring feedback into actionable types, and anomaly detection for identifying sudden changes in sentiment or feedback dynamics. The results show that transformer-based models, particularly fine-tuned BERT, outperform rule-based and traditional machine learning approaches in both accuracy and robustness. This advantage is explained by their ability to capture domain-specific language, sarcasm, and contextual dependencies, enabling more precise interpretation of complex feedback. The anomaly detection component, using LSTM autoencoders and Isolation Forest, demonstrated the ability to identify critical quality regressions up to two days before official issue reporting. These results can be applied in practice for continuous software quality monitoring in agile, open-source, or user-centric development environments where timely, data-driven decision-making is essential. The approach supports real-time insight generation, helping development teams respond proactively to quality risks and improve overall user satisfaction
NKNurzhamal KashkimbayevaOpen access
October 31 · Article · Scientific Contributions Oil and Gas · Fuel Technology
This study investigates the performance of a novel, environmentally friendly nanocomposite, utilizing the natural biopolymer Kappaphycus alvarezii enhanced with TiO2 nanoparticles, for Enhanced Oil Recovery (EOR) via polymer flooding. The application of this nanocomposite was aimed to simultaneously enhance microscopic displacement and macroscopic sweep efficiency. The research method used was laboratory testing which included solution stability, viscosity, interfacial tension (IFT), and rock wettability tests in various polymer concentrations (2,000–6,000 ppm), TiO₂ (2,000–4,000 ppm), and salinity (6,000–30,000 ppm) at temperatures of 30–80°C. Quantitative laboratory results confirm fluid property improvements: TiO2 addition increased the solution viscosity by up to 11 cP where an average increase up to 7.11% in high-salinity brines, reduced the Interfacial Tension (IFT) from 7.54 dyne/cm to 6.80 dyne/cm (a 9.8% reduction), and decreased the contact angle from 39.05° to 28.51°, confirming enhanced water-wetness. Core flooding experiments demonstrated that the polymer flooding yielded an incremental oil recovery factor after waterflooding ranging from 6.67% to 27.67%. The maximum total oil recovery achieved was 69.17% at the optimal concentration of Polymer 4,000 ppm and TiO2 2,000 ppm. These specific findings highlight the significant potential of the Kappaphycus alvarezii–TiO2 nanocomposite as an effective EOR agent.
SISonny IrawanOpen access
