Journal "Fundamental Sciences and Applications"

SQL Database Optimization as a Driver for SME Digital Transformation: A Case Study in the PV Sector

2026-08-03T11:01:43+03:00

Small and Medium-sized Enterprises (SMEs) in the photovoltaic sector face significant challenges in managing and leveraging data for strategic decision-making. This case study examines a comprehensive database optimization initiative within a European PV company, focusing on the digitalization of sales processes through Databricks and Power BI integration. The research documents a practical methodology for data consolidation, cleaning, semantic layer design, and installer segmentation that enabled real-time analytics and evidence-based decision-making. Results demonstrate improvements in data quality (67% to 94% completeness), reporting efficiency (days to real-time), and measurable business outcomes including resource reallocation and customer win-back campaigns.

Machine Learning-Based Heart Disease Prediction: A Comparative Analysis with Feature Importance Evaluation

2026-08-03T11:01:46+03:00

Heart disease continues to rank as the foremost contributor to premature death across the globe, and developing reliable automated screening tools has become a pressing priority in clinical informatics. This study presents a comparative analysis of three machine learning classifiers — Logistic Regression (LR), Random Forest (RF), and Gradient Boosting (GB) — for binary heart disease prediction using the UCI Cleveland Heart Disease dataset. The dataset comprises 297 patient records with 13 clinical features following removal of missing values. Models were evaluated using an 80/20 stratified train-test split with Min-Max normalisation. Logistic Regression achieved the highest AUC-ROC of 0.9554 and accuracy of 83.33%, followed by Random Forest (AUC-ROC = 0.9375, accuracy = 85.00%) and Gradient Boosting (AUC-ROC = 0.8828, accuracy = 76.67%). Feature importance analysis identified chest pain type (cp), thalassemia (thal), and maximum heart rate (thalach) as the most influential predictors. Results indicate that well-calibrated linear classifiers can match or exceed ensemble methods in structured clinical settings, a practically significant finding for risk-stratification tools where probability estimates must be trusted.

Implementing SLI/SLA/SLO Metrics in anASP.NET 8 Microservices Architecture Using Open Telemetry and Prometheus

2026-08-03T11:01:50+03:00

This article presents the results of a study on implementing a service level metrics system (SLI/SLA/SLO) in a high-load web application on the ASP.NET 8 platform. A practical implementation of a monitoring system using OpenTelemetry Metrics and a Prometheus endpoint is considered. A comparative analysis of system performance and reliability indicators before and after implementing the metrics is conducted. The mechanisms by which metrics influence operational indicators are described in detail: identifying hidden performance issues, transforming the alerting system, prioritizing engineering efforts, managing the balance between development speed and reliability through an error budget, and automating response processes. The study results showed an improvement in the average time to detect incidents by 73%, a reduction in service restoration time by 58%, and an increase in overall system availability from 98.2% to 99.7%. A methodology for determining target SLO values based on business requirements and architectural constraints is presented

Design and Feasibility Assessment of Implementing a Pneumatic Suspension System in a Vehicle with a Conventional Suspension System

2026-08-03T11:01:53+03:00

This study presents the design and feasibility analysis of retrofitting a pneumatic suspension system into a vehicle originally equipped with a conventional passive suspension. The aim is to evaluate structural compatibility, dynamic performance improvements, and techno-economic viability. A conceptual retrofit configuration including air springs, compressor, reservoir, valves, and control module is proposed. Analytical and simulation-based methods are used to compare ride comfort, vibration behavior, and load response under different conditions. The results show improved comfort and adaptability, while increased cost, weight, and system complexity remain important considerations for practical implementation.

Investigation of Airflow Parameters in a G-Shaped Channel

2026-08-03T11:01:55+03:00

This study presents a numerical investigation of airflow through a G-shaped channel, focusing on the influence of geometric parameters on pressure distribution and velocity field development. A three-dimensional CFD model was developed to analyze three channel configurations under identical boundary conditions, with an inlet velocity of 10 m/s and atmospheric pressure at the outlet. The results reveal significant pressure redistribution in the curved section and localized acceleration of the airflow near the inner wall, where velocity increases of up to 49% were observed. The findings demonstrate the strong effect of curvilinear geometry on flow energy transformation and support potential applications in adaptive wind turbine systems.

Numerical Analysis of Fluid Flow and Heat Transfer in Wavy Microchannels with Pin Inserts

2026-08-03T11:01:57+03:00

Effective thermal management is essential for maintaining reliability and performance of modern electronic devices as heat generation increases with system miniaturisation. This study presents a numerical investigation of fluid flow and heat transfer in wavy microchannel heat sinks with circular pin inserts of varying heights ranging from 0 to 0.4 mm. A 3D conjugate heat transfer model was developed in ANSYS Fluent to evaluate thermal-hydraulic performance with Reynolds numbers ranging from 300 to 800. The microchannels were examined with wave amplitudes of 0, 150, and 250 μm. Water was used as the coolant and a constant heat flux of 50 W/cm2 was applied at the base of the heat sink. Key performance indicators including the Nusselt number, friction factor, and performance evaluation criterion were used to assess heat transfer enhancement and flow resistance. Results show that channel waviness significantly improves heat transfer, with the 250 μm amplitude channel outperforming the straight and 150 μm channels. Increasing pin height further enhances the Nusselt number, reaching about 15% higher than the smooth channel, although it also increases the pressure drop. The best overall thermalhydraulic performance was obtained for a wavy microchannel with 250 μm amplitude and a pin height of 0.1 mm.

Quantifying Tram Overhead Contact Line Stagger and Its Impact on Carbon Strip Wear

2026-08-03T11:02:00+03:00

This study investigates the stagger of tram overhead lines and its effect on pantograph carbon strip wear. Using a specialized measurement vehicle equipped with a stagger decoder, field data were collected along selected tram routes. The measured wire geometry was compared with the original design documentation to assess deviations and their impact on energy collection efficiency and strip longevity. Results highlight areas where design tolerances differ from reality, providing insights for infrastructure optimization and maintenance planning. The findings demonstrate the importance of precise monitoring of overhead line alignment to ensure uniform wear and improve the reliability of tram systems