Leakage is the main cause of energy loss in pneumatic systems. In practice, no pneumatic system is perfectly sealed, and some level of leakage is inevitable. In well-maintained industrial facilities, the level of leakage considered acceptable is usually 2% to 10% of total air consumption. These small leaks are often tolerated because the cost of repairing them may outweigh the potential savings. However, in poorly maintained systems, leakage rates can increase significantly. Therefore, implementing active leak detection and a planned remediation program, along with timely repairs, can reduce leakage to less than 10% of total compressed air production.

The main objective of this paper is to develop a system for the detection of compressed air leaks and assessment the associated energy losses. This was accomplished by designing and testing a laboratory prototype under controlled conditions. The current practical application of this system enables quick and straightforward measurements at key points within the system, providing medium reliable detection of leak locations and estimates of associated losses. Future research is planned to test the prototype device in real industrial environments, where multiple sources of noise are present. Following these tests, the final version of the device will be developed, making it suitable for use in industrial production settings.

The use of SMART complexes with artificial intelligence in vocational education institutions in Ukraine improves learning quality and flexibility, addressing challenges of wartime conditions and advancing Vocational Education 4.0. This study evaluates the effectiveness of SMART complexes in optimizing vocational training by comparing remote education in the central-eastern region, often disrupted by air-raid alerts and power outages, with in-person learning in the western region. Surveys and learning outcome analysis highlight the advantages of individualized learning enabled by AI technologies.

Using a mixed-methods approach, the research integrates qualitative and quantitative data to assess the impact of different learning models on student performance. Findings show that SMART complexes facilitate personalized learning, allowing students to progress at their own pace while adapting task complexity to their abilities. Remote education in the central-eastern region ensures continuity, whereas the fixed pace of in-person learning in the western region restricts adaptability.

The study concludes that SMART complexes enhance vocational education by fostering personalized approaches, developing digital skills, and boosting motivation. Their integration effectively adapts educational content to individual needs and labor market demands, providing a robust solution for optimizing education in contemporary conditions.

The article examines the use of SMART complexes with artificial intelligence elements in the vocational education of Ukrainian students, which represents a significant step towards improving educational quality amid modern challenges, particularly during wartime. These complexes facilitate the advancement of Vocational Education 4.0 by allowing flexible adjustment of the learning pace and content to meet students’ individual needs. The study focuses on comparing the effectiveness of flexible and fixed learning paces in distance and in-person educational models. A key aspect is analyzing the use of distance learning in vocational institutions in central-eastern Ukraine, where frequent air alerts and power outages complicate in-person learning, while fixed-paced in-person learning predominates in western regions, often disregarding students’ individualized educational needs.

The research methodology adopts a mixed approach, combining qualitative and quantitative data collection and analysis. Surveys conducted among students and teachers assessed their experience with distance and in-person learning using SMART complexes. The study analyzed students' academic results, satisfaction with the educational process, and the flexibility provided by SMART complexes through artificial intelligence elements that adapt learning to individual educational needs. SMART complexes include tools for interactive content, personalized assignments, and automated assessment, enhancing student motivation and fostering the development of digital skills.

The findings highlight the advantages of SMART complexes for optimizing learning pace. In regions where in-person education is constrained by external factors, distance learning with integrated SMART complexes offers the only viable option for maintaining stable education. In contrast, western regions, with predominantly in-person models, tend to have less flexible approaches. Using SMART complexes enables vocational education institutions to adapt to labor market demands, develop flexible learning pathways, and significantly improve learning outcomes. Analytical tools within SMART complexes allow rapid responses to educational needs, guiding students toward relevant competencies.

This study examines the impact of a teacher’s disability on learning and teaching effectiveness in a problem-based remote laboratory setting. It seeks to determine if the teacher’s disability influences students' perceived learning gains, the efficiency of the teaching process, and whether the remote lab format makes the course more appealing.The research was conducted in a master's course called “Mathematical and Numerical Methods for Flow and Transport Processes in Chemical Engineering,” where students worked in groups using computer simulations. The course ran over a week-long period, with remote lab sessions lasting three to four hours, followed by an exam. Surveys were administered at the end of the course in 2023 and 2024. Students were asked if they noticed the teacher’s disability, whether it impacted their learning, and if it required extra time to reach learning goals. They were not informed about the teacher's visual impairment before starting the course.Survey results revealed that students did not perceive any negative impact on their learning gains due to the teacher’s disability, nor did they need extra time to achieve their learning objectives. A key difference between the 2023 and 2024 results was that students in 2024 were less aware of the teacher's disability. This change is attributed to the teacher’s improved preparation and experience, which made the teaching more effective and efficient.In conclusion, the study shows that a teacher’s disability does not negatively affect students’ learning outcomes if the teacher is well-prepared. Moreover, the remote lab format was generally well-received by students, even those accustomed to in-person courses.