Bioimpedance spectrum (BIS) measurements are highly appreciated in in vivo studies. This non-destructive method, supported by simple and efficient instrumentation, is widely used in clinical applications. The multi-frequency approach allows for the efficient extraction of the most information from the measured data. However, low-frequency implementations are still unexploited in the development of the technique. A self-developed BIS measurement technology is considered the pioneering approach for low (<5 kHz) and ultra-low (<100 Hz) frequency range studies. In this paper, the robustness of ultra-low frequency measurements in the prototypes is examined using specially constructed physical models and a dedicated neural network-based software. The physical models were designed to model the dispersion mainly in the ultra-low frequency range. The first set of models was used in the training of the software environment, while the second set allowed a complete verification of the technology. Further, the Hilbert transformation was employed to adjust the imaginary components of complex signals and for phase determination. The findings showed that the prototypes are capable of efficient and robust data acquisition, regardless of the applied frequency range, minimizing the impact of measurement errors. Consequently, in in vivo applications, these prototypes minimize the variance of the measurement results, allowing the resulting BIS data to provide a maximum representation of biological phenomena.

The increasing application of unmanned aerial vehicles (UAVs) in civil engineering provides new opportunities not only for data collection and site monitoring but also for supporting project management activities. This paper examines the implementation of drone technology in civil engineering from a project management perspective. Based on practical applications of UAVs in construction-related activities, the study analyses their potential contribution to project planning, monitoring and control, documentation, and decision-making. Particular attention is given to the integration of drone-based activities into the project workflow and to the identification of technical, operational, environmental, and organizational risks that may influence their successful implementation. The proposed approach demonstrates how drone technology can support more systematic project monitoring while providing timely visual information on project progress and site conditions. The results indicate that the effective integration of UAV technology requires not only appropriate technical solutions but also structured planning, risk management, and coordination with the overall project management process.

Industry-education collaboration plays an important role in improving the quality and practical relevance of engineering education, particularly in fields characterized by rapid technological development. This paper examines the integration of modern industrial measurement equipment into engineering education from a quality management perspective. The study is based on a case of cooperation between Subotica Tech and Rohde & Schwarz, in which modern measurement instruments were introduced into existing laboratory activities. Building on practical experience and comparative laboratory measurements, the collaboration is analysed in terms of stakeholder needs, educational process improvement, and the systematic integration of industrial technologies into teaching. A Plan-Do-Check-Act (PDCA) framework is used to structure the implementation and evaluation process and to identify opportunities for continual improvement. Particular attention is given to the contribution of modern equipment to measurement procedures, interpretation of results, documentation, and the alignment of practical education with current industrial practice. The analysis indicates that industry-education collaboration can contribute to educational quality not only by providing access to modern technology, but also by creating a structured feedback mechanism between industrial requirements and educational processes. The proposed approach demonstrates how such cooperation can be interpreted as a continual quality improvement process in engineering education.