2026-03-29
V. S. Mosiichuk, O. B. Sharpan, V. I. Yalosovetskyi
Section: Radioelectronics Medical Technologies Keywords: data collection automation, data set generation, Internet of Things, biosignal registration, data streaming processing, functional state determination Disciplines: 004.9:616-7 The effectiveness of modern methods of biosignal analysis largely depends on the availability of structured data sets containing both primary signals and related metadata. At the same time, most existing biosignal registration systems do not provide automated accumulation of such data in centralized databases, which complicates the formation of training samples and the further application of machine learning algorithms. The article considers an automated system for forming representative sets of biomedical data to increase the efficiency of machine learning tasks in the analysis of the human physiological state. The infrastructure of the information system for automated collection of biosignals and metadata and formation of data sets in real time has been developed. The system has a multi-level architecture that includes a sensor level for registering biosignals, a communication level for data transmission, and a server level for their processing and storage. During system testing signals were registered using a photoplethysmographic sensor integrated with a wireless module based on a microcontroller with Wi-Fi support. The server part is implemented in a virtualized environment using open source software, a web server, a database management system, and signal processing software modules. For visualization of biosignals and interaction with users, a Web-API and a web interface have been developed, which provide access to measurements, metadata management, and signal visualization. The system implements a data streaming pipeline that includes query verification, signal storage, and biomedical parameter calculation to assess the user's functional state. An experimental study of the system's performance was conducted in a load testing mode that simulates the simultaneous operation of a significant number of sensor devices. The results showed that the developed infrastructure is capable of handling more than a hundred simultaneous connections with an average query processing time of less than 100 ms. The results obtained confirm the possibility of using the proposed system for scalable collection of biosignals and the formation of data sets suitable for further application of machine learning methods.
2026-03-29
V. F. Komarov, Yu. V. Rassokhina
Section: Functional Electronics Keywords: phase-controlled rectifier, two-stage converter, parallel-bridge rectifier, reactive power, power factor correction, high-power DC drives Disciplines: 621.314.632:621.313.2:621.3.016.25 High-power phase-controlled thyristor DC drives, despite their reliability, have a fundamental drawback: significant reactive power consumption from the supply network, especially in dynamic operating modes with large firing angles (α). This leads to a low Displacement Power Factor (DPF) and additional losses. This study analyzes a cost-effective novel two-stage thyristor rectifier topology proposed to mitigate this problem. The topology utilizes a special transformer with secondary winding taps (e.g., at 50% and 100% voltage) that feed two 6-pulse bridges (R1 and R2), connected in parallel to a common DC load. The system functions as a high-speed solid-state equivalent of an On-Load Tap Changer (OLTC). By sequentially engaging the bridges, the converter maintains small firing angles (α) over a wide output voltage range. A detailed analysis of the energy characteristics, based on a case study of a typical acceleration cycle for a high-inertia drive (hoisting machine), demonstrates the topology's energy efficiency. Compared to a conventional single-bridge thyristor rectifier, the two-stage scheme reduces the total reactive energy consumed per acceleration cycle by 51% (from 54.4 kVAr · h to 26.8 kVAr · h in the example). An additional advantage of the solution is the reduction of the Root-Mean-Square (RMS) primary winding current during the initial acceleration stage, which leads to lower active power ( I 2 R ) losses in the transformer and supply lines. A drawback of the considered commutation algorithm is the presence of a 'discontinuous current mode' in the transformer primary winding during the mixed-mode (simultaneous operation of R1 and R2), which significantly degrades the harmonic spectrum (THD) of the input current, making the converter non-compliant with power quality standards (e.g., IEEE 519). The study concludes that practically implementing this energy-efficient topology requires hardware adaptation, specifically through the design of a custom Inter-Phase Reactor (IPR) or integration into multi-pulse configurations, to mitigate harmonic distortion while preserving the reactive power benefits.
2026-03-29
V. G. Kolobrodov
Section: Computing methods in radio electronics Keywords: thermal imager, polarization, degree of polarization, emission thermal radiation, reflected thermal radiation A physico-mathematical model of infrared (IR) radiation polarization from a drone, which can be used in the creation of polarimetric thermal imagers (PTI) for detection and recognition of surveillance objects, is developed. Analysis of Research . Thermal imaging systems are widely used, primarily in military applications, such as in the thermal cameras of drones. The principle of operation of classical thermal imagers is based on converting the brightness of IR radiation from the observed object and background from the plane of objects into an appropriate distribution of background-target scene (BTS) brightness on a display screen within the visible spectrum. If the contrast is low or absent, it becomes impossible to detect such an object. Current models do not simultaneously account for the drone’s emission and reflected radiation, leading to errors in the detection range estimation. The use of polarization properties of radiation allows solving this problem. Therefore, developing and researching a model of IR radiation polarization from the drone is a very important task for creating promising PTI for drone detection. Unresolved parts of the overall problem include the lack of a model that considers both emission and reflected polarization simultaneously. The purpose of the article is to develop a physico-mathematical model of IR radiation polarization from a drone, which can be used in the creation of PTI systems designed for drone detection and recognition. Research material presentation — the drone is modeled as a flat plate characterized by an reflection coefficient and a complex refractive index, which allowed the development of methods for calculating parameters of elliptically polarized radiation. Analysis of the developed methods indicates that for modeling the polarization state of the observed object’s radiation, it is appropriate to select the image intensity, degree of polarization, and polarization angle, all determined by the Stokes parameters. Comparison of obtained results with those from other researchers involves scientifically substantiating that the polarization of IR radiation from objects and backgrounds, due to their own and reflected radiation, has an opposite character, which significantly worsens the overall degree of polarization. Conclusions from this research . The obtained results are relevant for developing a test object model, necessary for designing PTI systems. Future prospects include conducting experimental measurements of IR radiation polarization from real drones and atmospheric conditions, which will help refine the test object parameters.