Мікросистеми, Електроніка та Акустика: науково-технічний журнал, Т. 29, № 2(127)
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Документ Відкритий доступ Investigation of Electrical Signals Transmission through Light-Induced Conductive Channels on the Surface of CdS Single Crystal(КПІ ім. Ігоря Сікорського, 2024) Boikynia, A. O.; Tkachenko, N. S.; Didenko, Yu. V.; Oliinyk, O. O.; Tatarchuk, D. D.Further development of information technologies hinges on innovations in the electronic components sector, particularly in enhancing electronic communication devices. This involves creating dynamic interconnects—electrically conductive channels that can be configured on-demand within chip circuitry to overcome the "tyranny of interconnects," which limits electronic systems due to the fixed nature of conventional interconnects. This paper presents experimental verification of transmitting information through photoconductive channels formed on a photosensitive cadmium sulfide (CdS) semiconductor single crystal using optical irradiation. By directing a focused light beam to specific areas of the CdS crystal, localized conductivity is induced, allowing for the dynamic formation of conductive channels. This method's efficacy in real-time signal transmission validates the theoretical framework and suggests new possibilities for semiconductor technology. The integration of dynamic interconnects could revolutionize communication systems by enhancing device efficiency and processing capabilities. This technology could lead to more complex electronic architectures needed in high-speed computing and advanced telecommunications. Additionally, this approach has potential applications in optoelectronics, improving device interaction with light. Dynamic interconnects could enhance solar cell efficiency, increase light sensor sensitivity, and aid in developing innovative visual displays. The ability to control material conductivity through light not only advances existing device performance but also opens doors to new electronic designs and operations. This includes fully reconfigurable circuits that adapt in real-time, self-optimizing network components, and smart sensors that respond to environmental changes. In summary, this research not only confirms the practicality of using photoconductive channels for information transmission but also emphasizes the significant implications for electronic and communication system advancements. As this technology evolves, it promises to significantly impact the design and functionality of future electronic devices, paving the way for more adaptable and powerful systems.Документ Відкритий доступ Deep Learning for the Detection and Classification of Diabetic Retinopathy Stages(КПІ ім. Ігоря Сікорського, 2024) Basarab, M. R.; Ivanko, K. O.The incidence of diabetic retinopathy (DR), a complication of diabetes leading to severe vision impairment and potential blindness, has surged worldwide in recent years. This condition is considered one of the leading causes of vision loss. To improve diagnostic accuracy for DR and reduce the burden on healthcare professionals, artificial intelligence (AI) methods are increasingly implemented in medical institutions. AI-based models, in particular, are integrating more algorithms to enhance the performance of existing neural network architectures that are commercially used for DR detection. However, these neural network models still exhibit limitations, such as the need for high computational power and lower accuracy in detecting early DR stages. To overcome these challenges, developing more advanced machine learning models for precise DR detection and classification of DR stages is essential, as it would aid ophthalmologists in making accurate diagnoses. This article reviews current research on the use of deep learning in diagnosing and classifying DR and related diseases, as well as the challenges ophthalmologists face in detecting this condition and potential solutions for early-stage DR detection. This review provides information on modern approaches to DR detection using deep learning applications and discusses the issues and limitations in this area.Документ Відкритий доступ Soitware Support for the Higher Mathematics Course at the Technical University(КПІ ім. Ігоря Сікорського, 2024) Bogdanov, O. V.; Butsenko, Yu. P.; Balina, O. I.; Bezklubenko, I. S.The paper addresses the challenges of training modern engineers in mathematical disciplines. It emphasizes the need for graduates to possess theoretical knowledge and be capable of using modern software solutions for efficient mathematical calculations. The article discusses the importance of incorporating mathematical software into higher education to enhance the teaching of mathematical disciplines. Explores the potential benefits and challenges of using mathematical software in the learning process, such as the need for coordination among teachers and the importance of familiarizing students with the interfaces of mathematical packages. The paper recommends using specific mathematical software packages, such as Scilab, for scientific and engineering calculations. It also highlights the necessity of guiding students in understanding the practical applications of mathematical software in solving complex mathematical problems. Furthermore, the paper addresses the issue of preventing students from inappropriately using online calculators for tasks, emphasizing the importance of mastering theoretical foundations before utilizing mathematical software packages. The paper generally advocates for a balanced approach that incorporates both traditional theoretical exposition and practical application of mathematical programs in higher education to promote effective teaching and learning of mathematical disciplines.Документ Відкритий доступ A Review of Broadband Microfabricated Ultrasonic Systems for Biomedical Applications(КПІ ім. Ігоря Сікорського, 2024) Kostiuk, R. Yu.; Naidas, S. A.Starting from an overview of historical aspects of biomedical ultrasound development and its application areas, as well as the brief description of state-of-the art microfabrication technologies, used for capacitive and piezoelectrical micromachined ultrasonic transducers manufacturing, also outlining their modelling approaches, the reader will be further presented with an overview of existing methods for achieving broadband operation both at unit transducer and transducers array levels. Moreover, a generalized signal processing system is discussed, including description of known approaches for building blocks implementation in analog, digital and mixed-signal domains (such as drivers, amplifiers, ADCs, etc.).Документ Відкритий доступ Comparison of the Efficiency of a Neural Network for Image Recognition on Microcontrollers(КПІ ім. Ігоря Сікорського, 2024) Sharuiev, R. D.; Popovych, P. V.The paper is devoted to comparing two popular models of 32-bit microcontrollers for working with neural networks for object recognition. The target devices were the ESP32 and STM32 microcontrollers, on which an artificial neural network was deployed, written using the Python programming language and the TensorFlow library. Micropython was chosen as the operating system for the microcontrollers. The paper compares the performance of the ESP32 and STM32 microcontrollers for object detection using a neural network and their classification. The image recognition time and the percentage of correctly classified objects were compared depending on the number of neuron layers and the number of training epochs within these networks. The article shows that the number of layers and training epochs directly affects the accuracy of object classification in the image. The obtained results show that increasing the number of layers of the neural network increases the overall accuracy of object recognition using the studied neural network, increasing the number of training epochs logarithmically increases the accuracy of recognition and classification within the neural network, but at the same time, increasing the number of neuron layers leads to an increase in the total recognition time. The difference in the obtained results for the accuracy of image recognition of microcontrollers differs within 5%.Документ Відкритий доступ Estimation of Acting Factor in Stress from Motorbike Sounds(КПІ ім. Ігоря Сікорського, 2024) Pareniuk, A. V.; Pareniuk, D. V.In the presented study, the search for the acting force in stressor acoustic signal and common everyday acoustic signal is presented. As stressors the signals of acoustic siren of air raid alert and other dangers in the different counties were used, and as everyday signals the sound of motorbikes passing by observers were used. In total five different signals of alert sirens were used. Numerical values presented in research were obtained via frequency analysis with Hann’s window and later – via spectrogram survey. This survey allowed us to find the presence of a steady frequency components in the observed signals, and, most importantly, the presence of rises and falls in said components. These changes in frequency had their speed of change calculated for sirens and motorbikes. For the rise of frequency mean speed in the siren group was calculated as 164 Hz/second, fall was 80 Hz/second. For the motorbike, the speed of frequency rise had a mean value calculated as 166 Hz/second and fall of frequency was estimated as 67 Hz/second. Possible sources for said effect in motorbike signals are Doppler effect and rise of RPM during acceleration. During the statistical analysis via implementation of the non-parametric method due to the character of data distribution in the studied group the lack of statistically meaningful differences between speeds of frequency rise in frequency components of the signals was found. Said rise is presumed to be the acting factor in stress from everyday sounds.