Browsing by Author "Zimoglyad, Andrew Yu."

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Development of a JFET Model with Increased Accuracy: Measurements of Wrangling Data, Acquisition and Model Analysis
(CEUR-WS Team, Aachen, Germany, 2025) Hnatushenko, Viktoriia V.; Guda, Anton I.; Zimoglyad, Andrew Yu.; Zhurba, Anna O.
ENG: Junction gate field – effect transistors have a significant role in the modern electronics. Simulation of the electronic schematics is a crucial part of the modern devices development. At the present time an existent model are used. A drawbacks of the exiting JFET models, with are commonly used during electronic schematics simulation a described. For the tasks of precision simulation the simple approximation functions and switching conditions lead to accuracy loss. A general purpose and specialized hardware and software complex was created to acquire measurement data. This measurement complex gives as possibility to acquire measurement data in automatic and semi-automatic modes. A bulk amount of data about selected JFET species was collected. According to this data a new model was proposed. This model allows us identify parameters in sequence, which significantly decreases the possibility of the identification errors. Proposed model requires more complex calculations to achieve results, and more data to conduct parametric identification. But as the result, new model provides better agreement with experimental data, especially in low-voltage regimes. New model allows us to decrease simulation error level from the 20% to 1—5%. The proposed model provides better qualitative conforming to the experimental data.
Research on Environmental Changes Based on Fractal Characteristics of Satellite Images
(CEUR-WS Team, Aachen, Germany, 2025) Hnatushenko, Viktoriia V.; Zhurba, Anna O.; Zimoglyad, Andrew Yu.; Ostrovska, Kateryna Yu.
ENG: Most natural structures that are widely studied today using computer science have a complex fractal structure. Fractal analysis of such structures is used to model, study, and explain the properties of surfaces and structures of complex objects in various fields of science and technology. Images of a large number of natural surfaces and structures are satellite images that exhibit fractal properties. Satellite images in modern life have high spatial resolution, which gives researchers and users satisfactory initial data for solving various types of problems. A promising direction for increasing the informativeness of satellite images is the use of fractal image analysis methods. The complexity of the forms of the underlying surface and vegetation can be described using the fractal dimension. Characteristic values of the fractal dimension allow decoding of space images. The paper proposes a method for studying environmental changes in satellite images based on the calculation of fractal characteristics, such as fractal dimension, fractal distribution and fractal segmentation. The ecological indicators for assessing the state of the environment were selected as trends in forest numbers, water and land resources. Satellite images of the Amazon forests, Bolivia in 1991, 1996, 2006, 2012, 2016, 2020, which were subjected to mass deforestation, were selected for the study. The experimental results show that the fractal dimension increases each time (Fractal Dimension (FR) = 1.441 in 1991, FR = 1.825 in 2020), and the green areas in this area decrease. The depth of the seas (Black Sea, Tyrrhenian Sea, Mediterranean Sea, Philippine Sea) was studied. The least homogeneous with the largest amplitude of distribution modes has the fractal distribution of the Philippine Sea, which indicates a more pronounced relief of the seabed. As a result of the study of winter fields with different levels of snow cover, it was found that an increase in its value leads to an increase in the value of the fractal dimension (FR=1.702 February, FR=1.894 March). Thus, fractal analysis of winter fields allows us to estimate the relative amount of moisture that will enter the soil in the spring. The study highlights the need for further research in developing more efficient fractal methods to improve the accuracy of change area detection, which will favor the analysis of the causes and consequences of the environmental situation.