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Information × Registration Number 0224U033282, (0124U004660) , R & D reports Title Scientific direction "Mathematical sciences and natural sciences"-2024 of Yuriy Fedkovych Chernivtsi National University popup.stage_title Науковий напрямок «Математичні науки та природничі науки»- 2024 Чернівецького національного університету імені Юрія Федьковича Head Ushenko Oleksandr G., д.ф.-м.н. Registration Date 24-12-2024 Organization Yuriy Fedkovych Chernivtsi National University popup.description1 To develop methods for diagnosing the condition and healing of postoperative wounds using the spatial-frequency spectrum of the scattered optical field and fluorescence spectrum. Develop potentiometric and luminescent methods for determining of pollutants entering water bodies. To develop recommendations for the use of modern secondary power sources power sources as part of electric energy storage. Improve information technologies for determining and classification of information context based on neural network methods. Develop algorithms for polarization-phase reconstruction of layer-by-layer and three-dimensional distributions of linear and circular parameters birefringence and dichroism of the polycrystalline structure of biological preparations of tissues and fluids. popup.description2  Developed methods for diagnosing the condition and healing of postoperative wounds based on the spatial-frequency spectrum of the scattered optical field and the fluorescence spectrum. Created potentiometric and luminescent methods for detecting pollutants (heavy metals, nitro compounds, and fuel components) entering water bodies due to military actions. Selective electrodes were used for potentiometric detection of these pollutants. The selectivity and sensitivity of photoluminescent composites based on AIBIIICVI and AIIBV nanoparticles were studied. Developed recommendations for the use of modern secondary power sources as part of energy storage systems and the implementation of components for autonomous small- and medium-scale solar power plants. Improved information technologies for sentiment analysis and context classification of information using neural network methods. Developed algorithms for polarization-phase reconstruction of layered and three-dimensional distributions of parameters of linear and circular birefringence and dichroism in the polycrystalline structures of biological tissue and fluid samples from injured, wounded, and deceased individuals. Product Description popup.authors Boruk Serhii D. Voitsekhivska Oksana М. Sachko Anastasiia V. Slotov Mykhailo M. Fochuk Petro M. popup.nrat_date 2024-12-24 Close