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Soil Analysis Software Tool for Smart Control of Agronomic Data
(2022-09-26) Satsyk, Viktor; Lishchyna, Nataliia; Khrystynets, Nataliia; Gumeniuk, Larysa; Korobchuk, Liudmyla
In this paper we develop system approach for obtaining, analysing and managing the agronomic parameters of the soil based on software and hardware IT-complex. The developed tool Soil Analysis Software Tool (S.A.S.T) is aasigned for measuring soil parameters with the possibility of integration into the system of research and online recommendations for optimization of consumables. Presented results makes a significant contribution to the concept of precision agriculture technic as farming IT model based on observing, control, detection regarding to inter and/or intra-field productive variability.
Development of network traffic monitoring system elements using Deep Learning
(Piscataway, NJ: IEEE, 2024) Melnyk, Vasyl; Bahniuk, Nataliia; Bortnyk, Kateryna; Kondius, Inna; Zubovetska, Nataliia; Kondius, Kostiantyn
In this article we develop a network traffic monitoring system elements using deep learning that demonstrates the high effectiveness of deep learning in detecting and analyzing network traffic, which contributes to ensuring the security and stability of corporate networks. In this context we develop algorithms for detecting and countering potential threats in network traffic, providing deeper analysis and effective response to cyber threats

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