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Astronomy and Astrophysics

NOAP – script package for planning and analysis of NEO observations

¹Kozhukhov ОМ, ¹Medina MS. NOAP – script package for planning and analysis of NEO observations. Space Science and Technology. 2023 ;29(6):080-092.

Hunting for exocomet transits in the TESS database using the Random Forest method

¹Dobrycheva DV, ¹Vasylenko MYu., ¹Kulyk IV, ¹Pavlenko Ya.V, ²Shubina OS, ³Luk’yanyk IV, ¹Korsun PP. Hunting for exocomet transits in the TESS database using the Random Forest method. Space Science and Technology. 2023 ;29(6):068-079.

Multiwavelength properties of the low-redshift isolated galaxies with active nuclei modelled with CIGALE

¹Kompaniiets OV. Multiwavelength properties of the low-redshift isolated galaxies with active nuclei modelled with CIGALE. Space Science and Technology. 2023 ;29(5):088-098.

Ateroid positions based on the Dushanbe part of the FON project observations

¹Shatokhina SV, ²Relke H, ¹Yizhakevych OM, ¹Andruk VM, ³Mullo-Abdulov ASh. Ateroid positions based on the Dushanbe part of the FON project observations. Space Science and Technology. 2023 ;29(5):079-087.

Improving the use of geodetic, geocentric, and topocentric coordinate systems in meteor astronomy and related tasks

¹Kozak PM, ¹Luk’yanyk IV, ²Kozak LV, ³Stelya OB. Improving the use of geodetic, geocentric, and topocentric coordinate systems in meteor astronomy and related tasks. Space Science and Technology. 2023 ;29(5):069-078.

Presentation of the gravity field of celestial bodies using the potentials of flat ellipsoidal disks

¹Fys MM, ¹Brydun AM, ¹Sohor AR, ¹Lozynskyy VA. Presentation of the gravity field of celestial bodies using the potentials of flat ellipsoidal disks. Space Science and Technology. 2023 ;29(2):78-85.

Machine learning technique for morphological classification of galaxies from the SDSS. III. The CNN image-based inference of detailed features

¹Khramtsov V, ²Vavilova IB, ²Dobrycheva DV, ²Vasylenko MYu., ²Melnyk OV, ²Elyiv AA, ³Akhmetov VS, ³Dmytrenko AM. Machine learning technique for morphological classification of galaxies from the SDSS. III. The CNN image-based inference of detailed features. Space Science and Technology. 2022 ;28(5):27-55.

Star occultation by small bodies of the Solar system: current state of observations in Ukraine

¹Kleshchonok VV, ²Karbovsky VI, ¹Buromsky MI, ²Lashko MV, ³Gorbanev Yu.M, ³Kashuba VI, ³Kimakovskiy SR, ²Shavlovskiy VI, ⁴Angelskiy OV, ⁵Tsekhmeistrenko VS, et al. Star occultation by small bodies of the Solar system: current state of observations in Ukraine. Space Science and Technology. 2022 ;28(5):56-66.

Creation of the Ukrainian meteor observation network: instruments, methods for processing, observatin possibilities

¹Golubaev AV, ²Gorbanev Yu.M, ³Shulga OV, ⁴Andreev ОА, ³Bushuev FI, ⁵Vidmachenko AP, ⁶Hrudynin BO, ⁵Zhilyaev BE, ³Kaliuzhnyi MP, ⁷Kozak PM, et al. Creation of the Ukrainian meteor observation network: instruments, methods for processing, observatin possibilities. Space Science and Technology. 2022 ;28(4):39-70.

Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02<z<0.1

¹Vavilova IB, ²Khramtsov V, ¹Dobrycheva DV, ¹Vasylenko MYu., ¹Elyiv AA, ¹Melnyk OV. Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02. Space Science and Technology. 2022 ;28(1):03-22.

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