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Lyalko VI, Shportiuk ZM, Sibirtseva OM, Dugin SS. Application of hyperspectral indices for the detection of grass cover changes from spectrometric survey data. 2014 ;(4):105-112.
Siryk SV, Salnikov NN. On the application of mass lumping in the Petrov–Galerkin finite element method for convection-diffusion problems. 2014 ;(5):39-44.
Kariaka NS, Litsis OO, Sliva TYu., Kolomzarov Yu.V, Minyailo MA, Minakova IE, Sorokin VM, Amirkhanov VM. Application of N-dimethyl benzoylamidophosphate-based coordination compounds in the development of the technology for metallorganic light-emitting diodes (MOLED). 2014 ;(4):125-132.
Semenyuta IV, Kovalishyn VV, Pilyo SG, Blagodatnyy VN, Trokhimenko EP, Brovarets VS, Metelitsa LA. Application of QSAR models to the search for tubulin inhibitors in a series of derivatives of 1,3-oxazole. Reports of the National Academy of Sciences of Ukraine. 2014 ;(12):152-157.
Avramenko AA, Tyrinov AI, Dmytrenko NP, Kravchuk OV. Application of the Boltzmann lattice method to the analysis of nanofluid flow in a curved channel with radial irregularities of the temperature and the concentration of nanoparticles. 2017 ;(1):52-59.
Selivanov MF, Chornoivan YO. Application of the complex cohesive zone model to the edge mi xed-mode crack problem for orthotropic media. 2019 ;(11):31-40.
Serebriakova SV. Application of the cyclic queueing systems. 2016 ;(3):32-37.
Melnytchuk SD, Khyzhnyak SV, Nardid OA, Cherkashyna Ya.O, Morozova VS, Repina SV, Voitsitsky VM. Application of the electron paramagnetic resonance to assess the functional activity of the respiratory chain of rates' hepatocyte mitochondria under artificial hypobiosis. Reports of the National Academy of Sciences of Ukraine. 2015 ;(4):144-149.
Lugovyy PZ, Skosarenko YV, Orlenko SP. Application of the method of spline-collocations to the solution of dynamic and static problems for structurally inhomogeneous cylindrical shells. 2019 ;(8):25-33.
Kuznetsov IN. Application of the Monte-Carlo simulation for the statistical testing of the hypothesis that a steady-state distribution of the number of customers in the queueing system GI/G/∞ tends to the normal distribution in the case of heavy traffic. 2016 ;(5):30-35.

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