Mokslinės publikacijos

 

Tyrėjo identifikatoriai:

Straipsniai Clarivate Analytics Web of Science leidiniuose turinčiuose citavimo rodiklį:

2022:

• Žvirblis, T., Petkevičius, L., Bzinkowski, D., Vaitkus, D., Vaitkus, P., Rucki, M., & Kilikevičius, A. (2022). Investigation of deep learning models on identification of minimum signal length for precise classification of conveyor rubber belt loads. Advances in mechanical engineering, 14(6), 16878132221102776.

2021:

• Kuodytė V, Petkevičius L. Education-to-Skill Mapping Using Hierarchical Classification and Transformer Neural Network. Applied Sciences. 2021; 11(13):5868. https://doi.org/10.3390/app11135868
• Daniušis, P., Juneja, S., Valatka, L., Petkevičius L. Topological navigation graph framework. Autonomous Robots (2021). https://doi.org/10.1007/s10514-021-09980-x
• Baronas, R., Kulys J., Petkevičius L. (2021). Modeling carbohydrates oxidation by oxygen catalyzed by bienzyme glucose dehydrogenase/laccase system immobilized into microreactor with carbon nanotubes. Journal of Mathematical Chemistry: 59, 168–185 (2021). doi:10.1007/s10910-020-01187-2.
• Seniutis M, Petružytė D, Baltrūnaitė M, Vainauskaitė S, Petkevičius L. The Impact of Information System on Interactions of Child Welfare Professionals with Managers and Clients. Sustainability. 2021; 13(12):6765. https://doi.org/10.3390/su13126765

2020:

• Bagdonavičius V., Petkevičius L. (2020). Multiple Outlier Detection Tests for Parametric Models . Mathematics, doi:10.3390/math8122156
• Bagdonavičius V., Petkevičius L. (2020). A new multiple outliers identification method in linear regression. Metrika, doi:10.1007/s00184-019-00731-8

2019:

• Žilinskas, A., Baronas, R., Litvinas, L. & Petkevičius, L. (2019). Multi-objective optimization and decision visualization of batch stirred tank reactor based on spherical catalyst particles, Nonlinear Analysis: Modelling and Control, 24(6), p. 1019–1033. doi: 10.15388/NA.2019.6.10.
• Baronas, R., Kulys J., Petkevičius L. (2019). Computational modeling of batch stirred tank reactor based on spherical catalyst particles. Journal of Mathematical Chemistry, doi:10.1007/S10910-018-0954-X.

2018:

• Baronas, R., Kulys J., Petkevičius L. (2018). Modelling the enzyme catalysed substrate conversion in a microbioreactor acting in continuous flow mode. Nonlinear Analysis: Modelling and Control, 23(3), 437-456. doi:10.15388/NA.2018.3.9
• Neverauskiene, A., Maciusovic, M., Burkanas, M., Griciene, B., Petkevicius, L., Zaleckas, L., Tamosiunas A. & Venius, J. (2018). Image based simulation of the low dose computed tomography images suggests 13 mAs 120 kV suitability for non-syndromic craniosynostosis diagnosis without iterative reconstruction algorithms. European Journal of Radiology, 105, 168-174. doi:10.1016/j.ejrad.2018.06.005
• Petrulis, A., Petkevičius, L., Vitta, P., Vaicekauskas, R., & Žukauskas, A. (2017). Exploring Preferred Correlated Color Temperature in Outdoor Environments Using a Smart Solid-State Light Engine. LEUKOS, 14(2), 95-106. doi:10.1080/15502724.2017.1377085

2016:

• Čelutkienė, J., Burneikaitė, G., Petkevičius, L., Balkevičienė, L., & Laucevičius, A. (2016). Combination of single quantitative parameters into multiparametric model for ischemia detection is not superior to visual assessment during dobutamine stress echocardiography. Cardiovascular ultrasound, 14(1), 13. doi:10.1186/s12947-016-0055-6

Tarptautinių recenzuojamų konferencijų darbai:

• Petkevicius, L., Saltenis, S., Civilis, A., & Torp, K. (2021). Probabilistic Deep Learning for Electric-Vehicle Energy-Use Prediction. In 17th International Symposium on Spatial and Temporal Databases (pp. 85-95).
• Žvirblis, T., Petkevičius, L., Vaitkus, P., Šabanovič, E., Skrickij, V., Kilikevičius, A. (2021). Investigation of Deep Neural Networks for Hypoid Gear Signal Classification to Identify Anomalies. In 2020 IEEE 8th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE) (pp. 1-6). IEEE.
• Jonaitytė, I., Petkevičius, L. (2021). Analysis of Information Compression of Medical Images for Survival Models. In 2021 IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream) (pp. 1-6). IEEE.
• Brusokas, J., Petkevičius L. (2020) Analysis of Deep Neural Network Architectures and Similarity Metrics for Low-Dose CT Reconstruction. IEEE Open Conference of Electrical, Electronic and Information Sciences (eStream). IEEE.
• Petkevičius L. (2019). Applying Homotopy Perturbation Method to Non-Linear Differential Equations. In ESM 2019: The 33rd annual European Simulation and Modelling Conference, (pp. 1-3).
• Petkevičius L., Baronas, R. (2019). Modeling and simulation of porous multi layer microbioreactors. In ECMS 2019: Communications of the ECMS, Vol. 33, Issue 1, (pp. 190-196).
• J. Brusokas, Petkevičius L. (2019). Numerical analysis of SLSSIM similarity on medical X-ray image domain. Proceedings of the XXIV International Master and Phd Students Conference “Information Society” (IVUS 2019) (pp. 119-124).
• Petkevičius L., Baronas, R. (2018). Numerical analysis of the dynamics of reactant conversion in batch stirred tank reactor. Advances in information, electronic and electrical engineering (AIEEE), 2018 (pp. 1-6).
• Petkevičius L., Baronas, R. (2017). Numerical Simulation and Analysis of Enzyme-Catalysed Substrate Conversion in a Microbioreactor. In SIMUL 2017: The Ninth International Conference on Advances in System Simulation (pp. 1-6).