Publications

The papers in selected ISI journals:

Gnip P, Vokorokos L, Drotár P. (2021). Selective oversampling approach for strongly imbalanced data. PeerJ Computer Science 7:e604 https://doi.org/10.7717/peerj-cs.604

Gazda, M., Hireš, M. and Drotár, P.,  Multiple-Fine-Tuned Convolutional Neural Networks for Parkinson's Disease Diagnosis From Offline Handwriting,  in IEEE Transactions on Systems, Man, and Cybernetics: Systems, doi: 10.1109/TSMC.2020.3048892.

Drotár, P., Dobeš, M. (2020). Dysgraphia detection through machine learning.Scientific Reports, 10, 21541. doi:10.1038/s41598-020-78611-9 (OPEN ACCESS)

Šlapak, E.., Gazda, J.,  Guo, W., Maksymyuk, T.,  Dohler M. (2021). Cost-Effective Resource Allocation for Multitier Mobile Edge Computing in 5G Mobile Networks, IEEE Access, doi: 10.1109/ACCESS.2021.3059029

Maksymyuk, T., Šlapak, E., Bugár, G., Horvath, D., Gazda, J. (2020). Intelligent framework for radio access network design, Wireless Networks, https://doi.org/10.1007/s11276-019-02172-7

Maksymyuk, T.,  Gazda, J., Volosin, M., Bugar, G., Horvath, D., Klymash, M., Dohler, M. (2020). Blockchain-Empowered Framework for Decentralized Network Management in 6G, IEEE Communications Magazine, doi: 10.1109/MCOM.001.2000175

Khan, M., Jamali, M., Maksymyuk, T., Gazda, J., (2020). A Blockchain Token-Based Trading Model for Secondary Spectrum Markets in Future Generation Mobile Networks, Wireless Communications and Mobile Computing, https://doi.org/10.1155/2020/7975393

Bugata, P., Drotar, P. (2020) On some aspects of minimum redundancy maximum relevance feature selection. Sci. China Inf. Sci. 63, 112103 (2020). https://doi.org/10.1007/s11432-019-2633-y 

Bugár, G., Vološin, M., Maksymyuk, T., Zausinová, J., Gazda, V., Horváth, D., Gazda, J. (2019). Techno-Economic Framework for Dynamic Operator Selection in a Multi-Tier Heterogeneous Network, Ad Hoc Networks. ISSN 1570-8705, https://doi.org/10.1016/j.adhoc.2019.102007

Zoričák, M., Gnip, P., Drotár, P., Gazda, V. (2019). Bankruptcy prediction for small- and medium-sized companies using severely imbalanced datasets, Economic Modelling. ISSN 0264-9993, https://doi.org/10.1016/j.econmod.2019.04.003.

Drotár, P., Gazda, M., Vokorokos, L. (2019). Ensemble feature selection using election methods and ranker clustering. Information Sciences, Vol. 480, pp. 365-380, ISSN 0020-0255

Bugata, P.,  Drotár, P. (2018). Weighted nearest neighbors feature selection. Knowledge-Based Systems, https://doi.org/10.1016/j.knosys.2018.10.004.

Dankovičová, Z., Sovák, D., Drotár, P., Vokorokos. L. (2018). Machine Learning Approach to Dysphonia Detection. Applied Sciences. 8, 1927, https://doi.org/10.3390/app8101927.

Gazda, J., Šlapak, E., Bugár, G., Horváth, D., Maksymyuk, T., & Jo, M. (2018). Unsupervised Learning Algorithm for Intelligent Coverage Planning and Performance Optimization of Multitier Heterogeneous Network. IEEE Access, 6, 39807-39819.

Gazda, J., Tóth, P., Zausinová, J., Vološin, M., & Gazda, V. (2017). On the Interdependence of the Financial Market and Open Access Spectrum Market in the 5G Network. Symmetry, 10(1), 12. 

Gazda, J., Bugár, G., Vološin, M., Drotár, P., Horváth, D., & Gazda, V. (2017). Dynamic spectrum leasing and retail pricing using an experimental economy. Computer Networks, 121, 173-184.
Horvath, D., Gazda, J., & Brutovsky, B. (2017). A new bio-inspired, population-level approach to the socioeconomic evolution of dynamic spectrum access services. International Journal of Modern Physics C, 28(05), 1750062.      

Gazda, J., Kováč, V., Tóth, P., Drotár, P., & Gazda, V. (2016). Tax optimization in an agent-based model of real-time spectrum secondary market. Telecommunication Systems, 1-16.

Pastirčák, J., Friga, L., Kováč, V., Gazda, J., & Gazda, V. (2016). An Agent-Based Economy Model of Real-Time Secondary Market for the Cognitive Radio Networks. Journal of Network and Systems Management, 24(2), 427-443.

Drotár, P., Gazda, J., & Smékal, Z. (2015). An experimental comparison of feature selection methods on two-class biomedical datasets. Computers in biology and medicine, 66, 1-10.

Drotár, P., Mekyska, J., Rektorová, I., Masarová, L., Smékal, Z., & Faundez-Zanuy, M. (2016). Evaluation of handwriting kinematics and pressure for differential diagnosis of Parkinson's disease. Artificial intelligence in medicine, 67, 39-46.

Drotár, P., Mekyska, J., Rektorová, I., Masarová, L., Smékal, Z., & Faundez-Zanuy, M. (2014). Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease. Computer methods and programs in biomedicine, 117(3), 405-411.

Drotár, P., Mekyska, J., Rektorová, I., Masarová, L., Smékal, Z., & Faundez-Zanuy, M. (2015). Decision support framework for parkinson’s disease based on novel handwriting markers. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 23(3), 508-516.

Kollár, Z., Gazda, J., Horváth, P., Varga, L., & Kocur, D. (2014). Iterative signal reconstruction of deliberately clipped SMT signals. Science China Information Sciences, 57(2), 1-13.

Horváth, D., Gazda, V., & Gazda, J. (2013). Agent-based modeling of the cooperative spectrum management with insurance in cognitive radio networks. EURASIP Journal on Wireless Communications and Networking, 2013(1), 1-14.

Gazda, J., Deumal, M., Bergada, P., Drotár, P., Kocur, D., & Galajda, P. (2011). Iterative Suboptimal Maximum Likelihood Receiver for Nonlinearly Distorted SC-FDMA Symbols. Frequenz, 65(11-12), 327-334.

Gazda, J., Drotar, P., Deumal, M., Galajda, P., & Kocur, D. (2010). Tone reservation for sfbc-ofdm with no spectral broadening. Frequenz, 64(7-8), 140-143.

Drotar, P., Gazda, J., Galajda, P., Kocur, D., & Pavelka, P. (2010). Receiver technique for iterative estimation and cancellation of nonlinear distortion in MIMO SFBC-OFDM systems. IEEE Transactions on Consumer Electronics, 56(2), 471-475.

Gazda, J., Kocur, D., Drotar, P., & Galajda, P. (2009). Effects of spreading sequences on the performance of MC-CDMA system with nonlinear models of HPA. Radioengineering.