@inbook{MTMT:34797365,
	title = {Massively Parallel EEG Algorithms for Pre-exascale Architectures},
	url = {https://m2.mtmt.hu/api/publication/34797365},
	author = {Wang, Zeyu and Juhász, Zoltán},
	booktitle = {Euro-Par 2023: Parallel Processing Workshops},
	doi = {10.1007/978-3-031-48803-0_34},
	unique-id = {34797365},
	year = {2024},
	pages = {290-295},
	orcid-numbers = {Juhász, Zoltán/0000-0003-0677-8588}
}

@article{MTMT:34765160,
	title = {Short-term system imbalance forecast using linear and non-linear methods},
	url = {https://m2.mtmt.hu/api/publication/34765160},
	author = {Balázs, István and Fodor, Attila and Magyar, Attila},
	doi = {10.1007/s12667-024-00667-7},
	journal-iso = {ENERGY SYSTEMS},
	journal = {ENERGY SYSTEMS: OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS},
	volume = {2024},
	unique-id = {34765160},
	issn = {1868-3967},
	abstract = {The imbalance between supply and demand is a critical factor in the operation of the power system, as it leads to a change in the system frequency. Therefore, it is essential to be able to predict its value from historical, measured and forecast data. Based on the assumption that system imbalance is correlated with measured values of system variables as well as predictions of exogenous variables, this work proposes a multi-step version of the autoregressive distributed lag model for the short-term forecast of system imbalance. The proposed forecasting model has been compared with a long short-term memory network-based procedure as well as with an extratree regression model using real data. The results show that the proposed multi-step autoregressive forecasting model outperforms the others in all three evaluation metrics. Since, in many cases, it is sufficient to specify the sign of the imbalance, this paper introduces the concept of sign accuracy as a function of the predicted imbalance and evaluates it for the investigated solutions.},
	year = {2024},
	eissn = {1868-3975},
	orcid-numbers = {Magyar, Attila/0000-0003-0196-7646}
}

@inbook{MTMT:34729046,
	title = {Word and Image Embeddings in Pill Recognition},
	url = {https://m2.mtmt.hu/api/publication/34729046},
	author = {Rádli, Richárd Bence and Vörösházi, Zsolt and Czúni, László},
	booktitle = {Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications},
	doi = {10.5220/0012460800003660},
	unique-id = {34729046},
	year = {2024},
	pages = {729-736}
}

@inproceedings{MTMT:34542541,
	title = {Visualization Methods to Support Real-time Process Monitoring},
	url = {https://m2.mtmt.hu/api/publication/34542541},
	author = {Nagy, Zsuzsanna and Starkné Werner, Ágnes},
	booktitle = {Proceedings of the 3rd International Workshop on Information Technologies: Theoretical and Applied Problems 2023},
	unique-id = {34542541},
	year = {2024},
	pages = {1-14}
}

@article{MTMT:34498874,
	title = {Európai cégek tulajdonosi szerkezetének dinamikus hálózatelemzése},
	url = {https://m2.mtmt.hu/api/publication/34498874},
	author = {Kosztyán, Zsolt Tibor and Király, Ferenc and Kurbucz, Marcell Tamás},
	doi = {10.18414/KSZ.2024.1.57},
	journal-iso = {KÖZGAZDASÁGI SZEMLE},
	journal = {KÖZGAZDASÁGI SZEMLE},
	volume = {71},
	unique-id = {34498874},
	issn = {0023-4346},
	abstract = {A társadalmi hálózatok elemzésének módszertanát egyre szélesebb körben alkalmazzák regionális kapcsolatok kialakulásának és fejlődésének modellezésére. Cikkünkben e módszertan, valamint a széleskörűen alkalmazott gravitációs modell segítségével megvizsgáljuk, hogy mely tényezők magyarázzák az európai vállalatok tulajdonosi szerkezetének kialakulását, illetve időbeli változásait. Az elemzés során felhasznált – 2010-től 2018-ig terjedő – adatok az európai vállalatokat tartalmazó Amadeus adatbázisból származnak, amely közel 24 millió vállalat gazdasági és tulajdonosi információit tartalmazza. A vállalati tulajdonosi kapcsolatokat NUTS3- (megyei) szinten aggregáltuk, majd az így meghatározott régiókhoz további földrajzi, technológiai és gazdasági adatokat rendeltünk.*
		Journal of Economic Literature (JEL) kód: C4, F1, M2, O3.},
	year = {2024},
	pages = {57-85},
	orcid-numbers = {Kosztyán, Zsolt Tibor/0000-0001-7345-8336; Kurbucz, Marcell Tamás/0000-0002-0121-6781}
}

@article{MTMT:34478524,
	title = {Impact of information technology supported serious leisure gardening on the wellbeing of older adults: The Turntable project},
	url = {https://m2.mtmt.hu/api/publication/34478524},
	author = {Vassányi, István and Szakonyi, Benedek and Loi, Daniela and Mantur-Vierendeel, Angelika and Quintas, Joăo and Solinas, Antonio and Blažica, Bojan and Raffo, Luigi and Guicciardi, Marco and Manca, Andrea and Gaál, Balázs and Rárosi, Ferenc},
	doi = {10.1016/j.gerinurse.2023.12.014},
	journal-iso = {GERIATR NURS},
	journal = {GERIATRIC NURSING},
	volume = {55},
	unique-id = {34478524},
	issn = {0197-4572},
	year = {2024},
	eissn = {1528-3984},
	pages = {339-345},
	orcid-numbers = {Mantur-Vierendeel, Angelika/0000-0001-6225-2308; Quintas, Joăo/0000-0002-8513-2664; Raffo, Luigi/0000-0001-9683-009X; Guicciardi, Marco/0000-0001-8136-775X; Manca, Andrea/0000-0003-2663-7475; Rárosi, Ferenc/0000-0002-1014-9242}
}

@article{MTMT:34395727,
	title = {Surpassing early stopping: A novel correlation-based stopping criterion for neural networks},
	url = {https://m2.mtmt.hu/api/publication/34395727},
	author = {Miseta, Tamás and Fodor, Attila and Fogarassyné Vathy, Ágnes},
	doi = {10.1016/j.neucom.2023.127028},
	journal-iso = {NEUROCOMPUTING},
	journal = {NEUROCOMPUTING},
	volume = {567},
	unique-id = {34395727},
	issn = {0925-2312},
	year = {2024},
	eissn = {1872-8286},
	pages = {127028},
	orcid-numbers = {Fogarassyné Vathy, Ágnes/0000-0002-5524-1675}
}

@CONFERENCE{MTMT:34818865,
	title = {Comparison of Optimization Algorithms for the Dynamic Capacitated Arc Routing Problem},
	url = {https://m2.mtmt.hu/api/publication/34818865},
	author = {Nagy, Zsuzsanna and Starkné Werner, Ágnes and Dulai, Tibor},
	booktitle = {Abstracts of the International Conference on Optimization and Algorithms (OPAL 2023) Semi Online 25},
	unique-id = {34818865},
	year = {2023},
	pages = {19-20}
}

@misc{MTMT:34734604,
	title = {Actuator Fault Estimation in Robot Platoons},
	url = {https://m2.mtmt.hu/api/publication/34734604},
	author = {Kurniawan, Wijaya and Márton, Lὄrinc},
	doi = {10.1109/ICSC58660.2023.10449746},
	publisher = {IEEE},
	unique-id = {34734604},
	abstract = {In controlled robot platoons, every subsystem needs information about the states of its neighbouring subsystems. On the other hand, actuator faults and communication errors have a considerable influence on the behaviour of the entire networked system. In this paper, an actuator fault diagnosis method is proposed that uses relative output information and it can be implemented without information interchange among the neighbouring subsystems. A subsystem model is proposed for the platoons, based on which the non-measurable states of the neighbouring subsystems can be determined by proper filtering techniques. In addition, the model is also used as the basis for designing a Proportional Integral (PI) observer for actuator fault estimation. Both the pole placement method and Linear Quadratic Estimator (LQE) are explored to determine the observer gain. The simulation results show that the model without network communication produces the same expected behaviour as the one that uses network communication. In addition, the proposed observer can correctly estimate the magnitude of the actuator fault.},
	year = {2023}
}

@inproceedings{MTMT:34573032,
	title = {Short-Term System Imbalance Forecast Using Autoregressive Distributed Lag Method},
	url = {https://m2.mtmt.hu/api/publication/34573032},
	author = {Balázs, István and Fodor, Attila and Magyar, Attila},
	booktitle = {2023 IEEE 6th International Conference and Workshop Óbuda on Electrical and Power Engineering (CANDO-EPE)},
	doi = {10.1109/CANDO-EPE60507.2023.10417995},
	unique-id = {34573032},
	abstract = {The imbalance between supply and demand is a crucial factor in the operation of the power system therefore, it is essential to be able to predict its value from historical, measured, and prediction data. This work proposes a multistep version of the autoregressive distributed lag model for the short-term forecast of imbalance. The proposed forecast model has been compared to a Long Short-Term Memory network-based procedure using real data. The results show that the proposed multistep autoregressive forecast model outperforms the others in all three evaluation metrics. Since, in many cases, it is sufficient to specify the sign of the imbalance, this paper introduces the concept of sign accuracy as a function of the forecasted imbalance and evaluates it for the investigated solutions.},
	year = {2023},
	pages = {000083-000088},
	orcid-numbers = {Magyar, Attila/0000-0003-0196-7646}
}