@article{MTMT:34735212,
	title = {Internal Model-Based Robust Path-Following Control for Autonomous Vehicles},
	url = {https://m2.mtmt.hu/api/publication/34735212},
	author = {Kovács, Adorján and Vajk, István},
	doi = {10.1007/s12239-024-00003-z},
	journal-iso = {INT J AUTOMOT TECHN},
	journal = {INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY},
	volume = {25},
	unique-id = {34735212},
	issn = {1229-9138},
	abstract = {The paper presents a new internal model control (IMC) based control technique for lateral trajectory tracking of autonomous vehicles. The controller’s proposed structure employs a robust, fault-tolerant nonlinear internal servo control with optimal reference generation concerning vehicle yaw stability and physical limitations. The presented inscription of the reference generation creates a convex optimization task that can be used in real-time applications. Improvements in yaw-rate stability of vehicle motion control are first shown through simulation results performed in a Simulink environment. The controller structure was also implemented in a real-time model and was examined in a Mercedes C-Class vehicle. In this article, the simulation results and the real-time measurements are presented. The results show that the proposed controller has high efficiency in disturbance rejection and lower sensitivity towards parameter changes compared to a model predictive control (MPC) structure.},
	keywords = {CONTROLLERS; Nonlinear control; Robust control; Control techniques; Model predictive control; Predictive control systems; Convex optimization; Model-based OPC; Internal model control; C (programming language); Non linear control; Internal models; Autonomous Vehicles; disturbance rejection; Path tracking control; Convex optimisation; path following control; Path-tracking control; Reference Generation},
	year = {2024},
	eissn = {1976-3832},
	pages = {249-260},
	orcid-numbers = {Vajk, István/0000-0002-2818-9162}
}

@article{MTMT:34450400,
	title = {A Novel Low Hardware Configurable Ring Oscillator (CRO) PUF for Lightweight Security Applications},
	url = {https://m2.mtmt.hu/api/publication/34450400},
	author = {AL-Magsoosi, Husam Kareem Farhan and Dunaev, Dmitriy},
	doi = {10.1016/j.micpro.2023.104989},
	journal-iso = {MICROPROCESS MICROSY},
	journal = {MICROPROCESSORS AND MICROSYSTEMS},
	volume = {104},
	unique-id = {34450400},
	issn = {0141-9331},
	year = {2024},
	eissn = {1872-9436}
}

@article{MTMT:34448114,
	title = {Optimal Selection of Switch Model Parameters for ADC-Based Power Converters},
	url = {https://m2.mtmt.hu/api/publication/34448114},
	author = {Alsarayreh, Saif and Sütő, Zoltán},
	doi = {10.3390/en17010056},
	journal-iso = {ENERGIES},
	journal = {ENERGIES},
	volume = {17},
	unique-id = {34448114},
	issn = {1996-1073},
	abstract = {Real-time hardware-in-the-loop-(HIL) simulation integration is now a fundamental component of the power electronics control design cycle. This integration is required to test the efficacy of controller implementations. Even though hardware-in-the-loop-(HIL) tools use FPGA devices with computing power that is rapidly evolving, developers constantly need to balance the ease of deploying models with acceptable accuracy. This study introduces a methodology for implementing a full-bridge inverter and buck converter utilising the associate-discrete-circuit-(ADC) model, which is optimised for real-time simulator applications. Additionally, this work introduces a new approach for choosing ADC parameter values by using the artificial-bee-colony-(ABC) algorithm, the firefly algorithm (FFA), and the genetic algorithm (GA). The implementation of the ADC-based model enables the development of a consistent architecture in simulation, regardless of the states of the switches. The simulation results demonstrate the efficacy of the proposed methodology in selecting optimal parameters for an ADC-switch-based full-bridge inverter and buck converter. These results indicate a reduction in overshoot and settling time observed in both the output voltage and current of the chosen topologies.},
	year = {2024},
	eissn = {1996-1073}
}

@article{MTMT:34415932,
	title = {A Robust Architecture of Ring Oscillator PUF: Enhancing Cryptographic Security with Configurability},
	url = {https://m2.mtmt.hu/api/publication/34415932},
	author = {AL-Magsoosi, Husam Kareem Farhan and Dunaev, Dmitriy},
	doi = {10.1016/j.mejo.2023.106022},
	journal-iso = {MICROELECTRON J},
	journal = {MICROELECTRONICS JOURNAL},
	volume = {143},
	unique-id = {34415932},
	issn = {0026-2692},
	year = {2024},
	eissn = {0959-8324}
}

@article{MTMT:34342470,
	title = {Exploring fair scheduling aspects-Through final exam scheduling},
	url = {https://m2.mtmt.hu/api/publication/34342470},
	author = {Erdős, Szilvia and Kővári, Bence András},
	doi = {10.1556/606.2023.00780},
	journal-iso = {POLLACK PERIODICA},
	journal = {POLLACK PERIODICA: AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES},
	volume = {19},
	unique-id = {34342470},
	issn = {1788-1994},
	year = {2024},
	eissn = {1788-3911},
	pages = {151-156},
	orcid-numbers = {Kővári, Bence András/0000-0003-1555-640X}
}

@article{MTMT:33999207,
	title = {Morphosyntactic probing of multilingual BERT models},
	url = {https://m2.mtmt.hu/api/publication/33999207},
	author = {Ács, Judit and Hamerlik, Endre and Schwartz, Roy and Smith, Noah A. and Kornai, András},
	doi = {10.1017/S1351324923000190},
	journal-iso = {NAT LANG ENG},
	journal = {NATURAL LANGUAGE ENGINEERING},
	unique-id = {33999207},
	issn = {1351-3249},
	abstract = {We introduce an extensive dataset for multilingual probing of morphological information in language models (247 tasks across 42 languages from 10 families), each consisting of a sentence with a target word and a morphological tag as the desired label, derived from the Universal Dependencies treebanks. We find that pre-trained Transformer models (mBERT and XLM-RoBERTa) learn features that attain strong performance across these tasks. We then apply two methods to locate, for each probing task, where the disambiguating information resides in the input. The first is a new perturbation method that “masks” various parts of context; the second is the classical method of Shapley values. The most intriguing finding that emerges is a strong tendency for the preceding context to hold more information relevant to the prediction than the following context.},
	year = {2024},
	eissn = {1469-8110},
	pages = {1-40},
	orcid-numbers = {Kornai, András/0000-0001-6078-6840}
}

@inproceedings{MTMT:34835609,
	title = {The survey of FPGA-based Hardware-In-The-Loop (HIL) simulation in Control Systems and Power Electronics},
	url = {https://m2.mtmt.hu/api/publication/34835609},
	author = {CHOWDHURY, MD MOSHIUR and Sütő, Zoltán},
	booktitle = {Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23)},
	unique-id = {34835609},
	year = {2023},
	pages = {103-114}
}

@inproceedings{MTMT:34763429,
	title = {Comparison of a Deep Learning-based Axle Load Estimator and the Matrix Method in Strain Gauge-based Bridge Weigh-In-Motion Systems},
	url = {https://m2.mtmt.hu/api/publication/34763429},
	author = {Szinyéri, Bence and Kővári, Bence András},
	booktitle = {2023 10th International Conference on Soft Computing & Machine Intelligence (ISCMI)},
	doi = {10.1109/ISCMI59957.2023.10458514},
	unique-id = {34763429},
	abstract = {One aspect of structural health monitoring of bridges is to monitor vehicular traffic. The demand for moni-toring bridge performance and life cycle has led to measuring traffic flow. We have previously developed a deep learning-based axle load estimator showing promising results considering COST 323 benchmark. This paper compares the deep learning-based solution to the established matrix method under different circumstances. Results show that the deep learning-based solution achieves better accuracy on several datasets of the BME-Simulated I corpus and has a better ability to handle noise than the matrix method. © 2023 IEEE.},
	keywords = {life cycle; BRIDGES; Bridge; Loads (forces); Axles; Deep learning; Deep learning; Deep learning; structural health monitoring; Comparison of methods; Comparison of methods; LOAD ESTIMATION; Strain gages; matrix methods; Axle load estimation; Weigh-In-Motion; Weigh-in-motion (WIM); Axle load estimation; Axle loads; Bridge performance; Strain-gages; Weigh-in-motion; Weigh-in-motion systems},
	year = {2023},
	pages = {12-16},
	orcid-numbers = {Kővári, Bence András/0000-0003-1555-640X}
}

@inproceedings{MTMT:34693431,
	title = {Towards Abstraction-Based Formal Verification of Static Modeling Constraints},
	url = {https://m2.mtmt.hu/api/publication/34693431},
	author = {Somogyi, Norbert},
	booktitle = {Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23)},
	unique-id = {34693431},
	year = {2023},
	pages = {174-185}
}

@inproceedings{MTMT:34689965,
	title = {Application of spherical lenses for efficiency enhancement of rectenna-based IR energy harvesting systems},
	url = {https://m2.mtmt.hu/api/publication/34689965},
	author = {Shubbar, Mustafa and Rakos, Balázs},
	booktitle = {Proceedings of the Automation and Applied Computer Science Workshop 2023 (AACS'23)},
	unique-id = {34689965},
	year = {2023},
	pages = {76-82}
}