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Bejelentkezés
A Tudóstér funkcióinak nagy része bejelentkezés nélkül is elérhető. Bejelentkezésre az alábbi műveletekhez van szükség:
Palinszky, A.,
Fazekas, A.:
Analyzing the Performance of the k-Nearest Neighbor Classifier Using Metrics Based on Neighborhood Sequences.
Proceedings of 13th International Conference on Applied Informatics 2026, 1-2, 2026.
Haoyuan, L.,
Bobály, M.,
Fazekas, A.:
A Proposed Method for Measuring the Esthetic Outcome of Head Surgery.
Proceedings of 13th International Conference on Applied Informatics 2026, 1-4, 2026.
Q1
Earth and Planetary Sciences (miscellaneous)
(2025)
Q1
Geography, Planning and Development
(2025)
5.
Al-Hamad, A.,
Csernoch, M.,
Gilányi, A.:
Enhancing warehouse safety and resilience through virtual reality: A user-centered design approach to training feasibility.
Journal of Safety Science and Resilience. [Epub ahead of print], 1-20, (cikkazonosító: 100305), 2026.
Fazekas, A.:
Factors Influencing Classification Performance and the Reliability of Performance Scores.
In: Book of Abstracts from the Innovation in Engineering Education Conference (IEE2026). Szerk.: Szilvia Árvai-Homolya, Sándor Lajos, László Rónai, Miskolci Egyetemi Kiadó, Miskolc, 11-11, 2026. ISBN: 9789633584255
Csernoch, M.,
Biró, P.:
Handling conditional calculation algorithms in spreadsheet environments.
In: Education and New Developments 2026. Ed.: Mafalda Carmo, World Institute for Advanced Research and Science, Portugal, 281-285, 2026, (ISSN 2184-1489) ISBN: 9789893683941
Csernoch, M.,
Hannusch, C.:
Problem-solving strategies of teachers and students in digital text management.
Humanit Soc Sci Commun. [Epub ahead of print], 2026.
Q1
Business, Management and Accounting (miscellaneous)
(2025)
Q1
Economics, Econometrics and Finance (miscellaneous)
(2025)
Q1
Psychology (miscellaneous)
(2025)
Q1
Social Sciences (miscellaneous)
(2025)
11.
Dömösi, P.,
Horváth, G.:
Szkrembler berendezés és eljárás különösen kriptográfiai alkalmazásokhoz, valamint deszkrembler berendezés és eljárás azokhoz.
Khudhair, M. A.,
Fazekas, A.:
A comparative study on the noise sensitivity of binary classification based on robust deep neural networks.
Ann. Math. Inform. 61, 129-140, 2025.
Ahmad, H.,
Hannusch, C.:
A Scalable Symmetric Cryptographic Scheme Based on Latin Square, Permutations, and Reed-Muller Codes for Resilient Encryption.
Cryptography. 9 (4), 1-28, (cikkazonosító: 70), 2025.
Biró, P.,
Nagy, Z.,
Csernoch, M.:
Assessment of prior knowledge and algorithmic skills among first-year computer science students.
In: 17th International Conference on Economics and Business: Challenges in the Carpathian Basin / Nagy Benedek, Editura Risoprint, Cluj-Napoca, 329-338, 2025.
Murvai, A.,
Vaszil, G.:
On the Power of Small Watson-Crick Automata and Variants of String Assembling Systems.
In: Machines, Computations, and Universality 10th International Conference, MCU 2024, Nice, France, June 5-7, 2024, Revised Selected Papers / Enrico Formenti, Jérôme Durand-Lose, Springer, Cham, 89-102, 2025, (Lecture Notes in Computer Science, ISSN 0302-9743 ; 15270) ISBN: 9783031812019
Revákné Markóczi, I.,
Csernoch, M.,
Czimre, K.,
Dávid, Á.,
Tóthné Kosztin, B.,
Malmos, E.,
Sütő, É.,
Kurucz, D.:
A systematic review of STEM teaching-learning methods and activities in early childhood.
EURASIA J Math Sci Tech Ed. 20 (8), 1-22, (cikkazonosító: 2481), 2024.
