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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.
Kondor, K.,
Horváth, G.:
Comparing evolutionary algorithms and reinforcement learning algorithms in “mate-in-N” puzzles.
In: 2026 IEEE 4th Conference on Information Technology and Data Science (CITDS) Proceedings. Ed.: Hajdu András ISBN: 9798319507006
Q1
Earth and Planetary Sciences (miscellaneous)
(2025)
Q1
Geography, Planning and Development
(2025)
6.
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. 7 (4), 1-20, (cikkazonosító: 100305), 2026.
Q2
Management Science and Operations Research
(2025)
Q2
Computer Science Applications
(2025)
Q1
Safety Research
(2025)
Q1
Safety, Risk, Reliability and Quality
(2025)
Q2
Statistics, Probability and Uncertainty
(2025)
7.
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.
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.
Battyányi, P.:
Normalization in the [lambda][mü][mü prime]-calculus.
In: 14th International Conference Logic and Applications, LAP 2025, September 24-28, 2025 Dubrovnik, Croatia Book of Abstracts. Eds.: Zvonimir Šikić; Andre Scedrov; Silvia Ghilezan; Zoran Ognjanović; Thomas Studer, Inter University Center Dubrovnik, Dubrovnik, Horvátország, 10-12, 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
