AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
How to
Here you can find the complete list of our publications.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Liu, Y.; Li, Z.
Research on the Design System of Bamboo-Woven Products Based on Traditional Bamboo-Weaving Craft VR Experience Journal Article
In: Forest Products Journal, vol. 75, no. 3, pp. 238–250, 2025, ISSN: 00157473 (ISSN), (Publisher: Forest Products Society).
Abstract | Links | BibTeX | Tags: 3D modeling, Artificial intelligence, Bamboo, Design models, Design systems, evaluation, Experience design, Function evaluation, Human computer interaction, Learn+, Low-costs, Novel techniques, Product design, Product experience, Products, Reliability analysis, Systems analysis, Systems Engineering, Techniques, user experience, User interfaces, Virtual Reality, Virtual reality experiences, Weaving, Weaving technique, Woven products
@article{liu_research_2025,
title = {Research on the Design System of Bamboo-Woven Products Based on Traditional Bamboo-Weaving Craft VR Experience},
author = {Y. Liu and Z. Li},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105013654324&doi=10.13073%2FFPJ-D-25-00005&partnerID=40&md5=d03d78771ee8194ffc8450d259b5f129},
doi = {10.13073/FPJ-D-25-00005},
issn = {00157473 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Forest Products Journal},
volume = {75},
number = {3},
pages = {238–250},
abstract = {Virtual reality (VR) is a simulated experience capable of replicating or creating an entirely new environment. Through VR experience, designers can learn bamboo-weaving techniques at a low cost and showcase their design models of bamboo-woven products virtually, allowing these products to be put into production after experience and evaluation. This study introduces novel techniques to transform and innovate traditional bamboo-woven products to establish a comprehensive VR-based product experience design system. This system follows a pioneering pathway, including the following steps: VR weaving skill experience, generative artificial intelligence design (AIGC)–driven bamboo design creativity, 3D modeling technology support, and VR product evaluation. Moreover, the framework conducts user experience research from three dimensions: visual design, system function design, and human–computer interaction design. Usability assessments and statistical analysis were employed before and after the VR experience to assess the system’s reliability. The findings indicate that designers and users can remarkably use and evaluate the new system, offering a practical technical pathway for the modern design exploration of traditional bamboo products. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Forest Products Society},
keywords = {3D modeling, Artificial intelligence, Bamboo, Design models, Design systems, evaluation, Experience design, Function evaluation, Human computer interaction, Learn+, Low-costs, Novel techniques, Product design, Product experience, Products, Reliability analysis, Systems analysis, Systems Engineering, Techniques, user experience, User interfaces, Virtual Reality, Virtual reality experiences, Weaving, Weaving technique, Woven products},
pubstate = {published},
tppubtype = {article}
}
Virtual reality (VR) is a simulated experience capable of replicating or creating an entirely new environment. Through VR experience, designers can learn bamboo-weaving techniques at a low cost and showcase their design models of bamboo-woven products virtually, allowing these products to be put into production after experience and evaluation. This study introduces novel techniques to transform and innovate traditional bamboo-woven products to establish a comprehensive VR-based product experience design system. This system follows a pioneering pathway, including the following steps: VR weaving skill experience, generative artificial intelligence design (AIGC)–driven bamboo design creativity, 3D modeling technology support, and VR product evaluation. Moreover, the framework conducts user experience research from three dimensions: visual design, system function design, and human–computer interaction design. Usability assessments and statistical analysis were employed before and after the VR experience to assess the system’s reliability. The findings indicate that designers and users can remarkably use and evaluate the new system, offering a practical technical pathway for the modern design exploration of traditional bamboo products. © 2025 Elsevier B.V., All rights reserved.
2024
Haramina, E.; Paladin, M.; Petričušić, Z.; Posarić, F.; Drobnjak, A.; Botički, I.
Learning Algorithms Concepts in a Virtual Reality Escape Room Proceedings Article
In: Babic, S.; Car, Z.; Cicin-Sain, M.; Cisic, D.; Ergovic, P.; Grbac, T. G.; Gradisnik, V.; Gros, S.; Jokic, A.; Jovic, A.; Jurekovic, D.; Katulic, T.; Koricic, M.; Mornar, V.; Petrovic, J.; Skala, K.; Skvorc, D.; Sruk, V.; Svaco, M.; Tijan, E.; Vrcek, N.; Vrdoljak, B. (Ed.): ICT Electron. Conv., MIPRO - Proc., pp. 2057–2062, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 9798350382495 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Computational complexity, Computer generated three dimensional environment, E-Learning, Education, Escape room, Extended reality, generative artificial intelligence, Learn+, Learning, Learning algorithms, Learning systems, Puzzle, puzzles, user experience, User study, User testing, Users' experiences, Virtual Reality
@inproceedings{haramina_learning_2024,
title = {Learning Algorithms Concepts in a Virtual Reality Escape Room},
author = {E. Haramina and M. Paladin and Z. Petričušić and F. Posarić and A. Drobnjak and I. Botički},
editor = {S. Babic and Z. Car and M. Cicin-Sain and D. Cisic and P. Ergovic and T. G. Grbac and V. Gradisnik and S. Gros and A. Jokic and A. Jovic and D. Jurekovic and T. Katulic and M. Koricic and V. Mornar and J. Petrovic and K. Skala and D. Skvorc and V. Sruk and M. Svaco and E. Tijan and N. Vrcek and B. Vrdoljak},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85198221737&doi=10.1109%2FMIPRO60963.2024.10569447&partnerID=40&md5=ee56896e4128fd5a8bef03825469a46f},
doi = {10.1109/MIPRO60963.2024.10569447},
isbn = {9798350382495 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {ICT Electron. Conv., MIPRO - Proc.},
pages = {2057–2062},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Although the standard way to learn algorithms is by coding, learning through games is another way to obtain knowledge while having fun. Virtual reality is a computer-generated three-dimensional environment in which the player is fully immersed by having external stimuli mostly blocked out. In the game presented in this paper, players are enhancing their algorithms skills by playing an escape room game. The goal is to complete the room within the designated time by solving puzzles. The puzzles change for every playthrough with the use of generative artificial intelligence to provide every player with a unique experience. There are multiple types of puzzles such as. time complexity, sorting algorithms, searching algorithms, and code execution. The paper presents the results of a study indicating students' preference for learning through gaming as a method of acquiring algorithms knowledge. © 2024 Elsevier B.V., All rights reserved.},
keywords = {Artificial intelligence, Computational complexity, Computer generated three dimensional environment, E-Learning, Education, Escape room, Extended reality, generative artificial intelligence, Learn+, Learning, Learning algorithms, Learning systems, Puzzle, puzzles, user experience, User study, User testing, Users' experiences, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
Although the standard way to learn algorithms is by coding, learning through games is another way to obtain knowledge while having fun. Virtual reality is a computer-generated three-dimensional environment in which the player is fully immersed by having external stimuli mostly blocked out. In the game presented in this paper, players are enhancing their algorithms skills by playing an escape room game. The goal is to complete the room within the designated time by solving puzzles. The puzzles change for every playthrough with the use of generative artificial intelligence to provide every player with a unique experience. There are multiple types of puzzles such as. time complexity, sorting algorithms, searching algorithms, and code execution. The paper presents the results of a study indicating students' preference for learning through gaming as a method of acquiring algorithms knowledge. © 2024 Elsevier B.V., All rights reserved.
2023
Park, J.; Choi, J.; Kim, S. -L.; Bennis, M.
Enabling the Wireless Metaverse via Semantic Multiverse Communication Proceedings Article
In: Annu. IEEE Commun.Soc. Conf. Sens., Mesh Ad Hoc Commun. Netw. workshops, pp. 85–90, IEEE Computer Society, 2023, ISBN: 21555486 (ISSN); 979-835030052-9 (ISBN).
Abstract | Links | BibTeX | Tags: Deep learning, Extended reality (XR), Federated learning, Fertilizers, Learn+, Learning systems, Metaverse, Metaverses, Modal analysis, Multi agent systems, Multi-agent reinforcement learning, Multi-modal data, Reinforcement Learning, Semantic communication, Semantics, Signal encoding, Signaling game, Split learning, Symbolic artificial intelligence
@inproceedings{park_enabling_2023,
title = {Enabling the Wireless Metaverse via Semantic Multiverse Communication},
author = {J. Park and J. Choi and S. -L. Kim and M. Bennis},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85177465286&doi=10.1109%2fSECON58729.2023.10287438&partnerID=40&md5=b052572fb2f78ce0694c7ae5726c8daf},
doi = {10.1109/SECON58729.2023.10287438},
isbn = {21555486 (ISSN); 979-835030052-9 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {Annu. IEEE Commun.Soc. Conf. Sens., Mesh Ad Hoc Commun. Netw. workshops},
volume = {2023-September},
pages = {85–90},
publisher = {IEEE Computer Society},
abstract = {Metaverse over wireless networks is an emerging use case of the sixth generation (6G) wireless systems, posing unprecedented challenges in terms of its multi-modal data transmissions with stringent latency and reliability requirements. Towards enabling this wireless metaverse, in this article we propose a novel semantic communication (SC) framework by decomposing the metaverse into human/machine agent-specific semantic multiverses (SMs). An SM stored at each agent comprises a semantic encoder and a generator, leveraging recent advances in generative artificial intelligence (AI). To improve communication efficiency, the encoder learns the semantic representations (SRs) of multi-modal data, while the generator learns how to manipulate them for locally rendering scenes and interactions in the metaverse. Since these learned SMs are biased towards local environments, their success hinges on synchronizing heterogeneous SMs in the background while communicating SRs in the foreground, turning the wireless metaverse problem into the problem of semantic multiverse communication (SMC). Based on this SMC architecture, we propose several promising algorithmic and analytic tools for modeling and designing SMC, ranging from distributed learning and multi-agent reinforcement learning (MARL) to signaling games and symbolic AI. © 2023 IEEE.},
keywords = {Deep learning, Extended reality (XR), Federated learning, Fertilizers, Learn+, Learning systems, Metaverse, Metaverses, Modal analysis, Multi agent systems, Multi-agent reinforcement learning, Multi-modal data, Reinforcement Learning, Semantic communication, Semantics, Signal encoding, Signaling game, Split learning, Symbolic artificial intelligence},
pubstate = {published},
tppubtype = {inproceedings}
}
Metaverse over wireless networks is an emerging use case of the sixth generation (6G) wireless systems, posing unprecedented challenges in terms of its multi-modal data transmissions with stringent latency and reliability requirements. Towards enabling this wireless metaverse, in this article we propose a novel semantic communication (SC) framework by decomposing the metaverse into human/machine agent-specific semantic multiverses (SMs). An SM stored at each agent comprises a semantic encoder and a generator, leveraging recent advances in generative artificial intelligence (AI). To improve communication efficiency, the encoder learns the semantic representations (SRs) of multi-modal data, while the generator learns how to manipulate them for locally rendering scenes and interactions in the metaverse. Since these learned SMs are biased towards local environments, their success hinges on synchronizing heterogeneous SMs in the background while communicating SRs in the foreground, turning the wireless metaverse problem into the problem of semantic multiverse communication (SMC). Based on this SMC architecture, we propose several promising algorithmic and analytic tools for modeling and designing SMC, ranging from distributed learning and multi-agent reinforcement learning (MARL) to signaling games and symbolic AI. © 2023 IEEE.