Analysis of the Dynamic Relationship between Transgressive Innovation Behavior and Team Network Structure in High-Tech Firms

Autor: Xu Xingqiang, Youngwook KO

Publikováno v: Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)

The current market economy has stepped into the stage of high-quality development led by innovation. How to effectively improve the innovation capacity of enterprises has become a widespread concern in the academic community. The article first analyz

Externí odkaz: https://doaj.org/article/e5f4bcb66da8404291b59924934ea628

Reinforcement Learning for NOMA-ALOHA Under Fading

Autor: Youngwook Ko, Jinho Choi

Publikováno v: IEEE Transactions on Communications. 70:6861-6873

We consider a non-orthogonal multiple access in a random-access ALOHA system, in which each user randomly accesses one out of different time slots and send uplink packets based on power differences. In the context of an asymmetric game, we propose a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64bafbc6ce5c9f4f5171f96461e25899
https://doi.org/10.1109/tcomm.2022.3198125

Do gender equality and work–life balance matter for innovation performance?

Autor: Chungwon Woo, Yanghon Chung, Youngwook Ko, Hyesoo Ko

Publikováno v: Technology Analysis & Strategic Management. 33:148-161

Gender equality and work–life balance are highlighted in innovation research, as those are directly related to the work environment of R&D personnel. This study empirically explores how scientists’...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::7280c54ce5f66327ac06a204cfe92b9c
https://doi.org/10.1080/09537325.2020.1799971

Deep Learning-Aided Multicarrier Systems

Autor: Michail Matthaiou, Minh-Tuan Le, Thien Van Luong, Vu-Duc Ngo, Youngwook Ko, Ngo Anh Vien

Publikováno v: Luong, T V, Ko, Y, Matthaiou, M, Ngo, V, Le, M-T & Ngo, V-D 2020, ' Deep Learning-Aided Multicarrier Systems ', IEEE Transactions on Wireless Communications . https://doi.org/10.1109/TWC.2020.3039180

This paper proposes a deep learning (DL)-aided multicarrier (MC) system operating on fading channels, where both modulation and demodulation blocks are modeled by deep neural networks (DNNs), regarded as the encoder and decoder of an autoencoder (AE)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::313680fe681a089eb07d46a17126a40d
https://eprints.whiterose.ac.uk/168094/1/FINAL_VERSION.pdf

Deep energy autoencoder for noncoherent multicarrier MU-SIMO systems

Autor: Youngwook Ko, Thien Van Luong, Hien Quoc Ngo, Ngo Anh Vien, Michail Matthaiou

Publikováno v: Luong, T V, Ko, Y, Vien, N A, Matthaiou, M & Ngo, H Q 2020, ' Deep energy autoencoder for noncoherent multicarrier MU-SIMO systems ', IEEE Transactions on Wireless Communications, vol. 19, no. 6, pp. 3952-3962 . https://doi.org/10.1109/TWC.2020.2979138

We propose a novel deep energy autoencoder (EA) for noncoherent multicarrier multiuser single-input multipleoutput (MU-SIMO) systems under fading channels. In particular, a single-user noncoherent EA-based (NC-EA) system, based on the multicarrier SI

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e0cbedb18ea6de5dc26e5af8a81bb58
https://pure.qub.ac.uk/en/publications/3781ff92-2f92-4aa1-95a9-af5cad82a0e9