研究業績

2023年度

主な論文・著書・特許等

1. A.K. Tran, D.V. Nguyen, M.S. Dao, K. Zettsu: AOP: Towards Adaptive Offloading Point Approach in a Federated Learning Framework for Edge AI Applications, The 29th IEEE International Conference on Parallel and Distributed Systems (ICPADS 2023), Ocean Flower Island (海花岛), Hainan, China (December 2023).
2. M.S. Dao, H.Q. Ung, S. Ito, S. Wada, K. Zettsu: Fostering Innovation in Urban Transportation Risk Management: A Multi-Sector Collaborative Benchmarking Platform, IEEE Big Data 2023, HILTON SORRENTO PALACE Via Sant'Antonio 13 | 80067 | Sorrento | Napoli | Italy, pp.1903-1907 (December 2023).
3. P. Veena, R.U. Kiran, P. Ravikumar, P. Likhitha, Y. Watanobe, S. Ito, K.Zettsu, M.Toyoda, B. Venus Vikranth Raj: 3P-ECLAT: mining partial periodic patterns in columnar temporal databases, Applied Intelligence (December 2023).
4. M.S. Dao, H. Pradana, K. Zettsu: MM-TrafficRisk: A Video-based Fleet Management Application for Traffic Risk Prediction, Prevention, and Querying, IEEE Big Data 2023, HILTON SORRENTO PALACE Via Sant'Antonio 13 | 80067 | Sorrento | Napoli | Italy, pp.1697-1706 (December 2023).
5. 是津耕司：スマート都市デジタルツインのためのAIプラットフォーム, 電子情報通信学会技術研究報告, Vol 123, No. 248, pp.42-46 (2023年11月).
6. D.V. Nguyen: Federated learning with Diverse Edges in IoT intelligent systems, The 9th IEEE World Forum on the Internet of Things, Online (October 2023).
7. P. Veena, T. Sreepada, R.U. Kiran, M.S. Dao, K. Zettsu, Y. Watanobe, J. Zhang: Mining Periodic-Frequent Patterns in Irregular Dense Temporal Databases Using Set Compliments, IEEE Access, Vol.11, pp.118676-118688 (October 2023).
8. P. Veena, R.U. Kiran, P. Ravikumar, P. Likhitha, Y. Hayamizu, K. Goda, M. Toyoda, K. Zettsu, S. Shrivastava: A fundamental approach to discover closed periodic‐frequent patterns in very large temporal databases, Journal of Applied Intelligence, pp.1-30 (September 2023).
9. K. Zettsu: Digital Twin Orchestration, IOWN Global Forum 6th Member Meeting, Munich, Germany (September 2023).
10. P. Veena, P. Likhitha, R.U. Kiran, J.M. Luna, P. Fournier-Viger, K. Zettsu: Discovering Fuzzy Partial Periodic Patterns in Quantitative Irregular Multiple Time Series, IEEE-Fuzzy 2023, Songdo Incheon, Korea (August 2023).
11. M.A. Ton-Thien, C.T. Nguyen, Q.M. Le, D.Q. Duong, M.S. Dao, B. Nguen: Air Pollution Forecasting Using Multimodal Data, International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE) 2023, Online, Vol.13926, pp.360-371 (July 2023).
12. M.S. Dao, K. Zettsu: Leveraging Knowledge Graphs for CheapFakes Detection: Beyond Dataset Evaluation, ICME 2023 - Grand Challenge of CheapFakes Detection, Brisbane, Australia, pp.99-104 (July 2023).
13. H. Pradana: An End-to-End Online Traffic-Risk Incident Prediction in First-Person Dash Camera Videos, Big Data and Cognitive Computing, Vol.7, pp.129 (July 2023).
14. G. Habault, M.S. Dao, M.A. Riegler, D.T.D. Nguyen, Y. Nakashima, C. Gurrin: ICDAR’23: Intelligent Cross-Data Analysis and Retrieval, ICMR2023 - ICDAR workshop, Thessaloniki, Greece, pp.674-675 (June 2023).
15. K.L. Pham, M.T. Nguyen, A.D. Tran, M.S. Dao, D.T. Dang-Nguyen: Detecting Cheapfakes using Self-Query Adaptive-Context Learning, ICMR 2023 - ICDAR workshop, Thessaloniki, Greece, pp.60-63 (June 2023).
16. W. Gan, M.S. Dao, K. Zettsu: Procedural Driving Skill Coaching from More Skilled Drivers to Safer Drivers: A Survey, 4th ACM Workshop on Intelligent Cross-Data Analysis and Retrieval, ACM International Conference on Multimedia Retrieval 2023, Thessaloniki, Greece, pp.10-18 (June 2023).
17. H.Q. Ung, Y. Mishima, H. Niu, S. Wada: Towards Multimodal Spatio-Temporal Transformer-based Modelsfor Traffic Congestion Prediction, ICMR 2023 - ICDAR Workshop, Thessaloniki, Greece, pp.19-23 (June 2023).
18. P. Likhitha, P. Veena, R.U. Kiran, K. Zettsu: Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases, PAKDD 2023, Osaka, Japan, pp.29-41 (May 2023).