Prof. Dake, Delali Kwasi
| dkdake@uew.edu.gh |
Dake, D. K., Bada, G. K., & Dadzie, A. E. (2023). Internet of Things (IoT) Applications in Education: Benefits and Implementation Challenges in Ghanaian Tertiary Institutions. Journal of Information Technology Education: Research, 22, 311 - 338. DOI: https://doi.org/10.28945/5183
Dake, D. K., Nwiah, E., Klogo, G. S., & Ativi, W. X. (2023). Instructor ‑ assisted question classification system using machine learning algorithms with N ‑ gram and weighting schemes. Discover Artificial Intelligence, 3, 29. DOI: https://doi.org/10.1007/s44163-023-00073-5
Dake, D. K., Gyimah, E., & Buabeng-Andoh, C. (2023). University Students Behaviour Modelling Using the K-Prototype Clustering Algorithm. Mathematical Problems in Engineering, 2023, 12. DOI: https://doi.org/10.1155/2023/5507814
Dake, D. K., & Bada, G. K. (2023). Unveiling learner emotions: Sentiment analysis of Moodle-based online assessments using machine learning. Journal of Information Technology Education: Innovations in Practice, 22, 109-132. DOI: https://doi.org/10.28945/5174
Dake, D. K. (2023). Artificial Intelligence Self-Organising (AI-SON) Frameworks for 5G-Enabled Networks: A Review. Journal of Computer and Communications, 11(4), 33–62. DOI: https://doi.org/10.4236/jcc.2023.114003
Dake, D. K. (2023). Online Recruitment Fraud Detection: A Machine Learning-based Model for Ghanaian Job Websites. International Journal of Computer Applications, 184(51), 20–28. DOI: https://doi.org/10.5120/ijca2023922639
Dake, D. K., Kudjo Bada, G., & Techie-Menson, H. (2023). Using Machine Learning to Cluster and Predict the Learning Pattern of University Students. In In 2023 Annual Conference on Education and E-learning (ACEE).
Dake, D. K., & Gyimah, E. (2022). Using sentiment analysis to evaluate qualitative students’ responses. Education and Information Technologies, 28, 4629–4647. DOI: https://doi.org/10.1007/s10639-022-11349-1
Dake, D. K., & Buabeng-Andoh, C. (2022). Using Machine Learning Techniques to Predict Learner Drop-out Rate in Higher Educational Institutions. Mobile Information Systems, 2022, 9. DOI: https://doi.org/10.1155/2022/2670562
Dake, D. K., Gadze, J. D., & Klogo, G. S. (2021). DDoS and Flash Event Detection in Higher Bandwidth SDN-IoT using Multiagent Reinforcement Learning. In International Conference on Computing, Computational Modelling and Applications (ICCMA). DOI: https://doi.org/10.1109/ICCMA53594.2021.00011
Dake, D. K., Gadze, J. D., Klogo, G. S., & Nunoo-Mensah, H. (2021). Multi-agent reinforcement learning framework in SDN-IoT for transient load detection and prevention. Technologies, 9(3), 44. DOI: https://doi.org/10.3390/technologies9030044
Dake, D. K., Essel, D. D., & Agbodaze, J. E. (2021). Using Machine Learning to Predict Students’ Academic Performance During Covid-19. In International Conference on Computing, Computational Modelling and Applications (ICCMA). DOI: https://doi.org/10.1109/ICCMA53594.2021.00010
Dake, D. K., Gadze, J. D., Klogo, G. S., & Nunoo-Mensah, H. (2021). Traffic Engineering in Software-defined Networks using Reinforcement Learning: a review. International Journal of Advanced Computer Science and Applications (IJACSA), 12(5), 330-345. DOI: http://dx.doi.org/10.14569/IJACSA.2021.012...
Dake, D.K., & Ofosu, B.A. (2019). 5G enabled technologies for smart education. International Journal of Advanced Computer Science and Applications (IJACSA), 10(12), 201-206. DOI: http://dx.doi.org/10.14569/IJACSA.2019.010...